RENEWABLE ENERGY SOURCES
AND
CLIMATE CHANGE MITIGATION
SPECIAL REPORT OF THE
INTERGOVERNMENTAL PANEL
ON CLIMATE CHANGE
SUMMARY FOR POLICYMAKERS AND TECHNICAL SUMMARY
• 10CC«Special
Report on Renewable Energy
Sources and Climate Change Mitigation
Ramón Pichs-Madruga
Co-Chair Working Group III
Centro de Investigaciones
de la Economía Mundial (CIEM)
Ottmar Edenhofer
Co-Chair Working Group III
Potsdam Institute for Climate
ImpactResearch (PIK)
Youba Sokona
Co-Chair Working Group III
African Climate Policy Centre,
United Nations Economic
Commission for Africa (UNECA)
Kristin Seyboth
Patrick Eickemeier
Patrick Matschoss
Gerrit Hansen
Susanne Kadner
Steffen Schlömer
Timm Zwickel
Christoph von Stechow
Technical Support Unit Working Group III
Potsdam Institute for Climate Impact Research (PIK)
Published for the Intergovernmental Panel on Climate Change
Edited by
Summary for Policymakers
A Report of Working Group III of the IPCC
and
Technical Summary
A Report accepted by Working Group III of the IPCC
but not approved in detail
Reprinted with corrections in 2012
© 2011, Intergovernmental Panel on Climate Change
ISBN 978-92-9169-131-9
Cover illustration: Parabolic mirrors at a solar thermal plant are used to heat oil.
©Michael Melford/National Geographic Stock
iii
Section I
Section II
Annexes
Contents
Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Summary for Policymakers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Technical Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Annex I Glossary, Acronyms, Chemical Symbols and Prefixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Annex II Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .181
Annex III Recent Renewable Energy Cost and Performance Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
v
Foreword and Preface I
vii
Foreword
Foreword
The IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) provides a
comprehensive review concerning these sources and technologies, the relevant costs and benefits, and their potential
role in a portfolio of mitigation options.
For the first time, an inclusive account of costs and greenhouse gas emissions across various technologies and scenarios
confirms the key role of renewable sources, irrespective of any tangible climate change mitigation agreement.
As an intergovernmental body established in 1988 by the World Meteorological Organization (WMO) and the United
Nations Environment Programme (UNEP), the IPCC has successfully provided policymakers over the ensuing period with
the most authoritative and objective scientific and technical assessments, which, while clearly policy relevant, never
claimed to be policy prescriptive. Moreover, this Special Report should be considered especially significant at a time
when Governments are pondering the role of renewable energy resources in the context of their respective climate
change mitigation efforts.
The SRREN was made possible thanks to the commitment and dedication of hundreds of experts from various regions
and disciplines. We would like to express our deep gratitude to Prof. Ottmar Edenhofer, Dr. Ramon Pichs-Madruga,
and Dr. Youba Sokona, for their untiring leadership throughout the SRREN development process, as well as to all
Coordinating Lead Authors, Lead Authors, Contributing Authors, Review Editors and Reviewers, and to the staff of the
Working Group III Technical Support Unit.
We greatly value Germany’s generous support and dedication to the SRREN, as evidenced in particular by its hosting
of the Working Group III Technical Support Unit. Moreover, we wish to express our appreciation to the United Arab
Emirates, for hosting the plenary session which approved the report; as well as to Brazil, Norway, the United Kingdom
and Mexico, which hosted the successive Lead Authors meetings; to all sponsors which contributed to the IPCC work
through their financial and logistical support; and finally to the IPCC Chairman, Dr. R. K. Pachauri, for his leadership
throughout the SRREN development process.
M. Jarraud
Secretary General
World Meteorological Organization
A. Steiner
Executive Director
United Nations Environment Programme
ix
Preface
Preface
The Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) of the IPCC Working Group
III provides an assessment and thorough analysis of renewable energy technologies and their current and potential
role in the mitigation of greenhouse gas emissions. The results presented here are based on an extensive assessment of
scientific literature, including specifics of individual studies, but also an aggregate across studies analyzed for broader
conclusions. The report combines information on technology specific studies with results of large-scale integrated
models, and provides policy-relevant (but not policy-prescriptive) information to decision makers on the characteristics
and technical potentials of different resources; the historical development of the technologies; the challenges of their
integration and social and environmental impacts of their use; as well as a comparison in levelized cost of energy for
commercially available renewable technologies with recent non-renewable energy costs. Further, the role of renewable
energy sources in pursuing GHG concentration stabilization levels discussed in this report and the presentation and
analysis of the policies available to assist the development and deployment of renewable energy technologies in climate
change mitigation and/or other goals answer important questions detailed in the original scoping of the report.
The process
This report has been prepared in accordance with the rules and procedures established by the IPCC and used for previous
assessment reports. After a scoping meeting in Lübeck, Germany from the 20th to the 25th of January, 2008, the
outline of the report was approved at the 28th IPCC Plenary held in Budapest, Hungary on the 9th and 10th of April, 2008.
Soon afterward, an author team of 122 Lead Authors (33 from developing countries, 4 from EIT countries, and 85 from
industrialized countries), 25 Review Editors and 132 contributing authors was formed.
The IPCC review procedure was followed, in which drafts produced by the authors were subject to two reviews. 24,766
comments from more than 350 expert reviewers and governments and international organizations were processed.
Review Editors for each chapter have ensured that all substantive government and expert review comments received
appropriate consideration.
The Summary for Policy Makers was approved line-by-line and the Final Draft of the report was accepted at the 11th
Session of the Third Working Group held in Abu Dhabi, United Arab Emirates from the 5th to the 8th of May, 2011. The
Special Report was accepted in its entirety at the 33rd IPCC Plenary Session held also in Abu Dhabi from the 10th to the
13th of May, 2011.
Structure of the Special Report
The SRREN consists of three categories of chapters: one introductory chapter; six technology specific chapters (Chapters
2-7); and four chapters that cover integrative issues across technologies (Chapters 8-11).
Chapter 1 is the introductory chapter designed to place renewable energy technologies within the broader framework
of climate change mitigation options and identify characteristics common to renewable energy technologies.
Each of the technology chapters (2-7) provides information on the available resource potential, the state of technological
and market development and the environmental and social impacts for each renewable energy source including
bioenergy, direct solar energy, geothermal energy, hydropower, ocean energy and wind energy. In addition, prospects
for future technological innovation and cost reductions are discussed, and the chapters end with a discussion on possible
future deployment.
x
Preface
Chapter 8 is the first of the integrative chapters and discusses how renewable energy technologies are currently integrated
into energy distribution systems, and how they may be integrated in the future. Development pathways for the
strategic use of renewable technologies in the transport, buildings, industry and agricultural sectors are also discussed.
Renewable energy in the context of sustainable development is covered in Chapter 9. This includes the social, environmental
and economic impacts of renewable energy sources, including the potential for improved energy access and a
secure supply of energy. Specific barriers for renewable energy technologies are also covered.
In a review of over 160 scenarios, Chapter 10 investigates how renewable energy technologies may contribute to
varying greenhouse gas emission reduction scenarios, ranging from business-as-usual scenarios to those reflecting
ambitious GHG concentration stabilization levels. Four scenarios are analyzed in depth and the costs of extensive
deployment of renewable energy technologies are also discussed.
The last chapter of the report, Chapter 11, describes the current trends in renewable energy support policies, as well as
trends in financing and investment in renewable energy technologies. It reviews current experiences with RE policies,
including effectiveness and efficiency measures, and discusses the influence of an enabling environment on the success
of policies.
While the authors of the report included the most recent literature available at the time of publication, readers should
be aware that topics covered in this Special Report may be subject to further rapid development. This includes state of
development of some renewable energy technologies, as well as the state of knowledge of integration challenges, mitigation
costs, co-benefits, environmental and social impacts, policy approaches and financing options. The boundaries
and names shown and the designations used on any geographic maps in this report do not imply official endorsement
or acceptance by the United Nations. In the geographic maps developed for the SRREN, the dotted line in Jammu and
Kashmir represents approximately the Line of Control agreed upon by India and Pakistan. The final status of Jammu and
Kashmir has not yet been agreed upon by the parties.
Acknowledgements
Production of this Special Report was a major enterprise, in which many people from around the world were involved,
with a wide variety of contributions. We wish to thank the generous contributions by the governments and institutions
involved, which enabled the authors, Review Editors and Government and Expert Reviewers to participate in this
process.
We are especially grateful for the contribution and support of the German Government, in particular the
Bundesministerium für Bildung und Forschung (BMBF), in funding the Working Group III Technical Support Unit (TSU).
Coordinating this funding, Gregor Laumann and Christiane Textor of the Deutsches Zentrum für Luft- und Raumfahrt
(DLR) were always ready to dedicate time and energy to the needs of the team. We would also like to express our
gratitude to the Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (BMU). In addition, the Potsdam
Institute for Climate Impact Research (PIK) kindly hosted and housed the TSU offices.
We would very much like to thank the governments of Brazil, Norway, the United Kingdom and Mexico, who, in collaboration
with local institutions, hosted the crucial lead author meetings in São José dos Campos (January 2009), Oslo
(September 2009), Oxford (March 2010) and Mexico City (September 2010). In addition, we would like to thank the
government of the United States and the Institute for Sustainability, with the Founder Society Technologies for Carbon
Management Project for hosting the SRREN Expert Review meeting in Washington D.C.(February 2010). Finally, we
xi
Preface
express our appreciation to PIK for welcoming the SRREN Coordinating Lead Authors on their campus for a concluding
meeting (January 2011).
This Special Report is only possible thanks to the expertise, hard work and commitment to excellence shown throughout
by our Coordinating Lead Authors and Lead Authors, with important assistance by many Contributing Authors. We
would also like to express our appreciation to the Government and Expert Reviewers, acknowledging the time and
energy invested to provide constructive and useful comments to the various drafts. Our Review Editors were also critical
in the SRREN process, supporting the author team with processing the comments and assuring an objective discussion
of relevant issues.
It is a pleasure to acknowledge the tireless work of the staff of the Working Group III Technical Support Unit, Patrick
Matschoss, Susanne Kadner, Kristin Seyboth, Timm Zwickel, Patrick Eickemeier, Gerrit Hansen, Steffen Schloemer,
Christoph von Stechow, Benjamin Kriemann, Annegret Kuhnigk, Anna Adler and Nina Schuetz, who were assisted by
Marilyn Anderson, Lelani Arris, Andrew Ayres, Marlen Goerner, Daniel Mahringer and Ashley Renders. Brigitte Knopf,
in her role as Senior Advisor to the TSU, consistently provided valuable input and direction. Graphics support by Kay
Schröder and his team at Daily-Interactive.com Digitale Kommunikation is gratefully appreciated, as is the layout work
by Valarie Morris and her team at Arroyo Writing, LLC.
The Working Group III Bureau – consisting of Antonina Ivanova Boncheva (Mexico), Carlo Carraro (Italy), Suzana Kahn
Ribeiro (Brazil), Jim Skea (UK), Francis Yamba (Zambia), and Taha Zatari (Saudi Arabia) and prior to his elevation to
IPCC Vice Chair, Ismail A.R. Elgizouli (Sudan) – provided continuous and constructive support to the Working Group III
Co-Chairs throughout the SRREN process.
We would like to thank the Renate Christ, Secretary of the IPCC, and the Secretariat staff Gaetano Leone, Mary Jean
Burer, Sophie Schlingemann, Judith Ewa, Jesbin Baidya, Joelle Fernandez, Annie Courtin, Laura Biagioni, Amy Smith
Aasdam, and Rockaya Aidara, who provided logistical support for government liaison and travel of experts from developing
and transitional economy countries.
Our special acknowledgement to Dr. Rajendra Pachauri, Chairman of the IPCC, for his contribution and support during
the preparation of this IPCC Special Report.
Ottmar Edenhofer Ramon Pichs-Madruga Youba Sokona
IPCC WG III Co-Chair IPCC WG III Co-Chair IPCC WG III Co-Chair
Patrick Matshoss Kristin Seyboth
IPCC WG III TSU Head IPCC WG III Senior Scientist
SRREN Manager
xii
Preface
This report is dedicated to
Wolfram Krewitt, Germany
Coordinating Lead Author in Chapter 8
Wolfram Krewitt passed away October 8th, 2009. He worked at the Deutsches Zentrum für Luft- und Raumfahrt (DLR) in
Stuttgart, Germany.
Raymond Wright, Jamaica
Lead Author in Chapter 10
Raymond Wright passed away July 7th, 2011. He worked at the Petroleum Corporation of Jamaica (PCJ) in Kingston,
Jamaica.
Wolfram Krewitt made a significant contribution to this Special Report and his vision for Chapter 8 (Integration
of Renewable Energy into Present and Future Energy Systems) remains embedded in the text for which he is
acknowledged. Raymond Wright was a critical member of the Chapter 10 (Mitigation Potential and Costs) author
team who consistently offered precise insights to the Special Report, ensuring balance and credibility. Both authors
were talented, apt and dedicated members of the IPCC author team - their passing represents a deep loss for the
international scientific communities working in climate and energy issues. Wolfram Krewitt and Raymond Wright are
dearly remembered by their fellow authors.
1
Summaries II
SPM
SPM Summary
for Policymakers
Coordinating Lead Authors:
Ottmar Edenhofer (Germany), Ramon Pichs-Madruga (Cuba),
Youba Sokona (Ethiopia/Mali), Kristin Seyboth (Germany/USA)
Lead Authors:
Dan Arvizu (USA), Thomas Bruckner (Germany), John Christensen (Denmark),
Helena Chum (USA/Brazil) Jean-Michel Devernay (France), Andre Faaij (The Netherlands),
Manfred Fischedick (Germany), Barry Goldstein (Australia), Gerrit Hansen (Germany),
John Huckerby (New Zealand), Arnulf Jäger-Waldau (Italy/Germany), Susanne Kadner (Germany),
Daniel Kammen (USA), Volker Krey (Austria/Germany), Arun Kumar (India),
Anthony Lewis (Ireland), Oswaldo Lucon (Brazil), Patrick Matschoss (Germany),
Lourdes Maurice (USA), Catherine Mitchell (United Kingdom), William Moomaw (USA),
José Moreira (Brazil), Alain Nadai (France), Lars J. Nilsson (Sweden), John Nyboer (Canada),
Atiq Rahman (Bangladesh), Jayant Sathaye (USA), Janet Sawin (USA), Roberto Schaeffer (Brazil),
Tormod Schei (Norway), Steffen Schlömer (Germany), Ralph Sims (New Zealand),
Christoph von Stechow (Germany), Aviel Verbruggen (Belgium), Kevin Urama (Kenya/Nigeria),
Ryan Wiser (USA), Francis Yamba (Zambia), Timm Zwickel (Germany)
Special Advisor:
Jeffrey Logan (USA)
This chapter should be cited as:
IPCC, 2011: Summary for Policymakers. In: IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation
[O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen,
S. Schlömer, C. von Stechow (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
3
4
Summary for Policymakers Summaries
Summaries Summary for Policymakers
5
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2. Renewable energy and climate change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3. Renewable energy technologies and markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
4. Integration into present and future energy systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
5. Renewable energy and sustainable development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
6. Mitigation potentials and costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
7. Policy, implementation and financing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
8. Advancing knowledge about renewable energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
6
1. Introduction
The Working Group III Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) presents
an assessment of the literature on the scientifi c, technological, environmental, economic and social aspects of the
contribution of six renewable energy (RE) sources to the mitigation of climate change. It is intended to provide policy
relevant information to governments, intergovernmental processes and other interested parties. This Summary for
Policymakers provides an overview of the SRREN, summarizing the essential fi ndings.
The SRREN consists of 11 chapters. Chapter 1 sets the context for RE and climate change; Chapters 2 through 7 provide
information on six RE technologies, and Chapters 8 through 11 address integrative issues (see Figure SPM.1).
2. Bioenergy
3. Direct Solar Energy
4. Geothermal Energy
5. Hydropower
6. Ocean Energy
7. Wind Energy
1. Renewable Energy and Climate Change
8. Integration of Renewable Energy into Present and Future Energy Systems
9. Renewable Energy in the Context of Sustainable Development
10. Mitigation Potential and Costs
11. Policy, Financing and Implementation
Integrative Chapters
Introductory Chapter
Technology Chapters
Special Report on Renewable Energy Sources and Climate Change Mitigation
Figure SPM.1 | Structure of the SRREN. [Figure 1.1, 1.1.2]
References to chapters and sections are indicated with corresponding chapter and section numbers in square brackets. An
explanation of terms, acronyms and chemical symbols used in this SPM can be found in the glossary of the SRREN (Annex I).
Conventions and methodologies for determining costs, primary energy and other topics of analysis can be found in Annex II
and Annex III. This report communicates uncertainty where relevant.1
1 This report communicates uncertainty, for example, by showing the results of sensitivity analyses and by quantitatively presenting ranges in cost
numbers as well as ranges in the scenario results. This report does not apply formal IPCC uncertainty terminology because at the time of the
approval of this report, IPCC uncertainty guidance was in the process of being revised.
Summary for Policymakers Summaries
7
Summaries Summary for Policymakers
2. Renewable energy and climate change
Demand for energy and associated services, to meet social and economic development and improve human
welfare and health, is increasing. All societies require energy services to meet basic human needs (e.g., lighting,
cooking, space comfort, mobility and communication) and to serve productive processes. [1.1.1, 9.3.2] Since approximately
1850, global use of fossil fuels (coal, oil and gas) has increased to dominate energy supply, leading to a rapid
growth in carbon dioxide (CO2) emissions. [Figure 1.6]
Greenhouse gas (GHG) emissions resulting from the provision of energy services have contributed signifi -
cantly to the historic increase in atmospheric GHG concentrations. The IPCC Fourth Assessment Report (AR4)
concluded that “Most of the observed increase in global average temperature since the mid-20th century is very likely2
due to the observed increase in anthropogenic greenhouse gas concentrations.”
Recent data confi rm that consumption of fossil fuels accounts for the majority of global anthropogenic GHG
emissions.3 Emissions continue to grow and CO2 concentrations had increased to over 390 ppm, or 39% above preindustrial
levels, by the end of 2010. [1.1.1, 1.1.3]
There are multiple options for lowering GHG emissions from the energy system while still satisfying the
global demand for energy services. [1.1.3, 10.1] Some of these possible options, such as energy conservation and
effi ciency, fossil fuel switching, RE, nuclear and carbon capture and storage (CCS) were assessed in the AR4. A comprehensive
evaluation of any portfolio of mitigation options would involve an evaluation of their respective mitigation
potential as well as their contribution to sustainable development and all associated risks and costs. [1.1.6] This report
will concentrate on the role that the deployment of RE technologies can play within such a portfolio of mitigation
options.
As well as having a large potential to mitigate climate change, RE can provide wider benefi ts. RE may, if
implemented properly, contribute to social and economic development, energy access, a secure energy supply, and
reducing negative impacts on the environment and health. [9.2, 9.3]
Under most conditions, increasing the share of RE in the energy mix will require policies to stimulate
changes in the energy system. Deployment of RE technologies has increased rapidly in recent years, and their share
is projected to increase substantially under most ambitious mitigation scenarios [1.1.5, 10.2]. Additional policies would
be required to attract the necessary increases in investment in technologies and infrastructure. [11.4.3, 11.5, 11.6.1,
11.7.5]
3. Renewable energy technologies and markets
RE comprises a heterogeneous class of technologies (Box SPM.1). Various types of RE can supply electricity, thermal
energy and mechanical energy, as well as produce fuels that are able to satisfy multiple energy service needs [1.2].
Some RE technologies can be deployed at the point of use (decentralized) in rural and urban environments, whereas
others are primarily deployed within large (centralized) energy networks [1.2, 8.2, 8.3, 9.3.2]. Though a growing
number of RE technologies are technically mature and are being deployed at signifi cant scale, others are in an earlier
phase of technical maturity and commercial deployment or fi ll specialized niche markets [1.2]. The energy output of
2 According to the formal uncertainty language used in the AR4, the term ‘very likely’ refers to a >90% assessed probability of occurrence.
3 The contributions of individual anthropogenic GHGs to total emissions in 2004, reported in AR4, expressed as CO2eq were: CO2 from fossil
fuels (56.6%), CO2 from deforestation, decay of biomass etc. (17.3%), CO2 from other (2.8%), methane (14.3%), nitrous oxide (7.9%) and
fl uorinated gases (1.1%) [Figure 1.1b, AR4, WG III, Chapter 1. For further information on sectoral emissions, including forestry, see also Figure
1.3b and associated footnotes.]
8
Summary for Policymakers Summaries
RE technologies can be (i) variable and—to some degree—unpredictable over differing time scales (from minutes to
years), (ii) variable but predictable, (iii) constant, or (iv) controllable. [8.2, 8.3]
Box SPM.1 | Renewable energy sources and technologies considered in this report.
Bioenergy can be produced from a variety of biomass feedstocks, including forest, agricultural and livestock residues; short-rotation
forest plantations; energy crops; the organic component of municipal solid waste; and other organic waste streams. Through a variety
of processes, these feedstocks can be directly used to produce electricity or heat, or can be used to create gaseous, liquid, or solid fuels.
The range of bioenergy technologies is broad and the technical maturity varies substantially. Some examples of commercially available
technologies include small- and large-scale boilers, domestic pellet-based heating systems, and ethanol production from sugar and starch.
Advanced biomass integrated gasifi cation combined-cycle power plants and lignocellulose-based transport fuels are examples of technologies
that are at a pre-commercial stage, while liquid biofuel production from algae and some other biological conversion approaches are
at the research and development (R&D) phase. Bioenergy technologies have applications in centralized and decentralized settings, with
the traditional use of biomass in developing countries being the most widespread current application.4 Bioenergy typically offers constant
or controllable output. Bioenergy projects usually depend on local and regional fuel supply availability, but recent developments show
that solid biomass and liquid biofuels are increasingly traded internationally. [1.2, 2.1, 2.3, 2.6, 8.2, 8.3]
Direct solar energy technologies harness the energy of solar irradiance to produce electricity using photovoltaics (PV) and concentrating
solar power (CSP), to produce thermal energy (heating or cooling, either through passive or active means), to meet direct lighting
needs and, potentially, to produce fuels that might be used for transport and other purposes. The technology maturity of solar applications
ranges from R&D (e.g., fuels produced from solar energy), to relatively mature (e.g., CSP), to mature (e.g., passive and active solar
heating, and wafer-based silicon PV). Many but not all of the technologies are modular in nature, allowing their use in both centralized
and decentralized energy systems. Solar energy is variable and, to some degree, unpredictable, though the temporal profi le of solar
energy output in some circumstances correlates relatively well with energy demands. Thermal energy storage offers the option to improve
output control for some technologies such as CSP and direct solar heating. [1.2, 3.1, 3.3, 3.5, 3.7, 8.2, 8.3]
Geothermal energy utilizes the accessible thermal energy from the Earth’s interior. Heat is extracted from geothermal reservoirs using
wells or other means. Reservoirs that are naturally suffi ciently hot and permeable are called hydrothermal reservoirs, whereas reservoirs
that are suffi ciently hot but that are improved with hydraulic stimulation are called enhanced geothermal systems (EGS). Once at the surface,
fl uids of various temperatures can be used to generate electricity or can be used more directly for applications that require thermal
energy, including district heating or the use of lower-temperature heat from shallow wells for geothermal heat pumps used in heating
or cooling applications. Hydrothermal power plants and thermal applications of geothermal energy are mature technologies, whereas
EGS projects are in the demonstration and pilot phase while also undergoing R&D. When used to generate electricity, geothermal power
plants typically offer constant output. [1.2, 4.1, 4.3, 8.2, 8.3]
Hydropower harnesses the energy of water moving from higher to lower elevations, primarily to generate electricity. Hydropower projects
encompass dam projects with reservoirs, run-of-river and in-stream projects and cover a continuum in project scale. This variety gives
hydropower the ability to meet large centralized urban needs as well as decentralized rural needs. Hydropower technologies are mature.
Hydropower projects exploit a resource that varies temporally. However, the controllable output provided by hydropower facilities that
have reservoirs can be used to meet peak electricity demands and help to balance electricity systems that have large amounts of variable
RE generation. The operation of hydropower reservoirs often refl ects their multiple uses, for example, drinking water, irrigation, fl ood and
drought control, and navigation, as well as energy supply. [1.2, 5.1, 5.3, 5.5, 5.10, 8.2]
4 Traditional biomass is defi ned by the International Energy Agency (IEA) as biomass consumption in the residential sector in developing countries and refers to the
often unsustainable use of wood, charcoal, agricultural residues, and animal dung for cooking and heating. All other biomass use is defi ned as modern [Annex I].
9
Summaries Summary for Policymakers
Ocean energy derives from the potential, kinetic, thermal and chemical energy of seawater, which can be transformed to provide electricity,
thermal energy, or potable water. A wide range of technologies are possible, such as barrages for tidal range, submarine turbines
for tidal and ocean currents, heat exchangers for ocean thermal energy conversion, and a variety of devices to harness the energy of
waves and salinity gradients. Ocean technologies, with the exception of tidal barrages, are at the demonstration and pilot project phases
and many require additional R&D. Some of the technologies have variable energy output profi les with differing levels of predictability
(e.g., wave, tidal range and current), while others may be capable of near-constant or even controllable operation (e.g., ocean thermal
and salinity gradient). [1.2, 6.1, 6.2, 6.3, 6.4, 6.6, 8.2]
Wind energy harnesses the kinetic energy of moving air. The primary application of relevance to climate change mitigation is to produce
electricity from large wind turbines located on land (onshore) or in sea- or freshwater (offshore). Onshore wind energy technologies are
already being manufactured and deployed on a large scale. Offshore wind energy technologies have greater potential for continued technical
advancement. Wind electricity is both variable and, to some degree, unpredictable, but experience and detailed studies from many
regions have shown that the integration of wind energy generally poses no insurmountable technical barriers. [1.2, 7.1, 7.3, 7.5, 7.7, 8.2]
On a global basis, it is estimated that RE accounted for 12.9% of the total 492 Exajoules (EJ)5 of primary
energy supply in 2008 (Box SPM.2 and Figure SPM.2). The largest RE contributor was biomass (10.2%), with the
majority (roughly 60%) being traditional biomass used in cooking and heating applications in developing countries
but with rapidly increasing use of modern biomass as well.6 Hydropower represented 2.3%, whereas other RE sources
accounted for 0.4%. [1.1.5] In 2008, RE contributed approximately 19% of global electricity supply (16% hydropower,
3% other RE) and biofuels contributed 2% of global road transport fuel supply. Traditional biomass (17%), modern
biomass (8%), solar thermal and geothermal energy (2%) together fuelled 27% of the total global demand for heat. The
contribution of RE to primary energy supply varies substantially by country and region. [1.1.5, 1.3.1, 8.1]
Deployment of RE has been increasing rapidly in recent years (Figure SPM.3). Various types of government policies,
the declining cost of many RE technologies, changes in the prices of fossil fuels, an increase of energy demand and
other factors have encouraged the continuing increase in the use of RE. [1.1.5, 9.3, 10.5, 11.2, 11.3] Despite global
fi nancial challenges, RE capacity continued to grow rapidly in 2009 compared to the cumulative installed capacity from
the previous year, including wind power (32% increase, 38 Gigawatts (GW) added), hydropower (3%, 31 GW added),
grid-connected photovoltaics (53%, 7.5 GW added), geothermal power (4%, 0.4 GW added), and solar hot water/heating
(21%, 31 GWth added). Biofuels accounted for 2% of global road transport fuel demand in 2008 and nearly 3% in
2009. The annual production of ethanol increased to 1.6 EJ (76 billion litres) by the end of 2009 and biodiesel to 0.6 EJ
(17 billion litres). [1.1.5, 2.4, 3.4, 4.4, 5.4, 7.4]
Of the approximate 300 GW of new electricity generating capacity added globally over the two-year period from 2008
to 2009, 140 GW came from RE additions. Collectively, developing countries host 53% of global RE electricity generation
capacity [1.1.5]. At the end of 2009, the use of RE in hot water/heating markets included modern biomass (270
GWth), solar (180 GWth), and geothermal (60 GWth). The use of decentralized RE (excluding traditional biomass) in
meeting rural energy needs at the household or village level has also increased, including hydropower stations, various
modern biomass options, PV, wind or hybrid systems that combine multiple technologies. [1.1.5, 2.4, 3.4, 4.4, 5.4]
5 1 Exajoule = 1018 joules = 23.88 million tonnes of oil equivalent (Mtoe).
6 In addition to this 60% share of traditional biomass, there is biomass use estimated to amount to 20 to 40% not reported in offi cial primary
energy databases, such as dung, unaccounted production of charcoal, illegal logging, fuelwood gathering, and agricultural residue use. [2.1, 2.5]
10
Summary for Policymakers Summaries
The global technical potential7 of RE sources will not limit continued growth in the use of RE. A wide range
of estimates is provided in the literature, but studies have consistently found that the total global technical potential
for RE is substantially higher than global energy demand (Figure SPM.4) [1.2.2, 10.3, Annex II]. The technical potential
for solar energy is the highest among the RE sources, but substantial technical potential exists for all six RE sources.
Even in regions with relatively low levels of technical potential for any individual RE source, there are typically signifi
cant opportunities for increased deployment compared to current levels. [1.2.2, 2.2, 2.8, 3.2, 4.2, 5.2, 6.2, 6.4, 7.2,
8.2, 8.3, 10.3] In the longer term and at higher deployment levels, however, technical potentials indicate a limit to the
7 Defi nitions of technical potential often vary by study. ‘Technical potential’ is used in the SRREN as the amount of RE output obtainable by
full implementation of demonstrated technologies or practices. No explicit reference to costs, barriers or policies is made. Technical potentials
reported in the literature and assessed in the SRREN, however, may have taken into account practical constraints and when explicitly stated
they are generally indicated in the underlying report. [Annex I]
Figure SPM.2 | Shares of energy sources in total global primary energy supply in 2008 (492 EJ). Modern biomass contributes 38% of the total biomass share. [Figure 1.10, 1.1.5]
Note: Underlying data for fi gure have been converted to the ‘direct equivalent’ method of accounting for primary energy supply. [Box SPM.2, 1.1.9, Annex II.4]
Wind Energy 0.2%
Geothermal Energy 0.1%
Ocean Energy 0.002%
Direct Solar Energy 0.1%
Gas
22.1%
Coal
28.4%
RE
12.9%
Oil
34.6%
Nuclear
Energy 2.0%
Hydropower 2.3%
Bioenergy
10.2%
Box SPM.2 | Accounting for primary energy in the SRREN.
There is no single, unambiguous accounting method for calculating primary energy from non-combustible energy sources such as noncombustible
RE sources and nuclear energy. The SRREN adopts the ‘direct equivalent’ method for accounting for primary energy supply.
In this method, fossil fuels and bioenergy are accounted for based on their heating value while non-combustible energy sources, including
nuclear energy and all non-combustible RE, are accounted for based on the secondary energy that they produce. This may lead to an
understatement of the contribution of non-combustible RE and nuclear compared to bioenergy and fossil fuels by a factor of roughly 1.2
up to 3. The selection of the accounting method also impacts the relative shares of different individual energy sources. Comparisons in
the data and fi gures presented in the SRREN between fossil fuels and bioenergy on the one hand, and non-combustible RE and nuclear
energy on the other, refl ect this accounting method. [1.1.9, Annex II.4]
11
Summaries Summary for Policymakers
Biofuels (incl. Biogas)
Wind Energy
Geothermal Energy
Solar Thermal Energy
Municipal Solid Waste
(Renewable Share)
Primary Solid Biomass
for Heat and Electricity
Applications
Hydropower
Global Primary Energy Supply [EJ/yr]
0
10
20
30
40
50
60
0
1
2
3
4
5
Solar PV Energy
Ocean Energy
0.00
0.01
0.02
0.03
0.04
0.05
1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Figure SPM.3 | Historical development of global primary energy supply from renewable energy from 1971 to 2008. [Figure 1.12, 1.1.5]
Notes: Technologies are referenced to separate vertical units for display purposes only. Underlying data for fi gure has been converted to the ‘direct equivalent’ method of accounting
for primary energy supply [Box SPM.2, 1.1.9, Annex II.4], except that the energy content of biofuels is reported in secondary energy terms (the primary biomass used to produce the
biofuel would be higher due to conversion losses. [2.3, 2.4])
contribution of some individual RE technologies. Factors such as sustainability concerns [9.3], public acceptance [9.5],
system integration and infrastructure constraints [8.2], or economic factors [10.3] may also limit deployment of RE
technologies.
■
■
□
■
■
■
■
12
Summary for Policymakers Summaries
Climate change will have impacts on the size and geographic distribution of the technical potential for RE
sources, but research into the magnitude of these possible effects is nascent. Because RE sources are, in many
cases, dependent on the climate, global climate change will affect the RE resource base, though the precise nature and
magnitude of these impacts is uncertain. The future technical potential for bioenergy could be infl uenced by climate
change through impacts on biomass production such as altered soil conditions, precipitation, crop productivity and
other factors. The overall impact of a global mean temperature change of less than 2°C on the technical potential
of bioenergy is expected to be relatively small on a global basis. However, considerable regional differences could
be expected and uncertainties are larger and more diffi cult to assess compared to other RE options due to the large
number of feedback mechanisms involved. [2.2, 2.6] For solar energy, though climate change is expected to infl uence
the distribution and variability of cloud cover, the impact of these changes on overall technical potential is expected
to be small [3.2]. For hydropower the overall impacts on the global technical potential is expected to be slightly positive.
However, results also indicate the possibility of substantial variations across regions and even within countries.
[5.2] Research to date suggests that climate change is not expected to greatly impact the global technical potential for
wind energy development but changes in the regional distribution of the wind energy resource may be expected [7.2].
Climate change is not anticipated to have signifi cant impacts on the size or geographic distribution of geothermal or
ocean energy resources. [4.2, 6.2]
Figure SPM.4 | Ranges of global technical potentials of RE sources derived from studies presented in Chapters 2 through 7. Biomass and solar are shown as primary energy due to
their multiple uses; note that the fi gure is presented in logarithmic scale due to the wide range of assessed data. [Figure 1.17, 1.2.3]
Notes: Technical potentials reported here represent total worldwide potentials for annual RE supply and do not deduct any potential that is already being utilized. Note that RE electricity
sources could also be used for heating applications, whereas biomass and solar resources are reported only in primary energy terms but could be used to meet various energy
service needs. Ranges are based on various methods and apply to different future years; consequently, the resulting ranges are not strictly comparable across technologies. For the
data behind Figure SPM.4 and additional notes that apply, see Chapter 1 Annex, Table A.1.1 (as well as the underlying chapters).
Global Electricity
Demand, 2008: 61 EJ
Global Primary Energy
Supply, 2008: 492 EJ
Global Heat
Demand, 2008: 164 EJ
0
10
100
1,000
10,000
100,000
Global Technical Potential [EJ/yr, log scale]
Direct Solar
Energy
Geothermal Biomass
Energy
Wind
Energy
Ocean
Energy
Electricity Heat Primary Energy
Geothermal Hydropower
Energy
49837
1575
500
50
312
10
580
85
331
7
52
50
1109
118
Max (in EJ/yr)
Min (in EJ/yr)
Range of Estimates of Global Technical Potentials
Range of Estimates
Summarized in Chapters 2-7
Maximum
Minimum
13
Summaries Summary for Policymakers
The levelized cost of energy8 for many RE technologies is currently higher than existing energy prices,
though in various settings RE is already economically competitive. Ranges of recent levelized costs of energy for
selected commercially available RE technologies are wide, depending on a number of factors including, but not limited
to, technology characteristics, regional variations in cost and performance, and differing discount rates (Figure SPM.5).
[1.3.2, 2.3, 2.7, 3.8, 4.8, 5.8, 6.7, 7.8, 10.5, Annex III] Some RE technologies are broadly competitive with existing
market energy prices. Many of the other RE technologies can provide competitive energy services in certain circumstances,
for example, in regions with favourable resource conditions or that lack the infrastructure for other low-cost
energy supplies. In most regions of the world, policy measures are still required to ensure rapid deployment of many RE
sources. [2.3, 2.7, 3.8, 4.7, 5.8, 6.7, 7.8, 10.5]
Monetizing the external costs of energy supply would improve the relative competitiveness of RE. The same applies if
market prices increase due to other reasons (Figure SPM.5). [10.6] The levelized cost of energy for a technology is not
the sole determinant of its value or economic competitiveness. The attractiveness of a specifi c energy supply option
depends also on broader economic as well as environmental and social aspects, and the contribution that the technology
provides to meeting specifi c energy services (e.g., peak electricity demands) or imposes in the form of ancillary
costs on the energy system (e.g., the costs of integration). [8.2, 9.3, 10.6]
The cost of most RE technologies has declined and additional expected technical advances would result
in further cost reductions. Signifi cant advances in RE technologies and associated long-term cost reductions have
been demonstrated over the last decades, though periods of rising prices have sometimes been experienced (due
to, for example, increasing demand for RE in excess of available supply) (Figure SPM.6). The contribution of different
drivers (e.g., R&D, economies of scale, deployment-oriented learning, and increased market competition among
RE suppliers) is not always understood in detail. [2.7, 3.8, 7.8, 10.5] Further cost reductions are expected, resulting in
greater potential deployment and consequent climate change mitigation. Examples of important areas of potential
technological advancement include: new and improved feedstock production and supply systems, biofuels produced
via new processes (also called next-generation or advanced biofuels, e.g., lignocellulosic) and advanced biorefi ning
[2.6]; advanced PV and CSP technologies and manufacturing processes [3.7]; enhanced geothermal systems (EGS) [4.6];
multiple emerging ocean technologies [6.6]; and foundation and turbine designs for offshore wind energy [7.7]. Further
cost reductions for hydropower are expected to be less signifi cant than some of the other RE technologies, but R&D
opportunities exist to make hydropower projects technically feasible in a wider range of locations and to improve the
technical performance of new and existing projects. [5.3, 5.7, 5.8]
A variety of technology-specifi c challenges (in addition to cost) may need to be addressed to enable RE
to signifi cantly upscale its contribution to reducing GHG emissions. For the increased and sustainable use of
bioenergy, proper design, implementation and monitoring of sustainability frameworks can minimize negative impacts
and maximize benefi ts with regard to social, economic and environmental issues [SPM.5, 2.2, 2.5, 2.8]. For solar energy,
regulatory and institutional barriers can impede deployment, as can integration and transmission issues [3.9]. For geothermal
energy, an important challenge would be to prove that enhanced geothermal systems (EGS) can be deployed
economically, sustainably and widely [4.5, 4.6, 4.7, 4.8]. New hydropower projects can have ecological and social
impacts that are very site specifi c, and increased deployment may require improved sustainability assessment tools, and
regional and multi-party collaborations to address energy and water needs [5.6, 5.9, 5.10]. The deployment of ocean
energy could benefi t from testing centres for demonstration projects, and from dedicated policies and regulations that
encourage early deployment [6.4]. For wind energy, technical and institutional solutions to transmission constraints and
operational integration concerns may be especially important, as might public acceptance issues relating primarily to
landscape impacts. [7.5, 7.6, 7.9]
8 The levelized cost of energy represents the cost of an energy generating system over its lifetime; it is calculated as the per-unit price at which
energy must be generated from a specifi c source over its lifetime to break even. It usually includes all private costs that accrue upstream in the
value chain, but does not include the downstream cost of delivery to the fi nal customer; the cost of integration, or external environmental or
other costs. Subsidies and tax credits are also not included.
14
Summary for Policymakers Summaries
Figure SPM.5 | Range in recent levelized cost of energy for selected commercially available RE technologies in comparison to recent non-renewable energy costs. Technology subcategories
and discount rates were aggregated for this fi gure. For related fi gures with less or no such aggregation, see [1.3.2, 10.5, Annex III].
Range of Oil and Gas
Based Heating Cost
Range of Non-Renewable
Electricity Cost
Range of Gasoline
and Diesel Cost
[UScent2005 /kWh]
0 10 20 30 40 50 60 70 80 90 100
[USD2005 /GJ]
Biofuels
Geothermal Heat
Solar Thermal Heat
Biomass Heat
Wind Electricity
Ocean Electricity
Hydropower
Geothermal Electricity
Solar Electricity
Biomass Electricity
0 25 50 75 100 125 150 175 200 225 250 275
Non-Renewables
Heat
Transport Fuels
Electricity
Lower Bound
Upper Bound
Medium Values
Biofuels:
1. Corn ethanol
2. Soy biodiesel
3. Wheat ethanol
4. Sugarcane ethanol
5. Palm oil biodiesel
Biomass Heat:
1. Municipal solid waste based CHP
2. Anaerobic digestion based CHP
3. Steam turbine CHP
4. Domestic pellet heating system
Solar Thermal Heat:
1. Domestic hot water systems in China
2. Water and space heating
Geothermal Heat:
1. Greenhouses
2. Uncovered aquaculture ponds
3. District heating
4. Geothermal heat pumps
5. Geothermal building heating
Biomass:
1. Cofiring
2. Small scale combined heat and power, CHP
(Gasification internal combustion engine)
3. Direct dedicated stoker & CHP
4. Small scale CHP (steam turbine)
5. Small scale CHP (organic Rankine cycle)
Solar Electricity:
1. Concentrating solar power
2. Utility-scale PV (1-axis and fixed tilt)
3. Commercial rooftop PV
4. Residential rooftop PV
Geothermal Electricity:
1. Condensing flash plant
2. Binary cycle plant
Hydropower:
1. All types
Ocean Electricity:
1. Tidal barrage
Wind Electricity:
1. Onshore
2. Offshore
Electricity Heat Transport Fuels
Notes: Medium values are shown for the following subcategories, sorted in the order as they appear in the respective ranges (from left to right):
The lower range of the levelized cost of energy for each RE technology is based on a combination of the most favourable input-values, whereas the upper range is based on a
combination of the least favourable input values. Reference ranges in the figure background for non-renewable electricity options are indicative of the levelized cost of centralized
non-renewable electricity generation. Reference ranges for heat are indicative of recent costs for oil and gas based heat supply options. Reference ranges for transport fuels are
based on recent crude oil spot prices of USD 40 to 130/barrel and corresponding diesel and gasoline costs, excluding taxes.
I I I
I I I I I I I I I I I
15
Summaries Summary for Policymakers
Figure SPM.6 | Selected experience curves in logarithmic scale for (a) the price of silicon PV modules and onshore wind power plants per unit of capacity; and (b) the cost of
sugarcane-based ethanol production [data from Figure 3.17, 3.8.3, Figure 7.20, 7.8.2, Figure 2.21, 2.7.2].
Notes: Depending on the setting, cost reductions may occur at various geographic scales. The country-level examples provided here derive from the published literature. No global
dataset of wind power plant prices or costs is readily available. Reductions in the cost or price of a technology per unit of capacity understate reductions in the levelized cost of energy
of that technology when performance improvements occur. [7.8.4, 10.5]
Onshore Wind Power Plants
(Denmark)
Onshore Wind Power Plants
(USA)
Produced Silicon PV Modules
(Global)
1
Cumulative Global Capacity [MW]
1
10
100
10 100 1,000 10,000 100,000 1,000,000
Average Price [USD2005 /W]
1976
[65 USD/W]
2010
[1.4 USD/W]
(a)
0,5
50
5
1981
[2.6 USD/W]
1984
[4.3 USD/W]
2009
[1.4 USD/W]
2009
[1.9 USD/W]
Sugarcane
Ethanol Prod. Cost (excl. Feedstock)
Cumulative Sugarcane Production in Brazil [106 Tonnes of Sugarcane]
1,000 2,000 4,000 8,000 16,000
Average Production Cost of Ethanol [USD2005 /m3]
and Sugarcane [USD2005 /t]
10
20
40
200
400
800
10 20 40 80 160 320 640
Cumulative Ethanol Production in Brazil [106 m3]
2004
1975 1985
1995
2004
1975
1985
1995
(b)
4. Integration into present and future energy systems
Various RE resources are already being successfully integrated into energy supply systems [8.2] and into
end-use sectors [8.3] (Figure SPM.7).
The characteristics of different RE sources can infl uence the scale of the integration challenge. Some RE
resources are widely distributed geographically. Others, such as large-scale hydropower, can be more centralized but
have integration options constrained by geographic location. Some RE resources are variable with limited predictability.
Some have lower physical energy densities and different technical specifi cations from fossil fuels. Such characteristics
can constrain ease of integration and invoke additional system costs particularly when reaching higher shares of RE.
[8.2]
Integrating RE into most existing energy supply systems and end-use sectors at an accelerated rate—
leading to higher shares of RE—is technologically feasible, though will result in a number of additional
challenges. Increased shares of RE are expected within an overall portfolio of low GHG emission technologies [10.3,
Tables 10.4-10.6]. Whether for electricity, heating, cooling, gaseous fuels or liquid fuels, including integration directly
into end-use sectors, the RE integration challenges are contextual and site specifi c and include the adjustment of existing
energy supply systems. [8.2, 8.3]
The costs and challenges of integrating increasing shares of RE into an existing energy supply system
depend on the current share of RE, the availability and characteristics of RE resources, the system characteristics,
and how the system evolves and develops in the future.
• RE can be integrated into all types of electricity systems, from large inter-connected continental-scale grids [8.2.1]
down to small stand-alone systems and individual buildings [8.2.5]. Relevant system characteristics include the
generation mix and its fl exibility, network infrastructure, energy market designs and institutional rules, demand
location, demand profi les, and control and communication capability. Wind, solar PV energy and CSP without
: "
16
Summary for Policymakers Summaries
storage can be more diffi cult to integrate than dispatchable9 hydropower, bioenergy, CSP with storage and geothermal
energy.
As the penetration of variable RE sources increases, maintaining system reliability may become more challenging
and costly. Having a portfolio of complementary RE technologies is one solution to reduce the risks and costs of RE
integration. Other solutions include the development of complementary fl exible generation and the more fl exible
operation of existing schemes; improved short-term forecasting, system operation and planning tools; electricity
demand that can respond in relation to supply availability; energy storage technologies (including storage-based
hydropower); and modifi ed institutional arrangements. Electricity network transmission (including interconnections
between systems) and/or distribution infrastructure may need to be strengthened and extended, partly because of
the geographical distribution and fi xed remote locations of many RE resources. [8.2.1]
• District heating systems can use low-temperature thermal RE inputs such as solar and geothermal heat, or biomass,
including sources with few competing uses such as refuse-derived fuels. District cooling can make use of cold natural
waterways. Thermal storage capability and fl exible cogeneration can overcome supply and demand variability
challenges as well as provide demand response for electricity systems. [8.2.2]
9 Electricity plants that can schedule power generation as and when required are classed as dispatchable [8.2.1.1, Annex I]. Variable RE
technologies are partially dispatchable (i.e., only when the RE resource is available). CSP plants are classifi ed as dispatchable when heat is
stored for use at night or during periods of low sunshine.
Figure SPM.7 | Pathways for RE integration to provide energy services, either into energy supply systems or on-site for use by the end-use sectors. [Figure 8.1, 8.1]
Fossil Fuels
and Nuclear
Energy Efficiency
Measures
Energy Efficiency
and Demand
Response Measures
Renewable Energy Resources
End-Use Sectors
(Section 8.3)
Energy Supply
Systems
(Section 8.2)
Electricity Generation and
Distribution
Heating and Cooling Networks
Gas Grids
Liquid Fuels Distribution
Autonomous Systems
Transport and Vehicles
Buildings and Households
Industry
Agriculture, Forests and
Fisheries
Energy
Carriers
Energy
Services
Energy
Consumers
I I
I I
17
Summaries Summary for Policymakers
• In gas distribution grids, injecting biomethane, or in the future, RE-derived hydrogen and synthetic natural gas, can
be achieved for a range of applications but successful integration requires that appropriate gas quality standards
are met and pipelines upgraded where necessary. [8.2.3]
• Liquid fuel systems can integrate biofuels for transport applications or for cooking and heating applications. Pure
(100%) biofuels, or more usually those blended with petroleum-based fuels, usually need to meet technical standards
consistent with vehicle engine fuel specifi cations. [8.2.4, 8.3.1]
There are multiple pathways for increasing the shares of RE across all end-use sectors. The ease of integration
varies depending on region, characteristics specifi c to the sector and the technology.
• For transport, liquid and gaseous biofuels are already and are expected to continue to be integrated into the fuel
supply systems of a growing number of countries. Integration options may include decentralized on-site or centralized
production of RE hydrogen for fuel cell vehicles and RE electricity for rail and electric vehicles [8.2.1, 8.2.3]
depending on infrastructure and vehicle technology developments. [8.3.1] Future demand for electric vehicles could
also enhance fl exible electricity generation systems. [8.2.1, 8.3.1]
• In the building sector, RE technologies can be integrated into both new and existing structures to produce electricity,
heating and cooling. Supply of surplus energy may be possible, particularly for energy effi cient building designs.
[8.3.2] In developing countries, the integration of RE supply systems is feasible for even modest dwellings. [8.3.2,
9.3.2]
• Agriculture as well as food and fi bre process industries often use biomass to meet direct heat and power demands
on-site. They can also be net exporters of surplus fuels, heat, and electricity to adjacent supply systems. [8.3.3,
8.3.4] Increasing the integration of RE for use by industries is an option in several sub-sectors, for example through
electro-thermal technologies or, in the longer term, by using RE hydrogen. [8.3.3]
The costs associated with RE integration, whether for electricity, heating, cooling, gaseous or liquid fuels,
are contextual, site-specifi c and generally diffi cult to determine. They may include additional costs for network
infrastructure investment, system operation and losses, and other adjustments to the existing energy supply systems as
needed. The available literature on integration costs is sparse and estimates are often lacking or vary widely.
In order to accommodate high RE shares, energy systems will need to evolve and be adapted. [8.2, 8.3]
Long-term integration efforts could include investment in enabling infrastructure; modifi cation of institutional and
governance frameworks; attention to social aspects, markets and planning; and capacity building in anticipation of
RE growth. [8.2, 8.3] Furthermore, integration of less mature technologies, including biofuels produced through new
processes (also called advanced biofuels or next-generation biofuels), fuels generated from solar energy, solar cooling,
ocean energy technologies, fuel cells and electric vehicles, will require continuing investments in research, development
and demonstration (RD&D), capacity building and other supporting measures. [2.6, 3.7, 11.5, 11.6, 11.7]
RE could shape future energy supply and end-use systems, in particular for electricity, which is expected to attain higher
shares of RE earlier than either the heat or transport fuel sectors at the global level [10.3]. Parallel developments in
electric vehicles [8.3.1], increased heating and cooling using electricity (including heat pumps) [8.2.2, 8.3.2, 8.3.3], fl exible
demand response services (including the use of smart meters) [8.2.1], energy storage and other technologies could
be associated with this trend.
As infrastructure and energy systems develop, in spite of the complexities, there are few, if any, fundamental
technological limits to integrating a portfolio of RE technologies to meet a majority share of total
18
Summary for Policymakers Summaries
energy demand in locations where suitable RE resources exist or can be supplied. However, the actual rate
of integration and the resulting shares of RE will be infl uenced by factors such as costs, policies, environmental
issues and social aspects. [8.2, 8.3, 9.3, 9.4, 10.2, 10.5]
5. Renewable energy and sustainable development
Historically, economic development has been strongly correlated with increasing energy use and growth of
GHG emissions, and RE can help decouple that correlation, contributing to sustainable development (SD).
Though the exact contribution of RE to SD has to be evaluated in a country-specifi c context, RE offers the opportunity
to contribute to social and economic development, energy access, secure energy supply, climate change mitigation, and
the reduction of negative environmental and health impacts. [9.2] Providing access to modern energy services would
support the achievement of the Millennium Development Goals. [9.2.2, 9.3.2]
• RE can contribute to social and economic development. Under favorable conditions, cost savings in comparison
to non-RE use exist, in particular in remote and in poor rural areas lacking centralized energy access. [9.3.1,
9.3.2.] Costs associated with energy imports can often be reduced through the deployment of domestic RE technologies
that are already competitive. [9.3.3] RE can have a positive impact on job creation although the studies
available differ with respect to the magnitude of net employment. [9.3.1]
• RE can help accelerate access to energy, particularly for the 1.4 billion people without access to electricity
and the additional 1.3 billion using traditional biomass. Basic levels of access to modern energy services
can provide signifi cant benefi ts to a community or household. In many developing countries, decentralized grids
based on RE and the inclusion of RE in centralized energy grids have expanded and improved energy access. In
addition, non-electrical RE technologies also offer opportunities for modernization of energy services, for example,
using solar energy for water heating and crop drying, biofuels for transportation, biogas and modern biomass for
heating, cooling, cooking and lighting, and wind for water pumping. [9.3.2, 8.1] The number of people without
access to modern energy services is expected to remain unchanged unless relevant domestic policies are implemented,
which may be supported or complemented by international assistance as appropriate. [9.3.2, 9.4.2]
• RE options can contribute to a more secure energy supply, although specifi c challenges for integration
must be considered. RE deployment might reduce vulnerability to supply disruption and market volatility if
competition is increased and energy sources are diversifi ed. [9.3.3, 9.4.3] Scenario studies indicate that concerns
regarding secure energy supply could continue in the future without technological improvements within the
transport sector. [2.8, 9.4.1.1, 9.4.3.1, 10.3] The variable output profi les of some RE technologies often necessitate
technical and institutional measures appropriate to local conditions to assure energy supply reliability. [8.2, 9.3.3]
• In addition to reduced GHG emissions, RE technologies can provide other important environmental
benefi ts. Maximizing these benefi ts depends on the specifi c technology, management, and site characteristics
associated with each RE project.
• Lifecycle assessments (LCA) for electricity generation indicate that GHG emissions from RE technologies
are, in general, signifi cantly lower than those associated with fossil fuel options, and in a range
of conditions, less than fossil fuels employing CCS. The median values for all RE range from 4 to 46 g
CO2eq/kWh while those for fossil fuels range from 469 to 1,001 g CO2eq/kWh (excluding land use change emissions)
(Figure SPM.8).
• Most current bioenergy systems, including liquid biofuels, result in GHG emission reductions, and
most biofuels produced through new processes (also called advanced biofuels or next-generation
biofuels) could provide higher GHG mitigation. The GHG balance may be affected by land use
19
Summaries Summary for Policymakers
changes and corresponding emissions and removals. Bioenergy can lead to avoided GHG emissions from
residues and wastes in landfi ll disposals and co-products; the combination of bioenergy with CCS may provide
for further reductions (see Figure SPM.8). The GHG implications related to land management and land use
changes in carbon stocks have considerable uncertainties. [2.2, 2.5, 9.3.4.1]
• The sustainability of bioenergy, in particular in terms of lifecycle GHG emissions, is infl uenced by
land and biomass resource management practices. Changes in land and forest use or management that,
according to a considerable number of studies, could be brought about directly or indirectly by biomass production
for use as fuels, power or heat, can decrease or increase terrestrial carbon stocks. The same studies also
Figure SPM.8 | Estimates of lifecycle GHG emissions (g CO2eq/kWh) for broad categories of electricity generation technologies, plus some technologies integrated with CCS. Land userelated
net changes in carbon stocks (mainly applicable to biopower and hydropower from reservoirs) and land management impacts are excluded; negative estimates10 for biopower
are based on assumptions about avoided emissions from residues and wastes in landfi ll disposals and co-products. References and methods for the review are reported in Annex II. The
number of estimates is greater than the number of references because many studies considered multiple scenarios. Numbers reported in parentheses pertain to additional references
and estimates that evaluated technologies with CCS. Distributional information relates to estimates currently available in LCA literature, not necessarily to underlying theoretical or
practical extrema, or the true central tendency when considering all deployment conditions. [Figure 9.8, 9.3.4.1]
10 ‘Negative estimates’ within the terminology of lifecycle assessments presented in the SRREN refer to avoided emissions. Unlike the case of bioenergy
combined with CCS, avoided emissions do not remove GHGs from the atmosphere.
Maximum
75th Percentile
Median
25th Percentile
Minimum
Single Estimates
with CCS
Electricity Generation Technologies Powered by Renewable Resources
Biopower
Photovoltaics
Concentrating Solar Power
Coal
Oil
Natural Gas
Geothermal Energy
Hydropower
Nuclear Energy
Ocean Energy
Wind Energy
-1,250
-1,500
-1,000
750
250
-250
-750
-500
0
500
1,750
1,250
1,000
1,500
2,000
Lifecycle Greenhouse Gas Emissions [g CO2 eq / kWh]
Electricity Generation Technologies
Powered by Non-Renewable Resources
Avoided Emissions, no Removal of GHGs from the Atmosphere
*
*
169(+12)
50(+10)
24
10
83(+7)
36(+4)
125
32
126
49
10
5
28
11
8
6
42
13
124
26
222(+4)
52(+0)
Count of
Estimates
Count of
References
$
20
Summary for Policymakers Summaries
show that indirect changes in terrestrial carbon stocks have considerable uncertainties, are not directly observable,
are complex to model and are diffi cult to attribute to a single cause. Proper governance of land use, zoning,
and choice of biomass production systems are key considerations for policy makers. [2.4.5, 2.5.1, 9.3.4, 9.4.4]
Policies are in place that aim to ensure that the benefi ts from bioenergy, such as rural development, overall
improvement of agricultural management and the contribution to climate change mitigation, are realized; their
effectiveness has not been assessed. [2.2, 2.5, 2.8]
• RE technologies, in particular non-combustion based options, can offer benefi ts with respect to air
pollution and related health concerns. [9.3.4.3, 9.4.4.1] Improving traditional biomass use can signifi cantly
reduce local and indoor air pollution (alongside GHG emissions, deforestation and forest degradation) and
lower associated health impacts, particularly for women and children in developing countries. [2.5.4, 9.3.4.4]
• Water availability could infl uence choice of RE technology. Conventional water-cooled thermal power
plants may be especially vulnerable to conditions of water scarcity and climate change. In areas where water
scarcity is already a concern, non-thermal RE technologies or thermal RE technologies using dry cooling can provide
energy services without additional stress on water resources. Hydropower and some bioenergy systems are
dependent on water availability, and can either increase competition or mitigate water scarcity. Many impacts
can be mitigated by siting considerations and integrated planning. [2.5.5.1, 5.10, 9.3.4.4]
• Site-specifi c conditions will determine the degree to which RE technologies impact biodiversity.
RE-specifi c impacts on biodiversity may be positive or negative. [2.5, 3.6, 4.5, 5.6, 6.5, , 9.3.4.6]
• RE technologies have low fatality rates. Accident risks of RE technologies are not negligible, but their often
decentralized structure strongly limits the potential for disastrous consequences in terms of fatalities. However,
dams associated with some hydropower projects may create a specifi c risk depending on site-specifi c factors.
[9.3.4.7]
6. Mitigation potentials and costs
A signifi cant increase in the deployment of RE by 2030, 2050 and beyond is indicated in the majority of
the 164 scenarios reviewed in this Special Report.11 In 2008, total RE production was roughly 64 EJ/yr (12.9% of
total primary energy supply) with more than 30 EJ/yr of this being traditional biomass. More than 50% of the scenarios
project levels of RE deployment in 2050 of more than 173 EJ/yr reaching up to over 400 EJ/yr in some cases (Figure
SPM.9). Given that traditional biomass use decreases in most scenarios, a corresponding increase in the production
level of RE (excluding traditional biomass) anywhere from roughly three-fold to more than ten-fold is projected. The
global primary energy supply share of RE differs substantially among the scenarios. More than half of the scenarios
show a contribution from RE in excess of a 17% share of primary energy supply in 2030 rising to more than 27% in
2050. The scenarios with the highest RE shares reach approximately 43% in 2030 and 77% in 2050. [10.2, 10.3]
RE can be expected to expand even under baseline scenarios. Most baseline scenarios show RE deployments
signifi cantly above the 2008 level of 64 EJ/yr and up to 120 EJ/yr by 2030. By 2050, many baseline scenarios reach
RE deployment levels of more than 100 EJ/yr and in some cases up to about 250 EJ/yr (Figure SPM.9). These baseline
deployment levels result from a range of assumptions, including, for example, continued demand growth for energy
services throughout the century, the ability of RE to contribute to increased energy access and the limited long-term
11 For this purpose a review of 164 global scenarios from 16 different large-scale integrated models was conducted. Although the set of scenarios
allows for a meaningful assessment of uncertainty, the reviewed 164 scenarios do not represent a fully random sample suitable for rigorous
statistical analysis and do not represent always the full RE portfolio (e.g., so far ocean energy is only considered in a few scenarios) [10.2.2]. For
more specifi c analysis, a subset of 4 illustrative scenarios from the set of 164 was used. They represent a span from a baseline scenario without
specifi c mitigation targets to three scenarios representing different CO2 stabilization levels. [10.3]
21
Summaries Summary for Policymakers
availability of fossil resources. Other assumptions (e.g., improved costs and performance of RE technologies) render RE
technologies increasingly economically competitive in many applications even in the absence of climate policy. [10.2]
RE deployment signifi cantly increases in scenarios with low GHG stabilization concentrations. Low GHG stabilization
scenarios lead on average to higher RE deployment compared to the baseline. However, for any given long-term
GHG concentration goal, the scenarios exhibit a wide range of RE deployment levels (Figure SPM.9). In scenarios that
stabilize the atmospheric CO2 concentrations at a level of less than 440 ppm, the median RE deployment level in 2050
is 248 EJ/yr (139 in 2030), with the highest levels reaching 428 EJ/yr by 2050 (252 in 2030). [10.2]
Many combinations of low-carbon energy supply options and energy effi ciency improvements can contribute
to given low GHG concentration levels, with RE becoming the dominant low-carbon energy supply
option by 2050 in the majority of scenarios. This wide range of results originates in assumptions about factors such
as developments in RE technologies (including bioenergy with CCS) and their associated resource bases and costs; the
comparative attractiveness of other mitigation options (e.g., end-use energy effi ciency, nuclear energy, fossil energy
with CCS); patterns of consumption and production; fundamental drivers of energy services demand (including future
population and economic growth); the ability to integrate variable RE sources into power grids; fossil fuel resources;
specifi c policy approaches to mitigation; and emissions trajectories towards long-term concentration levels. [10.2]
Figure SPM.9 | Global RE primary energy supply (direct equivalent) from 164 long-term scenarios versus fossil and industrial CO2 emissions in 2030 and 2050. Colour coding is based
on categories of atmospheric CO2 concentration stabilization levels that are defi ned consistently with those in the AR4. The panels to the right of the scatterplots show the deployment
levels of RE in each of the atmospheric CO2 concentration categories. The thick black line corresponds to the median, the coloured box corresponds to the inter-quartile range (25th to
75th percentile) and the ends of the white surrounding bars correspond to the total range across all reviewed scenarios. The grey crossed lines show the relationship in 2007. [Figure
10.2, 10.2.2.2]
Notes: For data reporting reasons only 161 scenarios are included in the 2030 results shown here, as opposed to the full set of 164 scenarios. RE deployment levels below those of
today are a result of model output and differences in the reporting of traditional biomass. For details on the use of the ‘direct equivalent’ method of accounting for primary energy
supply and the implied care needed in the interpretation of scenario results, see Box SPM.2. Note that categories V and above are not included and category IV is extended to 600
ppm from 570 ppm, because all stabilization scenarios lie below 600 ppm CO2 in 2100 and because the lowest baseline scenarios reach concentration levels of slightly more than
600 ppm by 2100.
CO2 Concentration Levels
Category I (<400 ppm)
Category II (400-440 ppm)
Category III (440-485 ppm)
Category IV (485-600 ppm)
Baselines
0 20 40 60 0 20 40 60 80
2030
0 100 200 300 400
0 100 200 300 400
N=161
2050
N=164
Renewable Primary Energy Supply [EJ/yr]
CO2 Emissions from Fossil Fuels
and Industrial Processes [Gt CO2/yr]
CO2 Emissions from Fossil Fuels
and Industrial Processes [Gt CO2/yr]
Category I
Category II
Category III
Category IV
Baselines
Category I
Category II
Category III
Category IV
Baselines
Maximum
75th
Median
25th
Minimum
• 0 •• •
• • • • ,$.
• so e
• • .%
·%.d+ • 6@@
• oz£' : •
·ii o. %%
• 6 2% • •
• •
6 @
• .' eo •• 6 0 • • .,
• ·% 2%
•
•
•
22
Summary for Policymakers Summaries
The scenario review in this Special Report indicates that RE has a large potential to mitigate GHG emissions.
Four illustrative scenarios span a range of global cumulative CO2 savings between 2010 and 2050, from about
220 to 560 Gt CO2 compared to about 1,530 Gt cumulative fossil and industrial CO2 emissions in the IEA World Energy
Outlook 2009 Reference Scenario during the same period. The precise attribution of mitigation potentials to RE depends
on the role scenarios attribute to specifi c mitigation technologies, on complex system behaviours and, in particular, on
the energy sources that RE displaces. Therefore, attribution of precise mitigation potentials to RE should be viewed with
appropriate caution. [10.2, 10.3, 10.4]
Scenarios generally indicate that growth in RE will be widespread around the world. Although the precise
distribution of RE deployment among regions varies substantially across scenarios, the scenarios are largely consistent
in indicating widespread growth in RE deployment around the globe. In addition, the total RE deployment is higher over
the long term in the group of non-Annex I countries12 than in the group of Annex I countries in most scenarios (Figure
SPM.10). [10.2, 10.3]
12 The terms ‘Annex I’ and ‘non-Annex I’ are categories of countries that derive from the United Nations Framework Convention on Climate
Change (UNFCCC).
Figure SPM.10 | Global RE primary energy supply (direct equivalent) by source in the group of Annex I (AI) and the group of Non-Annex I (NAI) countries in 164 long-term scenarios
by 2030 and 2050. The thick black line corresponds to the median, the coloured box corresponds to the inter-quartile range (25th to 75th percentile) and the ends of the white
surrounding bars correspond to the total range across all reviewed scenarios. [Figure 10.8, 10.2.2.5]
Notes: For details on the use of the ‘direct equivalent’ method of accounting for primary energy supply and the implied care needed in the interpretation of scenario results, see Box
SPM.2. More specifi cally, the ranges of secondary energy provided from bioenergy, wind energy and direct solar energy can be considered of comparable magnitude in their higher
penetration scenarios in 2050. Ocean energy is not presented here as only very few scenarios consider this RE technology.
2030
AI NAI AI NAI AI NAI AI NAI AI NAI
[EJ/yr]
0
50
100
150
200
2050
[EJ/yr] 0
50
100
150
200
AI NAI AI NAI AI NAI AI NAI AI NAI
Bioenergy
Hydropower
Wind Energy
Direct Solar Energy
Geothermal Energy
Maximum
75th
Median
25th
Minimum
-
e 7-.._=.
■
■
■
■
■
23
Summaries Summary for Policymakers
Scenarios do not indicate an obvious single dominant RE technology at a global level; in addition, the
global overall technical potentials do not constrain the future contribution of RE. Although the contribution of
RE technologies varies across scenarios, modern biomass, wind and direct solar commonly make up the largest contributions
of RE technologies to the energy system by 2050 (Figure SPM.11). All scenarios assessed confi rm that technical
potentials will not be the limiting factors for the expansion of RE at a global scale. Despite signifi cant technological and
regional differences, in the four illustrative scenarios less than 2.5% of the global available technical RE potential is
used. [10.2, 10.3]
Wind Energy
2030 2050
Primary Energy Supply [EJ/yr]
0
50
150
100
Direct Solar Energy
2030 2050
Hydropower
2030 2050
Geothermal Energy
2030 2050 2030 2050
Bioenergy
CO2 Concentration Levels
Baselines
Cat. III + IV (440 - 600 ppm)
Cat. I + II (<440 ppm)
Bioenergy Supply is Accounted for Prior to Conversion Primary Energy Supply is Accounted for Based on Secondary Energy Produced
300
Primary Energy Supply [EJ/yr]
0
50
150
100
Primary Energy Supply [EJ/yr]
0
50
150
100
Primary Energy Supply [EJ/yr]
0
50
150
100
200
250
350
Primary Energy Supply [EJ/yr]
0
50
150
100
Deployment Level 2008
Maximum
75th
Median
25th
Minimum
Figure SPM.11 | Global primary energy supply (direct equivalent) of bioenergy, wind, direct solar, hydro, and geothermal energy in 164 long-term scenarios in 2030 and 2050,
and grouped by different categories of atmospheric CO2 concentration level that are defi ned consistently with those in the AR4. The thick black line corresponds to the median, the
coloured box corresponds to the inter-quartile range (25th to 75th percentile) and the ends of the white surrounding bars correspond to the total range across all reviewed scenarios.
[Excerpt from Figure 10.9, 10.2.2.5]
Notes: For details on the use of the ‘direct equivalent’ method of accounting for primary energy supply and the implied care needed in the interpretation of scenario results, see Box
SPM.2. More specifi cally, the ranges of secondary energy provided from bioenergy, wind energy and direct solar energy can be considered of comparable magnitude in their higher
penetration scenarios in 2050. Ocean energy is not presented here as only very few scenarios consider this RE technology. Note that categories V and above are not included and
category IV is extended to 600 ppm from 570 ppm, because all stabilization scenarios lie below 600 ppm CO2 in 2100 and because the lowest baselines scenarios reach concentration
levels of slightly more than 600 ppm by 2100.
- -i-□- --- -- - - --
■■ ■ # - --- - --------
24
Summary for Policymakers Summaries
Individual studies indicate that if RE deployment is limited, mitigation costs increase and low GHG concentration
stabilizations may not be achieved. A number of studies have pursued scenario sensitivities that assume
constraints on the deployment of individual mitigation options, including RE as well as nuclear and fossil energy with
CCS. There is little agreement on the precise magnitude of the cost increase. [10.2]
A transition to a low-GHG economy with higher shares of RE would imply increasing investments in technologies
and infrastructure. The four illustrative scenarios analyzed in detail in the SRREN estimate global cumulative RE
investments (in the power generation sector only) ranging from USD2005 1,360 to 5,100 billion for the decade 2011 to
2020, and from USD2005 1,490 to 7,180 billion for the decade 2021 to 2030. The lower values refer to the IEA World
Energy Outlook 2009 Reference Scenario and the higher ones to a scenario that seeks to stabilize atmospheric CO2
(only) concentration at 450 ppm. The annual averages of these investment needs are all smaller than 1% of the world’s
gross domestic product (GDP). Beyond differences in the design of the models used to investigate these scenarios,
the range can be explained mainly by differences in GHG concentrations assessed and constraints imposed on the set
of admissible mitigation technologies. Increasing the installed capacity of RE power plants will reduce the amount of
fossil and nuclear fuels that otherwise would be needed in order to meet a given electricity demand. In addition to
investment, operation and maintenance (O&M) and (where applicable) feedstock costs related to RE power plants, any
assessment of the overall economic burden that is associated with their application will have to consider avoided fuel
and substituted investment costs as well. Even without taking the avoided costs into account, the lower range of the
RE power investments discussed above is lower than the respective investments reported for 2009. The higher values of
the annual averages of the RE power sector investment approximately correspond to a fi ve-fold increase in the current
global investments in this fi eld. [10.5, 11.2.2]
7. Policy, implementation and fi nancing
An increasing number and variety of RE policies—motivated by many factors—have driven escalated
growth of RE technologies in recent years. [1.4, 11.2, 11.5, 11.6] Government policies play a crucial role in accelerating
the deployment of RE technologies. Energy access and social and economic development have been the primary
drivers in most developing countries whereas secure energy supply and environmental concerns have been most
important in developed countries [9.3, 11.3]. The focus of policies is broadening from a concentration primarily on RE
electricity to include RE heating and cooling and transportation. [11.2, 11.5]
RE-specifi c policies for research, development, demonstration and deployment help to level the playing fi eld for RE.
Policies include regulations such as feed-in-tariffs, quotas, priority grid access, building mandates, biofuel blending
requirements, and bioenergy sustainability criteria. [2.4.5.2, 2.ES, TS.2.8.1] Other policy categories are fi scal incentives
such as tax policies and direct government payments such as rebates and grants; and public fi nance mechanisms such
as loans and guarantees. Wider policies aimed at reducing GHG emissions such as carbon pricing mechanisms may also
support RE.
Policies can be sector specifi c, can be implemented at the local, state/provincial, national and in some cases regional
level, and can be complemented by bilateral, regional and international cooperation. [11.5]
Policies have promoted an increase in RE capacity installations by helping to overcome various barriers. [1.4,
11.1, 11.4, 11.5, 11.6] Barriers to RE deployment include:
• Institutional and policy barriers related to existing industry, infrastructure and regulation of the energy system;
• Market failures, including non-internalized environmental and health costs, where applicable;
25
Summaries Summary for Policymakers
• Lack of general information and access to data relevant to the deployment of RE, and lack of technical and knowledge
capacity; and
• Barriers related to societal and personal values and affecting the perception and acceptance of RE technologies.
[1.4, 9.5.1, 9.5.2.1]
Public R&D investments in RE technologies are most effective when complemented by other policy instruments,
particularly deployment policies that simultaneously enhance demand for new technologies. Together,
R&D and deployment policies create a positive feedback cycle, inducing private sector investment. Enacting deployment
policies early in the development of a given technology can accelerate learning by inducing private R&D, which in turn
further reduces costs and provides additional incentives for using the technology. [11.5.2]
Some policies have been shown to be effective and effi cient in rapidly increasing RE deployment. However,
there is no one-size-fi ts-all policy. Experience shows that different policies or combinations of policies can be more
effective and effi cient depending on factors such as the level of technological maturity, affordable capital, ease of integration
into the existing system and the local and national RE resource base. [11.5]
• Several studies have concluded that some feed in tariffs have been effective and effi cient at promoting RE electricity,
mainly due to the combination of long-term fi xed price or premium payments, network connections, and
guaranteed purchase of all RE electricity generated. Quota policies can be effective and effi cient if designed to
reduce risk; for example, with long-term contracts. [11.5.4]
• An increasing number of governments are adopting fi scal incentives for RE heating and cooling. Obligations to
use RE heat are gaining attention for their potential to encourage growth independent of public fi nancial support.
[11.5.5]
• In the transportation sector, RE fuel mandates or blending requirements are key drivers in the development of most
modern biofuel industries. Other policies include direct government payments or tax reductions. Policies have infl uenced
the development of an international biofuel trade. [11.5.6]
The fl exibility to adjust as technologies, markets and other factors evolve is important. The details of design and implementation
are critical in determining the effectiveness and effi ciency of a policy. [11.5]. Policy frameworks that are
transparent and sustained can reduce investment risks and facilitate deployment of RE and the evolution of low-cost
applications. [11.5, 11.6]
‘Enabling’ policies support RE development and deployment. A favourable, or enabling, environment for RE
can be created by addressing the possible interactions of a given policy with other RE policies as well as with energy
and non-energy policies (e.g., those targeting agriculture, transportation, water management and urban planning); by
easing the ability of RE developers to obtain fi nance and to successfully site a project; by removing barriers for access
to networks and markets for RE installations and output; by increasing education and awareness through dedicated
communication and dialogue initiatives; and by enabling technology transfer. In turn, the existence of an ‘enabling’
environment can increase the effi ciency and effectiveness of policies to promote RE. [9.5.1.1, 11.6]
Two separate market failures create the rationale for the additional support of innovative RE technologies
that have high potential for technological development, even if an emission market (or GHG pricing policy
in general) exists. The fi rst market failure refers to the external cost of GHG emissions. The second market failure is in
the fi eld of innovation: if fi rms underestimate the future benefi ts of investments into learning RE technologies or if they
26
Summary for Policymakers Summaries
cannot appropriate these benefi ts, they will invest less than is optimal from a macroeconomic perspective. In addition
to GHG pricing policies, RE-specifi c policies may be appropriate from an economic point of view if the related opportunities
for technological development are to be addressed (or if other goals beyond climate mitigation are pursued).
Potentially adverse consequences such as lock-in, carbon leakage and rebound effects should be taken into account in
the design of a portfolio of policies. [11.1.1, 11.5.7.3]
The literature indicates that long-term objectives for RE and fl exibility to learn from experience would be
critical to achieve cost-effective and high penetrations of RE. This would require systematic development of
policy frameworks that reduce risks and enable attractive returns that provide stability over a time frame relevant to
the investment. An appropriate and reliable mix of policy instruments, including energy effi ciency policies, is even more
important where energy infrastructure is still developing and energy demand is expected to increase in the future. [11.5,
11.6, 11.7]
8. Advancing knowledge about renewable energy
Enhanced scientifi c and engineering knowledge should lead to performance improvements and cost reductions in RE
technologies. Additional knowledge related to RE and its role in GHG emissions reductions remains to be gained in a
number of broad areas including: [for details, see Table 1.1]
• Future cost and timing of RE deployment;
• Realizable technical potential for RE at all geographical scales;
• Technical and institutional challenges and costs of integrating diverse RE technologies into energy systems and
markets;
• Comprehensive assessments of socioeconomic and environmental aspects of RE and other energy technologies;
• Opportunities for meeting the needs of developing countries with sustainable RE services; and
• Policy, institutional and fi nancial mechanisms to enable cost-effective deployment of RE in a wide variety of
contexts.
Knowledge about RE and its climate change mitigation potential continues to advance. The existing scientifi c knowledge
is signifi cant and can facilitate the decision-making process. [1.1.8]
TS Technical Summary
Lead Authors:
Dan Arvizu (USA), Thomas Bruckner (Germany), Helena Chum (USA/Brazil), Ottmar Edenhofer (Germany),
Segen Estefen (Brazil) Andre Faaij (The Netherlands), Manfred Fischedick (Germany),
Gerrit Hansen (Germany), Gerardo Hiriart (Mexico), Olav Hohmeyer (Germany),
K. G. Terry Hollands (Canada), John Huckerby (New Zealand), Susanne Kadner (Germany),
Ånund Killingtveit (Norway), Arun Kumar (India), Anthony Lewis (Ireland), Oswaldo Lucon (Brazil),
Patrick Matschoss (Germany), Lourdes Maurice (USA), Monirul Mirza (Canada/Bangladesh),
Catherine Mitchell (United Kingdom), William Moomaw (USA), José Moreira (Brazil),
Lars J. Nilsson (Sweden), John Nyboer (Canada), Ramon Pichs-Madruga (Cuba), Jayant Sathaye (USA),
Janet L. Sawin (USA), Roberto Schaeffer (Brazil), Tormod A. Schei (Norway), Steffen Schlömer (Germany),
Kristin Seyboth (Germany/USA), Ralph Sims (New Zealand), Graham Sinden (United Kingdom/Australia),
Youba Sokona (Ethiopia/Mali), Christoph von Stechow (Germany), Jan Steckel (Germany),
Aviel Verbruggen (Belgium), Ryan Wiser (USA), Francis Yamba (Zambia), Timm Zwickel (Germany)
Review Editors:
Leonidas O. Girardin (Argentina), Mattia Romani (United Kingdom/Italy)
Special Advisor:
Jeffrey Logan (USA)
This Technical Summary should be cited as:
Arvizu, D., T. Bruckner, H. Chum, O. Edenhofer, S. Estefen, A. Faaij, M. Fischedick, G. Hansen, G. Hiriart, O. Hohmeyer,
K. G. T. Hollands, J. Huckerby, S. Kadner, Å. Killingtveit, A. Kumar, A. Lewis, O. Lucon, P. Matschoss, L. Maurice, M. Mirza,
C. Mitchell, W. Moomaw, J. Moreira, L. J. Nilsson, J. Nyboer, R. Pichs-Madruga, J. Sathaye, J. Sawin, R. Schaeffer, T. Schei,
S. Schlömer, K. Seyboth, R. Sims, G. Sinden, Y. Sokona, C. von Stechow, J. Steckel, A. Verbruggen, R. Wiser, F. Yamba,
T. Zwickel, 2011: Technical Summary. In IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation
[O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer,
C. von Stechow (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
27
28
Technical Summary Summaries
Table of Contents
1. Overview of Climate Change and Renewable Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
1.1 Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
1.2 Summary of renewable energy resources and potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
1.3 Meeting energy service needs and current status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
1.4 Opportunities, barriers, and issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
1.5 Role of policy, research and development, deployment and implementation strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2. Bioenergy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.1 Introduction to biomass and bioenergy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.2 Bioenergy resource potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.3 Bioenergy technology and applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.4 Global and regional status of markets and industry deployment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.5 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
2.6 Prospects for technology improvement and integration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
2.7 Current costs and trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
2.8 Potential deployment levels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3. Direct Solar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.2 Resource potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.3 Technology and applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.4 Global and regional status of market and industry deployment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.5 Integration into the broader energy system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.6 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
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3.7 Prospects for technology improvements and innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.8 Cost trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.9 Potential deployment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4. Geothermal Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.2 Resource potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3 Technology and applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.4 Global and regional status of market and industry development. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.5 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.6 Prospects for technology improvement, innovation and integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.7 Cost trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.8 Potential deployment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5. Hydropower . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2 Resource potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.3 Technology and applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.4 Global and regional status of market and industry development. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.5 Integration into broader energy systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.6 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.7 Prospects for technology improvement and innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.8 Cost trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
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5.9 Potential deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.10 Integration into water management systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6. Ocean Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6.2 Resource potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6.3 Technology and applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
6.4 Global and regional status of the markets and industry development. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
6.5 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
6.6 Prospects for technology improvement, innovation and integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.7 Cost trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
6.8 Potential deployment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
7. Wind Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
7.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
7.2 Resource potential. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
7.3 Technology and applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
7.4 Global and regional status of market and industry development. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
7.5 Near-term grid integration issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
7.6 Environmental and social impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
7.7 Prospects for technology improvement and innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
7.8 Cost trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
7.9 Potential deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
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8. Integration of Renewable Energy into Present and Future Energy Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
8.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
8.2 Integration of renewable energy into electrical power systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
8.3 Integration of renewable energy into heating and cooling networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
8.4 Integration of renewable energy into gas grids. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
8.5 Integration of renewable energy into liquid fuels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
8.6 Integration of renewable energy into autonomous systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
8.7 End-use sectors: Strategic elements for transition pathways. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
9. Renewable Energy in the Context of Sustainable Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
9.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
9.2 Interactions between sustainable development and renewable energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
9.3 Social, environmental and economic impacts: Global and regional assessment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
9.4 Implication of sustainable development pathways for renewable energy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
9.5 Barriers and opportunities for renewable energy in the context of sustainable development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
9.6 Synthesis, knowledge gaps and future research needs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
10. Mitigation Potential and Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
10.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
10.2 Synthesis of mitigation scenarios for different renewable energy strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
10.3 Assessment of representative mitigation scenarios for different renewable energy strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
10.4 Regional cost curves for mitigation with renewable energy sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
10.5 Cost of commercialization and deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
10.6 Social and environmental costs and benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
32
Technical Summary Summaries
11. Policy, Financing and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
11.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
11.2 Current trends: Policies, financing and investment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
11.3 Key drivers, opportunities and benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
11.4 Barriers to renewable energy policymaking, implementation and financing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
11.5 Experience with and assessment of policy options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
11.6 Enabling environment and regional issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
11.7 A structural shift. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
33
Summaries Technical Summary
1. Overview of Climate Change and
Renewable Energy
1.1 Background
All societies requir e energy services to meet basic human needs (e.g.,
lighting, cooking, space comfort, mobility, communication) and to
serve productive processes. For development to be sustainable, delivery
of energy services needs to be secure and have low environmental
impacts. Sustainable social and economic development requires assured
and affordable access to the energy resources necessary to provide
essential and sustainable energy services. This may mean the application
of different strategies at different stages of economic development.
To be environmentally benign, energy services must be provided with
low environmental impacts and low greenhouse gas (GHG) emissions.
However, the IPCC Fourth Assessment Report (AR4) reported that fossil
fuels provided 85%1 of the total primary energy in 2004, which is
the same value as in 2008. Furthermore, the combustion of fossil fuels
accounted for 56.6% of all anthropogenic GHG emissions (CO2eq)2 in
2004. [1.1.1, 9.2.1, 9.3.2, 9.6, 11.3]
Renewable energy (RE) sources play a role in providing energy services
in a sustainable manner and, in particular, in mitigating climate change.
This Special Report on Renewable Energy Sources and Climate Change
Mitigation explores the current contribution and potential of RE sources
to provide energy services for a sustainable social and economic development
path. It includes assessments of available RE resources and
technologies, costs and co-benefi ts, barriers to up-scaling and integration
requirements, future scenarios and policy options. In particular, it
provides information for policymakers, the private sector and civil society
on:
• Identifi cation of RE resources and available technologies and
impacts of climate change on these resources [Chapters 2–7];
• Technology and market status, future developments and projected
rates of deployment [Chapters 2–7,10];
• Options and constraints for integration into the energy supply system
and other markets, including energy storage, modes of transmission,
integration into existing systems and other options [Chapter 8];
• Linkages among RE growth, opportunities and sustainable development
[Chapter 9];
• Impacts on secure energy supply [Chapter 9];
• Economic and environmental costs, benefi ts, risks and impacts of
deployment [Chapters 9, 10];
1 The number from AR4 is 80% and has been converted from the physical content
method for energy accounting to the direct equivalent method as the latter method
is used in this report. Please refer to Section 1.1.9 and Annex II (Section A.II.4) for
methodological details.
2 The contributions from other sources and/or gases are: CO2 from deforestation,
decay of biomass etc. (17.3%), CO2 from other (2.8%), CH4 (14.3%), N2O (7.9%)
and fl uorinated gases (1.1%).
• Mitigation potential of RE resources [Chapter 10];
• Scenarios that demonstrate how accelerated deployment might be
achieved in a sustainable manner [Chapter 10];
• Capacity building, technology transfer and fi nancing [Chapter 11];
and
• Policy options, outcomes and conditions for effectiveness [Chapter
11].
The report consists of 11 chapters. Chapter 1 sets the scene on RE and
climate change; Chapters 2 through 7 provide information on six RE
technologies while Chapters 8 through 11 deal with integrative issues
(see Figure TS.1.1). The report communicates uncertainty where relevant.
3 This Technical Summary (TS) provides an overview of the report,
summarizing the essential fi ndings.
While the TS generally follows the structure of the full report, references
to the various applicable chapters and sections are indicated
with corresponding chapter and section numbers in square brackets. An
explanation of terms, acronyms and chemical symbols used in the TS can
be found in Annex I. Conventions and methodologies for determining
costs, primary energy and other topics of analysis can be found in Annex
II. Information on levelized costs of RE can be found in Annex III.
GHG emissions associated with the provision of energy services is a
major cause of climate change. The AR4 concluded that “Most of the
observed increase in global average temperature since the mid-20th
century is very likely due to the observed increase in anthropogenic
GHG (greenhouse gas) concentrations.” Concentrations have continued
to grow since the AR4 to over 390 ppm CO2 or 39% above pre-industrial
levels by the end of 2010. Since approximately 1850, global use of fossil
fuels (coal, oil and gas) has increased to dominate energy supply, leading
to a rapid growth in carbon dioxide (CO2) emissions [Figure 1.6]. The
amount of carbon in fossil fuel reserves and resources not yet burned
[Figure 1.7] has the potential to add quantities of CO2 to the atmosphere—
if burned over coming centuries—that would exceed the range
of any scenario considered in the AR4 [Figure 1.5] or in Chapter 10 of
this report. [1.1.3, 1.1.4]
Despite substantial associated decarbonization, the overwhelming
majority of the non-intervention emission projections exhibit considerably
higher emissions in 2100 compared with those in 2000, implying
rising GHG concentrations and, in turn, an increase in global mean temperatures.
To avoid such adverse impacts of climate change on water
resources, ecosystems, food security, human health and coastal settlements
with potentially irreversible abrupt changes in the climate system,
3 This report communicates uncertainty, for example, by showing the results of
sensitivity analyses and by quantitatively presenting ranges in cost numbers as well
as ranges in the scenario results. This report does not apply formal IPCC uncertainty
terminology because at the time of the approval of this report, IPCC uncertainty
guidance was in the process of being revised.
34
Technical Summary Summaries
2. Bioenergy
3. Direct Solar Energy
4. Geothermal Energy
5. Hydropower
6. Ocean Energy
7. Wind Energy
1. Renewable Energy and Climate Change
8. Integration of Renewable Energy into Present and Future Energy Systems
9. Renewable Energy in the Context of Sustainable Development
10. Mitigation Potential and Costs
11. Policy, Financing and Implementation
Integrative Chapters
Introductory Chapter
Technology Chapters
Special Report on Renewable Energy Sources and Climate Change Mitigation
Figure TS.1.1 | Structure of the report. [Figure 1.1]
the Cancun Agreements call for limiting global average temperature
rises to no more than 2°C above pre-industrial values, and agreed to
consider limiting this rise to 1.5°C. In order to be confi dent of achieving
an equilibrium temperature increase of only 2°C to 2.4°C, atmospheric
GHG concentrations would need to be stabilized in the range of 445
to 490 ppm CO2eq in the atmosphere. This in turn implies that global
emissions of CO2 will need to decrease by 50 to 85% below 2000 levels
by 2050 and begin to decrease (instead of continuing their current
increase) no later than 2015. [1.1.3]
To develop strategies for reducing CO2 emissions, the Kaya identity can
be used to decompose energy-related CO2 emissions into four factors:
1) population, 2) gross domestic product (GDP) per capita, 3) energy
intensity (i.e., total primary energy supply (TPES) per GDP) and 4) carbon
intensity (i.e., CO2 emissions per TPES). [1.1.4]
CO2 emissions = Population x (GDP/population) x (TPES/GDP) x (CO2/
TPES)
The annual change in these four components is illustrated in Figure
TS.1.2. [1.1.4]
While GDP per capita and population growth had the largest effect on
emissions growth in earlier decades, decreasing energy intensity signifi -
cantly slowed emissions growth in the period from 1971 to 2008. In the
past, carbon intensity fell because of improvements in energy effi ciency
and switching from coal to natural gas and the expansion of nuclear
energy in the 1970s and 1980s that was particularly driven by Annex I
countries.4 In recent years (2000 to 2007), increases in carbon intensity
have been driven mainly by the expansion of coal use in both developed
and developing countries, although coal and petroleum use have fallen
slightly since 2007. In 2008 this trend was broken due to the fi nancial
crisis. Since the early 2000s, the energy supply has become more carbon
intensive, thereby amplifying the increase resulting from growth in GDP
per capita. [1.1.4]
On a global basis, it is estimated that RE accounted for 12.9% of the
492 EJ of total primary energy supply in 2008. The largest RE contributor
was biomass (10.2%), with the majority (roughly 60%) of the biomass
fuel used in traditional cooking and heating applications in developing
countries but with rapidly increasing use of modern biomass as well.5
Hydropower represented 2.3%, whereas other RE sources accounted for
0.4%. (Figure TS.1.3). In 2008, RE contributed approximately 19% of
global electricity supply (16% hydropower, 3% other RE). [1.1.5]
Deployment of RE has been increasing rapidly in recent years. Under most
conditions, increasing the share of RE in the energy mix will require policies
to stimulate changes in the energy system. Government policy, the
declining cost of many RE technologies, changes in the prices of fossil
4 See Glossary (Annex I) for a defi nition of Annex I countries.
5 Not accounted for here or in offi cial databases is the estimated 20 to 40% of
additional traditional biomass used in informal sectors. [2.1]
35
Summaries Technical Summary
Carbon Intensity
Energy Intensity
GDP per Capita
Population
Change in CO2
1971 1975 1980 1985 1990 1995 2000 2005 2008
−1
-0.5
0
0.5
1
1.5
2
1971 1975 1980 1985 1990 1995 2000 2005 2008
−2
0
2
4
6
8
Δ CO2 / yr [Gt]
Δ CO2 / yr [%]
Figure TS.1.2 | Decomposition of (left) annual absolute change and (right) annual growth rate in global energy-related CO2 emissions by the factors in the Kaya identity; population
(red), GDP per capita (orange), energy intensity (light blue) and carbon intensity (dark blue) from 1971 to 2008. The colours show the changes that would occur due to each factor
alone, holding the respective other factors constant. Total annual changes are indicated by a black triangle. [Figure 1.8]
fuels and other factors have supported the continuing increase in the use
of RE. While the RE share is still relatively small, its growth has accelerated
in recent years as shown in Figure TS.1.4. In 2009, despite global
fi nancial challenges, RE capacity continued to grow rapidly, including
wind power (32%, 38 GW added), hydropower (3%, 31 GW added),
grid-connected photovoltaics (53%, 7.5 GW added), geothermal power
(4%, 0.4 GW added), and solar hot water/heating (21%, 31 GWth added).
Biofuels accounted for 2% of global road transport fuel demand in 2008
and nearly 3% in 2009. The annual production of ethanol increased to
1.6 EJ (76 billion litres) by the end of 2009 and biodiesel production
increased to 0.6 EJ (17 billion litres). Of the approximate 300 GW of new
electricity generating capacity added globally from 2008 to 2009, about
140 GW came from RE additions. Collectively, developing countries host
53% of global RE electricity generation capacity (including all sizes of
hydropower), with China adding more RE power capacity than any other
country in 2009. The USA and Brazil accounted for 54 and 35% of global
bioethanol production in 2009, respectively, while China led in the use
of solar hot water. At the end of 2009, the use of RE in hot water/heating
Wind Energy 0.2%
Geothermal Energy 0.1%
Ocean Energy 0.002%
Direct Solar Energy 0.1%
Gas
22.1%
Coal
28.4%
RE
12.9%
Oil
34.6%
Nuclear
Energy 2.0%
Hydropower 2.3%
Bioenergy
10.2%
Figure TS.1.3 | Shares of energy sources in total global total primary energy supply in 2008 (492 EJ). Modern biomass contributes 38% of the total biomass share. [Figure 1.10]
- 11] -
36
Technical Summary Summaries
Biofuels (incl. Biogas)
Wind Energy
Geothermal Energy
Solar Thermal Energy
Municipal Solid Waste
(Renewable Share)
Primary Solid Biomass
for Heat and Electricity
Applications
Hydropower
Global Primary Energy Supply [EJ/yr]
0
10
20
30
40
50
60
0
1
2
3
4
5
Solar PV Energy
Ocean Energy
0.00
0.01
0.02
0.03
0.04
0.05
1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
Figure TS.1.4 | Historical development of global primary energy supply from renewable energy from 1971 to 2008. [Figure 1.12]
Note: Technologies are referenced to separate vertical units for display purposes only. Underlying data for the fi gure has been converted to the ‘direct equivalent’ method of accounting
for primary energy supply [1.1.9, Annex II.4], except that the energy content of biofuels is reported in secondary energy terms (the primary biomass used to produce the biofuel
would be higher due to conversion losses [2.3, 2.4]).
markets included modern biomass (270 GWth), solar energy (180 GWth),
and geothermal energy (60 GWth). The use of RE (excluding traditional
biomass) in meeting rural energy needs has also increased,
including small-scale hydropower stations, various modern biomass
options, and household or village photovoltaic (PV), wind or
hybrid systems that combine multiple technologies. [1.1.5]
■
■
□
■
■
■
■
37
Summaries Technical Summary
There are multiple means for lowering GHG emissions from the
energy system while still providing desired energy services. The
AR4 identifi ed a number of ways to lower heat-trapping emissions
from energy sources while still providing energy services:
[1.1.6]
• Improve supply side effi ciency of energy conversion, transmission
and distribution, including combined heat and power.
• Improve demand side effi ciency in the respective sectors and
applications (e.g., buildings, industrial and agricultural processes,
transportation, heating, cooling and lighting).
• Shift from high-GHG energy carriers such as coal and oil to lower-
GHG energy carriers such as natural gas, nuclear fuels and RE
sources.
• Utilize CO2 capture and storage (CCS) to prevent post-combustion
or industrial process CO2 from entering the atmosphere. CCS has the
potential for removing CO2 from the atmosphere when biomass is
processed, for example, through combustion or fermentation.
• Change behaviour to better manage energy use or to use fewer
carbon- and energy-intensive goods and services.
The future share of RE applications will heavily depend on climate
change mitigation goals, the level of requested energy services and
resulting energy needs as well as their relative merit within the
Climate Stabilization Goal
CO2 - Emissions Trajectory
Freely Emitting Fossil Fuels Zero- or Low-Carbon Energies:
RE, Nuclear, CCS
Carbon Budget (Limit on
Cumulative Emissions)
Share of Renewable Energies in the
Provision of Primary Energy Supply
Selection of a Portfolio According
to the Following Criteria:
•Economic Competition
•Environmental Impacts
(Beyond Climate Change)
• Security Aspects
• Societal Aspects
“Scale”: Energy Services and Resulting Energy Needs
Energy Efficiency
Figure TS.1.5 | The role of renewable energies within the portfolio of zero- or low-carbon
mitigation options (qualitative description). [Figure 1.14]
portfolio of zero- or low-carbon technologies (Figure TS.1.5). A comprehensive
evaluation of any portfolio of mitigation options would
involve an evaluation of their respective mitigation potential as well as
all associated risks, costs and their contribution to sustainable development.
[1.1.6]
Setting a climate protection goal in terms of the admissible change
in global mean temperature broadly defi nes a corresponding GHG
concentration limit with an associated CO2 budget and subsequent
time-dependent emission trajectory, which then defi nes the admissible
amount of freely emitting fossil fuels. The complementary contribution
of zero- or low-carbon energies to the primary energy supply
is infl uenced by the ‘scale’ of the requested energy services. [1.1.6]
As many low-cost options to improve overall energy effi ciency are
already part of the non-intervention scenarios, the additional opportunities
to decrease energy intensity in order to mitigate climate
change are limited. In order to achieve ambitious climate protection
goals, energy effi ciency improvements alone do not suffi ce, requiring
additional zero- or low-carbon technologies. The contribution
RE will provide within the portfolio of these low-carbon technologies
heavily depends on the economic competition between these
technologies, a comparison of the relative environmental burden
(beyond climate change) associated with them, as well as security
and societal aspects (Figure TS.1.5). [1.1.6]
The body of scientifi c knowledge on RE and on the possible contribution
of RE towards meeting GHG mitigation goals, as compiled
and assessed in this report, is substantial. Nonetheless, due in part
to the site-specifi c nature of RE, the diversity of RE technologies,
the multiple end-use energy service needs that those technologies
might serve, the range of markets and regulations governing integration,
and the complexity of energy system transitions, knowledge
about RE and its climate mitigation potential continues to advance.
Additional knowledge remains to be gained in a number of broad
areas related to RE and its possible role in GHG emissions reductions:
[1.1.8]
• Future cost and timing of RE deployment;
• Realizable technical potential for RE at all geographical scales;
• Technical and institutional challenges and costs of integrating
diverse RE technologies into energy systems and markets;
• Comprehensive assessment of socioeconomic and environmental
aspects of RE and other energy technologies;
• Opportunities for meeting the needs of developing countries with
sustainable RE services; and
• Policy, institutional and fi nancial mechanisms to enable costeffective
deployment of RE in a wide variety of contexts.
Though much is already known in each of these areas, as compiled in
this report, additional research and experience would further reduce
uncertainties and thus facilitate decision making related to the use of
RE in the mitigation of climate change. [1.1.6]
t
__ t __
J
38
Technical Summary Summaries
energy service needs. Figure TS.1.6 illustrates the multi-step conversion
processes. [1.2.1]
Since it is energy services and not energy that people need, the process
should be driven in an effi cient manner that requires less primary
energy consumption with low-carbon technologies that minimize CO2
emissions. Thermal conversion processes to produce electric ity (including
biomass and geothermal) suffer losses of approximately 40 to 90%,
and losses of around 80% occur when supplying the mechanical energy
needed for transport based on internal combustion engines. These conversion
losses raise the share of primary energy from fossil fuels, and
the primary energy required from fossil fuels to produce electricity and
mechanical energy from heat. Direct energy conversions from solar PV,
hydro, ocean and wind energy to electricity do not suffer thermodynamic
power cycle (heat to work) losses although they do experience
other conversion ineffi ciencies in extracting energy from natural energy
fl ows that may also be relatively large and irreducible (chapters 2-7).
[1.2.1]
Some RE technologies can be deployed at the point of use (decentralized)
in rural and urban environments, whereas others are primarily
employed within large (centralized) energy networks. Though many
1.2 Summary of renewable energy resources
and potential
RE is any form of energy from solar, geophysical or biological sources
that is replenished by natural processes at a rate that equals or exceeds
its rate of use. RE is obtained from the continuing or repetitive fl ows
of energy occurring in the natural environment and includes resources
such as biomass, solar energy, geothermal heat, hydropower, tide and
waves, ocean thermal energy and wind energy. However, it is possible
to utilize biomass at a greater rate than it can grow or to draw heat
from a geothermal fi eld at a faster rate than heat fl ows can replenish
it. On the other hand, the rate of utilization of direct solar energy
has no bearing on the rate at which it reaches the Earth. Fossil fuels
(coal, oil, natural gas) do not fall under this defi nition, as they are not
replenished within a time frame that is short relative to their rate of
utilization. [1.2.1]
There is a multi-step process whereby primary energy is converted
into an energy carrier, and then into an energy service. RE technologies
are diverse and can serve the full range of energy service needs.
Various types of RE can supply electricity, thermal energy and mechanical
energy, as well as produce fuels that are able to satisfy multiple
Energy Carrier
Key to Figure
Useable Energy
Flow
Gaseous
Fuel
Heat Work
Liquid Fuel Solid Fuel Electricity
Conversion Type
Energy Services
Primary Energy
Source
Nuclear
Fuels
Geothermal
Bioenergy Energy
Thermal
Conversion
Heat-Based
Energy Services
Direct Heating &
Lighting Services
Electrical Energy
Services
Mechanical Energy
Services
Kinetic
Conversion
Fossil Fuels Direct
Solar Energy Wind Energy Hydro Energy Ocean Energy
Figure TS.1.6 | Illustrative paths of energy from source to service. All connected lines indicate possible energy pathways. The energy services delivered to the users can be provided
with differing amounts of end-use energy. This in turn can be provided with more or less primary energy from different sources, and with differing emissions of CO2 and other environmental
impacts. [Figure 1.16]
39
Summaries Technical Summary
RE technologies are technically mature and are being deployed at signifi
cant scale, others are in an earlier phase of technical maturity and
commercial deployment. [1.2.1]
The theoretical potential for RE exceeds current and projected global
energy demand by far, but the challenge is to capture and utilize a sizable
share of that potential to provide the desired energy services in a
cost-effective and environmentally sound manner. [1.2.2]
The global technical potential of RE sources will also not limit continued
market growth. A wide range of estimates are provided in the literature
but studies have consistently found that the total global technical
potential for RE is substantially higher than both current and projected
future global energy demand. The technical potential for solar energy is
the highest among the RE sources, but substantial technical potential
exists for all forms of RE. The absolute size of the global technical potential
for RE as a whole is unlikely to constrain RE deployment. [1.2.3]
Figure TS.1.7 shows that the technical potential6 exceeds by a considerable
margin the global electricity and heat demand, as well as the global
6 See Annex I for a complete defi nition of technical potential.
primary energy supply, in 2008. While the fi gure provides a perspective
for the reader to understand the relative sizes of the RE resources in the
context of current energy demand and supply, note that the technical
potentials are highly uncertain. Table A.1.1 in the Annex to Chapter 1
includes more detailed notes and explanations. [1.2.3]
RE can be integrated into all types of electricity systems from large,
interconnected continental-scale grids down to small autonomous
buildings. Whether for electricity, heating, cooling, gaseous fuels or
liquid fuels, RE integration is contextual, site specifi c and complex.
Partially dispatchable wind and solar energy can be more diffi cult to
integrate than fully dispatchable hydropower, bioenergy and geothermal
energy. As the penetration of partially dispatchable RE electricity
increases, maintaining system reliability becomes more challenging
and costly. A portfolio of solutions to minimize the risks and costs of
RE integration can include the development of complementary fl exible
generation, strengthening and extending network infrastructure
and interconnections, electricity demand that can respond in relation
to supply availability, energy storage technologies (including
reservoir-based hydropower), and modifi ed institutional arrangements
Global Electricity
Demand, 2008: 61 EJ
Global Primary Energy
Supply, 2008: 492 EJ
Global Heat
Demand, 2008: 164 EJ
0
10
100
1,000
10,000
100,000
Global Technical Potential [EJ/yr, log scale]
Direct Solar
Energy
Geothermal Biomass
Energy
Wind
Energy
Ocean
Energy
Electricity Heat Primary Energy
Geothermal Hydropower
Energy
49837
1575
500
50
312
10
580
85
331
7
52
50
1109
118
Max (in EJ/yr)
Min (in EJ/yr)
Range of Estimates of Global Technical Potentials
Range of Estimates
Summarized in Chapters 2-7
Maximum
Minimum
Figure TS.1.7 | Ranges of global technical potentials of RE sources derived from studies presented in Chapters 2 through 7. Biomass and solar are shown as primary energy due to
their multiple uses. Note that the fi gure is presented in logarithmic scale due to the wide range of assessed data. [Figure 1.17]
Notes: Technical potentials reported here represent total worldwide potentials for annual RE supply and do not deduct any potential that is already being utilized. Note that RE electricity
sources could also be used for heating applications, whereas biomass and solar resources are reported only in primary energy terms but could be used to meet various energy
service needs. Ranges are based on various methods and apply to different future years; consequently, the resulting ranges are not strictly comparable across technologies. For the data
behind the fi gure and additional notes that apply, see Table A.1.1 (as well as the underlying chapters).
40
Technical Summary Summaries
including regulatory and market mechanisms. As the penetration level
of RE increases, there is need for a mixture of inexpensive and effective
communications systems and technologies, as well as smart meters.
[1.2.4]
Energy services are the tasks performed using energy. A specifi c energy
service can be provided in many ways and may therefore be characterized
by high or low energy effi ciency, implying the release of relatively smaller
or larger amounts of CO2 (under a given energy mix). Reducing energy
needs at the energy services delivery stage through energy effi ciency is an
important means of reducing primary energy demand. This is particularly
important for RE sources since they usually have lower power densities
than fossil or nuclear fuels. Effi ciency measures are often the lowest-cost
option to reducing end-use energy demand. This report provides some
specifi c defi nitions for different dimensions of effi ciency. [1.2.5]
Energy savings resulting from effi ciency measures are not always fully
realized in practice. There may be a rebound effect in which some fraction
of the measure is offset because the lower total cost of energy (due
to less energy use) to perform a specifi c energy service may lead to
utilization of more energy services. It is estimated that the rebound
effect is probably limited by saturation effects to between 10 and
30% for home heating and vehicle use in Organisation for Economic
Co-operation and Development (OECD) countries, and is very small for
more effi cient appliances and water heating. An effi ciency measure
that is successful in lowering economy-wide energy demand, however,
lowers the price of energy as well, leading in turn to a decrease
in economy-wide energy costs and additional cost savings (lower
energy prices and less energy use). It is expected that the rebound
effect may be greater in developing countries and among poor consumers.
For climate change, the main concern with any rebound effect
is its infl uence on CO2 emissions. [1.2.5]
Carbon leakage may also reduce the effectiveness of carbon reduction
policies. If carbon reduction policies are not applied uniformly
across sectors and political jurisdictions, then it may be possible for
carbon emitting activities to move to a sector or country without such
policies. Recent research suggests, however, that estimates of carbon
leakage are too high. [1.2.5]
1.3 Meeting energy service needs and
current status
Global renewable energy fl ows from primary energy through carriers to
end uses and losses in 2008 are shown in Figure TS.1.8. [1.3.1]
Globally in 2008, around 56% of RE was used to supply heat in private
households and in the public and services sector. Essentially, this
refers to wood and charcoal, widely used in developing countries for
cooking. On the other hand, only a small amount of RE is used in the
transport sector. Electricity production accounts for 24% of the end-use
consumption. Biofuels contributed 2% of global road transport fuel supply
in 2008, and traditional biomass (17%), modern biomass (8%), solar
thermal and geothermal energy (2%) together fuelled 27% of the total
global demand for heat in 2008. [1.3.1]
While the resource is obviously large and could theoretically supply all
energy needs long into the future, the levelized cost of energy for many
RE technologies is currently higher than existing energy prices, though
in various settings RE is already economically competitive. Ranges of
recent levelized costs of energy for selected commercially available RE
technologies are wide, depending on a number of factors, including, but
not limited to, technology characteristics and size, regional variations in
cost and performance and differing discount rates (Figure TS.1.9). [1.3.2,
2.3, 2.7, 3.8, 4.8, 5.8, 6.7, 7.8, 10.5, Annex III]
The cost of most RE technologies has declined and additional expected
technical advances would result in further cost reductions. Such cost
reductions as well as monetizing the external cost of energy supply would
improve the relative competitiveness of RE. The same applies if market
prices increase due to other reasons. [1.3.2, 2.6, 2.7, 3.7, 3.8, 4.6, 4.7, 5.3,
5.7, 5.8, 6.6, 6.7, 7.7, 7.8, 10.5]
The contribution of RE to primary energy supply varies substantially by
country and region. The geographic distribution of RE manufacturing, use
and export is now being diversifi ed from the developed world to other
developing regions, notably Asia including China. In terms of installed
renewable power capacity, China now leads the world followed by the
USA, Germany, Spain and India. RE is more evenly distributed than fossil
fuels and there are countries or regions rich in specifi c RE resources. [1.3.3]
1.4 Opportunities, barriers, and issues
The major global energy challenges are securing energy supply to meet
growing demand, providing everybody with access to energy services
and curbing energy’s contribution to climate change. For developing
countries, especially the poorest, energy is needed to stimulate production,
income generation and social development, and to reduce
the serious health problems caused by the use of fuel wood, charcoal,
dung and agricultural waste. For industrialized countries, the primary
reasons to encourage RE include emission reductions to mitigate climate
change, secure energy supply concerns and employment creation.
RE can open opportunities for addressing these multiple environmental,
social and economic development dimensions, including adaptation to
climate change. [1.4, 1.4.1]
Some form of renewable resource is available everywhere in the world,
for example, solar radiation, wind, falling water, waves, tides and stored
ocean heat or heat from the Earth. Furthermore, technologies exist that
can harness these forms of energy. While the opportunities [1.4.1] seem
great, there are barriers [1.4.2] and issues [1.4.3] that slow the introduction
of RE into modern economies. [1.4]
41
Summaries Technical Summary
CSP 0.002 0.002
Primary Energy Supply
Hydro 11.6 Input
Energy 17.8
Output
Electricity
13.4
Output
Heat 0.4
Wind 0.8
0.01
0.04
0.003
0.4
PV 0.04
Tide&Wave 0.002
Combustible
Biomass &
Renewable
Wastes
50.3
Other
Sectors 43.3
Geothermal 0.4
Solarthermal 0.5
Electricity-, CHP- and Heat Plants
Transport 2.1
Industry 13.5
Losses 4.6
Total Final Consumption and Losses
0.01
0.002
0.2
1.9
7.75
7.6
5.6
0.6
0.2
0.2
0.2
4.0
5.2
0.8
0.2
34.9
11.6
33.7 Residential
0.65 Commercial & Public Services
0.3 Agriculture & Forestry
0.2 Non-Specified
Unaccounted traditional
use of biomass
Figure TS.1.8 | Global energy fl ows (EJ in 2008) from primary RE through carriers to end-uses and losses (based on International Energy Agency (IEA) data). ‘Other sectors’ include
agriculture, commercial and residential buildings, public services and non-specifi ed other sectors. ‘Transport sector’ includes road transport, international aviation and international
marine bunkers. [Figure 1.18]
Opportunities can be defi ned as circumstances for action with the
attribute of a chance character. In the policy context that could be the
anticipation of additional benefi ts that may go along with the deployment
of RE but that are not intentionally targeted. These include four
major opportunity areas: social and economic development; energy
access; energy security; and climate change mitigation and the reduction
of environmental and health impacts. [1.4.1, 9.2–9.4]
Globally, per capita incomes as well as broader indicators such as
the Human Development Index (HDI) are positively correlated with
per capita energy use, and economic growth can be identifi ed as the
most relevant factor behind increasing energy consumption in the last
decades. Economic development has been associated with a shift from
direct combustion of fuels to higher quality electricity. [1.4.1, 9.3.1]
Particularly for developing countries, the link between social and economic
development and the need for modern energy services is evident.
Access to clean and reliable energy constitutes an important prerequisite
for fundamental determinants of human development, contributing,
inter alia, to economic activity, income generation, poverty alleviation,
health, education and gender equality. Due to their decentralized
nature, RE technologies can play an important role in fostering rural
development. The creation of (new) employment opportunities is seen
as a positive long-term effect of RE in both developed and developing
countries. [1.4.1, 9.3.1.4, 11.3.4]
Access to modern energy services can be enhanced by RE. In 2008, 1.4
billion people around the world lacked electricity, some 85% of them in
rural areas, and the number of people relying on the traditional use of
biomass for cooking is estimated to be 2.7 billion. In particular, reliance
on RE in rural applications, use of locally produced bioenergy to produce
electricity, and access to clean cooking facilities will contribute to
attainment of universal access to modern energy services. The transition
to modern energy access is referred to as moving up the energy ladder
and implies a progression from traditional to more modern devices/fuels
that are more environmentally benign and have fewer negative health
impacts. This transition is infl uenced by income level. [1.4.1, 9.3.2]
Energy security concerns that may be characterized as availability and distribution
of resources, as well as variability and reliability of energy supply,
may also be enhanced by the deployment of RE. As RE technologies help
to diversify the portfolio of energy sources and to reduce the economy’s
Le
Io >« «
42
Technical Summary Summaries
Range of Oil and Gas
Based Heating Cost
Range of Non-Renewable
Electricity Cost
Range of Gasoline
and Diesel Cost
[UScent2005 /kWh]
0 10 20 30 40 50 60 70 80 90 100
[USD2005 /GJ]
Biofuels
Geothermal Heat
Solar Thermal Heat
Biomass Heat
Wind Electricity
Ocean Electricity
Hydropower
Geothermal Electricity
Solar Electricity
Biomass Electricity
0 25 50 75 100 125 150 175 200 225 250 275
Non-Renewables
Heat
Transport Fuels
Electricity
Lower Bound
Upper Bound
Medium Values
Biofuels:
1. Corn ethanol
2. Soy biodiesel
3. Wheat ethanol
4. Sugarcane ethanol
5. Palm oil biodiesel
Biomass Heat:
1. Municipal solid waste based CHP
2. Anaerobic digestion based CHP
3. Steam turbine CHP
4. Domestic pellet heating system
Solar Thermal Heat:
1. Domestic hot water systems in China
2. Water and space heating
Geothermal Heat:
1. Greenhouses
2. Uncovered aquaculture ponds
3. District heating
4. Geothermal heat pumps
5. Geothermal building heating
Biomass:
1. Cofiring
2. Small scale combined heat and power, CHP
(Gasification internal combustion engine)
3. Direct dedicated stoker & CHP
4. Small scale CHP (steam turbine)
5. Small scale CHP (organic Rankine cycle)
Solar Electricity:
1. Concentrating solar power
2. Utility-scale PV (1-axis and fixed tilt)
3. Commercial rooftop PV
4. Residential rooftop PV
Geothermal Electricity:
1. Condensing flash plant
2. Binary cycle plant
Hydropower:
1. All types
Ocean Electricity:
1. Tidal barrage
Wind Electricity:
1. Onshore
2. Offshore
Electricity Heat Transport Fuels
Notes: Medium values are shown for the following subcategories, sorted in the order as they appear in the respective ranges (from left to right):
The lower range of the levelized cost of energy for each RE technology is based on a combination of the most favourable input-values, whereas the upper range is based on a
combination of the least favourable input values. Reference ranges in the figure background for non-renewable electricity options are indicative of the levelized cost of centralized
non-renewable electricity generation. Reference ranges for heat are indicative of recent costs for oil and gas based heat supply options. Reference ranges for transport fuels are
based on recent crude oil spot prices of USD 40 to 130/barrel and corresponding diesel and gasoline costs, excluding taxes.
■
■■ ■
I I I
43
Summaries Technical Summary
Figure TS.1.9 | (Preceding page) Range in recent levelized cost of energy for selected commercially available RE technologies in comparison to recent non-renewable energy costs.
Technology subcategories and discount rates were aggregated for this fi gure. For related fi gures with less or no such aggregation, see [1.3.2, 10.5, Annex III]. Additional information
concerning the cost of non-renewable energy supply options is given in [10.5]. [Figure 10.28]
Figure TS.1.10 | Illustrative system for energy production and use illustrating the role of RE along with other production options. A systemic approach is needed to conduct lifecycle
assessments. [Figure 1.22]
Energy Conversion
Biomass for Energy
Recovery & Extraction
Nuclear
Renewable
Fossil
Raw Material
Movement
Electricity
Distribution
Liquid Fuel
Transportation
Product
Conversion
Biomass Co-Product Co-Product
Residental
Commercial
Electric Transportation
Fuel Combustion
Gasoline/Ethanol
Bunker Fuel
Jet Fuel
Transportation
Productivity
Transportation
Productivity
Economic
Productivity
Diesel Fuel
Electricity Consumption
CO2
GHG
GHG
GHG GHG
GHG
GHG
GHG
GHG
Agriculture,
Forestry, Residues
vulnerability to price volatility and redirect foreign exchange fl ows away
from energy imports, they reduce social inequities in energy supply. Current
energy supplies are dominated by fossil fuels (petroleum and natural gas)
whose prices have been volatile with signifi cant implications for social,
economic and environmental sustainability in the past decades, especially
for developing countries and countries with high shares of imported fuels.
[1.4.1, 9.2.2, 9.3.3, 9.4.3]
Climate change mitigation is one of the key driving forces behind a growing
demand for RE technologies. In addition to reducing GHG emissions, RE
technologies can also offer benefi ts with respect to air pollution and health
compared to fossil fuels. However, to evaluate the overall burden from the
energy system on the environment and society, and to identify potential
trade-offs and synergies, environmental impacts apart from GHG emissions
and categories have to be taken into account as well. The resource may
also be affected by climate change. Lifecycle assessments facilitate a quantitative
comparison of ‘cradle to grave’ emissions across different energy
technologies. Figure TS.1.10 illustrates the lifecycle structure for CO2 emission
analysis, and qualitatively indicates the relative GHG implications for
RE, nuclear power and fossil fuels. [1.4.1, 9.2.2, 9.3.4, 11.3.1]
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44
Technical Summary Summaries
Informational and awareness barriers include defi cient data about natural
resources, often due to site-specifi city (e.g., local wind regimes), lack
of skilled human resources (capacity) especially in rural areas of developing
countries as well as the lack of public and institutional awareness.
Socio-cultural barriers are intrinsically linked to societal and personal
values and norms that affect the perception and acceptance of RE and
may be slow to change. Institutional and policy barriers include existing
industry, infrastructure and energy market regulation. Despite liberalization
of energy markets in several countries in the 1990s, current industry
structures are still highly concentrated and regulations governing energy
businesses in many countries are still designed around monopoly or
near-monopoly providers. Technical regulations and standards have
evolved under the assumption that energy systems are large and centralized,
and of high power density and/or high voltage. Intellectual
property rights, tariffs in international trade and lack of allocation of
government fi nancial support may constitute further barriers. [1.4.2]
Issues are not readily amenable to policies and programmes. An issue is
that the resource may be too small to be useful at a particular location
or for a particular purpose. Some renewable resources such as wind and
solar energy are variable and may not always be available for dispatch
when needed. Furthermore, the energy density of many renewable
sources is relatively low, so that their power levels may be insuffi cient
on their own for some purposes such as very large-scale industrial facilities.
[1.4.3]
1.5 Role of policy, research and
development, deployment and
implementation strategies
An increasing number and variety of RE policies—motivated by a variety
of factors—have driven escalated growth in RE technologies in recent
years. For policymakers wishing to support the development and deployment
of RE technologies for climate change mitigation goals, it is critical
to consider the potential of RE to reduce emissions from a lifecycle perspective,
as addressed in each technology chapter of this report. Various
policies have been designed to address every stage of the development
chain involving research and development (R&D), testing, deployment,
commercialization, market preparation, market penetration, maintenance
and monitoring, as well as integration into the existing system.
[1.4.1, 1.4.2, 9.3.4, 11.1.1, 11.2, 11.4, 11.5]
Two key market failures are typically addressed: 1) the external cost of
GHG emissions are not priced at an appropriate level; and 2) deployment
of low-carbon technologies such as RE create benefi ts to society
beyond those captured by the innovator, leading to under-investment in
such efforts. [1.4, 1.5, 11.1, 11.4]
Policy- and decision-makers approach the market in a variety of ways.
No globally-agreed list of RE policy options or groupings exists. For
Traditional biomass use results in health impacts from the high concentrations
of particulate matter and carbon monoxide, among other
pollutants. In this context, non-combustion-based RE power generation
technologies have the potential to signifi cantly reduce local and
regional air pollution and lower associated health impacts compared
to fossil-based power generation. Improving traditional biomass use
can reduce negative sustainable development (SD) impacts, including
local and indoor air pollution, GHG emissions, deforestation and forest
degradation. [1.4.1, 2.5.4, 9.3.4, 9.3.4, 9.4.2]
Impacts on water resources from energy systems strongly depend on
technology choice and local conditions. Electricity production with
wind and solar PV, for example, requires very little water compared
to thermal conversion technologies, and has no impacts on water
or air quality. Limited water availability for cooling thermal power
plants decreases their effi ciency, which can affect plants operating
on coal, biomass, gas, nuclear and concentrating solar power. There
have been signifi cant power reductions from nuclear and coal plants
during drought conditions in the USA and France in recent years.
Surface-mined coal in particular produces major alterations of land;
coal mines can create acid mine drainage and the storage of coal
ash can contaminate surface and ground waters. Oil production and
transportation have led to signifi cant land and water spills. Most
renewable technologies produce lower conventional air and water
pollutants than fossil fuels, but may require large amounts of land
as, for example, reservoir-based hydropower, wind and biofuels. Since
a degree of climate change is now inevitable, adaptation to climate
change is also an essential component of sustainable development.
[1.4.1, 9.3.4]
Barriers are defi ned in AR4 as “any obstacle to reaching a goal, adaptation
or mitigation potential that can be overcome or attenuated by
a policy programme or measure”. The various barriers to RE use can
be categorized as market failures and economic barriers, information
and awareness barriers, socio-cultural barriers and institutional
and policy barriers. Policies and fi nancing mechanisms to overcome
those barriers are extensively assessed in Chapter 11. When a barrier
is particularly pertinent to a specifi c technology, it is examined in
the appropriate ‘technology’ chapters of this report [Chapters 2–7].
A summary of barriers and potential policy instruments to overcome
these barriers is shown in Table 1.5 of Chapter 1. Market failures are
often due to external effects. These arise from a human activity, when
agents responsible for the activity do not take full account of the activity’s
impact on others. Another market failure is rent appropriation by
monopolistic entities. In the case of RE deployment, these market failures
may appear as underinvestment in invention and innovation in
RE technologies, un-priced environmental impacts and risks of energy
use as well as the occurrence of monopoly (one seller) or monopsony
(one buyer) powers in energy markets. Other economic barriers
include up-front investment cost and fi nancial risks, the latter sometimes
due to immaturity of the technology. [1.4.2, 1.5, 11.4]
45
Summaries Technical Summary
the purpose of simplifi cation, R&D and deployment policies have been
organized within the following categories in this report: [1.5.1, 11.5]
• Fiscal incentive: actors (individuals, households, companies) are
granted a reduction of their contribution to the public treasury via
income or other taxes;
• Public fi nance: public support for which a fi nancial return is expected
(loans, equity) or fi nancial liability is incurred (guarantee);
and
• Regulation: rule to guide or control conduct of those to whom it
applies.
R&D, innovation, diffusion and deployment of new low-carbon technologies
create benefi ts to society beyond those captured by the innovator,
resulting in under-investment in such efforts. Thus, government R&D
can play an important role in advancing RE technologies. Public R&D
investments are most effective when complemented by other policy
instruments, particularly RE deployment policies that simultaneously
enhance demand for new RE technologies. [1.5.1, 11.5.2]
Some policy elements have been shown to be more effective and
effi cient in rapidly increasing RE deployment, but there is no one-sizefi
ts-all policy. Experience shows that different policies or combinations
of policies can be more effective and effi cient depending on factors
such as the level of technological maturity, affordable capital, ease
of integration into the existing system and the local and national RE
resource base:
• Several studies have concluded that some feed-in tariffs have been
effective and effi cient at promoting RE electricity, mainly due to
the combination of long-term fi xed price or premium payments,
network connections, and guaranteed purchase of all RE electricity
generated. Quota policies can be effective and effi cient if designed
to reduce risk; for example, with long-term contracts.
• An increasing number of governments are adopting fi scal incentives
for RE heating and cooling. Obligations to use RE heat are
gaining attention for their potential to encourage growth independent
of public fi nancial support.
• In the transportation sector, RE fuel mandates or blending requirements
are key drivers in the development of most modern biofuel
industries. Other policies include direct government payments or
tax reductions. Policies have infl uenced the development of an
international biofuel and pellet trade.
One important challenge will be fi nding a way for RE and carbon-pricing
policies to interact such that they take advantage of synergies rather
than tradeoffs. In the long-term, support for technological learning in
RE can help reduce costs of mitigation, and putting a price on carbon
can increase the competitiveness of RE. [1.5.1, 11.1, 11.4, 11.5.7]
RE technologies can play a greater role if they are implemented in
conjunction with ‘enabling’ policies. A favourable, or ‘enabling’, environment
for RE can be created by addressing the possible interactions
of a given policy with other RE policies as well as with other non-RE
policies and the existence of an ‘enabling’ environment can increase the
effi ciency and effectiveness of policies to promote RE. Since all forms of
RE capture and production involve spatial considerations, policies need
to consider land use, employment, transportation, agricultural, water,
food security and trade concerns, existing infrastructure and other sectoral
specifi cs. Government policies that complement each other are
more likely to be successful. [1.5.2, 11.6]
Advancing RE technologies in the electric power sector, for example,
will require policies to address their integration into transmission and
distribution systems both technically [Chapter 8] and institutionally
[Chapter 11]. The grid must be able to handle both traditional, often
more central, supply as well as modern RE supply, which is often variable
and distributed. [1.5.2, 11.6.5]
In the transport sector, infrastructure needs for biofuels, recharging
hydrogen, battery or hybrid electric vehicles that are ‘fuelled’ by the
electric grid or from off-grid renewable electrical production need to
be addressed.
If decision makers intend to increase the share of RE and, at the same
time, to meet ambitious climate mitigation targets, then long-standing
commitments and fl exibility to learn from experience will be critical. To
achieve international GHG concentration stabilization levels that incorporate
high shares of RE, a structural shift in today’s energy systems
will be required over the next few decades. The available time span is
restricted to a few decades and RE must develop and integrate into a
system constructed in the context of an existing energy structure that
is very different from what might be required under higher-penetration
RE futures. [1.5.3, 11.7]
A structural shift towards a world energy system that is mainly based
on RE might begin with a prominent role for energy effi ciency in combination
with RE. Additional policies are required that extend beyond
R&D to support technology deployment; the creation of an enabling
environment that includes education and awareness raising; and the
systematic development of integrative policies with broader sectors,
including agriculture, transportation, water management and urban
planning. The appropriate and reliable mix of instruments is even more
important where energy infrastructure is not yet developed and energy
demand is expected to increase signifi cantly in the future. [1.2.5, 1.5.3,
11.7, 11.6, 11.7]
46
Technical Summary Summaries
2. Bioenergy
2.1 Introduction to biomass and bioenergy
Bioenergy is embedded in complex ways in global biomass systems for
food, fodder and fi bre production and for forest products as well as in
wastes and residue management. Perhaps most importantly, bioenergy
plays an intimate and critical role in the daily livelihoods of billions of
people in developing countries. Figure TS.2.1 shows the types of biomass
used for bioenergy in developing and developed countries. Expanding
bioenergy production signifi cantly will require sophisticated land and
water use management; global feedstock productivity increases for
food, fodder, fi bre, forest products and energy; substantial conversion
technology improvements; and a refi ned understanding of the complex
social, energy and environmental interactions associated with bioenergy
production and use.
In 2008, biomass provided about 10% (50.3 EJ/yr) of the global primary
energy supply (see Table TS.2.1). Major biomass uses fall into two broad
categories:
• Low-effi ciency traditional biomass7 such as wood, straws, dung and
other manures are used for cooking, lighting and space heating,
generally by the poorer populations in developing countries. This
biomass is mostly combusted, creating serious negative impacts
on health and living conditions. Increasingly, charcoal is becoming
secondary energy carrier in rural areas with opportunities to create
productive chains. As an indicator of the magnitude of traditional
biomass use, Figure TS.2.1(b) illustrates that the global primary
energy supply from traditional biomass parallels the world’s industrial
wood production. [2.5.4, 2.3, 2.3.2.2, 2.4.2, 2.5.7]
• High-effi ciency modern bioenergy uses more convenient solids,
liquids and gases as secondary energy carriers to generate heat,
electricity, combined heat and power (CHP), and transport fuels for
various sectors. Liquid biofuels include ethanol and biodiesel for global
road transport and some industrial uses. Biomass derived gases, primarily
methane, from anaerobic digestion of agricultural residues and
municipal solid waste (MSW) treatment are used to generate electricity,
heat or both. The most important contribution to these energy services
is based on solids, such as chips, pellets, recovered wood previously
used and others. Heating includes space and hot water heating such as
in district heating systems. The estimated total primary biomass supply
for modern bioenergy is 11.3 EJ/yr and the secondary energy delivered
to end-use consumers is roughly 6.6 EJ/yr. [2.3.2, 2.4, 2.4.6, 2.6.2]
Additionally, the industry sector, such as the pulp and paper, forestry, and
food industries, consumes approximately 7.7 EJ of biomass annually, primarily
as a source for industrial process steam. [2.7.2, 8.3.4]
2.2 Bioenergy resource potential
The inherent complexity of biomass resources makes the assessment of their
combined technical potential controversial and diffi cult to characterize.
Estimates in the literature range from zero technical potential (no biomass
available for energy production) to a maximum theoretical potential of
7 Traditional biomass is defi ned as biomass consumption in the residential sector in
developing countries and refers to the often unsustainable use of wood, charcoal,
agricultural residues and animal dung for cooking and heating. All other biomass
use is defi ned as modern biomass; this report further differentiates between highly
effi cient modern bioenergy and industrial bioenergy applications with varying
degrees of effi ciency. [Annex I] The renewability and sustainability of biomass use is
primarily discussed in Sections 2.5.4 and 2.5.5, respectively (see also Section 1.2.1
and Annex I).
Figure TS.2.1 | (a) Shares of global primary biomass sources for energy; and (b) fuelwood
used in developing countries parallels world industrial roundwood1 production levels.
[Figure 2.1]
Note: 1. Roundwood products are saw logs and veneer logs for the forest products
industry and wood chips that are used for making pulpwood used in paper, newsprint and
Kraft paper. In 2009, refl ecting the downturn in the economy, there was a decline to 3.25
(total) and 1.25 (industrial) billion m3.
Fuelwood
67%
Charcoal
7%
Wood Industry Residues 5%
Forest Residues 1%
Black Liquor 1%
Recovered Wood 6%
Agriculture
10%
MSW and Landfill Gas 3%
Animal
By-Products 3%
Agricultural
By-Products
4%
Energy Crops
3%
Fuelwood
Indoor Heating, Cooking and Lighting in
Developing Countries (95%)
World Industrial Roundwood
For Products
4.0
3.0
2.0
1.0
0.0 1961
1963
1967
1971
1975
1978
1983
1987
1991
1995
1999
2003
2007
[Billion m3]
(a)
(b)
-
47
Summaries Technical Summary
Table TS.2.1 | Examples of traditional and select modern biomass energy fl ows in 2008; see Table 2.1 for notes on specifi c fl ows and accounting challenges. [Table 2.1]
Type
Approximate Primary Energy
(EJ/yr)
Approximate Average
Effi ciency (%)
Approximate Secondary
Energy (EJ/yr)
Traditional Biomass
Accounted for in IEA energy balance statistics 30.7
10–20
3–6
Estimated for informal sectors (e.g., charcoal) [2.1] 6–12 0.6–2.4
Total Traditional Biomass 37–43 3.6–8.4
Modern Bioenergy
Electricity and CHP from biomass, MSW, and biogas 4.0 32 1.3
Heat in residential, public/commercial buildings from solid biomass and biogas 4.2 80 3.4
Road Transport Fuels (ethanol and biodiesel) 3.1 60 1.9
Total Modern Bioenergy 11.3 58 6.6
about 1,500 EJ from global modelling efforts. Figure TS.2.2 presents a summary
of technical potentials found in major studies, including data from
the scenario analysis of Chapter 10. To put biomass technical potential for
energy in perspective, global biomass used for energy currently amounts
to approximately 50 EJ/yr and all harvested biomass used for food, fodder
and fi bre, when expressed in a caloric equivalent, contains about 219 EJ/
yr (2000 data); nearly the entire current global biomass harvest would be
required to achieve a 150 EJ/yr deployment level of bioenergy by 2050.
[2.2.1]
An assessment of technical potential based on an analysis of the literature
available in 2007 and additional modelling studies arrived at the conclusion
that the upper bound of the technical potential in 2050 could amount to
about 500 EJ, shown in the stacked bar of Figure TS.2.2. The study assumes
policy frameworks that secure good governance of land use and major
improvements in agricultural management and takes into account water
limitations, biodiversity protection, soil degradation and competition
with food. Residues originating from forestry, agriculture and organic
wastes (including the organic fraction of MSW, dung, process residues,
etc.) are estimated to amount to 40 to 170 EJ/yr, with a mean estimate
of around 100 EJ/yr. This part of the technical potential is relatively certain,
but competing applications may push net availability for energy
applications to the lower end of the range. Surplus forestry products
other than from forestry residues have an additional technical potential
2008 Global TPES
2000 Total Biomass
Harvested for Food/
Fodder/Fibre Caloric Value
2008 Global TPES
from Biomass
2050 Global
TPES
AR4, 2007
Technical
Potential
2050 Global
Biomass
for Energy
AR4, 2007
Chapter 2
Review
Potential Deployment
Levels
Literature Technical
Potentials Range:
0 to 1500 EJ
(Theoretical)
Land Use 5
Million km2
Land Use 3
Million km2
Plant
Productivity
Improvement
Technical Potential
Based on 2008
Model and Literature
Assessment
Deployment Levels
Chapter 10
Scenario Assessment
440-600
ppm
<440 ppm
300
265
100
300
150
190
Maximum
Minimum
118
80
20 25
25th
Median
75th
Marginal/
Degraded Land
Surplus
Good Land
Surplus Forestry
Forestry and Agriculture
Residues; Organic Wastes
1000
750
500
250
50
Global Primary Energy Supply [EJ/yr]
2050 Projections
Figure TS.2.2 | A summary of major 2050 projections of global terrestrial biomass technical potential for energy and possible deployment levels compared to 2008 global total primary
energy and biomass supply as well as the equivalent energy of world total biomass harvest. [Figure 2.25]
l
7
- l
48
Technical Summary Summaries
of about 60 to 100 EJ/yr. A lower estimate for energy crop production
on possible surplus, good quality agricultural and pasture lands is 120
EJ/yr. The potential contribution of water-scarce, marginal and degraded
lands could amount to up to an additional 70 EJ/yr. This would comprise
a large area where water scarcity imposes limitations and soil degradation
is more severe. Assuming strong learning in agricultural technology
for improvements in agricultural and livestock management would add
140 EJ/yr. The three categories added together lead to a technical potential
from this analysis of up to about 500 EJ/yr (Figure TS 2.2).
Developing this technical potential would require major policy efforts,
therefore, actual deployment would likely be lower and the biomass
resource base will be largely constrained to a share of the biomass
residues and organic wastes, some cultivation of bioenergy crops on
marginal and degraded lands, and some regions where biomass is a
cheaper energy supply option compared to the main reference options
(e.g., sugarcane-based ethanol production). [2.2.2, 2.2.5, 2.8.3]
The expert review conclusions based on available scientifi c literature
are: [2.2.2–2.2.4]
• Important factors include (1) population and economic/technology
development, food, fodder and fi bre demand (including diets),
and developments in agriculture and forestry; (2) climate change
impacts on future land use including its adaptation capability; and
(3) the extent of land degradation, water scarcity and biodiversity
and nature conservation requirements.
• Residue fl ows in agriculture and forestry and unused (or extensively
used thus becoming marginal/degraded) agricultural land are important
sources for expansion of biomass production for energy, both in
the near- and longer term. Biodiversity-induced limitations and the
need to ensure maintenance of healthy ecosystems and avoidance
of soil degradation set limits on residue extraction in agriculture and
forestry.
• The cultivation of suitable plants (e.g., perennial crops or woody
species) can allow for higher technical potentials by making it possible
to produce bioenergy on lands less suited for conventional food
crops—also when considering that the cultivation of conventional
crops on such lands can lead to soil carbon emissions.
• Multi-functional land use systems with bioenergy production integrated
into agriculture and forestry systems could contribute to
biodiversity conservation and help restore/maintain soil productivity
and healthy ecosystems.
• Regions experiencing water scarcity may have limited production.
The possibility that conversion of lands to biomass plantations
reduces downstream water availability needs to be considered. The
use of suitable drought-tolerant energy crops can help adaptation in
water-scarce situations. Assessments of biomass resource potentials
need to more carefully consider constraints and opportunities in
relation to water availability and competing uses.
Following the restrictions outlined above, the expert review concludes
that potential deployment levels of biomass for energy by 2050 could
be in the range of 100 to 300 EJ. However, there are large uncertainties
in this potential, such as market and policy conditions, and there
is strong dependence on the rate of improvements in the agricultural
sector for food, fodder and fi bre production and forest products. One
example from the literature suggests that bioenergy can expand from
around 100 EJ/yr in 2020 to 130 EJ/yr in 2030, and could reach 184 EJ/
yr in 2050. [2.2.1, 2.2.2, 2.2.5]
To reach the upper range of the expert review deployment level of 300
EJ/yr (shown in Figure TS.2.2) would require major policy efforts, especially
targeting improvements and effi ciency increases in the agricultural
sector and good governance, such as zoning, of land use.
2.3 Bioenergy technology and applications
Commercial bioenergy technology applications include heat production—
with scales ranging from home cooking with stoves to large
district heating systems; power generation from biomass via combustion,
CHP, or co-fi ring of biomass and fossil fuels; and fi rst-generation
liquid biofuels from oil crops (biodiesel) and sugar and starch crops
(ethanol) as shown in the solid lines of Figure TS.2.3. The fi gure also
illustrates developing feedstocks (e.g., aquatic biomass), conversion
routes and products.8 [2.3, 2.6, 2.7, 2.8]
Section 2.3 addresses key issues related to biomass production and the
logistics of supplying feedstocks to the users (individuals for traditional
and modern biomass, fi rms that use and produce secondary energy
products or, increasingly, an informal sector of production and distribution
of charcoal). The conversion technologies that transform biomass to
convenient secondary energy carriers use thermochemical, chemical or
biochemical processes, and are summarized in Sections 2.3.1–2.3.3 and
2.6.1–2.6.3. Chapter 8 addresses energy product integration with the
existing and evolving energy systems. [2.3.1–2.3.3, 2.6.1–2.6.3]
2.4 Global and regional status of markets
and industry deployment
A review of biomass markets and policy shows that bioenergy has seen
rapid developments in recent years such as the use of modern biomass
for liquid and gaseous energy carriers (an increase of 37% from 2006
to 2009). Projections from the IEA, among others, count on biomass
delivering a substantial increase in the share of RE, driven in some cases
by national targets. International trade in biomass and biofuels has
8 Biofuels produced via new processes are also called advanced or next-generation
biofuels, e.g. lignocellulosic.
49
Summaries Technical Summary
also become much more important over recent years, with roughly 6%
(reaching levels of up to 9% in 2008) of biofuels (ethanol and biodiesel
only) traded internationally and one-third of all pellet production for
energy use in 2009. The latter facilitated both increased utilization of
biomass in regions where supplies were constrained as well as mobilized
resources from areas lacking demand. Nevertheless, many barriers
remain in developing effective commodity trading of biomass and biofuels
that, at the same time, meets sustainability criteria. [2.4.1, 2.4.4]
In many countries, the policy context for bioenergy and, in particular,
biofuels, has changed rapidly and dramatically in recent years. The
debate surrounding biomass in the food versus fuel competition, and
growing concerns about other confl icts, have resulted in a strong push
for the development and implementation of sustainability criteria and
frameworks as well as changes in target levels and schedules for bioenergy
and biofuels. Furthermore, support for advanced biorefi nery and
Figure TS.2.3 | Schematic view of the variety of commercial (solid lines) and developing bioenergy routes (dotted lines) from biomass feedstocks through thermochemical, chemical,
biochemical and biological conversion routes to heat, power, CHP and liquid or gaseous fuels. Commercial products are marked with an asterisk. [Figure 2.2, 2.1.1]
Notes: 1. Parts of each feedstock could be used in other routes. 2. Each route can also make coproducts. 3. Biomass upgrading includes densifi cation processes (such as pelletization,
pyrolysis, torrefaction, etc.). 4. Anaerobic digestion processes to various gases which can be upgraded to biomethane, essentially methane, the major component of natural gas. 5.
Could be other thermal processing routes such as hydrothermal, liquefaction, etc. Other chemical routes include aqueous phase reforming. DME=dimethyl ether.
Feedstock1
Oil Crops
(Rape, Sunflower, Soya etc.)
Waste Oils, Animal Fats
Sugar and Starch Crops
Lignocellulosic Biomass
(Wood, Straw, Energy Crop,
MSW, etc.)
Biodegradable MSW,
Sewage Sludge, Manure, Wet
Wastes (Farm and Food Wastes)
Macroalgae
Photosynthetic
Microorganisms,
e.g. Microalgae and Bacteria
Heat and/or Power*
Gaseous Fuels
Liquid Fuels
Biodiesel*
Ethanol*, Butanols,
Hydrocarbons
Syndiesel / Renewable
Diesel*
Methanol, Ethanol,
Alcohols
Other Fuels and Fuel
Additives
DME, Hydrogen
Biomethane*
Conversion Routes2
(Biomass Upgrading3) +
Combustion
Transesterification
or Hydrogenation
(Hydrolysis) + Fermentation*
or Microbial Processing
Gasification
(+ Secondary Process)4
Pyrolysis5
(+ Secondary Process)
Anaerobic Digestion
(+ Biogas Upgrading)
Other Biological /
Chemical Routes
Bio-Photochemical Routes
next-generation biofuel9 options is driving bioenergy to be more sustainable.
[2.4.5]
Persistent and stable policy support has been a key factor in building
biomass production capacity and markets, requiring infrastructure and
conversion capacity that gets more competitive over time. These conditions
have led to the success of the Brazilian programme to the point
that ethanol production costs are now lower than those for gasoline.
Sugarcane fi bre bagasse generates heat and electricity, with an energy
portfolio mix that is substantially based on RE and that minimizes foreign
oil imports. Sweden and Finland also have shown signifi cant growth
in renewable electricity and in management of integrated resources,
which steadily resulted in innovations such as industrial symbiosis of
collocated industries. The USA has been able to quickly ramp up production
with alignment of national and sub-national policies for power
in the 1980s to 1990s and for biofuels in the 1990s to the present, as
9 Biofuels produced by new processes (e.g. from lignocellulosic biomass) are also
called advanced biofuels.
'
t ---
tlijE.-i
±'; i{ i
l
'
r I
!e
TTI L
50
Technical Summary Summaries
petroleum prices and instability in key producing countries increased
and to foster rural development and a secure energy supply. [2.4.5]
Countries differ in their priorities, approaches, technology choices and
support schemes for further developing bioenergy. Market and policy
complexities emerge when countries seek to balance specifi c priorities
in agriculture and land use, energy policy and security, rural development
and environmental protection while considering their unique
stage of development, geographic access to resources, and availability
and costs of resources. [2.4.5, 2.4.7]
One overall trend is that as policies surrounding bioenergy and biofuels
become more holistic, sustainability becomes a stronger criterion at
the starting point. This is true for the EU, the USA and China, but also
for many developing countries such as Mozambique and Tanzania. This
is a positive development, but by no means settled. The registered 70
initiatives worldwide by 2009 to develop and implement sustainability
frameworks and certifi cation systems for bioenergy and biofuels, as well
as agriculture and forestry, can lead to a fragmentation of efforts. The
need for harmonization and international and multilateral collaboration
and dialogue are widely stressed. [2.4.6, 2.4.7]
2.5 Environmental and social impacts
Bioenergy production has complex interactions with other social and
environmental systems. Concerns—ranging from health and poverty to
biodiversity and water scarcity and quality—vary depending upon many
factors including local conditions, technology and feedstock choices,
sustainability criteria design, and the design and implementation of specifi
c projects. Perhaps most important is the overall management and
governance of land use when biomass is produced for energy purposes
on top of meeting food and other demands from agricultural, livestock
and fi bre production. [2.5]
Direct land use change (dLUC) occurs when bioenergy feedstock production
modifi es an existing land use, resulting in a change in above- and
below-ground carbon stocks. Indirect LUC (iLUC) occurs when a change
in production level of an agricultural product (i.e., a reduction in food
or feed production induced by agricultural land conversion to produce
a bioenergy feedstock) leads to a market-mediated shift in land management
activities (i.e., dLUC) outside the region of primary production
expansion. iLUC is not directly observable and is complex to model and
diffi cult to attribute to a single cause as multiple actors, industry, countries,
policies and markets dynamically interact. [2.5.3, 9.3.4.1]
In cases where increases in land use due to biomass production for
bioenergy are accompanied by improvements in agricultural management
(e.g., intensifi cation of perennial crop and livestock production
in degraded lands), undesirable (i)LUC effects can be avoided. If left
unmanaged, confl icts can emerge. The overall performance of bioenergy
production systems is therefore interlinked with management of land
and water resources use. Trade-offs between those dimensions exist and
need to be managed through appropriate strategies and decision making
(Figure TS.2.4). [2.5.8]
Most bioenergy systems can contribute to climate change mitigation if
they replace traditional fossil fuel use and if the bioenergy production
emissions are kept low. High nitrous oxide emissions from feedstock
production and use of fossil fuels (especially coal) in the biomass conversion
process can strongly impact the GHG savings. Options to lower
GHG emissions include best practices in fertilizer management, process
integration to minimize losses, utilization of surplus heat, and use of
biomass or other low-carbon energy sources as process fuel. However,
the displacement effi ciency (GHG emissions relative to carbon in biomass)
can be low when additional biomass feedstock is used for process
energy in the conversion process - unless the displaced energy is generated
from coal. If the biomass feedstock can produce both liquid fuel
and electricity, the displacement effi ciency can be high. [2.5.1–2.5.3]
There are different methods to evaluate the GHG emissions of key
fi rst- and second-generation biofuel options. Well-managed bioenergy
projects can reduce GHG emissions signifi cantly compared to fossil
alternatives, especially for lignocellulosic biomass used in power generation
and heat, and when that feedstock is commercially available.
Advantages can be achieved by making appropriate use of agricultural
residues and organic wastes, principally animal residues. Most current
biofuel production systems have signifi cant reductions in GHG emissions
relative to the fossil fuels displaced, if no iLUC effects are considered.
Figure TS.2.5 shows a snapshot of the ranges of lifecycle GHG emissions
associated with various energy generation technologies from modern
biomass compared to the respective fossil reference systems commonly
used in these sectors. Commercial chains such as biomass direct power,
anaerobic digestion biogas to power, and very effi cient modern heating
technologies are shown on the right side and provide signifi cant
GHG savings compared to the fossil fuels. More details of the GHG
meta-analysis study comparing multiple biomass electricity generating
technologies are available in Figure 2.11, which shows that the majority
of lifecycle GHG emission estimates cluster between about 16 and 74
g CO2eq/kWh.
The transport sector is addressed for today’s and tomorrow’s technologies.
For light-duty vehicle applications, sugarcane today and
lignocellulosic feedstocks in the medium term can provide signifi cant
emissions savings relative to gasoline. In the case of diesel, the range
of GHG emissions depends on the feedstock carbon footprint. Biogasderived
biomethane also offers emission reductions (compared to
natural gas) in the transport sector. [2.5.2, 9.3.4.1]
When land high in carbon (notably forests and especially drained peat
soil forests) is converted to bioenergy production, upfront emissions may
cause a time lag of decades to centuries before net emission savings
are achieved. In contrast, the establishment of bioenergy plantations on
marginal and degraded soils can lead to assimilation of CO2 into soils
51
Summaries Technical Summary
Climate
Change
Risks
1. Business as Usual
2. Un-Reconciled Growth
and Environment
• Food vs. Fuel
1. Good Governance
• Supportive Policies
2. Sustainable
Use of Resources
• Ecosystems Services
Food, Fodder, Fibre, Fuel
Enablers
Micro Scale:
Agrobiodiversity
Meso Scale:
Ecological Services,
Agroecological Areas
Macro Scale:
Biodiversity
Energy
Land Use
Dynamic
Interactions
in Space &
Time
Biomass &
Water
Figure TS.2.4 | The complex dynamic interactions among society, energy and the environment associated with bioenergy. Approaches of uncoordinated production of food and fuel
that emerge in poor governance of land use are examples of business as usual practices. [Figure 2.15]
and aboveground biomass and when harvested for energy production
it will replace fossil fuel use. Appropriate governance of land use (e.g.,
proper zoning) and choice of biomass production systems are crucial to
achieve good performance. The use of post-consumer organic waste and
by-products from the agricultural and forest industries does not cause
LUC if these biomass sources were not utilized for alternative purposes.
[2.5.3]
Lignocellulosic feedstocks for bioenergy can decrease the pressure on
prime cropland. Stimulating increased productivity in all forms of land
use reduces the LUC pressure. [2.2.4.2, 2.5.2]
The assessment of available iLUC literature indicates that initial models
were lacking in geographic resolution leading to higher proportions of
assignments of land use to deforestation. While a 2008 study claimed an
iLUC factor of 0.8 (losing 0.8 ha of forest land for each hectare of land
used for bioenergy) later (2010) studies that coupled macro-economic
to biophysical models reported a reduction to 0.15 to 0.3. Major factors
are the rate of improvement in agricultural and livestock management
and the rate of deployment of bioenergy production. The results from
increased model sophistication and improved data on the actual dynamics
of land distribution in the major biofuel producing countries are
leading to lower overall LUC impacts, but still with wide uncertainties.
All studies acknowledge that land use management at large is a key.
Research to improve LUC assessment methods and increase the availability
and quality of information on current land use, bioenergy-derived
products and other potential LUC drivers can facilitate evaluation and
provide tools to mitigate the risk of bioenergy-induced LUC. [2.5.3,
9.3.4.1]
Air pollution effects of bioenergy depend on both the bioenergy technology
(including pollution control technologies) and the displaced energy
technology. Improved biomass cookstoves for traditional biomass use
can provide large and cost-effective mitigation of GHG emissions with
substantial co-benefi ts for the 2.7 billion people that rely on traditional
biomass for cooking and heating in terms of health and quality of life.
[2.5.4, 2.5.5]
Without proper management, increased biomass production could come
with increased competition for water in critical areas, which is highly
undesirable. Water is a critical issue that needs to be better analyzed at
a regional level to understand the full impact of changes in vegetation
and land use management. Recent studies indicate that considerable
improvements can be made in water use effi ciency in conventional
52
Technical Summary Summaries
agriculture, bioenergy crops and, depending on location and climate,
perennial cropping systems by improving water retention and lowering
direct evaporation from soils. [2.5.5, 2.5.5.1]
Similar remarks can be made with respect to biodiversity, although
more scientifi c uncertainty exists due to ongoing debates on methods
of biodiversity impact assessment. Clearly, development of large-scale
monocultures at the expense of natural areas is detrimental for biodiversity,
as highlighted in the 2007 Convention on Biological Diversity.
However, integrating different perennial grasses and woody crops into
agricultural landscapes can also increase soil carbon and productivity,
reduce shallow landslides and local ‘fl ash fl oods’, provide ecological
corridors, reduce wind and water erosion and reduce sediment and
nutrients transported into river systems. Forest biomass harvesting can
improve conditions for replanting, improve productivity and growth of
the remaining stand and reduce wildfi re risk. [2.5.5.3]
Social impacts associated with large expansions in bioenergy production
are very complex and diffi cult to quantify. The demand for biofuels
represents one driver of demand growth in the agricultural and forestry
sectors and therefore contributes to global food price increases. Even
considering the benefi t of increased prices to poor farmers, higher food
prices adversely affect poverty levels, food security, and malnourishment
of children. On the other hand, biofuels can also provide opportunities
for developing countries to make progress in rural development
and agricultural growth, especially when this growth is economically
sustainable. In addition, expenditures on imported fossil fuels can be
reduced. However, whether such benefi ts end up with rural farmers
depends largely on the way production chains are organized and how
land use is governed. [2.5.7.4–2.5.7.6, 9.3.4]
The development of sustainability frameworks and standards can reduce
potential negative impacts associated with bioenergy production and
lead to higher effi ciency than today’s systems. Bioenergy can contribute
to climate change mitigation, a secure and diverse energy supply, and
economic development in developed and developing countries alike, but
the effects of bioenergy on environmental sustainability may be positive
or negative depending upon local conditions, how criteria are defi ned,
and how projects are designed and implemented, among many other
factors. [2.4.5.2, 2.8.3, 2.5.8, 2.2.5, 9.3.4]
Diesel Substitutes from Biomass, Coal and Coal/Biomass
Lifecycle GHG Emissions [g CO2 eq / MJ]
-100
400
300
200
100
0
600
500
Sugarcane
Sugar Beet
Corn and Wheat
Lignocellulose
Petroleum Gasoline
Plant Oil BD
Algae BD
Plant Oils RD
Lignocellulose FTD
BCTL (10% Biomass w/ or w/o Power)
BCTL (10% to 55% Biomass w/ CCS)
CTL (FT Diesel) (w/ or w/o Power)
CTL (FT Diesel w/ CCS)
Petroleum Diesel
Biogas
Natural Gas
Biomass
Biogas
Coal
Oil
Fossil Gas
Biomass
Coal
Oil
Natural Gas
Fossil Electric Heating
Heat
Ethanol and Gasoline
Transportation Electricity
Biomass and Coal to Liquids
(B/CTL)
Biodiesel (BD), Renewable
Diesel (RD) & Fischer Tropsch
Diesel (FTD)
Biogas &
Natural Gas
CO2 Savings
*CCS=Carbon Capture and Storage
Modern Bioenergy
Fossil Fuel Energy
BCTL
Figure TS.2.5 | Ranges of GHG emissions per unit energy output (MJ) from major modern bioenergy chains compared to current and selected advanced fossil fuel energy systems
(land use-related net changes in carbon stocks and land management impacts are excluded). Commercial and developing (e.g., algae biofuels, Fischer-Tropsch) systems for biomass and
fossil technologies are illustrated. When CCS technologies are developed, capture and sequestration of biomass carbon emissions can compensate fossil fuel-based energy production
emissions. [Figure 2.10]
-
I 1 I I
I " ■
■ 'hi.'I'?
j il
1 11-
53
Summaries Technical Summary
2.6 Prospects for technology
improvement and integration
Further improvements in biomass feedstock production and conversion
technologies are quite possible and necessary if bioenergy is to contribute
to global energy supply to the degree refl ected in the high end of
deployment levels shown in Figure TS.2.2. Increasing land productivity,
whether for food or energy purposes, is a crucial prerequisite for realizing
large-scale future deployment of biomass for energy since it would
make more land available for growing biomass and reduce the associated
demand for land. In addition, multi-functional land and water
use systems could develop with bioenergy and biorefi neries integrated
into agricultural and forestry systems, contributing to biodiversity conservation
and helping to restore/maintain soil productivity and healthy
ecosystems. [2.6.1]
Lignocellulosic feedstocks offer signifi cant promise because they 1) do
not compete directly with food production, 2) can be bred specifi cally
for energy purposes, enabling higher production per unit land area and
a large market for energy products, 3) can be harvested as residues from
crop production and other systems that increase land use effi ciency, and
4) allow the integration of waste management operations with a variety
of other industries offering prospects for industrial symbiosis at the local
level. Literature on and investment trends in conversion technologies
indicate that the industry is poised to increase product diversifi cation,
as did the petroleum industry, with increased interest in the high energy
density fuels for air transport, an application for which other non-carbon
fuels have not been identifi ed. [2.6.4]
A new generation of aquatic feedstocks that produce algal lipids for diesel,
jet fuels, or higher value products from CO2 and water with sunlight
can provide strategies for lower land use impacts, as algae can grow in
brackish waters, lands inappropriate for cultivation, and industrial waste
water. Algal organisms can operate in the dark and metabolize sugars
for fuels and chemicals. Many microbes could become microscopic factories
to produce specifi c products, fuels and materials that decrease
society’s dependence on fossil energy sources. [2.6.1.2, 2.7.3]
Although signifi cant technical progress has been made, the more
complex processing required by solid lignocellulosic biomass and the
integration of a number of new steps takes time and support to bring
development through the ‘Valley of Death’ in demonstration plants, fi rstof-
a-kind plants and early commercialization. Projected costs of biofuels
from a wide range of sources and process variables are very sensitive
to feedstock cost and range from USD2005 10 to 30/GJ. The US National
Academies project a 40% reduction in operating costs for biochemical
routes by 2035 to USD2005 12 to 15/GJ. [2.6.3, 2.6.4]
Biomass gasifi cation currently provides about 1.4 GWth in industrial
applications, thermal applications and co-fi ring. Small-scale systems
ranging from cooking stoves and anaerobic digestion systems to small
gasifi ers have been improving in effi ciency over time. Many stakeholders
have had a special interest in integrated gasifi cation combined-cycle
(IGCC) power plants that use bioenergy as a feedstock. These plants are
projected to be more effi cient than traditional steam turbine systems
but have not yet reached full commercialization. However, they also
have the potential to be integrated into CCS systems more effectively.
In addition to providing power, syngas from gasifi cation plants can be
used to produce a wide range of fuels (methanol, ethanol, butanols and
syndiesel) or can be used in a combined power and fuels approach.
Technical and engineering challenges have so far prevented more rapid
deployment of this technology option. Biomass to liquids conversion
uses commercial technology developed for fossil fuels. Figure TS.2.5
illustrates projected emissions from coal to liquid fuels and the offsetting
emissions that biomass could offer all the way to removal of GHG
from the atmosphere when coupled with CCS technologies. Gaseous
products (hydrogen, methane, synthetic natural gas) have lower estimated
production costs and are in an early commercialization phase.
[2.6.3, 2.6.4]
Pyrolysis and hydrothermal oils are low-cost transportable oils, used in
heat or CHP applications and could become a feedstock for upgrading
either in stand-alone facilities or coupled to a petrochemical refi nery.
[2.3.4, 2.6.3, 2.6.4, 2.7.1]
The production of biogas from a variety of waste streams and its
upgrading to biomethane is already penetrating small markets for
multiple applications, including transport in small networks in Sweden
and for heat and power in Nordic and European countries. A key factor
is the combination of waste streams, including agriculture residues.
Improved upgrading and reducing costs is also needed. [2.6.3, 2.6.4]
Many bioenergy/biofuels routes enable CCS with signifi cant
opportunities for emissions reductions and sequestration. As CCS
technologies are further developed and verifi ed, coupling fermentation
with concentrated CO2 streams or IGCC offers opportunities to
achieve carbon-neutral fuels, and in some cases negative net emissions.
Achieving this goal will be facilitated by well-designed systems
that span biomass selection, feedstock supply system, conversion to
a secondary energy carrier and integration of this carrier into the
existing and future energy systems. [2.6.3, 2.6.4, 9.3.4]
2.7 Current costs and trends
Biomass production, supply logistics, and conversion processes contribute
to the cost of fi nal products. [2.3, 2.6, 2.7]
The economics and yields of feedstocks vary widely across world regions
and feedstock types with costs ranging from USD2005 0.9 to 16/GJ (data
from 2005 to 2007). Feedstock production for bioenergy competes with
the forestry and food sectors, but integrated production systems such as
agro-forestry or mixed cropping may provide synergies along with additional
environmental services. Handling and transport of biomass from
production sites to conversion plants may contribute 20 to up to 50%
of the total costs of bioenergy production. Factors such as scale increase
54
Technical Summary Summaries
and technological innovations increase competition and contribute to a
decrease in economic and energy costs of supply chains by more than
50%. Densifi cation via pelletization or briquetting is required for transportation
distances over 50 km. [2.3.2, 2.6.2]
Several important bioenergy systems today, most notably sugarcanebased
ethanol and heat and power generation from residues and waste
biomass, can be deployed competitively. [Tables 2.6, 2.7]
Based on a standardized methodology outlined in Annex II, and the cost
and performance data summarized in Annex III, the estimated production
costs for commercial bioenergy systems at various scales and with
some consideration of geographical regions are summarized in Figure
TS.2.6. Values include production, supply logistics and conversion costs.
[1.3.2, 2.7.2, 10.5.1, Annex II, Annex III]
Costs vary by world regions, feedstock types, feedstock supply costs,
the scale of bioenergy production, and production time during the year,
which is often seasonal. Examples of estimated commercial bioenergy
levelized10 cost ranges are roughly USD2005 2 to 48/GJ for liquid and gaseous
biofuels; roughly 3.5 to 25 US cents2005/kWh (USD2005 10 to 50/
GJ) for electricity or CHP systems larger than about 2 MW (with feed
stock costs of USD2005 3/GJ feed and a heat value of USD2005 5/GJ for
steam or USD2005 12/GJ for hot water); and roughly USD2005 2 to 77/GJ for
domestic or district heating systems with feedstock costs in the range of
USD2005 0 to 20/GJ (solid waste to wood pellets). These calculations refer
to 2005 to 2008 data and are in expressed USD2005 at a 7% discount
rate. The cost ranges for biofuels in Figure TS.2.6 cover the Americas,
India, China and European countries. For heating systems, the costs are
primarily European and the electricity and CHP costs come from primarily
large user countries. [2.3.1–2.3.3, 2.7.2, Annex III]
In the medium term, the performance of existing bioenergy technologies
can still be improved considerably, while new technologies offer
the prospect of more effi cient and competitive deployment of biomass
for energy (and materials). Bioenergy systems, namely for ethanol and
biopower production, show technological learning and related cost
reductions with learning rates comparable to those of other RE technologies.
This applies to cropping systems (following progress in agricultural
management for sugarcane and maize), supply systems and logistics (as
observed in Nordic countries and international logistics) and in conversion
(ethanol production, power generation and biogas) as shown in
Table TS.2.2.
Although not all bioenergy options discussed in Chapter 2 have been
investigated in detail with respect to technological learning, several
important bioenergy systems have reduced their cost and improved environmental
performance. However, they usually still require government
10 As in the electricity production in CHP systems in which calculations assumed a
value for the co-produced heat, for biofuels systems, there are cases in which two
co-products are obtained; for instance, sugarcane to sugar, ethanol, and electricity.
Sugar co-product revenue could be about US$2005 2.6/GJ and displace the ethanol
cost by that amount.
subsidies provided for economic development (e.g., poverty reduction
and a secure energy supply) and other country-specifi c reasons. For
traditional biomass, charcoal made from biomass is a major fuel in
developing countries, and should benefi t from the adoption of highereffi
ciency kilns. [2.3, 2.6.1, 2.6.2, 2.6.3, 2.7.2, 10.4, 10.5]
The competitive production of bio-electricity (through methane or biofuels)
depends on the integration with the end-use systems, performance
of alternatives such as wind and solar energy, developing CCS technologies
coupled with coal conversion, and nuclear energy. The implications
of successful deployment of CCS in combination with biomass conversion
could result in removal of GHGs from the atmosphere and attractive
mitigation cost levels but have so far received limited attention. [2.6.3.3,
8.2.1, 8.2.3, 8.2.4, 8.3, 9.3.4]
Table TS.2.3 illustrates that costs for some key bioenergy technology
are expected to decline over the near- to mid-term. With respect
to lignocellulosic biofuels, recent analyses have indicated that the
improvement potential is large enough for competition with oil at
prices of USD2005 60 to 80/barrel (USD2005 0.38 to 0.44/litre). Currently
available scenario analyses indicate that if shorter-term R&D and
market support is strong, technological progress could allow for
their commercialization around 2020 (depending on oil and carbon
prices). Some scenarios also indicate that this would mean a major
shift in the deployment of biomass for energy, since competitive production
would decouple deployment from policy targets (mandates)
and demand for biomass would move away from food crops to biomass
residues, forest biomass and perennial cropping systems. The
implications of such a (rapid) shift are so far poorly studied. [2.8.4,
2.4.3, 2.4.5]
Lignocellulosic ethanol development and demonstration continues
in several countries. A key development step is the pretreatment to
overcome the recalcitrance of the cell wall of woody, herbaceous or
agricultural residues to make carbohydrate polymers accessible to
hydrolysis (e.g., by enzymes) and fermentation of sugars to ethanol
(or butanol) and lignin for process heat or electricity. Alternatively,
multiple steps can be combined and bio-processed with multiple
organisms simultaneously. A review of progress in the enzymatic
area suggests that a 40% reduction in cost could be expected by
2030 from process improvements, which would bring down the estimated
cost of production from USD2005 18 to 22/GJ (pilot data) to
USD 12 to 15/GJ, a competitive range. [2.6.3]
Biomass pyrolysis routes and hydrothermal concepts are also developing
in conjunction with the oil industry and have demonstrated
technically that upgrading of oils to blendstocks of gasoline or diesel
and even jet fuel quality products is possible. [2.6.3]
Photosynthetic organisms such as algae biologically produce (using CO2,
water and sunlight) a variety of carbohydrates and lipids that can be
used directly or for biofuels. These developments have signifi cant longterm
potential because algae photosynthetic effi ciency is much higher
55
Summaries Technical Summary
Figure TS.2.6 | Typical recent levelized cost of energy services from commercially available bioenergy systems at a 7% discount rate, calculated over a year of feedstock costs, which differ
between technologies. These costs do not include interest, taxes, depreciation and amortization. [Figure 2.18] Levelized costs of electricity (LCOE), heat (LCOH), fuels (LCOF), intermediate
fuel (LCOIF), BFB: Bubbling Fluidized Bed, ORC: Organic Rankine Cycle and ICE: Internal Combustion Engine. For biofuels, the range of LCOF represents production in a wide range of
countries whereas LCOE and LCOH are given only for major user markets of the technologies for which data were available. Calculations are based on High Heating Value.
Power (Direct Fired, BFB & Stoker), 25 - 100 MW
Power (Co-Firing), 25 - 100 MW
CHP (Stoker), 25 - 100 MW
CHP (ORC), 0.65 - 1.6 MW
CHP (Steam Turbine), 2.5 - 10 MW
CHP (Gasification ICE), 2.2 - 13 MW
CHP (MSW), 1 - 10 MW
CHP (Steam Turbine), 12 - 14 MW
CHP (Anaerobic Digestion), 0.5 - 5 MW
Heat (Domestic Pellet Heating), 5 - 100 kW
Intermediate Fuel (Pyrolysis Fuel Oil)
Transport Fuel from Sugarcane (Ethanol, Sugar, Electricity)
Transport Fuel from Corn (Ethanol, Feed - Dry Mill)
Transport Fuel from Wheat (Ethanol, Feed)
Transport Fuel from Soy Oil (Biodiesel)
Transport Fuel from Palm Oil (Biodiesel)
[USD2005 /GJ]
0 5 10 15 20 25 30 35
[UScents2005 /kWh]
0 10 20 30 40 50 60 70 80 90
1 The LCOE of CHP options account for the
heat output as by-product revenue;
2 The LCOH of CHP options do only account
for the heat-related cost shares.
Levelized Cost of Transport Fuel
Levelized Cost of Intermediate Fuel
Levelized Cost of Heat2
Levelized Cost of Electricity1
than that of oil crops. Potential bioenergy supplies from plants are very
uncertain, but because their development can utilize brackish waters
and heavily saline soils, their use is a strategy for low LUC impacts.
[2.6.2, 3.3.5, 3.7.6]
Data availability is limited with respect to production of biomaterials,
while cost estimates for chemicals from biomass are rare in peerreviewed
literature and future projections and learning rates even more
so. This condition is linked, in part, to the fact that successful bio-based
products are entering the market place either as partial components
of otherwise fossil-derived products or as fully new synthetic polymers
such as polylactides based on lactic acid derived from sugar fermentation.
In addition to producing biomaterials to replace fossil fuels,
analyses indicate that cascaded use of biomaterials and subsequent use
of waste material for energy can offer more effective and larger mitigation
impacts per hectare or tonne of biomass used. [2.6.3.5]
2.8 Potential deployment levels
Between 1990 and 2008, bioenergy use increased at an average annual
growth rate of 1.5% for solid biomass, while the more modern biomass
use for secondary carriers such as liquid and gaseous forms increased at
12.1 and 15.4% respectively. As a result, the share of biofuels in global
road transport was 2% in 2008. The production of ethanol and biodiesel
increased by 10 and 9%, respectively, in 2009, to 90 billion litres, such
that biofuels contributed nearly 3% of global road transport in 2009,
as oil demand decreased for the fi rst time since 1980. Government
- ■
■
■
■
56
Technical Summary Summaries
policies in various countries led to a fi ve-fold increase in global biofuels
production from 2000 to 2008. Biomass and renewable waste
power generation was 259 TWh (0.93 EJ) in 2007 and 267 TWh (0.96
EJ) in 2008 representing 1% of the world’s electricity and a doubling
since 1990 (from 131 TWh (0.47 EJ)). [2.4]
The expected continued deployment of biomass for energy in the 2020
to 2050 time frame varies considerably between studies. A key message
from the review of available insights is that large-scale biomass
deployment strongly depends on sustainable development of the
resource base, governance of land use, development of infrastructure
and cost reduction of key technologies, for example, effi cient and
complete use of primary biomass for energy from the most promising
fi rst-generation feedstocks and new-generation lignocellulosic biomass.
[2.4.3, 2.8]
The scenario results summarized in Figure TS.2.7 derive from a diversity
of modelling teams and a wide range of assumptions including
energy demand growth, cost and availability of competing low-carbon
technologies, and cost and availability of RE technologies. Traditional
biomass use is projected to decline in most scenarios while the use
of liquid biofuels, biogas and electricity and hydrogen produced from
biomass tends to increase. Results for biomass deployment for energy
under these scenarios for 2020, 2030 and 2050 are presented for
three GHG stabilization ranges based on the AR4: Categories III and IV
(440-600 ppm CO2), Categories I and II (<440 ppm CO2) and Baselines
(>600 ppm CO2) all by 2100. [10.1–10.3]
Global biomass deployment for energy is projected to increase with
more ambitious GHG concentration stabilization levels indicating its
long-term role in reducing global GHG emissions. Median levels are 75
Table TS.2.3 | Projected production cost ranges for developing technologies. [Table 2.18]
Selected Bioenergy Technologies Energy Sector (Electricity, Thermal, Transport)6 2020-2030 Projected Production Costs (USD2005/GJ)
Integrated gasifi cation combined cycle 1 Electricity and/or transport 12.8–19.1 (4.6–6.9 cents/kWh)
Oil plant-based renewable diesel and jet fuel Transport and electricity 15–30
Lignocellulose sugar-based biofuels2
Transport
6–30
Lignocellulose syngas-based biofuels3 12–25
Lignocellulose pyrolysis-based biofuels4 14–24 (fuel blend components)
Gaseous biofuels5 Thermal and transport 6–12
Aquatic plant-derived fuels, chemicals Transport 30–140
Notes: 1. Feed cost USD2005 3.1/GJ, IGCC (future) 30 to 300 MW, 20-yr life, 10% discount rate. 2. Ethanol, butanols, microbial hydrocarbons and microbial hydrocarbons from sugar
or starch crops or lignocellulose sugars. 3. Syndiesel, methanol and gasoline, etc.; syngas fermentation routes to ethanol. 4. Biomass pyrolysis and catalytic upgrading to gasoline and
diesel blend components or to jet fuels. 5. Synfuel to synthetic natural gas, methane, dimethyl ether, hydrogen from biomass thermochemical and anaerobic digestion (larger scale).
6. Several applications can be coupled with CCS when these technologies, including CCS, are mature and thus could remove GHG from the atmosphere.
Table TS.2.2 | Experience curves for major components of bioenergy systems and fi nal energy carriers expressed as reduction (%) in cost (or price) per doubling of cumulative
production, the Learning Rate (LR); N: number of doublings of cumulative production; R2 is the correlation coeffi cient of the statistical data; O&M: Operations and Maintenance.
[Table 2.17]
Learning system LR (%) Time frame Region N R²
Feedstock production
Sugarcane (tonnes sugarcane)
Corn (tonnes corn)
32±1
45±1.6
1975–2005
1975–2005
Brazil
USA
2.9
1.6
0.81
0.87
Logistic chains
Forest wood chips (Sweden) 15–12 1975–2003 Sweden/Finland 9 0.87–0.93
Investment and O&M costs
CHP plants
Biogas plants
Ethanol production from sugarcane
Ethanol production from corn (only O&M costs)
19-25
12
19±0.5
13±0.15
1983–2002
1984–1998
1975–2003
1983–2005
Sweden
Brazil
USA
2.3
6
4.6
6.4
0.17–0.18
0.69
0.80
0.88
Final energy carriers
Ethanol from sugarcane
Ethanol from sugarcane
Ethanol from corn
Electricity from biomass CHP
Electricity from biomass
Biogas
7
29
20±0.5
18±0.2
9-8
15
0–15
1970–1985
1985–2002
1975–2003
1983–2005
1990–2002
Unknown
1984–2001
Brazil
Brazil
USA
Sweden
OECD
Denmark
~6.1
4.6
6.4
~9
N/A
~10
N/A
0.84
0.96
0.85–0.88
N/A
0.97
57
Summaries Technical Summary
to 85 EJ and 120 to 155 EJ for the two mitigation scenarios in 2030
and 2050, respectively, almost two and three times the 2008 deployment
level of 50 EJ. These deployment levels are similar to the expert
review mid-range levels for 2050. Global biofuels production shown
in Figure TS.2.7(b) for 2020 and 2030 are at fairly low levels, but most
models lack a detailed description of different conversion pathways
and related learning potential. [2.7.3] For the <440 ppm mitigation
scenario, biofuels production reaches six (2030) and ten (2050) times
the 2008 actual value of 2 EJ. [2.2.5, 2.8.2, 2.5.8, 2.8.3]
The sector-level penetration of bioenergy is best explained using a
single model with detailed transport sector representation such as the
2010 IEA World Energy Outlook (WEO) that also models both traditional
and modern biomass applications and takes into account anticipated
industrial and government investments and goals. This model projects
very signifi cant increases in modern bioenergy and a decrease in traditional
biomass use. These projections are in qualitative agreement
with the results from Chapter 10. In 2030, for the WEO 450-ppm mitigation
scenario, the IEA projects that 11% of global transport fuels will
be provided by biofuels with second-generation biofuels contributing
60% of the projected 12 EJ and half of this amount is projected to
be supplied owing to continuation of current policies. Biomass and
renewable wastes would supply 5% of the world’s electricity generation
or 1,380 TWh/yr (5 EJ/yr) of which 555 TWh/yr (2 EJ/yr) are a result
of the stringent climate mitigation strategy. Biomass industrial heating
applications for process steam and space and hot water heating
for buildings (3.3 EJ in 2008) would each double in absolute terms
from 2008 levels. However, the total heating demand is projected to
decrease because of assumed traditional biomass decline. Heating is
seen as a key area for continued modern bioenergy growth. Biofuels
Figure TS.2.7 | (a) The global primary energy supply from biomass in long-term scenarios for electricity, heat and biofuels, all accounted for as primary energy; and (b) global biofuels
production in long-term scenarios reported in secondary energy terms. For comparison, the historical levels in 2008 are indicated in the small black arrows on the left axis. [Figure 2.23]
(a) (b)
2020 2030 2050
0
20
40
60
80
100
Global Liquid Biofuel Production [EJ/yr]
N=98
Global Biomass Primary Energy Supply [EJ/yr]
2020 2030 2050
0
CO2 Concentration Levels
Baselines
Cat. III + IV (440 - 600 ppm)
Cat. I + II (< 440 ppm)
CO2 Concentration Levels
50
150
100
Baselines
N=137
Cat. III + IV (440 - 600 ppm)
Cat. I + II (< 440 ppm)
200
250
300
350
2008
2008
are projected to mitigate 17% of road and 3% of air transport emissions
by 2030. [2.8.3]
2.8.1 Conclusions regarding deployment: Key
messages about bioenergy
The long-term scenarios reviewed in Chapter 10 show increases in bioenergy
supply with increasingly ambitious GHG concentration stabilization
levels, indicating that bioenergy could play a signifi cant long-term role
in reducing global GHG emissions. [2.8.3]
Bioenergy is currently the largest RE source and is likely to remain one of
the largest RE sources for the fi rst half of this century. There is considerable
growth potential, but it requires active development. [2.8.3]
• Assessments in the recent literature show that the technical potential
of biomass for energy may be as large as 500 EJ/yr by 2050.
However, large uncertainty exists about important factors such as
market and policy conditions that affect this potential. [2.8.3]
• The expert assessment in Chapter 2 suggests potential deployment
levels by 2050 in the range of 100 to 300 EJ/yr. Realizing this potential
represents a major challenge but would make a substantial
contribution to the world’s primary energy demand in 2050—
roughly equal to the equivalent heat content of today’s worldwide
biomass extraction in agriculture and forestry. [2.8.3]
• Bioenergy has signifi cant potential to mitigate GHGs if resources
are sustainably developed and effi cient technologies are applied.
■■ ■
-■■
■
58
Technical Summary Summaries
Certain current systems and key future options, including perennial
crops, forest products and biomass residues and wastes, and
advanced conversion technologies, can deliver signifi cant GHG
mitigation performance—an 80 to 90% reduction compared to the
fossil energy baseline. However, land conversion and forest management
that lead to a large loss of carbon stocks and iLUC effects can
lessen, and in some cases more than neutralize, the net positive
GHG mitigation impacts. [2.8.3]
• In order to achieve the high potential deployment levels of biomas
for energy, increases in competing food and fi bre demand must be
moderate, land must be properly managed and agricultural and forestry
yields must increase substantially. Expansion of bioenergy in
the absence of monitoring and good governance of land use carries
the risk of signifi cant confl icts with respect to food supplies, water
resources and biodiversity, as well as a risk of low GHG benefi ts.
Conversely, implementation that follows effective sustainability
frameworks could mitigate such confl icts and allow realization of
positive outcomes, for example, in rural development, land amelioration
and climate change mitigation, including opportunities to
combine adaptation measures. [2.8.3]
• The impacts and performance of biomass production and use are
region- and site-specifi c. Therefore, as part of good governance of
Figure TS.2.8 | Storylines for the key SRES scenario variables used to model biomass and bioenergy, the basis for the 2050 sketches adapted to this report and used to derive the
stacked bar showing the biomass technical potential in Figure TS.2.2. [Figure 2.26]
Globally Oriented Regionally Oriented
IPCC SRES Scenarios Material/Economic
Environment/Social
Food Trade:
Meat Consumption:
Technology Development:
Food Crop Fertilization:
Crop Intensity Growth:
2050 Population (Billion):
2100 Population (Billion):
Relative 2100 GDP:
Food Trade:
Meat Consumption:
Technology Development:
Food Crop Fertilization:
Crop Intensity Growth:
2050 Population (Billion):
2100 Population (Billion):
Relative 2100 GDP:
Very Low
Low
Low
Low
Low
9.4
10.4
44%
Low
High
Low
High
Low
11.3
15.1
46%
Maximal High
High
High
Very High
High
8.7
7.1
100%
High
Low
High
Low
High
8.7
7.1
61%
(B1)
Future world convergent in
global population, with
rapid change in economic
structures toward a service
and information economy,
low material intensity, and
clean and resource efficient
technologies.
(B2)
World emphasis is on local
solutions to economic,
social and environmental
sustainability. Less rapid
and more diverse
technological change.
(A1)
Future world of very rapid
economic growth, global
population peaks in
mid-century and declines
thereafter, and introduces
rapidly new and more
efficient technologies.
(A2)
Very heterogeneous future
world characterized by self
reliance and preservation
of local identities.
Fragmented and slower
technological change.
land use and rural development, bioenergy policies need to consider
regional conditions and priorities along with the agricultural (crops
and livestock) and forestry sectors. Biomass resource potentials are
infl uenced by and interact with climate change impacts but the
specifi c impacts are still poorly understood; there will be strong
regional differences in this respect. Bioenergy and new (perennial)
cropping systems also offer opportunities to combine adaptation
measures (e.g., soil protection, water retention and modernization
of agriculture) with production of biomass resources. [2.8.3]
• Several important bioenergy options (i.e., sugarcane ethanol production
in Brazil, select waste-to-energy systems, effi cient biomass
cookstoves, biomass-based CHP) are competitive today and can provide
important synergies with longer-term options. Lignocellulosic
biofuels to replace gasoline, diesel and jet fuels, advanced bioelectricity
options, and biorefi nery concepts can offer competitive
deployment of bioenergy for the 2020 to 2030 timeframe. Combining
biomass conversion with CCS raises the possibility of achieving
GHG removal from the atmosphere in the long term—a necessity
for substantial GHG emission reductions. Advanced biomaterials
are promising as well for economics of bioenergy production and
mitigation, though the potential is less well understood as is the
potential role of aquatic biomass (algae), which is highly uncertain.
[2.8.3]
59
Summaries Technical Summary
• Rapidly changing policy contexts, recent market-based activities,
the increasing support for advanced biorefi neries and lignocellulosic
biofuel options, and in particular the development of sustainability
criteria and frameworks, all have the potential to drive bioenergy
systems and their deployment in sustainable directions. Achieving
this goal will require sustained investments that reduce costs of
key technologies, improved biomass production and supply infrastructure,
and implementation strategies that can gain public and
political acceptance. [2.8.3]
In conclusion and for illustrating the interrelations between scenario
variables (see Figure TS.2.8), key preconditions under which bioenergy
production capacity is developed and what the resulting impacts may
be, Figure TS.2.8 presents four different sketches for biomass deployment
for energy at a global scale by 2050. The 100 to 300 EJ range that
follows from the resource potential review delineates the lower and
upper limit for deployment. The assumed storylines roughly follow the
IPCC Special Report on Emissions Scenarios (SRES) defi nitions, applied
to bioenergy and summarized in Figure TS.2.9 and which were also used
Key Preconditions
• Well working sustainability frameworks and strong policies are implemented.
• Well developed bioenergy markets.
• Progressive technology development, e.g. biorefineries, new generation biofuels
and multiple products, successful use of degraded lands.
• Developing countries succeed in transitioning to higher efficiency technologies
and implement biorefineries at scales compatible with available resources.
• Satellite processing emerges.
Key Impacts
• 35% biomass from residues and wastes, 25% from marginal/degraded lands
and 40% from arable and pasture lands (˜3 and ˜1 million km2, respectively).
• Moderate energy price (notably oil) due to strong increase of biomass and
biofuels supply.
• Food and fuel conflicts largely avoided due to strong land-use planning and
alignment of bioenergy production capacity with efficiency increases in
agriculture and livestock management.
• Soil quality and soil carbon improve and negative biodiversity impacts are
minimised using diverse and mixed cropping systems.
Globally Oriented Regionally Oriented
2050 Bioenergy
Storylines
Material/Economic
Environment/Social
(A1) ˜ 300 EJ/Poor Governance
Key Preconditions
• High energy demand results in high energy prices and drive strong
biomass demand.
• Limited oversight on biomass production and use, largely driven by
market demand.
• Fully liberalized markets for bioenergy as well as in agriculture as a whole.
• Strong technology development leading to increased demand for biochemicals
and advanced transport fuels from biomass.
Key Impacts
• Production emphasis is on higher quality land, converted pastures, etc.
• Biomass produced and used in large scale operations, limiting small
farmers’ benefits.
• Large scale global trade and conversion capacity developed in major seaports.
• Competition with conventional agriculture for the better quality land, driving
up food prices and increasing pressure on forest resources.
• GHG benefits overall but sub-optimal due to significant iLUC effects.
(A2) ˜ 100 EJ/Poor Governance
Key Preconditions
• High fossil fuel prices expected due to high demand and limited innovation,
which pushes demand for biofuels use from an energy security perspective.
• Increased biomass demand directly affects food markets.
Key Impacts
• Increased biomass demand partly covered by residues and wastes, partly by
annual crops.
• Additional crop demand leads to significant iLUC effects and
biodiversity impacts.
• Overall increased food prices linked to high oil prices.
• Limited net GHG benefits.
• Sub-optimal socio-economic benefits.
(B2) ˜ 100 EJ/Good Governance
Key Preconditions
• Focus on smaller scale technologies, utilization of residues, waste streams and
smaller scale cropping schemes (e.g. Jathropha) and a large array of specific
cropping schemes.
• International trade is constrained and trade barriers remain.
• Effective national policy frameworks control bioenergy deployment, put priority
on food and optimize biomass production and use for specific
regional conditions.
Key Impacts
• Biomass comes from residues, organic wastes and cultivation on more
marginal lands.
• Smaller scale bioenergy applications developed specially and used locally.
• Substantial benefits provided for rural economies in terms of employment and
diversified energy sources providing services.
• Food, land-use and nature conservation conflicts are largely avoided.
• Significant GHG mitigation benefits are constrained by limited
bioenergy deployment.
• Transport sector still uses a high share of petroleum to cover energy needs.
(B1) ˜ 300 EJ/Good Governance
Figure TS.2.9 | Possible futures for 2050 biomass deployment for energy: Four illustrative contrasting sketches describing key preconditions and impacts following world conditions
typical of the IPCC SRES storylines summarized in Figure TS.2.8. [Figure 2.27]
60
Technical Summary Summaries
to derive the technical potential shown on the stacked bar of Figure
TS.2.2. [2.8.3]
Biomass and its multiple energy products can be developed alongside
food, fodder, fi bre and forest products in both sustainable and unsustainable
ways. As viewed through IPCC scenario storylines and
sketches, high and low penetration levels can be reached with and
without taking into account sustainable development and climate
change mitigation pathways. Insights into bioenergy technology
developments and integrated systems can be gleaned from these
storylines. [2.8.3]
3. Direct Solar
3.1 Introduction
Direct solar energy technologies are diverse in nature. Responding
to the various ways that humans use energy—such as heating,
electricity, and fuels—they constitute a family of technologies.
This summary focuses on four major types: 1) solar thermal, which
includes both active and passive heating of buildings, domestic and
commercial solar water heating, swimming pool heating and process
heat for industry; 2) photovoltaic (PV) electricity generation
via direct conversion of sunlight to electricity by photovoltaic cells;
3) concentrating solar power (CSP) electricity generation by optical
concentration of solar energy to obtain high-temperature fl uids or
materials to drive heat engines and electrical generators; and 4)
solar fuels production methods, which use solar energy to produce
useful fuels. [3.1]
The term ‘direct’ solar energy refers to the energy base for those RE
technologies that draw on the Sun’s energy directly. Certain renewable
technologies, such as wind and ocean thermal, use solar energy
after it has been absorbed on the Earth and converted to other
forms. (In the remainder of this section, the adjective ‘direct’ applied
to solar energy will often be deleted as being understood.) [3.1]
3.2 Resource potential
Solar energy constitutes the thermal radiation emitted by the Sun’s
outer layer. Just outside Earth’s atmosphere, this radiation, called solar
irradiance, has a magnitude that averages 1,367 W/m2 for a surface perpendicular
to the Sun’s rays. At ground level (generally specifi ed as sea
level with the sun directly overhead), this irradiance is attenuated by the
atmosphere to about 1,000 W/m2 in clear sky conditions within a few
hours of noon—a condition called ‘full sun’. Outside the atmosphere, the
Sun’s energy is carried in electromagnetic waves with wavelengths ranging
from about 0.25 to 3 μm. Part of the solar irradiance is contributed
by rays arriving directly from the sun without being scattered in the
atmosphere. This ‘beam’ irradiance, which is capable of being concentrated
by mirrors and lenses, is most available in low cloud-cover areas.
The remaining irradiance is called the diffuse irradiance. The sum of the
beam and diffuse irradiance is called global solar irradiation. [3.2]
The theoretical solar energy potential, which indicates the amount of
irradiance at the Earth’s surface (land and ocean) that is theoretically
available for energy purposes, has been estimated at 3.9×106 EJ/yr. This
number, clearly intended for illustrative purposes only, would require the
full use of all available land and sea area at 100% conversion effi ciency.
A more useful metric is the technical potential; this requires assessing
the fraction of land that is of practical use for conversion devices using a
more realistic conversion effi ciency. Estimates for solar energy’s technical
potential range from 1,575 to 49,837 EJ/yr, that is, roughly 3 to 100
times the world’s primary energy consumption in 2008. [3.2, 3.2.2]
3.3 Technology and applications
Figure TS.3.1 illustrates the types of passive and active solar technologies
currently in use to capture the Sun’s energy to provide both residential
energy services and direct electricity. In this summary, only technologies
for active heating and electricity are treated in depth. [3.3.1–3.3.4]
Solar thermal: The key component in active solar thermal systems is
the solar collector. A fl at-plate solar collector consists of a blackened
plate with attached conduits, through which passes a fl uid to be heated.
Flat-plate collectors may be classifi ed as follows: unglazed, which
are suitable for delivering heat at temperatures a few degrees above
ambient temperature; glazed, which have a sheet of glass or other
transparent material placed parallel to the plate and spaced a few centimetres
above it, making it suitable for delivering heat at temperatures
of about 30°C to 60°C; or evacuated, which are similar to glazed, but
the space between the plate and the glass cover is evacuated, making
this type of collector suitable for delivering heat at temperatures of
about 50°C to 120°C. To withstand the vacuum, the plates of an evacuated
collector are usually put inside glass tubes, which constitute both
the collector’s glazing and its container. In the evacuated type, a special
black coating called a ‘selective surface’ is put on the plate to help prevent
re-emission of the absorbed heat; such coatings are often used on
the non-evacuated glazed type as well. Typical effi ciencies of solar collectors
used in their proper temperature range extend from about 40 to
70% at full sun. [3.3.2.1]
Flat-plate collectors are commonly used to heat water for domestic and
commercial use, but they can also be used in active solar heating to provide
comfort heat for buildings. Solar cooling can be obtained by using
solar collectors to provide heat to drive an absorption refrigeration
cycle. Other applications for solar-derived heat are industrial process
heat, agricultural applications such as drying of crops, and for cooking.
Water tanks are the most commonly used items to store heat during
61
Summaries Technical Summary
the day/night period or short periods of cloudy weather. Supplemented
by other energy sources, these systems typically provide 40 to 80% of
the demand for heat energy of the target application. [3.3.2.2–3.3.2.4]
For passive solar heating, the building itself—particularly its windows—
acts as the solar collector, and natural methods are used to distribute
and store the heat. The basic elements of passive heating architecture
are high-effi ciency equatorial-facing windows and large internal thermal
mass. The building must also be well insulated and incorporate methods
such as shading devices to prevent it from overheating. Another feature
of passive solar is ‘daylighting’, which incorporates special strategies
to maximize the use of natural (solar) lighting in the building. Studies
have shown that with current technology, using these strategies in new
buildings in northern Europe or North America can reduce the building
Ventilated
Slab
Passive
Slab
Exhaust
Fan
Variable
Speed Fan
BIPV/T
Roof
Air
Inlet
Dryer
HRV
DHW
Geothermal
Pump
Side-Fin
Light
Shelf
q
Solar
Blinds
Internal
Rolling
Shutter
External
Rolling
Shutter
Tilted
Slats
+
-
Back Contact
n-Type Semiconductor
p-Type Semiconductor
Front Contact
Anti-Reflection Coating
Recombination
Electron (-) Hole (+)
Solar Field Piping
Absorber Tube
Reflector
Figure TS.3.1 | Selected examples of (top) solar thermal, both passive and active integrated into a building; (bottom left) a photovoltaic device schematic for direct solar to electricity
conversion; and (bottom right) one common type of concentrating solar power technology, a trough collector. [Derived from Figures 3.2, 3.5, 3.7]
62
Technical Summary Summaries
heating demands by as much as 40%. For existing, rather than new,
buildings retrofi tted with passive heating concepts, reductions of as
much as 20% are achievable. [3.3.1]
Photovoltaic electricity generation: A detailed description of how PV
conversion works is available in many textbooks. In the simplest terms,
a thin sheet of semiconductor material such as silicon is placed in the
Sun. The sheet, known as a cell, consists of two distinct layers formed by
introducing impurities into the silicon resulting in an n-type layer and a
p-type layer that form a junction at the interface. Solar photons striking
the cell generate electron-hole pairs that are separated spatially by an
internal electric fi eld at the junction. This creates negative charges on
one side of the interface and positive charges are on the other side.
This resulting charge separation creates a voltage. When the two sides
of the illuminated cell are connected to a load, current fl ows from one
side of the device via the load to the other side of the cell generating
electricity. [3.3.3]
Various PV technologies have been developed in parallel. Commercially
available PV technologies include wafer-based crystalline silicon PV, as
well as the thin-fi lm technologies of copper indium/gallium disulfi de/(di)
selenide (CIGS), cadmium telluride (CdTe), thin-fi lm silicon (amorphous
and microcrystalline silicon), and dye-sensitized solar cells. In addition,
there are commercially available concentrating PV concepts, in which
very high effi ciency cells (such as gallium arsenide (GaAs)-based materials)
are placed at the focus of concentrating mirrors or other collectors
such as Fresnel lenses. Mono- and multi- crystalline (sometimes called
“polycrystalline”) silicon wafer PV (including ribbon technologies) are
the dominant technologies on the PV market, with a 2009 market share
of about 80%. Peak effi ciencies achieved by various cell types include
more than 40% for GaAs-based concentrator cells, about 25% for monocrystalline,
20% for multicrystalline and CIGS, 17% for CdTe, and about
10% for amorphous silicon. Typically, groups of cells are mounted side
by side under a transparent sheet (usually glass) and connected in series
to form a ‘module’ with dimensions of up to 1 m by 1 m. In considering
effi ciencies, it is important to distinguish between cell effi ciencies
(quoted above) and module effi ciencies; the latter are typically 50 to
80% of the former. Manufacturers continue to improve performance
and reduce costs with automation, faster cell processing, and low-cost,
high-throughput manufacturing. The performance of modules is typically
guaranteed by manufacturers for 20 to 30 years. [3.3.3.1, 3.3.3.2]
The application of PV for useful power involves more than just the cells
and modules; the PV system, for example, will often include an inverter
to convert the DC power from the cells to AC power to be compatible
with common networks and devices. For off-grid applications, the system
may include storage devices such as batteries. Work is ongoing to
make these devices more reliable, reduce their cost, and extend their
lifetime to be comparable with that of the modules. [3.3.3.4]
PV power systems are classifi ed as two major types: off-grid and gridconnected.
Grid-connected systems are themselves classifi ed into two
types: distributed and centralized. The distributed system is made up of
a large number of small local power plants, some of which supply the
electricity mainly to an on-site customer, and the remaining electricity
feeds the grid. The centralized system, on the other hand, works as one
large power plant. Off-grid systems are typically dedicated to a single
or small group of customers and generally require an electrical storage
element or back-up power. These systems have signifi cant potential in
non-electrifi ed areas. [3.3.3.5]
Concentrating solar power electricity generation: CSP technologies
produce electricity by concentrating the Sun’s rays to heat a medium
that is then used (either directly or indirectly) in a heat engine process
(e.g., a steam turbine) to drive an electrical generator. CSP uses only the
beam component of solar irradiation, and so its maximum benefi t tends
to be restricted to a limited geographical range. The concentrator brings
the solar rays to a point (point focus) when used in central-receiver or
dish systems and to a line (line focus) when used in trough or linear
Fresnel systems. (These same systems can also be used to drive thermochemical
processes for fuel production, as described below.) In trough
concentrators, long rows of parabolic refl ectors that track the movement
of the Sun concentrate the solar irradiation on the order of 70
to 100 times onto a heat-collection element (HCE) mounted along the
refl ector’s focal line. The HCE comprises a blackened inner pipe (with
a selective surface) and a glass outer tube, with an evacuated space
between the two. In current commercial designs, a heat transfer oil is circulated
through the steel pipe where it is heated (to nearly 400°C), but
systems using other heat transfer materials such as circulating molten
salt or direct steam are currently being demonstrated. [3.3.4]
The second kind of line-focus system, the linear Fresnel system, uses
long parallel mirror strips as the concentrator, again with a fi xed linear
receiver. One of the two point-focus systems, the central-receiver (also
called the ‘power tower’), uses an array of mirrors (heliostats) on the
ground, each tracking the Sun on two axes so as to focus the Sun’s
rays at a point on top of a tall tower. The focal point is directed onto a
receiver, which comprises either a fi xed inverted cavity and/or tubes in
which the heat transfer fl uid circulates. It can reach higher temperatures
(up to 1,000°C) than the line-focus types, which allows the heat engine
to convert (at least theoretically) more of the collected heat to power.
In the second type of point-focus system, the dish concentrator, a single
paraboloidal refl ector (as opposed to an array of refl ectors) tracking the
sun on two axes is used for concentration. The dish focuses the solar
rays onto a receiver that is not fi xed, but moves with the dish, being only
about one dish diameter away. Temperatures on the receiver engine can
reach as high as 900°C. In one popular realization of this concept, a
Stirling engine driving an electrical generator is mounted at the focus.
Stirling dish units are relatively small, typically producing 10 to 25 kW,
but they can be aggregated in fi eld confi guration to realize a larger
central station-like power output. [3.3.4]
The four different types of CSP plants have relative advantages and
disadvantages. [3.3.4] All four have been built and demonstrated. An
63
Summaries Technical Summary
important advantage of CSP technologies (except for dishes) is the ability
to store thermal energy after it has been collected at the receiver and
before going to the heat engine. Storage media considered include molten
salt, pressurized air or steam accumulators (for short-term storage
only), solid ceramic particles, high-temperature, phase-change materials,
graphite, and high-temperature concrete. Commercial CSP plants
are being built with thermal storage capacities reaching 15 hours, allowing
CSP to offer dispatchable power. [3.3.4]
Solar fuel production: Solar fuel technologies convert solar energy
into chemical fuels such as hydrogen, synthetic gas and liquids such
as methanol and diesel. The three basic routes to solar fuels, which
can work alone or in combination, are: (1) electrochemical; (2) photochemical/
photo-biological; and (3) thermo-chemical. In the fi rst route,
hydrogen is produced by an electrolysis process driven by solar-derived
electrical power that has been generated by a PV or CSP system.
Electrolysis of water is an old and well-understood technology, typically
achieving 70% conversion effi ciency from electricity to hydrogen. In the
second route, solar photons are used to drive photochemical or photobiological
reactions, the products of which are fuels: that is, they mimic
what plants and organisms do. Alternatively, semiconductor material
can be used as a solar light-absorbing anode in photoelectrochemical
cells, which also generate hydrogen by water decomposition. In the third
route, high-temperature solar-derived heat (such as that obtained at the
receiver of a central-receiver CSP plant) is used to drive an endothermic
chemical reaction that produces fuel. Here, the reactants can include
combinations of water, CO2, coal, biomass and natural gas. The products,
which constitute the solar fuels, can be any (or combinations) of the
following: hydrogen, syngas, methanol, dimethyl ether and synthesis oil.
When a fossil fuel is used as the reactant, overall calorifi c values of the
products will exceed those of the reactants, so that less fossil fuel needs
to be burned for the same energy release. Solar fuel can also be synthesized
from solar hydrogen and CO2 to produce hydrocarbons compatible
with existing energy infrastructures. [3.3.5]
3.4 Global and regional status of
market and industry deployment
3.4.1 Installed capacity and generated energy
Solar thermal: Active solar heating and cooling technologies for
residential and commercial buildings represent a mature market. This
market, which is distributed to various degrees in most countries of the
world, grew by 34.9% from 2007 to 2009 and continues to grow at a
rate of about 16% per year. At the end of 2009, the global installed
capacity of thermal power from these devices was estimated to be 180
GWth. The global market for sales of active solar thermal systems reached
an estimated 29.1 GWth in 2008 and 31 GWth in 2009. Glazed collectors
comprise the majority of the world market. China accounted for 79%
of the installation of glazed collectors in 2008, and the EU accounted
for about 14.5%. In the USA and Canada, swimming pool heating is
still the dominant application, with an installed capacity of 12.9 GWth
of unglazed plastic collectors. Notably in 2008, China led the world in
installed capacity of fl at-plate and evacuated-tube collectors with 88.7
GWth. Europe had 20.9 GWth and Japan 4.4 GWth. In Europe, the market
size more than tripled between 2002 and 2008. Despite these gains,
solar thermal still accounts for only a relatively small portion of the
demand for hot water in Europe. For example, in Germany, with the
largest market, about 5% of one- and two-family homes are using solar
thermal energy. One measure of the market penetration is the per capita
annual usage of solar energy. The lead country in this regard is Cyprus,
where the fi gure is 527 kWth per 1,000 people. Note that there is no
available information on passive solar regarding the status of its market
and its deployment by industry. Consequently, the preceding numbers
refer only to active solar. [3.4.1]
Photovoltaic electricity generation: In 2009, about 7.5 GW of PV systems
were installed. That brought the cumulative installed PV capacity
worldwide in 2009 to about 22 GW—a capacity able to generate up to
26 TWh (93,600 TJ) per year. More than 90% of this capacity is installed
in three leading markets: the EU with 73% of the total, Japan with
12% and the USA with 8%. Roughly 95% of the PV installed capacity
in the OECD countries is grid connected, the remainder being
off-grid. Growth in the top eight PV markets through 2009 is illustrated
in Figure TS.3.2. Spain and Germany have seen, by far, the
largest amounts of solar installed in recent years. [3.4.1]
Concentrating solar power: CSP has reached a cumulative
installed capacity of about 0.7 GW, with another 1.5 GW under construction.
The capacity factors for a number of these CSP plants are
expected to range from 25 to 75%; these can be higher than for
PV because CSP plants contain the opportunity to add thermal storage
where there is a commensurate need to overbuild the collector
fi eld to charge the thermal storage. The lower end of the capacity
factor range is for no thermal storage and the upper end is for
up to 15 hours of thermal storage. [3.8.4] The earliest commercial
CSP plants were the Solar Electric Generating Systems in California
10,000
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Cumulative Installed Capacity [MW]
Germany
Spain
Japan
USA
Italy
Korea
France
China
Figure TS.3.2 | Installed PV capacity for the years 2000 to 2009 in eight markets. [Figure
3.9]
■ ■
■ ■
■ ■
■ ■
64
Technical Summary Summaries
always low-iron glass, now readily available. Most production is in
China, where it is aimed at internal consumption. Evacuated collectors,
suitable for mass produc tion techniques, are starting to dominate that
market. Other important production sites are in Europe, Turkey, Brazil
and India. Much of the export market comprises total solar water heating
systems rather than solar collectors per se. The largest exporters of
solar water heating systems are Australia, Greece, the USA and France.
Australian exports constitute about 50% of its production. [3.4.2]
For passive solar heating, part of the industry capacity and supply
chain lies in people: namely, the engineers and architects who must
systematically collaborate to produce a passively heated building. Close
collaboration between the two disciplines has often been lacking in the
past, but the dissemination of systematic design methodologies issued
by different countries has improved the design capabilities. Windows
and glazing are an important part of passively heated buildings, and
the availability of a new generation of high-effi ciency (low-emissivity,
argon-fi lled) windows is having a major impact on solar energy’s
contribution to heating requirements in the buildings sector. These
windows now constitute the bulk of new windows being installed in
most northern-latitude countries. There do not appear to be any issues
of industrial capacity or supply chains hindering the adoption of better
windows. Another feature of passive design is adding internal mass to
the building’s structure. Concrete and bricks, the most commonly used
storage materials, are readily available; phase-change materials (e.g.,
paraffi n), considered to be the storage materials of the future, are not
expected to have supply-chain issues. [3.4.2]
Photovoltaic electricity generation: The compound annual growth
rate in PV manufacturing production from 2003 to 2009 exceeded 50%.
In 2009, solar cell production reached about 11.5 GW per year (rated
at peak capacity) split among several economies: China had about
51% of world production (including 14% from the Chinese province
of Taiwan); Europe about 18%; Japan about 14%; and the USA about
5%. Worldwide, more than 300 factories produce solar cells and modules.
In 2009, silicon-based solar cells and modules represented about
80% of the worldwide market. The remaining 20% mostly comprised
cadmium telluride, amorphous silicon, and copper indium gallium diselenide.
The total market is expected to increase signifi cantly during the
next few years, with thin-fi lm module production gaining market share.
Manufacturers are moving towards original design of manufacturing
units and are also moving components of module production closer to
the fi nal market. Between 2004 and early 2008, the demand for crystalline
silicon (or polysilicon) outstripped supply, which led to a price hike.
With the new price, ample supplies have become available; the PV market
is now driving its own supply of polysilicon. [3.4.2]
Concentrating solar power: In the past several years, the CSP industry
has experienced a resurgence from a stagnant period to more
than 2 GW being either commissioned or under construction. More
than 10 different companies are now active in building or preparing
for commercial-scale plants. They range from start-up companies to
large organizations, including utilities, with international construction
capable of producing 354 MW of power; installed between 1985
and 1991, they are still operating today. The period from 1991 to
the early 2000s was slow for CSP, but since about 2004, there has
been strong growth in planned generation. The bulk of the current
operating CSP generation consists of trough technology, but centralreceiver
technology comprises a growing share, and there is strong
proposed commercial activity in dish-Stirling. In early 2010, most of
the planned global capacity was in the USA and Spain, but recently
other countries announced commercial plans. Figure TS.3.3 shows
the current and planned deployment of CSP capacity through the
year 2015. [3.3.4, 3.4.1]
Solar fuel production: Currently, solar fuel production is in the
pilot-plant phase. Pilot plants in the power range of 300 to 500 kW
have been built for the carbo-thermic reduction of zinc oxide, steam
methane reforming, and steam gasifi cation of petcoke. A 250-kW
steam-reforming reactor is operating in Australia. [3.3.4, 3.4.1]
3.4.2 Industry capacity and supply chain
Solar thermal: In 2008, manufacturers produced approximately 41.5
million m2 of solar collectors, a scale large enough to adapt to mass
production, even though production is spread among a large number of
companies around the world. Indeed, large-scale industrial production
levels have been attained in most parts of the industry. In the manufacturing
process, a number of readily available materials—including
copper, aluminium, stainless steel, and thermal insulation—are being
applied and combined through different joining technologies to produce
the absorber plate. This box is topped by the cover glass, which is almost
Installed Capacity [MW]
1990 2000 2006 2007 2008 2009 2010 2012 2015
12,000
10,000
8,000
6,000
4,000
2,000
0
South Africa
Jordan
Morocco
Australia
Tunesia
Spain
Israel
Algeria
China
Egypt
Abu Dhabi
USA
Figure TS.3.3 | Installed and planned concentrated solar power plants by country. [Figure
3.10]
■□ ■■ ■■ ■■ ■■ ■■
a
65
Summaries Technical Summary
management expertise. None of the supply chains for construction of
plants are limited by the availability of raw material. Expanded capacity
can be introduced with a lead time of about 18 months. [3.4.2]
Solar fuel production: Solar fuel technology is still at an emerging
stage, and there is no supply chain in place at present for commercial
applications. Solar fuels will comprise much of the same solar-fi eld technology
as is being deployed for other high-temperature CSP systems, in
addition to downstream technologies similar to those in the petrochemical
industry. [3.4.2]
3.4.3 Impact of policies
Direct solar energy technologies face a range of potential barriers to
achieving wide-scale deployment. Solar technologies differ in levels of
maturity, and although some applications are already competitive in
localized markets, they generally face one common barrier: the need
to reduce costs. Utility-scale CSP and PV systems face different barriers
than distributed PV and solar heating and cooling technologies.
Important barriers include: siting, permitting, and fi nancing challenges
to develop land with favourable solar resources for utility-scale projects;
lack of access to transmission lines for large projects far from electric
load centres; complex access laws, permitting procedures, and fees
for smaller-scale projects; lack of consistent interconnection standards
and time-varying utility rate structures that capture the value of distributed
generated electricity; inconsistent standards and certifi cations
and enforcement of these issues; and lack of regulatory structures that
capture environmental and risk-mitigation benefi ts across technologies.
Through appropriate policy designs, governments have shown that they
can support solar technologies by funding R&D and by providing incentives
to overcome economic barriers. Price-driven incentive frameworks,
for example, were popularized after FIT policies boosted levels of PV
deployment in Germany and Spain. Quota-driven frameworks such as
renewable portfolio standards and government bidding are common in
the USA and China, respectively. In addition to these regulatory frameworks,
fi scal policies and fi nancing mechanisms (e.g., tax credits, soft
loans and grants) are often employed to support the manufacturing of
solar goods and to increase consumer demand. Most successful solar
policies are tailored to the barriers imposed by specifi c applications, and
the most successful policies are those that send clear, long-term and
consistent signals to the market. [3.4.3]
3.5 Integration into the broader energy
system
Solar technologies have a number of attributes that allow their advantageous
integration into a broader energy system. In this section, only
the integration features unique to solar technologies are summarized.
These include low-capacity energy demand, district heating and other
thermal loads, PV generation characteristics and smoothing effects, and
CSP generation characteristics and grid stabilization. [3.5.1–3.5.4]
For applications that have low power consumption, such as lighting or
solar-derived hot water, solar technologies sometimes have a comparative
advantage relative to non-renewable fuel technologies. In addition,
solar technologies allow small decentralized applications as well as
larger centralized ones. In some regions of the world, integration of
solar energy into district heating and other thermal loads has proven
to be an effective strategy, especially because highly insulated buildings
can be heated effectively with relatively low-temperature energy carriers.
In some locations, a district cooling and heating system can provide
additional advantages compared to decentralized cooling, including
cost advantages for economies of scale, diversity of cooling demand of
different buildings, reducing noise and structural load, and equipment
space savings. Also, by combining biomass and low-temperature solar
thermal energy, system capacity factor and emissions profi les can be
improved. [3.5.1, 3.5.2]
For PV power generation at a specifi c location, electricity varies systematically
during a day and a year, but also randomly according to weather
conditions. This variation can, in some instances, have a large impact
on voltage and power fl ow in the local transmission and distribution
system from the early penetration stage, and the supply-demand balance
in total power system operation in the high-penetration stage. This
effect can potentially constrain PV system integration. However, modelling
and system simulations suggest that numerous PV systems in a
broad area should have less-random and slower variations, which are
sometimes referred to as the ‘smoothing effect’. Studies are underway
to evaluate and quantify actual smoothing effects at a large scale (1,000
sites at distances from 2 to 200 km) and at time scales of 1 minute or
less. [3.5.3]
In a CSP plant, even without storage, the inherent thermal mass in the
collector system and spinning mass in the turbine tend to signifi cantly
reduce the impact of rapid solar transients on electrical output, and thus,
lead to a reduced impact on the grid. By including integrated thermal
storage systems, capacity factors typical of base-load operation could be
achieved in the future. In addition, integrating CSP plants with fossil fuel
generators, especially with gas-fi red integrated solar combined-cycle
systems (with storage), can offer better fuel effi ciency and extended
operating hours and ultimately be more cost effective than operating
separate CSP and/or combined-cycle plants. [3.5.4]
3.6 Environmental and social impacts
3.6.1 Environmental impacts
Apart from its benefi ts in GHG reduction, the use of solar energy can
reduce the release of pollutants—such as particulates and noxious
gases—from the older fossil fuel plants that it replaces. Solar thermal
and PV technologies do not generate any type of solid, liquid or gaseous
by-products when producing electricity. The family of solar energy
technologies may create other types of air, water, land and ecosystem
impacts, depending on how they are managed. The PV industry uses
66
Technical Summary Summaries
some toxic, explosive gases as well as corrosive liquids in its production
lines. The presence and amount of those materials depend strongly on
the cell type. However, the intrinsic needs of the productive process of
the PV industry force the use of quite rigorous control methods that
minimize the emission of potentially hazardous elements during module
production. For other solar energy technologies, air and water pollution
impacts are generally expected to be relatively minor. Furthermore,
some solar technologies in certain regions may require water usage for
cleaning to maintain performance. [3.6.1]
Lifecycle assessment estimates of the GHGs associated with various
types of PV modules and CSP technologies are provided in Figure TS.3.4.
The majority of estimates for PV modules cluster between 30 and 80 g of
CO2eq/kWh. Lifecycle GHG emissions for CSP-generated electricity have
recently been estimated to range from about 14 to 32 g of CO2eq/kWh.
These emission levels are about an order of magnitude lower than those
of natural gas-fi red power plants. [3.6.1, 9.3.4]
Land use is another form of environmental impact. For roof-mounted
solar thermal and PV systems, this is not an issue, but it can be an issue
for central-station PV as well as for CSP. Environmentally sensitive lands
may pose a special challenge for CSP permitting. One difference for CSP
vis-à-vis PV is that it needs a method to cool the working fl uid, and
such cooling often involves the use of scarce water. Using local air as
the coolant (dry cooling) is a viable option, but this can decrease plant
effi ciency by 2 to 10%. [3.6.1]
3.6.2 Social impacts
The positive benefi ts of solar energy in the developing world provide
arguments for its expanded use. About 1.4 billion people do not have
access to electricity. Solar home systems and local PV-powered community
grids can provide electricity to many areas for which connection
to a main grid is cost prohibitive. The impact of electricity and solar
energy technologies on the local population is shown through a long
list of important benefi ts: the replacement of indoor-polluting kerosene
lamps and ineffi cient cook stoves; increased indoor reading; reduced
time gathering fi rewood for cooking (allowing the women and children
who normally gather it to focus on other priorities); street lighting for
security; improved health by providing refrigeration for vaccines and
food products; and, fi nally, communications devices (e.g., televisions,
radios). All of these provide a myriad of benefi ts that improve the lives
of people. [3.6.2]
Job creation is an important social consideration associated with
solar energy technology. Analysis indicates that solar PV has the highest
job-generating potential among the family of solar technologies.
Approximately 0.87 job-years per GWh are created through solar PV, followed
by CSP with 0.23 job-years per GWh. When properly put forward,
these job-related arguments can help accelerate social acceptance and
increase public willingness to tolerate the perceived disadvantages of
solar energy, such as visual impacts. [3.6.2]
3.7 Prospects for technology improvements
and innovation
Solar thermal: If integrated at the earliest stages of planning, buildings
of the future could have solar panels – including PV, thermal collector,
and combined PV-thermal (hybrids) – making up almost all viewed components
of the roof and façades. Such buildings could be established
not just through the personal desires of individual builders/owners, but
also as a result of public policy mandates, at least in some areas. For
example, the vision of the European Solar Thermal Technology Platform is
to establish the ‘Active Solar Building’ as a standard for new buildings by
2030, where an Active Solar Building, on average, covers all of its energy
demand for water heating and space conditioning. [3.7.2]
In highlighting the advances in passive solar, two climates can be distinguished
between: those that are dominated by the demand for heating
and those dominated by the demand for cooling. For the former, a widerscale
adoption of the following items can be foreseen: evacuated (as
opposed to sealed) glazing, dynamic exterior night-time insulation, and
translucent glazing systems that can automatically change solar/visible
transmittance and that also offer improved insulation values. For the
latter, there is the expectation for an increased use of cool roofs (i.e.,
light-coloured roofs that refl ect solar energy); heat-dissipation techniques
such as use of the ground and water as heat sinks; methods that
improve the microclimate around the buildings; and solar control devices
that allow penetration of the lighting, but not the thermal, component of
solar energy. For both climates, improved thermal storage is expected to
be embedded in building materials. Also anticipated are improved methods
for distributing the absorbed solar heat around the building and/
or to the outside air, perhaps using active methods such as fans. Finally,
improved design tools are expected to facilitate these various improved
methods. [3.7.1]
Photovoltaic electricity generation: Although now a relatively mature
technology, PV is still experiencing rapid improvements in performance
and cost, and a continuation of this steady progress is expected. The efforts
required are being taken up in a framework of intergovernmental cooperation,
complete with roadmaps. For the different PV technologies, four
broad technological categories, each requiring specifi c R&D approaches,
have been identifi ed: 1) cell effi ciency, stability, and lifetime; 2) module
productivity and manufacturing; 3) environmental sustainability; and 4)
applicability, all of which include standardization and harmonization.
Looking to the future, PV technologies can by categorized in three major
classes: current; emerging, which represent medium risk with a mid-term
(10 to 20 year) time line; and the high-risk technologies aimed at 2030
and beyond, which have extraordinary potential but require technical
breakthroughs. Examples of emerging cells are multiple-junction, polycrystalline
thin fi lms and crystalline silicon in the sub-100-μm thickness
range. Examples of high-risk cells are organic solar cells, biomimetic
devices and quantum dot designs that have the potential to substantially
increase the maximum effi ciency. Finally, there is important work to be
done on the balance of systems (BOS), which comprises inverters, storage,
charge controllers, system structures and the energy network. [3.7.3]
67
Summaries Technical Summary
Estimates:
References:
*same value
124
26
30
9
56
15
12
3
13
3
4
1
6
2
2*
2
1
1
Lifecycle GHG Emissions [g CO2 eq /kWh]
250
200
150
100
225
175
125
75
25
50
0
All Values Mono-Crystalline
Silicon (m-Si)
Poly-Crystalline
Silicon (p-Si)
Nano-Crystalline
Dye Sensitized
(DSC)
Concentrator Ribbon
Silicon
Cadmium
Selenide
Quantum Dot
(QDPV)
Amorphous
Silicon (a-Si)
Cadmium
Telluride
(CdTe)
Lifecycle GHG Emissions of Photovoltaic Technologies
Maximum
75th Percentile
Median
25th Percentile
Minimum
Single Estimates
Figure TS.3.4 | GHG emissions from the life cycles of (top) PV modules and (bottom)
CSP technologies. See Annex II for details of literature search and citations of literature
contributing to the estimates displayed. [Figures 3.14, 3.15]
Lifecycle GHG Emissions [g CO2 eq / kWh]
Estimates:
References:
110
100
90
80
70
60
50
40
30
All Values Trough Tower Stirling Fresnel
20
10
0
CSP Lifecycle GHG Emissions by Technology
4
1
4
3
14
5
20
7
42
13
Maximum
75th Percentile
Median
25th Percentile
Minimum
CSP electricity generation: Although CSP is now a proven technology
at the utility scale, technology advances are still taking place. As plants
are built, both mass production and economies of scale are leading to
cost reductions. There is scope for continuing improvement in solar-toelectricity
effi ciency, partly through higher collector temperatures. To
increase temperature and effi ciency, alternatives to the use of oil as the
heat-transfer fl uid—such as water (boiling in the receiver) or molten
salts—are being developed, permitting higher operating temperatures.
For central-receiver systems, the overall effi ciencies can be higher
because the operating temperatures are higher, and further improvements
are expected to achieve peak effi ciencies (solar to electricity)
almost twice those of existing systems, up to 35%. Trough technology
will benefi t from continuing advances in solar-selective surfaces,
and central receivers and dishes will benefi t from improved receiver/
absorber designs that afford high levels of solar irradiance at the focus.
Capital cost reduction is expected to come from the benefi ts of mass
production, economies of scale and learning from previous experience.
[3.7.4]
- ♦
I I
=
68
Technical Summary Summaries
Solar fuel production: Solar electrolysis using PV or CSP is available
for niche applications, but it remains costly. Many paths are being pursued
to develop a technology that will reduce the cost of solar fuels.
These include solid-oxide electrolysis cells, the photoelectrochemical
cell (which combines all the steps in solar electrolysis into a single
unit), advanced thermo-chemical processes, and photochemical and
photobiological processes—sometimes in combinations that integrate
artifi cial photosynthesis in man-made biomimetic systems and photobiological
hydrogen production in living organisms. [3.7.5]
Other potential future applications: Other methods under investigation
for producing electricity using solar thermal technologies
without an intermediate thermodynamic cycle include thermoelectric,
thermionic, magnetohydrodynamic and alkali-metal methods. Space
solar power, in which solar power collected in space is beamed via
microwaves to receiving antennae on the ground, has also been proposed.
[3.7.6]
3.8 Cost trends
Although the cost of solar energy varies widely by technology, application,
location and other factors, costs have been reduced signifi cantly
during the past 30 years, and technical advances and supportive public
policies continue to offer the potential for additional cost reductions.
The degree of continued innovation will have a signifi cant bearing on
the level of solar deployment. [3.7.2–3.7.5, 3.8.2–3.8.5]
Solar thermal: The economics of solar heating applications depend
on appropriate design of the system with regard to energy service
needs, which often involves the use of auxiliary energy sources. In some
regions, for example, in southern parts of China, solar water heating
(SWH) systems are cost competitive with traditional options. SWH systems
are generally more competitive in sunny regions, but this picture
changes for space heating based on its usually higher overall heating
load. In colder regions capital costs can be spread over a longer heating
season, and solar thermal can then become more competitive. [3.8.2]
The investment costs for solar thermal heating systems vary widely
depending on the complexity of the technology used as well as the market
conditions in the country of operation. The costs for an installed
system vary from as low as USD2005 83/m² for SWH systems in China
to more than USD2005 1,200/m² for certain space-heating systems. The
levelized cost of heat (LCOH) mirrors the wide variation in investment
cost, and depends on an even larger number of variables, including the
particular type of system, investment cost of the system, available solar
irradiance in a particular location, conversion effi ciency of the system,
operating costs, utilization strategy of the system and the applied discount
rate. Based on a standardized methodology outlined in Annex II
and the cost and performance data summarized in Annex III, the LCOH
for solar thermal systems over a large set and range of input parameters
has been calculated to vary widely from USD2005 9 to 200/GJ, but
can be estimated for more specifi c settings with parametric analysis.
Figure TS.3.5 shows the LCOH over a somewhat narrower set and range
of input parameters. More specifi cally, the fi gure shows that for SWH
systems with costs in the range of USD2005 1,100 to 1,200/kWth and conversion
effi ciencies of roughly 40%, LCOH is expected to range from
slightly more than USD2005 30/GJ to slightly less than USD2005 50/GJ in
regions comparable to Central and Southern European locations and
up to almost USD2005 90/GJ for regions with less solar irradiation. Not
surprisingly, LCOH estimates are highly sensitive to all of the parameters
shown in Figure TS.3.5, including investment costs and capacity factors.
[3.8.2, Annex II, Annex III]
Over the last decade, for each 50% increase in installed capacity of solar
water heaters, investment costs have fallen 20% in Europe. According
to the IEA, further cost reductions in OECD countries will come from
the use of cheaper materials, improved manufacturing processes, mass
production, and the direct integration into buildings of collectors as
multi-functional building components and modular, easy-to-install systems.
Delivered energy costs in OECD countries are anticipated by the
IEA to eventually decline by around 70 to 75%. [3.8.2]
PV electricity generation: PV prices have decreased by more than a
factor of 10 during the last 30 years; however, the current levelized cost
of electricity (LCOE) from solar PV is generally still higher than wholesale
market prices for electricity. In some applications, PV systems are
already competitive with other local alternatives (e.g., for electricity supply
in certain rural areas in developing countries ). [3.8.3, 8.2.5, 9.3.2]
The LCOE of PV highly depends on the cost of individual system components,
with the highest cost share stemming from the PV module.
The LCOE also includes BOS components, cost of labour for installation,
operation and maintenance (O&M) cost, location and capacity factor,
and the applied discount rate. [3.8.3]
The price for PV modules dropped from USD2005 22/W in 1980 to less
than USD2005 1.50/W in 2010. The corresponding historical learning rate
ranges from 11 to 26%, with a median learning rate of 20%. The price in
USD/W for an entire system, including the module, BOS, and installation
costs, has also decreased steadily, reaching numbers as low as USD2005
2.72/W for some thin-fi lm technologies by 2009. [3.8.3]
The LCOE for PV depends not only on the initial investment; it also takes
into account operation costs and the lifetime of the system components,
local solar irradiation levels and system performance. Based on the
standardized methodology outlined in Annex II and the cost and performance
data summarized in Annex III, the recent LCOE for different
types of PV systems has been calculated. It shows a wide variation from
as low as USD2005 0.074/kWh to as high as USD2005 0.92/kWh, depending
on a large set and range of input parameters. Narrowing the range
of parameter variations, the LCOE in 2009 for utility-scale PV electricity
generation in regions of high solar irradiance in Europe and the USA
were in the range of about USD2005 0.15/kWh to USD2005 0.4/kWh at a
69
Summaries Technical Summary
7% discount rate, but may be lower or higher depending on the available
resource and on other framework conditions. Figure TS.3.6 shows a
wide variation of LCOE for PV depending on the type of system, investment
cost, discount rates and capacity factors. [1.3.2, 3.8.3, 10.5.1,
Annex II, Annex III]
Costs of electricity generation or LCOE are projected by the IEA to reach
the following in 2020: US cent2005 14.5/kWh to US cent2005 28.6/kWh
for the residential sector and US cent2005 9.5/kWh to US cent2005 19/
kWh for the utility sector under favourable conditions of 2,000 kWh/
kW (equivalent to a 22.8% capacity factor) and less favourable conditions
of 1,000 kWh/kW (equivalent to a 11.4% capacity factor),
respectively. The goal of the US Department of Energy is even more
ambitious, with an LCOE goal of US cent2005 5/kWh to US cent2005 10/
kWh, depending on the end user, by 2015. [3.8.3]
CSP electricity generation: CSP electricity systems are a complex
technology operating in a complex resource and fi nancial environment;
so many factors affect the LCOE. The publicized investment
costs of CSP plants are often confused when compared to other
renewable sources, because varying levels of integrated thermal
storage increase the investment, but also improve the annual output
and capacity factor of the plant. For large, state-of-the-art trough
plants, current investment costs are estimated to be USD2005 3.82/W
(without storage) to USD2005 7.65/W (with storage) depending on
labour and land costs, technologies, the amount and distribution of
beam irradiance and, above all, the amount of storage and the size of
the solar fi eld. Performance data for modern CSP plants are limited,
particularly for plants equipped with thermal storage, because new
plants only became operational from 2007 onward. Capacity factors
for early plants without storage were up to 28%. For modern plants
without storage, capacity factors of roughly 20 to 30% are envisioned;
for plants with thermal storage, capacity factors of 30 to 75% may be
achieved. Based on the standardized methodology outlined in Annex
II and the cost and performance data summarized in Annex III, the
LCOE for a solar trough plant with six hours of thermal storage in
2009 over a large set and range of input parameters has been calculated
to range from slightly more than US cent2005 10/kWh to about US
cent2005 30/kWh. Restricting the range of discount rates to 10% results
in a somewhat narrower range of about US cent2005 20/kWh to US
cent2005 30/kWh, which is roughly in line with the range of US cent2005
18 to US cent2005 27/kWh available in the literature. Particular cost Levelized Cost of Heat [
USD2005 /
GJ]
Capacity Factor [%]
4 5 6 7 8 9 10 11 12 13
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
Solar Thermal Heat (DHW, China), 540 USD/kWth
Solar Thermal Heat (DHW, China), 330 USD/kWth
Solar Thermal Heat (DHW, China), 120 USD/kWth
Solar Thermal Heat (DHW, Thermo-Siphon, Combi), 1800 USD/kWth
Solar Thermal Heat (DHW, Thermo-Siphon, Combi), 1165 USD/kWth
Solar Thermal Heat (DHW, Thermo-Siphon, Combi), 530 USD/kWth
Solar Irradiation: 800 kWh/m²/a;
Conversion Efficiency/Degree of
Utilization: 35%
Solar Irradiation: 1000 kWh/m²/a;
Conversion Efficiency/Degree of
Utilization: 77% or
Solar Irradiation: 2200 kWh/m²/a;
Conversion Efficiency/Degree of
Utilization: 35%
Solar Irradiation: 800 kWh/m²/a;
Conversion Efficiency/Degree of
Utilization: 60% or
Solar Irradiation: 1200 kWh/m²/a;
Conversion Efficiency/Degree of
Utilization: 40%
Figure TS.3.5 | Sensitivity of levelized cost of heat with respect to investment cost as a function of capacity factor. (Discount rate assumed to be 7%, annual operation and maintenance
cost USD2005 5.6 and14/kW, and lifetimes set at 12.5 and 20 years for domestic hot water (DHW) systems in China and various types of systems in OECD countries, respectively.)
[Figure 3.16]
'' '' .. ' ' '' '' '
·····' - ' ,,,,, '' '
- - - - -
' -, ''
- ·' ---
70
Technical Summary Summaries
Figure TS.3.6 | Levelized cost of PV electricity generation, 2008–2009: (top) as a function of capacity factor and investment cost*,***; and (bottom) as a function of capacity factor
and discount rate**,***. [Figure 3.19]
Notes: * Discount rate assumed to equal 7%. ** Investment cost for residential rooftop systems assumed at USD 5,500 US/kW, for commercial rooftop systems at USD 5,150, for
utility-scale fi xed tilt projects at USD 3,650/kW and for utility-scale one-axis projects at USD 4,050/kW. ***Annual O&M cost assumed at USD 41 to 64/kW, lifetime at 25 years.
and performance parameters, including the applied discount rate and
capacity factor, affect the specifi c LCOE estimate, although the LCOE
of different system confi gurations for otherwise identical conditions
are expected to differ only marginally. [3.8.4]
Capacity Factor [%]
0
10
20
30
40
50
60
70
11% 13% 15% 17% 19% 21% 23% 25% 27%
Levelized Cost of Energy [US cent2005 /kWh]
PV (residential rooftop), USD2005 3700
PV (residential rooftop), USD2005 5250
PV (residential rooftop), USD2005 6800
PV (commercial rooftop), USD2005 3500
PV (commerical rooftop), USD2005 5050
PV (commercial rooftop), USD2005 6600
PV (utility scale, fixed tilt), USD2005 2700
PV (utility scale, fixed tilt), USD2005 3950
PV (utility scale, fixed tilt), USD2005 5200
PV (utility scale, 1-axis), USD2005 3100
PV (utility scale, 1-axis), USD2005 4650
PV (utility scale, 1-axis), USD2005 6200
0
10
20
30
40
50
60
70
80
11% 13% 15% 17% 19% 21% 23% 25% 27%
Levelized Cost of Energy [US cent2005 /kWh]
PV - residential rooftop, Discount Rate = 3%
PV - residential rooftop, Discount Rate = 7%
PV - residential rooftop, Discount Rate = 10%
PV - commerical rooftop, Discount Rate = 3%
PV - commerical rooftop, Discount Rate = 7%
PV - commerical rooftop, Discount Rate = 10%
PV - utility scale, fixed tilt, Discount Rate = 3%
PV - utility scale, fixed tilt, Discount Rate = 7%
PV - utility scale, fixed tilt, Discount Rate = 10%
PV - utility scale, 1-axis, Discount Rate = 3%
PV - utility scale, 1-axis, Discount Rate = 7%
PV - utility scale, 1-axis, Discount Rate = 10%
--
""zw......................................................................
---- ---
- __
- -- - -
71
Summaries Technical Summary
The learning ratio for CSP, excluding the power block, has been estimated
at 10 ± 5%. Specifi c LCOE goals for the USA are US cent2005 6/kWh to US
cent2005 8/kWh with 6 hours storage by 2015 and US cent2005 50/kWh to
US cent2005 60/kWh with 12 to 17 hours of storage by 2020. The EU is
pursuing similar goals. [3.8.4]
3.9 Potential deployment
3.9.1 Near-term (2020) forecasts
Table TS.3.1 summarizes fi ndings from the available studies on potential
deployment up to 2020, as taken from the literature. Sources for the
tabulated data are the following: European Renewable Energy Council
(EREC) – Greenpeace (Energy [r]evolution, reference and advanced scenarios);
and IEA (CSP and PV Technology Roadmaps). With regard to
the solar thermal entries, note that passive solar contributions are not
included in these data; although this technology reduces the demand for
energy, it is not part of the supply chain considered in energy statistics.
[3.9]
3.9.2 Long-term deployment in the context of carbon
mitigation
Figure TS.3.7 presents the results of more than 150 long-term modelling
scenarios described in Chapter 10. The potential deployment scenarios
vary widely—from direct solar energy playing a marginal role in 2050 to
it becoming one of the major sources of energy supply. Although direct
solar energy today provides only a very small fraction of the world energy
supply, it remains undisputed that this energy source has one of the largest
potential futures.
Reducing cost is a key issue in making direct solar energy more commercially
relevant and in position to claim a larger share of the worldwide
energy market. This can only be achieved if solar technologies’ costs
are reduced as they move along their learning curves, which depend
primarily on market volumes. In addition, continuous R&D efforts are
required to ensure that the slopes of the learning curves do not fl atten
too early. The true costs of deploying solar energy are still unknown
because the main deployment scenarios that exist today consider
only a single technology. These scenarios do not take into account the
co-benefi ts of a renewable/sustainable energy supply via a range of
different RE sources and energy effi ciency measures.
Potential deployment depends on the actual resources and availability
of the respective technology. However, to a large extent, the regulatory
and legal framework in place can foster or hinder the uptake of direct
solar energy applications. Minimum building standards with respect to
building orientation and insulation can reduce the energy demand of
buildings signifi cantly and can increase the share of RE supply without
increasing the overall demand. Transparent, streamlined administrative
procedures to install and connect solar power sources to existing grid
infrastructures can further lower the cost related to direct solar energy.
4. Geothermal Energy
4.1 Introduction
Geothermal resources consist of thermal energy from the Earth’s interior
stored in both rock and trapped steam or liquid water, and are used to
generate electric energy in a thermal power plant or in other domestic
and agro-industrial applications requiring heat as well as in CHP applications.
Climate change has no signifi cant impacts on the effectiveness of
geothermal energy. [4.1]
Geothermal energy is a renewable resource as the tapped heat from
an active reservoir is continuously restored by natural heat production,
conduction and convection from surrounding hotter regions, and the
extracted geothermal fl uids are replenished by natural recharge and by
reinjection of the cooled fl uids. [4.1]
Table TS.3.1 | Evolution of cumulative solar capacities. [Table 3.7]
Low-Temperature Solar Heat
(GWth)
Solar PV Electricity (GW) CSP Electricity (GW)
Year 2009 2015 2020 2009 2015 2020 2009 2015 2020
Name of Scenario
Current cumulative installed capacity 180 22 0.7
EREC – Greenpeace (reference scenario) 180 230 44 80 5 12
EREC – Greenpeace ([r]evolution scenario) 715 1,875 98 335 25 105
EREC – Greenpeace (advanced scenario) 780 2,210 108 439 30 225
IEA Roadmaps N/A 951 210 N/A 148
Note: 1. Extrapolated from average 2010 to 2020 growth rate.
72
Technical Summary Summaries
0
10
20
30
40
50
60
Global CSP Electricity Generation [EJ/yr]
2020 2030 2050
0
50
100
150
(a) Global Solar Primary Energy Supply
Global Solar Primary Energy Supply [EJ/yr]
N=156
2020 2030 2050
50
60
(b) Global Solar Thermal Heat Generation
Global Solar Thermal Heat Generation [EJ/yr]
N=44
2020 2030 2050
0
20
40
60
80
100
(c) Global Solar PV Electricity Generation
Global Solar PV Electricity Generation [EJ/yr]
N=123
2020 2030 2050
(d) Global CSP Electricity Generation
N=59
0
10
20
30
40
CO2 Concentration Levels
Baselines
Cat. III + IV (440−600 ppm)
Cat. I + II (<440 ppm)
Figure TS.3.7 | Global solar supply and generation in long-term scenarios (median, 25th to 75th percentile range, and full range of scenario results; colour coding is based on categories
of atmospheric CO2 concentration level in 2100; the specifi c number of scenarios underlying the fi gure is indicated in the upper right-hand corner). (a) Global solar primary
energy supply; (b) global solar thermal heat generation; (c) global solar PV electricity generation; and (d) global CSP electricity generation. [Figure 3.22]
4.2 Resource potential
The accessible stored heat from hot dry rocks in the Earth is estimated to
range from 110 to 403 x 106 EJ down to 10 km depth, 56 to 140 x 106 EJ
down to 5 km depth, and around 34 x 106 EJ down to 3 km depth. Using previous
estimates for hydrothermal resources and calculations for enhanced
(or engineered) geothermal systems derived from stored heat estimates at
depth, geothermal technical potentials for electric generation range from
118 to 146 EJ/yr (at 3 km depth) to 318 to 1,109 EJ/yr (at 10 km depth), and
for direct uses range from 10 to 312 EJ/yr (Figure TS.4.1). [4.2.1]
Technical potentials are presented on a regional basis in Table TS.4.1.
The regional breakdown is based on the methodology applied by the
Electric Power Research Institute to estimate theoretical geothermal
■
■
■
73
Summaries Technical Summary
potentials for each country, and then countries are grouped regionally.
Thus, the present disaggregation of global technical potential is based
on factors accounting for regional variations in the average geothermal
gradient and the presence of either a diffuse geothermal anomaly or a
high-temperature region associated with volcanism or plate boundaries.
The separation into electric and thermal (direct uses) potentials is
somewhat arbitrary in that most higher-temperature resources could be
used for either, or both, in CHP applications depending on local market
conditions. [4.2.2]
The heat extracted to achieve the technical potentials can be fully or
partially replenished over the long term by the continental terrestrial
heat fl ow of 315 EJ/yr at an average fl ux of 65 mW/m2. [4.2.1]
4.3 Technology and applications
Geothermal energy is currently extracted using wells and other means
that produce hot fl uids from: (a) hydrothermal reservoirs with naturally
high permeability, or (b) Enhanced or engineered geothermal systems
(EGS) with artifi cial fl uid pathways (Figure TS.4.2). Technology for electricity
generation from hydrothermal reservoirs is mature and reliable,
and has been operating for about 100 years. Technologies for direct
heating using geothermal heat pumps (GHPs) for district heating and
for other applications are also mature. Technologies for EGS are in the
demonstration stage. [4.3]
Electric power from geothermal energy is especially suitable for supplying
base-load power, but also can be dispatched and used to meet peak
demand. Hence, geothermal electric power can complement variable
electricity generation. [4.3]
Since geothermal resources are underground, exploration methods
(including geological, geochemical and geophysical surveys) have been
developed to locate and assess them. The objectives of geothermal
exploration are to identify and rank prospective geothermal reservoirs
prior to drilling. Today, geothermal wells are drilled over a range of
depths up to 5 km using conventional rotary drilling methods similar
to those for accessing oil and gas reservoirs. Advanced drilling technologies
allow for high-temperature operation and provide directional
capability. [4.3.1]
The basic types of geothermal power plants in use today are steam condensing
turbines and binary cycle units. Condensing plants can be of
the fl ash or dry-steam type (the latter do not require brine separation,
resulting in simpler and cheaper plants) and are more common than
binary units. They are installed in intermediate- and high-temperature
resources (≥150°C) with capacities often between 20 and 110 MWe.
Depth [km]
Min
Max
0
200
400
600
800
1000
1200
10 5 3 Direct Uses
Electricity Thermal
Electric or Thermal [EJ/yr]
Figure TS.4.1 | Geothermal technical potentials for electricity and direct uses (heat). Direct
uses usually do not require development to depths greater than about three km. [Figure 4.2]
Table TS.4.1 | Geothermal technical potentials on continents for the IEA regions. [Table 4.3]
REGION1
Electric technical potential (EJ/yr) at depths to: Technical potentials (EJ/yr) for
3 km 5 km 10 km direct uses
Lower Upper Lower Upper Lower Upper Lower Upper
OECD North America 25.6 31.8 38.0 91.9 69.3 241.9 2.1 68.1
Latin America 15.5 19.3 23.0 55.7 42.0 146.5 1.3 41.3
OECD Europe 6.0 7.5 8.9 21.6 16.3 56.8 0.5 16.0
Africa 16.8 20.8 24.8 60.0 45.3 158.0 1.4 44.5
Transition Economies 19.5 24.3 29.0 70.0 52.8 184.4 1.6 51.9
Middle East 3.7 4.6 5.5 13.4 10.1 35.2 0.3 9.9
Developing Asia 22.9 28.5 34.2 82.4 62.1 216.9 1.8 61.0
OECD Pacifi c 7.3 9.1 10.8 26.2 19.7 68.9 0.6 19.4
Total 117.5 145.9 174.3 421.0 317.5 1,108.6 9.5 312.2
Note: 1. For regional defi nitions and country groupings see Annex II.
I -1- · •
I I
-
-
-
-
74
Technical Summary Summaries
In binary cycle plants, the geothermal fl uid passes through a heat
exchanger heating another working fl uid with a low boiling point, which
vaporizes and drives a turbine. They allow for use of lower-temperature
hydrothermal reservoirs and of EGS reservoirs (generally from 70°C to
170°C), and are often constructed as linked modular units of a few MWe in
capacity. Combined or hybrid plants comprise two or more of the above basic
types to improve versatility, increase overall thermal effi ciency, improve loadfollowing
capability, and effi ciently cover a wide resource temperature range.
Finally, cogeneration plants, or CHP plants, produce both electricity and hot
water for direct use. [4.3.3]
EGS reservoirs require stimulation of subsurface regions where temperatures
are high enough for effective utilization. A reservoir consisting of a fracture
network is created or enhanced to provide well-connected fl uid pathways
between injection and production wells. Heat is extracted by circulating
water through the reservoir in a closed loop and can be used for power generation
and for industrial or residential heating (see Figure TS.4.2). [4.3.4]
Direct use provides heating and cooling for buildings including district
heating, fi sh ponds, greenhouses, bathing, wellness and swimming
pools, water purifi cation/desalination and industrial and process heat
for agricultural products and mineral drying. Although it can be debated
whether GHPs are a ‘true’ application of geothermal energy, they can be
utilized almost anywhere in the world for heating and cooling, and take
advantage of the relatively constant ground or groundwater temperature
in the range of 4°C to 30°C. [4.3.5]
4.4 Global and regional status of market
and industry development
For nearly a century, geothermal resources have been used to generate
electricity. In 2009, the global geothermal electric market had a wide
range of participants with 10.7 GWe of installed capacity. Over 67 TWhe
(0.24 EJ) of electricity were generated in 2008 in 24 countries (Figure
TS.4.3), and provided more than 10% of total electricity demand in 6
of them. There were also 50.6 GWth of direct geothermal applications
operating in 78 countries, which generated 121.7 TWhth (0.44 EJ) of heat
in 2008. GHPs contributed 70% (35.2 GWth) of this installed capacity for
direct use. [4.4.1, 4.4.3]
The global average annual growth rate of installed geothermal electric
capacity over the last fi ve years (2005-2010) was 3.7%, and over the
last 40 years (1970-2010), 7.0%. For geothermal direct uses rates were
12.7% (2005-2010), and 11% between 1975 and 2010. [4.4.1]
EGS is still in the demonstration phase, with one small plant in operation
in France and one pilot project in Germany. In Australia considerable
investment has been made in EGS exploration and development
in recent years, and the USA has recently increased support for EGS
research, development and demonstration as part of a revived national
geothermal programme. [4.4.2]
In 2009, the main types (and relative percentages) of direct geothermal
applications in annual energy use were: space heating of buildings
(63%), bathing and balneology (25%), horticulture (greenhouses and
soil heating) (5%), industrial process heat and agricultural drying (3%),
aquaculture (fi sh farming) (3%) and snow melting (1%). [4.4.3]
For geothermal to reach its full capacity in climate change mitigation
it is necessary to overcome technical and non-technical barriers. Policy
measures specifi c to geothermal technology can help overcome these
barriers. [4.4.4]
4.5 Environmental and social impacts
Environmental and social impacts related to geothermal energy do exist,
and are typically site- and technology-specifi c. Usually, these impacts
are manageable, and the negative environmental impacts are minor.
The main GHG emission from geothermal operations is CO2, although
it is not created through combustion, but emitted from naturally occurring
sources. A fi eld survey of geothermal power plants operating in
2001 found a wide spread in the direct CO2 emission rates, with values
ranging from 4 to 740 g/kWhe depending on technology design
and composition of the geothermal fl uid in the underground reservoir.
Direct CO2 emissions for direct use applications are negligible, while
EGS power plants are likely to be designed as liquid-phase closed-loop
circulation systems, with zero direct emissions. Lifecycle assessments
anticipate that CO2-equivalent emissions are less than 50 g/kWhe for
geothermal power plants; less than 80 g/kWhe for projected EGS; and
Heat Source
Confined
Permeable
Reservoir
Vapour Dominated
Geothermal System
Liquid Dominated
Geothermal System
Geyser Hot Spring
Impermeable
Rocks
Permeable
Rocks
Impermeable Rocks
Natural
Fracture
or Joint
(a)
Figure TS.4.2a | Scheme showing convective (hydrothermal) resources. [Figure 4.1a] ••••••
75
Summaries Technical Summary
Reservoir
Monitoring
Rechange
Reservoir
ORC or
Kalina
Cycle
District
Heating
Power
Cooling
Unit
Monitoring
Well
Monitoring
Well
Enhanced
Reservoir
3 km to 10 km
~ 0.5 - 1.5 km
Injection
Well
Production
Wells
Heat
Exchanger
(b)
Figure TS.4.2b | Scheme showing conductive (EGS) resources. [Figure 4.1b]
76
Technical Summary Summaries
United States
Philippines
Indonesia
Mexico
Italy
N. Zealand
Iceland
Japan
El Salvador
Kenya
Costa Rica
Nicaragua
Turkey
Russia
Papua-N.G.
Guatemala
Portugal
China
France
Ethiopia
Germany
Austria
Thailand
Australia
2,750
2,250
1,750
1,250
750
250
3,750
3,500
3,250
3,000
2,500
2,000
1,500
1,000
500
Geothermal-Electric Installed Capacity [MW]
0 40 50 60 70 80 90 100 110 150
3,094
1,904
1,197
Total: 10,715 MW
[mW/m2]
Figure TS.4.3 | Geothermal electric installed capacity by country in 2009. Figure shows worldwide average heat fl ow in mW/m2 and tectonic plate boundaries. [Figure 4.5]
between 14 and 202 g/kWhth for district heating systems and GHPs.
[4.5, 4.5.1, 4.5.2]
Environmental impacts associated with geothermal projects involve
consideration of a range of local air, land and water use impacts during
both construction and operational phases that are common to most
energy projects as well as specifi c to geothermal energy. Geothermal
systems involve natural phenomena, and typically discharge gases
mixed with steam from surface features, and minerals dissolved in
water from hot springs. Some gases may be dangerous, but are typically
either treated or monitored during production. In the past, surface disposal
of separated water was more common, but today happens only
in exceptional circumstances. Geothermal brine is usually injected back
into the reservoir to support reservoir pressures and to avoid adverse
environmental effects. Surface disposal, if signifi cantly in excess of natural
hot-spring fl ow rates, and if not strongly diluted, can have adverse
effects on the ecology of rivers, lakes or marine environments. [4.5.3.1]
Local hazards arising from natural phenomena, such as micro-earthquakes,
hydrothermal steam eruptions and ground subsidence may be infl uenced
by the operation of geothermal fi elds. During 100 years of development,
no buildings or structures within a geothermal operation or local community
have been signifi cantly damaged by shallow earthquakes originating
from either geothermal production or injection activities. Some EGS demonstration
projects, particularly in populated areas of Europe, have raised
social opposition. The process of high-pressure injection of cold water
into hot rock generates small seismic events. Induced seismic events
have not been large enough to lead to human injury or signifi cant property
damage, but proper management of this issue will be an important
step to facilitating signifi cant expansion of future EGS projects. [4.5.3.2]
Land use requirements range from 160 to 290 m²/GWhe/yr excluding
wells, and up to 900 m²/GWh/yr including wells. Specifi c geothermal
impacts on land use include effects on outstanding natural features such
as springs, geysers and fumaroles. Land use issues in many settings (e.g.,
Japan, the USA and New Zealand) can be a serious impediment to further
expansion of geothermal development. [4.5.3.3]
Geothermal resources may also have signifi cant environmental advantages
compared to the energy use they otherwise offset. [4.5.1]
0
c
0 e
_:;:i_l--'-------u:,---;L === o {3
0o
77
Summaries Technical Summary
4.6 Prospects for technology improvement,
innovation and integration
Geothermal resources can be integrated into all types of electrical power
supply systems, from large, interconnected continental transmission
grids to onsite use in small, isolated villages or autonomous buildings.
Since geothermal energy typically provides base-load electric generation,
integration of new power plants into existing power systems does
not present a major challenge. For geothermal direct uses, no integration
problems have been observed, and for heating and cooling, geothermal
energy (including GHPs) is already widespread at the domestic, community
and district scales. Section 8 of this summary addresses integration
issues in greater depth. [4.6]
Several prospects for technology improvement and innovation can
reduce the cost of producing geothermal energy and lead to higher
energy recovery, longer fi eld and plant lifetimes, and better reliability.
Advanced geophysical surveys, injection optimization, scaling/corrosion
inhibition, and better reservoir simulation modelling will help reduce
the resource risks by better matching installed capacity to sustainable
generation capacity. [4.6]
In exploration, R&D is required to locate hidden geothermal systems
(e.g., with no surface manifestations) and for EGS prospects.
Refi nement and wider usage of rapid reconnaissance geothermal tools
such as satellite- and airborne-based hyper-spectral, thermal infrared,
high-resolution panchromatic and radar sensors could make exploration
efforts more effective. [4.6.1]
Special research in drilling and well construction technology is needed
to improve the rate of penetration when drilling hard rock and to
develop advanced slim-hole technologies, with the general objectives of
reducing the cost and increasing the useful life of geothermal production
facilities. [4.6.1]
The effi ciency of the different system components of geothermal power
plants and direct uses can still be improved, and it is important to
develop conversion systems that more effi ciently utilize the energy in
the produced geothermal fl uid. Another possibility is the use of suitable
oil and gas wells potentially capable of supplying geothermal energy for
power generation. [4.6.2]
EGS projects are currently at a demonstration and experimental stage.
EGS require innovative methods to hydraulically stimulate reservoir connectivity
between injection and production wells to attain sustained,
commercial production rates while reducing the risk of seismic hazard,
and to improve numerical simulators and assessment methods to enable
reliable predictions of chemical interaction between geo-fl uids and geothermal
reservoirs rocks. The possibility of using CO2 as a working fl uid
in geothermal reservoirs, particularly in EGS, is also under investigation
since it could provide a means for enhancing the effect of geothermal
energy deployment, lowering CO2 emissions beyond just generating
electricity with a carbon-free renewable resource. [4.6.3]
Currently there are no technologies in use to tap submarine geothermal
resources, but in theory electrical energy could be produced directly
from a hydrothermal vent. [4.6.4]
4.7 Cost trends
Geothermal projects typically have high upfront investment costs, due
to the need to drill wells and construct power plants, and relatively
low operational costs. Though costs vary by project, the LCOE of power
plants using hydrothermal resources are often competitive in today’s
electricity markets; the same is true for direct uses of geothermal heat.
EGS plants remain in the demonstration phase, but estimates of EGS
costs are higher than those for hydrothermal reservoirs. [4.7]
The investment costs of a typical geothermal electric project are: (a)
exploration and resource confi rmation (10 to 15% of the total); (b) drilling
of production and injection wells (20 to 35% of the total); (c) surface
facilities and infrastructure (10 to 20% of the total); and (d) power
plant (40 to 81% of the total). Current investment costs vary worldwide
between USD2005 1,800 and 5,200/kWe. [4.7.1]
Geothermal electric O&M costs, including make-up wells (i.e., new wells
to replace failed wells and restore lost production or injection capacity),
have been calculated to be USD2005 152 to 187/kWe/yr, but in some
countries can be signifi cantly lower (e.g., USD2005 83 to 117/kWe/yr in
New Zealand). [4.7.2]
Power plant longevity and capacity factor are also important economic
parameters. The worldwide capacity factor average in 2008 for existing
geothermal power plants was 74.5%, with newer installations above
90%. [4.7.3]
Based on a standardized methodology outlined in Annex II and the cost
and performance data summarized in Annex III, the LCOE for hydrothermal
geothermal projects over a large set and range of input parameters
has been calculated to range from US cents2005 3.1/kWh to US cents2005
17/kWh, depending on the particular type of technology and projectspecifi
c conditions. Using a narrower set and range of parameters, Figure
TS.4.4 shows that, at a 7% discount rate, recently installed green-fi eld
hydrothermal projects operating at the global average capacity factor of
74.5% (and under other conditions specifi ed in [4.7.4]) have LCOE in the
range from US cents2005 4.9/kWh to US cents2005 7.2/kWh for condensing
fl ash plants and, for binary cycle plants, from US cents2005 5.3/kWh
to US cents2005 9.2/kWh. The LCOE is shown to vary substantially with
capacity factor, investment cost and discount rate. No LCOE data exist
for EGS, but some projections have been made using different models
for several cases with diverse temperatures and depths, for example, US
cents2005 10/kWh to US cents2005 17.5/kWh for relatively high-grade EGS
resources. [1.3.2, 4.7.4, 10.5.1, Annex II, Annex III]
Estimates of possible cost reductions from design changes and technical
advances rely solely on expert knowledge of the geothermal process
78
Technical Summary Summaries
value chain, as published learning curve studies are limited. Engineering
improvements in design and stimulation of geothermal reservoirs, and
improvements in materials, operation and maintenance are expected to
have the greatest impact on LCOE in the near term, for example, leading
to higher capacity factors and a lower contribution of drilling cost
to overall investment costs. For green-fi eld projects in 2020, the worldwide
average projected LCOE is expected to range from US cents2005 4.5/
kWh to US cents2005 6.6/kWh for condensing fl ash plants and from US
cents2005 4.9/kWh to US cents2005 8.6/kWh for binary cycle plants ranges,
given an average worldwide capacity factor of 80%, a 27.5-year lifetime
and a discount rate of 7%. Therefore, a global average LCOE reduction
of about 7% is expected for geothermal fl ash and binary plants
by 2020. Future costs of EGS are expected to decline to lower levels as
well. [4.7.5]
The LCOH for direct-use projects has a wide range, depending upon
specifi c use, temperature and fl ow rate required, associated O&M and
labour costs, and output of the produced product. In addition, costs
for new construction are usually less than costs for retrofi tting older
structures. The cost fi gures given in Table TS.4.2 are based on a climate
typical of the northern half of the USA or Europe. Heating loads would
be higher for more northerly climates such as Iceland, Scandinavia and
Russia. Most fi gures are based on cost in the USA, but would be similar
in developed countries and lower in developing countries. [4.7.6]
Industrial applications are more diffi cult to quantify, as they vary widely
depending upon the energy requirements and the product to be produced.
These plants normally require higher temperatures and often
compete with power plant use; however, they do have a high load
factor of 0.40 to 0.70, which improves the economics. Industrial applications
vary from large food, timber and mineral drying plants (USA
and New Zealand) to pulp and paper plants (New Zealand). [4.7.6]
4.8 Potential deployment
Geothermal energy can contribute to near- and long-term carbon emissions
reduction. In 2008, global geothermal energy use represented only
about 0.1% of the global primary energy supply. However, by 2050, geothermal
could meet roughly 3% of the global electricity demand and 5%
of the global demand for heating and cooling. [4.8]
Taking into account the geothermal electric projects under construction
or planned in the world, installed geothermal capacity is expected to
reach 18.5 GWe by 2015. Practically all the new power plants expected
to be on line by 2015 will be fl ash-condensing and binary utilizing
hydrothermal resources, with a small contribution from EGS projects.
Geothermal direct uses (heat applications including GHP) are expected
to grow at the same historic annual rate (11% between 1975 and 2010)
to reach 85.2 GWth. By 2015, total electric generation could reach 121.6
TWh/yr (0.44 EJ/yr) while direct generation of heat could reach 224
TWhth/yr (0.8 EJ/yr), with the regional breakdown presented in Table
TS.4.3. [4.8.1]
The long-term potential deployment of geothermal energy based on
a comprehensive assessment of numerous model-based scenarios is
mentioned in Section 10 of this summary and spans a broad range. The
scenario medians for three GHG concentration stabilization ranges, based
Global Average in 2008
(a) (b)
Levelized Cost of Energy [UScent2005 /kWh]
Capacity Factor [%]
60 65 70 75 80 85 90
Geothermal (Condensing-Flash), USD2005 1,800
5
6
7
8
9
10
11
13 13
12
4
0
Geothermal (Binary Cycle), USD2005 5,200
Geothermal (Condensing-Flash), USD2005 2,700
Geothermal (Condensing-Flash), USD2005 3,600
Geothermal (Binary Cycle), USD2005 2,100
Geothermal (Binary Cycle), USD2005 3,650
Levelized Cost of Energy [UScent2005 /kWh]
Capacity Factor [%]
60 65 70 75 80 85 90
Geothermal (Condensing-Flash), Discount Rate = 3%
5
6
7
8
9
10
11
12
4
0
Geothermal (Binary Cycle), Discount Rate = 10%
Geothermal (Condensing-Flash), Discount Rate = 7%
Geothermal (Condensing-Flash), Discount Rate = 10%
Geothermal (Binary Cycle), Discount Rate = 3%
Geothermal (Binary Cycle), Discount Rate = 7%
Figure TS.4.4 | Levelized cost of geothermal power, 2008: a) as a function of capacity factor and cost*,***; and b) as a function of capacity factor and discount rate**,***. [Figure 4.8]
Notes: * Discount rate assumed to equal 7%. ** Investment cost for condensing fl ash plants assumed at USD 2,700/kW and for binary-cycle plants at USD 3,650/kW. ***Annual
O&M cost assumed to be USD 170/kW and lifetime 27.5 years.
·······»···»»··et,,,
_____J •••••
""·................
""··..._, J ..... ··..,,
"··...........,
""····,,,,,,,,,,,, ---__
1-
I
I
•••••••••• 1.
r"a.....................
79
Summaries Technical Summary
Table TS.4.4 | Potential geothermal deployments for electricity and direct uses in 2020 through 2050. [Table 4.10]
Year Use Capacity1 (GW) Generation (TWh/yr) Generation (EJ/yr) Total (EJ/yr)
2020
Electricity 25.9 181.8 0.65
2.01
Direct 143.6 377.5 1.36
2030
Electricity 51.0 380.0 1.37
5.23
Direct 407.8 1,071.7 3.86
2050
Electricity 150.0 1,182.8 4.26
11.83
Direct 800.0 2,102.3 7.57
Notes: 1. Installed capacities for 2020 and 2030 are extrapolated from 2015 estimates using a 7% annual growth rate for electricity and 11% for direct uses, and for 2050 are the
middle value between projections cited in Chapter 4. Generation was estimated with average worldwide capacity factors of 80% (2020), 85% (2030) and 90% (2050) for electricity
and of 30% for direct uses.
on the AR4 baselines (>600 ppm CO2), 440 to 600 ppm (Categories III
and IV) and <440 ppm (Categories I and II), range from 0.39 to 0.71 EJ/
yr for 2020, 0.22 to 1.28 EJ/yr for 2030 and 1.16 to 3.85 EJ/yr for 2050.
Carbon policy is likely to be one of the main driving factors for future
geothermal development, and under the most favourable GHG concentration
stabilization policy (<440 ppm), geothermal deployment by
2020, 2030 and 2050 could be signifi cantly higher than the median
values noted above. By projecting the historic average annual growth
rates of geothermal power plants (7%) and direct uses (11%) from
the estimates for 2015, the installed geothermal capacity in 2020 and
2030 for electricity and direct uses could be as shown in Table TS.4.4.
By 2050, the geothermal-electric capacity would be as high as 150
GWe (with half of that comprised of EGS plants), and up to an additional
800 GWth of direct-use plants (Table TS.4.4). [4.8.2]
Even the highest estimates for the long-term contribution of geothermal
energy to the global primary energy supply (52.5 EJ/yr by 2050)
are within the technical potential ranges (118 to 1,109 EJ/yr for electricity
and 10 to 312 EJ/yr for direct uses) and even within the upper
range of hydrothermal resources (28.4 to 56.8 EJ/yr). Thus, technical
potential is not likely to be a barrier to reaching more ambitious levels
of geothermal deployment (electricity and direct uses), at least on a
global basis. [4.8.2]
Table TS.4.2 | Investment costs and calculated levelized cost of heat (LCOH) for several direct geothermal applications. [Table 4.8]
Heat application Investment cost (USD2005/kWth)
LCOH (USD2005/GJ) at discount rates of:
3% 7% 10%
Space heating (buildings) 1,600–3,940 20–50 24–65 28–77
Space heating (districts) 570–1,570 12–24 14–31 15–38
Greenhouses 500–1,000 7.7–13 8.6–14 9.3–16
Uncovered aquaculture ponds 50–100 8.5–11 8.6–12 8.6–12
GHP (residential and commercial) 940–3,750 14–42 17–56 19–68
Table TS.4.3 | Regional current and forecast installed capacity for geothermal power and direct uses (heat) and forecast generation of electricity and heat by 2015. [Table 4.9]
REGION1
Current capacity (2010) Forecast capacity (2015) Forecast generation (2015)
Direct (GWth) Electric (GWe) Direct (GWth) Electric (GWe) Direct (TWth) Electric (TWhe)
OECD North America 13.9 4.1 27.5 6.5 72.3 43.1
Latin America 0.8 0.5 1.1 1.1 2.9 7.2
OECD Europe 20.4 1.6 32.8 2.1 86.1 13.9
Africa 0.1 0.2 2.2 0.6 5.8 3.8
Transition Economies 1.1 0.1 1.6 0.2 4.3 1.3
Middle East 2.4 0 2.8 0 7.3 0
Developing Asia 9.2 3.2 14.0 6.1 36.7 40.4
OECD Pacifi c 2.8 1.2 3.3 1.8 8.7 11.9
TOTAL 50.6 10.7 85.2 18.5 224.0 121.6
Notes: 1. For regional defi nitions and country groupings see Annex II. Estimated average annual growth rate for 2010 to 2015 is 11.5% for power and 11% for direct uses. Average
worldwide capacity factors of 75% (for electric) and 30% (for direct use) were assumed by 2015.
80
Technical Summary Summaries
Evidence suggests that geothermal supply could meet the upper
range of projections derived from a review of about 120 energy and
GHG-reduction scenarios. With its natural thermal storage capacity,
geothermal is especially suitable for supplying base-load power.
Considering its technical potential and possible deployment, geothermal
energy could meet roughly 3% of global electricity demand by
2050, and also has the potential to provide roughly 5% of the global
demand for heating and cooling by 2050. [4.8.3]
5. Hydropower
5.1 Introduction
Hydropower is a renewable energy source where power is derived
from the energy of water moving from higher to lower elevations. It
is a proven, mature, predictable and cost-competitive technology.
The mechanical power of falling water is an old tool used for various
services from the time of the Greeks more than 2,000 years ago. The
world’s fi rst hydroelectric station of 12.5 kW was commissioned on 30
September 1882 on Fox River at the Vulcan Street Plant in Appleton,
Wisconsin, USA. Though the primary role of hydropower in global
energy supply today is in providing centralized electricity generation,
hydropower plants also operate in isolation and supply independent
systems, often in rural and remote areas of the world. [5.1]
5.2 Resource potential
The annual global technical potential for hydropower generation is
14,576 TWh (52.47 EJ) with a corresponding estimated total capacity
potential of 3,721 GW—four times the currently installed global
hydropower capacity (Figure TS.5.1). Undeveloped capacity ranges
from about 47% in Europe to 92% in Africa, indicating large and welldistributed
opportunities for hydropower development worldwide (see
Table TS.5.1). Asia and Latin America have the largest technical potentials
and the largest undeveloped resources. Africa has highest portion
of total potential that is still undeveloped. [5.2.1]
It is noteworthy that the total installed capacities of hydropower in
North America, Latin America, Europe and Asia are of the same order
of magnitude and, in Africa and Australasia/Oceania, an order of magnitude
less; Africa due to underdevelopment and Australasia/Oceania
because of size, climate and topography. The global average capacity
factor for hydropower plants is 44%. Capacity factor can be indicative
of how hydropower is employed in the energy mix (e.g., peaking versus
base-load generation) or water availability, or can be an opportunity
for increased generation through equipment upgrades and operational
optimization. [5.2.1]
The resource potential for hydropower could change due to climate
change. Based on a limited number of studies to date, the climate change
impacts on existing global hydropower systems is expected to be slightly
positive, even though individual countries and regions could have signifi
cant positive or negative changes in precipitation and runoff. Annual
power production capacity in 2050 could increase by 2.7 TWh (9.72 PJ) in
Asia under the SRES A1B scenario, and decrease by 0.8 TWh (2.88 PJ) in
Europe. In other regions, changes are found to be even smaller. Globally,
the changes caused by climate change in the existing hydropower production
system are estimated to be less than 0.1%, although additional
research is needed to lower the uncertainty of these projections. [5.2.2]
5.3 Technology and applications
Hydropower projects are usually designed to suit particular needs and
specifi c site conditions, and are classifi ed by project type, head (i.e.,
the vertical height of water above the turbine) or purpose (single- or
multi-purpose). Size categories (installed capacity) are based on national
defi nitions and differ worldwide due to varying policies. There is no immediate,
direct link between installed capacity as a classifi cation criterion
and general properties common to all hydropower plants (HPPs) above
or below that MW limit. All in all, classifi cation according to size, while
both common and administratively simple, is—to a degree—arbitrary:
general concepts like ‘small’ or ‘large’ hydropower are not technically
or scientifi cally rigorous indicators of impacts, economics or characteristics.
It may be more useful to evaluate a hydropower project on its
sustainability or economic performance thus setting out more realistic
indicators. The cumulative relative environmental and social impacts of
large versus small hydropower development remain unclear and context
dependent. [5.3.1]
Hydropower plants come in three main project types: run-of-river (RoR),
storage and pumped storage. RoR HPPs have small intake basins with
no storage capacity. Power production therefore follows the hydrological
cycle of the watershed. For RoR HPPs the generation varies as water
availability changes and thus they may be operated as variable in small
streams or as base-load power plants in large rivers. Large-scale RoR
HPPs may have some limited ability to regulate water fl ow, and if they
operate in cascades in unison with storage hydropower in upstream
reaches, they may contribute to the overall regulating and balancing
ability of a fl eet of HPPs. A fourth category, in-stream (hydrokinetic)
technology, is less mature and functions like RoR without any regulation.
[5.3.2]
Hydropower projects with a reservoir (storage hydropower) deliver
a broad range of energy services such as base load, peak, and energy
storage, and act as a regulator for other sources. In addition they often
deliver services that go beyond the energy sector, including fl ood control,
water supply, navigation, tourism and irrigation. Pumped storage
plants store water as a source for electricity generation. By reversing the
81
Summaries Technical Summary
HPP performance: depletion of reservoir storage capacity over time;
an increase in downstream degradation; increased fl ood risk upstream
of reservoirs; generation losses due to reductions in turbine effi ciency;
increased frequency of repair and maintenance; and reductions in turbine
lifetime and in regularity of power generation. The sedimentation
problem may ultimately be controlled through land use policies and the
fl ow of water, electrical energy can be produced on demand, with a very
fast response time. Pumped storage is the largest-capacity form of grid
energy storage now available. [5.3.2.2–5.3.2.3]
Sediment transport and reservoir sedimentation are problems that
need to be understood as they have a number of negative effects on
Figure TS.5.1 | Regional hydropower technical potential in terms of annual generation and installed capacity and the percentage of undeveloped technical potential in 2009. [Figure 5.2]
World Hydropower
Technical Potential:
14,576 TWh/yr
Capacity [GW]
Generation [TWh/yr]
*Undeveloped [%]
Installed [%]
Technical Potential
388
GW
1659 61%*
TWh/yr
338
GW
1021 47%*
TWh/yr
283
GW
1174 92%*
TWh/yr
2037
GW
7681 80%*
TWh/yr
67
GW
185 80%*
TWh/yr
608
GW
2856 74%*
TWh/yr
Europe Asia Australasia/
Oceania
North America Latin America Africa
Table TS.5.1 | Regional hydro power technical potential in terms of annual generation and installed capacity (GW); and current generation, installed capacity, average capacity
factors and resulting undeveloped potential as of 2009. [Table 5.1]
World region
Technical potential,
annual generation
TWh/yr (EJ/yr)
Technical potential,
installed capacity
(GW)
2009
Total generation
TWh/yr (EJ/yr)
2009
Installed capacity
(GW)
Undeveloped
potential
(%)
Average regional
capacity factor
(%)
North America 1,659 (5.971) 388 628 (2.261) 153 61 47
Latin America 2,856 (10.283) 608 732 (2.635) 156 74 54
Europe 1,021 (3.675) 338 542 (1.951) 179 47 35
Africa 1,174 (4.226) 283 98 (0.351) 23 92 47
Asia 7,681 (27.651) 2,037 1,514 (5.451) 402 80 43
Australasia/Oceania 185 (0.666) 67 37 (0.134) 13 80 32
World 14,576 (52.470) 3,721 3,551 (12.783) 926 75 44
.@ lo ..@ ..ell@ _o
■
■
G
82
Technical Summary Summaries
protection of vegetation coverage. Hydropower has the best conversion
effi ciency of all known energy sources (about 90% effi ciency, water to
wire) and a very high energy payback ratio. [5.3.3]
Normally the life of a hydroelectric power plant is 40 to 80 years.
Electrical and mechanical components and control equipment wear out
early compared to civil structures, typically in 30 to 40 years, after which
they require renovation. Upgrading/up-rating of HPPs calls for a systematic
approach as there are a number of factors (hydraulic, mechanical,
electrical and economic) that play a vital role in deciding the course of
action. From a techno-economic viewpoint, up-rating should be considered
along with renovation and modernization measures. Hydropower
generating equipment with improved performance can be retrofi tted,
often to accommodate market demands for more fl exible, peaking
modes of operation. Most of the 926 GW of hydropower equipment in
operation today (2010) will need to be modernized by 2030 to 2040.
Refurbishment of existing hydropower plants often results in enhanced
hydropower capacity, both where turbine capacity is being renovated/
up-rated or where existing civil infrastructure (like barrages, weirs, dams,
canal tunnels, etc.) is being reworked to add new hydropower facilities.
[5.3.4]
5.4 Global and regional status of market and
industry development
Hydropower is a mature, predictable and price-competitive technology.
It currently provides approximately 16% of the world’s total electricity
production and 86% of all electricity from renewable sources. While
hydropower contributes to some level of power generation in 159 countries,
5 countries make up more than half of the world’s hydropower
production: China, Canada, Brazil, the USA and Russia. The importance of
hydroelectricity in the electricity matrix of these countries differs widely,
however. While Brazil and Canada are heavily dependent on hydropower
to produce 84% and 59% of total generation, respectively, Russia and
China produce only 19% and 16% of their total electricity from hydropower,
respectively. Despite the signifi cant growth of hydroelectric
production around the globe, the percentage share of hydroelectricity
has dropped during the last three decades (1973 to 2008) from 21 to
16%, because electricity load and other generation sources have grown
more rapidly than has hydropower. [5.4.1]
Carbon credits benefi t hydropower projects by helping to secure fi nancing
and to reduce risks. Financing is the most decisive step in the entire
project development process. Hydropower projects are one of the largest
contributors to the fl exible mechanisms of the Kyoto Protocol and
therefore to existing carbon credit markets. Out of the 2,062 projects
registered by the Clean Development Mechanism (CDM) Executive
Board by 1 March 2010, 562 are hydropower projects. With 27% of the
total number of projects, hydropower is the CDM’s leading deployed RE
source. China, India, Brazil and Mexico represent roughly 75% of the
hosted projects. [5.4.3.1]
Many economical hydropower projects are fi nancially challenged. High
up-front costs are a deterrent for investment. Also, hydropower tends
to have lengthy lead times for planning, permitting and construction.
In the evaluation of lifecycle costs, hydropower often has a very high
performance, with annual O&M costs being a fraction of the capital
investment. As hydropower and its industry are old and mature, it is
expected that the hydropower industry will be able to meet the demand
that will be created by the predicted deployment rate in the years to
come. For example, in 2008 the hydropower industry managed to install
more than 41 GW of new capacity worldwide. [5.4.3.2]
The development of more appropriate fi nancing models is a major challenge
for the hydropower sector, as is fi nding the optimum roles for the
public and private sectors. The main challenges for hydropower relate to
creating private-sector confi dence and reducing risk, especially prior to
project permitting. Green markets and trading in emissions reductions
will undoubtedly provide incentives. Also, in developing regions, such as
Africa, interconnection between countries and the formation of power
pools is building investor confi dence in these emerging markets. [5.4.3.2]
The concepts of classifying HPPs as ‘small’ or ‘large’, as defi ned by
installed capacity (MW), can act as a barrier to the development of
hydropower. For example, these classifi cations can impact the fi nancing
of new hydropower plants, determining how hydropower is treated
in climate change and energy policies. Different incentives are used for
small-scale hydropower (FITs, green certifi cates and bonuses) depending
on the country, but no incentives are available for large-scale HPPs. The
EU Linking Directive sets a limit for carbon credits issued from HPPs to 20
MW. The same limit is found in the UK Renewables Obligation, a green
certifi cate market-based mechanism. Likewise, in several countries FITs
do not apply to hydropower above a certain size limit (e.g., France 12
MW, Germany 5 MW, India 5 and 25 MW). [5.4.3.4]
The UNFCCC CDM Executive Board has decided that storage hydropower
projects will have to follow the power density indicator (PDI:
installed capacity/reservoir area in W/m2) to be eligible for CDM credits.
The PDI rule seems to presently exclude storage hydropower from
qualifying for CDM (or Joint Implementation) credits and may lead to
suboptimal development of hydropower resources as the non-storage
RoR option will be favoured.
5.5 Integration into broader energy systems
Hydropower’s large capacity range, its fl exibility, storage capability
(when coupled with a reservoir), and ability to operate in a stand-alone
mode or in grids of all sizes enables it to deliver a broad range of services.
[5.5]
Hydropower can be delivered through the national and regional electric
grid, mini-grids and also in isolated mode. Realization has been growing
in developing countries that small-scale hydropower schemes have
83
Summaries Technical Summary
an important role to play in the socioeconomic development of remote
rural, especially hilly, areas as those can provide power for industrial,
agricultural and domestic uses. In China, small-scale HPPs have been
one of the most successful examples of rural electrifi cation, where over
45,000 small HPPs totalling over 55,000 MW of capacity and producing
160 TWh (576 PJ) of generation annually benefi t over 300 million
people. [5.5.2]
With a very large reservoir relative to the size of the hydropower plant
(or very consistent river fl ows), HPPs can generate power at a nearconstant
level throughout the year (i.e., operate as a base-load plant).
Alternatively, in the case that the hydropower capacity far exceeds
the amount of reservoir storage, the hydropower plant is sometimes
referred to as energy-limited. An energy-limited hydro plant would
exhaust its ‘fuel supply’ by consistently operating at its rated capacity
throughout the year. In this case, the use of reservoir storage allows
hydropower generation to occur at times that are most valuable from
the perspective of the power system rather than at times dictated solely
by river fl ows. Since electrical demand varies during the day and night,
during the week and seasonally, storage hydropower generation can
be timed to coincide with times where the power system needs are the
greatest. In part, these times will occur during periods of peak electrical
demand. Operating hydropower plants in a way to generate power during
times of high demand is referred to as peaking operation (in contrast
to base-load). Even with storage, however, hydropower generation will
still be limited by the size of the storage, the rated electrical capacity
of the hydropower plant, and downstream fl ow constraints for irrigation,
recreation or environmental uses of the river fl ows. Hydropower
peaking may, if the outlet is directed to a river, lead to rapid fl uctuations
in river fl ow, water-covered area, depth and velocity. In turn this
may, depending on local conditions, lead to negative impacts in the river
unless properly managed. [5.5.3]
In addition to hydropower supporting fossil and nuclear generation
technologies, it can also help reduce the challenges with integrating
variable renewable resources. In Denmark, for example, the high level of
variable wind energy (>20% of the annual energy demand) is managed
in part through strong interconnections (1 GW) to Norway, which has
substantial storage hydropower. More interconnectors to Europe may
further support increasing the share of wind power in Denmark and
Germany. Increasing variable generation will also increase the amount
of balancing services, including regulation and load following, required
by the power system. In regions with new and existing hydropower
facilities, providing these services from hydropower may avoid the need
to rely on increased part-load and cycling of conventional thermal plants
to provide these services. [5.5.4]
Though hydro has the potential to offer signifi cant power system services
in addition to energy and capacity, interconnecting and reliably
utilizing HPPs may also require changes to power systems. The interconnection
of hydropower to the power system requires adequate
transmission capacity from HPPs to demand centres. Adding new HPPs
has in the past required network investments to extend the transmission
network. Without adequate transmission capacity, HPP operation can
be constrained such that the services offered by the plant are less than
what it could offer in an unconstrained system. [5.5.5]
5.6 Environmental and social impacts
Like all energy and water management options, hydropower projects
have negative and positive environmental and social impacts. On the
environmental side, hydropower may have a signifi cant environmental
footprint at local and regional levels but offers advantages at the macroecological
level. With respect to social impacts, hydropower projects may
entail the relocation of communities living within or nearby the reservoir
or the construction sites, compensation for downstream communities,
public health issues, and others. A properly designed hydropower project
may, however, be a driving force for socioeconomic development,
though a critical question remains about how these benefi ts are shared.
[5.6]
All hydroelectric structures affect a river’s ecology, mainly by inducing
a change into its hydrologic characteristics and by disrupting the
ecological continuity of sediment transport and fi sh migration through
the building of dams, dikes and weirs. However, the extent to which a
river’s physical, chemical, biological and ecosystem characteristics are
modifi ed depends largely on the type of HPP. Whereas RoR hydropower
projects do not alter a river’s fl ow regime, the creation of a reservoir
for storage hydropower entails a major environmental change by transforming
a fast-running river ecosystem into a still-standing artifi cial lake.
[5.6.1.1–5.6.1.6]
Similar to a hydropower project’s ecological effects, the extent of its social
impacts on the local and regional communities, land use, economy, health
and safety or heritage varies according to project type and site-specifi c
conditions. While RoR projects generally introduce little social change,
the creation of a reservoir in a densely populated area can entail signifi
cant challenges related to resettlement and impacts on the livelihoods
of the downstream populations. Restoration and improvement of living
standards of affected communities is a long-term and challenging task
that has been managed with variable success in the past. Whether HPPs
can contribute to fostering socioeconomic development depends largely
on how the generated services and revenues are shared and distributed
among different stakeholders. HPPs can also have positive impacts on
the living conditions of local communities and the regional economy, not
only by generating electricity but also by facilitating through the creation
of freshwater storage schemes multiple other water-dependent activities,
such as irrigation, navigation, tourism, fi sheries or suffi cient water supply
to municipalities and industries while protecting against fl oods and
droughts. [5.6.1.7–5.6.1.11]
The assessment and management of environmental and social impacts
associated with, especially, larger HPPs represent a key challenge for
hydropower development. Emphasizing transparency and an open,
participatory decision-making process, the stakeholder consultation
84
Technical Summary Summaries
approach is driving both present-day and future hydropower projects
towards increasingly more environmentally friendly and sustainable solutions.
In many countries, a national legal and regulatory framework has
been put in place to determine how hydropower projects shall be developed
and operated, while numerous multilateral fi nancing agencies have
developed their own guidelines and requirements to assess the economic,
social and environmental performance of hydropower projects. [5.6.2]
One of hydropower’s main environmental advantages is that it creates
no atmospheric pollutants or waste associated with fuel combustion.
However, all freshwater systems, whether they are natural or man-made,
emit GHGs (e.g., CO2, methane) due to decomposing organic material.
Lifecycle assessments (LCAs) carried out on hydropower projects have
so far demonstrated the diffi culty of generalizing estimates of lifecycle
GHG emissions for hydropower projects in all climatic conditions, preimpoundment
land cover types, ages, hydropower technologies, and
other project-specifi c circumstances. The multipurpose nature of most
hydropower projects makes allocation of total impacts to the several
purposes challenging. Many LCAs to date allocate all impacts of hydropower
projects to the electricity generation function, which in some
cases may overstate the emissions for which they are ‘responsible’. LCAs
(Figure TS.5.2) that evaluate GHG emissions of HPPs during construction,
operation and maintenance, and dismantling, show that the majority of
lifecycle GHG emission estimates for hydropower cluster between about
4 and 14 g CO2eq/kWh, but under certain scenarios there is potential to
emit much larger quantities of GHGs, as shown by the outliers. [5.6.3.1]
While some natural water bodies and freshwater reservoirs may even
absorb more GHGs than they emit, there is a defi nite need to properly
assess the net change in GHG emissions induced by the creation
of such reservoirs. All LCAs included in these assessments evaluated
only gross GHG emissions from reservoirs. Whether reservoirs are net
emitters of GHGs, considering emissions that would have occurred
without the reservoir, is an area of active research. When considering
net anthropogenic emissions as the difference in the overall carbon
cycle between the situations with and without the reservoir, there is
currently no consensus on whether reservoirs are net emitters or net
sinks. Presently two international processes are investigating this issue:
the UN Educational, Scientifi c and Cultural Organization/International
Hydrological Programme research project and the IEA Hydropower
Agreement Annex XII. [5.6.3.2]
5.7 Prospects for technology improvement
and innovation
Though hydropower is a proven and well-advanced technology, there
is still room for further improvement, for example, by optimizing operations,
mitigating or reducing environmental impacts, adapting to new
social and environmental requirements and implementing more robust
and cost-effective technological solutions. Large hydropower turbines
are now close to the theoretical limit for effi ciency, with up to 96% effi -
ciency when operated at the best effi ciency point, but this is not always
possible and continued research is needed to make more effi cient operation
possible over a broader range of fl ows. Older turbines can have
lower effi ciency by design or reduced effi ciency due to corrosion and
cavitation. There is therefore the potential to increase energy output
by retrofi tting with new higher effi ciency equipment and usually also
with increased capacity. Most of the existing electrical and mechanical
equipment in operation today will need to be modernized during the
next three decades, allowing for improved effi ciency and higher power
and energy output. Typically, generating equipment can be upgraded
or replaced with more technologically advanced electro-mechanical
equipment two or three times during the lifetime of the project, making
more effective use of the same fl ow of water. [5.7]
There is much ongoing technology innovation and material research
aiming to extend the operational range in terms of head and discharge,
and also to improve environmental performance, reliability and reduce
costs. Some of the promising technologies under development are
variable-speed and matrix technologies, fi sh-friendly turbines, hydrokinetic
turbines, abrasive-resistant turbines, and new tunnelling and
dam technologies. New technologies aiming at utilizing low (<15 m)
or very low (<5 m) head may open up many sites for hydropower that
have not been within reach of conventional technology. As most of the
data available on hydropower potential are based on fi eld work produced
several decades ago, when low-head hydropower was not a high
priority, existing data on low-head hydropower potential may not be
complete. Finally, there is a signifi cant potential for improving operation
of HPPs by utilizing new methods for optimizing plant operation.
[5.7.1–5.7.8]
5.8 Cost trends
Hydropower is often economically competitive with current market
energy prices, though the cost of developing, deploying and operating
new hydropower projects will vary from project to project. Hydropower
projects often require a high initial investment, but have the advantage
of very low O&M costs and a long lifespan. [5.8]
Investment costs for hydropower include costs of planning; licensing;
plant construction; impact reductions for fi sh and wildlife, recreational,
historical and archaeological sites; and water quality monitoring. Overall,
there are two major cost groups: the civil construction costs, which
normally are the greatest costs of the hydropower project; and electromechanical
equipment costs. The civil construction costs follow the price
trends in the country where the project is going to be developed. In the
case of countries with economies in transition, the costs are likely to be
relatively low due to the use of local labour and local materials. The costs
of electromechanical equipment follow the tendency of prices at a global
level. [5.8.1]
Based on a standardized methodology outlined in Annex II and the cost
and performance data summarized in Annex III, the LCOE for hydropower
projects over a large set and range of input parameters has been
85
Summaries Technical Summary
0
20
40
60
80
100
120
140
160
200
180
Lifecycle GHG Emissions [g CO2 eq /kWh]
Estimates:
References:
All Values Reservoir Run-of-River Pumped Storage
1
1
8
2
18
9
27
11
0
20
40
60
80
100
120
140
160
All Other
Lifecycle Emissions
LUC-Related
Emissions –
Decommissioning
LUC-Related
Emissions –
Reservoir
16
7
3
2
16
7
Estimates:
References:
Maximum
75th Percentile
Median
25th Percentile
Minimum
Figure TS.5.2 | Life-cycle GHG emissions of hydropower technologies (unmodifi ed literature values, after quality screen). See Annex I for details of literature search and citations of
literature contributing to the estimates displayed. Surface emissions from reservoirs are referred to as gross GHG emissions. [Figure 5.15]
calculated to range from as low as US cent2005 1.1/kWh to US cent2005
15/kWh, depending on site-specifi c parameters for investment costs of
each project and on assumptions regarding the discount rate, capacity
factor, lifetime and O&M costs. [1.3.2, 5.8, 10.5.1, Annex II, Annex III]
Figure TS.5.3 presents the LCOE for hydropower projects over a
somewhat different and more typical set and range of parameters
consistent with the majority of hydropower projects, and does so as a
function of capacity factor while applying different investment costs
and discount rates.
Capacity factors will be determined by hydrological conditions,
installed capacity and plant design, and the way the plant is operated.
For power plant designs intended for maximum energy production
(base-load) and/or with some regulation, capacity factors will often
be from 30 to 60%, with average capacity factors for different world
regions shown in the graph. For peaking-type power plants, the
capacity factor can be even lower, whereas capacity factors for RoR
systems vary across a wide range (20 to 95%) depending on the geographical
and climatological conditions, technology, and operational
characteristics. For an average capacity factor of 44% and investment
costs between USD2005 1,000/kW and USD2005 3,000/kW, the LCOE
ranges from US cent2005 2.5/kWh to US cent2005 7.5/kWh.
Most of the projects developed in the near-term future (up to 2020)
are expected to have investment costs and LCOE in this range, though
projects with both lower and higher costs are possible. Under good
conditions, the LCOE of hydropower can be in the range of US cent2005
3/kWh to US cent2005 5/kWh. [5.8.3, 8.2.1.2, Annex III]
There is relatively little information on historical trends in hydropower
costs in the literature. One reason for this—besides the fact
that project costs are highly site-specifi c—may be the complex cost
structure for hydropower plants, where some components may have
decreasing cost trends (e.g., tunnelling costs), while others may have
increasing cost trends (e.g., social and environmental mitigation
costs). [5.8.4]
One complicating factor when considering the cost of hydropower is
that, for multipurpose reservoirs, there is a need to share or allocate
the cost of serving other water uses like irrigation, fl ood control, navigation,
roads, drinking water supply, fi sh, and recreation. There are
I
I $
•
86
Technical Summary Summaries
Hydro, USD2005 3,000
Hydro, USD2005 2,000
Hydro, USD2005 1,000
Levelized Cost of Energy [UScent2005 /kWh]
Capacity Factor [%]
0
1
2
3
4
5
6
7
8
9
10
11
12
30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60
Average CF in
Australasia/
Oceania: 32%
Average CF in
Europe: 35%
Average CF
in Asia: 43%
Average CF
in Africa & North
America: 47%
Average CF in
Latin America: 54%
Hydro, Discount Rate = 10%
Hydro, Discount Rate = 7%
Hydro, Discount Rate = 3%
Levelized Cost of Energy [UScent2005 /kWh]
Capacity Factor [%]
0
1
2
3
4
5
6
7
8
9
10
11
12
30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60
Figure TS.5.3 | Recent and near-term estimated levelized cost of hydropower (a) as a function of capacity factor and investment cost*, ***; and (b) as a function of capacity factor
and discount rate**,***. [Figure 5.20]
Notes: * Discount rate is assumed to equal 7%. ** Investment cost is assumed to be USD 2,000/kW. *** Annual O&M cost is assumed at 2.5%/yr of investment cost and plant
lifetime as 60 years.
different methods of allocating the cost to individual purposes, each
of which has advantages and drawbacks. The basic rules are that the
allocated cost to any purpose does not exceed that benefi t of that
purpose and each purpose will be carried out at its separable cost.
Separable cost for any purpose is obtained by subtracting the cost of
a multipurpose project without that purpose from the total cost of
the project with the purpose included. Merging economic elements
(energy and water selling prices) with social benefi ts (supplying water
to farmers in case of lack of water) and the value of the environment
(to preserve a minimum environmental fl ow) is becoming a tool for
consideration of cost sharing for multipurpose reservoirs. [5.8.5]
5.9 Potential deployment
Hydropower offers a signifi cant potential for near- and long-term carbon
emissions reduction. On a global basis, the hydropower resource is
unlikely to constrain further development in the near to medium term,
though environmental and social concerns may limit deployment opportunities
if not carefully managed. [5.9]
So far, only 25% of the hydropower potential has been developed across
the world (that is, 3,551 TWh out of 14,575 TWh) (12.78 EJ out of 52.47
EJ). The different long-term prospective scenarios propose a continuous
increase for the next decades. The increase in hydropower capacity over
the last 10 years is expected by several studies to continue in the near to
medium term: from 926 GW in 2009 to between 1,047 and 1,119 GW by
2015; an annual addition ranging from 14 to 25 GW. [5.9, 5.9.1]
The reference-case projections presented in Chapter 10 (based on 164
analyzed longer-term scenarios) show hydropower’s role in the global
energy supply covering a broad range, with a median of roughly 13 EJ
(3,600 TWh) in 2020, 16 EJ (4,450 TWh) in 2030 and 19 EJ (5,300 TWh)
in 2050. 12.78 EJ was reached already in 2009 and thus the average
estimate of 13 EJ for 2020 has probably been exceeded today. Also,
some scenario results provide lower values than the current installed
capacity for 2020, 2030 and 2050, which is counterintuitive given, for
example, hydropower’s long lifetimes, its signifi cant market potential
and other important services. These results could maybe be explained by
model/scenario weaknesses (see discussions in Section 10.2.1.2 of this
report). Growth of hydropower is therefore projected to occur even in
the absence of GHG mitigation policies, even with hydropower’s median
contribution to global electricity supply dropping from about 16% today
to less than 10% by 2050. As GHG mitigation policies are assumed to
become more stringent in the alternative scenarios, the contribution of
hydropower grows: by 2030, hydropower’s median contribution equals
roughly 16.5 EJ (4,600 TWh) in the 440 to 600 and <440 ppm CO2 stabilization
ranges (compared to the median of 15 EJ in the baseline cases),
increasing to about 19 EJ by 2050 (compared to the median of 18 EJ in
the baseline cases). [5.9.2]
Regional projections of hydropower generation in 2035 show a 98%
increase in the Asia Pacifi c region compared to 2008 levels and a 104%
increase in Africa. Brazil is the main driving force behind the projected
46% increase in hydropower generation in the South and Central
America region over the same time period. North America and Europe/
Eurasia expect more modest increases of 13 and 27%, respectively,
over the period. [5.9.2]
Overall, evidence suggests that relatively high levels of deployment in
the next 20 years are feasible. Even if hydropower’s share in global
electricity supply decreases by 2050, hydropower would remain an
attractive RE source within the context of global carbon mitigation
scenarios. Furthermore, increased development of storage hydropower
I
l
I
___I ,_
I
I
87
Summaries Technical Summary
may enable investment into water management infrastructure, which
is needed in response to growing problems related to water resources.
[5.9.3]
5.10 Integration into water management
systems
Water, energy and climate change are inextricably linked. Water availability
is crucial for many energy technologies, including hydropower,
while energy is needed to secure water supply for agriculture, industries
and households, in particular in water-scarce areas in developing
countries. This close relationship has led to the understanding that the
water-energy nexus must be addressed in a holistic way, in particular
with regard to climate change and sustainable development. Providing
energy and water for sustainable development may require improved
regional and global water governance. As it is often associated with the
creation of water storage facilities, hydropower is at the crossroads of
these issues and can play an important role in enhancing both energy
and water security. [5.10]
Today, about 700 million people live in countries experiencing water stress
or scarcity. By 2035, it is projected that three billion people will be living
in conditions of severe water stress. Many countries with limited water
availability depend on shared water resources, increasing the risk of confl
ict over these scarce resources. Therefore, adaptation to climate change
impacts will become very important in water management. [5.10.1]
In a context where multipurpose hydropower can be a tool to mitigate
both climate change and water scarcity, these projects may have an
enabling role beyond the electricity sector as a fi nancing instrument for
reservoirs, helping to secure freshwater availability. However, multiple
uses may increase the potential for confl icts and reduce energy production
during times of low water levels. As major watersheds are shared by
several nations, regional and international cooperation is crucial. Both
intergovernmental agreements and initiatives by international institutions
are actively supporting these important processes. [5.10.2, 5.10.3]
6. Ocean Energy
6.1 Introduction
Ocean energy offers the potential for long-term carbon emissions reduction
but is unlikely to make a signifi cant short-term contribution before
2020 due to its nascent stage of development. The theoretical potential of
7,400 EJ/yr contained in the world’s oceans easily exceeds present human
energy requirements. Government policies are contributing to accelerate
the deployment of ocean energy technologies, heightening expectations
that rapid progress may be possible. The six main classes of ocean energy
technology offer a diversity of potential development pathways, and most
offer potentially low environmental impacts as currently understood.
There are encouraging signs that the investment cost of ocean energy
technologies and the levelized cost of electricity generated will decline
from their present non-competitive levels as R&D and demonstrations
proceed, and as deployment occurs. Whether these cost reductions are
suffi cient to enable broad-scale deployment of ocean energy is the most
critical uncertainty in assessing the future role of ocean energy in mitigating
climate change. [6 ES, 6.1]
6.2 Resource potential
Ocean energy can be defi ned as energy derived from technologies that
utilize seawater as their motive power or harness the water’s chemical
or heat potential. The RE resource in the ocean comes from six distinct
sources, each with different origins and each requiring different technologies
for conversion. These sources are:
Wave energy derived from the transfer of the kinetic energy of the wind
to the upper surface of the ocean. The total theoretical wave energy
resource is 32,000 TWh/yr (115 EJ/yr), but the technical potential is likely
to be substantially less and will depend on development of wave energy
technologies. [6.2.1]
Tidal range (tidal rise and fall) derived from gravitational forces of
the Earth-Moon-Sun system. The world’s theoretical tidal power potential
is in the range of 1 to 3 TW, located in relatively shallow waters.
Again, technical potential is likely to be signifi cantly less than theoretical
potential. [6.2.2]
Tidal currents derived from water fl ow that results from the fi lling and
emptying of coastal regions associated with tides. Current regional estimates
of tidal current technical potential include 48 TWh/yr (0.17 EJ)
for Europe and 30 TWh/yr (0.11EJ/yr) for China. Commercially attractive
sites have also been identifi ed in the Republic of Korea, Canada, Japan,
the Philippines, New Zealand and South America. [6.2.3]
Ocean currents derived from wind-driven and thermohaline ocean
circulation. The best-characterized system of ocean currents is the Gulf
Stream in North America, where the Florida Current has a technical
potential for 25 GW of electricity capacity. Other regions with potentially
promising ocean circulation include the Agulhas/Mozambique
Currents off South Africa, the Kuroshio Current off East Asia and the
East Australian Current. [6.2.4]
Ocean thermal energy conversion (OTEC) derived from temperature
differences arising from solar energy stored as heat in upper ocean layers
and colder seawater, generally below 1,000 m. Although the energy
density of OTEC is relatively low, the overall resource potential is much
88
Technical Summary Summaries
larger than for other forms of ocean energy. One 2007 study estimates
that about 44,000 TWh/yr (159 EJ/yr) of steady-state power may be possible.
[6.2.5]
Salinity gradients (osmotic power) derived from salinity differences
between fresh and ocean water at river mouths. The theoretical potential
of salinity gradients is estimated at 1,650 TWh/yr (6 EJ/yr). [6.2.6]
Figure TS.6.1 provides examples of how selected ocean energy resources
are distributed across the globe. Some ocean energy resources, such as
ocean currents or power from salinity gradients, are globally distributed.
Ocean thermal energy is principally located in the Tropics around
the equatorial latitudes (latitudes 0° to 35°), whilst the highest annual
wave power occurs between latitudes of 30° to 60°. Wave power in the
southern hemisphere undergoes smaller seasonal variation than in the
northern hemisphere. Ocean currents, ocean thermal energy, salinity
gradients and, to some extent, wave energy are consistent enough to
generate base-load power. Given the early state of the available literature
and the substantial uncertainty in ocean energy’s technical potential, the
estimates for technical ocean energy potential vary widely. [6.2.1–6.2.6]
(a)
(b) (c)
Mean Power
kW/m
125
115
105
95
85
75
65
55
45
35
25
15
5
Figure TS.6.1a-c | Global distribution of various ocean energy resources: (a) Wave power; (b) Tidal range, (c) Ocean thermal energy. [Figures 6.1, 6.2, 6.4]
16 18 20 22 24 C°
Ocean Data View
0 10 20 30 40 50 60 70 80 90 100 110 120 130 cm
GOT99.2 NASA/GSFC
6/99
89
Summaries Technical Summary
6.3 Technology and applications
The current development status of ocean energy technologies ranges
from the conceptual and pure R&D stages to the prototype and demonstration
stage, and only tidal range technology can be considered
mature. Presently there are many technology options for each ocean
energy source and, with the exception of tidal range barrages, technology
convergence has not yet occurred. Over the past four decades, other
marine industries (primarily offshore oil and gas) have made signifi cant
advances in the fi elds of materials, construction, corrosion, submarine
cables and communications. Ocean energy is expected to directly benefi
t from these advances. [6.3.1]
Many wave energy technologies representing a range of operating
principles have been conceived, and in many cases demonstrated, to
convert energy from waves into a usable form of energy. Major variables
include the method of wave interaction with respective motions
(heaving, surging, pitching) as well as water depth (deep, intermediate,
shallow) and distance from shore (shoreline, near-shore, offshore).
Wave energy technologies can be classifi ed into three groups: oscillating
water columns (OWC: shore-based, fl oating), oscillating bodies (surface
buoyant, submerged), and overtopping devices (shore-based, fl oating).
[6.2.3] Principles of operation are presented in Figure TS.6.2.
Tidal range energy can be harnessed by the adaptation of river-based
hydroelectric dams to estuarine situations, where a barrage encloses an
estuary. The barrage may generate electricity on both the ebb and fl ood
tides and some future barrages may have multiple basins to enable
almost continuous generation. The most recent technical concepts are
stand-alone offshore ‘tidal lagoons’. [6.3.3]
Technologies to harness power from tidal and ocean currents are also
under development, but tidal energy turbines are more advanced. Some
of the tidal/ocean current energy technologies are similar to mature
wind turbine generators but submarine turbines must also account for
reversing fl ow, cavitation at blade tips and harsh underwater marine
conditions. Tidal currents tend to be bidirectional, varying with the tidal
cycle, and relatively fast-fl owing, compared with ocean currents, which
are usually unidirectional and slow-moving but continuous. Converters
are classifi ed by their principle of operation into axial fl ow turbines,
cross fl ow turbines and reciprocating devices as presented in Figure
TS.6.3. [6.3.4]
Ocean thermal energy conversion (OTEC) plants use the temperature
differences between warm seawater from the ocean surface and cool
seawater from depth (1,000 m is often used as a reference level) to
produce electricity. Open-cycle OTEC systems use seawater directly
as the circulating fl uid, whilst closed-cycle systems use heat exchangers
and a secondary working fl uid (most commonly ammonia) to drive
a turbine. Hybrid systems use both open- and closed-cycle operation.
Although there have been trials of OTEC technologies, problems have
been encountered with maintenance of vacuums, heat exchanger biofouling
and corrosion issues. Current research is focused on overcoming
these problems. [6.3.5]
(d)
Equatorial Counter
N. Equatorial
S. Equatorial
N. Equatorial
Equatorial Counter
S. Equatorial
N. Equatorial
Equatorial Counter
S. Equatorial
N. Equatorial
Equatorial Counter
S. Equatorial
W. Australia E. Australia
Agulhas
S. Indian
Antarctic Circumpolar
S. Pacific
N. Pacific
Kuroshio
N. Atlantic
Drift
Gulf Stream
N. Atlantic
Drift
Canary
Peru
Antarctic Circumpolar
Antarctic Subpolar Antarctic Subpolar
Antarctic Circumpolar
S. Pacific S. Atlantic
Brazil
Benguela
Oyashio
Alaska
California
N. Pacific
Figure TS.6.1d | Global distribution of various ocean energy resources: (d) Ocean currents. [Figure 6.3]
90
Technical Summary Summaries
Figure TS.6.2a/b | Type of wave energy converter and its operation: oscillating water column device. [Figure 6.6] (design by the National Renewable Energy Laboratory (NREL))
Wave
Crest
Rising
Water
Falling Water Column
Column
Rotor
Wave
Trough
Electric
Generator
Air Flow
In-Take
The salinity gradient between freshwater from rivers and seawater can be
utilized as a source of power with at least two concepts under development.
The reversed electro dialysis (RED) process is a concept in which
the difference in chemical potential between the two solutions is the driving
force (Figure TS.6.4). The pressure-retarded osmosis, or osmotic power
process, utilizes the concept of naturally occurring osmosis, a hydraulic
pressure potential, caused by the tendency of freshwater to mix with seawater
due to the difference in salt concentration (Figure TS.6.5). [6.3.6]
6.4 Global and regional status of the
markets and industry development
R&D projects on wave and tidal current energy technologies have proliferated
over the past two decades, with some now reaching the full-scale
pre-commercial prototype stage. Presently, the only full-size and operational
ocean energy technology available is the tidal barrage, of which
the best example is the 240 MW La Rance Barrage in north-western
France, completed in 1966. The 254 MW Sihwa Barrage (South Korea) is
due to become operational in 2011. Technologies to develop other ocean
energy sources including OTEC, salinity gradients and ocean currents are
still at the conceptual, R&D or early prototype stages. Currently, more
than 100 different ocean energy technologies are under development in
over 30 countries. [6.4.1]
The principal investors in ocean energy R&D and deployments are
national, federal and state governments, followed by major energy utilities
and investment companies. National and regional governments are
Cable
Mooring
Stationary
Center
Float Spar
Upward
Motion
Downward
Motion
Figure TS.6.2c/d | Wave energy converters and their operation: (left) oscillating body
device; and (right) overtopping device. [Figure 6.6] (design by the National Renewable
Energy Laboratory (NREL))
Turbine Outlet
Reservoir Overtopping
Turbine
91
Summaries Technical Summary
Figure TS.6.3 | Tidal current energy converters and their operation: (Top left) twin turbine
horizontal axis device; (Bottom left) cross-fl ow device; and (Top right) vertical axis device.
[Figure 6.8]
Rotation
Generator
Tidal
Stream
Tidal
Stream
Rotation
Generator
particularly supportive of ocean energy through a range of fi nancial,
regulatory and legislative initiatives to support developments. [6.4.7]
Industrial involvement in ocean energy is at a very early stage and there
is no manufacturing industry for these technologies at present. The
growth of interest may lead to the transfer of capacity, skills and capabilities
from related industries, combined with new specifi c innovative
aspects. One interesting feature of ocean energy is the development of a
number of national marine energy testing centres and these are becoming
foci for device testing, certifi cation and advanced R&D. [6.4.1.2]
The status of industry development can be assessed by the current and
recent deployments of ocean energy systems.
Wave energy: A number of shore-based wave energy prototypes are
operating around the world. Two OWC devices have been operational in
Portugal and Scotland for approximately a decade, while two other offshore
OWC devices have been tested at prototype scale in Australia and
Ireland. Another OWC was operational off the southern coast of India
between 1990 and 2005. A number of companies in Australia, Brazil,
Denmark, Finland, Ireland, Norway, Portugal, Spain, Sweden, New Zealand,
the UK and the USA have been testing pilot scale or pre-commercial prototypes
at sea, with the largest being 750 kW. [6.4.2]
Tidal range: The La Rance 240 MW plant in France has been operational
since 1966. Other smaller projects have been commissioned since then
in China, Canada and Russia. The Sihwa barrage 254 MW plant in Korea
will be commissioned during 2011, and several other large projects are
under consideration. [6.4.3]
Tidal and ocean currents: There are probably more than 50 tidal current
devices at the proof-of-concept or prototype development stage,
but large-scale deployment costs are yet to be demonstrated. The most
advanced example is the SeaGen tidal turbine, which was installed near
Northern Ireland and has delivered electricity into the electricity grid for
more than one year. An Irish company has tested its open-ring turbine
in Scotland, and more recently in Canada. Two companies have demonstrated
horizontal-axis turbines at full scale in Norway and Scotland,
whilst another has demonstrated a vertical-axis turbine in Italy. Lastly,
- - -- -
- -
92
Technical Summary Summaries
a reciprocating device was demonstrated in the UK in 2009. No pilot or
demonstration plants have been deployed for ocean currents to date,
although much larger scales are envisioned if technologies are able to
capture the slower-velocity currents. [6.4.4]
OTEC: Japan, India, the USA and several other countries have tested pilot
OTEC projects. Many have experienced engineering challenges related to
pumping, vacuum retention and piping. Larger-scale OTEC developments
could have signifi cant markets in tropical maritime nations, including
the Pacifi c Islands, Caribbean Islands, and Central American and African
nations if the technology develops to the point of being a cost-effective
energy supply option. [6.4.5]
Salinity gradients: Research into osmotic power is being pursued in
Norway, with a prototype in operation since 2009 as part of a drive
to deliver a commercial osmotic power plant. At the same time, the
RED technology has been proposed for retrofi tting the 75-year-old
Afsluitdijk dike in The Netherlands. [6.4.6]
6.5 Environmental and social impacts
Ocean energy does not directly emit CO2 during operation; however,
GHG emissions may arise from different aspects of the lifecycle of
ocean energy systems, including raw material extraction, component
manufacturing, construction, maintenance and decommissioning.
A comprehensive review of lifecycle assessment studies published
since 1980 suggests that lifecycle GHG emissions from wave and tidal
energy systems are less than 23 g CO2eq/kWh, with a median estimate
of lifecycle GHG emissions of around 8 g CO2eq/kWh for wave
energy. Insuffi cient studies are available to estimate lifecycle emissions
from the other classes of ocean energy technology. Regardless,
in comparison to fossil energy generation technologies, the lifecycle
GHG emissions from ocean energy devices appear low. [6.5.1]
The local social and environmental impacts of ocean energy projects
are being evaluated as actual deployments multiply, but can be
estimated based on the experience of other maritime and offshore
CEM AEM CEM AEM CEM AEM CEM
Sea Water
Anode
River Water
e-
Fe3+
Cl- Cl- Cl-
Fe2+ Fe3+
Fe2+
Na+ Na+ Na+ Na+
e-
Cathode
N N N
C
+
C
+
C
+
C
+
Figure TS.6.4 | Reversed electro dialysis (RED) system. [Figure 6.9]
Notes: CEM = cation exchange membrane; AEM = anion exchange membrane, Na = sodium, Cl = Chlorine, Fe = iron.
I I I
I I I
93
Summaries Technical Summary
Sea Water
Pump
Pump
Pump
Freshwater
Brackish Water
Pressure
Exchanger
Membrane Modules
Freshwater
Bleed
Brackish Water
Water
Filter
Water
Filter
Power
Turbine
Figure TS.6.5 | Pressure-retarded osmosis (PRO) process. [Figure 6.10]
industries. Environmental risks from ocean energy technologies appear
to be relatively low, but the early stage of ocean energy deployment
creates uncertainty about the degree to which social and environmental
concerns might eventually constrain development. [6 ES]
Each ocean power technology has its own specifi c set of environmental
and social impacts. Possible positive effects from ocean energy
may include avoidance of adverse effects on marine life by virtue of
reducing other human activities in the area around the ocean devices,
and the strengthening of energy supply and regional economic
growth, employment and tourism. Negative effects may include a
reduction in visual amenity and loss of access to space for competing
users, noise during construction, noise and vibration during operation,
electromagnetic fi elds, disruption to biota and habitats, water quality
changes and possible pollution, for instance from chemical or oil
leaks, and other limited specifi c impacts on local ecosystems. [6.5.2]
6.6 Prospects for technology improvement,
innovation and integration
As emerging technologies, ocean energy devices have the potential
for signifi cant technological advances. Not only will device-specifi c
R&D and deployment be important to achieving these advances, but
technology improvements and innovation in ocean energy converters
are also likely to be infl uenced by developments in related fi elds. [6.6]
Integration of ocean energy into wider energy networks will need to
recognize the widely varying generation characteristics arising from
the different resources. For example, electricity generation from tidal
stream resources shows very high variability over one to four hours, yet
extremely limited variability over monthly or longer time horizons. [6.6]
6.7 Cost trends
Commercial markets are not yet driving marine energy technology development.
Government-supported R&D and national policy incentives are
the key motivations. Because none of the ocean energy technologies but
tidal barrages are mature (experience with other technologies is only now
becoming available for validation of demonstration/prototype devices), it
is diffi cult to accurately assess the economic viability of most ocean energy
technologies. [6.7.1]
Table TS.6.1 shows the best available data for some of the primary cost
factors that affect the levelized cost of electricity by each of the ocean
energy sub-types. In most cases, these cost and performance parameters
are based on sparse information due to the lack of peer-reviewed reference
data and actual operating experience, and in many cases therefore
refl ect estimated cost and performance assumptions based on engineering
knowledge. Present-day investment costs were found in a few instances
but are based on a small sample of projects and studies, which may not be
representative of the entire industry. [6.7.1]
Based on a standardized methodology outlined in Annex II and the cost
and performance data summarized in Annex III, the LCOE for tidal barrages
(which is currently the only commercially available ocean energy
technology) over a large set and range of input parameters has been
g
94
Technical Summary Summaries
calculated to range from US cent2005 12/kWh to US cent2005 32/kWh. This
range should, however, only be considered as indicative given the present
state of deployment experience. [1.3.2, 6.7.1, 6.7.3, 10.5.1, Annex II,
Annex III]
Because of the early stage of technology development, estimates of future
costs for ocean energy should be considered speculative. Nonetheless, the
cost of ocean energy is expected to decline over time as R&D, demonstrations,
and deployments proceed. [6.7.1–6.7.5]
6.8 Potential deployment
Until about 2008, ocean energy was not considered in any of the
major global energy scenario modelling activities and therefore its
potential impact on future world energy supplies and climate change
mitigation is just now beginning to be investigated. As such, the
results of the published scenarios literature as they relate to ocean
energy are sparse and preliminary, refl ecting a wide range of possible
outcomes. Specifi cally, scenarios for ocean energy deployment are
considered in only three major sources here: Energy [R]evolution (E[R])
2010, IEA World Energy Outlook (WEO) 2009 and Energy Technology
Perspectives (ETP) 2010. Multiple scenarios were considered in the
E[R] and the ETP reports and a single reference scenario was documented
in the WEO report. Each scenario is summarized in Table TS.6.2.
This preliminary presentation of scenarios that describe alternative levels
of ocean energy deployment is among the fi rst attempts to review the
potential role of ocean energy in the medium- to long-term scenarios
literature with the intention of establishing the potential contribution of
ocean energy to future energy supplies and climate change mitigation.
As shown by the limited number of existing scenarios, ocean energy has
the potential to help mitigate long-term climate change by offsetting
GHG emissions with projected deployments resulting in energy delivery
of up to 1,943 TWh/yr (~7 EJ/yr) by 2050. Other scenarios have been
developed that indicate deployment as low as 25 TWh/yr (0.9 EJ/yr) from
ocean energy. The wide range in results is based in part on uncertainty
about the degree to which climate change mitigation will drive energy
Table TS.6.2 | Main characteristics of medium- to long-term scenarios from major published studies that include ocean energy. [Table 6.5]
Deployment TWh/yr (PJ/yr) GW
Scenario 2010 2020 2030 2050 2050 Notes
Energy [R]evolution - Reference N/A
3
(10.8)
11
(36.6)
25
(90)
N/A No policy changes
Energy [R]evolution N/A
53
(191)
128
(461)
678
(2,440)
303 Assumes 50% carbon reduction
Energy [R]evolution – Advanced N/A
119
(428)
420
(1,512)
1,943
(6,994)
748 Assumes 80% carbon reduction
WEO 2009 N/A
3
(10.8)
13
(46.8)
N/A N/A Basis for E[R] reference case
ETP BLUE map 2050 N/A N/A N/A
133
(479)
N/A Power sector is virtually decarbonized
ETP BLUE map no CCS 2050 N/A N/A N/A
274
(986)
N/A
BLUE Map Variant – Carbon capture and storage is found
to not be possible
ETP BLUE map hi NUC 2050 N/A N/A N/A
99
(356)
N/A
BLUE Map Variant – Nuclear share is increased to 2,000
GW
ETP BLUE Map hi REN 2050 N/A N/A N/A
552
(1,987)
N/A BLUE Map Variant – Renewable share is increased to 75%
ETP BLUE map 3% N/A N/A N/A
401
(1,444)
N/A
BLUE Map Variant – Discount rates are set to 3% for
energy generation projects.
Table TS.6.1 | Summary of core available cost and performance parameters for all ocean energy technology sub-types. [Table 6.3]
Ocean Energy Technology
Investment Costs
(USD2005/kW)
Annual O&M Costs
(USD2005/kW)
Capacity Factor (CF)
(%)
Design Life
(years)
Wave 6,200–16,100 180 25–40 20
Tidal Range 4,500–5,000 100 22.5–28.5 40
Tidal Current 5,400–14,300 140 26–40 20
Ocean Current N/A N/A N/A 20
Ocean Thermal 4,200–12,3001 N/A N/A 20
Salinity Gradient N/A N/A N/A 20
Note: 1. Cost fi gures for ocean thermal energy have not been converted to 2005 USD.
95
Summaries Technical Summary
sector transformation, but for ocean energy, is also based on inherent
uncertainty as to when and if various ocean energy technologies become
commercially available at attractive costs. To better understand the possible
role of ocean energy in climate change mitigation, not only will
continued technical advances be necessary, but the scenarios modelling
process will need to increasingly incorporate the range of potential
ocean energy technology sub-types, with better data for resource potential,
present and future investment costs, O&M costs, and anticipated
capacity factors. Improving the availability of the data at global and
regional scales will be an important ingredient to improving coverage of
ocean energy in the scenarios literature. [6.8.4]
7. Wind Energy
7.1 Introduction
Wind energy has been used for millennia in a wide range of applications.
The use of wind energy to generate electricity on a commercial
scale, however, became viable only in the 1970s as a result of technical
advances and government support. A number of different wind energy
technologies are available across a range of applications, but the primary
use of wind energy of relevance to climate change mitigation is to
generate electricity from larger, grid-connected wind turbines, deployed
either on land (‘onshore’) or in sea- or freshwater (‘offshore’).11 [7.1]
Wind energy offers signifi cant potential for near-term (2020) and
long-term (2050) GHG emissions reductions. The wind power capacity
installed by the end of 2009 was capable of meeting roughly 1.8%
of worldwide electricity demand, and that contribution could grow
to in excess of 20% by 2050 if ambitious efforts are made to reduce
GHG emissions and to address other impediments to increased wind
energy deployment. Onshore wind energy is already being deployed at
a rapid pace in many countries, and no insurmountable technical barriers
exist that preclude increased levels of wind energy penetration
into electricity supply systems. Moreover, though average wind speeds
vary considerably by location, ample technical potential exists in most
regions of the world to enable signifi cant wind energy deployment. In
some areas with good wind resources, the cost of wind energy is already
competitive with current energy market prices, even without considering
relative environmental impacts. Nonetheless, in most regions of the
world, policy measures are still required to ensure rapid deployment.
Continued advancements in on- and offshore wind energy technology
are expected, however, further reducing the cost of wind energy and
improving wind energy’s GHG emissions reduction potential. [7.9]
11 Smaller wind turbines, higher-altitude wind electricity, and the use of wind energy in
mechanical and propulsion applications are only briefl y discussed in Chapter 7.
7.2 Resource potential
The global technical potential for wind energy is not fi xed, but is instead
related to the status of the technology and assumptions made regarding
other constraints to wind energy development. Nonetheless, a growing
number of global wind resource assessments have demonstrated that
the world’s technical potential exceeds current global electricity production.
[7.2]
No standardized approach has been developed to estimate the global
technical potential of wind energy: the diversity in data, methods,
assumptions, and even defi nitions for technical potential complicate
comparisons. The AR4 identifi ed the technical potential for onshore
wind energy as 180 EJ/yr (50,000 TWh/yr). Other estimates of the
global technical potential for wind energy that consider relatively more
development constraints range from a low of 70 EJ/yr (19,400 TWh/
yr) (onshore only) to a high of 450 EJ/yr (125,000 TWh/yr) (on- and
near-shore). This range corresponds to roughly one to six times global
electricity production in 2008, and may understate the technical potential
due to several of the studies relying on outdated assumptions, the
exclusion or only partial inclusion of offshore wind energy in some of
the studies, and methodological and computing limitations. Estimates
of the technical potential for offshore wind energy alone range from 15
EJ/yr to 130 EJ/yr (4,000 to 37,000 TWh/yr) when only considering relatively
shallower and near-shore applications; greater technical potential
is available if also considering deeper-water applications that might rely
on fl oating wind turbine designs. [7.2.1]
Regardless of whether existing estimates under- or overstate the technical
potential for wind energy, and although further advances in wind
resource assessment methods are needed, it is evident that the technical
potential of the resource itself is unlikely to be a limiting factor for
global wind energy deployment. Instead, economic constraints associated
with the cost of wind energy, institutional constraints and costs
associated with transmission access and operational integration, and
issues associated with social acceptance and environmental impacts are
likely to restrict growth well before any absolute limit to the global technical
potential is encountered. [7.2.1]
In addition, ample technical potential exists in most regions of the world
to enable signifi cant wind energy deployment. The wind resource is not
evenly distributed across the globe nor uniformly located near population
centres, however, and wind energy will therefore not contribute
equally in meeting the needs of every country. The technical potentials
for onshore wind energy in OECD North America and Eastern Europe/
Eurasia are found to be particularly sizable, whereas some areas of
non-OECD Asia and OECD Europe appear to have more limited onshore
technical potential. Figure TS.7.1, a global wind resource map, also
shows limited technical potential in certain areas of Latin America
and Africa, though other portions of those continents have signifi cant
96
Technical Summary Summaries
technical potential. Recent, detailed regional assessments have generally
found the size of the wind resource to be greater than estimated in
previous assessments. [7.2.2]
Global climate change may alter the geographic distribution and/or
the inter- and intra-annual variability of the wind resource, and/or the
quality of the wind resource, and/or the prevalence of extreme weather
events that may impact wind turbine design and operation. Research
to date suggests that it is unlikely that multi-year annual mean wind
speeds will change by more than a maximum of ±25% over most of
Europe and North America during the present century, while research
covering northern Europe suggests that multi-year annual mean wind
power densities will likely remain within ±50% of current values. Fewer
studies have been conducted for other regions of the world. Though
research in this fi eld is nascent and additional study is warranted,
research to date suggests that global climate change may alter the
geographic distribution of the wind resource, but that those effects are
unlikely to be of a magnitude to greatly impact the global potential for
wind energy deployment. [7.2.3]
7.3 Technology and applications
Modern, commercial grid-connected wind turbines have evolved from
small, simple machines to large, highly sophisticated devices. Scientifi c
and engineering expertise and advances, as well as improved computational
tools, design standards, manufacturing methods and O&M
procedures, have all supported these technology developments. [7.3]
Generating electricity from the wind requires that the kinetic energy
of moving air be converted to electrical energy, and the engineering
challenge for the wind energy industry is to design cost-effective wind
turbines and power plants to perform this conversion. Though a variety
of turbine confi gurations have been investigated, commercially available
turbines are primarily horizontal-axis machines with three blades
positioned upwind of the tower. In order to reduce the levelized cost of
wind energy, typical wind turbine sizes have grown signifi cantly (Figure
TS.7.2), with the largest fraction of onshore wind turbines installed
globally in 2009 having a rated capacity of 1.5 to 2.5 MW. As of 2010,
onshore wind turbines typically stand on 50- to 100-m towers, with
rotors that are often 50 to 100 m in diameter; commercial machines
Figure TS.7.2 | Growth in size of typical commercial wind turbines. [Figure 7.6]
Hub Height (m)
0
20
40
60
80
100
120
140
160
180
200
220
240
260
320
300
280 Past and Present
Wind Turbines
125m
5,000kW
150m
10,000kW
250m
20,000kW
100m
3,000kW
80m
70m 1,800kW
1,500kW
50m
750kW
30m
300kW
17m
75kW
2005- 2010-? 2010-? Future Future
2010
2000-
2005
1995-
2000
1990-
1995
1980-
1990
Rotor Diameter (m)
Rating (kW)
Future Wind
Turbines
Figure TS.7.1 | Example global wind resource map with 5 km x 5 km resolution. [Figure 7.1]
5km Global Wind Map
5 km Wind Map at 80m
Wind Speed (m/s)
3 6 9
\. 16% ¢}
· l]
97
Summaries Technical Summary
with rotor diameters and tower heights in excess of 125 m are operating,
and even larger machines are under development. Onshore wind
energy technology is already being commercially manufactured and
deployed at a large scale. [7.3.1]
Offshore wind energy technology is less mature than onshore, with
higher investment costs. Lower power plant availabilities and higher
O&M costs have also been common both because of the comparatively
less mature state of the technology and because of the inherently greater
logistical challenges of maintaining and servicing offshore turbines.
Nonetheless, considerable interest in offshore wind energy exists in the
EU and, increasingly, in other regions. The primary motivation to develop
offshore wind energy is to provide access to additional wind resources
in areas where onshore wind energy development is constrained by limited
technical potential and/or by planning and siting confl icts with other
land uses. Other motivations include the higher-quality wind resources
located at sea; the ability to use even larger wind turbines and the
potential to thereby gain additional economies of scale; the ability to
build larger power plants than onshore, gaining plant-level economies
of scale; and a potential reduction in the need for new, long-distance,
land-based transmission infrastructure to access distant onshore wind
energy. To date, offshore wind turbine technology has been very similar
to onshore designs, with some modifi cations and with special foundations.
As experience is gained, water depths are expected to increase and
more exposed locations with higher winds will be utilized. Wind energy
technology specifi cally tailored for offshore applications will become
more prevalent as the offshore market expands, and it is expected tha t
larger turbines in the 5 to 10 MW range may come to dominate this segment.
[7.3.1.3]
Alongside the evolution of wind turbine design, improved design and
testing methods have been codifi ed in International Electrotechnical
Commission standards. Certifi cation agencies rely on accredited design
and testing bodies to provide traceable documentation demonstrating
conformity with the standards in order to certify that turbines, components
or entire wind power plants meet common guidelines relating to
safety, reliability, performance and testing. [7.3.2]
From an electric system reliability perspective, an important part of the
wind turbine is the electrical conversion system. For modern turbines,
variable-speed machines now dominate the market, allowing for the
provision of real and reactive power as well as some fault ride-through
capability, but no intrinsic inertial response (i.e., turbines do not increase
or decrease power output in synchronism with system power imbalances);
wind turbine manufacturers have recognized this latter limitation
and are pursuing a variety of solutions. [7.3.3]
7.4 Global and regional status of market and
industry development
The wind energy market has expanded substantially, demonstrating
the commercial and economic viability of the technology and industry.
Wind energy expansion has been concentrated in a limited number of
regions, however, and further expansion, especially in regions with
little wind energy deployment to date and in offshore locations, is
likely to require additional policy measures. [7.4]
Wind energy has quickly established itself as part of the mainstream
electricity industry. From a cumulative capacity of 14 GW at the end
of 1999, global installed capacity increased twelve-fold in 10 years to
reach almost 160 GW by the end of 2009. The majority of the capacity
has been installed onshore, with offshore installations primarily
in Europe and totalling a cumulative 2.1 GW. The countries with the
highest installed capacity by the end of 2009 were the USA (35 GW),
China (26 GW), Germany (26 GW), Spain (19 GW) and India (11 GW).
The total investment cost of new wind power plants installed in 2009
was USD2005 57 billion, while worldwide direct employment in the
sector in 2009 has been estimated at approximately 500,000. [7.4.1,
7.4.2]
In both Europe and the USA, wind energy represents a major new
source of electric capacity additions. In 2009, roughly 39% of all
capacity additions in the USA and the EU came from wind energy;
in China, 16% of the net capacity additions in 2009 came from wind
energy. On a global basis, from 2000 through 2009, roughly 11% of
all newly installed net electric capacity additions came from new wind
power plants; in 2009 alone, that fi gure was probably more than 20%.
As a result, a number of countries are beginning to achieve relatively
high levels of annual wind electricity penetration in their respective
electric systems. By the end of 2009, wind power capacity was
capable of supplying electricity equal to roughly 20% of Denmark’s
annual electricity demand, 14% of Portugal’s, 14% of Spain’s, 11% of
Ireland’s and 8% of Germany’s. [7.4.2]
Despite these trends, wind energy remains a relatively small fraction of
worldwide electricity supply. The total wind power capacity installed
by the end of 2009 would, in an average year, meet roughly 1.8%
of worldwide electricity demand. Additionally, though the trend over
time has been for the wind energy industry to become less reliant on
European markets, with signifi cant recent expansion in the USA and
China, the market remains concentrated regionally: Latin America,
Africa and the Middle East, and the Pacifi c regions have installed relatively
little wind power capacity despite signifi cant technical potential
for wind energy in each region (Figure TS.7.3). [7.4.1, 7.4.2]
The deployment of wind energy must overcome a number of challenges,
including: the relative cost of wind energy compared to energy
market prices, at least if environmental impacts are not internalized
and monetized; concerns about the impact of wind energy’s variability;
challenges of building new transmission; cumbersome and slow
planning, siting and permitting procedures; the technical advancement
needs and higher cost of offshore wind energy technology; and
lack of institutional and technical knowledge in regions that have
not yet experienced substantial wind energy deployment. As a result,
growth is affected by a wide range of government policies. [7.4.4]
98
Technical Summary Summaries
7.5 Near-term grid integration issues
As wind energy deployment has increased, so have concerns about the
integration of that energy into electric systems. The nature and magnitude
of the integration challenge will depend on the characteristics of
the existing electric system and the level of wind electricity penetration.
Moreover, as discussed in Chapter 8, integration challenges are not
unique to wind energy. Nevertheless, analysis and operating experience
primarily from certain OECD countries suggests that, at low to medium
levels of wind electricity penetration (defi ned here as up to 20% of total
annual average electrical energy demand)12, the integration of wind
energy generally poses no insurmountable technical barriers and is economically
manageable. At the same time, even at low to medium levels
of wind electricity penetration, certain (and sometimes system-specifi c)
technical and/or institutional challenges must be addressed. Concerns
about (and the costs of) wind energy integration will grow with wind
energy deployment, and even higher levels of penetration may depend
on or benefi t from the availability of additional technological and institutional
options to increase fl exibility and maintain a balance between
supply and demand, as discussed further in Chapter 8 (Section 8.2). [7.5]
Wind energy has characteristics that present integration challenges,
and that must be considered in electric system planning and operation
to ensure the reliable and economical operation of the electric power
system. These include: the localized nature of the wind resource with
possible implications for new transmission for both on- and offshore
wind energy; the variability of wind power output over multiple time
scales; and the lower levels of predictability of wind power output than
12 This level of penetration was chosen to loosely separate the integration needs for wind
energy in the relatively near term from the broader, longer- term, and non-wind-specifi c
discussion of power system changes provided in Chapter 8.
are common for many other types of power plants. The aggregate variability
and uncertainty of wind power output depends, in part, on the
degree of correlation between the output of different geographically
dispersed wind power plants: generally, the outputs of wind power
plants that are farther apart are less correlated with each other, and
variability over shorter time periods (minutes) is less correlated than
variability over longer time periods (multiple hours). Forecasts of wind
power output are also more accurate over shorter time periods, and
when multiple plants are considered together. [7.5.2]
Detailed system planning for new generation and transmission
infrastructure is used to ensure that the electric system can be operated
reliably and economically in the future. To do so, planners need
computer-based simulation models that accurately characterize wind
energy. Additionally, as wind power capacity has increased, so has
the need for wind power plants to become more active participants in
maintaining the operability and power quality of the electric system,
and technical standards for grid connection have been implemented
to help prevent wind power plants from adversely affecting the electric
system during normal operation and contingencies. Transmission
adequacy evaluations, meanwhile, must account for the location dependence
of the wind resource, and consider any trade-offs between the
costs of expanding the transmission system to access higher-quality
wind resources in comparison to the costs of accessing lower-quality
wind resources that require less transmission investment. Even at low
to medium levels of wind electricity penetration, the addition of large
quantities of on- or offshore wind energy in areas with higher-quality
wind resources may require signifi cant new additions or upgrades to the
transmission system. Depending on the legal and regulatory framework
in any particular region, the institutional challenges of transmission
expansion can be substantial. Finally, planners need to account for wind
Figure TS.7.3 | Annual wind power capacity additions by region. [Figure 7.10]
Note: Regions shown in the fi gure are defi ned by the study.
0
2
4
6
8
10
12
14
16
Europe North America Asia Latin America Africa &
Middle East
Pacific
Annual Capacity Additions, by Region [GW]
2006
2007
2008
2009
■■
,--------_J :
99
Summaries Technical Summary
demand. Experience is limited, in particular with regard to system faults
at high instantaneous penetration levels, however, and as more wind
energy is deployed in diverse regions and electric systems, additional
knowledge about wind energy integration will be gained. [7.5.3]
In addition to actual operating experience, a number of high-quality
studies of the increased transmission and generation resources required
to accommodate wind energy have been completed, primarily covering
OECD countries. These studies employ a wide variety of methodologies
and have diverse objectives, but the results demonstrate that the cost
of integrating up to 20% wind energy into electric systems is, in most
cases, modest but not insignifi cant. Specifi cally, at low to medium levels
of wind electricity penetration, the available literature (again, primarily
from a subset of OECD countries) suggests that the additional costs
of managing electric system variability and uncertainty, ensuring generation
adequacy, and adding new transmission to accommodate wind
energy will be system specifi c but generally in the range of US cent2005
0.7/kWh to US cent2005 3/kWh. The technical challenges and costs of integration
are found to increase with wind electricity penetration. [7.5.4]
7.6 Environmental and social impacts
Wind energy has signifi cant potential to reduce (and is already reducing)
GHG emissions. Moreover, attempts to measure the relative impacts of
various electricity supply technologies suggest that wind energy generally
has a comparatively small environmental footprint. [9.3.4, 10.6]
As with other industrial activities, however, wind energy has the potential
to produce some detrimental impacts on the environment and on
human activities and well being, and many local and national governments
have established planning and siting requirements to reduce
those impacts. As wind energy deployment increases and as larger wind
power plants are considered, existing concerns may become more acute
and new concerns may arise. [7.6]
Although the major environmental benefi ts of wind energy result from
displacing electricity generated from fossil fuel-based power plants,
estimating those benefi ts is somewhat complicated by the operational
characteristics of the electric system and the investment decisions that
are made about new power plants. In the short run, increased wind
energy will typically displace the operations of existing fossil fuelfi
red plants. In the longer term, however, new generating plants may
be needed, and the presence of wind energy can infl uence what types
of power plants are built. The impacts arising from the manufacture,
transport, installation, operation and decommissioning of wind turbines
should also be considered, but a comprehensive review of available
studies demonstrates that the energy used and GHG emissions produced
during these steps are small compared to the energy generated
and emissions avoided over the lifetime of wind power plants. The GHG
emissions intensity of wind energy is estimated to range from 8 to 20 g
CO2/kWh in most instances, whereas energy payback times are between
3.4 and 8.5 months. In addition, managing the variability of wind power
power output variability in assessing the contribution of wind energy to
generation adequacy and therefore the long-term reliability of the electric
system. Though methods and objectives vary from region to region,
the contribution of wind energy to generation adequacy usually depends
on the correlation of wind power output with the periods of time when
there is a higher risk of a supply shortage, typically periods of high electricity
demand. The marginal contribution of wind energy to generation
adequacy typically declines as wind electricity penetration increases, but
aggregating wind power plants over larger areas may slow this decline
if adequate transmission capacity is available. The relatively low average
contribution of wind energy to generation adequacy (compared to
fossil units) suggests that electric systems with large amounts of wind
energy will also tend to have signifi cantly more total nameplate generation
capacity to meet the same peak electricity demand than will electric
systems without large amounts of wind energy. Some of this generation
capacity will operate infrequently, however, and the mix of other generation
will therefore tend (on economic grounds) to increasingly shift
towards fl exible ‘peaking’ and ‘intermediate’ resources and away from
’base-load’ resources. [7.5.2]
The unique characteristics of wind energy also have important implications
for electric system operations. Because wind energy is generated
with a very low marginal operating cost, it is typically used to meet
demand when it is available; other generators are then dispatched to
meet demand minus any available wind energy (i.e., ‘net demand’). As
wind electricity penetration grows, the variability of wind energy results
in an overall increase in the magnitude of changes in net demand, and
also a decrease in the minimum net demand. As a result of these trends,
wholesale electricity prices will tend to decline when wind power output
is high and transmission interconnector capacity to other energy markets
is constrained, and other generating units will be called upon to operate
in a more fl exible manner than required without wind energy. At low to
medium levels of wind electricity penetration, the increase in minute-tominute
variability is expected to be relatively small. The more signifi cant
operational challenges relate to the need to manage changes in wind
power output over one to six hours. Incorporating wind energy forecasts
into electric system operations can reduce the need for fl exibility from
other generators, but even with high-quality forecasts, system operators
will need a broad range of strategies to actively maintain the supply/
demand balance, including the use of fl exible power generation technologies,
wind energy output curtailment, and increased coordination
and interconnection between electric systems. Mass-market demand
response, bulk energy storage technologies, large-scale deployment of
electric vehicles and their associated contributions to system fl exibility
through controlled battery charging, diverting excess wind energy
to fuel production or local heating, and geographic diversifi cation of
wind power plant siting will also become increasingly benefi cial as wind
electricity penetration rises. Despite the challenges, actual operating
experience in different parts of the world demonstrates that electric systems
can operate reliably with increased contributions of wind energy; in
four countries (Denmark, Portugal, Spain, Ireland), wind energy in 2010
was already able to supply from 10 to roughly 20% of annual electricity
100
Technical Summary Summaries
output has not been found to signifi cantly degrade the GHG emissions
benefi ts of wind energy. [7.6.1]
Other studies have considered the local ecological impacts of wind
energy development. The construction and operation of both on- and
offshore wind power plants impacts wildlife through bird and bat collisions
and through habitat and ecosystem modifi cations, with the nature
and magnitude of those impacts being site- and species-specifi c. For
offshore wind energy, implications for benthic resources, fi sheries and
marine life more generally must be considered. Research is also underway
on the potential impact of wind power plants on the local climate.
Bird and bat fatalities through collisions with wind turbines are among
the most publicized environmental concerns. Though much remains
unknown about the nature and population-level implications of these
impacts, avian fatality rates have been reported at between 0.95 and
11.67 per MW per year. Raptor fatalities, though much lower in absolute
number, have raised special concerns in some cases, and as offshore
wind energy has increased, concerns have also been raised about seabirds.
Bat fatalities have not been researched as extensively, but fatality
rates ranging from 0.2 to 53.3 per MW per year have been reported; the
impact of wind power plants on bat populations is of particular contemporary
concern. The magnitude and population-level consequences
of bird and bat collision fatalities can also be viewed in the context of
other fatalities caused by human activities. The number of bird fatalities
at existing wind power plants appears to be orders of magnitude lower
than other anthropogenic causes of bird deaths, it has been suggested
that onshore wind power plants are not currently causing meaningful
declines in bird population levels, and other energy supply options
also impact birds and bats through collisions, habitat modifi cations and
contributions to global climate change. Improved methods to assess
species-specifi c population-level impacts and their possible mitigation
are needed, as are robust comparisons between the impacts of wind
energy and of other electricity supply options. [7.6.2]
Wind power plants can also impact habitats and ecosystems through
avoidance of or displacement from an area, habitat destruction and
reduced reproduction. Additionally, the impacts of wind power plants
on marine life have moved into focus as offshore development has
increased. The impacts of offshore wind energy on marine life vary
between the installation, operation and decommissioning phases,
depend greatly on site-specifi c conditions, and may be negative or
positive. Potential negative impacts include underwater sounds and
vibrations, electromagnetic fi elds, physical disruption and the establishment
of invasive species. The physical structures may, however, create
new breeding grounds or shelters and act as artifi cial reefs or fi sh
aggregation devices. Additional research is warranted on these impacts
and their long-term and population-level consequences, but they do
not appear to be disproportionately large compared to onshore wind
energy. [7.6.2]
Surveys have consistently found wind energy to be widely accepted by
the general public. Translating this support into increased deployment,
however, often requires the support of local host communities and/or
decision makers. To that end, in addition to ecological concerns, a number
of concerns are often raised about the impacts of wind power plants
on local communities. Perhaps most importantly, modern wind energy
technology involves large structures, so wind turbines are unavoidably
visible in the landscape. Other impacts of concern include land and
marine usage (including possible radar interference), proximal impacts
such as noise and fl icker, and property value impacts. Regardless of the
type and degree of social and environmental concerns, addressing them
is an essential part of any successful wind power planning and plant
siting process, and engaging local residents is often an integral aspect
of that process. Though some of the concerns can be readily mitigated,
others—such as visual impacts—are more diffi cult to address. Efforts to
better understand the nature and magnitude of the remaining impacts,
together with efforts to minimize and mitigate those impacts, will need
to be pursued in concert with increasing wind energy deployment. In
practice, planning and siting regulations vary dramatically by jurisdiction,
and planning and siting processes have been obstacles to wind
energy development in some countries and contexts. [7.6.3]
7.7 Prospects for technology improvement
and innovation
Over the past three decades, innovation in wind turbine design has led
to signifi cant cost reductions. Public and private R&D programmes have
played a major role in these technical advances, leading to system- and
component-level technology improvements, as well as improvements in
resource assessment, technical standards, electric system integration,
wind energy forecasting and other areas. From 1974 to 2006, government
R&D budgets for wind energy in IEA countries totalled USD2005
3.8 billion, representing 1% of total energy R&D expenditure. In 2008,
OECD research funding for wind energy totalled USD2005 180 million.
[7.7, 7.7.1]
Though onshore wind energy technology is already commercially manufactured
and deployed at a large scale, continued incremental advances
are expected to yield improved turbine design procedures, more effi cient
materials usage, increased reliability and energy capture, reduced O&M
costs and longer component lifetimes. In addition, as offshore wind
energy gains more attention, new technology challenges arise and more
radical technology innovations are possible. Wind power plants and turbines
are complex systems that require integrated design approaches to
optimize cost and performance. At the plant level, considerations include
the selection of a wind turbine for a given wind resource regime; wind
turbine siting, spacing and installation procedures; O&M methodologies;
and electric system integration. Studies have identifi ed a number of
areas where technology advances could result in changes in the investment
cost, annual energy production, reliability, O&M cost and electric
system integration of wind energy. [7.3.1, 7.7.1, 7.7.2]
At the component level, a range of opportunities are being pursued,
including: advanced tower concepts that reduce the need for large
cranes and minimize materials demands; advanced rotors and blades
101
Summaries Technical Summary
through better designs, coupled with better materials and advanced
manufacturing methods; reduced energy losses and improved availability
through advanced turbine control and condition monitoring;
advanced drive trains, generators and power electronics; and manufacturing
learning improvements. [7.7.3]
In addition, there are several areas of possible advancement that are
more specifi c to offshore wind energy, including O&M procedures,
installation and assembly schemes, support structure design, and the
development of larger turbines, possibly including new turbine concepts.
Foundation structure innovation, in particular, offers the potential
to access deeper waters, thereby increasing the technical potential of
wind energy. Offshore turbines have historically been installed primarily
in relatively shallow water, up to 30 m deep, on a mono-pile structure
that is essentially an extension of the tower, but gravity-based structures
have become more common. These approaches, as well as other
concepts that are more appropriate for deeper waters, including fl oating
platforms, are depicted in Figure TS.7.4. Additionally, offshore turbine
size is not restricted in the same way as onshore wind turbines, and the
relatively higher cost of offshore foundations provides motivation for
larger turbines. [7.7.3]
Wind turbines are designed to withstand a wide range of challenging
conditions with minimal attention. Signifi cant effort is therefore needed
to enhance fundamental understanding of the operating environment in
which turbines operate in order to facilitate a new generation of reliable,
safe, cost-effective wind turbines, and to further optimize wind power
plant siting and design. Research in the areas of aeroelastics, unsteady
aerodynamics, aeroacoustics, advanced control systems, and atmospheric
science, for example, is anticipated to lead to improved design
tools, and thereby increase the reliability of the technology and encourage
further design innovation. Fundamental research of this nature
will help improve wind turbine design, wind power plant performance
estimates, wind resource assessments, short-term wind energy forecasting,
and estimates of the impact of large-scale wind energy deployment
on the local climate, as well as the impact of potential climate change
effects on wind resources. [7.7.4]
7.8 Cost trends
Though the cost of wind energy has declined signifi cantly since the
1980s, policy measures are currently required to ensure rapid deployment
in most regions of the world. In some areas with good wind
resources, however, the cost of wind energy is competitive with current
energy market prices, even without considering relative environmental
impacts. Moreover, continued technology advancements are expected,
supporting further cost reduction. [7.8]
The levelized cost of energy from on- and offshore wind power plants is
affected by fi ve primary factors: annual energy production; investment
costs; O&M costs; fi nancing costs; and the assumed economic life of
Monopile Tri-Pod Jacket Suction Caisson Gravity Base
(b)
Ballast Stabilized “Spar-Buoy”
with Catenary Mooring Drag
Embedded Anchors
Mooring Line Stabilized
Tension Leg Platform
with Suction Pile Anchors
Buoyancy Stabilized
“Barge” with Catenary
Mooring Lines
Floating Wind Turbine Concepts
(a)
Figure TS.7.4 | Offshore wind turbine foundation designs: (a) near-term concepts and (b) fl oating offshore turbine concepts. [Figure 7.19]
102
Technical Summary Summaries
the power plant.13 From the 1980s to roughly 2004, the investment cost
of onshore wind power plants dropped. From 2004 to 2009, however,
investment costs increased, the primary drivers of which were: escalation
in the cost of labour and materials inputs; increasing profi t margins
among turbine manufacturers and their suppliers; the relative strength
of the Euro currency; and the increased size of turbine rotors and hub
heights. In 2009, the average investment cost for onshore wind power
plants installed worldwide was approximately USD2005 1,750/kW, with
many plants falling in the range of USD2005 1,400 to 2,100/kW; investment
costs in China in 2008 and 2009 were around USD2005 1,000 to
1,350/kW. There is far less experience with offshore wind power plants,
and the investment costs of offshore plants are highly site-specifi c.
Nonetheless, the investment costs of offshore plants have historically
been 50 to more than 100% higher than for onshore plants; O&M costs
are also greater for offshore plants. Offshore costs have also been infl uenced
by some of the same factors that caused rising onshore costs
from 2004 through 2009, as well as by several unique factors. The most
recently installed or announced offshore plants have investment costs
that are reported to range from roughly USD2005 3,200/kW to USD2005
5,000/kW. Notwithstanding the increased water depth of offshore
plants over time, the majority of the operating plants have been built in
relatively shallow water. The performance of wind power plants is highly
site-specifi c, and is primarily governed by the characteristics of the local
13 The economic competitiveness of wind energy in comparison to other energy
sources, which necessarily must also include other factors such as subsidies and
environmental externalities, is not covered in this section.
wind regime, but is also impacted by wind turbine design optimization,
performance and availability, and by the effectiveness of O&M procedures.
Performance therefore varies by location, but has also generally
improved with time. Offshore wind power plants are often exposed to
better wind resources. [7.8.1–7.8.3]
Based on a standardized methodology outlined in Annex II and the
cost and performance data summarized in Annex III, the LCOE for onand
offshore wind power plants over a large set and range of input
parameters has been calculated to range from US cent2005 3.5/kWh to
US cent2005 17/kWh and from US cent2005 7.5/kWh to US cent2005 23/kWh,
respectively. [1.3.2, 10.5.1, Annex II, Annex III]
Figure TS.7.5 presents the LCOE of on- and offshore wind energy over
a somewhat different set and range of parameters, and shows that the
LCOE varies substantially depending on assumed investment costs, energy
production and discount rates. For onshore wind energy, estimates are
provided for plants built in 2009; for offshore wind energy, estimates are
provided for plants built from 2008 to 2009 as well as those plants that
were planned for completion in the early 2010s. The LCOE for onshore
wind energy in good to excellent wind resource regimes are estimated
to average approximately US cent2005 5/kWh to US cent2005 10/kWh, and
can reach more than US cent2005 15/kWh in lower-resource areas. Though
(a) (b)
Levelized Cost of Energy [UScent2005 /kWh]
15 20 30 35 40 45 50
Capacity Factor [%]
0
5
10
15
20
35
30
25
Onshore Discount Rate = 10%
Onshore Discount Rate = 7%
Onshore Discount Rate = 3%
Offshore Discount Rate = 10%
Offshore Discount Rate = 7%
Offshore Discount Rate = 3%
25
Levelized Cost of Energy [UScent2005 /kWh]
15 20 30 35 40 45 50
Capacity Factor [%]
0
5
10
15
20
35
30
25
Onshore USD 2,100/kW
Europe Offshore Projects
China
European Low-Medium Wind Areas US Great Plains
Onshore USD 1,750/kW
Onshore USD 1,200/kW
Offshore USD 5,000/kW
Offshore USD 3,900/kW
Offshore USD 3,200/kW
25
Figure TS.7.5 | Estimated levelized cost of on- and offshore wind energy, 2009: (a) as a function of capacity factor and investment cost* and (b) as a function of capacity factor and
discount rate**. [Figure 7.23]
Notes: * Discount rate assumed to equal 7%. ** Onshore investment cost assumed at USD2005 1,750/kW, and offshore at USD2005 3,900/kW.
·E-
t
-El·
a-
E103
Summaries Technical Summary
the offshore cost estimates are more uncertain, typical LCOE are estimated
to range from US cent2005 10/kWh to more than US cent2005 20/kWh
for recently built or planned plants located in relatively shallow water.
Where the exploitable onshore wind resource is limited, offshore plants
can sometimes compete with onshore plants. [7.8.3, Annex II, Annex III]
A number of studies have developed forecasted cost trajectories for onand
offshore wind energy based on differing combinations of learning
curve estimates, engineering models and/or expert judgement. Among
these studies, the starting year of the forecasts, the methodological
approaches and the assumed wind energy deployment levels vary.
Nonetheless, a review of this literature supports the idea that continued
R&D, testing and experience could yield reductions in the levelized cost
of onshore wind energy of 10 to 30% by 2020. Offshore wind energy is
anticipated to experience somewhat deeper cost reductions of 10 to 40%
by 2020, though some studies have identifi ed scenarios in which market
factors lead to cost increases in the near to medium term. [7.8.4]
7.9 Potential deployment
Given the commercial maturity and cost of onshore wind energy technology,
increased utilization of wind energy offers the potential for
signifi cant near-term GHG emission reductions: this potential is not conditioned
on technology breakthroughs, and no insurmountable technical
barriers exist that preclude increased levels of wind energy penetration
into electricity supply systems. As a result, in the near to medium term,
the rapid increase in wind power capacity from 2000 to 2009 is expected
by many studies to continue. [7.9, 7.9.1]
Moreover, a number of studies have assessed the longer-term potential
of wind energy, often in the context of GHG concentration stabilization
scenarios. [10.2, 10.3] Based on a review of this literature (including 164
different long-term scenarios), and as summarized in Figure TS.7.6, wind
energy could play a signifi cant long-term role in reducing global GHG
emissions. By 2050, the median contribution of wind energy among the
scenarios with GHG concentration stabilization ranges of 440 to 600
ppm CO2 and <440 ppm CO2 is 23 to 27 EJ/yr (6,500 to 7,600 TWh/yr),
increasing to 45 to 47 EJ/yr at the 75th percentile of scenarios (12,400 to
12,900 TWh/yr), and to more than 100 EJ/yr in the highest study (31,500
TWh). Achieving this contribution would require wind energy to deliver
around 13 to 14% of global electricity supply in the median scenario
result by 2050, increasing to 21 to 25% at the 75th percentile of the
reviewed scenarios. [7.9.2]
Achieving the higher end of this range of global wind energy utilization
would likely require not only economic support policies of adequate
size and predictability, but also an expansion of wind energy utilization
regionally, increased reliance on offshore wind energy in some regions,
technical and institutional solutions to transmission constraints and
operational integration concerns, and proactive efforts to mitigate and
manage social and environmental concerns. Additional R&D is expected
to lead to incremental cost reductions for onshore wind energy, and
enhanced R&D expenditures may be especially important for offshore
wind energy technology. Finally, for those markets with good wind
resource potential but that are new to wind energy deployment, both
knowledge and technology transfer may help facilitate early wind power
plant installations. [7.9.2]
8. Integration of Renewable Energy
into Present and Future Energy
Systems
8.1 Introduction
In many countries, energy supply systems have evolved over decades,
enabling the effi cient and cost-effective distribution of electricity, gas,
heat and transport energy carriers to provide useful energy services to
end users. The transition to a low-carbon future that employs high shares
of RE may require considerable investment in new RE technologies and
infrastructure, including more fl exible electricity grids, expansion of district
heating and cooling schemes, distribution systems for RE-derived
gases and liquid fuels, energy storage systems, novel methods of transport,
and innovative distributed energy and control systems in buildings.
Enhanced RE integration can lead to the provision of the full range of
energy services for large and small communities in both developed and
developing countries. Regardless of the energy supply system presently
in place, whether in energy-rich or energy-poor communities, over the
long term, and through measured system planning and integration,
Figure TS.7.6 | Global primary energy supply of wind energy in long-term scenarios
(median, 25th to 75th percentile range, and full range of scenario results; colour coding is
based on categories of atmospheric CO2 concentration level in 2100; the specifi c number
of scenarios underlying the fi gure is indicated in the right upper corner). [Figure 7.24]
Global Wind Primary Energy Supply [EJ/yr]
CO2 Concentration Levels
Baselines
N=152
Cat. III + IV (440 - 600 ppm)
Cat. I + II (< 440 ppm)
0
20
60
40
80
100
120
2020 2030 2050
■■ ■
104
Technical Summary Summaries
there are few, if any, technical limits to increasing the shares of RE at
the national, regional and local scales as well as for individual buildings,
although other barriers may need to be overcome. [8.1, 8.2]
Energy supply systems are continuously evolving, with the aim of
increasing conversion technology effi ciencies, reducing losses and lowering
the costs of providing energy services to end users. To provide a
greater share of RE heating, cooling, transport fuels and electricity may
require modifi cation of current policies, markets and existing energy
supply systems over time so that they can accommodate higher rates of
deployment leading to greater supplies of RE. [8.1]
All countries have access to some RE resources and in many parts of the
world these are abundant. The characteristics of many of these resources
distinguish them from fossil fuels and nuclear systems. Some resources,
such as solar and ocean energy, are widely distributed, whereas others,
such as large-scale hydropower, are constrained by geographic location
and hence integration options are more centralized. Some RE resources
are variable and have limited predictability. Others have lower energy
densities and their technical specifi cations differ from solid, liquid and
gaseous fossil fuels. Such RE resource characteristics can constrain the
ease of integration and invoke additional system costs, particularly
when reaching higher shares of RE. [8.1, 8.2]
Following the structural outline of Chapter 8, RE resources can be used
through integration into energy supply networks delivering energy to
consumers using energy carriers with varying shares of RE embedded or
by direct integration into the transport, buildings, industry and agriculture
end-use sectors (Figure TS.8.1). [8.2, 8.3]
The general and specifi c requirements for enhanced integration of RE
into energy supply systems are reasonably well understood. However,
since integration issues tend to be site-specifi c, analyses of typical additional
costs for RE integration options are limited and future research is
required for use in scenario modelling. For example, it is not clear how
the possible trend towards more decentralized energy supply systems
might affect the future costs for developing further centralized heat and
power supplies and the possible avoidance of constructing new infrastructure.
[8.2]
Centralized energy systems, based mainly on fossil fuels, have evolved
to provide reasonably cost-effective energy services to end users using
Fossil Fuels
and Nuclear
Energy Efficiency
Measures
Energy Efficiency
and Demand
Response Measures
Renewable Energy Resources
End-Use Sectors
(Section 8.3)
Energy Supply
Systems
(Section 8.2)
Electricity Generation and
Distribution
Heating and Cooling Networks
Gas Grids
Liquid Fuels Distribution
Autonomous Systems
Transport and Vehicles
Buildings and Households
Industry
Agriculture, Forests and
Fisheries
Energy
Carriers
Energy
Services
Energy
Consumers
Figure TS.8.1 | Pathways for RE integration to provide energy services, either into energy supply systems or on-site for use by the end-use sectors. [Figure 8.1]
I
I
I
I
105
Summaries Technical Summary
a range of energy carriers including solid, liquid and gaseous fuels, electricity,
and heat. Increasing the deployment of RE technologies requires
their integration into these existing systems by overcoming the associated
technical, economic, environmental and social barriers. The advent
of decentralized energy systems could open up new deployment opportunities.
[8.1, 8.2]
In some regions, RE electricity systems could become the dominant
future energy supply, especially if heating and transport demands are
also to be met by electricity. This could be driven by parallel developments
in electric vehicles, increased heating and cooling using electricity
(including heat pumps), fl exible demand response services (including the
use of smart meters), and other innovative technologies. [8.1, 8.2.1.2,
8.2.2, 8.3.1–8.3.3]
The various energy systems differ markedly between countries and
regions around the world and each is complex. As a result, a range of
approaches are needed to encourage RE integration, whether centralized
or decentralized. Prior to making any signifi cant change in an energy
supply system that involves increasing the integration of RE, a careful
assessment of the RE resource availability; the suitability of existing
technologies; institutional, economic and social constraints; the potential
risks; and the need for related capacity building and skills development
should be undertaken. [8.1, 8.2]
The majority of scenarios that stabilize atmospheric GHG concentrations
around 450 ppm CO2eq show that RE will exceed a 50% share of
low-carbon primary energy by 2050. This transition can be illustrated by
many scenarios, the single example of increasing market shares shown
in Figure TS.8.2 being based on the IEA’s World Energy Outlook 2010
‘450 Policy Scenario’. To achieve such increased shares of primary and
consumer energy from RE by 2035 would require the annual average
incremental growth in primary RE to more than treble from today’s level
to around 4.0 EJ/yr. [8.1, 10.2, 10.2.2.4]
In order to gain greater RE deployment in each of the transport, building,
industry and agriculture sectors, strategic elements need to be better
understood, as do the social issues. Transition pathways for increasing
the shares of each RE technology through integration depend on the
specifi c sector, technology and region. Facilitating a smoother integration
with energy supply systems and providing multiple benefi ts for energy
end users should be the ultimate aims. [8.2, 8.3]
Several mature RE technologies have already been successfully integrated
into a wide range of energy supply systems, mostly at relatively
low shares but with some examples (including small- and large-scale
hydropower, wind power, geothermal heat and power, fi rst-generation
biofuels and solar water heating systems) exceeding 30%. This was due
mainly to their improved cost-competitiveness, an increase in support
policies and growing public support due to the threats of an insecure
energy supply and climate change. Exceptional examples are large-scale
hydropower in Norway and hydro and geothermal power in Iceland
approaching 100% of RE electricity, as has also been achieved by several
small islands and towns. [8.2.1.3, 8.2.5.5, 11.2, 11.5]
Other less mature technologies require continuing investment in
research, development, and demonstration (RD&D), infrastructure, capacity
building and other supporting measures over the longer term. Such
technologies include advanced biofuels, fuel cells, solar fuels, distributed
power generation control systems, electric vehicles, solar absorption
cooling and enhanced geothermal systems. [11.5, 11.6]
The current status of RE use varies for each end-use sector. There are
also major regional variations in future pathways to enhance further
integration by removal of barriers. For example, in the building sector,
integrating RE technologies is vastly different for commercial high-rise
buildings and apartments in mega-cities than for integration into small,
modest village dwellings in developing countries that currently have limited
access to energy services. [8.3.2]
Most energy supply systems can accommodate a greater share of RE
than at present, particularly if the RE share is at relatively low levels (usually
assumed to be below a 20% share of electricity, heat, pipeline gas
blend or biofuel blend). To accommodate higher RE shares in the future,
most energy supply systems will need to evolve and be adapted. In all
cases, the maximum practical RE share will depend on the technologies
involved, the RE resources available and the type and age of the present
energy system. Further integration and increased rates of deployment
can be encouraged by local, national and regional initiatives. The overall
aim of Chapter 8 is to present the current knowledge on opportunities
and challenges relating to RE integration for governments wishing to
develop a coherent framework in preparation for future higher levels of
RE penetration. Existing power supply systems, natural gas grids, heating/
cooling schemes, petroleum-based transport fuel supply distribution
networks and vehicles can all be adapted to accommodate greater supplies
of RE than at present. RE technologies range from mature to those
at the early concept demonstration stage. New technologies could enable
increased RE uptake and their integration will depend upon improved
cost-effectiveness, social acceptance, reliability and political support at
national and local government levels in order to gain greater market
shares. [8.1.2, 11.5]
Taking a holistic approach to the whole energy system may be a prerequisite
to ensure effi cient and fl exible RE integration. This would include
achieving mutual support between the different energy sectors, an intelligent
forecasting and control strategy and coherent long-term planning.
Together, these would enable the provision of electricity, heating, cooling
and mobility to be more closely inter-linked. The optimum combination
of technologies and social mechanisms to enable RE integration to reach
high shares varies with the limitations of specifi c site conditions, characteristics
of the available RE resources, and local energy demands. Exactly
how present energy supply and demand systems can be adapted and
developed to accommodate higher shares of RE, and the additional costs
involved for their integration, depend on the specifi c circumstances, so
106
Technical Summary Summaries
Final
Consumption
374 EJ
Final
Consumption
294 EJ
Primary Energy
577 EJ
2035
2008
Primary Energy
492 EJ
Agriculture
8 EJ
Transport
96 EJ
Industry
98 EJ
Buildings
92 EJ
Agriculture
9 EJ
Transport
119 EJ
Industry
130 EJ
Buildings
116EJ
Modern Renewable
Traditional Biomass
Non-Renewable Energy
Losses
203 EJ
Losses
197 EJ
1 EJ
7 EJ
2 EJ
7 EJ
427 EJ
31 EJ
33 EJ
4 EJ
2 EJ
30 EJ
100 EJ
4
EJ4 EJ
78 EJ
34 EJ
18 EJ 101 EJ
11 EJ
87 EJ
80 EJ
8 EJ
94 EJ
29 EJ
128 EJ
420 EJ
L
159 EJ
25 EJ
44 EJ
134 EJ
11 EJ
27 EJ
159 EJ
■
■
■
.-
107
Summaries Technical Summary
further studies will be required. This is particularly the case for the electricity
sector due to the wide variety of existing power generation systems
and scales that vary with country and region. [8.2.1, 8.2.2, 8.3]
8.2 Integration of renewable energy into
electrical power systems
Electrical power systems have been evolving since the end of the 19th
century. Today, electrical power systems vary in scale and technological
sophistication from the synchronized Eastern Interconnection in North
America to small individual diesel-powered autonomous systems, with
some systems, as in China, undergoing rapid expansion and transformation.
Within these differences, however, electrical power systems are
operated and planned with a common purpose of providing a reliable
and cost-effective supply of electricity. Looking forward, electric power
systems are expected to continue to expand in importance given that they
supply modern energy, enable the transport of energy over long distances,
and provide a potential pathway for delivering low-carbon energy. [8.2.1]
Electric power systems have several important characteristics that affect
the challenges of integrating RE. The majority of electric power systems
operate using alternating current (AC) whereby the majority of generation
is synchronized and operated at a frequency of approximately either
50 or 60 Hz, depending on the region. The demand for electricity varies
throughout the day, week and season, depending on the needs of electricity
users. The aggregate variation in demand is matched by variation
in schedules and dispatch instructions for generation in order to continuously
maintain a balance between supply and demand. Generators and
other power system assets are used to provide active power control to
maintain the system frequency and reactive power control to maintain
voltage within specifi ed limits. Minute-to-minute variations in supply
and demand are managed with automatic control of generation through
services called regulation and load following, while changes over longer
time scales of hours to days are managed by dispatching and scheduling
generation (including turning generation on or off, which is also known
as unit commitment). This continuous balancing is required irrespective
of the mechanism used to achieve it. Some regions choose organized
electricity markets in order to determine which generation units should
be committed and/or how they should be dispatched. Even autonomous
systems must employ methods to maintain a balance between generation
and demand (via controllable generators, controllable loads, or storage
resources like batteries). [8.2.1.1]
In addition to maintaining a balance between supply and demand, electric
power systems must also transfer electricity between generation
and demand through transmission and distribution networks with limited
capacity. Ensuring availability of adequate generation and network
capacity requires planning over multiple years. Planning electrical power
systems incorporates the knowledge that individual components of the
system, including generation and network components, will periodically
fail (a contingency). A target degree of reliability can be met, however,
by building adequate resources. One important metric used to determine
the contribution of generation—fossil-fuel based or renewable—to
meeting demand with a target level of reliability is called the capacity
credit. [8.2.1.1]
Based on the features of electrical power systems, several RE characteristics
are important for integrating RE into power systems. In
particular, variability and predictability (or uncertainty) of RE is relevant
for scheduling and dispatch in the electrical power system, the location
of RE resources is a relevant indicator for impact on needs for electrical
networks, and capacity factor, capacity credit and power plant
characteristics are indicators relevant for comparison, for example, with
thermal generation. [8.2.1.2]
Some RE electricity resources (particularly ocean, solar PV, wind)
are variable and only partially dispatchable: generation from these
resources can be reduced if needed, but maximum generation depends
on availability of the RE resource (e.g., tidal currents, sun or wind). The
capacity credit can be low if the generation is not well correlated with
times of high demand. In addition, the variability and partial predictability
of some RE increases the burden on dispatchable generation or
other resources to ensure balance between supply and demand given
deviations in RE. In many cases variability and partial predictability are
somewhat mitigated by geographic diversity—changes and forecast
errors will not always occur at the same time in the same direction. A
general challenge for most RE, however, is that renewable resources are
location specifi c, therefore concentrated renewably generated electricity
may need to be transported over considerable distances and require
network expansion. Dispatchable renewable sources (including hydropower,
bioenergy, geothermal energy, and CSP with thermal storage)
can in many cases offer extra fl exibility for the system to integrate other
renewable sources and often have a higher capacity credit. [8.2.1.2]
A very brief summary of the particular characteristics for a selection of
the technologies is given in Table TS.8.1. [8.2.1.3]
Figure TS.8.2 | (Preceding page) RE shares (red) of primary and fi nal consumption energy in the transport, buildings (including traditional biomass), industry and agriculture sectors
in 2008 and an indication of the projected increased RE shares needed by 2035 in order to be consistent with a 450 ppm CO2eq stabilization level. [Figure 8.2]
Notes: Area of circles are approximately to scale. Energy system losses occur during the conversion, refi ning and distribution of primary energy sources to produce energy services for
fi nal consumption. ‘Non-renewable’ energy (blue) includes coal, oil, natural gas (with and without CCS by 2035) and nuclear power. This scenario example is based on data taken from
the IEA World Energy Outlook 2010 but converted to direct equivalents. [Annex II.4] Energy effi ciency improvements above the baseline are included in the 2035 projection. RE in
the buildings sector includes traditional solid biomass fuels (yellow) for cooking and heating for 2.7 billion people in developing countries [2.2] along with some coal. By 2035, some
traditional biomass has been partly replaced by modern bioenergy conversion systems. Excluding traditional biomass, the overall RE system effi ciency (when converting from primary
to consumer energy) remains around 66%.
108
Technical Summary Summaries
Table TS.8.1 | Summary of integration characteristics for a selection of RE technologies. [Table 8.1]
Technology
Plant size
range
(MW)
Variability:
Characteristic time
scales for power system
operation
(Time scale)
Dispatchability
(See legend)
Geographical
diversity potential
(See legend)
Predictability
(See legend)
Capacity factor
range
%
Capacity
credit range
%
Active power,
frequency
control
(See legend)
Voltage,
reactive power
control
(See legend)
Bioenergy 0.1–100
Seasons (depending on biomass
availability)
+++ + ++ 50–90
Similar to thermal
and CHP
++ ++
Direct solar
energy
PV
0.004–100
modular
Minutes to years + ++ + 12–27 <25–75 + +
CSP with thermal
storage1
50–250 Hours to years
++ +2 ++ 35–42 90 ++ ++
Geothermal
energy
2–100 Years +++ N/A ++ 60–90
Similar to
thermal
++ ++
Hydro power
Run of river 0.1–1,500 Hours to years ++ + ++ 20–95 0–90 ++ ++
Reservoir 1–20,000 Days to years +++ + ++ 30–60
Similar to
thermal
++ ++
Ocean Energy
Tidal range 0.1–300 Hours to days + + ++ 22.5–28.5 <10% ++ ++
Tidal current 1–200 Hours to days + + ++ 19–60 10–20 + ++
Wave 1–200 Minutes to years + ++ + 22–31 16 + +
Wind energy 5–300
Minutes to years + ++ +
20–40 onshore,
30–45 offshore
5–40 + ++
Notes: 1. Assuming a CSP system with six hours of thermal storage in US Southwest. 2. In areas with direct-normal irradiance (DNI) >2,000 kWh/m2/yr (7,200 MJ/m2/yr).
Plant size: range of typical rated plant capacity.
Characteristic time scales: time scales where variability signifi cant for power system integration occurs.
Dispatchability: degree of plant dispatchability: + low partial dispatchability, ++ partial dispatchability, +++ dispatchable.
Geographical diversity potential: degree to which siting of the technology may mitigate variability and improve predictability, without substantial need for additional network: +moderate potential, ++ high diversity potential.
Predictability: Accuracy to which plant output power can be predicted at relevant time scales to assist power system operation: + moderate prediction accuracy (typical <10% Root Mean Square (RMS) error of rated power day ahead),
++ high prediction accuracy.
Active power and frequency control: technology possibilities enabling plant to participate in active power control and frequency response during normal situations (steady state, dynamic) and during network fault situations (for example active
power support during fault ride-through): + good possibilities, ++ full control possibilities.
Voltage and reactive power control: technology possibilities enabling plant to participate in voltage and reactive power control during normal situations (steady state, dynamic) and during network fault situations (for example reactive power
support during fault ride-through): + good possibilities, ++ full control possibilities.
109
Summaries Technical Summary
There is already signifi cant experience with operating electrical power
systems with a large share of renewable sources, in particular hydropower
and geothermal power. Hydropower storage and strong interconnections
help manage fl uctuations in river fl ows. Balancing costs for variable generation
are incurred when there are differences between the scheduled
generation (according to forecasts) and the actual production. Variability
and uncertainty increase balancing requirements. Overall, balancing is
expected to become more diffi cult to achieve as partially dispatchable RE
penetrations increase. Studies show clearly that combining different variable
renewable sources, and resources from larger geographical areas,
will be benefi cial in smoothing the variability and decreasing overall
uncertainty for the power systems. [8.2.1.3]
The key issue is the importance of network infrastructure, both to deliver
power from the generation plant to the consumer as well as to enable
larger regions to be balanced. Strengthening connections within an
electrical power system and introducing additional interconnections to
other systems can directly mitigate the impact of variable and uncertain
RE sources. Network expansion is required for most RE, although
the level is dependent on the resource and location relative to existing
network infrastructure. Amongst other challenges will be expanding network
infrastructure within the context of public opposition to overhead
network infrastructure. In general, major changes will be required in the
generation plant mix, the electrical power systems’ infrastructure and
operational procedures to make the transition to increased renewable
generation while maintaining cost and environmental effectiveness.
These changes will require major investments far enough in advance to
maintain a reliable and secure electricity supply. [8.2.1.3]
In addition to improving network infrastructure, several other important
integration options have been identifi ed through operating experience
or studies:
Increased generation fl exibility: An increasing penetration of variable
renewable sources implies a greater need to manage variability
and uncertainty. Greater fl exibility is required from the generation mix.
Generation provides most of a power system’s existing fl exibility to cope
with variability and uncertainty through ramping up or down and cycling
as needed. Greater need for fl exibility can imply either investment in
new fl exible generation or improvements to existing power plants to
enable them to operate in a more fl exible manner. [8.2.1.3]
Demand side measures: Although demand side measures have historically
been implemented only to reduce average demand or demand
during peak load periods, demand side measures may potentially contribute
to meeting needs resulting from increased variable renewable
generation. The development of advanced communications technology,
with smart electricity meters linked to control centres, offers the potential
to access much greater levels of fl exibility from demand. Electricity
users can be provided with incentives to modify and/or reduce their consumption
by pricing electricity differently at different times, in particular
with higher prices during higher demand periods. This reduction in
demand during high demand periods can mitigate the impact of the
low capacity credit of some types of variable generation. Furthermore,
demand that can quickly be curtailed without notice during any time of
the year can provide reserves rather than requiring generation resources
to provide this reserve. Demand that can be scheduled to be met at
anytime of the day or that responds to real-time electricity prices can
participate in intra-day balancing thereby mitigating operational challenges
that are expected to become increasingly diffi cult with variable
generation. [8.2.1.3]
Electrical energy storage: By storing electrical energy when renewable
output is high and the demand low, and generating when
renewable output is low and the demand high, the curtailment of RE
can be reduced, and the base-load units on the system will operate more
effi ciently. Storage can also reduce transmission congestion and may
reduce the need for, or delay, transmission upgrades. Technologies such
as batteries or fl ywheels that store smaller amounts of energy (minutes
to hours) can in theory be used to provide power in the intra-hour timeframe
to regulate the balance between supply and demand. [8.2.1.3]
Improved operational/market and planning methods: To help cope
with the variability and uncertainty associated with variable generation
sources, forecasts of their output can be combined with improved operational
methods to determine both the required reserve to maintain the
demand-generation balance, and also optimal generation scheduling.
Making scheduling decisions closer to real time (i.e., shorter gate closure
time in markets) and more frequently allows newer, more accurate
information to be used in dispatching generating units. Moving to larger
balancing areas, or shared balancing between areas, is also desirable
with large amounts of variable generation, due to the aggregation benefi
ts of multiple, dispersed renewable sources. [8.2.1.3]
In summary, RE can be integrated into all types of electrical power
systems from large interconnected continental-scale systems to small
autonomous systems. System characteristics including the network
infrastructure, demand pattern and its geographic location, generation
mix, control and communication capability combined with the
location, geographical footprint, variability and predictability of the
renewable resources determine the scale of the integration challenge.
As the amounts of RE resources increase, additional electricity network
infrastructure (transmission and/or distribution) will generally have to
be constructed. Variable renewable sources, such as wind, can be more
diffi cult to integrate than dispatchable renewable sources, such as bioenergy,
and with increasing levels maintaining reliability becomes more
challenging and costly. These challenges and costs can be minimized by
deploying a portfolio of options including electrical network interconnection,
the development of complementary fl exible generation, larger
balancing areas, sub-hourly markets, demand that can respond in relation
to supply availability, storage technologies, and better forecasting,
system operating and planning tools.
110
Technical Summary Summaries
Several high-latitude countries already have a district heating market
penetration of 30 to 50%, with Iceland reaching 96% using its geothermal
resources. World annual delivery of district heat has been estimated
to be around 11 EJ though heat data are uncertain. [8.2.2.1]
DH schemes can provide electricity through CHP system designs and
can also provide demand response options that can facilitate increased
integration of RE, including by using RE electricity for heat pumps and
electric boilers. Thermal storage systems can bridge the heat supply/
demand gap resulting from variable, discontinuous or non-synchronized
heating systems. For short-term storage (hours and days), the thermal
capacity of the distribution network itself can be used. Thermal storage
systems with storage periods up to several months at temperatures up
to hundreds of degrees Celsius use a variety of materials and corresponding
storage mechanisms that can have capacities up to several
TJ. Combined production of heat, cold and electricity (tri-generation), as
well as the possibility for diurnal and seasonal storage of heat and cold,
mean that high overall system effi ciency can be obtained and higher
shares of RE achieved through increased integration. [8.2.2.2, 8.2.2.3]
Many commercial geothermal and biomass heat and CHP plants have
been successfully integrated into DH systems without government support.
Several large-scale solar thermal systems with collector areas
8.3 Integration of renewable energy into
heating and cooling networks
A district heating (DH) or district cooling (DC) network allows multiple
energy sources (Figure TS.8.3) to be connected to many energy consumers
by pumping the energy carriers (hot or cold water and sometimes
steam) through insulated underground pipelines. Centralized heat production
can facilitate the use of low-cost and/or low-grade RE heat from
geothermal or solar thermal sources or combustion of biomass (including
refuse-derived fuels and waste by-products that are often unsuitable
for use by individual heating systems). Waste heat from CHP generation
and industrial processes can also be used. This fl exibility produces competition
among various heat sources, fuels and technologies. Centralized
heat production can also facilitate the application of cost-effective measures
that reduce local air pollution compared with having a multitude
of small individual boilers. Being fl exible in the sources of heat or cold
utilized, district heating and cooling systems allow for the continuing
uptake of several types of RE so that a gradual or rapid substitution of
competing fossil fuels is usually feasible. [8.2.2]
Occupiers of buildings and industries connected to a network can benefi
t from a professionally managed central system, hence avoiding the
need to operate and maintain individual heating/cooling equipment.
Integrated Renewable Energy District Heating & Cooling System
Accumulator
(Hot Water)
7 C
1
5 4
University
R&D Centre
Commercial &
Domestic Buildings
Hydrogen
Dispenser
Heat Pump
for Heating & Cooling
(Heat Source: Sewage)
Landfill Gas
Bioenergy Oil
Wood Chips
Energy Plant
Solar Thermal
Collectors B
6 A
3
2
Figure TS.8.3 | An integrated RE-based energy plant in Lillestrøm, Norway, supplying the University, R&D Centre and a range of commercial and domestic buildings using a district
heating and cooling system incorporating a range of RE heat sources, thermal storage and a hydrogen production and distribution system. (Total investment around USD2005 25 million
and due for completion in 2011.) 1) Central energy system with 1,200 m3 accumulator hot water storage tank; (2) 20 MWth wood burner system (with fl ue gas heat recovery); (3) 40
MWth bio-oil burner; (4) 4.5 MWth heat pump; (5) 1.5 MWth landfi ll gas burner and a 5 km pipeline; (6) 10,000 m2 solar thermal collector system; and (7) RE-based hydrogen production
(using water electrolysis and sorption-enhanced steam methane reforming of landfi ll gas) and vehicle dispensing system. [Figure 8.3]
0
0
0 e •• •• • .»
0
111
Summaries Technical Summary
of around 10,000 m2 (Figure TS.8.3) have also been built in Denmark,
Norway and elsewhere. The best mix of hot and cold sources, and heat
transfer and storage technologies, depends strongly on local conditions,
including user demand patterns. As a result, the heat energy supply mix
varies widely between different systems. [3.5.3, 8.2.2]
Establishing or expanding a DH scheme involves high up-front capital
costs for the piping network. Distribution costs alone can represent
roughly half of the total cost but are subject to large variations depending
on the heat demand density and the local conditions for building the
insulated piping network. Increasing urbanization facilitates DH since
network capital costs are lower for green-fi eld sites and distribution
losses per unit of heat delivered are lower in areas with higher heat
demand densities. Heat distribution losses typically range from 5 to 30%
but the extent to which high losses are considered a problem depends
on the source and cost of the heat. [8.2.2.1, 8.2.2.3]
Expanding the use of deep geothermal and biomass CHP plants in DH
systems can facilitate a higher share of RE sources, but to be economically
viable this usually requires the overall system to have a large heat
load. Some governments therefore support investments in DH networks
as well as provide additional incentives for using RE in the system.
[8.2.2.4]
Modern building designs and uses have tended to reduce their
demand for additional heating whereas the global demand for cooling
has tended to increase. The cooling demand to provide comfort has
increased in some low-latitude regions where countries have become
wealthier and in some higher latitudes where summers have become
warmer. Cooling load reductions can be achieved by the use of passive
cooling building design options or active RE solutions including solar
absorption chillers. As for DH, the rate of uptake of energy effi ciency
to reduce cooling demand, deployment of new technologies, and the
structure of the market, will determine the viability of developing a DC
scheme. Modern DC systems, ranging from 5 to 300 MWth, have been
operating successfully for many years using natural aquifers, waterways,
the sea or deep lakes as the sources of cold, classed as a form of
RE. [8.2.2.4]
DH and DC schemes have typically been developed in situations
where strong planning powers have existed, such as centrally planned
economies, US university campuses, Western European countries with
multi-utilities, and urban areas controlled by local municipalities.
8.4 Integration of renewable energy into
gas grids
Over the past 50 years, large natural gas networks have been developed
in several parts of the world. And more recently there has been
increasing interest to ‘green’ them by integrating RE-based gases.
Gaseous fuels from RE sources originate largely from biomass and can
be produced either by anaerobic digestion to produce biogas (mainly
methane and CO2) or thermo-chemically to give synthesis (or producer)
gas (mainly hydrogen and carbon monoxide). Biomethane, synthesis gas
and, in the longer term, RE-based hydrogen can be injected into existing
gas pipelines for distribution at the national, regional or local level.
Differences in existing infrastructure, gas quality, and production and
consumption levels can make planning diffi cult for increasing the RE
share of gases by integration into an existing grid. [8.2.3, 8.2.3.1]
Biogas production is growing rapidly and several large gas companies
are now making plans to upgrade large quantities for injection at the
required quality into national or regional transmission gas pipelines.
Most of the biomethane currently produced around the world is already
distributed in local gas pipeline systems primarily dedicated for heating
purposes. This can be a cheaper option per unit of energy delivered
(Figure TS.8.4) than when transported by trucks (usually to fi lling stations
for supplying gas-powered vehicles) depending on distance and
the annual volume to be transported. [8.2.3.4]
Gas utilization can be highly effi cient when combusted for heat; used
to generate electricity by fuelling gas engines, gas boilers or gas turbines;
or used in vehicles either compressed or converted to a range of
liquid fuels using various processes. For example, biogas or landfi ll gas
can be combusted onsite to produce heat and/or electricity; cleaned and
upgraded to natural gas quality biomethane for injection into gas grids;
or, after compressing or liquefying, distributed to vehicle fi lling stations
for use in dedicated or dual gas-fuelled vehicles. [8.2.3.2–8.2.3.4]
Technical challenges relate to gas source, composition and quality. Only
biogas and syngas of a specifi ed quality can be injected into existing gas
Liquid Methane Tapped
from Natural Gas Pipeline
Pressure Stations
Compressed Methane
Transported in Pipelines
Liquid Methane with
Cryogenic Upgrading
Transported by Truck
Compressed Gas
Transported by Truck
0
5
10
15
[USD2005 /GJ]
30
25
20
Figure TS.8.4 | Relative costs for distributing and dispensing biomethane (either
compressed or liquefi ed) at the medium scale by truck or pipeline in Europe. [Figure 8.9]
■
■
■
■
112
Technical Summary Summaries
grids so clean-up is a critical step to remove water, CO2 (thereby increasing
the heating value) and additional by-products from the gas stream.
The cost of upgrading varies according to the scale of the facility and the
process, which can consume around 3 to 6% of the energy content of
the gas. RE gas systems are likely to require signifi cant storage capacity
to account for variability and seasonality of supply. The size and shape
of storage facilities and the required quality of the gas will depend on
the primary energy source of production and its end use. [8.2.3]
Hydrogen gas can be produced from RE sources by several routes including
biomass gasifi cation, the reformation of biomethane, or electrolysis
of water. The potential RE resource base for hydrogen is therefore greater
than for biogas or syngas. Future production of hydrogen from variable
RE resources, such as wind or solar power by electrolysis, will depend
signifi cantly on the interaction with existing electricity systems and the
degree of surplus capacity. In the short term, blending of hydrogen with
natural gas (up to 20% by volume) and transporting it long distances
in existing gas grids could be an option. In the longer term, the construction
of pipelines for carrying pure hydrogen is possible, constructed
from special steels to avoid embrittlement. The rate-limiting factors for
deploying hydrogen are likely to be the capital and time involved in
building a new hydrogen infrastructure and any additional cost for storage
in order to accommodate variable RE sources. [8.2.3.2, 8.2.3.4]
In order to blend a RE gas into a gas grid, the gas source needs to be
located near to the existing system to avoid high costs of additional
pipeline construction. In the case of remote plant locations due to
resource availability, it may be better to use the gas onsite where feasible
to avoid the need for transmission and upgrading. [8.2.3.5]
8.5 Integration of renewable energy into
liquid fuels
Most of the projected demand for liquid biofuels is for transport purposes,
though industrial demand could emerge for bio-lubricants and
bio-chemicals such as methanol. In addition, large amounts of traditional
solid biomass could eventually be replaced by more convenient,
safer and healthier liquid fuels such as RE-derived dimethyl ether (DME)
or ethanol gels. [8.2.4]
Producing bioethanol and biodiesel fuels from various crops, usually
used for food, is well understood (Figure TS.8.5). The biofuels produced
can take advantage of existing infrastructure components already used
for petroleum-based fuels including storage, blending, distribution and
dispensing. However, sharing petroleum-product infrastructure (storage
tanks, pipelines, trucks) with ethanol or blends can lead to problems
from water absorption and equipment corrosion, so may require investment
in specialized pipeline materials or linings. Decentralized biomass
production, seasonality and remote agricultural locations away from
existing oil refi neries or fuel distribution centres, can impact the supply
chain logistics and storage of biofuels. Technologies continue to
evolve to produce biofuels from non-food feedstocks and biofuels that
are more compatible with existing petroleum fuels and infrastructure.
Quality control procedures need to be implemented to ensure that such
biofuels meet all applicable product specifi cations. [8.2.4.1, 8.2.4.3,
8.2.4.4]
The use of blended fuels produced by replacing a portion (typically 5
to 25% but can be up to 100% substitution) of gasoline with ethanol,
Preparation and
Conversion Process
into Liquid Fuel
(Industrial Phase)
Transportation of Raw
Material to Processing Plants
Storage of Raw Material
Terminals/ Distribution
Points
Transportation to Blending
Centres
Storage of Biofuels near the
Biorefineries or in Blending
Centres
Transportation to Terminals or
Distributing Centres
Final Consumption
Storage
Transportation of Biofuels to
Retailers and Final Consumers
Production of Biomass
(Agricultural Phase)
Figure TS.8.5 | The production, blending and distribution system for a range of liquid biofuels is similar regardless of the biomass feedstock. [Figure 8.11]
113
Summaries Technical Summary
equal, be more costly than in larger integrated networks because of the
restricted set of options, but in most instances, such as on islands or in
remote rural areas, there is no choice for the energy users. One implication
is that autonomous electricity system users and designers can face
diffi cult trade-offs between a desire for reliable and continuous supply
and minimizing overall supply costs. [8.2.5]
The integration of RE conversion technologies, balancing options and
end-use technologies in an autonomous energy system depend on the
site-specifi c availability of RE resources and the local energy demand.
These can vary with local climate and lifestyles. The balance between
cost and reliability is critical when designing and deploying autonomous
power systems, particularly for rural areas of developing economies
because the additional cost of providing continuous and reliable supply
may become higher for smaller autonomous systems. [8.2.5.2]
8.7 End-use sectors: Strategic elements for
transition pathways
RE technology developments have continued to evolve, resulting in
increased deployment in the transport, building, industry, and agriculture,
forestry and fi shery sectors. In order to achieve greater RE deployment in
all sectors, both technical and non-technical issues should be addressed.
Regional variations exist for each sector due to the current status of RE
uptake, the wide range of energy system types, the related infrastructure
currently in place, the different possible pathways to enhance increased
RE integration, the transition issues yet to be overcome, and the future
trends affected by variations in national and local ambitions and cultures.
[8.3, 8.3.1]
8.7.1 Transport
Recent trends and projections show strong growth in transport demand,
including the rapidly increasing number of vehicles worldwide. Meeting
this demand, whilst achieving a low-carbon, secure energy supply, will
require strong policy initiatives, rapid technological change, monetary
incentives and/or the willingness of customers to pay additional costs.
[8.3.1]
In 2008, the combustion of fossil fuels for transport consumed around
19% of global primary energy use, equivalent to 30% of total consumer
energy and producing around 22% of GHG emissions, plus a signifi cant
share of local air-polluting emissions. Light duty vehicles (LDVs) accounted
for over half of transport fuel consumption worldwide, with heavy duty
vehicles (HDVs) accounting for 24%, aviation 11%, shipping 10% and rail
3%. Demand for mobility is growing rapidly with the number of motorized
vehicles projected to triple by 2050 and with a similar growth in air
travel. Maintaining a secure supply of energy is therefore a serious concern
for the transport sector with about 94% of transport fuels presently
coming from oil products that, for most countries, are imported. [8.3.1]
or diesel with biodiesel, requires investment in infrastructure including
additional tanks and pumps at vehicle service stations. Although the
cost of biofuel delivery is a small fraction of the overall cost, the logistics
and capital requirements for widespread integration and expansion
could present major hurdles if not well planned. Since ethanol has only
around two-thirds the energy density (by volume) of gasoline, larger
storage systems, more rail cars or vessels, and larger capacity pipelines
are needed to store and transport the same amount of energy.
This increases the fuel storage and delivery costs. Although pipelines
would, in theory, be the most economical method of delivery, and pipeline
shipments of ethanol have been successfully achieved, a number of
technical and logistical challenges remain. Typically, current volumes of
ethanol produced in an agricultural region to meet local demand, or for
export, are usually too low to justify the related investment costs and
operational challenges of constructing a dedicated pipeline. [8.2.4.3]
8.6 Integration of renewable energy into
autonomous systems
Autonomous energy supply systems are typically small scale and are
often located in off-grid remote areas, on small islands, or in individual
buildings where the provision of commercial energy is not readily available
through grids and networks. Several types of autonomous systems
exist and can make use of either single energy carriers, for example,
electricity, heat, or liquid, gaseous or solid fuels, or a combination of
carriers. [8.2.5, 8.2.5.1]
In principle, RE integration issues for autonomous systems are similar
to centralized systems, for example, for supply/demand balancing of
electricity supply systems, selection of heating and cooling options, production
of RE gases and liquid biofuel production for local use. However,
unlike larger centralized supply systems, smaller autonomous systems
often have fewer RE supply options that are readily available at a local
scale. Additionally, some of the technical and institutional options for
managing integration within larger networks become more diffi cult or
even implausible for smaller autonomous systems, such as RE supply
forecasting, probabilistic unit commitment procedures, stringent fuel
quality standards, and the smoothing effects of geographical and technical
diversity. [8.2.1–8.2.5]
RE integration solutions typically become more restricted as supply
systems become smaller. Therefore greater reliance must be placed
on those solutions that are readily available. Focusing on variable RE
resources, because of restricted options for interconnection and operating
and planning procedures, autonomous systems will naturally have a
tendency to focus on energy storage options, various types of demand
response, and highly fl exible fossil fuel generation to help match supply
and demand. RE supply options that better match local load profi les,
or that are dispatchable, may be chosen over other lower-cost options
that do not have as strong a match with load patterns or are variable.
Managing RE integration within autonomous systems will, all else being
114
Technical Summary Summaries
There are a number of possible fuel/vehicle pathways from the conversion
of the primary energy source to an energy carrier (or fuel) through
to the end use, whether in advanced internal combustion engine vehicles
(ICEVs), electric battery vehicles (EVs), hybrid electric vehicles (HEVs),
plug-in hybrid electric vehicles (PHEVs) or hydrogen fuel cell vehicles
(HFCVs) (Figure TS.8.6). [8.3.1.2]
Improving the effi ciency of the transport sector, and decarbonizing
it, have been identifi ed as being critically important to achieving
long-term, deep reductions in global GHG emissions. The approaches
to reducing transport-related emissions include a reduction in travel
demand, increased vehicle effi ciency, shifting to more effi cient modes
of transport, and replacing petroleum-based fuels with alternative lowor
near-zero-carbon fuels (including biofuels, electricity or hydrogen
produced from low-carbon primary energy sources). Scenario studies
strongly suggest that a combination of technologies will be needed to
accomplish 50 to 80% reductions (compared to current rates) in GHG
emissions by 2050 whilst meeting the growing transport energy demand
(Figure TS.8.7). [8.3.1.1]
The current use of RE for transport is only a few percent of the total
energy demand, mainly through electric rail and the blending of liquid
biofuels with petroleum products. Millions of LDVs capable of running
on high-biofuel blends are already in the world fl eet and biofuel technology
is commercially mature, as is the use of compressed biomethane
in vehicles suitable for running on compressed natural gas. [8.2.3]
However, making a transition to new fuels and engine types is a
complex process involving technology development, cost, infrastructure,
consumer acceptance, and environmental and resource impacts.
Transition issues vary for biofuels, hydrogen, and electric vehicles (Table
TS.8.2) with no one option seen to be a clear ‘winner’ and all needing
several decades to be deployed at a large scale. Biofuels are well
proven, contributing around 2% of road transport fuels in 2008, but
there are issues of sustainability. [2.5] Many hydrogen fuel cell vehicles
have been demonstrated, but these are unlikely to be commercialized
until at least 2015 to 2020 due to the barriers of fuel cell durability, cost,
onboard hydrogen storage issues and hydrogen infrastructure availability.
For EVs and PHEVs, the cost and relatively short life of present
Liquid Fuel
Gaseous Fuel
Electricity
ICEV HEV Plug-in HEV Battery EV Fuel Cell EV
Fuel Processor
Gasoline
Diesel
Oil Unconv. Oil Nat. Gas Coal Biomass
Solar,
Hydropower,
Wind, Ocean,
Geothermal
Nuclear
Renewable
Fossil
Nuclear
Primary
Energy Source
Energy
Carrier
Vehicle
SYNTHETIC LIQUIDS
Methanol, DME, F-T, CH4, Ethanol
H2 Electricity
Figure TS.8.6 | A range of possible light duty vehicle fuel pathways, from primary energy sources (top), through energy carriers, to end-use vehicle drive train options (bottom) (with
RE resources highlighted in green). [Figure 8.13]
Notes: F-T= Fischer-Tropsch process; DME = dimethyl ether; ICE = internal combustion engine; HEV = hybrid electric vehicle; EV = electric vehicle; ‘unconventional oil’ refers to oil
sands, oil shale and other heavy crudes.
I
115
Summaries Technical Summary
battery technologies, the limited vehicle range between recharging, and
the time for recharging, can be barriers to consumer acceptance. EV
and PHEV designs are undergoing rapid development, spurred by recent
policy initiatives worldwide, and several companies have announced
plans to commercialize them. One strategy could be to introduce PHEVs
initially while developing and scaling up battery technologies. For hydrogen
and electric vehicles, it may take several decades to implement a
practical transport system by developing the necessary infrastructure at
the large scale.
An advantage of biofuels is their relative compatibility with the existing
liquid fuel infrastructure. They can be blended with petroleum products
and most ICE vehicles can be run on blends, some even on up to
100% biofuel. They are similar to gasoline or diesel in terms of vehicle
performance14 and refuelling times, though some have limits on the
concentrations that can be blended and they typically cannot be easily
distributed using existing fuel pipelines without modifi cations. The sustainability
of the available biomass resource is a serious issue for some
biofuels. [2.5, 8.2.4, 8.3.1.2]
14 Performance in this instance excludes energy content. The energy content of biofuels
is generally lower than their equivalent petroleum product.
Hydrogen has the potential to tap vast new energy resources to provide
transport with zero or near-zero emissions. The technology for hydrogen
from biomass gasifi cation is being developed, and could become
competitive beyond 2025. Hydrogen derived from RE sources by electrolysis
has cost barriers rather than issues of technical feasibility or
resource availability. Initially RE and other low-carbon technologies will
likely be used to generate electricity, a development that could help
enable near-zero-carbon hydrogen to be co-produced with electricity or
heat in future energy complexes. Hydrogen is not yet widely distributed
compared to electricity, natural gas, gasoline, diesel or biofuels but could
be preferred in the future for large HDVs that have a long range and need
relatively fast refuelling times. Bringing hydrogen to large numbers of
vehicles would require building a new refuelling infrastructure that could
take several decades to construct. The fi rst steps to provide hydrogen to
test fl eets and demonstrate refuelling technologies in mini-networks have
begun in several countries. [2.6.3.2, 8.3.1, 8.3.1.2]
For RE electricity to supply high numbers of EVs and PHEVs in future markets,
several innovations must occur such as development of batteries and
low-cost electricity supply available for recharging when the EVs need it.
If using night-time, off-peak recharging, new capacity is less likely to be
needed and in some locations there may be a good temporal match with
Well-to--Wheels GHG Emissions per km Normalized
Fuel/Vehicle Pathway
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Wang et al. 2006
Brinkman et al. 2005
Kromer and Heywood 2007
Bandivadekar et al. 2008
CONCAWE 2007
NRC 2008, 2010 for 2030
Rousseau and Sharer 2004
IEA 2009c
Gasoline ICEV
Gasoline HEV
Diesel ICEV
Diesel HEV
CNG -ICEV
Biomethane - ICEV
Ethanol (Corn) - ICEV
Ethanol (Cellulose) - ICEV
Ethanol (Cellulose) - HEV
F-T (Wood) - Diesel
PHEV-10 (Gasoline, US Grid)
PHEV-40 (Gasoline, US Grid)
PHEV-40 (Ethanol (Cellulose), Low-C Grid)
EV - Current US Grid
EV - Future Zero-C Grid
GH2 (Onsite SMR) HFCV
GH2 (Biomass) HFCV
GH2 (Coal CCS) HFCV
GH2 (Wind) HFCV
Figure TS.8.7 | Well-to-wheels (WTW) GHG emission reductions per kilometre travelled, with ranges shown taken from selected studies of alternative light duty fuel/vehicle pathways,
normalized to the GHG emissions of a gasoline, internal combustion engine, light-duty vehicle. [Figure 8.17]
Notes: To allow for easier comparison among studies, WTW GHG emissions per km were normalized to emissions from a gasoline ICEV (such that ‘Gasoline ICEV’ = 1) taken from
each study and ranging from 170 to 394 g CO2/km. For all hydrogen pathways, hydrogen is stored onboard the vehicle as a compressed gas (GH2). CNG = compressed natural gas;
SMR = steam methane reformer.
• • ♦
ii. ■ • 4 $
,__ • x
• • - • +• - - e
Xx • 9
x I
116
Technical Summary Summaries
Table TS.8.2 | Transition issues for the use of biofuels, hydrogen and electricity as transport fuels for light duty vehicles. [Summarized from 8.3.1]
Technology Status Biofuels Hydrogen Electricity
Existing and potential primary
resources
Sugar, starch, oil crops; cellulosic crops; forest,
agricultural and solid wastes; algae and other
biological oils.
Fossil fuels; nuclear; all RE. Potential RE
resource base is large but ineffi ciencies and
costs of converting to H2 can be an issue.
Fossil fuels, nuclear, all RE. Potential RE resource
base is large.
Fuel production
First generation: ethanol from sugar and
starch crops, biomethane, biodiesel. Advanced
second-generation biofuels, e.g., from cellulosic
biomass, bio-wastes, bio-oils, and algae
after at least 2015.
Fossil H2 commercial for large-scale
industrial applications, but not competitive
as transport fuel. Renewable H2 generally
more costly.
Commercial power readily available. RE electricity
can be more costly, but preferred for transport
due to low GHG emissions on a lifecycle basis.
Vehicles
Millions of fl exi-fuel vehicles exist that use
high shares of ethanol. Conventional ICEVs
limited to low concentration blends of ethanol
(<25%). Some commercial agricultural tractors
and machinery can run on 100% biodiesel.
Demonstration HFCVs. Commercial HFCVs
not until 2015 to 2020.
Demonstration PHEVs, Commercial PHEVs not
until 2012 to 2015. Limited current use of EVs.
Commercial EVs not until 2015 to 2020.
Costs1 compared with gasoline
ICE vehicles
Incremental vehicle price compared to
future gasoline ICEV (USD2005)
Similar price.
HFCV experience (by 2035) price increment
>USD 5,300
Experience (by 2035) price increment: PHEVs
>USD 5,900; EVs >USD 14,000
Fuel cost (USD2005/km)
Fuel cost per km varies with biofuel type
and level of agricultural subsidy. Biofuel can
compete if price per unit of energy equates to
gasoline/diesel price per unit of energy. Ethanol
in Brazil competes without subsidies.
Target fuel cost at USD 3 to 4/kg for mature
H2 infrastructure—may prove optimistic.
When used in HFCVs, competes with gasoline
in HCEVs at USD 0.40 to 0.53/l. Assumes
HFCV has twice fuel economy of gasoline
ICEV. RE-derived H2 around 1.5 to 3 times
more expensive than other from sources.
Electricity cost per km, when the power is
purchased at USD 0.10 to 0.30/kWh, competes
with gasoline when purchased at USD 0.3 to 0.9/l
(assuming the EV has fuel economy 3 times that
of the gasoline ICEV).
Compatibility with existing
infrastructure
Partly compatible with existing petroleum
distribution system. Separate distribution
and storage infrastructure may be needed for
ethanol.
New H2 infrastructure needed, as well as
renewable H2 production sources. Infrastructure
deployment must be coordinated with
vehicle market growth.
Widespread electric infrastructure in place. Need
to add in-home and public recharger costs, RE
generation sources, and upgrading of transmission
and distribution (especially for fast chargers).
Consumer acceptance
Depends upon comparative fuel costs. Alcohol
vehicles can have shorter range than gasoline.
Potential cost impact on food crops. Land use
and water issues can be factors.
Depends upon comparative vehicle and
fuel costs. Public perception of safety. Poor
public refuelling station availability in early
markets.
High initial vehicle cost. High electricity cost of
charging on-peak. Limited range unless PHEV.
Modest to long recharging time, but home
recharging possible. Signifi cantly degraded
performance in extreme cold winters or hot summers.
Poor public refuelling station availability in
early markets
GHG emissions
Depends on feedstock, pathway and land use
issue2. Low for fuels from biomass residues
including sugarcane. Near-term can be high
for corn ethanol. Advanced second-generation
biofuels likely to be lower.
Depends on H2 production mix. Compared
to future hybrid gasoline ICEVs, WTW GHG
emissions for HFCVs using H2 from natural
gas can be slightly more or less depending
on assumptions. WTW GHG emissions can
approach zero for RE or nuclear pathways.
Depends on grid mix. Using coal-dominated grid
mix, EVs and PHEVs have WTW GHG emissions
similar or higher than gasoline HEV. With larger
fraction of RE and low-carbon electricity, WTW
emissions are lower.
Petroleum consumption Low for blends Very low Very low
Environmental and sustainability
issues
Air pollution
Similar to gasoline. Additional issues for
ethanol due to permeation of volatile organic
compounds through fuel tank seals. Aldehyde
emissions.
Zero emission vehicle Zero emission vehicle.
Water use
More than gasoline depending on feedstock
and crop irrigation needs.
Potentially low but depends on pathway as
electrolysis and steam reformation depend
on water.
Potentially very low but depends on pathway
used for power generation.
Land use
Might compete with food and fi bre production
on cropland.
Depends on pathway. Depends on pathway.
Materials use
Platinum in fuel cells. Neodymium and
other rare earths in electric motors. Material
recycling.
Lithium in batteries. Neodymium and other rare
earths in electric motors. Material recycling.
Notes: 1. Costs quoted do not always include payback of incremental fi rst vehicle costs. 2. Indirect land use-related GHG emissions linked to biofuels is not included.
117
Summaries Technical Summary
wind or hydropower resources. Grid fl exibility and/or energy storage may
also be needed to balance vehicle recharging electricity demand with RE
source availability. [8.2.1]
Other than LDVs, it is possible to introduce RE options and lower GHG
emissions in the other transport sectors: HDVs, aviation, maritime and
rail. The use of biofuels is key for increasing the share of RE in these subsectors
but current designs of ICEs would probably need to be modifi ed
to operate on high-biofuel blends (above 80%). Aviation has perhaps less
potential for fuel switching than the other sub-sectors due to safety needs
and to minimize fuel weight and volume. However, various airlines and
aircraft manufacturers have fl own demonstration test fl ights using various
biofuel blends, but signifi cantly more processing is needed than for
road fuels to ensure that stringent aviation fuel specifi cations are met,
particularly at cold temperatures. For rail transport, as around 90% of the
industry is powered by diesel fuel, greater electrifi cation and the increased
use of biodiesel are the two primary options for introducing RE. [8.3.1.5]
Given all these uncertainties and cost reduction challenges, it is important
to maintain a portfolio approach over a long time line that includes
behavioural changes (for example to reduce annual vehicle kilometres
travelled or kilometres fl own), more energy effi cient vehicles, and a variety
of low-carbon fuels. [8.3.1.5]
8.7.2 Buildings and households
The building sector provides shelter and a variety of energy services to
support the livelihoods and well-being of people living in both developed
and developing countries. In 2008, it accounted for approximately 120 EJ
(about 37%) of total global fi nal energy use (including between 30 and
45 EJ of primary energy from traditional biomass used for cooking and
heating). The high share of total building energy demand for heating
and cooling is usually met by fossil fuels (oil burners, gas heaters) and
electricity (fans and air-conditioners). In many regions, these can be
replaced economically by district heating and cooling (DHC) schemes
or by the direct use of RE systems in buildings, such as modern biomass
pellets and enclosed stoves, heat pumps (including ground source), solar
thermal water and space heating, and solar sorption cooling systems.
[2.2, 8.2.2, 8.3.2]
RE electricity generation technologies integrated into buildings (such as
solar PV panels) provide the potential for buildings to become energy
suppliers rather than energy consumers. Integration of RE into existing
urban environments, combined with energy effi cient appliances and
‘green building’ designs, are key to further deployment. For both household
and commercial building sub-sectors, energy vectors and energy
service delivery systems vary depending on the local characteristics and
RE resources of a region, its wealth, and the average age of the current
buildings and infrastructure impacting stock turnover. [8.3.2]
The features and conditions of energy demands in an existing or new
building, and the prospects for RE integration, differ with location and
between one building design and another. In both urban and rural
settlements in developed countries, most buildings are connected to
electricity, water and sewage distribution schemes. With a low building
stock turnover rate of only around 1% per year in developed countries,
future retrofi tting of existing buildings will need to play a signifi cant
role in RE integration as well as energy effi ciency improvements.
Examples include installation of solar water heaters and ground source
heat pumps and development or extensions of DHC systems that, being
fl exible on sources of heat or cold, allow for a transition to a greater
share of RE over time. These can involve relatively high up-front investment
costs and long payback periods, but these can possibly be offset
by amended planning consents and regulations so they become more
enabling, improved energy effi cient designs, and the provision of economic
incentives and fi nancial arrangements. [8.2.2, 8.3.2.1]
Grid electricity supply is available in most urban areas of developing
countries, although often the supply system has limited capacity and
is unreliable. Increased integration of RE technologies using local RE
resources could help ensure a secure energy supply and also improve
energy access. In urban and rural settlements in developing countries,
energy consumption patterns often include the unsustainable use of
biomass and charcoal. The challenge is to reverse the increasing traditional
biomass consumption patterns by providing improved access
to modern energy carriers and services and increasing the share of RE
through integration measures. The distributed nature of solar and other
RE resources is benefi cial for their integration into new and existing
buildings however modest they might be, including dwellings in rural
areas not connected to energy supply grids. [8.2.2.2, 8.2.5]
8.7.3 Industry
Manufacturing industries account for about 30% of global fi nal energy
use, although the share differs markedly between countries. The sector
is highly diverse, but around 85% of industrial energy use is by the more
energy-intensive ‘heavy’ industries including iron and steel, non-ferrous
metals, chemicals and fertilizers, petroleum refi ning, mineral mining,
and pulp and paper. [8.3.3.1]
There are no severe technical limits to increasing the direct and indirect
use of RE in industry in the future. However, integration in the short
term may be limited by factors such as land and space constraints or
demands for high reliability and continuous operation. In addition to
the integration of higher shares of RE, key measures to reduce industrial
energy demands and/or GHG emissions include energy effi ciency,
recycling of materials, CCS for CO2-emitting industries such as cement
manufacturing, and the substitution of fossil fuel feedstocks. In addition,
industry can provide demand-response facilities that are likely to
118
Technical Summary Summaries
Figure TS.8.8 | Industrial heat demands for various temperature quality ranges by the
heavy industrial and light manufacturing sub-sectors, based on an assessment within 32
European countries. [Figure 8.23]
0 500 1,000 1,500 2,000 2,500
[PJ]
High, Over 400°C
Medium, 100-400°C
Low, Below 100°C
Basic Metals
Chemical
Non-Metallic Minerals
Transport Equipment
Machinery
Mining and Quarrying
Food and Tobacco
Pulp & Paper
Others
achieve greater prominence in future electricity systems that have a
higher penetration of variable RE sources. [8.3.3.1]
The main opportunities for RE integration in industry include:
• Direct use of biomass-derived fuels and process residues for onsite
production, and use of biofuels, heat and CHP; [2.4.3]
• Indirect use through increased use of RE-based electricity, including
electro-thermal processes; [8.3.3]
• Indirect use through other purchased RE-based energy carriers
including heat, liquid fuels, biogas, and, possibly to a greater
degree in the future, hydrogen; [8.2.2–8.2.4]
• Direct use of solar thermal energy for process heat and steam
demands although few examples exist to date; [3.3.2] and
• Direct use of geothermal resources for process heat and steam
demands. [4.3.5]
Industry is not only a potential user of RE but also a potential supplier
of bioenergy as a co-product. The current direct use of RE in industry
is dominated by biomass produced in the pulp and paper, sugar and
ethanol industries as process by-products and used for cogenerated
heat and electricity, mainly onsite for the process but also sold offsite.
Biomass is also an important fuel for many small and medium
enterprises such as brick making, notably as charcoal in developing
countries. [8.3.3.1]
Possible pathways for increased use of RE in energy-intensive industries
vary between the different industrial sub-sectors. Biomass, for
example, is technically able to replace fossil fuels in boilers, kilns and
furnaces or to replace petrochemicals with bio-based chemicals and
materials. However, due to the scale of many industrial operations,
access to suffi cient volumes of local biomass may be a constraint. Use
of solar technologies can be constrained in some locations with low
annual sunshine hours. The direct supply of hydropower to aluminium
smelters is not unusual but, for many energy-intensive processes, the
main option is indirect integration of RE through switching to RE electricity
from the grid, or, in the future, to hydrogen. The broad range of
options for producing low-carbon electricity, and its versatility of use,
implies that electro-thermal processes could become more important
in the future for replacing fossil fuels in a range of industrial processes.
[8.3.3.2]
Less energy-intensive ‘light’ industries, including food processing, textiles,
light manufacturing of appliances and electronics, automotive
assembly plants, and saw-milling, although numerous, account for a
smaller share of total energy use than do the heavy industries. Much
of the energy demand by these ‘light’ industries refl ects the energy use
in commercial buildings for lighting, space heating, cooling, ventilation
and offi ce equipment. In general, light industries are more fl exible and
offer more readily accessible opportunities for the integration of RE
than do energy-intensive industries. [8.3.3.3]
RE integration for process heat is practical at temperatures below around
400°C using the combustion of biomass (including charcoal) as well as
solar thermal or direct geothermal energy. To meet process heat demand
above 400°C, RE resources, with the exception of high-temperature solar,
are less suitable (Figure TS.8.8). [8.3.3.3]
The potentials and costs for increasing the use of RE in industry are
poorly understood due to the complexity and diversity of industry and
the various geographical and local climatic conditions. Near-term opportunities
for achieving higher RE shares could result from the increased
utilization of process residues, CHP in biomass-based industries, and
substitution of fossil fuels used for heating. Solar thermal technologies
are promising with further development of collectors, thermal storage,
back-up systems, process adaptation and integration under evaluation.
RE integration using electricity generated from RE sources for electrotechnologies
may have the largest impact both in the near and long
term. [8.3.3.2, 8.3.3.3]
Use of RE in industry has had diffi culty in competing in the past in many
regions due to relatively low fossil fuel prices together with low, or
■
■
■
119
Summaries Technical Summary
non-existent, energy and carbon taxes. RE support policies in different
countries tend to focus more on the transport and building sectors than
on industry and consequently the potential for RE integration is relatively
uncertain. Where support policies have been applied, successful RE
deployment has resulted. [8.3.3.3]
8.7.4 Agriculture, forestry and fi shing
Agriculture is a relatively low energy-consuming sector, utilizing only
around 3% of total global consumer energy. The sector includes large
corporate-owned farms and forests as well as subsistence farmers and
fi sher-folk in developing countries. The relatively high indirect energy
use for the manufacture of fertilizers and machinery is included in the
industry sector. Pumping water for irrigation usually accounts for the
highest on-farm energy demand, along with diesel use for machinery
and electricity for milking, refrigeration and fi xed equipment. [8.3.4.1]
In many regions, land under cultivation could simultaneously be used
for RE production. Multi-use of land for agriculture and energy purposes
is becoming common, such as wind turbines constructed on
grazing land; biogas plants used for treating animal manure with the
nutrients recycled to the land; waterways used for small- and microhydropower
systems; crop residues collected and combusted for heat
and power; and energy crops grown and managed specifi cally to provide
a biomass feedstock for liquid biofuels, heat and power generation
(with co-products possibly used for feed and fi bre). [2.6, 8.3.4.2, 8.3.4.3]
Since RE resources including wind, solar, crop residues and animal
wastes are often abundant in rural areas, their capture and integration
can enable the landowner or farm manager to utilize them locally for
the farming operations. They can also earn additional revenue when
energy carriers such as RE electricity or biogas are exported off the
farm. [8.3.4]
Despite barriers to greater RE technology deployment including high
capital costs, lack of available fi nancing and remoteness from energy
demand, it is likely that RE will be used to a greater degree by the
global agricultural sector in the future to meet energy demands for primary
production and post-harvest operations at both large and small
scales. [8.3.4.1–8.3.4.2]
Integration strategies that could increase the deployment of RE in
the primary sector will partly depend upon the local and regional RE
resources, on-farm energy demand patterns, project fi nancing opportunities
and existing energy markets. [8.3.4.3]
9. Renewable Energy in the Context
of Sustainable Development
9.1 Introduction
Sustainable development (SD) addresses concerns about relationships
between human society and nature. Traditionally, SD has been framed
in the three-pillar model—Economy, Ecology, and Society—allowing a
schematic categorization of development goals, with the three pillars
being interdependent and mutually reinforcing. Within another conceptual
framework, SD can be oriented along a continuum between the
two paradigms of weak sustainability and strong sustainability. The two
paradigms differ in assumptions about the substitutability of natural
and human-made capital. RE can contribute to the development goals
of the three-pillar model and can be assessed in terms of both weak and
strong SD, since RE utilization is defi ned as sustaining natural capital
as long as the resource use does not reduce the potential for future
harvest. [9.1]
9.2 Interactions between sustainable
development and renewable energy
The relationship between RE and SD can be viewed as a hierarchy of goals
and constraints that involve both global and regional or local considerations.
Though the exact contribution of RE to SD has to be evaluated
in a country-specifi c context, RE offers the opportunity to contribute to
a number of important SD goals: (1) social and economic development;
(2) energy access; (3) energy security; and (4) climate change mitigation
and the reduction of environmental and health impacts. The mitigation
of dangerous anthropogenic climate change is seen as one strong driving
force behind the increased use of RE worldwide. [9.2, 9.2.1]
These goals can be linked to both the three-pillar model and the weak
and strong SD paradigms. SD concepts provide useful frameworks for
policymakers to assess the contribution of RE to SD and to formulate
appropriate economic, social and environmental measures. [9.2.1]
The use of indicators can assist countries in monitoring progress made
in energy subsystems consistent with sustainability principles, although
there are many different ways to classify indicators of SD. The assessments
carried out for the report and Chapter 9 are based on different
methodological tools, including bottom-up indicators derived from
attributional lifecycle assessments (LCA) or energy statistics, dynamic
integrated modelling approaches, and qualitative analyses. [9.2.2]
120
Technical Summary Summaries
Conventional economic growth metrics (GDP) as well as the conceptually
broader Human Development Index (HDI) are analyzed to evaluate
the contribution of RE to social and economic development. Potential
employment opportunities, which serve as a motivation for some countries
to support RE deployment, as well as critical fi nancing questions for
developing countries are also addressed. [9.2.2]
Access to modern energy services, whether from renewable or nonrenewable
sources, is closely correlated with measures of development,
particularly for those countries at earlier development stages. Providing
access to modern energy for the poorest members of society is crucial
for the achievement of any single of the eight Millennium Development
Goals. Concrete indicators used include per capita fi nal energy consumption
related to income, as well as breakdowns of electricity access
(divided into rural and urban areas), and numbers for those parts of the
population using coal or traditional biomass for cooking. [9.2.2]
Despite the lack of a commonly accepted defi nition, the term ‘energy
security’ can best be understood as robustness against (sudden) disruptions
of energy supply. Two broad themes can be identifi ed that are
relevant to energy security, whether for current systems or for the planning
of future RE systems: availability and distribution of resources; and
variability and reliability of energy supply. The indicators used to provide
information about the energy security criterion of SD are the magnitude
of reserves, the reserves-to-production ratio, the share of imports in
total primary energy consumption, the share of energy imports in total
imports, as well as the share of variable and unpredictable RE sources.
[9.2.2]
To evaluate the overall burden from the energy system on the environment,
and to identify potential trade-offs, a range of impacts and
categories have to be taken into account. These include mass emissions
to air (in particular GHGs) and water, and usage of water, energy and
land per unit of energy generated and these must be evaluated across
technologies. While recognizing that LCAs do not give the only possible
answer as to the sustainability of a given technology, they are a particularly
useful methodology for determining total system impacts of
a given technology, which can serve as a basis for comparison. [9.2.2]
Scenario analyses provide insights into what extent integrated models
take account of the four SD goals in different RE deployment pathways.
Pathways are primarily understood as scenario results that attempt to
address the complex interrelations among the different energy technologies
at a global scale. Therefore, Chapter 9 mainly refers to global
scenarios derived from integrated models that are also at the core of the
analysis in Chapter 10. [9.2.2]
9.3 Social, environmental and economic
impacts: Global and regional assessment
Countries at different levels of development have different incentives to
advance RE. For developing countries, the most likely reasons to adopt
RE technologies are providing access to energy, creating employment
opportunities in the formal (i.e., legally regulated and taxable) economy,
and reducing the costs of energy imports (or, in the case of fossil energy
exporters, prolonging the lifetime of their natural resource base). For
industrialized countries, the primary reasons to encourage RE include
reducing carbon emissions to mitigate climate change, enhancing energy
security, and actively promoting structural change in the economy, such
that job losses in declining manufacturing sectors are softened by new
employment opportunities related to RE. [9.3]
9.3.1 Social and economic development
Globally, per capita incomes are positively correlated with per capita
energy use and economic growth can be identifi ed as the most relevant
factor behind increasing energy consumption in the last decades.
However, there is no agreement on the direction of the causal relationship
between energy use and increased macroeconomic output. [9.3.1.1]
As economic activity expands and diversifi es, demands for more sophisticated
and fl exible energy sources arise: from a sectoral perspective,
countries at an early stage of development consume the largest part
of total primary energy in the residential (and to a lesser extent agricultural)
sector; in emerging economies the manufacturing sector
dominates, while in fully industrialized countries services and transport
account for steadily increasing shares (see Figure TS.9.1). [9.3.1.1]
Despite the close correlation between GDP and energy use, a wide variety
of energy use patterns across countries prevails: some have achieved
high levels of per capita incomes with relatively low energy consumption.
Others remain rather poor despite elevated levels of energy use, in
particular countries abundantly endowed with fossil fuel resources, in
which energy is often heavily subsidized. One hypothesis suggests that
economic growth can largely be decoupled from energy use by steady
declines in energy intensity. Further, it is often asserted that developing
economies and economies in transition can ‘leapfrog’, that is, limit their
energy use by adopting modern, highly effi cient energy technologies.
[9.3.1.1, Box 9.5]
Access to clean and reliable energy constitutes an important prerequisite
for fundamental determinants of human development, such as health,
education, gender equality and environmental safety. Using the HDI as
a proxy indicator of development, countries that have achieved high HDI
levels in general consume relatively large amounts of energy per capita
and no country has achieved a high or even a medium HDI without
signifi cant access to non-traditional energy supplies. A certain minimum
amount of energy is required to guarantee an acceptable standard of
living (e.g., 42 GJ per capita), after which raising energy consumption
yields only marginal improvements in the quality of life. [9.3.1.2]
Estimates of current net employment effects of RE differ due to disagreements
regarding the use of the appropriate methodology. Still,
there seems to be agreement about the positive long-term effects of RE
121
Summaries Technical Summary
as an important contribution to job creation, which has been stressed in
many national green-growth strategies. [9.3.1.3]
In general, the purely economic costs of RE exceed those of fossil fuelbased
energy production in most instances. Especially for developing
countries, the associated costs are a major factor determining the desirability
of RE to meet increasing energy demand, and concerns have
been voiced that increased energy prices might endanger industrializing
countries’ development prospects. Overall, cost considerations cannot be
discussed independently of the burden-sharing regime adopted, that is,
without specifying who assumes the costs for the benefi ts brought about
from reduced GHG emissions, which can be characterized as a global public
good. [9.3.1.4]
9.3.2 Energy access
Signifi cant parts of the global population today have no or limited access
to modern and clean energy services. From a sustainable development
perspective, sustainable energy expansion needs to increase the availability
of energy services to groups that currently have no or limited
access to them: the poor (measured by wealth, income or more integrative
indicators), those in rural areas and those without connections to
the grid. [9.3.2]
Acknowledging the existing constraints regarding data availability and
quality, 2009 estimates of the number of people without access to electricity
are around 1.4 billion. The number of people relying on traditional
biomass for cooking is around 2.7 billion, which causes signifi cant health
problems (notably indoor air pollution) and other social burdens (e.g.,
time spent gathering fuel) in the developing world. Given the strong correlation
between household income and use of low quality fuels (Figure
TS.9.2), a major challenge is to reverse the pattern of ineffi cient biomass
consumption by changing the present, often unsustainable, use to more
sustainable and effi cient alternatives. [9.3.2]
By defi ning energy access as ‘access to clean, reliable and affordable energy
services for cooking and heating, lighting, communications and productive
uses’, the incremental process of climbing the steps of the energy ladder
is illustrated; even basic levels of access to modern energy services can
provide substantial benefi ts to a community or household. [9.3.2]
In developing countries, decentralized grids based on RE have expanded
and improved energy access; they are generally more competitive in rural
areas with signifi cant distances to the national grid and the low levels of
rural electrifi cation offer signifi cant opportunities for RE-based mini-grid
systems. In addition, non-electrical RE technologies offer opportunities
for direct modernization of energy services, for example, using solar
energy for water heating and crop drying, biofuels for transportation,
biogas and modern biomass for heating, cooling, cooking and lighting,
and wind for water pumping. While the specifi c role of RE in providing
energy access in a more sustainable manner than other energy sources
is not well understood, some of these technologies allow local communities
to widen their energy choices; they stimulate economies, provide
incentives for local entrepreneurial efforts and meet basic needs and services
related to lighting and cooking, thus providing ancillary health and
education benefi ts. [9.3.2]
0 10 20 30 40 50 60 70
[EJ]
80
Other
Transport
Services
Households
Manufacturing
OECD Europe 1990
2005
OECD Pacific 1990
2005
US & Canada 1990
2005
Mexico 1990
2005
China 1990
2005
India 1990
2005
Brazil 1990
2005
South Africa 1990
2005
Russia 1990
2005
RoW 1990
2005
Figure TS.9.1 | Energy use (EJ) by economic sector. Note that the underlying data are
calculated using the IEA physical content method, not the direct equivalent method.1
Notes: RoW = Rest of World. [Figure 9. 2] 1. Historical energy data have only been available
for energy use by economic sector. For a conversion of the data using the direct
equivalent method, the different energy carriers used by each economic sector would
need to be known.
■
■
■
■
■
I I
122
Technical Summary Summaries
9.3.3 Energy security
The use of RE permits substitution away from increasingly scarce fossil
fuel supplies; current estimates of the ratio of proven reserves to
current production show that globally oil and natural gas would be
exhausted in about four and six decades, respectively. [9.3.3.1]
As many renewable sources are localized and not internationally tradable,
increasing their share in a country’s energy portfolio diminishes
the dependence on imports of fossil fuels, whose spatial distribution
of reserves, production and exports is very uneven and highly concentrated
in a few regions (Figure TS.9.3). As long as RE markets are
not characterized by such geographically concentrated supply, this
helps to diversify the portfolio of energy sources and to reduce the
economy’s vulnerability to price volatility. For oil-importing developing
countries, increased uptake of RE technologies could be an avenue to
redirect foreign exchange fl ows away from energy imports towards
imports of goods that cannot be produced locally, such as high-tech
capital goods. For example, Kenya and Senegal spend more than half
of their export earnings for importing energy, while India spends over
45%. [9.3.3.1]
However, import dependencies can also occur in relation to the technologies
needed for implementation of RE, with the secure access to
required scarce inorganic mineral raw materials at reasonable prices
constituting an upcoming challenge for all industries. [9.3.3.1]
The variable output profi les of some RE technologies often necessitate
technical and institutional measures appropriate to local conditions to
assure a constant and reliable energy supply. Reliable energy access
is a particular challenge in developing countries and indicators for the
reliability of infrastructure services show that in sub-Saharan Africa,
almost 50% of fi rms maintain their own generation equipment. Many
developing countries therefore specifi cally link energy access and security
issues by broadening the defi nition of energy security to include
stability and reliability of local supply. [9.3.3.2]
9.3.4 Climate change mitigation and reduction of
environmental and health impacts
Sustainable development must ensure environmental quality and
prevent undue environmental harm. No large-scale technology deployment
comes without environmental trade-offs and a large body of
literature is available that assesses various environmental impacts of
the broad range of energy technologies (RE, fossil and nuclear) from a
bottom-up perspective. [9.3.4]
Impacts on the climate through GHG emissions are generally well covered,
and LCAs [Box 9.2] facilitate a quantitative comparison of ‘cradle
to grave’ emissions across technologies. While a signifi cant number of
studies report on air pollutant emissions and operational water use, evidence
is scarce for lifecycle emissions to water, land use, and health
impacts other than those linked to air pollution. The assessment concentrates
on those sectors which are best covered by the literature, such
as electricity generation and transport fuels for GHG emissions. Heating
and household energy are discussed only briefl y, in particular with
regards to air pollution and health. Impacts on biodiversity and ecosystems
are mostly site-specifi c, diffi cult to quantify and are presented in a
more qualitative manner. To account for burdens associated with accidents
as opposed to normal operation, an overview of risks associated
with energy technologies is provided. [9.3.4]
LCAs for electricity generation indicate that GHG emissions from RE
technologies are, in general, considerably lower than those associated
with fossil fuel options, and in a range of conditions, less than fossil
fuels employing CCS. The maximum estimate for CSP, geothermal, hydropower,
ocean and wind energy is less than or equal to 100 g CO2eq/kWh,
and median values for all RE range from 4 to 46 g CO2eq/kWh. The upper
quartile of the distribution of estimates for PV and biopower extend two
to three times above the maximum for other RE technologies. However,
GHG balances of bioenergy production have more uncertainties: excluding
LUC, biopower could reduce GHG emissions compared to fossil
fuelled systems and can lead to avoided GHG emissions from residues
and wastes in landfi ll disposals and co-products; the combination of
Figure TS.9.2 | The relationship between per capita fi nal energy consumption and
income in developing countries. Data refer to the most recent year available during the
period 2000 to 2008. [Figure 9.5]
Note: LPG = liquid petroleum gas.
>75 40 - 75 5 - 40 <5
0
[GJ]
10
20
30
40
50
Other Petroleum Products
LPG & Kerosene
Coal
Gas
Electricity
Traditional Biomass
Share of Population with an Income of less than USD 2 per Day [%]
■■ ■■ ■■
123
Summaries Technical Summary
Coal
Oil
Gas
-300
-250
-200
-150
-100
-50
0
50
100
Africa Asia Pacific EU-27 FSU Latin America Middle East North America
Share of Imports in Consumption [%], 2008
-0.6
1.5
Figure TS.9.3 | Energy imports as the share of total primary energy consumption (%) for coal (hard coal and lignite), crude oil and natural gas for selected world regions in 2008.
Negative values denote net exporters of energy carriers. [Figure 9.6]
bioenergy with CCS may provide for further reductions (Figure TS.9.4).
[9.3.4.1]
Accounting for differences in the quality of power produced, potential
impacts to grid operation related to the addition of variable generation
sources, and for direct or indirect LUC could reduce the GHG emissions
benefi t from switching to renewable electricity generation, but is not
likely to negate the benefi t. [9.3.4.1]
Measures such as the energy payback time, describing the energetic
effi ciency of technologies or fuels, have been declining rapidly for some
RE technologies over recent years (e.g., wind and PV) due to technological
advances and economies of scale. Fossil and nuclear power
technologies are characterized by the continuous energy requirements
for fuel extraction and processing, which might become increasingly
important as qualities of conventional fuel supply decline and shares of
unconventional fuels rise. [9.3.4.1]
For the assessment of GHG emissions from transportation fuels, selected
petroleum fuels, fi rst-generation biofuels (i.e., sugar- and starch-based
ethanol, oilseed-based biodiesel and renewable diesel), and selected
next-generation biofuels derived from lignocellulosic biomass (i.e.,
ethanol and Fischer-Tropsch diesel) are compared on a well-to-wheel
basis. In this comparison, GHG emissions from LUC (direct and indirect)
and other indirect effects (e.g., petroleum consumption rebound)
have been excluded, but are separately considered below. Substituting
biofuels for petroleum-based fuels has the potential to reduce lifecycle
GHG emissions directly associated with the fuel supply chain. While
fi rst-generation biofuels result in relatively modest GHG mitigation
potential (-19 to 77 g CO2eq/MJ for fi rst-generation biofuels versus 85
to 109 g CO2eq/MJ for petroleum fuels), most next-generation biofuels
(with lifecycle GHG emissions between -10 and 38 g CO2eq/MJ) could
provide greater climate benefi ts. Estimates of lifecycle GHG emissions
are variable and uncertain for both biofuels and petroleum fuels, primarily
due to assumptions about biophysical parameters, methodological
issues and where and how the feedstocks are produced. [9.3.4.1]
Lifecycle GHG emissions from LUC are diffi cult to quantify, with land and
biomass resource management practices strongly infl uencing any GHG
emission reduction benefi ts and as such the sustainability of bioenergy.
Changes to land use or management, brought about directly or indirectly
by biomass production for use as fuels, power or heat, can lead to changes
in terrestrial carbon stocks. Depending on the converted land’s prior condition,
this can either cause signifi cant upfront emissions, requiring a time
■ ----I ■
□
124
Technical Summary Summaries
lag of decades to centuries before net savings are achieved, or improve the
net uptake of carbon into soils and aboveground biomass. Assessments
of the net GHG effects of bioenergy are made diffi cult by challenges in
observation, measurement, and attribution of indirect LUC, which depends
on the environmental, economic, social and policy context and is neither
directly observable nor easily attributable to a single cause. Illustrative estimates
of direct and indirect LUC-related GHG emissions induced by several
fi rst-generation biofuel pathways provide central tendencies (based on different
reporting methods) for a 30-year timeframe: for ethanol (EU wheat,
US maize, Brazilian sugarcane) 5 to 82 g CO2eq/MJ and for diesel (soy and
rapeseed) 35 to 63 g CO2eq/MJ. [9.3.4.1]
Impacts from local and regional air pollution constitute another important
assessment category, with air pollutants (including particulate
matter (PM), nitrous oxides (NOx), sulphur dioxide (SO2) and non-methane
volatile organic compounds (NMVOC)) having effects at the global [Box
9.4], regional and local scale. Compared to fossil-based power generation,
non-combustion-based RE power generation technologies have the
169(+12)
50(+10)
24
10
83(+7)
36(+4)
125
32
126
49
10
5
28
11
8
6
42
13
124
26
222(+4)
52(+0)
Count of
Estimates
Count of
References
Maximum
75th Percentile
Median
25th Percentile
Minimum
Single Estimates
with CCS
Electricity Generation Technologies Powered by Renewable Resources
Biopower
Photovoltaics
Concentrating Solar Power
Coal
Oil
Natural Gas
Geothermal Energy
Hydropower
Nuclear Energy
Ocean Energy
Wind Energy
-1,250
-1,500
-1,000
750
250
-250
-750
-500
0
500
1,750
1,250
1,000
1,500
2,000
Lifecycle Greenhouse Gas Emissions [g CO2 eq / kWh]
Electricity Generation Technologies
Powered by Non-Renewable Resources
Avoided Emissions, no Removal of GHGs from the Atmosphere
*
*
Figure TS.9.4 | Estimates of lifecycle GHG emissions (g CO2eq/kWh) for broad categories of electricity generation technologies, plus some technologies integrated with CCS. Land-use
related net changes in carbon stocks (mainly applicable to biopower and hydropower from reservoirs) and land management impacts are excluded; negative estimates1 for biopower
are based on assumptions about avoided emissions from residues and wastes in landfi ll disposals and co-products. References and methods for the review are reported in Annex II. The
number of estimates is greater than the number of references because many studies considered multiple scenarios. Numbers reported in parentheses pertain to additional references
and estimates that evaluated technologies with CCS. Distributional information relates to estimates currently available in LCA literature, not necessarily to underlying theoretical or
practical extrema, or the true central tendency when considering all deployment conditions. [Figure 9.8]
Note: 1. ‘Negative estimates’ within the terminology of lifecycle assessments presented in this report refer to avoided emissions. Unlike the case of bioenergy combined with CCS,
avoided emissions do not remove GHGs from the atmosphere.
-
-•
$
125
Summaries Technical Summary
potential to signifi cantly reduce regional and local air pollution and associated
health impacts (see this section below). For transportation fuels,
however, the effect of switching to biofuels on tailpipe emissions is not
yet clear. [9.3.4.2]
Local air pollutant emissions from fossil fuels and biomass combustion
constitute the most important energy related impacts on human health.
Ambient air pollution, as well as exposure to indoor air pollution from the
combustion of coal and traditional biomass, has major health impacts and
is recognized as one of the most important causes of morbidity and mortality
worldwide, particularly for women and children in developing countries.
In 2000, for example, comparative quantifi cations of health risks showed
that more than 1.6 million deaths and over 38.5 million of disabilityadjusted
life-years (DALYs) were attributable to indoor smoke from solid
fuels. Besides a fuel switch, mitigation options include improved cookstoves,
ventilation and building design and behavioural changes. [9.3.4.3]
Impacts on water relate to operational and upstream water consumption
of energy technologies and to water quality. These impacts are site specifi c
and need to be considered with respect to local resources and needs. RE
technologies like hydropower and some bioenergy systems, for example,
are dependent on water availability and can either increase competition
or mitigate water scarcity. In water-scarce areas, non-thermal RE technologies
(e.g., wind and PV) can provide clean electricity without putting
additional stress on water resources. Conventionally cooled thermal RE
technologies (e.g., CSP, geothermal, biopower) can use more water during
operation than non-RE technologies, yet dry cooling confi gurations
can reduce this impact (Figure TS.9.5). Water use in upstream processes
can be high for some energy technologies, particularly for fuel extraction
and biomass feedstock production; including the latter, the current water
footprint for electricity generation from biomass can be up to several hundred
times greater than operational water consumption requirements for
thermal power plants. Feedstock production, mining operations and fuel
processing can also affect water quality. [9.3.4.4]
Most energy technologies have substantial land requirements when the
whole supply chain is included. While the literature on lifecycle estimates
for land use by energy technologies is scarce, the available evidence suggests
that lifecycle land use by fossil energy chains can be comparable
to or higher than land use by RE sources. For most RE sources, land use
requirements are largest during the operational stage. An exception is the
land intensity of bioenergy from dedicated feedstocks, which is signifi -
cantly higher than for any other energy technology and shows substantial
variations in energy yields per hectare for different feedstocks and climatic
zones. A number of RE technologies (wind, wave and ocean) occupy large
areas, but allow secondary uses such as farming, fi shing and recreational
activities. [9.3.4.5] Connected to land use are (site-specifi c) impacts on
ecosystems and biodiversity. Occurring through various pathways, the
most evident ones are through large-scale direct physical alteration of
habitats and, more indirectly, habitat deterioration. [9.3.4.6]
The comparative assessment of accident risks is a pivotal aspect in a
comprehensive evaluation of energy security aspects and sustainability
performance associated with current and future energy systems.
Risks of various energy technologies to society and the environment
occur not only during the actual energy generation, but at all stages
of energy chains. Accident risks of RE technologies are not negligible,
but the technologies’ often decentralized structure strongly limits the
potential for disastrous consequences in terms of fatalities. While RE
technologies overall exhibit low fatality rates, dams associated with
some hydropower projects may create a specifi c risk depending on sitespecifi
c factors. [9.3.4.7]
9.4 Implication of sustainable development
pathways for renewable energy
Following the more static analysis of the impacts of current and emerging
RE systems on the four SD goals, the SD implications of possible
future RE deployment pathways are assessed in a more dynamic manner
and thus incorporate the intertemporal component of SD. Since
the interaction of future RE and SD pathways cannot be anticipated
by relying on a partial analysis of individual energy technologies, the
discussion is based on results from the scenario literature that typically
treats the portfolio of technological alternatives in the framework of a
global or regional energy system. [9.4]
The vast majority of models used to generate the scenarios reviewed
(see Chapter 10, Section 10.2) capture the interactions between different
options for supplying, transforming and using energy. The models
range from regional, energy-economic models to integrated assessment
models (IAMs) and are here referred to as integrated models.
Historically, these models have focused much more on the technological
and macroeconomic aspects of energy transitions, and in the
process have produced largely aggregated measures of technological
penetration or energy generated by particular sources of supply. The
value of these models in generating long-term scenarios and their
potential to help understand the interrelation between SD and RE rests
on their ability to consider interactions across a broad set of human
activities over different regional and time scales. Integrated models
continually undergo developments, some of which will be crucial for
the representation of sustainability concerns in the future, for example,
increasing their temporal and spatial resolution, allowing for a better
representation of the distribution of wealth across the population and
incorporating greater detail in human and physical Earth system characterization.
[9.4]
The assessment focuses on what model-based analyses currently have
to say with respect to SD pathways and the role of RE and evaluates
how model-based analyses can be improved to provide a better understanding
of sustainability issues in the future. [9.4]
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Technical Summary Summaries
9.4.1 Social and economic development
Integrated models usually have a strong macro-perspective and do not
consider advanced welfare measures. [9.2.2, 9.3.1] Instead, they focus
on economic growth, which in itself is an insuffi cient measure of sustainability,
but can be used as an indicative welfare measure in the
context of different stabilization pathways. Mitigation scenarios usually
include a tentative strong sustainability constraint by putting an upper
limit on future GHG emissions. This results in welfare losses (usually
measured as GDP or consumption foregone) based on assumptions
about the availability and costs of mitigation technologies. Limiting the
availability of technological alternatives for constraining GHGs further
increases welfare losses. Studies that specifi cally assess the implications
of constraining RE for different GHG concentration stabilization levels
Figure TS.9.5 | Ranges of rates of operational water consumption by thermal and non-thermal electricity-generating technologies based on a review of available literature (m3/MWh).
Bars represent absolute ranges from available literature, diamonds single estimates; n represents the number of estimates reported in the sources. Methods and references used in
this literature review are reported in Annex II. Note that upper values for hydropower result from a few studies measuring gross evaporation values, and may not be representative
(see Box 5.2). [Figure 9.14]
Notes: CSP: concentrated solar power; CCS: carbon capture and storage; IGCC: integrated gasifi cation combined cycle; CC: combined cycle; PV: photovoltaic.
209 m3/MWh
0
1
2
3
4
5
Operational Water Consumption [m3/MWh]
Recirculating Cooling Once-Through
Cooling
Pond
Cooling
Dry
Cooling
Non-Thermal
Technologies
Hybrid Cooling
CSP
Biopower Steam
Biopower Biogas
Nuclear
Natural Gas CC
Natural Gas CC with CCS
Coal
Coal with CCS
Coal IGCC
Coal IGCC with CCS
Biopower Steam
Nuclear
Natural Gas CC
Coal
Biopower Steam
Nuclear
Natural Gas CC
Coal
CSP
Natural Gas CC
CSP
CSP Dish Stirling
Biopower Biogas
Hydropower
PV
Wind
Ocean
18
11
4
2
1
1
2
2
2
2
4
2
2
2
1
1
2
2
11
4
7
2
1
1
1
1
1
1
9
4
3
3
3
3
1
1
3
1
7
2
2
1
16
8
1
1
4
4
5
5
1
1
4
3
N:
Sources:
Non Renewables
■■ Renewables
I I I I I I I I I I I I I I I I I I I I I I I
127
Summaries Technical Summary
show that the wide availability of all RE technologies is essential in order
to reach low stabilization levels and that the full availability of lowcarbon
technologies, including RE, is crucial for keeping mitigation costs
at relatively low levels, even for less strict stabilization levels. [9.4.1]
With respect to regional effects, scenario analyses show that developing
countries are likely to see most of the expansion in RE production. With
the challenge to overcome high LCOEs of RE technologies still to be
met, these results hint at the potential of developing countries to leapfrog
the emission-intensive developing paths that developed countries
have taken so far. Regional mitigation opportunities will, however, vary,
depending on many factors including technology availability, but also
population and economic growth. Costs will also depend on the allocation
of tradable emission permits, both initially and over time, under a
global climate mitigation regime. [9.4.1]
In general, scenario analyses point to the same links between RE, mitigation
and economic growth in developed and developing countries,
only the forces are generally larger in non-Annex I countries than in
Annex I countries due to more rapid assumed economic growth and
the consequently increasing mitigation burden over time. However, the
modelling structures used to generate long-term global scenarios generally
assume perfectly functioning economic markets and institutional
infrastructures across all regions of the globe. They also discount the
special circumstances that prevail in all countries, particularly in developing
countries where these assumptions are particularly tenuous. These
sorts of differences and the infl uence they might have on social and
economic development among countries should be an area of active
future research. [9.4.1]
9.4.2 Energy access
Integrated models thus far have often been based on developed country
information and experience and assumed energy systems in other parts
of the world and at different stages of development to behave likewise.
Usually, models do not capture important and determinative dynamics
in developing countries, such as fuel choices, behavioural heterogeneity
and informal economies. This impedes an assessment of the interaction
between RE and the future availability of energy services for different
populations, including basic household level tasks, transportation, and
energy for commerce, manufacturing and agriculture. However, some
models have started to integrate factors such as potential supply shortages,
informal economies and diverse income groups, and to increase
the distributional resolution. [9.4.2]
Available scenario analyses are still characterized by large uncertainties.
For India, results suggested that income distribution in a society
is as important for increasing energy access as income growth. Also,
increasing energy access is not necessarily benefi cial for all aspects of
SD, as a shift to modern energy away from, for example, traditional biomass
could simply be a shift to fossil fuels. In general, available scenario
analyses highlight the role of policies and fi nance for increased energy
access, even though forced shifts to RE that would provide access to
modern energy services could negatively affect household budgets.
[9.4.2]
Further improvements in the distribution resolution and structural rigidity
(inability of many models to capture social phenomena and structural
changes that underlie peoples’ utilization of energy technologies) are
particularly challenging. An explicit representation of the energy consequences
for the poorest, women, specifi c ethnic groups within countries,
or those in specifi c geographical areas, tends to be outside the range
of current global model output. In order to provide a more comprehensive
view of the possible range of energy access options, future energy
models should aim for a more explicit representation of relevant determinants
(such as traditional fuels, modes of electrifi cation, and income
distribution) and link these to representations of alternative development
pathways. [9.4.2]
9.4.3 Energy security
RE can infl uence energy security by mitigating concerns with respect
to both availability and distribution of resources, as well as to the variability
of energy sources. [9.2.2, 9.3.1] To the extent that RE deployment
in mitigation scenarios reduces the overall risk of disruption by diversifying
the energy portfolio, the energy system is less susceptible to
(sudden) energy supply disruption. In scenarios, this role of RE will vary
with the energy form. Solar, wind and ocean energy, which are closely
associated with electricity production, have the potential to replace
concentrated and increasingly scarce fossil fuels in the buildings and
the industry sector. With appropriate carbon mitigation policies in place,
electricity generation can be relatively easily decarbonized. In contrast,
the demand for liquid fuels in the transport sector remains inelastic if
no technological breakthrough can be achieved. While bioenergy could
play an important role, this will depend on the availability of CCS that
could divert its use to power generation with CCS—resulting in negative
net carbon emissions for the system and smoothing the overall
mitigation efforts signifi cantly. [9.4.1, 9.4.3]
Against this background, energy security concerns raised in the past
that related to oil supply disruptions are likely to remain relevant in
the future. For developing countries the issue will become even more
important, as their share in global total oil consumption increases in
all assessed scenarios (Figure TS.9.6b). As long as technological alternatives
for oil, for example, biofuels and/or the electrifi cation of the
transportation sector, do not play a dominant role in scenario analyses,
128
Technical Summary Summaries
most mitigation scenarios do not see dramatic differences between the
baseline and policy scenarios with respect to cumulative oil consumption
(Figure TS.9.6a). [9.4.3]
An increased market for bioenergy could raise additional energy security
concerns in the future if it was characterized by a small number of sellers
and thus showed parallels to today’s oil market. In such an environment,
the risk that food prices could be linked to volatile bioenergy markets
would have to be mitigated to impede severe impacts on SD as high and
volatile food prices would clearly hurt the poor. [9.4.3]
The introduction of variable RE technologies also adds new concerns,
such as vulnerability to extreme natural events or international price fl uctuations,
which are not yet satisfactorily addressed by large integrated
models. Additional efforts to increase system reliability are likely to add
costs and involve balancing needs (such as holding stocks of energy),
the development of complementary fl exible generation, strengthening
network infrastructure and interconnections, energy storage technologies
and modifi ed institutional arrangements including regulatory and
market mechanisms [7.5, 8.2.1, 9.4.3]
Energy security considerations today usually focus on the most prominent
energy security issues in recent memory. However, energy security
aspects of the future might go well beyond these issues, for example,
in relation to critical material inputs for RE technologies. These broader
concerns as well as options for addressing them, for example, recycling,
are largely absent from future scenarios of mitigation and RE. [9.4.3]
9.4.4 Climate change mitigation and environmental
and health impacts in scenarios of the future
Replacing fossil fuels with RE or other low-carbon technologies can signifi
cantly contribute to the reduction of NOx and SO2 emissions. Several
models have included explicit representation of factors, such as sulphate
pollution, that are linked to environmental or health impacts. Some scenario
results show that climate policy can help drive improvements in
local air pollution (i.e., PM), but air pollution reduction policies alone do
not necessarily drive reductions in GHG emissions. Another implication
of some potential energy trajectories is the possible diversion of land to
support biofuel production. Scenario results have pointed at the possibility
that, if not accompanied by other policy measures, climate policy
could drive widespread deforestation, with land use being shifted to
bioenergy crops with possibly adverse SD implications, including GHG
emissions. [9.4.4]
Unfortunately, existing scenario literature does not explicitly treat the
many non-emissions related elements of sustainable energy development,
such as water use, the impacts of energy choices on household-level
services, or indoor air quality. This can be partly explained by models
being designed to look at fairly large world regions without income or
geographic distributional detail. For a broad assessment of environmental
impacts at the regional and local level, models would need to look
at smaller scales of geographical impacts, which is currently a matter of
ongoing research. Finally, many models do not explicitly allow for incorporation
of LCA results of the technological alternatives. What these
(a) (b)
Share of Global Oil Consumption in Developing Countries
Conventional Oil Reserves [ZJ]
Cumulative Oil Consumption 2010-2100 [ZJ]
2005 2020 2040 2060 2080 2100
0
5
10
15
20
25
30
35
0
5
10
15
20
25
30
35
Conventional
Oil Reserves
Baseline Cat III+IV Cat I+II
0.2
0.4
0.6
0.8
1.0
Cat I+II Median
Cat III+IV Cat III+IV Median
Cat I+II
Baseline Baseline Median
Figure TS.9.6 | (a) Conventional oil reserves compared to projected cumulative oil consumption (ZJ) from 2010 to 2100 in scenarios assessed in Chapter 10 for different scenario
categories: baseline scenarios, Category III and IV scenarios and low stabilization (Category I+II) scenarios. The thick dark blue line corresponds to the median, the light blue bar
corresponds to the inter-quartile range (25th to 75th percentile) and the white surrounding bar corresponds to the total range across all reviewed scenarios. The last column shows
the range of proven recoverable conventional oil reserves (light blue bar) and estimated additional reserves (white surrounding bar). (b) Range of share of global oil consumed in non-
Annex I countries for different scenario categories over time, based on scenarios assessed in Chapter 10. [Figure 9.18]
□
■
■
■
129
Summaries Technical Summary
impacts are, whether and how to compare them across categories, and
whether they might be incorporated into future scenarios would constitute
useful areas for future research. [9.4.4]
9.5 Barriers and opportunities for renewable
energy in the context of sustainable
development
Pursuing a renewable energy deployment strategy in the context of SD
implies that most environmental, social and economic effects are taken
explicitly into account. Integrated planning, policy and implementation
processes can support this by anticipating and overcoming potential
barriers to and exploiting opportunities of RE deployment. [9.5]
Barriers that are particularly pertinent in a sustainable development
context and that may either impede RE deployment or result in tradeoffs
with SD criteria relate to socio-cultural, information and awareness,
market-related and economic barriers. [9.5.1]
Socio-cultural barriers or concerns have different origins and are intrinsically
linked to societal and personal values and norms. Such values
and norms affect the perception and acceptance of RE technologies and
the potential impacts of their deployment by individuals, groups and
societies. From a sustainable development perspective, barriers may
arise from inadequate attention to such socio-cultural concerns, which
include barriers related to behaviour; natural habitats and natural and
human heritage sites, including impacts on biodiversity and ecosystems;
landscape aesthetics; and water/land use and water/land use rights, as
well as their availability for competing uses. [9.5.1.1]
Public awareness and acceptance is an important element in the need
to rapidly and signifi cantly scale up RE deployment to help meet climate
change mitigation goals. Large-scale implementation can only be undertaken
successfully with the understanding and support of the public. This
may require dedicated communication efforts related to the achievements
and the opportunities associated with wider-scale applications.
At the same time, however, public participation in planning decisions
as well as fairness and equity considerations in the distribution of the
benefi ts and costs of RE deployment play an equally important role and
cannot be side-stepped. [9.5.1.1]
In developing countries, limited technical and business skills and the
absence of technical support systems are particularly apparent in the
energy sector, where awareness of and information dissemination
regarding available and appropriate RE options among potential consumers
is a key determinant of uptake and market creation. This gap
in awareness is often perceived as the single most important factor
affecting the deployment of RE and development of small and medium
enterprises that contribute to economic growth. Also, there is a need to
focus on the capacity of private actors to develop, implement and deploy
RE technologies, which includes increasing technical and business capability
at the micro or fi rm level. [9.5.1.2]
Attitudes towards RE in addition to rationality are driven by emotions
and psychological issues. To be successful, RE deployment and information
and awareness efforts and strategies need to take this explicitly into
account. [9.5.1.2]
To assess the economics of RE in the context of SD, social costs and
benefi ts need to be explicitly considered. RE should be assessed against
quantifi able criteria targeted at cost effectiveness, regional appropriateness,
and environmental and distributional consequences. Grid size
and technologies are key determinants of the economic viability of RE
and of the competitiveness of RE compared to non-renewable energy.
Appropriate RE technologies that are economically viable are often
found to be available for expanding rural off-grid energy access, in
particular smaller off-grid and mini-grid applications. [9.5.1.3]
In cases where deployment of RE is viable from an economic perspective,
other economic and fi nancial barriers may affect its deployment.
High upfront costs of investments, including high installation and grid
connection costs, are examples of frequently identifi ed barriers to
RE deployment. In developing countries, policy and entrepreneurial
support systems are needed along with RE deployment to stimulate
economic growth and SD and catalyze rural and peri-urban cash
economies. Lack of adequate resource potential data directly affects
uncertainty regarding resource availability, which may translate into
higher risk premiums for investors and project developers. The internalization
of environmental and social externalities frequently results
in changes in the ranking of various energy sources and technologies,
with important lessons for SD objectives and strategies. [9.5.1.3]
Strategies for SD at international, national and local levels as well as
in private and nongovernmental spheres of society can help overcome
barriers and create opportunities for RE deployment by integrating RE
and SD policies and practices. [9.5.2]
Integrating RE policy into national and local SD strategies (explicitly
recognized at the 2002 World Summit on Sustainable Development)
provides a framework for countries to select effective SD and RE strategies
and to align those with international policy measures. To that end,
national strategies should include the removal of existing fi nancial
mechanisms that work against SD. For example, the removal of fossil
fuel subsidies may have the potential to open up opportunities
for more extensive use or even market entry of RE, but any subsidy
reform towards the use of RE technologies needs to address the specifi
c needs of the poor and demands a case-specifi c analysis. [9.5.2.1]
The CDM established under the Kyoto Protocol is a practical example
of a mechanism for SD that internalizes environmental and social
externalities. However, there are no international standards for
130
Technical Summary Summaries
sustainability assessments (including comparable SD indicators) to
counter weaknesses in the existing system regarding sustainability
approval. As input to the negotiations for a post-2012 climate regime,
many suggestions have been made about how to reform the CDM to
better achieve new and improved mechanisms for SD. [9.5.2.1]
Opportunities for RE to play a role in national strategies for SD can be
approached by integrating SD and RE goals into development policies
and by development of sectoral strategies for RE that contribute to
goals for green growth and low-carbon and sustainable development
including leapfrogging. [9.5.2.1]
At the local level, SD initiatives by cities, local governments, and private
and nongovernmental organizations can be drivers of change and
contribute to overcome local resistance to RE installations. [9.5.2.2]
9.6 Synthesis, knowledge gaps and future
research needs
RE can contribute to SD and the four goals assessed to varying
degrees. While benefi ts with respect to reduced environmental and
health impacts may appear more clear-cut, the exact contribution to,
for example, social and economic development is more ambiguous.
Also, countries may prioritize the four SD goals according to their level
of development. To some extent, however, these SD goals are also
strongly interlinked. Climate change mitigation constitutes in itself a
necessary prerequisite for successful social and economic development
in many developing countries. [9.6.6]
Following this logic, climate change mitigation can be assessed under
the strong SD paradigm, if mitigation goals are imposed as constraints
on future development pathways. If climate change mitigation is
balanced against economic growth or other socioeconomic criteria,
the problem is framed within the paradigm of weak SD allowing for
trade-offs between these goals and using cost-benefi t type analyses
to provide guidance in their prioritization. [9.6.6]
However, the existence of uncertainty and ignorance as inherent
components of any development pathway, as well as the existence
of associated and possibly ‘unacceptably high’ opportunity costs, will
make continued adjustments crucial. In the future, integrated models
may be in a favourable position to better link the weak and strong
SD paradigms for decision-making processes. Within well-defi ned
guardrails, integrated models could explore scenarios for different
mitigation pathways, taking account of the remaining SD goals by
including important and relevant bottom-up indicators. According
to model type, these alternative development pathways might be
optimized for socially benefi cial outcomes. Equally, however, the
incorporation of GHG emission-related LCA data will be crucial for a
clear defi nition of appropriate GHG concentration stabilization levels
in the fi rst place. [9.6.6]
In order to improve the knowledge regarding the interrelations between
SD and RE and to fi nd answers to the question of effective, economically
effi cient and socially acceptable transformations of the energy system,
it is necessary to develop a closer integration of insights from social,
natural and economic sciences (e.g., through risk analysis approaches),
refl ecting the different dimensions of sustainability (especially intertemporal,
spatial, and intergenerational). So far, the knowledge base is
often limited to very narrow views from specifi c branches of research,
which do not fully account for the complexity of the issue. [9.7]
10. Mitigation Potential and Costs
10.1 Introduction
Future GHG emission estimates are highly dependent on the evolution
of many variables, including, among others, economic growth,
population growth, energy demand, energy resources and the future
costs and performance of energy supply and end-use technologies.
Mitigation and other non-mitigation policy structures in the future will
also infl uence deployment of mitigation technologies and therefore
GHG emissions and the ability to meet climate goals. Not only must
all these different forces be considered simultaneously when exploring
the role of RE in climate mitigation [see Figure 1.14], it is not possible
to know today with any certainty how these different key forces might
evolve decades into the future. [10.1]
Questions about the role that RE sources are likely to play in the future,
and how they might contribute to GHG mitigation pathways, need to
be explored within this broader context. Chapter 10 provides such an
exploration through the review of 164 existing medium- to long-term
scenarios from large-scale, integrated models. The comprehensive
review explores the range of global RE deployment levels emerging in
recent published scenarios and identifi es many of the key forces that
drive the variation among scenarios (note that the chapter relies exclusively
on existing published scenarios and does not create any new
scenarios). It does so both at the scale of RE as a whole and also in the
context of individual RE technologies. The review highlights the importance
of interactions and competition with other technologies as well
as the evolution of energy demand more generally. [10.2]
This large-scale review is complemented with a more detailed discussion
of future RE deployment, using 4 of the 164 scenarios as
illustrative examples. The chosen scenarios span a range of different
future expectations about RE characteristics, are based on different
methodologies and cover different GHG concentration stabilization
levels. This approach provides a next level of detail for exploring the
role of RE in climate change mitigation, distinguishing between different
applications (electricity generation, heating and cooling, transport)
and regions. [10.3]
131
Summaries Technical Summary
As the resulting role of RE is signifi cantly determined by cost factors,
a more general discussion about cost curves and cost aspects is then
provided. This discussion starts with an assessment of the strengths
and shortcomings of supply curves for RE and GHG mitigation, and
then reviews the existing literature on regional RE supply curves, as
well as abatement cost curves, as they pertain to mitigation using RE
sources. [10.4]
Costs of RE commercialization and deployment are then addressed.
The chapter reviews present RE technology costs, as well as expectations
about how these costs might evolve into the future. To allow an
assessment of future market volumes and investment needs, based
on the results of the four illustrative scenarios investments in RE are
discussed in particular with respect to what might be required if ambitious
climate protection goals are to be achieved. [10.5]
Standard economic measures do not cover the full set of costs.
Therefore, social and environmental costs and benefi ts of increased
deployment of RE in relation to climate change mitigation and SD are
synthesized and discussed. [10.6]
10.2 Synthesis of mitigation scenarios for
different renewable energy strategies
An increasing number of integrated scenario analyses that are able to
provide relevant insights into the potential contribution of RE to future
energy supplies and climate change mitigation has become available.
To provide a broad context for understanding the role of RE in mitigation
and the infl uence of RE on the costs of mitigation, 164 recent
medium- to long-term scenarios from 16 global energy-economic and
integrated assessment models were reviewed. The scenarios were collected
through an open call. The scenarios cover a large range of CO2
concentrations (350 to 1,050 ppm atmospheric CO2 concentration by
2100), representing both mitigation and baseline scenarios. [10.2.2.1]
Although these scenarios represent some of the most recent and
sophisticated thinking regarding climate mitigation and the role of RE
in climate mitigation in the medium- to long-term, they, as with any
analysis looking decades into the future, must be interpreted carefully.
All of the scenarios were developed using quantitative modelling, but
there is enormous variation in the detail and structure of the models
used to construct the scenarios. In addition, the scenarios do not represent
a random sample of possible scenarios that could be used for
formal uncertainty analysis. Some modelling groups provided more scenarios
than others. In scenario ensemble analyses based on collecting
scenarios from different studies, such as the review here, there is an
inevitable tension between the fact that the scenarios are not truly a
random sample and the sense that the variation in the scenarios does
still provide real and often clear insights into our knowledge about the
future, or lack thereof. [10.2.1.2, 10.2.2.1]
A fundamental question relating to the role of RE in climate mitigation
is how closely RE deployment levels are correlated with long-term
atmospheric CO2 concentration or related climate goals. The scenarios
indicate that although there is a strong correlation between fossil and
industrial CO2 emissions pathways and long-term CO2 concentration
goals across the scenarios, the relationship between RE deployment and
CO2 concentration goals is far less robust (Figure TS.10.1). RE deployment
generally increases with the stringency of the CO2 concentration
goal, but there is enormous variation among RE deployment levels for
any given CO2 concentration goal. For example, in scenarios that stabilize
the atmospheric CO2 concentration at a level of less than 440 ppm
(Categories I and II), the median RE deployment levels are 139 EJ/yr in
2030 and 248 EJ/yr in 2050, with the highest levels reaching 252 EJ/yr in
2030 and up to 428 EJ/yr in 2050. These levels are considerably higher
than the corresponding RE deployment levels in baseline scenarios,
although it has to be acknowledged that the range of RE deployment in
each of the CO2 stabilization categories is wide. [10.2.2.2]
At the same time, it is also important to note that despite the variation,
the absolute magnitudes of RE deployment are dramatically higher than
those of today in the vast majority of the scenarios. In 2008, global
renewable primary energy supply in direct equivalent stood at roughly
64 EJ/yr. The majority of this, about 30 EJ/yr, was traditional biomass. In
contrast, by 2030, many scenarios indicate a doubling of RE deployment
or more compared to today, and this is accompanied in most scenarios
by a reduction in traditional biomass, implying substantial growth in
non-traditional RE sources. By 2050, RE deployment levels in most scenarios
are higher than 100 EJ/yr (median at 173 EJ/yr), reach 200 EJ/yr
in many of the scenarios and more than 400 EJ/yr in some cases. Given
that traditional biomass use decreases in most scenarios, the scenarios
represent an increase in RE production (excluding traditional biomass)
of anywhere from roughly three- to more than ten-fold. More than half
of the scenarios show a contribution of RE in excess of a 17% share of
primary energy supply in 2030, rising to more than 27% in 2050. The
scenarios with the highest RE shares reach approximately 43% in 2030
and 77% in 2050. Deployments after 2050 are even larger. This is an
extraordinary expansion in energy production from RE. [10.2.2.2]
Indeed, RE deployment is quite large in many of the baseline scenarios
with no assumed GHG concentration stabilization level. By 2030, RE
deployment levels of up to about 120 EJ/yr are projected, with many
baseline scenarios reaching more than 100 EJ/yr in 2050 and in some
cases up to 250 EJ/yr. These large RE baseline deployments result from a
range of underlying scenario assumptions, for example, the assumption
that energy consumption will continue to grow substantially throughout
the century, assumptions about the ability of RE to contribute to
increased energy access, assumptions about the availability of fossil
resources, and other assumptions (e.g., improved costs and performance
of RE technologies) that would render RE technologies economically
increasingly competitive in many applications even absent climate policy.
[10.2.2.2]
132
Technical Summary Summaries
CO2 Concentration Levels
Category I (<400 ppm)
Category II (400-440 ppm)
Category III (440-485 ppm)
Category IV (485-600 ppm)
Baselines
0 20 40 60 0 20 40 60 80
2030
0 100 200 300 400
0 100 200 300 400
N=161
2050
N=164
Renewable Primary Energy Supply [EJ/yr]
CO2 Emissions from Fossil Fuels
and Industrial Processes [Gt CO2/yr]
CO2 Emissions from Fossil Fuels
and Industrial Processes [Gt CO2/yr]
Category I
Category II
Category III
Category IV
Baselines
Category I
Category II
Category III
Category IV
Baselines
Maximum
75th
Median
25th
Minimum
F igure TS.10.1 | Global RE primary energy supply (direct equivalent) from 164 long-term scenarios as a function of fossil and industrial CO2 emissions in 2030 and 2050. Colour
coding is based on categories of atmospheric CO2 concentration level in 2100. The panels to the right of the scatterplots show the deployment levels of RE in each of the atmospheric
CO2 concentration categories. The thick black line corresponds to the median, the coloured box corresponds to the inter-quartile range (25th to 75th percentile) and the ends of the
white surrounding bars correspond to the total range across all reviewed scenarios. The blue crossed-lines show the relationship in 2007. Pearson’s correlation coeffi cients for the two
data sets are -0.40 (2030) and -0.55 (2050). For data reporting reasons, only 161 scenarios are included in the 2030 results shown here, as opposed to the full set of 164 scenarios.
RE deployment levels below those of today are a result both of model output as well as differences in the reporting of traditional biomass. [Figure 10.2]
The uncertainty in RE’s role in climate mitigation results from uncertainty
regarding a number of important forces that infl uence the deployment of
RE. Two important factors are energy demand growth and the competition
with other options to reduce CO2 emissions (primarily nuclear energy and
fossil energy with CCS). Meeting long-term climate goals requires a reduction
in the CO2 emissions from energy and other anthropogenic sources.
For any given climate goal, this reduction is relatively well defi ned; there
is a tight relationship between fossil and industrial CO2 emissions and the
deployment of freely emitting fossil energy across the scenarios (Figure
TS.10.2). The demand for low-carbon energy (including RE, nuclear energy
and fossil energy with CCS) is simply the difference between total primary
energy demand and the production of freely-emitting fossil energy; that
is, whatever energy cannot be supplied by freely-emitting fossil energy
because of climate constraints must be supplied either by low-carbon
energy or by measures that reduce energy consumption. However, scenarios
indicate enormous uncertainty about energy demand growth,
particularly many decades into the future. This variation is generally much
larger than the effect of mitigation on energy consumption. Hence, there is
substantial variability in low-carbon energy for any given CO2 concentration
goal due to variability in energy demand (Figure TS.10.2). [10.2.2.3]
The competition between RE, nuclear energy, and fossil energy with CCS
then adds another layer of variability in the relationship between RE
deployment and the CO2 concentration goal. The cost, performance and
availability of the competing supply side options—nuclear energy and
fossil energy with CCS—is also uncertain. If the option to deploy these
other supply-side mitigation technologies is constrained—because of
cost and performance, but also potentially due to environmental, social
or national security barriers—then, all things being equal, RE deployment
levels will be higher (Figure TS.10.3). [10.2.2.4]
There is also great variation in the deployment characteristics of
individual RE technologies. The absolute scales of deployments vary
considerably among technologies and also deployment magnitudes are
characterized by greater variation for some technologies relative to others
(Figures TS.10.4 and TS.10.5). Further, the time scale of deployment
varies across different RE sources, in large part representing differences
in deployment levels today and (often) associated assumptions about
relative technological maturity. [10.2.2.5]
The scenarios generally indicate that RE deployment is larger in non-
Annex I countries over time than in the Annex I countries. Virtually all
scenarios include the assumption that economic and energy demand
growth will be larger at some point in the future in the non-Annex I
countries than in the Annex I countries. The result is that the non-Annex
I countries account for an increasingly large proportion of CO2 emissions
in baseline, or no-policy, cases and must therefore make larger
emissions reductions over time (Figure TS.10.4). [10.2.2.5]
•
•
•
•
•
• •
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133
Summaries Technical Summary
Figure TS.10.2 | Global freely emitting fossil fuel (left panel; direct equivalent) and low-carbon primary energy supply (right panel; direct equivalent) in 164 long-term scenarios in
2050 as a function of fossil and industrial CO2 emissions. Low-carbon energy refers to energy from RE, fossil energy with CCS, and nuclear energy. Colour coding is based on categories
of atmospheric CO2 concentration level in 2100. The blue crossed lines show the relationship in 2007. Pearson’s correlation coeffi cients for the two data sets are 0.97 (freely emitting
fossil) and -0.68 (low-carbon energy). For data reporting reasons, only 153 scenarios and 161 scenarios are included in the freely-emitting fossil and low-carbon primary energy results
shown here, respectively, as opposed to the full set of 164 scenarios. [Figure 10.4, right panel, Figure 10.5, right panel]
0 20 40 60 80
0 200 400 600 800
2050
Fossil and Industrial CO2 Emissions [Gt CO2/yr]
Freely Emitting Fossil Primary Energy Supply [EJ/yr]
N=153 N=164
0 200 400 600 800
0 20 40 60 80
2050
Fossil and Industrial CO2 Emissions [Gt CO2/yr]
Low−Carbon Primary Energy Supply [EJ/yr]
Another fundamental question regarding RE and mitigation is the relationship
between RE and mitigation costs. A number of studies have
pursued scenario sensitivities that assume constraints on the deployment
of individual mitigation options, including RE as well as nuclear
energy and fossil energy with CCS (Figures TS.10.6 and TS.10.7).
These studies indicate that mitigation costs are higher when options,
including RE, are not available. Indeed, the cost penalty for limits
on RE is often at least of the same order of magnitude as the cost
penalty for limits on nuclear energy and fossil energy with CCS. The
studies also indicate that more aggressive concentration goals may
not be possible when RE options, or other low-carbon options, are
not available. At the same time, when taking into account the wide
range of assumptions across the full range of scenarios explored in this
assessment, the scenarios demonstrate no meaningful link between
measures of cost (e.g., carbon prices) and absolute RE deployment
levels. This variation is a refl ection of the fact that large-scale integrated
models used to generate scenarios are characterized by a wide
range of carbon prices and mitigation costs based on both parameter
assumptions and model structure. To summarize, while there is an
agreement in the literature that mitigation costs will increase if the
deployment of RE technologies is constrained and that more ambitious
concentration stabilization levels may not be reachable, there
is little agreement on the precise magnitude of the cost increase.
[10.2.2.6]
10.3 Assessment of representative mitigation
scenarios for different renewable energy
strategies
An in-depth analysis of 4 selected illustrative scenarios from the
larger set of 164 scenarios allowed a more detailed look at the possible
contribution of specifi c RE technologies in different regions and
sectors. The IEA’s World Energy Outlook (IEA WEO 2009) was selected
as an example of a baseline scenario, while the other scenarios set
clear GHG concentration stabilization levels. The chosen mitigation
scenarios are ReMIND-RECIPE from the Potsdam Institute, MiniCAM
EMF 22 from the Energy Modelling Forum Study 22 and the Energy [R]
evolution scenario from the German Aerospace Centre, Greenpeace
International and EREC (ER 2010). The scenarios work as illustrative
examples, but they are not representative in a strict sense. However
they represent four different future paths based on different methodologies
and a wide range of underlying assumptions. Particularly,
they stand for different RE deployment paths reaching from a typical
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••&0 •
•
•
• •
•
•
0
•• •
•
•
•
134
Technical Summary Summaries
0
10
20
30
40
50
450 ppmv
CO2
450 ppmv
CO2
450 ppmv
CO2
400 ppmv
CO2 eq (*)
550 ppmv
CO2 eq
400 ppmv
CO2 eq (*)
550 ppmv
CO2 eq
400 ppmv
CO2 eq (*)
550 ppmv
CO2 eq
450 ppmv
CO2 eq
550 ppmv
CO2 eq
550 ppmv
CO2 eq (*)
DNE21+ MESSAGE (EMF22) MERGE-ETL (ADAM) POLES (ADAM) ReMIND (ADAM) WITCH
(RECIPE)
IMACLIM
(RECIPE)
ReMIND
(RECIPE)
No CCS & Limited Nuclear
Limited Nuclear
No CCS
Standard
Additional Renewable Primary Energy Share
[Percentage Points Change Relative to Baseline]
Not Evaluated
Not Evaluated
Not Evaluated
Not Evaluated
Not Evaluated
Not Evaluated
Not Evaluated
X
Not Evaluated
Figure TS.10.3 | Increase in global renewable primary energy share (direct equivalent) in 2050 in selected constrained technology scenarios compared to the respective baseline scenarios.
The ‘X’ indicates that the respective concentration level for the scenario was not achieved. The defi nition of ‘lim Nuclear’ and ‘no CCS’ cases varies across models. The DNE21+,
MERGE-ETL and POLES scenarios represent nuclear phase-outs at different speeds; the MESSAGE scenarios limit the deployment to 2010; and the ReMIND, IMACLIM and WITCH
scenarios limit nuclear energy to the contribution in the respective baseline scenarios, which can still imply a signifi cant expansion compared to current deployment levels. The REMIND
(ADAM) 400 ppmv no CCS scenario refers to a scenario in which cumulative CO2 storage is constrained to 120 Gt CO2. The MERGE-ETL 400 ppmv no CCS case allows cumulative CO2
storage of about 720 Gt CO2. The POLES 400 ppmv CO2eq no CCS scenario was infeasible and therefore the respective concentration level of the scenario shown here was relaxed by
approximately 50 ppm CO2. The DNE21+ scenario is approximated at 550 ppmv CO2eq based on the emissions pathway through 2050. [Figure 10.6]
baseline perspective to a scenario that follows an optimistic application
path for RE assuming that amongst others driven by specifi c
policies the current high dynamic (increase rates) in the sector can be
maintained. [10.3.1]
Figure TS.10.8 provides an overview of the resulting primary energy
production by source for the four selected scenarios for 2020, 2030
and 2050 and compares the numbers with the range of the global primary
energy supply. Using the direct equivalent methodology as done
here, in 2050 bioenergy has the highest market share in all selected
scenarios, followed by solar energy. The total RE share in the primary
energy mix by 2050 has a substantial variation across all four scenarios.
With 15% by 2050—more or less about today’s level (12.9%
in 2008)—the IEA WEO 2009 projects the lowest primary RE share,
while the ER 2010 with 77% marks the upper level. The MiniCam EMF
22 expects that 31% and ReMIND-RECIPE that 48% of the world’s
primary energy demand will be provided by RE in 2050. The wide
ranges of RE shares are a function of different assumptions for technology
cost and performance data, availability of other mitigation
technologies (e.g., CCS, nuclear power), infrastructure or integration
constraints, non-economic barriers (e.g., sustainability aspects), specifi
c policies and future energy demand projections. [10.3.1.4]
In addition, although deployment of the different technologies signifi
cantly increases over time, the resulting contribution of RE in the
scenarios for most technologies in the different regions of the world
is much lower than their corresponding technical potentials (Figure
TS.10.9). The overall total global RE deployment by 2050 in all analyzed
scenarios represents less than 3% of the available technical RE
potential. On a regional level, the maximum deployment share out
of the overall technical potential for RE in 2050 was found for China,
with a total of 18% (ER 2010), followed by OECD Europe with 15%
(ER 2010) and India with 13% (MiniCam EMF 22). Two regions have
deployment rates of around 6% of the regional available technical RE
potential by 2050: 7% in Developing Asia (MiniCam EMF 22) and 6%
in OECD North America (ER 2010). The remaining fi ve regions use less
than 5% of the available technical potential for RE. [10.3.2.1]
Based on the resulting RE deployment for the selected four illustrative
scenarios, the corresponding GHG mitigation potential has been calculated.
For each sector, emission factors have been specifi ed, addressing
the kind of electricity generation or heat supply that RE displaces. As the
substituted energy form depends on the overall system behaviour, this
cannot be done exactly without conducting new and consistent scenario
analysis or complex power plant dispatching analysis. Therefore,
the calculation is necessarily based on simplifi ed assumptions and can
only be seen as indicative. Generally, attribution of precise mitigation
potentials to RE should be viewed with caution. [10.3.3]
Very often RE applications are supposed to fully substitute for the existing
mix of fossil fuel use, but in reality that may not be true as RE
can compete, for instance, with nuclear energy or within the RE portfolio
itself. To cover the uncertainties even partly for the specifi cation
of the emission factor, three different cases have been distinguished
135
Summaries Technical Summary
Figure TS.10.4 | Global RE primary energy supply (direct equivalent) by source in Annex
I (AI) and Non-Annex I (NAI) countries in 164 long-term scenarios by 2030 and 2050.
The thick black line corresponds to the median, the coloured box corresponds to the
inter-quartile range (25th to 75th percentile) and the ends of the white surrounding bars
correspond to the total range across all reviewed scenarios. Depending on the source,
the number of scenarios underlying these fi gures varies between 122 and 164. Although
instructive for interpreting the information, it is important to note that the 164 scenarios
are not explicitly a random sample meant for formal statistical analysis. (One reason that
bioenergy supply appears larger than supplies from other sources is that the direct equivalent
method is used to represent primary energy in this fi gure. Bioenergy is accounted for
prior to conversion to fuels such as ethanol or electricity. The other technologies produce
primarily (but not entirely) electricity, and they are accounted for based on the electricity
produced. If primary equivalents were used, based on the substitution method, rather
than direct equivalents, then energy production from non-biomass RE would be of the
order of three times larger than shown here.) Ocean energy is not presented here as only
very few scenarios consider this RE technology. [Figure 10.8]
Additionally, to refl ect the embedded GHG emissions from bioenergy
used for direct heating, only half of the theoretical CO2 savings have
been considered in the calculation. Given the high uncertainties and
variability of embedded GHG emissions, this is necessarily once more a
simplifi ed assumption. [10.3.3]
Figure TS.10.10 shows cumulative CO2 reduction potentials from RE
sources up to 2020, 2030 and 2050 resulting from the four scenarios
reviewed here in detail. The analyzed scenarios outline a cumulative
reduction potential (2010 to 2050) in the medium-case approach of
between 244 Gt CO2 (IEA WEO 2009) under the baseline conditions,
297 Gt CO2 (MiniCam EMF 22), 482 Gt CO2 (ER 2010) and 490 Gt CO2
(ReMIND-RECIPE scenario). The full range across all calculated cases
and scenarios is cumulative CO2 savings of 218 Gt CO2 (IEA WEO
2009) to 561 Gt CO2 (ReMIND-RECIPE) compared to about 1,530 Gt
CO2 cumulative fossil and industrial CO2 emissions in the WEO 2009
Reference scenario during the same period. However, these numbers
exclude CO2 savings for RE use in the transport sector (including biofuels
and electric vehicles). The overall CO2 mitigation potential can
therefore be higher. [10.3.3]
10.4 Regional cost curves for mitigation with
renewable energy sources
The concept of supply curves of carbon abatement, energy, or conserved
energy all rest on the same foundation. They are curves consisting
typically of discrete steps, each step relating the marginal cost of the
abatement measure/energy generation technology or measure to conserve
energy to its potential; these steps are ranked according to their
cost. Graphically, the steps start at the lowest cost on the left with the
next highest cost added to the right and so on, making an upward sloping
left-to-right marginal cost curve. As a result, a curve is obtained that
can be interpreted similarly to the concept of supply curves in traditional
economics. [10.4.2.1]
The concept of energy conservation supply curves is often used, but it
has common and specifi c limitations. The most often cited limitations in
2030
AI NAI AI NAI AI NAI AI NAI AI NAI
[EJ/yr]
0
50
100
150
200
2050
[EJ/yr]
0
50
100
150
200
AI NAI AI NAI AI NAI AI NAI AI NAI
Bioenergy
Hydropower
Wind Energy
Direct Solar Energy
Geothermal Energy
Maximum
75th Percentile
Median
25th Percentile
Minimum
(upper case: specifi c average CO2 emissions of the fossil generation mix
under the baseline scenario; medium case: specifi c average CO2 emissions
of the overall generation mix under the baseline scenario; and
lower case: specifi c average CO2 emissions of the generation mix of the
particular analyzed scenario). Biofuels and other RE options for transport
are excluded from the calculation due to limited data availability.
■
■
■
■
■
136
Technical Summary Summaries
Deployment Level 2008
Maximum
75th
Median
25th
Minimum
CO2 Concentration Levels
Direct Solar Energy
Geothermal Energy
Wind Energy
Hydropower
Wind and Solar PV Electricity Share
Primary Energy Supply [EJ/yr] Primary Energy Supply [EJ/yr]
Primary Energy Supply [EJ/yr] Primary Energy Supply [EJ/yr]
Primary Energy Supply [EJ/yr]
Electricity Supply [%]
2020 2030 2050 2020 2030 2050
2020 2030 2050
2020 2030 2050
2020 2030 2050
2020 2030 2050
0
50
150
100
0
50
150
100
0
0
50
150
100
0
50
150
100
0
50
100
Bioenergy
50
150
100
Baselines
Cat. III + IV (440 - 600 ppm)
Cat. I + II (<440 ppm)
200
250
300
350
N=122
N=137 N=156
N=164
N=152 N=149
■■ ■
-
----□- --- ---i-o- --- --- -b- ---- _illliL _Dill _
!
l
---□--□--□---· n n_O__ n D -.... .---=
a-=a- = ---- ·-------------------------
.
- ·--- - ----------
137
Summaries Technical Summary
Figure TS.10.5 | (Preceding page) Global primary energy supply (direct equivalent) of biomass, wind, solar, hydro, and geothermal energy in 164 long-term scenarios in 2020, 2030
and 2050, and grouped by different categories of atmospheric CO2 concentration level in 2100. The thick black line corresponds to the median, the coloured box corresponds to the
inter-quartile range (25th to 75th percentile) and the ends of the white surrounding bars correspond to the total range across all reviewed scenarios. [Figure 10.9]
Notes: For data reporting reasons, the number of scenarios included in each of the panels shown here varies considerably. The number of scenarios underlying the individual panels,
as opposed to the full set of 164 scenarios, is indicated in the right upper corner of each panel. One reason that bioenergy supply appears larger than supplies from other sources is
that the direct equivalent method is used to represent primary energy in this fi gure. Bioenergy is accounted for prior to conversion to fuels such as biofuels, electricity and heat. The
other technologies produce primarily (but not entirely) electricity and heat, and they are accounted for based on this secondary energy produced. If primary equivalents based on the
substitution method were used rather than direct equivalent accounting, then energy production from non-biomass RE would be of the order of two to three times larger than shown
here. Ocean energy is not presented here as scenarios so far seldom consider this RE technology. Finally, categories V and above are not included and Category IV is extended to 600
ppm from 570 ppm, because all stabilization scenarios lie below 600 ppm CO2 in 2100, and because the lowest baselines scenarios reach concentration levels of slightly more than
600 ppm by 2100.
Biomax
All Options
No Nuclear
Biomin
No CCS
No RE
Biomax
All Options
No Nuclear
Biomin
No CCS
No RE
XX XX XXX
6
5
4
3
2
1
0
6
5
4
3
2
1
0
6
5
4
3
2
1
0
6
5
4
3
2
1
0
Mitigation Cost [%GDP]
Mitigation Cost [%GDP]
Abatement Costs [%GDP]
Abatement Costs [%GDP]
MERGE ReMIND POLES MERGE ReMIND POLES
Mitigation Costs, World, 550ppm Mitigation Costs, World 400ppm
Figure TS.10.6 | Global mitigation costs (measured in terms of consumption loss) from the ADAM project under varying assumptions regarding technology availability for long-term
stabilization levels of 550 and 400 ppmv CO2eq. ‘All options’ refers to the standard technology portfolio assumptions in the different models, while ‘biomax’ and ‘biomin’ assume
double and half the standard biomass potential of 200 EJ respectively. ‘noccs’ excludes CCS from the mitigation portfolio and ‘nonuke’ and ‘norenew’ constrain the deployment levels
of nuclear and RE to the baseline level, which still potentially means a considerable expansion compared to today. The ‘X’ in the right panel indicates non-attainability of the 400 ppmv
CO2eq level in the case of limited technology options. [Figure 10.11]
this context are: controversy among scientists about potentials at negative
costs; simplifi cation of reality as actors also base their decisions on
other criteria than those refl ected in the curves; economic and technological
uncertainty inherent to predicting the future, including energy
price developments and discount rates; further uncertainty due to strong
aggregation; high sensitivity relative to baseline assumptions and the
entire future generation and transmission portfolio; consideration of
individual measures separately, ignoring interdependencies between
measures applied together or in different order; and, for carbon abatement
curves, high sensitivity to (uncertain) emission factor assumptions.
[10.4.2.1]
Having these criticisms in mind, it is also worth noting that it is very diffi
cult to compare data and fi ndings from RE abatement cost and supply
curves, as very few studies have used a comprehensive and consistent
approach that details their methodologies. Many of the regional and
country studies provide less than 10% abatement of the baseline CO2
emissions over the medium term at abatement costs under approximately
USD2005 100/t CO2. The resulting low-cost abatement potentials
are quite low compared to the reported mitigation potentials of many of
the scenarios reviewed here. [10.4.3.2]
10.5 Cost of commercialization and
deployment
Some RE technologies are broadly competitive with current market
energy prices. Many of the other RE technologies can provide competitive
energy services in certain circumstances, for example, in regions
with favourable resource conditions or that lack the infrastructure for
other low-cost energy supplies. In most regions of the world, however,
policy measures are still required to ensure rapid deployment of many
RE sources. [2.7, 3.8, 4.6, 5.8, 6.7, 7.8, 10.5.1, Figure TS.1.9]
Figures TS.10.11 and TS.10.12 provide additional data on levelized costs
of energy (LCOE), also called levelized unit costs or levelized generation
costs, for selected renewable power technologies and for renewable
heating technologies, respectively. Figure TS.10.13 shows the levelized
■
■
■
I
■
■
■ -----1■
■
-----1 ■
■
I---- ---1 ■
138
Technical Summary Summaries
cost of transport fuels (LCOF). LCOEs capture the full costs (i.e., investment
costs, O&M costs, fuel costs and decommissioning costs) of an
energy conversion installation and allocate these costs over the energy
output during its lifetime, although not taking into account subsidies
or policy incentives. As some RE technologies (e.g., PV, CSP and wind
energy) are characterized by high shares of investment costs relative
to variable costs, the applied discount rate has a prominent infl uence
on the LCOE of these technologies (see Figures TS.10.11, TS.10.12 and
TS.10.13). [10.5.1] The LCOEs are based on literature reviews and represent
the most current cost data available. The respective ranges are
rather broad as the levelized cost of identical technologies can vary
across the globe depending on the RE resource base and local costs of
investment, fi nancing and O&M. Comparison between different technologies
should not be based solely on the cost data provided in Figures TS 1.9,
Figure TS.10.8 | Global RE development projections by source and global primary RE shares by source for a set of four illustrative scenarios. [Figure 10.14]
X X X X
[EJ/yr]
Solar Energy Wind Energy Geothermal Energy Bioenergy Ocean Energy Hydropower
0
100
80
60
40
20
120
140
180
160
2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050
10 % of Global Energy
Supply under IEA-WEO2009-
Demand Projection by 2050
10 % of Global Energy Supply
Under ER Demand Projection
by 2050
Global Renewable Energy Development Projections by Source
IEA-WEO2009-Baseline
ReMIND-RECIPE
MiniCAM-EMF22
ER-2010
Figure TS.10.7 | Mitigation costs from the RECIPE project under varying assumptions regarding technology availability for a long-term stabilization level of 450 ppmv CO2. Option
values of technologies in terms of consumption losses for scenarios in which the option indicated is foregone (CCS) or limited to baseline levels (all other technologies) for the periods
a) 2005 to 2030 and b) 2005 to 2100. Option values are calculated as differences in consumption losses for a scenario in which the use of certain technologies is limited with respect
to the baseline scenario. Note that for WITCH, the generic backstop technology was assumed to be unavailable in the ‘fi x RE’ scenario. [Figure 10.12]
450 ppm C&C
Fix Nuclear
Fix Biomass
No CCS
Fix RE
No CCS, Fix Nuclear
(a) Global, 2005–2030
Consumption Losses [%]
Consumption Losses [%]
0
1
2
3
4
IMACLIM-R ReMIND-R WITCH IMACLIM-R ReMIND-R WITCH
(b) Global, 2005–2100
0
1
2
3
4 : I
..I.l
■■ ■■
I- I139
Summaries Technical Summary
Range graphs: Level of RE Deployment
in 2050 by Scenario and Renewable
Energy, in EJ/yr:
IEA-WEO2009-Baseline
ReMIND-RECIPE
MiniCAM-EMF22
ER-2010
Range
0
50
100
150
200
250
300
350
0-2.5 2.6-5.0 5.1-7.5 7.6-10 10-12.5 12.6-15 15.1-17.5 17.6-20 20.1-22.5 22.6-25 25-50 Over 50
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
World - EJ/yr
Total Technical RE Potential
in EJ/yr for 2050 by
Renewable Energy Source:
Solar
Wind
Geothermal
Hydro
Ocean
Bio energy
X EJ/yr
Technical RE Potential Can Supply the 2007 Primary Energy Demand by a Factor of:
RE potential analysis: Technical RE potentials reported here represent total worldwide and regional potentials based on a review of
studies published before 2009 by Krewitt et al. (2009). They do not deduct any potential that is already being utilized for energy
production. Due to methodological differences and accounting methods among studies, strict comparability of these estimates across
technologies and regions, as well as to primary energy demand, is not possible. Technical RE potential analyses published after 2009
show higher results in some cases but are not included in this figure. However, some RE technologies may compete for land which
could lower the overall RE potential.
Scenario data: IEA WEO 2009 Reference Scenario (International Energy Agency (IEA), 2009; Teske et al., 2010), ReMIND-RECIPE 450ppm
Stabilization Scenario (Luderer et al., 2009), MiniCAM EMF22 1st-best 2.6 W/2 Overshoot Scenario (Calvin et al., 2009), Advanced
Energy
[R]evolution 2010 (Teske et al., 2010)
193 EJ/yr
193 EJ/yr
306 EJ/yr
571 EJ/yr
11,941 EJ/yr
1,335 EJ/yr
5,360 EJ/yr
864 EJ/yr
761 EJ/yr
1,911 EJ/yr
464 EJ/yr
E E E
»
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140
Technical Summary Summaries
OECD Europe - EJ/yr
0
5
10
15
20
25
30
35
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
n
l
r
Developing Asia - EJ/yr
0
30
60
90
120
150
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
r
d
al
r
an
Transition Economies - EJ/yr
0
5
10
15
20
25
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
ar
d
al
n
OECD North America - EJ/yr
0
10
20
30
40
50
60
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
r
l
an
Latin America - EJ/yr
0
5
10
15
20
25
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
an
al
d
r
OECD Pacific - EJ/yr
0
5
10
15
20
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
n
l
r
Africa - EJ/yr
0
5
10
15
20
25
30
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
an
al
d
r
Middle East - EJ/yr
0
5
10
15
20
Direct Solar
Wind
Geothermal
Hydropower
Ocean
Bioenergy
Total
y
an
er
al
d
r
LI
[
1
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141
Summaries Technical Summary
TS 10.11, TS.10.12 and TS.10.13; instead site, project and/or investor-specifi c
conditions should be taken into account. The technology chapters [2.7, 3.8,
4.7, 5.8, 6.7, 7.8] provide useful sensitivities in this respect. [10.5.1]
The cost ranges provided here do not refl ect costs of integration (Chapter
8), external costs or benefi ts (Chapter 9) or costs of policies (Chapter
11). Given suitable conditions, the lower ends of the ranges indicate
that some RE technologies already can compete with traditional forms
at current energy market prices in many regions of the world. [10.5.1]
The supply cost curves presented [10.4.4, Figures 10.23, 10.25, 10.26,
and 10.27] provide additional information about the available resource
base (given as a function of the LCOE associated with harvesting it).
The supply cost curves discussed [10.3.2.1, Figures 10.15–10.17], in
contrast, illustrate the amount of RE that is harnessed (once again as a
function of the associated LCOE) in different regions once specifi c trajectories
for the expansion of RE are followed. In addition, it must be
emphasized that most of the supply cost curves refer to future points in
time (e.g., 2030 or 2050), whereas the LCOE given in the cost sections
of the technology chapters as well as those shown in Figures TS.10.11,
TS.10.12, and TS.10.13 (and in Annex III) refer to current costs. [10.5.1]
Signifi cant advances in RE technologies and associated cost reductions
have been demonstrated over the last decades, though the contribution
and mutual interaction of different drivers (e.g., learning by searching,
learning by doing, learning by using, learning by interacting, upsizing
of technologies, and economies of scale) is not always understood in
detail. [2.7, 3.8, 7.8, 10.5.2]
Figure TS.10.9 | (Preceding pages) Regional breakdown of RE deployment in 2050 for an illustrative set of four scenarios and comparison of the potential deployment to the corresponding
technical potential for different technologies. The selected four illustrative scenarios are a part of the comprehensive survey of 164 scenarios. They represent a span from
a reference scenario (IEA WEO 2009) without specifi c GHG concentration stabilization levels to three scenarios representing different CO2 concentration categories, one of them
(REMind-RECIPE) Category III (440 to 485 ppm) and two of them (MiniCam EMF 22 and ER 2010 Category I (<400 ppm). Of the latter, MiniCam EMF 22 includes nuclear energy and
CCS as mitigation options and allows overshoot to get to the concentration level, while ER 2010 follows an optimistic application path for RE. Transition economies are countries that
changed from a former centrally planned economy to a free market system. [Figure 10.19]
Figure TS.10.10 | Global cumulative CO2 savings between 2010 and 2050 for four illustrative scenarios. The presented ranges mark the high uncertainties regarding the substituted
conventional energy source. While the upper limit assumes a full substitution of high-carbon fossil fuels, the lower limit considers specifi c CO2 emissions of the analyzed scenario itself.
The line in the middle was calculated assuming that RE displaces the specifi c energy mix of a reference scenario. [Figure 10.22]
Global Cumulative CO2 Savings for Different Scenario-Based RE Deployment Paths 2010 up to 2020, 2030 and 2050
[Gt CO2]
IEA-WEO2009-Baseline ReMind-RECIPE MiniCam-EMF22 ER-2010
100
0
200
300
400
500
600
2020 2030 2050 2020 2030 2050 2020 2030 2050 2020 2030 2050
I
-•
142
Technical Summary Summaries
Any efforts to assess future costs by extrapolating historic experience curves
must take into account the uncertainty of learning rates as well as caveats and
knowledge gaps discussed. [10.5.6, 7.8.4.1] As a supplementary approach,
expert elicitations could be used to gather additional information about future
cost reduction potentials, which might be contrasted with the assessments
gained by using learning rates. Furthermore, engineering model analyses to
identify technology improvement potentials could also provide additional
information for developing cost projections. [2.6, 3.7, 4.6, 6.6, 7.7, 10.5.2]
From an empirical point of view, the resulting cost decrease can be
described by experience (or ‘learning’) curves. For a doubling of the
(cumulative) installed capacity, many technologies showed a more or
less constant percentage decrease in the specifi c investment costs (or
in the levelized costs or unit price, depending on the selected cost indicator).
The numerical value describing this improvement is called the
learning rate (LR). A summary of observed learning rates is provided in
Table TS.10.1. [10.5.2]
Figure TS.10.11 | Levelized cost of electricity for commercially available RE technologies at 3, 7 and 10% discount rates. The levelized cost of electricity estimates for all technologies
are based on input data summarized in Annex III and the methodology outlined in Annex II. The lower bound of the levelized cost range is based on the low ends of the ranges of
investment, operations and maintenance (O&M), and (if applicable) feedstock cost and the high ends of the ranges of capacity factors and lifetimes as well as (if applicable) the high
ends of the ranges of conversion effi ciencies and by-product revenue. The higher bound of the levelized cost range is accordingly based on the high end of the ranges of investment,
O&M and (if applicable) feedstock costs and the low end of the ranges of capacity factors and lifetimes as well as (if applicable) the low ends of the ranges of conversion effi ciencies and
by-product revenue. Note that conversion effi ciencies, by-product revenue and lifetimes were in some cases set to standard or average values. For data and supplementary information
see Annex III. (CHP: combined heat and power; ORC: organic Rankine cycle, ICE: internal combustion engine.) [Figure 10.29]
0 10 20 30 40 50 60 70 80 90
Bioenergy (Direct Dedicated & Stoker CHP)
Bioenergy (Co-Firing)
Bioenergy (Small Scale CHP, ORC)
Bioenergy (Small Scale CHP, Steam Turbine)
Bioenergy (Small Scale CHP, Gasification ICE)
Solar PV (Residential Rooftop)
Solar PV (Commercial Rooftop)
Solar PV (Utility Scale, Fixed Tilt)
Solar PV (Utility Scale, 1-Axis)
Concentrating Solar Power
Geothermal Energy (Condensing-Flash Plants)
Geothermal Energy (Binary-Cycle Plants)
Hydropower
Ocean Energy (Tidal Range)
Wind Energy (Onshore, Large Turbines)
Wind Energy (Offshore, Large Turbines)
[UScent2005 /kWh]
3% Discount Rate
7% Discount Rate
10% Discount Rate
I I I
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■
= I I I ■■ I
I I I
I I I I
I I I I I
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143
Summaries Technical Summary
Important potential technological advances and associated cost reductions,
for instance, are expected in (but are not limited to) the following
application fi elds: next-generation biofuels and biorefi neries; advanced
PV and CSP technologies and manufacturing processes; enhanced
geothermal systems; multiple emerging ocean technologies; and
foundation and turbine designs for offshore wind energy. Further cost
reductions for hydropower are likely to be less signifi cant than some of
the other RE technologies, but R&D opportunities exist to make hydropower
projects technically feasible in a wider range of natural conditions
and to improve the technical performance of new and existing projects.
[2.6, 3.7, 4.6, 5.3, 5.7, 5.8, 6.6, 7.7]
An answer to the question whether or not upfront investments in a
specifi c innovative technology are justifi ed cannot be given as long as
the technology is treated in isolation. In a fi rst attempt to clarify this
issue and, especially, to investigate the mutual competition of prospective
climate protection technologies, integrated assessment modellers
have started to model technological learning in an endogenous way.
The results obtained from these modelling comparison exercises indicate
that—in the context of stringent climate goals—upfront investments in
learning technologies can be justifi ed in many cases. [10.5.3.]
However, as the different scenarios considered in Figure TS.10.14 and
other studies clearly show, considerable uncertainty surrounds the exact
volume and timing of these investments. [10.5.4]
The four illustrative scenarios that were analyzed in detail in Section
10.3 span a range of cumulative global decadal investments (in
the power generation sector) ranging from USD2005 1,360 to 5,100
billion (for the decade 2011 to 2020) and from USD2005 1,490 to
7,180 billion (for the decade 2021 to 2030). These numbers allow
the assessment of future market volumes and resulting investment
opportunities. The lower values refer to the IEA World Energy Outlook
2009 Reference Scenario and the higher ones to a scenario that seeks
to stabilize atmospheric CO2 (only) concentration at 450 ppm. The
average annual investments in the reference scenario are slightly
lower than the respective investments reported for 2009. Between
2011and 2020, the higher values of the annual averages of the RE
power generation sector investment approximately correspond to
a three-fold increase in the current global investments in this fi eld.
For the next decade (2021 to 2030), a fi ve-fold increase is projected.
Even the upper level of the annual investments is smaller than 1%
of the world’s GDP. Additionally, increasing the installed capacity of
Figure TS.10.12 | Levelized cost of heat (LCOH) for commercially available RE technologies at 3, 7 and 10% discount rates. The LCOH estimates for all technologies are based on
input data summarized in Annex III and the methodology outlined in Annex II. The lower bound of the levelized cost range is based on the low ends of the ranges of investment,
operations and maintenance (O&M), and (if applicable) feedstock cost and the high ends of the ranges of capacity factors and lifetimes as well as (if applicable) the high ends of the
ranges of conversion effi ciencies and by-product revenue. The higher bound of the levelized cost range is accordingly based on the high end of the ranges of investment, O&M and (if
applicable) feedstock costs and the low end of the ranges of capacity factors and lifetimes as well as (if applicable) the low ends of the ranges of conversion effi ciencies and by-product
revenue. Note that capacity factors and lifetimes were in some cases set to standard or average values. For data and supplementary information see Annex III. (MSW: municipal solid
waste; DHW: domestic hot water.) [Figure 10.30]
0 50 100 150 200
Biomass (Domestic Pellet Heating)
Biomass (MSW, CHP)
Biomass (Steam Turbine, CHP)
Biomass (Anaerobic Digestion, CHP)
Solar Thermal Heating (DHW, China)
Solar Thermal Heating (DHW,
Thermo-Siphon, Combi)
Geothermal (Building Heating)
Geothermal (District Heating)
Geothermal (Greenhouses)
Geothermal (Aquaculture Ponds,
Uncovered)
Geothermal Heat Pumps (GHP)
[USD2005 /GJ]
3% Discount Rate
7% Discount Rate
10% Discount Rate
I f'is
l = j
I ]
_=
]= [
I I:
'
144
Technical Summary Summaries
RE power plants will reduce the amount of fossil and nuclear fuels
that otherwise would be needed in order to meet a given electricity
demand. [10.5.4]
10.6 Social and environmental costs and
benefi ts
Energy extraction, conversion and use cause signifi cant environmental
impacts and external costs. Although replacing fossil fuel-based
energy with RE often can reduce GHG emissions and also to some
extent other environmental impacts and external costs, RE technologies
can also have environmental impacts and external costs
themselves, depending on the energy source and technology. These
impacts and costs should be considered if a comprehensive cost
assessment is required. [10.6.2]
Figure TS.10.15 shows the large uncertainty ranges of two dominant
external cost components, namely climate- and health-related external
costs. Small-scale biomass fi red CHP plants cause relatively high
external costs due to health effects via particulate emissions. Offshore
wind energy seems to cause the smallest external cost. External cost
estimates for nuclear power are not reported here because the character
and assessment of external costs and risk from release of radionuclides
due to low-probability accidents or due to leakages from waste
repositories in a distant future are very different, for example, from climate
change and air pollution, which are practically unavoidable. Those
external impacts related to nuclear power can be, however, considered
by discussion and judgment in the society. Accident risks in terms of
fatalities due to various energy production chains (e.g., coal, oil, gas
and hydro) are generally higher in non-OECD countries than in OECD
countries. [10.6.3, 9.3.4.7]
As only external costs of individual technologies are shown in Figure
TS.10.15, benefi ts can be derived when assuming that one technology
replaces another one. RE sources and the technologies using them for
electricity generation have mostly lower external costs per produced
electricity than fossil fuel-based technologies. However, case-specifi c
considerations are needed as there can also be exceptions. [10.6.3]
There are, however, considerable uncertainties in the assessment and
valuation of external impacts of energy sources. The assessment of
physical, biological and health damages includes considerable uncertainty
and the estimates are based typically on calculational models,
the results of which are often diffi cult to validate. The damages or
changes seldom have market values that could be used in cost estimation,
thus indirect information or other approaches must be used for
damage valuation. Further, many of the damages will take place far
in the future or in societies very different from those benefi ting from
the use of the considered energy production, which complicates the
Figure TS.10.13 | Levelized cost of fuels (LCOF) for commercially available biomass conversion technologies at 3, 7 and 10% discount rates. LCOF estimates for all technologies
are based on input data summarized in Annex III and the methodology outlined in Annex II. The lower bound of the levelized cost range is based on the low ends of the ranges of
investment, O&M and feedstock cost. The higher bound of the levelized cost range is accordingly based on the high end of the ranges of investment, O&M and feedstock costs. Note
that conversion effi ciencies, by-product revenue, capacity factors and lifetimes were set to average values. For data and supplementary information see Annex III. (HHV: higher heating
value.) [Figure 10.31]
[USD/GJHHV]
0 10 20 30 40 50 60
Ethanol - Sugarcane
Ethanol - Corn
Ethanol - Wheat
Biodiesel - Soy Oil
Biodiesel - Palm Oil
3% Discount Rate
7% Discount Rate
10% Discount Rate
■
l ■
■
I
145
Summaries Technical Summary
Table TS.10.1 | Observed learning rates for various energy supply technologies. Note that values cited by older publications are less reliable as these refer to shorter time periods.
[Table 10.10]
Technology Source Country / region Period
Learning
rate (%)
Performance measure
Onshore wind
Neij, 1997 Denmark 1982-1995 4 Price of wind turbine (USD/kW)
Mackay and Probert, 1998 USA 1981-1996 14 Price of wind turbine (USD/kW)
Neij, 1999 Denmark 1982-1997 8 Price of wind turbine (USD/kW)
Durstewitz, 1999 Germany 1990-1998 8 Price of wind turbine (USD/kW)
IEA, 2000 USA 1985-1994 32 Electricity production cost (USD/kWh)
IEA, 2000 EU 1980-1995 18 Electricity production cost (USD/kWh)
Kouvaritakis et al., 2000 OECD 1981-1995 17 Price of wind turbine (USD/kW)
Neij, 2003 Denmark 1982-1997 8 Price of wind turbine (USD/kW)
Junginger et al., 2005a Spain 1990-2001 15 Turnkey investment costs (EUR/kW)
Junginger et al., 2005a UK 1992-2001 19 Turnkey investment costs (EUR/kW)
Söderholm and Sundqvist,
2007
Germany, UK,
Denmark
1986-2000 5 Turnkey investment costs (EUR/kW)
Neij, 2008 Denmark 1981-2000 17 Electricity production cost (USD/kWh)
Kahouli-Brahmi, 2009 Global 1979-1997 17 Investment costs (USD/kW)
Nemet, 2009 Global 1981-2004 11 Investment costs (USD/kW)
Wiser and Bolinger, 2010 Global 1982-2009 9 Investment costs (USD/kW)
Offshore wind
Isles, 2006 8 EU countries 1991-2006 3 Investment cost of wind farms (USD/kW)
Photovoltaics (PV)
Harmon, 2000 Global 1968-1998 20 Price PV module (USD/Wpeak)
IEA, 2000 EU 1976-1996 21 Price PV module (USD/Wpeak)
Williams, 2002 Global 1976-2002 20 Price PV module (USD/Wpeak)
ECN, 2004 EU 1976-2001 20-23 Price PV module (USD/Wpeak)
ECN, 2004 Germany 1992-2001 22 Price of balance of system costs
van Sark et al., 2007 Global 1976-2006 21 Price PV module (USD/Wpeak)
Kruck and Eltrop, 2007 Germany 1977-2005 13 Price PV module (EUR/Wpeak)
Kruck and Eltrop, 2007 Germany 1999-2005 26 Price of balance of system costs
Nemet, 2009 Global 1976-2006 15-21 Price PV module (USD/Wpeak)
Concentrating Solar Power (CSP)
Enermodal, 1999 USA 1984-1998 8-15 Plant investment cost (USD/kW)
Biomass
IEA, 2000 EU 1980-1995 15 Electricity production cost (USD/kWh)
Goldemberg et al., 2004 Brazil 1985-2002 29 Prices for ethanol fuel (USD/m3)
Junginger et al., 2005b Sweden, Finland 1975-2003 15 Forest wood chip prices (EUR/GJ)
Junginger et al., 2006 Denmark 1984-1991 15 Biogas production costs (EUR/Nm3)
Junginger et al., 2006 Sweden 1990-2002 8-9 Biomass CHP power (EUR/kWh)
Junginger et al., 2006 Denmark 1984-2001 0-15 Biogas production costs (EUR/Nm3)
Junginger et al., 2006 Denmark 1984-1998 12 Biogas plants (€/m3 biogas/day)
Van den Wall Bake et al., 2009 Brazil 1975-2003 19 Ethanol from sugarcane (USD/m3)
Goldemberg et al., 2004 Brazil 1980-1985 7 Ethanol from sugarcane (USD/m3)
Goldemberg et al., 2004 Brazil 1985-2002 29 Ethanol from sugarcane (USD/m3)
Van den Wall Bake et al., 2009 Brazil 1975-2003 20 Ethanol from sugarcane (USD/m3)
Hettinga et al., 2009 USA 1983-2005 18 Ethanol from corn (USD/m3)
Hettinga et al., 2009 USA 1975-2005 45 Corn production costs (USD/t corn)
Van den Wall Bake et al., 2009 Brazil 1975-2003 32 Sugarcane production costs (USD/t)
146
Technical Summary Summaries
Figure TS.10.14 | Illustrative global decadal investments (in billion USD2005)
needed in order to achieve ambitious climate protection goals: (b) MiniCAM-EMF22
(fi rst-best 2.6 W/m2 overshoot scenario, nuclear and carbon capture technologies are permitted);
(c) ER-2010 (450 ppm CO2eq, nuclear and carbon capture technologies are not
permitted); and (d) ReMIND-RECIPE (450 ppm CO2, nuclear power plants and carbon capture
technologies are permitted). Compared to the other scenarios, the PV share is high
in (d) as concentrating solar power has not been considered. For comparison, (a) shows
the IEA-WEO2009-Baseline (baseline scenario without climate protection). Sources: (a)
IEA (2009); (b) Calvin et al. (2009); (c) Teske et al. (2010); and (d) Luderer et al. (2009).
2011-2020 2021-2030 2031-2040 2041-2050
2011-2020 2021-2030 2031-2040 2041-2050
2011-2020 2021-2030 2031-2040 2041-2050
2011-2020 2021-2030 2031-2040 2041-2050
0
100
200
300
400
500
Wind Turbine
Solar Thermal
Power Plant
PV Power Plant
Ocean Energy
Power Plant
Hydro
Geothermal
Power Plant
Biomass and Waste
Power Plant
0
200
400
600
800
1000
1,200
0
500
1,000
1,500
2,000
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Decadal Investments
[Billion USD2005 ]
Decadal Investments
[Billion USD2005 ]
Decadal Investments
[Billion USD2005 ]
Decadal Investments
[Billion USD2005 ]
(d)
(c)
(b)
(a)
considerations. These factors contribute to the uncertainty of external costs.
[10.6.5]
However, the knowledge about external costs and benefi ts due to RE sources
can provide some guidance for society to select best alternatives and to steer
the energy system towards overall effi ciency and high welfare gains. [10.6.5]
11. Policy, Financing and
Implementation
11.1 Introduction
RE capacity is increasing rapidly around the world, but a number of
barriers continue to hold back further advances. Therefore, if RE is to
contribute substantially to the mitigation of climate change, and to do
so quickly, various forms of economic support policies as well as policies
to create an enabling environment are likely to be required. [11.1]
RE policies have promoted an increase in RE shares by helping to
overcome various barriers that impede technology development
and deployment of RE. RE policies might be enacted at all levels
of government—from local to state/provincial to national to international—
and range from basic R&D for technology development
through to support for installed RE systems or the electricity, heat or
fuels they produce. In some countries, regulatory agencies and public
utilities may be given responsibility for, or on their own initiative,
design and implement support mechanisms for RE. Nongovernmental
actors, such as international agencies and development banks, also
have important roles to play. [1.4, 11.1, 11.4, 11.5]
RE may be measured by additional qualifi ers such as time and reliability
of delivery (availability) and other metrics related to RE’s integration into
networks. There is also much that governments and other actors can do
to create an environment conducive for RE deployment. [11.1, 11.6]
11.1.1 The rationale of renewable energy-specifi c
policies in addition to climate change policies
Renewable energies can provide a host of benefi ts to society. Some RE
technologies are broadly competitive with current market energy prices.
.----· -· ■
■ ■ ■----·
% ·- ---·
•---■
-■-
-■-
-■-
-■-
-■-
-■-
-■-
147
Summaries Technical Summary
Of the other RE technologies that are not yet broadly competitive, many
can provide competitive energy services in certain circumstances. In
most regions of the world, however, policy measures are still required
to facilitate an increasing deployment of RE. [11.1, 10.5]
Climate policies (carbon taxes, emissions trading or regulatory policies)
decrease the relative costs of low-carbon technologies compared
to carbon-intensive technologies. It is questionable, however, whether
climate policies (e.g., carbon pricing) alone are capable of promoting RE
at suffi cient levels to meet the broader environmental, economic and
social objectives related to RE. [11.1.1]
Two separate market failures create the rationale for the additional
support of innovative RE technologies that have high potential for
technological development, even if an emission market (or GHG pricing
policy in general) exists. The fi rst market failure refers to the external
cost of GHG emissions. The second market failure is in the fi eld of innovation:
if fi rms underestimate the future benefi ts of investments into
learning RE technologies or if they cannot appropriate these benefi ts,
they will invest less than is optimal from a macroeconomic perspective.
In addition to GHG pricing policies, RE-specifi c policies may be
appropriate from an economic point of view if the related opportunities
for technological development are to be addressed (or if the goals
beyond climate change mitigation are pursued). Potentially adverse
consequences such as lock-in, carbon leakage and rebound effects
should be taken into account in the design of a portfolio of policies.
[11.1.1, 11.5.7.3]
11.1.2 Policy timing and strength
The timing, strength and level of coordination of R&D versus deployment
policies have implications for the effi ciency and effectiveness of the policies,
and for the total cost to society in three main ways: 1) whether a
country promotes RE immediately or waits until costs have declined further;
2) once a country has decided to support RE, the timing, strength
and coordination of when R&D policies give way to deployment policies;
and 3) the cost and benefi t of accelerated versus slower ‘market demand’
policy implementation. With regard to the fi rst, in order to achieve full
competitiveness with fossil fuel technologies, signifi cant upfront investments
in RE will be required until the break-even point is achieved.
When those investments should be made depends on the goal. If the
Health
Climate Change
Renewable Energy
(B) Solar Thermal
(B) Geothermal
(B) Wind 2.5 MW Offshore
(B) Wind 1.5 MW Onshore
(C) Wind Offshore
(B) Hydro 300 kW
(B) PV (2030)
(B) PV (2000)
(C) PV Southern Europe
(C) Biomass CHP 6 MWel
(D) Biomass Grate Boiler ESP 5
and 10 MW Fuel
0.01 0.1 1 10
External Costs [UScent/kWh]
Coal Fired Plants
(A) Existing US Plants
(B) Coal Comb.C n=46%
(B) Coal n=43%
(B) Lignite Comb.C n=48%
(B) Lignite n=40%
(C) Hard Coal 800 MW
(C) Hard Coal Postcom. CCS
(C) Lignite Oxyfuel CCS
Natural Gas Fired Plants
(A) Existing US Plants
(B) Natural Gas n=58%
(C) Natural Gas Comb.C
(C) Natural Gas Postcom.CCS
Figure TS.10.15 | Illustration of external costs due to the lifecycle of electricity production based on RE and fossil energy. Note the logarithmic scale of the fi gure. The black lines
indicate the range of the external cost due to climate change and the red lines indicate the range of the external costs due to air pollutant health effects. External costs due to climate
change mainly dominate in fossil energy if not equipped with CCS. Comb.C: Combined Cycle; Postcom: Post-Combustion; η: effi ciency factor. The results are based on four studies
having different assumptions (A–D). The uncertainty for the external costs of health impacts is assumed to be a factor of three. [Figure 10.36]
148
Technical Summary Summaries
international community aims to stabilize global temperature increases
at 2°C, then investments in low-carbon technologies must start almost
immediately.
11.2 Current trends: Policies, fi nancing and
investment
An increasing number and variety of RE policies have driven substantial
growth in RE technologies in recent years. Until the early 1990s, few
countries had enacted policies to promote RE. Since then, and particularly
since the early- to mid-2000s, policies have begun to emerge in a growing
number of countries at the municipal, state/provincial and national
levels, as well as internationally (see Figure TS.11.1). [1.4, 11.1, 11.2.1,
11.4, 11.5]
Initially, most policies adopted were in developed countries, but an
increasing number of developing countries have enacted policy frameworks
at various levels of government to promote RE since the late
1990s and early 2000s. Of those countries with RE electricity policies
by early 2010, approximately half were developing countries from
every region of the world. [11.2.1]
Most countries with RE policies have more than one type of mechanism
in place, and many existing policies and targets have been strengthened
over time. Beyond national policies, the number of international
policies and partnerships is increasing. Several hundred city and local
governments around the world have also established goals or enacted
renewable promotion policies and other mechanisms to spur local RE
deployment. [11.2.1]
The focus of RE policies is shifting from a concentration almost entirely
on electricity to include the heating/cooling and transportation sectors.
These trends are matched by increasing success in the development of
a range of RE technologies and their manufacture and implementation
(see Chapters 2 through 7), as well as by a rapid increase in annual
investment in RE and a diversifi cation of fi nancing institutions, particularly
since 2004/2005. [11.2.2]
In response to the increasingly supportive policy environment, the
overall RE sector globally has seen a signifi cant rise in the level of
investment since 2004-2005. Financing occurs over what is known as
the ‘continuum’ or stages of technology development. The fi ve segments
of the continuum are: 1) R&D; 2) technology development and
commercialization; 3) equipment manufacture and sales; 4) project
construction; and 5) the refi nancing and sale of companies, largely
through mergers and acquisitions. Financing has been increasing over
time in each of these stages, providing indications of the RE sector’s current
and expected growth, as follows: [11.2.2]
• Trends in (1) R&D funding and (2) technology investment are indicators
of the long- to mid-term expectations for the sector—investments
are being made that will begin to pay off in several years’ time, once
the technology is fully commercialized. [11.2.2.2, 11.2.2.3]
• Trends in (3) manufacturing and sales investment are an indicator of
near-term expectations for the sector—essentially, that the growth in
market demand will continue. [11.2.2.4]
• Trends in (4) construction investment are an indicator of current
sector activity, including the extent to which internalizing costs associated
with GHGs can result in new fi nancial fl ows to RE projects.
[11.2.2.5]
• Trends in (5) industry mergers and acquisitions can refl ect the overall
maturity of the sector, and increasing refi nancing activity over
time indicates that larger, more conventional investors are entering
the sector, buying up successful early investments from fi rst movers.
[11.2.2.6]
11.3 Key drivers, opportunities and benefi ts
Renewable energy can provide a host of benefi ts to society. In addition
to the reduction of CO2 emissions, governments have enacted RE policies
to meet any number of objectives, including the creation of local environmental
and health benefi ts; facilitation of energy access, particularly
for rural areas; advancement of energy security goals by diversifying the
portfolio of energy technologies and resources; and improving social and
economic development through potential employment opportunities and
economic growth. [11.3.1–11.3.4]
The relative importance of the drivers for RE differ from country to country,
and may vary over time. Energy access has been described as the primary
driver in developing countries whereas energy security and environmental
concerns have been most important in developed countries. [11.3]
11.4 Barriers to renewable energy
policymaking, implementation and
fi nancing
RE policies have promoted an increase in RE shares by helping to
overcome various barriers that impede technology development and
deployment of RE. Barriers specifi c to RE policymaking, to implementation
and to fi nancing (e.g., market failures) may further impede
deployment of RE. [1.4, 11.4]
Barriers to making and enacting policy include a lack of information
and awareness about RE resources, technologies and policy options;
lack of understanding about best policy design or how to undertake
energy transitions; diffi culties associated with quantifying and internalizing
external costs and benefi ts; and lock-in to existing technologies
and policies. [11.4.1]
149
Summaries Technical Summary
Figure TS.11.1 | Countries with at least one RE target and/or at least one RE-specifi c policy, in mid-2005 and in early 2011. This fi gure includes only national-level targets and policies
(not municipal or state/provincial) and is not necessarily all-inclusive. [Figure 11.1]
2005
Early 2011
Countries with at least one RE-specific Policy and at least one RE Target
Countries with at least one RE-specific Policy
Countries with at least one RE Target
■■ Countries with neither RE-specific Policies nor RE Targets
7 -e■
□
150
Technical Summary Summaries
Barriers related to policy implementation include confl icts with existing
regulations; lack of skilled workers; and/or lack of institutional capacity
to implement RE policies. [11.4.2]
Barriers to fi nancing include a lack of awareness among fi nanciers and
lack of timely and appropriate information; issues related to fi nancial
structure and project scale; issues related to limited track records; and, in
some countries, institutional weakness, including imperfect capital markets
and insuffi cient access to affordable fi nancing, all of which increase
perceived risk and thus increase costs and/or make it more diffi cult to
obtain RE project fi nancing. Most importantly, many RE technologies are
not economically competitive with current energy market prices, making
them fi nancially unprofi table for investors absent various forms of policy
support, and thereby restricting investment capital. [11.4.3]
11.5 Experience with and assessment of
policy options
Many policy options are available to support RE technologies, from their
infant stages to demonstration and pre-commercialization, and through
to maturity and wide-scale deployment. These include government R&D
policies (supply-push) for advancing RE technologies, and deployment
policies (demand-pull) that aim to create a market for RE technologies.
Policies could be categorized in a variety of ways and no globally-agreed
list of RE policy options or groupings exists. For the purpose of simplifi
cation, R&D and deployment policies have been organized within the
following categories [11.5]:
• Fiscal incentive: actors (individuals, households, companies) are
allowed a reduction of their contribution to the public treasury via
income or other taxes or are provided payments from the public
treasury in the form of rebates or grants.
• Public fi nance: public support for which a fi nancial return is expected
(loans, equity) or fi nancial liability is incurred (guarantee); and
• Regulation: rule to guide or control conduct of those to whom it
applies.
Although targets are a central component of policies, policies in place
may not need specifi c targets to be successful. Further, targets without
policies to deliver them are unlikely to be met. [11.5]
The success of policy instruments is determined by how well they are
able to achieve various objectives or criteria, including:
• Effectiveness: extent to which intended objectives are met;
• Effi ciency: ratio of outcomes to inputs, or RE targets realized for
economic resources spent;
• Equity: the incidence and distributional consequences of a policy;
and
• Institutional feasibility: the extent to which a policy instrument is
likely to be viewed as legitimate, gain acceptance, and be adopted
and implemented, including the ability to implement a policy once it
has been designed and adopted. [11.5.1]
Most literature focuses on effectiveness and effi ciency of policies.
Elements of specifi c policy options make them more or less apt to
achieve the various criteria, and how these policies are designed and
implemented can also determine how well they meet these criteria. The
selection of policies and details of their design ultimately will depend on
the goals and priorities of policymakers. [11.5.1]
11.5.1 Research and development policies for
renewable energy
R&D, innovation, diffusion and deployment of new low-carbon technologies
create benefi ts to society beyond those captured by the innovator,
resulting in under-investment in such efforts. Thus, government R&D
can play an important role in advancing RE technologies. Not all countries
can afford to support R&D with public funds, but in the majority
of countries where some level of support is possible, public R&D for
RE enhances the performance of nascent technologies so that they can
meet the demands of initial adopters. Public R&D also improves existing
technologies that already function in commercial environments. [11.5.2]
Government R&D policies include fi scal incentives, such as academic
R&D funding, grants, prizes, tax credits, and use of public research centres;
as well as public fi nance, such as soft or convertible loans, public
equity stakes, and public venture capital funds. Investments falling under
the rubric of R&D span a wide variety of activities along the technology
development lifecycle, from RE resource mapping to improvements in
commercial RE technologies. [11.5.2]
The success of R&D policies depends on a number of factors, some of
which can be clearly determined, and others which are debated in the
literature. Successful outcomes from R&D programmes are not solely
related to the total amount of funding allocated, but are also related
to the consistency of funding from year to year. On-off operations in
R&D are detrimental to technical learning, and learning and cost reductions
depend on continuity, commitment and organization of effort, and
where and how funds are directed, as much as they rely on the scale
of effort. In the literature, there is some debate as to the most successful
approach to R&D policy in terms of timing: bricolage (progress
via research aiming at incremental improvements) versus breakthrough
(radical technological advances) with arguments favouring either option
or a combination of both. Experience has shown that it is important that
subsidies for R&D (and beyond) are designed to have an ‘exit-strategy’
151
Summaries Technical Summary
whereby the subsidies are progressively phased out as the technology
commercializes, leaving a functioning and sustainable sector in place.
[11.5.2.3]
One of the most robust fi ndings, from both the theoretical literature
and technology case studies, is that R&D investments are most effective
when complemented by other policy instruments—particularly, but
not limited to, policies that simultaneously enhance demand for new
RE technologies. Relatively early deployment policies in a technology’s
development accelerate learning, whether learning through R&D or
learning through utilization (as a result of manufacture) and cost reduction.
Together, R&D and deployment policies create a positive feedback
cycle, inducing private sector investment in R&D (See Figure TS.11.2).
[11.5.2.4]
11.5.2 Policies for deployment
Policy mechanisms enacted specifi cally to promote deployment of
RE are varied and can apply to all energy sectors. They include fi scal
incentives (grants, energy production payments, rebates, tax credits,
reductions and exemptions, variable or accelerated depreciation); public
fi nance (equity investment, guarantees, loans, public procurement); and
regulations (quotas, tendering/bidding, FITs, green labelling and green
energy purchasing, net metering, priority or guaranteed access, priority
dispatch). While regulations and their impacts vary quite signifi cantly
from one end-use sector to another, fi scal incentives and public fi nance
apply generally to all sectors. [11.5.3.1]
Fiscal incentives can reduce the costs and risks of investing in RE by lowering
the upfront investment costs associated with installation, reducing
the cost of production, or increasing the payment received for RE generated.
Fiscal incentives also compensate for the various market failures
that leave RE at a competitive disadvantage compared to fossil fuels
and nuclear energy, and help to reduce the fi nancial burden of investing
in RE. [11.5.3.1]
Fiscal incentives tend to be most effective when combined with other
types of policies. Incentives that subsidize production are generally
preferable to investment subsidies because they promote the desired
outcome—energy generation. However, policies must be tailored to
particular technologies and stages of maturation, and investment
subsidies can be helpful when a technology is still relatively expensive
or when the technology is applied at a small scale (e.g., small
Market
Development
Industry
Development
Technology
Development
Higher performance,
cost reductions,
enhanced applications
result in more and
higher quality RE
technologies and
deployment
More and higher quality RE
technologies and deployment result
in more R&D, innovation and
technological progress
More and higher quality RE
technologies and deployment
result in enlarged markets and
open new sectors
Enlarged markets and
new sectors stimulate
innovators and investors
More R&D, innovation and
technological progress result in
higher performance, cost
reductions, enhanced applications
Market
Cycle
Technology
Cycle
Figure TS.11.2 | The mutually-reinforcing cycles of technology development and market deployment drive down technology costs. [Figure 11.5]
152
Technical Summary Summaries
rooftop solar systems), particularly if they are paired with technology
standards and certifi cation to ensure minimum quality of systems
and installation. Experience with wind energy policies suggests that
production payments and rebates may be preferable to tax credits
because the benefi ts of payments and rebates are equal for people of
all income levels and thus promote broader investment and use. Also,
because they are generally provided at or near the time of purchase or
production, they result in more even growth over time (rather than the
tendency to invest in most capacity toward the end of a tax period).
Tax-based incentives have historically tended to be used to promote only
the most mature and cheapest available technologies. Generally, tax
credits work best in countries where there are numerous profi table, taxpaying
private sector fi rms that are in a position to take advantage of
them. [11.5.3.1]
Public fi nance mechanisms have a twofold objective: to directly mobilize
or leverage commercial investment into RE projects, and to indirectly
create scaled-up and commercially sustainable markets for these technologies.
In addition to the more traditional public fi nance policies such
as soft loans and guarantees, a number of innovative mechanisms are
emerging at various levels of government, including the municipal level.
These include fi nancing of RE projects through long-term loans to property
owners that allow repayment to be matched with energy savings
(for example, Property Assessed Clean Energy in California), and the
‘recycling’ of government funds for multiple purposes (e.g., using public
funds saved through energy effi ciency improvements for RE projects).
[11.5.3.2]
Public procurement of RE technologies and energy supplies is a frequently
cited but not often utilized mechanism to stimulate the market
for RE. Governments can support RE development by making commitments
to purchase RE for their own facilities or encouraging clean
energy options for consumers. The potential of this mechanism is signifi -
cant: in many nations, governments are the largest consumer of energy,
and their energy purchases represent the largest components of public
expenditures. [11.5.3.2]
Regulatory policies include quantity- and price-driven policies such
as quotas and FITs; quality aspects and incentives; and access instruments
such as net metering. Quantity-driven policies set the quantity
to be achieved and allow the market to determine the price, whereas
price-driven policies set the price and allow the market to determine
quantity. Quantity-driven policies can be used in all three end-use sectors
in the form of obligations or mandates. Quality incentives include
green energy purchasing and green labelling programmes (occasionally
mandated by governments, but not always), which provide information
to consumers about the quality of energy products to enable consumers
to make voluntary decisions and drive demand for RE. [11.5.3.3]
Policies for deployment: Electricity
To date, far more policies have been enacted to promote RE for electricity
generation than for heating and cooling or transport. These include
fi scal incentives and public fi nance to promote investment in and
generation of RE electricity, as well as a variety of electricity-specifi c
regulatory policies. Although governments use a variety of policy types
to promote RE electricity, the most common policies in use are FITs and
quotas or Renewable Portfolio Standards (RPS). [11.5.4]
There is a wealth of literature assessing quantity-based (quotas, RPS;
and tendering/bidding policies) and price-based (fi xed-price and
premium-price FITs) policies, primarily quotas and FITs, and with a
focus on effectiveness and effi ciency criteria. A number of historical
studies, including those carried out for the European Commission,
have concluded that ‘well-designed’ and ‘well–implemented’ FITs
have to date been the most effi cient (defi ned as comparison of total
support received and generation cost) and effective (ability to deliver
an increase in the share of RE electricity consumed) support policies
for promoting RE electricity. [11.5.4]
One main reason for the success of well-implemented FITs is that they
usually guarantee high investment security due to the combination of
long-term fi xed-price payments, network connection, and guaranteed
grid access for all generation. Well-designed FITs have encouraged both
technological and geographic diversity, and have been found to be
more suitable for promoting projects of varying sizes. The success of FIT
policies depends on the details. The most effective and effi cient policies
have included most or all of the following elements [11.5.4.3]:
• Utility purchase obligation;
• Priority access and dispatch;
• Tariffs based on cost of generation and differentiated by technology
type and project size, with carefully calculated starting values;
• Regular long-term design evaluations and short-term payment level
adjustments, with incremental adjustments built into law in order to
refl ect changes in technologies and the marketplace, to encourage
innovation and technological change, and to control costs;
• Tariffs for all potential generators, including utilities;
• Tariffs guaranteed for a long enough time period to ensure an adequate
rate of return;
• Integration of costs into the rate base and shared equally across
country or region;
• Clear connection standards and procedures to allocate costs for
transmission and distribution;
• Streamlined administrative and application processes; and
• Attention to preferred exempted groups, for example, major users
on competitiveness grounds or low-income and other vulnerable
customers.
Experiences in several countries demonstrate that the effectiveness
of quota schemes can be high and compliance levels achieved if RE
certifi cates are delivered under well-designed policies with long-term
contracts that mute (if not eliminate) price volatility and reduce risk.
However, they have been found to benefi t the most mature, leastcost
technologies. This effect can be addressed in the design of the
153
Summaries Technical Summary
policy if different RE options are distinguished or are paired with
other incentives. The most effective and effi cient quantity-based
mechanisms have included most if not all of the following elements,
particularly those that help to minimize risk [11.5.4.3]:
• Application to large segment of the market (quota only);
• Clearly defi ned eligibility rules including eligible resources and
actors (applies to quotas and tendering/bidding);
• Well-balanced supply-demand conditions with a clear focus on new
capacities—quotas should exceed existing supply but be achievable
at reasonable cost (quota only);
• Long-term contracts/specifi c purchase obligations and end dates,
and no time gaps between one quota and the next (quota only);
• Adequate penalties for non-compliance, and adequate enforcement
(applies to quotas and tendering/bidding);
• Long-term targets, of at least 10 years (quota only);
• Technology-specifi c bands or carve-outs to provide differentiated
support (applies to quotas and tendering/bidding); and
• Minimum payments to enable adequate return and fi nancing
(applies to quotas and tendering/bidding).
Net metering enables small producers to ‘sell’ into the grid, at the retail
rate, any renewable electricity that they generate in excess of their total
demand in real time as long as that excess generation is compensated
for by excess customer load at other times during the designated netting
period. It is considered a low-cost, easily administered tool for motivating
customers to invest in small-scale, distributed power and to feed it
into the grid, while also benefi ting providers by improving load factors
if RE electricity is produced during peak demand periods. On its own,
however, it is generally insuffi cient to stimulate signifi cant growth of
less competitive technologies like PV at least where generation costs are
higher than retail prices. [11.5.4]
Policies for deployment: Heating and cooling
An increasing number of governments are adopting incentives and mandates
to advance RE heating and cooling (H/C) technologies. Support for
RE H/C presents policymakers with a unique challenge due to the often
distributed nature of heat generation. Heating and cooling services can
be provided via small- to medium-scale installations that service a single
dwelling, or can be used in large-scale applications to provide district
heating and cooling. Policy instruments for both RE heating (RE-H) and
cooling (RE-C) need to specifi cally address the more heterogeneous
characteristics of resources, including their wide range in scale, varying
ability to deliver different levels of temperature, widely distributed
demand, relationship to heat load, variability of use, and the absence of
a central delivery or trading mechanism. [11.5.5]
The number of policies to support RE sources of heating and cooling
has increased in recent years, resulting in increasing generation of RE
H/C. However, a majority of support mechanisms have been focused on
RE-H. Policies in place to promote RE-H include fi scal incentives such as
rebates and grants, tax reductions and tax credits; public fi nance policies
like loans; regulations such as use obligations; and educational efforts.
[11.5.5.1–11.5.5.3, 11.6]
To date, fi scal incentives have been the prevalent policy in use, with grants
being the most commonly applied. Tax credits available after the installation
of a RE-H system (i.e., ex-post) may be logistically advantageous over, for
example, grants requiring pre-approval before installation, though there is
limited experience with this option. Regulatory mechanisms like use obligations
and quotas have attracted increased interest for their potential to
encourage growth of RE-H independent of public budgets, though there has
been little experience with these policies to date. [11.5.5]
Similar to RE electricity and RE transport, RE H/C policies will be better
suited to particular circumstances/locations if, in their design, consideration
is given to the state of maturity of the particular technology, of the existing
markets and of the existing supply chains. Production incentives are considered
be more effective for larger H/C systems, such as district heating grids,
than they are for smaller, distributed onsite H/C generation installations
for which there are few cost-effective metering or monitoring procedures.
[11.5.5]
Though there are some examples of policies supporting RE-C technologies,
in general policy aiming to drive deployment of RE-C solely is considerably
less well-developed than that for RE-H. Many of the mechanisms described
in the above paragraphs could also be applied to RE-C, generally with similar
advantages and disadvantages. The lack of experience with deployment
policies for RE-C is probably linked to the early levels of technological development
of many RE-C technologies. R&D support as well as policy support
to develop the early market and supply chains may be of particular importance
for increasing the deployment of RE-C technologies in the near future.
[11.5.5.4]
Policies for deployment: Transportation
A range of policies has been implemented to support the deployment of RE
for transport, though the vast majority of these policies and related experiences
have been specifi c to biofuels. Biofuel support policies aim to promote
domestic consumption via fi scal incentives (e.g., tax exemptions for biofuel
at the pump) or regulations (e.g., blending mandates), or to promote
domestic production via public fi nance (e.g., loans) for production facilities,
via feedstock support or tax incentives (e.g., excise tax exemptions). Most
commonly, governments enact a combination of policies. [11.5.6]
Tax incentives are commonly used to support biofuels because they change
their cost-competitiveness relative to fossil fuels. They can be installed along
the whole biofuel value chain, but are most commonly provided to either
biofuel producers (e.g., excise tax exemptions/credits) and/or to end consumers
(e.g., tax reductions for biofuels at the pump). [11.5.6]
However, several European and other G8+5 countries have begun
gradually shifting from the use of tax breaks for biofuels to blending
mandates. It is diffi cult to assess the level of support under biofuel
mandates because prices implied by these obligations are generally
154
Technical Summary Summaries
not public (in contrast to the electricity sector, for example). While
mandates are key drivers in the development and growth of most
modern biofuels industries, they are found to be less appropriate for
the promotion of specifi c types of biofuel because fuel suppliers tend
to blend low-cost biofuels. By nature, mandates need to be carefully
designed and accompanied by further requirements in order to
reach a broader level of distributional equity and to minimize potential
negative social and environmental impacts. Those countries with
the highest share of biofuels in transport fuel consumption have had
hybrid systems that combine mandates (including penalties) with
fi scal incentives (tax exemptions foremost). [11.5.6]
Synthesis
Some policy elements have been shown to be more effective and
effi cient in rapidly increasing RE deployment and enabling governments
and society to achieve specifi c targets. The details of policy
design and implementation can be as important in determining
effectiveness and effi ciency as the specifi c policies that are used.
Key policy elements include [11.5.7]:
• Adequate value derived from subsidies, FITs, etc. to cover cost
such that investors are able to recover their investment at a rate
of return that matches their risk.
• Guaranteed access to networks and markets or at a minimum
clearly defi ned exceptions to that guaranteed access.
• Long-term contracts to reduce risk thereby reducing fi nancing
costs.
• Provisions that account for diversity of technologies and applications.
RE technologies are at varying levels of maturity and
with different characteristics, often facing very different barriers.
Multiple RE sources and technologies may be needed to mitigate
climate change, and some that are currently less mature and/or
more costly than others could play a signifi cant role in the future
in meeting energy needs and reducing GHG emissions.
• Incentives that decline predictably over time as technologies
and/or markets advance.
• Policy that is transparent and easily accessible so that actors
can understand the policy and how it works, as well as what
is required to enter the market and/or to be in compliance.
Also includes longer-term transparency of policy goals, such as
medium- and long-term policy targets.
• Inclusive, meaning that the potential for participation is as broad
as possible on both the supply side (traditional producers, distributors
of technologies or energy supplies, whether electricity, heat or
fuel), and the demand side (businesses, households, etc.), which
can ‘self-generate’ with distributed RE, enabling broader participation
that unleashes more capital for investment, helps to build
broader public support for RE, and creates greater competition.
• Attention to preferred exempted groups, for example, major users
on competitiveness grounds or low-income and vulnerable customers
on equity and distributional grounds.
It is also important to recognize that there is no one-size-fi ts-all policy,
and policymakers can benefi t from the ability to learn from experience
and adjust programmes as necessary. Policies need to respond to
local political, economic, social, ecological, cultural and fi nancial needs
and conditions, as well as factors such as the level of technological
maturity, availability of affordable capital, and the local and national
RE resource base. In addition, a mix of policies is generally needed to
address the various barriers to RE. Policy frameworks that are transparent
and sustained—from predictability of a specifi c policy, to pricing
of carbon and other externalities, to long-term targets for RE—have
been found to be crucial for reducing investment risks and facilitating
deployment of RE and the evolution of low-cost applications. [11.5.7]
Macroeconomic impacts of renewable energy policies
Payment for supply-push type RE support tends to come from public
budgets (multinational, national, local), whereas the cost of demand-pull
mechanisms often lands on the end users. For example, if a renewable
electricity policy is added to a countries’ electricity sector, this additional
cost is often borne by electricity consumers, although exemptions or
re-allocations can reduce costs for industrial or vulnerable customers
where necessary. Either way, there are costs to be paid. If the goal is
to transform the energy sector over the next several decades, then it is
important to minimize costs over this entire period; it is also important
to include all costs and benefi ts to society in that calculation. [11.5.7.2]
Conducting an integrated analysis of costs and benefi ts of RE is
extremely demanding because so many elements are involved in determining
net impacts. Effects fall into three categories: direct and indirect
costs of the system as well as benefi ts of RE expansion; distributional
effects (in which economic actors or groups enjoy benefi ts or suffer burdens
as a result of RE support); and macroeconomic aspects such as
impacts on GDP or employment. For example, RE policies provide opportunities
for potential economic growth and job creation, but measuring
net effects is complex and uncertain because the additional costs of RE
support create distributional and budget effects on the economy. Few
studies have examined such impacts on national or regional economies;
however, those that have been carried out have generally found net
positive economic impacts. [11.3.4, 11.5.7.2]
Interactions and potential unintended consequences of renewable
energy and climate policies
Due to overlapping drivers and rationales for RE deployment and overlapping
jurisdictions (local, national, international) substantial interplay
155
Summaries Technical Summary
may occur among policies at times with unintended consequences.
Therefore, a clear understanding of the interplay among policies and the
cumulative effects of multiple policies is crucial. [11.3, 11.5.7, 11.6.2]
If not applied globally and comprehensively, both carbon pricing and
RE policies create risks of ‘carbon leakage’, where RE policies in one
jurisdiction or sector reduce the demand for fossil fuel energy in that
jurisdiction or sector, which ceteris paribus reduces fossil fuel prices
globally and hence increases demand for fossil energy in other jurisdictions
or sectors. Even if implemented globally, suboptimal carbon prices
and RE policies could potentially lead to higher carbon emissions. For
example, if fossil fuel resource owners fear more supportive RE deployment
policies in the long term, they could increase resource extraction
as long as RE support is moderate. Similarly, the prospect of future
carbon price increases may encourage owners of oil and gas wells to
extract resources more rapidly, while carbon taxes are lower, undermining
policymakers’ objectives for both the climate and the spread of RE
technology. The conditions of such a ‘green paradox’ are rather specifi c:
carbon pricing would have to begin at low levels and increase rapidly.
Simultaneously, subsidized RE would have to remain more expensive
than fossil fuel-based technologies. However, if carbon prices and RE
subsidies begin at high levels from the beginning, such green paradoxes
become unlikely. [11.5.7]
The cumulative effect of combining policies that set fi xed carbon prices,
like carbon taxes, with RE subsidies is largely additive: in other words,
extending a carbon tax with RE subsidies decreases emissions and
increases the deployment of RE. However, the effect on the energy system
of combining endogenous-price policies, like emissions trading and/
or RE quota obligations, is usually not as straightforward. Adding RE
policies on top of an emissions trading scheme usually reduces carbon
prices which, in turn, makes carbon-intensive (e.g., coal-based) technologies
more attractive compared to other non-RE abatement options
such as natural gas, nuclear energy and/or energy effi ciency improvements.
In such cases, although overall emissions remain fi xed by the cap,
RE policies reduce the costs of compliance and/or improve social welfare
only if RE technologies experience specifi c externalities and market barriers
to a greater extent than other energy technologies. [11.5.7]
Finally, RE policies alone (i.e., without carbon pricing) are not necessarily
an effi cient instrument to reduce carbon emissions because they
do not provide enough incentives to use all available least-cost mitigation
options, including non-RE low-carbon technologies and energy
effi ciency improvements. [11.5.7]
11.6 Enabling environment and regional
issues
RE technologies can play a greater role in climate change mitigation if
they are implemented in conjunction with broader ‘enabling’ policies
that can facilitate change in the energy system. An ‘enabling’ environment
encompasses different institutions, actors (e.g., the fi nance
community, business community, civil society, government), infrastructures
(e.g., networks and markets), and political outcomes (e.g.,
international agreements/cooperation, climate change strategies) (see
Table TS.11.1). [11.6]
A favourable or ‘enabling’ environment for RE can be created by
encouraging innovation in the energy system; addressing the possible
interactions of a given policy with other RE policies as well as with other
non-RE policies; easing the ability of RE developers to obtain fi nance
and to successfully site a project; removing barriers for access to networks
and markets for RE installations and output; enabling technology
transfer and capacity building; and by increasing education and awareness
raising at the institutional level and within communities. In turn,
the existence of an ‘enabling’ environment can increase the effi ciency and
effectiveness of policies to promote RE. [11.6.1–11.6.8]
A widely accepted conclusion in innovation literature is that established
socio-technical systems tend to narrow the diversity of innovations
because the prevailing technologies develop a fi tting institutional environment.
This may give rise to strong path dependencies and exclude
(or lock out) rivalling and potentially better-performing alternatives. For
these reasons, socio-technical system change takes time, and it involves
change that is systemic rather than linear. RE technologies are being integrated
into an energy system that, in much of the world, was constructed
to accommodate the existing energy supply mix. As a result, infrastructure
favours the currently dominant fuels, and existing lobbies and interests
all need to be taken into account. Due to the intricacies of technological
change, it is important that all levels of government (from local through
to international) encourage RE development through policies, and that
nongovernmental actors also be involved in policy formulation and implementation.
[11.6.1]
Government policies that complement each other are more likely to be
successful, and the design of individual RE policies will also affect the
success of their coordination with other policies. Attempting to actively
promote the complementarities of policies across multiple sectors—from
energy to agriculture to water policy, etc.—while also considering the
independent objectives of each, is not an easy task and may create winwin
and/or win-lose situations, with possible trade-offs. This implies a
need for strong central coordination to eliminate contradictions and confl
icts among sectoral policies and to simultaneously coordinate action at
more than one level of governance. [11.6.2]
A broader enabling environment includes a fi nancial sector that can
offer access to fi nancing on terms that refl ect the specifi c risk/reward
profi le of a RE technology or project. The cost of fi nancing and access to
it depends on the broader fi nancial market conditions prevalent at the
time of investment, and on the specifi c risks of a project, technology,
and actors involved. Beyond RE-specifi c policies, broader conditions can
156
Technical Summary Summaries
Table TS.11.1 | Factors and participants contributing to a successful RE governance regime. [Table 11.4]
Dimensions of
an Enabling
Environment >>
Factors and actors
contributing to the
success of RE policy
Section 11.6.2
Integrating Policies
(national/
supranational
policies)
Section 11.6.3
Reducing Financial
and Investment Risk
Section 11.6.4
Planning and
Permitting at the
local level
Section 11.6.5
Providing
infrastructures
networks and
markets for RE
technology
Section 11.6.6
Technology
Transfer and
Capacity Building
Section 11.6.7
Learning from
actors beyond
government
Institutions
Integrating RE policies
with other policies at
the design level reduces
potential for confl ict
among government
policies
Development of fi nancing
institutions and agencies
can aid cooperation
between countries, provide
soft loans or international
carbon fi nance (CDM).
Long-term commitment
can reduce the perception
of risk
Planning and permitting
processes enable RE
policy to be integrated
with non-RE policies at
the local level
Policymakers and regulators
can enact incentives
and rules for networks
and markets, such as
security standards and
access rules
Reliability of RE
technologies can
be ensured through
certifi cation
Institutional agreements
enable technology
transfer
Openness to learning
from other actors can
complement design of
policies and enhance
their effectiveness by
working within existing
social conditions
Civil society
(individuals, households,
NGOs,
unions ...)
Municipalities or cities
can play a decisive role
in integrating state policies
at the local level
Community investment
can share and reduce
investment risk
Public-private partnerships
in investment and
project development can
contribute to reducing
risks associated with policy
instruments
Appropriate international
institutions can enable
an equitable distribution
of funds
Participation of civil
society in local planning
and permitting processes
might allow for selection
of the most socially
relevant RE projects
Civil society can become
part of supply networks
through co-production of
energy and new decentralized
models.
Local actors and
NGOs can be involved
in technology transfer
through new business
models bringing together
multi-national
companies / NGOs /
Small and Medium
Enterprises
Civil society
participation in open
policy processes
can generate new
knowledge and induce
institutional change
Municipalities or cities
may develop solutions
to make RE technology
development possible at
the local level
People (individually
or collectively) have a
potential for advancing
energy-related
behaviours when policy
signals and contextual
constraints are coherent
Finance and business
communities
Public private partnerships
in investment and
project development can
contribute to reducing
risks associated with policy
instruments
RE project developers
can offer know-how and
professional networks
in : i) aligning project
development with
planning and permitting
requirements ; ii)
adapting planning and
permitting processes
to local needs and
conditions
Businesses can be active
in lobbying for coherent
and integrated policies
Clarity of network and
market rules improves
investor confi dence
Financing institutions
and agencies can
partner with national
governments, provide
soft loans or international
carbon fi nance
(CDM).
Multi-national
companies can involve
local NGOs or SMEs
as partners in new
technology development
(new business models)
Development of corporations
and international
institutions reduces risk
of investment
Infrastructures
Policy integration with
network and market
rules can enable development
of infrastructure
suitable for a lowcarbon
economy
Clarity of network and
market rules reduces risk
of investment and improves
investor confi dence
Clear and transparent
network and market rules
are more likely to lead to
infrastructures complementary
to a low-carbon
future
City and community
level frameworks for the
development of longterm
infrastructure and
networks
can sustain the
involvement of local
actors in policy
development
Continued next Page ➔
157
Summaries Technical Summary
Dimensions of
an Enabling
Environment >>
Factors and actors
contributing to the
success of RE policy
Section 11.6.2
Integrating Policies
(national/
supranational
policies)
Section 11.6.3
Reducing Financial
and Investment Risk
Section 11.6.4
Planning and
Permitting at the
local level
Section 11.6.5
Providing
infrastructures
networks and
markets for RE
technology
Section 11.6.6
Technology
Transfer and
Capacity Building
Section 11.6.7
Learning from
actors beyond
government
Politics
(international agreements
/ cooperation,
climate change
strategy,
technology transfer...)
Supra-national
guidelines (e.g., EU on
“streamlining”, ocean
planning, impact study)
may contribute to
integrating RE policy
with other policies
Long-term political
commitment to RE policy
reduces investors risk in RE
projects
Supra- national guidelines
may contribute to
evolving planning and
permitting processes
Development cooperation
helps sustain infrastructure
development and
allows easier access to
low-carbon technologies
CDMs, Intellectual
property rights (IPR)
and patent agreements
can contribute
to technology transfer
Appropriate input from
non-government institutions
stimulates more
agreements that are
socially connected
UNFCCC process mechanisms
such as Expert
Group on Technology
Transfer (EGTT), the
Global Environment
Facility (GEF), and the
Clean Development
Mechanism (CDM)
and Joint Implementation
(JM) may provide
guidelines to facilitate
the involvement of nonstate
actors in RE policy
development
include political and currency risks, and energy-related issues such as
competition for investment from other parts of the energy sector, and the
state of energy sector regulations or reform. [11.6.3]
The successful deployment of RE technologies to date has depended on a
combination of favourable planning procedures at both national and local
levels. Universal procedural fi xes, such as ‘streamlining’ of permitting
applications, are unlikely to resolve confl icts among stakeholders at the
level of project deployment because they would ignore place- and scalespecifi
c conditions. A planning framework to facilitate the implementation
of RE might include the following elements: aligning stakeholder expectations
and interests; learning about the importance of context for RE
deployment; adopting benefi t-sharing mechanisms; building collaborative
networks; and implementing mechanisms for articulating confl ict for
negotiation. [11.6.4]
After a RE project receives planning permission, investment to build it is
only forthcoming once its economic connection to a network is agreed;
when it has a contract for the ‘off-take’ of its production into the network;
and when its sale of energy, usually via a market, is assured. The ability,
ease and cost of fulfi lling these requirements is central to the feasibility
of a RE project. Moreover, the methods by which RE is integrated into
the energy system will have an effect on the total system cost of RE integration
and the cost of different scenario pathways. In order to ensure
the timely expansion and reinforcement of infrastructure for and connection
of RE projects, economic regulators may need to allow ‘anticipatory’
or ‘proactive’ network investment and/or allow projects to connect in
advance of full infrastructure reinforcement. [11.6.5, 8.2.1.3]
For many countries, a major challenge involves gaining access to RE technologies.
Most low-carbon technologies, including RE technologies, are
developed and concentrated in a few countries. It has been argued that
many developing nations are unlikely to ‘leapfrog’ pollution-intensive
stages of industrial development without access to clean technologies
that have been developed in more advanced economies. However, technologies
such as RE technologies typically do not fl ow across borders
unless environmental policies in the recipient country provide incentives
for their adoption. Further, technology transfer should not replace
but rather should complement domestic efforts at capacity building. In
order to have the capacity to adapt, install, maintain, repair and improve
on RE technologies in communities without ready access to RE, investment
in technology transfer must be complemented by investment in
community-based extension services that provide expertise, advice and
training regarding installation, technology adaptation, repair and maintenance.
[11.6.6]
In addition to technology transfer, institutional learning plays an
important role in advancing deployment of RE. Institutional learning is
conducive to institutional change, which provides space for institutions
to improve the choice and design of RE policies. It also encourages a
stronger institutional capacity at the deeper, often more local, level where
numerous decisions are made on siting and investments in RE projects.
Institutional learning can occur if policymakers can draw on nongovernmental
actors, including private actors (companies, etc.) and civil society
for collaborative approaches in policymaking. Information and education
are often emphasized as key policy tools for infl uencing energy-related
behaviours. However, the effectiveness of education- and informationbased
policies is limited by contextual factors, which cautions against an
over-reliance on information- and education-based policies alone. Changes
in energy-related behaviours are the outcome of a process in which personal
norms or attitudes interact with prices, policy signals, and the RE
technologies themselves, as well as the social context in which individuals
158
Technical Summary Summaries
fi nd themselves. These contextual factors point to the importance of
collective action as a more effective, albeit more complex medium for
change than individual action. This supports coordinated, systemic
policies that go beyond narrow ‘attitude-behaviour-change’ policies if
policymakers wish to involve individuals in the RE transition. [11.6.7,
11.6.8]
11.7 A structural shift
If decision makers intend to increase the share of RE and, at the same
time, meet ambitious climate mitigation targets, then long-standing
commitments and fl exibility to learn from experience will be critical. To
achieve GHG concentration stabilization levels with high shares of RE, a
structural shift in today’s energy systems will be required over the next
few decades. Such a transition to low-carbon energy differs from previous
energy transitions (e.g., from wood to coal, or coal to oil) because
the available time span is restricted to a few decades, and because RE
must develop and integrate into a system constructed in the context of
an existing energy structure that is very different from what might be
required under higher penetration RE futures. [11.7]
A structural shift towards a world energy system that is mainly based
on renewable energy might begin with a prominent role for energy
effi ciency in combination with RE. This requires, however, a reasonable
carbon pricing policy in the form of a tax or emission trading scheme
that avoids carbon leakage and rebound effects. Additional policies are
required that extend beyond R&D to support technology deployment;
the creation of an enabling environment that includes education and
awareness raising; and the systematic development of integrative policies
with broader sectors, including agriculture, transportation, water
management and urban planning. [11.6, 11.7] The policy frameworks
that induce the most RE investment are those designed to reduce risks
and enable attractive returns, and to provide stability over a time frame
relevant to the investment. [11.5] The appropriate and reliable mix of
instruments is even more important where energy infrastructure is not
yet developed and energy demand is expected to increase signifi cantly
in the future. [11.7]
Annexes
I Glossary, Acronyms, Chemical
Symbols and Prefixes
Editors:
Aviel Verbruggen (Belgium), William Moomaw (USA), John Nyboer (Canada)
This annex should be cited as:
Verbruggen, A., W. Moomaw, J. Nyboer, 2011: Annex I: Glossary, Acronyms, Chemical Symbols and Prefixes.
In IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation [O. Edenhofer, R. Pichs-
Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer,
C. von Stechow (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
ANNEX
161
162
Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
Glossary, Acronyms, Chemical Symbols and Prefixes
Glossary entries (highlighted in bold) are by preference subjects; a main entry can contain subentries, in bold italic, for example, Final Energy is
defined under the entry Energy. The Glossary is followed by a list of acronyms/abbreviations, a list of chemical names and symbols, and a list of
prefixes (international standard units). Some definitions are adapted from C.J. Cleveland and C. Morris, 2006: Dictionary of Energy, Elsevier,
Amsterdam. Definitions of regions and country groupings are given in Section A.II.6 of Annex II of this report.
Glossary
Adaptation: Initiatives and measures to reduce the vulnerability
or increase the resilience of natural and human systems to actual or
expected climate change impacts. Various types of adaptation exist, for
example, anticipatory and reactive, private and public, and autonomous
and planned. Examples are raising river or coastal dikes, retreating
from coastal areas subject to flooding from sea level rise or introducing
alternative temperature-appropriate or drought-adapted crops for
conventional ones.
Aerosols: A collection of airborne solid or liquid particles, typically
between 0.01 and 10 μm in size and residing in the atmosphere for at
least several hours. Aerosols may be of natural or anthropogenic origin.
See also black carbon.
Afforestation: Direct human-induced conversion of land that has not
been forested historically to forested land through planting, seeding
and/or the human-induced promotion of natural seed sources.1 See also
deforestation, reforestation, land use.
Annex I countries: The group of countries included in Annex I (as
amended since Malta was added after that date) to the UNFCCC,
including developed countries and some countries with economies in
transition. Under Articles 4.2 (a) and 4.2 (b) of the Convention, Annex I
countries were encouraged to return individually or jointly to their 1990
levels of greenhouse gas emissions by 2000. The group is largely similar
to the Annex B countries to the Kyoto Protocol. By default, the other
countries are referred to as Non-Annex I countries. See also UNFCCC,
Kyoto Protocol.
Annex B countries: This is the subset of Annex I countries that have
specified greenhouse gas reduction commitments under the Kyoto
Protocol. The group is largely similar to the Annex I countries to the
UNFCCC. By default, the other countries are referred to as Non-Annex I
countries. See also UNFCCC, Kyoto Protocol.
1 For a discussion of the term forest and related terms such as afforestation, reforestation
and deforestation, see IPCC 2000: Land Use, Land-Use Change, and Forestry, A
Special Report of the IPCC [R.T. Watson, I.A. Noble, B. Bolin, N.H. Ravindranath, D.J.
Verardo, D.J. Dokken (eds.)], Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA.
Anthropogenic: Related to or resulting from the influence of human
beings on nature.
Anthropogenic emissions of greenhouse gases, greenhouse gas
precursors and aerosols result from burning fossil fuels, deforestation,
land use changes, livestock, fertilization, industrial, commercial
and other activities that result in a net increase in emissions.
Availability (of a production plant): The percentage of time a plant is
ready to produce, measured as uptime to total time (total time = uptime
+ downtime due to maintenance and outages).
Balancing power/reserves: Due to instantaneous and short-term
fluctuations in electric loads and uncertain availability of power plants
there is a constant need for spinning and quick-start generators that
balance demand and supply at the imposed quality levels for frequency
and voltage.
Barrier: Any obstacle to developing and deploying a renewable energy
(RE) potential that can be overcome or attenuated by a policy, programme
or measure. Barriers to RE deployment are unintentional or
intentionally constructed impediments made by man (e.g., badly oriented
buildings or power grid access criteria that discriminate against
independent RE generators). Distinct from barriers are issues like intrinsically
natural properties impeding the application of some RE sources
at some place or time (e.g., flat land impedes hydropower and night the
collection of direct solar energy).
Barrier removal includes correcting market failures directly or
reducing the transactions costs in the public and private sectors
by, for example, improving institutional capacity, reducing risk and
uncertainty, facilitating market transactions and enforcing regulatory
policies.
Baseline: The reference scenario for measurable quantities from which
an alternative outcome can be measured, for example, a non-intervention
scenario is used as a reference in the analysis of intervention scenarios.
A baseline may be an extrapolation of recent trends, or it may assume
frozen technology or costs. See also business as usual, models, scenario.
Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
163
Benchmark: A measurable variable used as a baseline or reference in
evaluating the performance of a technology, a system or an organization.
Benchmarks may be drawn from internal experience, from external
correspondences or from legal requirements and are often used to
gauge changes in performance over time.
Biodiversity: The variability among living organisms from all sources
including, inter alia, terrestrial, marine and other aquatic ecosystems
and the ecological complexes of which they are part; this includes diversity
within species, among species and of ecosystems.
Bioenergy: Energy derived from any form of biomass.
Biofuel: Any liquid, gaseous or solid fuel produced from biomass, for
example, soybean oil, alcohol from fermented sugar, black liquor from
the paper manufacturing process, wood as fuel, etc. Traditional biofuels
include wood, dung, grass and agricultural residues.
First-generation manufactured biofuel is derived from grains,
oilseeds, animal fats and waste vegetable oils with mature conversion
technologies.
Second-generation biofuel uses non-traditional biochemical and
thermochemical conversion processes and feedstock mostly derived
from the lignocellulosic fractions of, for example, agricultural and
forestry residues, municipal solid waste, etc.
Third-generation biofuel would be derived from feedstocks like
algae and energy crops by advanced processes still under development.
These second- and third-generation biofuels produced
through new processes are also referred to as next-generation or
advanced biofuels or advanced biofuel technologies.
Biomass: Material of biological origin (plants or animal matter), excluding
material embedded in geological formations and transformed to
fossil fuels or peat. The International Energy Agency (World Energy
Outlook 2010) defines traditional biomass as biomass consumption
in the residential sector in developing countries that refers to the often
unsustainable use of wood, charcoal, agricultural residues and animal
dung for cooking and heating. All other biomass use is defined as modern
biomass, differentiated further by this report into two groups.
Modern bioenergy encompasses electricity generation and combined
heat and power (CHP) from biomass and municipal solid
waste (MSW), biogas, residential space and hot water in buildings
and commercial applications from biomass, MSW, and biogas, and
liquid transport fuels.
Industrial bioenergy applications include heating through steam
generation and self generation of electricity and CHP in the pulp and
paper industry, forest products, food and related industries.
Black carbon: Operationally defined aerosol species based on measurement
of light absorption and chemical reactivity and/or thermal
stability; consists of soot, charcoal and/or light-absorbing refractory
organic matter.
Business as usual (BAU): The future is projected or predicted on the
assumption that operating conditions and applied policies remain what
they are at present. See also baseline, models, scenario.
Capacity: In general, the facility to produce, perform, deploy or contain.
Generation capacity of a renewable energy installation is the
maximum power, that is, the maximum quantity of energy delivered
per unit of time.
Capacity credit is the share of the capacity of a renewable energy
unit counted as guaranteed available during particular time periods
and accepted as a ‘firm’ contribution to total system generation
capacity.
Capacity factor is the ratio of the actual output of a generating
unit over a period of time (typically a year) to the theoretical output
that would be produced if the unit were operating uninterruptedly
at its nameplate capacity during the same period of time. Also
known as rated capacity or nominal capacity, nameplate capacity
is the facility’s intended output level for a sustained period under
normal circumstances.
Capacity building: In the context of climate change policies, the development
of technical skills and institutional capability (the art of doing)
and capacity (sufficient means) of countries to enable their participation
in all aspects of adaptation to, mitigation of and research on climate
change. See also mitigation capacity.
Carbon cycle: Describes the flow of carbon (in various forms, e.g., carbon
dioxide, methane, etc) through the atmosphere, oceans, terrestrial
biosphere and lithosphere.
Carbon dioxide (CO2): CO2 is a naturally occurring gas and a by-product
of burning fossil fuels or biomass, of land use changes and of industrial
processes. It is the principal anthropogenic greenhouse gas that affects
Earth’s radiative balance. It is the reference gas against which other
greenhouse gases are measured and therefore it has a global warming
potential of 1.
Carbon dioxide capture and storage (CCS): CO2 from industrial and
energy-related sources is separated, compressed and transported to a
storage location for long-term isolation from the atmosphere.
Cellulose: The principal chemical constituent of the cell walls of
plants and the source of fibrous materials for the manufacturing of
164
Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
various goods like paper, rayon, cellophane, etc. It is the main input for
manufacturing second-generation biofuels.
Clean Development Mechanism (CDM): A mechanism under the
Kyoto Protocol through which developed (Annex B) countries may
finance greenhouse gas emission reduction or removal projects in developing
(Non-Annex B) countries, and receive credits for doing so which
they may apply for meeting mandatory limits on their own emissions.
Climate Change: Climate change refers to a change in the state of the
climate that can be identified (e.g. using statistical tests) by changes in
the mean and/or the variability of these properties and that persists for
an extended period, typically decades or longer. Climate change may be
due to natural internal processes or external forcings, or to persistent
anthropogenic changes in the composition of the atmosphere or in land
use. Note that Article 1 of the UNFCCC defines ‘climate change’ as “a
change of climate which is attributed directly or indirectly to human
activity that alters the composition of the global atmosphere and which
is in addition to natural climate variability observed over comparable
time periods”. The UNFCCC thus makes a distinction between ‘climate
change’ attributable to human activities altering atmospheric composition,
and ‘climate variability’ attributable to natural causes.
CO2-equivalent emission (CO2eq): The amount of CO2 emission that
would cause the same radiative forcing as an emitted amount of a
greenhouse gas or of a mixture of greenhouse gases, all multiplied by
their respective global warming potentials, which take into account the
differing times they remain in the atmosphere. See also global warming
potential.
Co-benefits: The ancillary benefits of targeted policies that accrue to
non-targeted, valuable objectives, for example, a wider use of renewable
energy may also reduce air pollutants while lowering CO2 emissions.
Different definitions exist in the literature with co-benefits either
being addressed intentionally (character of an opportunity) or gained
unintentionally (character of a windfall profit). The term co-impact is
more generic in covering both benefits and costs. See also drivers and
opportunities.
Cogeneration: At thermal electricity generation plants otherwise
wasted heat is utilized. The heat from steam turbines or hot flue gases
exhausted from gas turbines may be used for industrial purposes,
heating water or buildings or for district heating. Also referred to as
combined heat and power (CHP).
Combined-cycle gas turbine (CCGT): A power plant that combines
two processes for generating electricity. First, gas or light fuel oil feeds a
gas turbine that exhausts hot flue gases (> 600°C). Second, heat recovered
from these gases, with additional firing, is the source for producing
steam that drives a steam turbine. The turbines rotate separate alternators.
It becomes an integrated CCGT when the fuel is syngas from
a coal or biomass gasification reactor with exchange of energy flows
between the gasification and CCGT plants.
Compliance: Compliance is whether and to what extent countries
adhere to the provisions of an accord or individuals or firms adhere to
regulations. Compliance depends on implementing policies ordered, and
on whether measures follow up the policies.
Conversion: Energy shows itself in numerous ways, with transformations
from one type to another called energy conversions. For example,
kinetic energy in wind flows is captured as rotating shaft work further
converted to electricity; solar light is converted into electricity by photovoltaic
cells. Also, electric currents of given characteristics (e.g., direct/
alternating, voltage level) are converted to currents with other characteristics.
A converter is the equipment used to realize the conversion.
Cost: The consumption of resources such as labour time, capital, materials,
fuels, etc. as the consequence of an action. In economics, all
resources are valued at their opportunity cost, which is the value of
the most valuable alternative use of the resources. Costs are defined in
a variety of ways and under a variety of assumptions that affect their
value. The negative of costs are benefits and often both are considered
together, for example, net cost is the difference between gross costs and
benefits.
Private costs are carried by individuals, companies or other entities
that undertake the action.
Social costs include additionally the external costs for the environment
and for society as a whole, for example, damage costs
of impacts on ecosystems, economies and people due to climate
change.
Total cost includes all costs due to a specific activity; average
(unit, specific) cost is total costs divided by the number of units
generated; marginal or incremental cost is the cost of the last
additional unit.
Project costs of a renewable energy project include investment
cost (costs, discounted to the starting year of the project, of making
the renewable energy device ready to commence production);
operation and maintenance (O&M) costs (which occur during
operation of the renewable energy facility); and decommissioning
costs (which occur once the device has ceased production to restore
the state of the site of production).
Lifecycle costs include all of the above discounted to the starting
year of a project.
Levelized cost of energy (see Annex II) is the unique cost price of
the outputs (US cent/kWh or USD/GJ) of a project that makes the
165
Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
present value of the revenues (benefits) equal to the present value
of the costs over the lifetime of the project. See also discounting and
present value.
There are many more categories of costs labelled with names that are
often unclear and confusing, for example, installation costs may refer to
the hardware equipment installed, or to the activities to put the equipment
in place.
Cost–benefit analysis: Monetary measurement of all negative and
positive impacts associated with a given action. Costs and benefits are
compared in terms of their difference and/or ratio as an indicator of how
a given investment or other policy effort pays off seen from the society’s
point of view.
Cost-effectiveness analysis: A reduction of cost–benefit analysis in
which all the costs of a portfolio of projects are assessed in relation to
a fixed policy goal. The policy goal in this case represents the benefits
of the projects and all the other impacts are measured as costs or as
negative costs (benefits). The policy goal can be, for example, realizing
particular renewable energy potentials.
Deforestation: The natural or anthropogenic process that converts forest
land to non-forest. See also afforestation, reforestation and land use.
Demand-side management: Policies and programmes for influencing
the demand for goods and/or services. In the energy sector, demandside
management aims at reducing the demand for electricity and other
forms of energy required to deliver energy services.
Density: Quantity or mass per unit volume, unit area or unit length.
Energy density is the amount of energy per unit volume or mass
(for example, the heating value of a litre of oil).
Power density is typically understood as the capacity deliverable
of solar, wind, biomass, hydropower or ocean power per unit area
(watts/m2). For batteries the capacity per unit weight (watts/kg) is
used.
Direct solar energy - See solar energy
Discounting: A mathematical operation making monetary (or other)
amounts received or expended at different points in time (years) comparable
across time (see Annex II). The operator uses a fixed or possibly
time-varying discount rate (>0) from year to year that makes future
value worth less today. A descriptive discounting approach accepts
the discount rates that people (savers and investors) actually apply in
their day-to-day decisions (private discount rate). In a prescriptive
(ethical or normative) discounting approach, the discount rate is
fixed from a social perspective, for example, based on an ethical judgement
about the interests of future generations (social discount rate).
In this report, potentials of renewable energy supplies are assessed
using discount rates of 3, 7 and 10%.
Dispatch (power dispatching / dispatchable): Electrical power systems
that consist of many power supply units and grids are governed
by system operators. They allow generators to supply power to the system
for balancing demand and supply in a reliable and economical way.
Generation units are fully dispatchable when they can be loaded from
zero to their nameplate capacity without significant delay. Not fully
dispatchable are variable renewable sources that depend on natural
currents, but also large-scale thermal plants with shallow ramping rates
in changing their output. See also balancing, capacity, grid.
District heating (DH): Hot water (steam in old systems) is distributed
from central stations to buildings and industries in a densely occupied
area (a district, a city or an industrialized area). The insulated two-pipe
network functions like a water-based central heating system in a building.
The central heat sources can be waste heat recovery from industrial
processes, waste incineration plants, geothermal sources, cogeneration
power plants or stand-alone boilers burning fossil fuels or biomass.
More and more DH systems also provide cooling via cold water or slurries
(district heating and cooling - DHC).
Drivers: In a policy context, drivers provide an impetus and direction
for initiating and supporting policy actions. The deployment of renewable
energy is, for example, driven by concerns about climate change
or energy security. In a more general sense, a driver is the leverage to
bring about a reaction, for example, emissions are caused by fossil fuel
consumption and/or economic growth. See also opportunities.
Economies of scale (scale economies): The unit cost of an activity
declines when the activity is extended, for example, more units are
produced.
Ecosystem: An open system of living organisms, interacting with
each other and with their abiotic environment, that is capable of selfregulation
to a certain degree. Depending on the focus of interest or
study the extent of an ecosystem may range from very small spatial
scales to the entire planet.
Electricity: The flow of passing charge through a conductor, driven by
a difference in voltage between the ends of the conductor. Electrical
power is generated by work from heat in a gas or steam turbine or from
wind, oceans or falling water, or produced directly from sunlight using a
photovoltaic device or chemically in a fuel cell. Being a current, electricity
cannot be stored and requires wires and cables for its transmission
(see grid). Because electric current flows immediately, the demand for
electricity must be matched by production in real time.
Emissions: Direct emissions are released and attributed at points in
a specific renewable energy chain, whether a sector, a technology or an
activity. For example, methane emissions from decomposing submerged
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organic materials in hydropower reservoirs, or the release of CO2 dissolved
in hot water from geothermal plants, or CO2 from biomass
combustion. Indirect emissions are due to activities outside the considered
renewable energy chain but which are required to realize the
renewable energy deployment. For example, emissions from increased
production of fertilizers used in the cultivation of biofuel crops or emissions
from displaced crop production or deforestation as the result of
biofuel crops. Avoided emissions are emission reductions arising from
mitigation measures like renewable energy deployment.
Emission factor: An emission factor is the rate of emission per unit of
activity, output or input.
Emissions trading: A market-based instrument to reduce greenhouse
gas or other emissions. The environmental objective or sum of total
allowed emissions is expressed as an emissions cap. The cap is divided
in tradable emission permits that are allocated—either by auctioning or
handing out for free (grandfathering)—to entities within the jurisdiction
of the trading scheme. Entities need to surrender emission permits equal
to the amount of their emissions (e.g., tonnes of CO2 ). An entity may
sell excess permits. Trading schemes may occur at the intra-company,
domestic or international level and may apply to CO2 , other greenhouse
gases or other substances. Emissions trading is also one of the mechanisms
under the Kyoto Protocol.
Energy: The amount of work or heat delivered. Energy is classified in
a variety of types and becomes available to human ends when it flows
from one place to another or is converted from one type into another.
Daily, the sun supplies large flows of radiation energy. Part of that
energy is used directly, while part undergoes several conversions creating
water evaporation, winds, etc. Some share is stored in biomass
or rivers that can be harvested. Some share is directly usable such as
daylight, ventilation or ambient heat.
Primary energy (also referred to as energy sources) is the energy
embodied in natural resources (e.g., coal, crude oil, natural gas, uranium,
and renewable sources). It is defined in several alternative
ways. The International Energy Agency utilizes the physical energy
content method, which defines primary energy as energy that has
not undergone any anthropogenic conversion. The method used
in this report is the direct equivalent method (see Annex II), which
counts one unit of secondary energy provided from non-combustible
sources as one unit of primary energy, but treats combustion energy
as the energy potential contained in fuels prior to treatment or
combustion. Primary energy is transformed into secondary energy
by cleaning (natural gas), refining (crude oil to oil products) or by
conversion into electricity or heat. When the secondary energy is
delivered at the end-use facilities it is called final energy (e.g.,
electricity at the wall outlet), where it becomes usable energy in
supplying services (e.g., light).
Embodied energy is the energy used to produce a material substance
(such as processed metals or building materials), taking
into account energy used at the manufacturing facility (zero order),
energy used in producing the materials that are used in the manufacturing
facility (first order), and so on.
Renewable energy (RE) is any form of energy from solar, geophysical
or biological sources that is replenished by natural processes at
a rate that equals or exceeds its rate of use. Renewable energy is
obtained from the continuing or repetitive flows of energy occurring
in the natural environment and includes low-carbon technologies
such as solar energy, hydropower, wind, tide and waves and ocean
thermal energy, as well as renewable fuels such as biomass. For a
more detailed description see specific renewable energy types in
this glossary, for example, biomass, solar, hydropower, ocean, geothermal
and wind.
Energy access: People are provided the ability to benefit from affordable,
clean and reliable energy services for basic human needs (cooking
and heating, lighting, communication, mobility) and productive uses.
Energy carrier: A substance for delivering mechanical work or transfer
of heat. Examples of energy carriers include: solid, liquid or gaseous
fuels (e.g., biomass, coal, oil, natural gas, hydrogen); pressurized/heated/
cooled fluids (air, water, steam); and electric current.
Energy efficiency: The ratio of useful energy or other useful physical
outputs obtained from a system, conversion process, transmission or
storage activity to the input of energy (measured as kWh/kWh, tonnes/
kWh or any other physical measure of useful output like tonne-km transported,
etc.). Energy efficiency is a component of energy intensity.
Energy intensity: The ratio of energy inputs (in Joules) to the economic
output (in dollars) that absorbed the energy input. Energy intensity
is the reciprocal of energy productivity. At the national level, energy
intensity is the ratio of total domestic primary (or final) energy use to
gross domestic product (GDP). The energy intensity of an economy is
the weighted sum of the energy intensities of particular activities with
the activities’ shares in GDP as weights. Energy intensities are obtained
from available statistics (International Energy Agency, International
Monetary Fund) and published annually for most countries in the world.
Energy intensity is also used as a name for the ratio of energy inputs to
output or performance in physical terms (e.g., tonnes of steel output,
tonne-km transported, etc.) and in such cases, is the reciprocal of energy
efficiency.
Energy productivity: The reciprocal of energy intensity.
Energy savings: Decreasing energy intensity by changing the activities
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cal, organizational, institutional and structural actions and by changed
behaviour.
Energy security: The goal of a given country, or the global community
as a whole, to maintain an adequate energy supply. Measures encompass
safeguarding access to energy resources; enabling development
and deployment of technologies; building sufficient infrastructure to
generate, store and transmit energy supplies; ensuring enforceable contracts
of delivery; and access to energy at affordable prices for a specific
society or groups in society.
Energy services: Energy services are the tasks to be performed using
energy. A specific energy service such as lighting may be supplied by a
number of different means from daylighting to oil lamps to incandescent,
fluorescent or light-emitting diode devices. The amount of energy used
to provide a service may vary over a factor of 10 or more, and the corresponding
greenhouse gas emissions may vary from zero to a very high
value depending on the source of energy and the type of end-use device.
Energy transfer: Energy is transferred as work, light or heat. Heat
transfer spontaneously occurs from objects at higher temperature to
objects at lower temperature and is classified as conduction (when the
objects have contact), convection (when a fluid like air or water takes
the heat from the warmer object and is moved to the colder object to
deliver the heat) and radiation (when heat travels through space in the
form of electromagnetic waves).
Externality / external cost / external benefit: Externalities arise from
a human activity, when agents responsible for the activity do not take
full account of the activity’s impact on others’ production and consumption
possibilities, and no compensation exists for such impacts. When
the impact is negative, they are external costs. When positive they are
referred to as external benefits.
Feed-in tariff: The price per unit of electricity that a utility or power
supplier has to pay for distributed or renewable electricity fed into the
grid by non-utility generators. A public authority regulates the tariff.
There may also be a tariff for supporting renewable heat supplies.
Financing: Raising or providing money or capital by individuals, businesses,
banks, venture funds, public instances, etc. for realizing a project
or continuing an activity. Depending on the financier the money is raised
and is provided differently. For example, businesses may raise money
from internal company profits, debt or equity (shares).
Project financing of renewable energy may be provided by financiers
to distinct, single-purpose companies, whose renewable energy
sales are usually guaranteed by power purchase agreements.
Non-recourse financing is known as off-balance sheet since the
financiers rely on the certainty of project cash flows to pay back the
loan, not on the creditworthiness of the project developer.
Public equity financing is capital provided for publicly listed
companies.
Private equity financing is capital provided directly to private
companies.
Corporate financing by banks via debt obligations uses ‘onbalance
sheet’ assets as collateral and is therefore limited by the
debt ratio of companies that must rationalize each additional loan
with other capital needs.
Fiscal incentive: Actors (individuals, households, companies) are
granted a reduction of their contribution to the public treasury via
income or other taxes.
Fuel cell: A fuel cell generates electricity in a direct and continuous way
from the controlled electrochemical reaction of hydrogen or another fuel
and oxygen. With hydrogen as fuel it emits only water and heat (no CO2)
and the heat can be utilized (see cogeneration).
General equilibrium models: General equilibrium models consider
simultaneously all the markets and feedback effects among them in an
economy leading to market clearance.
Generation control: Generation of electricity at a renewable energy
plant may be subject to various controls.
Active control is a deliberate intervention in the functioning of
a system (for example, wind turbine pitch control: changing the
orientation of the blades for varying a wind turbine’s output).
Passive control is when natural forces adjust the functioning of a
system (for example, wind turbine stall control: the design of the
blade shape such that at a desired speed the blade spills the wind in
order to automatically control the wind turbine’s output).
Geothermal energy: Accessible thermal energy stored in the Earth’s
interior, in both rock and trapped steam or liquid water (hydrothermal
resources), which may be used to generate electric energy in a thermal
power plant, or to supply heat to any process requiring it. The main
sources of geothermal energy are the residual energy available from
planet formation and the energy continuously generated from radionuclide
decay.
Geothermal gradient: Rate at which the Earth’s temperature increases
with depth, indicating heat flowing from the Earth’s warm interior to its
colder parts.
Global warming potential (GWP): GWP is an index, based upon
radiative properties of well-mixed greenhouse gases, measuring the
radiative forcing of a unit mass of a given well-mixed greenhouse gas
in today’s atmosphere integrated over a chosen time horizon, relative
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to that of CO2. The GWP represents the combined effect of the differing
lengths of time that these gases remain in the atmosphere and their relative
effectiveness in absorbing outgoing infrared radiation. The Kyoto Protocol
ranks greenhouse gases on the basis of GWPs from single pulse emissions
over subsequent 100-year time frames. See also climate change and CO2-
equivalent emission.
Governance: Governance is a comprehensive and inclusive concept of
the full range of means for deciding, managing and implementing policies
and measures. Whereas government is defined strictly in terms of the
nation-state, the more inclusive concept of governance, recognizes the contributions
of various levels of government (global, international, regional,
local) and the contributing roles of the private sector, of nongovernmental
actors and of civil society to addressing the many types of issues facing the
global community.
Greenhouse gases (GHGs): Greenhouse gases are those gaseous constituents
of the atmosphere, both natural and anthropogenic, that absorb and
emit radiation at specific wavelengths within the spectrum of thermal infrared
radiation emitted by the Earth’s surface, the atmosphere and clouds.
This property causes the greenhouse effect. Water vapour (H2O), carbon
dioxide (CO2 ), nitrous oxide (N2O), methane (CH4 ) and ozone (O3) are the
primary greenhouse gases in the Earth’s atmosphere. Moreover, there are a
number of entirely human-made greenhouse gases in the atmosphere, such
as the halocarbons and other chlorine- and bromine-containing substances,
dealt with under the Montreal Protocol. Besides CO2 , N2O and CH4 , the
Kyoto Protocol deals with the greenhouse gases sulphur hexafluoride (SF6 ),
hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs).
Grid (electric grid, electricity grid, power grid): A network consisting of
wires, switches and transformers to transmit electricity from power sources
to power users. A large network is layered from low-voltage (110-240 V)
distribution, over intermediate voltage (1-50 kV) to high-voltage (above 50
kV to MV) transport subsystems. Interconnected grids cover large areas up
to continents. The grid is a power exchange platform enhancing supply reliability
and economies of scale.
Grid connection for a power producer is mostly crucial for economical
operation.
Grid codes are technical conditions for equipment and operation that
a power producer must obey for getting supply access to the grid; also
consumer connections must respect technical rules.
Grid access refers to the acceptance of power producers to deliver to
the grid.
Grid integration accommodates power production from a portfolio
of diverse and some variable generation sources in a balanced power
system. See also transmission and distribution.
Gross Domestic Product (GDP): The sum of gross value added, at purchasers’
prices, by all resident and non-resident producers in the economy,
plus any taxes and minus any subsidies not included in the value of the
products in a country or a geographic region for a given period, normally
one year. It is calculated without deducting for depreciation of fabricated
assets or depletion and degradation of natural resources.
Heat exchanger: Devices for efficient heat transfer from one medium
to another without mixing the hot and cold flows, for example, radiators,
boilers, steam generators, condensers.
Heat pump: Installation that transfers heat from a colder to a hotter
place, opposite to the natural direction of heat flows (see energy transfer).
Technically similar to a refrigerator, heat pumps are used to extract heat
from ambient environments like the ground (geothermal or ground
source), water or air. Heat pumps can be inverted to provide cooling in
summer.
Human Development Index (HDI): The HDI allows the assessment of
countries’ progress regarding social and economic development as a
composite index of three indicators: 1) health measured by life expectancy
at birth; 2) knowledge as measured by a combination of the adult
literacy rate and the combined primary, secondary and tertiary school
enrolment ratio; and 3) standard of living as gross domestic product per
capita (in purchasing power parity). The HDI only acts as a broad proxy
for some of the key issues of human development; for instance, it does
not reflect issues such as political participation or gender inequalities.
Hybrid vehicle: Any vehicle that employs two sources of propulsion,
most commonly a vehicle that combines an internal combustion engine
with an electric motor and storage batteries.
Hydropower: The energy of water moving from higher to lower elevations
that is converted into mechanical energy through a turbine or other
device that is either used directly for mechanical work or more commonly
to operate a generator that produces electricity. The term is also used to
describe the kinetic energy of stream flow that may also be converted
into mechanical energy of a generator through an in-stream turbine to
produce electricity.
Informal sector/economy: The informal sector/economy is broadly
characterized as comprising production units that operate at a small
scale and at a low level of organization, with little or no division between
labour and capital as factors of production, and with the primary objective
of generating income and employment for the persons concerned.
The economic activity of the informal sector is not accounted for in determining
sectoral or national economic activity.
Institution: A structure, a mechanism of social order or cooperation,
which governs the behaviour of a group of individuals within a human
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community. Institutions are intended to be functionally relevant for an
extended period, able to help transcend individual interests and help
govern cooperative human behaviour. The term can be extended to also
cover regulations, technology standards, certification and the like.
Integrated assessment: A method of analysis that combines results
and models from the physical, biological, economic and social sciences,
and the interactions between these components in a consistent framework
to evaluate the status and the consequences of environmental
change and the policy responses to it. See also models.
Kyoto Protocol: The Kyoto Protocol to the UNFCCC was adopted at
the Third Session of the Conference of the Parties in 1997 in Kyoto. It
contains legally binding commitments, in addition to those included in
the UNFCCC. Annex B countries agreed to reduce their anthropogenic
greenhouse gas emissions (CO2, methane, nitrous oxide, hydrofluorocarbons,
perfluorocarbons and sulphur hexafluoride) by at least 5% below
1990 levels in the commitment period 2008 to 2012. The Kyoto Protocol
came into force on 16 February 2005. See also UNFCCC.
Land use (change; direct and indirect): The total of arrangements,
activities and inputs undertaken in a certain land cover type. The social
and economic purposes for which land is managed (e.g., grazing, timber
extraction and conservation).
Land use change occurs whenever land is transformed from one
use to another, for example, from forest to agricultural land or to
urban areas. Since different land types have different carbon storage
potential (e.g., higher for forests than for agricultural or urban
areas), land use changes may lead to net emissions or to carbon
uptake.
Indirect land use change refers to market-mediated or policydriven
shifts in land use that cannot be directly attributed to land
use management decisions of individuals or groups. For example, if
agricultural land is diverted to fuel production, forest clearance may
occur elsewhere to replace the former agricultural production. See
also afforestation, deforestation and reforestation.
Landfill: A solid waste disposal site where waste is deposited below, at
or above ground level. Limited to engineered sites with cover materials,
controlled placement of waste and management of liquids and gases. It
excludes uncontrolled waste disposal. Landfills often release methane,
CO2 and other gases as organic materials decay.
Leapfrogging: The ability of developing countries to bypass intermediate
technologies and jump straight to advanced clean technologies.
Leapfrogging can enable developing countries to move to a low-emissions
development trajectory.
Learning curve / rate: Decreasing cost-prices of renewable energy supplies
shown as a function of increasing (total or yearly) supplies. Learning
improves technologies and processes over time due to experience, as production
increases and/or with increasing research and development. The
learning rate is the percent decrease of the cost-price for every doubling
of the cumulative supplies (also called progress ratio).
Levelized cost of energy – See Cost.
Lifecycle analysis (LCA): LCA aims to compare the full range of environmental
damages of any given product, technology, or service (see Annex II).
LCA usually includes raw material input, energy requirements, and waste
and emissions production. This includes operation of the technology/facility/
product as well as all upstream processes (i.e., those occurring prior to when
the technology/facility/product commences operation) and downstream
processes (i.e., those occurring after the useful lifetime of the technology/
facility/product), as in the ‘cradle to grave’ approach.
Load (electrical): The demand for electricity by (thousands to millions)
power users at the same moment aggregated and raised by the losses in
transport and delivery, and to be supplied by the integrated power supply
system.
Load levelling reduces the amplitude of the load fluctuations over
time.
Load shedding occurs when available generation or transmission
capacity is insufficient to meet the aggregated loads.
Peak load is the maximum load observed over a given period of time
(day, week, year) and of short duration.
Base load is power continuously demanded over the period.
Loans: Loans are money that public or private lenders provide to borrowers
mandated to pay back the nominal sum increased with interest
payments.
Soft loans (also called soft financing or concessional funding) offer
flexible or lenient terms for repayment, usually at lower than market
interest rates or no interest. Soft loans are provided customarily by
government agencies and not by financial institutions.
Convertible loans entitle the lender to convert the loan to common
or preferred stock (ordinary or preference shares) at a specified conversion
rate and within a specified time frame.
Lock-in: Technologies that cover large market shares continue to be used
due to factors such as sunk investment costs, related infrastructure development,
use of complementary technologies and associated social and
institutional habits and structures.
Carbon lock-in means that the established technologies and practices
are carbon intensive.
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Low-carbon technology: A technology that over its lifecycle causes
very low to zero CO2eq emissions. See emissions.
Market failure: When private decisions are based on market prices that
do not reflect the real scarcity of goods and services, they do not generate
an efficient allocation of resources but cause welfare losses. Factors
causing market prices to deviate from real economic scarcity are environmental
externalities, public goods and monopoly power.
Measures: In climate policy, measures are technologies, processes or
practices that reduce greenhouse gas emissions or impacts below anticipated
future levels, for example renewable energy technologies, waste
minimization processes, public transport commuting practices, etc. See
also policies.
Merit order (of power plants): Ranking of all available power generating
units in an integrated power system, being the sequence of their
short-run marginal cost per kWh starting with the cheapest for delivering
electricity to the grid.
Millennium Development Goals (MDG): A set of eight time-bound
and measurable goals for combating poverty, hunger, disease, illiteracy,
discrimination against women and environmental degradation. These
were agreed to at the UN Millennium Summit in 2000 together with an
action plan to reach these goals.
Mitigation: Technological change and changes in activities that reduce
resource inputs and emissions per unit of output. Although several
social, economic and technological policies would produce an emission
reduction, with respect to climate change, mitigation means implementing
policies to reduce greenhouse gas emissions and enhance sinks.
Renewable energy deployment is a mitigation option when avoided
greenhouse gas emissions exceed the sum of direct and indirect emissions
(see emissions).
Mitigation capacity is a country’s ability to reduce anthropogenic
greenhouse gas emissions or to enhance natural sinks, where ability
refers to skills, competencies, fitness and proficiencies that a country
has attained and depends on technology, institutions, wealth,
equity, infrastructure and information. Mitigation capacity is rooted
in a country’s sustainable development path.
Models: Models are structured imitations of a system’s attributes
and mechanisms to mimic appearance or functioning of systems, for
example, the climate, the economy of a country, or a crop. Mathematical
models assemble (many) variables and relations (often in a computer
code) to simulate system functioning and performance for variations in
parameters and inputs.
Bottom-up models aggregate technological, engineering and cost
details of specific activities and processes.
Top-down models apply macroeconomic theory, econometric and
optimization techniques to aggregate economic variables, like total
consumption, prices, incomes and factor costs.
Hybrid models integrate bottom-up and top-down models to some
degree.
Non-Annex I countries – See Annex I countries.
Non-Annex B countries – See Annex B countries.
Ocean energy: Energy obtained from the ocean via waves, tidal ranges,
tidal and ocean currents, and thermal and saline gradients (note: submarine
geothermal energy is covered under geothermal energy and
marine biomass is covered under biomass energy).
Offset (in climate policy): A unit of CO2-equivalent (CO2eq) that is
reduced, avoided or sequestered to compensate for emissions occurring
elsewhere.
Opportunities: In general: conditions that allow for advancement,
progress or profit. In the policy context, circumstances for action with
the attribute of a chance character. For example, the anticipation of
additional benefits that may go along with the deployment of renewable
energy (enhanced energy access and energy security, reduced local
air pollution) but are not intentionally targeted. See also co-benefits and
drivers.
Path dependence: Outcomes of a process are conditioned by previous
decisions, events and outcomes, rather than only by current actions.
Choices based on transitory conditions can exert a persistent impact
long after those conditions have changed.
Payback: Mostly used in investment appraisal as financial payback,
which is the time needed to repay the initial investment by the returns of
a project. A payback gap exists when, for example, private investors and
micro-financing schemes require higher profitability rates from renewable
energy projects than from fossil-fired ones. Imposing an x-times
higher financial return on renewable energy investments is equivalent
to imposing an x-times higher technical performance hurdle on delivery
by novel renewable solutions compared to incumbent energy expansion.
Energy payback is the time an energy project needs to deliver as much
energy as had been used for setting the project online. Carbon payback
is the time a renewable energy project needs to deliver as much
net greenhouse gas savings (with respect to the fossil reference energy
system) as its realization has caused greenhouse gas emissions from a
perspective of lifecycle analysis (including land use changes and loss of
terrestrial carbon stocks).
Photosynthesis: The production of carbohydrates in plants, algae and
some bacteria using the energy of light. CO2 is used as the carbon source.
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Photovoltaics (PV): The technology of converting light energy directly
into electricity by mobilizing electrons in solid state devices. The specially
prepared thin sheet semiconductors are called PV cells. See solar
energy.
Policies: Policies are taken and/or mandated by a government—often
in conjunction with business and industry within a single country, or collectively
with other countries—to accelerate mitigation and adaptation
measures. Examples of policies are support mechanisms for renewable
energy supplies, carbon or energy taxes, fuel efficiency standards for
automobiles, etc.
Common and co-ordinated or harmonized policies refer to
those adopted jointly by parties. See also measures.
Policy criteria: General: a standard on which a judgment or decision
may be based. In the context of policies and policy instruments to support
renewable energy, four inclusive criteria are common:
Effectiveness (efficacy) is the extent to which intended objectives
are met, for instance the actual increase in the output of renewable
electricity generated or shares of renewable energy in total energy
supplies within a specified time period. Beyond quantitative targets,
this may include factors such as achieved degrees of technological
diversity (promotion of different renewable energy technologies) or
of spatial diversity (geographical distribution of renewable energy
supplies).
Efficiency is the ratio of outcomes to inputs, for example, renewable
energy targets realized for economic resources spent, mostly
measured at one point of time (static efficiency), also called costeffectiveness.
Dynamic efficiency adds a future time dimension by
including how much innovation is triggered to improve the ratio of
outcomes to inputs.
Equity covers the incidence and distributional consequences of a
policy, including fairness, justice and respect for the rights of indigenous
peoples. The equity criterion looks at the distribution of costs
and benefits of a policy and at the inclusion and participation of
wide ranges of different stakeholders (e.g., local populations, independent
power producers).
Institutional feasibility is the extent to which a policy or policy
instrument is seen as legitimate, able to gain acceptance, and able
to be adopted and implemented. It covers administrative feasibility
when compatible with the available information base and
administrative capacity, legal structure and economic realities.
Political feasibility needs acceptance and support by stakeholders,
organizations and constituencies, and compatibility with prevailing
cultures and traditions.
Polluter pays principle: In 1972 the OECD agreed that polluters should
pay the costs of abating the own environmental pollution, for example
by installation of filters, sanitation plants and other add-on techniques.
This is the narrow definition. The extended definition is when polluters
would additionally pay for the damage caused by their residual pollution
(eventually also historical pollution). Another extension is the precautionary
polluter pays principle where potential polluters are mandated
to take insurance or preventive measures for pollution that may occur in
the future. The acronym PPP has also other meanings, such as Preventing
Pollution Pays-off, Public Private Partnership, or Purchasing Power Parity.
Portfolio analysis: Examination of a collection of assets or policies that
are characterized by different risks and payoffs. The objective function is
built up around the variability of returns and their risks, leading up to the
decision rule to choose the portfolio with highest expected return.
Potential: Several levels of renewable energy supply potentials can be
identified, although every level may span a broad range. In this report,
resource potential encompasses all levels for a specific renewable
energy resource.
Market potential is the amount of renewable energy output
expected to occur under forecast market conditions, shaped by private
economic agents and regulated by public authorities. Private
economic agents realize private objectives within given, perceived
and expected conditions. Market potentials are based on expected
private revenues and expenditures, calculated at private prices
(incorporating subsidies, levies and rents) and with private discount
rates. The private context is partly shaped by public authority policies.
Economic potential is the amount of renewable energy output
projected when all social costs and benefits related to that output
are included, there is full transparency of information, and assuming
exchanges in the economy install a general equilibrium characterized
by spatial and temporal efficiency. Negative externalities and
co-benefits of all energy uses and of other economic activities are
priced. Social discount rates balance the interests of consecutive
human generations.
Sustainable development potential is the amount of renewable
energy output that would be obtained in an ideal setting of perfect
economic markets, optimal social (institutional and governance)
systems and achievement of the sustainable flow of environmental
goods and services. This is distinct from economic potential because
it explicitly addresses inter- and intra-generational equity (distribution)
and governance issues.
Technical potential is the amount of renewable energy output
obtainable by full implementation of demonstrated technologies or
practices. No explicit reference to costs, barriers or policies is made.
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Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
Technical potentials reported in the literature being assessed in this
report, however, may have taken into account practical constraints
and when explicitly stated there, they are generally indicated in the
underlying report.
Theoretical potential is derived from natural and climatic (physical)
parameters (e.g., total solar irradiation on a continent’s surface).
The theoretical potential can be quantified with reasonable accuracy,
but the information is of limited practical relevance. It represents the
upper limit of what can be produced from an energy resource based
on physical principles and current scientific knowledge. It does not
take into account energy losses during the conversion process necessary
to make use of the resource, nor any kind of barriers.
Power: Power is the rate in which energy is transferred or converted per
unit of time or the rate at which work is done. It is expressed in watts
(joules/second).
Present value: The value of a money amount differs when the amount
is available at different moments in time (years). To make amounts at
differing times comparable and additive, a date is fixed as the ‘present.’
Amounts available at different dates in the future are discounted back
to a present value, and summed to get the present value of a series of
future cash flows. Net present value is the difference between the
present value of the revenues (benefits) and the present value of the
costs. See also discounting.
Project cost – see Cost.
Progress ratio – see Learning curve / rate.
Public finance: Public support for which a financial return is expected
(loans, equity) or financial liability is incurred (guarantee).
Public good: Public goods are simultaneously used by several parties
(opposite to private goods). Some public goods are fully free from
rivalry in use; for others the use by some subtract from the availability
for others, creating congestion. Access to public goods may be restricted
dependent on whether public goods are commons, state-owned or res
nullius (no one’s case). The atmosphere and climate are the ultimate
public goods of mankind. Many renewable energy sources are also public
goods.
Public-private partnerships: Arrangements typified by joint working
between the public and private sector. In the broadest sense, they cover
all types of collaboration across the interface between the public and
private sectors to deliver services or infrastructure.
Quota (on renewable electricity/energy): Established quotas
obligate designated parties (generators or suppliers) to meet minimum
(often gradually increasing) renewable energy targets, generally
expressed as percentages of total supplies or as an amount of renewable
energy capacity, with costs borne by consumers. Various countries use
different names for quotas, for example, Renewable Portfolio Standards,
Renewable Obligations. See also tradable certificates
Reactive power: The part of instantaneous power that does no real
work. Its function is to establish and sustain the electric and magnetic
fields required to let active power perform useful work.
Rebound effect: After implementation of efficient technologies and
practices, part of the expected energy savings is not realized because
the accompanying savings in energy bills may be used to acquire more
energy services. For example, improvements in car engine efficiency
lower the cost per kilometre driven, encouraging consumers to drive
more often or longer distances, or to spend the saved money on other
energy-consuming activities. Successful energy efficiency policies may
lead to lower economy-wide energy demand and if so to lower energy
prices with the possibility of the financial savings stimulating rebound
effects. The rebound effect is the ratio of non-realized energy and
resource savings compared to the potential savings in case consumption
would have remained constant as before the efficiency measures were
implemented. For climate change, the main concern about rebound
effects is their impact on CO2 emissions (carbon rebound).
Reforestation: Direct human-induced conversion of non-forested land
to forested land through planting, seeding and/or the human-induced
promotion of natural seed sources, on land that was previously forested
but converted to non-forested land. See also afforestation, deforestation
and land use.
Regulation: A rule or order issued by governmental executive authorities
or regulatory agencies and having the force of law. Regulations
implement policies and are mostly specific for particular groups of
people, legal entities or targeted activities. Regulation is also the act
of designing and imposing rules or orders. Informational, transactional,
administrative and political constraints in practice limit the regulator’s
capability for implementing preferred policies.
Reliability: In general: reliability is the degree of performance according
to imposed standards or expectations.
Electrical reliability is the absence of unplanned interruptions of
the current by, for example, shortage of supply capacity or by failures
in parts of the grid. Reliability differs from security and from
fluctuations in power quality due to impulses or harmonics.
Renewable energy – see Energy
Scenario: A plausible description of how the future may develop based
on a coherent and internally consistent set of assumptions about key
relationships and driving forces (e.g., rate of technological change,
prices) on social and economic development, energy use, etc. Note that
scenarios are neither predictions nor forecasts, but are useful to provide
a view of the implications of alternative developments and actions. See
also baseline, business as usual, models.
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Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
Seismicity: The distribution and frequency of earthquakes in time, magnitude
and space, for example, the yearly number of earthquakes of
magnitude between 5 and 6 per 100 km2 or in some region.
Sink: Any process, activity or mechanism that removes a greenhouse
gas or aerosol, or a precursor of a greenhouse gas or aerosol, from the
atmosphere.
Solar collector: A device for converting solar energy to thermal energy
(heat) of a flowing fluid.
Solar energy: Energy from the Sun that is captured either as heat, as
light that is converted into chemical energy by natural or artificial photosynthesis,
or by photovoltaic panels and converted directly into electricity.
Concentrating solar power (CSP) systems use either lenses or
mirrors to capture large amounts of solar energy and focus it down
to a smaller region of space. The higher temperatures produced can
operate a thermal steam turbine or be used in high-temperature
industrial processes.
Direct solar energy refers to the use of solar energy as it arrives at
the Earth’s surface before it is stored in water or soils.
Solar thermal is the use of direct solar energy for heat end-uses,
excluding CSP.
Active solar needs equipment like panels, pumps and fans to collect
and distribute the energy.
Passive solar is based on structural design and construction techniques
that enable buildings to utilize solar energy for heating,
cooling and lighting by non-mechanical means.
Solar irradiance: The rate of solar power incidence on a surface (W/
m2). Irradiance depends on the orientation of the surface, with as special
orientations: (a) surfaces perpendicular to the beam solar radiation; (b)
surfaces horizontal with or on the ground. Full sun is solar irradiance
that is approximately 1,000 W/m2.
Solar radiation: The sun radiates light and heat energy in wavelengths
from ultraviolet to infrared. Radiation arriving at surfaces may be
absorbed, reflected or transmitted.
Global solar radiation consists of beam (arriving on Earth in a
straight line) and diffuse radiation (arriving on Earth after being
scattered by the atmosphere and by clouds).
Standards: Set of rules or codes mandating or defining product performance
(e.g., grades, dimensions, characteristics, test methods and rules
for use).
Product, technology or performance standards establish minimum
requirements for affected products or technologies.
Subsidy: Direct payment from the government or a tax reduction to
a private party for implementing a practice the government wishes to
encourage. The reduction of greenhouse gas emissions is stimulated
by lowering existing subsidies that have the effect of raising emissions
(such as subsidies for fossil fuel use) or by providing subsidies for practices
that reduce emissions or enhance sinks (e.g., renewable energy
projects, insulation of buildings or planting trees).
Sustainable development (SD): The concept of sustainable development
was introduced in the World Conservation Strategy of the
International Union for Conservation of Nature in 1980 and had its
roots in the concept of a sustainable society and in the management of
renewable resources. Adopted by the World Council for Environment and
Development in 1987 and by the Rio Conference in 1992 as a process
of change in which the exploitation of resources, the direction of investments,
the orientation of technological development and institutional
change are all in harmony and enhance both current and future potential
to meet human needs and aspirations. SD integrates the political,
social, economic and environmental dimensions, and respects resource
and sink constraints.
Tax: A carbon tax is a levy on the carbon content of fossil fuels. Because
virtually all of the carbon in fossil fuels is ultimately emitted as CO2,
a carbon tax is equivalent to an emission tax on CO2 emissions. An
energy tax—a levy on the energy content of fuels—reduces demand
for energy and so reduces CO2 emissions from fossil fuel use. An ecotax
is a carbon, emissions or energy tax designed to influence human
behaviour (specifically economic behaviour) to follow an ecologically
benign path. A tax credit is a reduction of tax in order to stimulate
purchasing of or investment in a certain product, like greenhouse gas
emission-reducing technologies. A levy or charge is used as synonymous
for tax.
Technological change: Mostly considered as technological improvement,
that is, more or better goods and services can be provided from a
given amount of resources (production factors). Economic models distinguish
autonomous (exogenous), endogenous and induced technological
change.
Autonomous (exogenous) technological change is imposed
from outside the model (i.e., as a parameter), usually in the form of a
time trend affecting factor or/and energy productivity and therefore
energy demand or output growth.
Endogenous technological change is the outcome of economic
activity within the model (i.e., as a variable) so that factor productivity
or the choice of technologies is included within the model and
affects energy demand and/or economic growth.
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Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
Induced technological change implies endogenous technological
change but adds further changes induced by policies and measures,
such as carbon taxes triggering research and development efforts.
Technology: The practical application of knowledge to achieve particular
tasks that employs both technical artefacts (hardware, equipment)
and (social) information (‘software’, know-how for production and use
of artefacts).
Supply push aims at developing specific technologies through support
for research, development and demonstration.
Demand pull is the practice of creating market and other incentives
to induce the introduction of particular sets of technologies (e.g.,
low-carbon technologies through carbon pricing) or single technologies
(e.g., through technology-specific feed-in tariffs).
Technology transfer: The exchange of knowledge, hardware and associated
software, money and goods among stakeholders, which leads to
the spread of technology for adaptation or mitigation. The term encompasses
both diffusion of technologies and technological cooperation
across and within countries.
Tradable certificates (tradable green certificates): Parties subject
to a renewable energy quota meet the annual obligation by delivering
the appropriate amount of tradable certificates to a regulatory office.
The certificates are created by the office and assigned to the renewable
energy producers to sell or for their own use in fulfilling their quota. See
quota.
Transmission and distribution (electricity): The network that transmits
electricity through wires from where it is generated to where it is
used. The distribution system refers to the lower-voltage system that
actually delivers the electricity to the end user. See also grid.
Turbine: Equipment that converts the kinetic energy of a flow of air,
water, hot gas or steam into rotary mechanical power, used for direct
drive or electricity generation (see wind, hydro, gas or steam turbines).
Condensing steam turbines exhaust depleted steam in a heat
exchanger (called condenser) using ambient cooling from water (river,
lake, sea) or air sources (cooling towers). A backpressure steam turbine
has no condenser at ambient temperature conditions, but exhausts
all steam at higher temperatures for use in particular heat end-uses.
United Nations Framework Convention on Climate Change
(UNFCCC): The Convention was adopted on 9 May 1992 in New York
and signed at the 1992 Earth Summit in Rio de Janeiro by more than 150
countries and the European Economic Community. Its ultimate objective
is the “stabilization of greenhouse gas concentrations in the atmosphere
at a level that would prevent dangerous anthropogenic interference
with the climate system”. It contains commitments for all parties. Under
the Convention, parties included in Annex I aimed to return greenhouse
gas emissions not controlled by the Montreal Protocol to 1990 levels by
the year 2000. The convention came into force in March 1994. In 1997,
the UNFCCC adopted the Kyoto Protocol. See also Annex I countries,
Annex B countries and Kyoto Protocol.
Valley of death: Expression for a phase in the development of some
technology when it is generating a large and negative cash flow because
development costs increase but the risks associated with the technology
are not reduced enough to entice private investors to take on the financing
burden.
Value added: The net output of a sector or activity after adding up all
outputs and subtracting intermediate inputs.
Values: Worth, desirability or utility based on individual preferences.
Most social science disciplines use several definitions of value. Related
to nature and environment, there is a distinction between intrinsic and
instrumental values, the latter assigned by humans. Within instrumental
values, there is an unsettled catalogue of different values, such as (direct
and indirect) use, option, conservation, serendipity, bequest, existence,
etc.
Mainstream economics define the total value of any resource as the
sum of the values of the different individuals involved in the use of the
resource. The economic values, which are the foundation of the estimation
of costs, are measured in terms of the willingness to pay by
individuals to receive the resource or by the willingness of individuals to
accept payment to part with the resource.
Vent (geothermal/hydrothermal/submarine): An opening at the surface
of the Earth (terrestrial or submarine) through which materials and
energy flow.
Venture capital: A type of private equity capital typically provided for
early-stage, high-potential technology companies in the interest of generating
a return on investment through a trade sale of the company or
an eventual listing on a public stock exchange.
Well-to-tank (WTT): WTT includes activities from resource extraction
through fuel production to delivery of the fuel to vehicle. Compared
to WTW, WTT does not take into consideration fuel use in vehicle
operations.
Well-to-wheel (WTW): WTW analysis refers to specific lifecycle analysis
applied to transportation fuels and their use in vehicles. The WTW
stage includes resource extraction, fuel production, delivery of the fuel
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Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
to vehicle, and end use of fuel in vehicle operations. Although feedstocks
for alternative fuels do not necessarily come from a well, the WTW terminology
is adopted for transportation fuel analysis.
Wind energy: Kinetic energy from air currents arising from uneven heating
of the Earth’s surface. A wind turbine is a rotating machine including
its support structure for converting the kinetic energy to mechanical shaft
energy to generate electricity. A windmill has oblique vanes or sails and
the mechanical power obtained is mostly used directly, for example, for
water pumping. A wind farm, wind project or wind power plant is a
group of wind turbines interconnected to a common utility system through
a system of transformers, distribution lines, and (usually) one substation.
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Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
Acronyms
AA-CAES Advanced adiabatic compressed air energy storage
AC Alternating current
AEM Anion exchange membrane
AEPC Alternative Energy Promotion Centre
AFEX Ammonia fibre expansion
APU Auxiliary power unit
AR4 4th assessment report (of the IPCC)
AR5 5th assessment report (of the IPCC)
BC Black carbon
BCCS Biological carbon sequestration
Bio-CCS Biomass with carbon capture and storage
BIPV Building-integrated photovoltaic
BMU Bundesministerium für Umwelt, Naturschutz und
Reaktorsicherheit (German Federal Ministry for the
Environment, Nature Conservation and Nuclear
Safety)
BNEF Bloomberg New Energy Finance
BOS Balance of systems
BSI Better Sugarcane Initiative
CAES Compressed air energy storage
CBP Consolidated bioprocessing
CC Combined cycle
CCIY China Coal Industry Yearbook
CCS Carbon dioxide capture and storage
CDM Clean Development Mechanism
CEM Cation exchange membrane
CER Certified Emissions Reduction
CF Capacity factor
CFB Circulating fluid bed
CFD Computational fluid dynamics
CFL Compact fluorescent lightbulb
CHP Combined heat and power
CIGSS Copper indium/gallium disulfide/(di)selenide
CIS Commonwealth of Independent States
CMA China’s Meteorological Administration
CNG Compressed natural gas
CoC Chain of custody
COP Coefficient of performance
CPP Captive power plant
CPV Concentrating photovoltaics
CREZ Competitive renewable energy zone
CRF Capital recovery factor
CSIRO Commonwealth Scientific and Industrial Research
Organisation
CSP Concentrating solar power
CPV Concentrating photovoltaics
CSTD Commission on Science and Technology (UN)
DALY Disability-adjusted life year
dBA A-weighted decibels
DC Direct current or district cooling
DDG Distillers dried grains
DDGS Distillers dried grains plus solubles
DH District heating
DHC District heating or cooling
DHW Domestic hot water
DLR Deutsches Zentrum für Luft- und Raumfahrt
(German Aerospace Centre)
DLUC Direct land use change
DME Dimethyl ether
DNI Direct-normal irradiance
DPH Domestic pellet heating
DSSC Dye-sensitized solar cell
EGS Enhanced geothermal systems
EGTT Expert Group on Technology Transfer
EIA Energy Information Administration (USA)
EIT
EMEC
Economy In Transition
European Marine Energy Centre
EMF Energy Modelling Form
EMI Electromagnetic interference
ENSAD Energy-Related Severe Accident Database
EPRI Electric Power Research Institute (USA)
EPT Energy payback time
E[R] Energy [R]evolution
ER Energy ratio
ERCOT Electric Reliability Council of Texas
EREC European Renewable Energy Council
EROEI Energy return on energy investment
ESMAP Energy Sector Management Program (World Bank)
ETBE Ethyl tert-butyl ether
ETP Energy Technology Perspectives
EU European Union
EV Electric vehicle
FACTS Flexible AC transmission system
FASOM Forest and Agricultural Sector Optimization Model
FAO Food and Agriculture Organization (of the UN)
FFV Flexible fuel vehicle
FQD Fuel quality directive
FIT Feed-in tariff
FOGIME Crediting System in Favour of Energy Management
FRT Fault ride through
FSU Former Soviet Union
FTD Fischer-Tropsch diesel
GBD Global burden of disease
GBEP Global Bioenergy Partnership
GCAM Global Change Assessment Model
GCM Global climate model; General circulation model
GDP
GEF
GHG
GHP
Gross domestic product
Global Environment Facility
Greenhouse gas
Geothermal heat pump
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Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
GIS Geographic information system
GM Genetically modified
GMO Genetically modified organism
GO Guarantee of origin
GPI Genuine progress indicator
GPS Global positioning system
GSHP Ground source heat pump
HANPP Human appropriation of terrestrial NPP
HCE Heat collection element
HDI Human Development Index
HDR Hot dry rock
HDV Heavy duty vehicle
HFCV Hydrogen fuel cell electric vehicle
HFR Hot fractured rock
HHV Higher heating value
HPP Hydropower plant
HRV Heat recovery ventilator
HEV Hybrid electric vehicle
HVAC Heating, ventilation and air-conditioning
HVDC High voltage direct current
HWR Hot wet rock
IA Impact assessment
IAP Indoor air pollution
IBC interdigitated back-contact
ICE Internal combustion engine
ICEV Internal combustion engine vehicle
ICLEI Local Governments for Sustainability
ICOLD International Commission on Large Dams
ICS Improved cookstove or Integral collector storage (Ch 3)
ICTSD International Centre for Trade and Sustainable
Development
IEA International Energy Agency
IEC International Electrotechnical Commission
IEEE Institute of Electrical and Electronics Engineers
IHA International Hydropower Association
ILUC Indirect land use change
IGCC Integrated gasification combined cycle
IPCC Intergovernmental Panel on Climate Change
IPR Intellectual property rights
IQR Inter-quartile range
IREDA Indian Renewable Energy Development Agency
IRENA International Renewable Energy Agency
IRM Inorganic mineral raw materials
ISCC Integrated solar combined-cycle
ISES International Solar Energy Society
ISEW Index of sustainable economic welfare
ISO International Organization for Standardization
J Joule
JI Joint implementation
LCA Lifecycle assessment
LCOE Levelized cost of energy (or of electricity)
LCOF Levelized cost of fuel
LCOH Levelized cost of heat
LDV Light duty vehicle
LED Light-emitting diode
LHV Lower heating value
LNG Liquefied natural gas
LPG Liquefied petroleum gas
LR Learning rate
LUC Land use change
M&A Mergers and acquisitions
MDG Millennium Development Goals
MEH Multiple-effect humidification
MHS Micro-hydropower systems
MITI Ministry of International Trade and Industry (Japan)
MSW Municipal solid waste
NASA National Aeronautics and Space Administration (USA)
NDRC National Development and Reform Commission
(China)
NFFO Non Fossil Fuel Obligation
NG Natural gas
NGO Nongovernmental organization
Nm3 Normal cubic metre (of gas) at standard temperature
and pressure
NMVOC Non-methane volatile organic compounds
NPP Net primary production
NPV Net present value
NRC National Research Council (USA)
NREL National Renewable Energy Laboratory (USA)
NSDS National Sustainable Development Strategies
O&M Operation and maintenance
OB Oscillating-body
OC Organic carbon
OECD Organisation for Economic Co-operation and
Development
OM Organic matter
OPV Organic photovoltaic
ORC Organic Rankine Cycle
OTEC Ocean thermal energy conversion
OWC Oscillating water column
PACE Property Assessed Clean Energy
PBR Photobioreactor
PCM Phase-change material
PDI Power density index
PEC Photoelectrochemical
PHEV Plug-in hybrid electric vehicle
PM Particulate matter
POME Palm oil mill effluent
PPA Purchase power agreement
PRO
PROALCOOL
PSA
PSI
Pressure-retarded osmosis
Brazilian Alcohol Program
Probabilistic safety assessment
Paul Scherrer Institute
PSP Pumped storage plants
PTC Production tax credit
PV Photovoltaic
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Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
PV/T Photovoltaic/thermal
PWR Pressurized water reactor
R&D Research and development
RBMK Reaktor bolshoy moshchnosty kanalny
RCM Regional climate model
RD&D Research, development and demonstration
R/P Reserves to current production (ratio)
RD Renewable diesel
RE Renewable energy
RE-C Renewable energy cooling
RE-H Renewable energy heating
RE-H/C Renewable energy heating/cooling
REC Renewable energy certificate
RED Reversed electro dialysis
REN21 Renewable Energy Policy Network for the 21st
Century
RES Renewable electricity standard
RM&U Renovation, modernization and upgrading
RMS Root mean square
RNA Rotor nacelle assembly
RO Renewables obligation
RoR Run of river
RPS Renewable portfolio standard
RSB Roundtable for Sustainable Biofuels
SCADA Supervisory control and data acquisition
SCC Stress corrosion cracking
SD Sustainable development
SEGS Solar Electric Generating Station (California)
SHC Solar heating and cooling
SHP Small-scale hydropower plant
SI Suitability index
SME Small and medium sized enterprises
SNG Synthesis gas
SNV Netherlands Development Organization
SPF Seasonal performance factor
SPM Summary for Policymakers
SPP Small power producer
SPS Sanitary and phytosanitary
SR Short rotation
SRES Special Report on Emission Scenarios (of the IPCC)
SRREN Special Report on Renewable Energy Sources and
Climate Change Mitigation (of the IPCC)
SSCF Simultaneous saccharification and co-fermentation
SSF Simultaneous saccharification and fermentation
SSP Space-based solar power
STP Standard temperature and pressure
SWH Solar water heating
TBM Tunnel-boring machines
TERM Tonga Energy Roadmap
TGC Tradable green certificate
TPA Third-party access
TPES Total primary energy supply
TPWind European Wind Energy Technology Platform
TS Technical Summary or thermosyphon
US United States of America (adjective)
USA United States of America (noun)
UN United Nations
UNCED United Nations Conference on Environment and
Development
UNCTAD United Nations Conference on Trade and
Development
UNDP United Nations Development Programme
UNEP United Nations Environment Programme
UNFCCC United Nations Framework Convention on Climate
Change
USD US dollar
USDOE US Department of Energy
V Volt
VKT Vehicle kilometres travelled
VRB Vanadium redox battery
W Watt
We Watt of electricity
Wp Watt peak of PV installation
WBG World Bank Group
WCD World Commission on Dams
WCED World Commission on Environment and Development
WEA World Energy Assessment
WEO World Energy Outlook
WindPACT Wind Partnership for Advanced Component
Technologies
WTO World Trade Organization
WTW Well to wheel
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Annex I Glossary, Acronyms, Chemical Symbols and Prefixes
Prefixes (International Standard Units)
Symbol Multiplier Prefix Symbol Multiplier Prefix
Z 10 21 zetta d 10 -1 deci
E 1018 exa c 10 -2 centi
P 1015 peta m 10 -3 milli
T 1012 tera μ 10 -6 micro
G 10 9 giga n 10 -9 nano
M 10 6 mega p 10 -12 pico
k 10 3 kilo f 10 -15 femto
h 10 2 hecto a 10 -18 atto
da 10 deca
Chemical Symbols
a-Si Amorphous silicon
C Carbon
CdS Cadmium sulphide
CdTe Cadmium telluride
CH4 Methane
CH3CH2OH Ethanol
CH3OCH3 Dimethyl ether (DME)
CH3OH Methanol
CIGS(S) Copper indium gallium diselenide (disulfide)
Cl Chlorine
CO Carbon monoxide
CO2 Carbon dioxide
CO2eq Carbon dioxide equivalent
c-Si Crystalline silicon
Cu Copper
CuInSe2 Copper indium diselenide
DME Dimethyl ether
Fe Iron
GaAs Gallium arsenide
H2 Hydrogen gas
H2O Water
H2S Hydrogen sulphide
HFC Hydrofluorocarbons
K Potassium
Mg Magnesium
N Nitrogen
N2 Nitrogen gas
N2O Nitrous oxide
Na Sodium
NaS Sodium-sulfur
NH3 Ammonia
Ni Nickel
NiCd Nickel-cadmium
NOX Nitrous oxides
O3 Ozone
P Phosphorus
PFC Perfluorocarbon
SF6 Sulfur hexafluoride
Si Silicon
SiC Silicon carbide
SO2 Sulfur dioxide
ZnO Zinc oxide
180
Glossary, Acronyms, Chemical Symbols and Prefixes Annex I
II ANNEX
Methodology
Lead Authors:
William Moomaw (USA), Peter Burgherr (Switzerland), Garvin Heath (USA),
Manfred Lenzen (Australia, Germany), John Nyboer (Canada), Aviel Verbruggen (Belgium)
This annex should be cited as:
Moomaw, W., P. Burgherr, G. Heath, M. Lenzen, J. Nyboer, A. Verbruggen, 2011: Annex II: Methodology. In IPCC
Special Report on Renewable Energy Sources and Climate Change Mitigation [O. Edenhofer,
R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen,
S. Schlömer, C. von Stechow (eds)], Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA.
181
182
Methodology Annex II
Table of Contents
A.II.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A.II.2 Metrics for analysis in this report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A.II.3 Financial assessment of technologies over project lifetime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A.II.3.1 Constant (real) values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A.II.3.2 Discounting and net present value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
A.II.3.3 Levelized cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
A.II.3.4 Annuity factor or capital cost recovery factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
A.II.4 Primary energy accounting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
A.II.5 Lifecycle assessment and risk analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
A.II.5.1 Energy payback time and energy ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
A.II.5.2 Review of lifecycle assessments of electricity generation technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
A.II.5.2.1 Review methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
A.II.5.2.2 List of references . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
A.II.5.3 Review of operational water use of electricity generation technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
A.II.5.3.1 Review methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
A.II.5.3.2 List of references . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
A.II.5.4 Risk analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
A.II.6 Regional definitions and country groupings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
A.II.7 General conversion factors for energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
Annex II Methodology
183
or resources comparable, at least in terms of costs, costs that may
occur at various moments in time (e.g., in various years) are represented
as a single number anchored at one particular year, the reference
year (2005). Textbooks on investment appraisal provide background on
the concepts of constant values, discounting, net present value calculations,
and levelized costs, for example (Jelen and Black, 1983).
A.II.3.1 Constant (real) values
The analyses of costs are in constant or real1 dollars (i.e., excluding the
impacts of inflation) based in a particular year, the base year 2005,
in USD. Specific studies on which the report depends may use market
exchange rates as a default option or use purchasing power parities,
but where these are part of the analysis, they will be stated clearly and,
where possible, converted to USD2005.
When the monetary series in the analyses are in real dollars, consistency
requires that the discount rate should also be real (free of inflationary components).
This consistency is often not obeyed; studies refer to ‘observed
market interest rates’ or ‘observed discount rates’, which include inflation
or expectations about inflation. ‘Real/constant’ interest rates are never
directly observed, but derived from the ex-post identity:
(1+ m) = (1+ i ) × (1+ f ) (1)
where
m = nominal rate (%)
i = real or constant rate (%)
f = inflation rate (%)
The reference year for discounting and the base year for anchoring
constant prices may differ in studies used in the various chapters;
where possible, an attempt was made to harmonize the data to reflect
discount rates applied here.
A.II.3.2 Discounting and net present value
Private agents assign less value to things further in the future than to
things in the present because of a ‘time preference for consumption’
or to reflect a ‘return on investment’. Discounting reduces future cash
flows by a value less than 1. Applying this rule on a series of net cash
flows in real USD, the net present value (NPV) of the project can be
ascertained and, thus, compared to other projects using:
(2)
where
n = lifetime of the project
i = discount rate
1 The economists’ term ‘real’ may be confusing because what they call real does not
correspond to observed financial flows (‘nominal’, includes inflation); ‘real’ reflects
the actual purchasing power of the flows in constant dollars.
NPV =
j
n
=
0
Net cas h flow s ( j)
(1+i ) j
A.II.1 Introduction
Parties need to agree upon common data, standards, supporting theories
and methodologies. This annex summarizes a set of agreed upon
conventions and methodologies. These include the establishment of
metrics, determination of a base year, definitions of methodologies and
consistency of protocols that permit a legitimate comparison between
alternative types of energy in the context of climate change phenomena.
This section defines or describes these fundamental definitions and
concepts as used throughout this report, recognizing that the literature
often uses inconsistent definitions and assumptions.
This report communicates uncertainty where relevant, for example, by
showing the results of sensitivity analyses and by quantitatively presenting
ranges in cost numbers as well as ranges in the scenario results. This
report does not apply formal IPCC uncertainty terminology because at
the time of approval of this report, IPCC uncertainty guidance was in the
process of being revised.
A.II.2 Metrics for analysis in this report
A number of metrics can simply be stated or are relatively easy to define.
Annex II provides the set of agreed upon metrics. Those which require
further description are found below. The units used and basic parameters
pertinent to the analysis of each RE type in this report include:
• International System of Units (SI) for standards and units
• Metric tonnes (t) CO2, CO2eq
• Primary energy values in exajoules (EJ)
• IEA energy conversion factors between physical and energy units
• Capacity: GW thermal (GWt ), GW electricity (GWe )
• Capacity factor
• Technical and economic lifetime
• Transparent energy accounting (e.g., transformations of nuclear or
hydro energy to electricity)
• Investment cost in USD/kW (peak capacity)
• Energy cost in USD2005 /kWh or USD2005 /EJ
• Currency values in USD2005 (at market exchange rate where
applicable, no purchasing power parity is used)
• Discount rates applied = 3, 7 and 10%
• World Energy Outlook (WEO) 2008 fossil fuel price assumptions
• Baseline year = 2005 for all components (population, capacity, production,
costs). Note that more recent data may also be included
(e.g., 2009 energy consumption)
• Target years: 2020, 2030 and 2050.
A.II.3 Financial assessment of technologies
over project lifetime
The metrics defined here provides the basis from which one renewable
resource type (or project) can be compared to another. To make projects
184
Methodology Annex II
(CRF) but may be known as the Annuity Factor ‘δ’. Like NPV, the annuity
factor δ depends on the two parameters i and n:
The CRF (or δ) can be used to quickly calculate levelized costs for very
simple projects where investment costs during one given year are the
only expenditures and where production remains constant over the lifetime
(n):
(5)
or where one can assume that operation and maintenance (O&M) costs
do not change from year to year:
(6)
where
CLev = levelized cost
B = investment cost
Q = production
O&M = annual operating and maintenance costs
n = life time of the project
i = discount rate
A.II.4 Primary energy accounting
This section introduces the primary energy accounting method used
throughout this report. Different energy analyses use different accounting
methods that lead to different quantitative outcomes for reporting
both current primary energy use and energy use in scenarios that
explore future energy transitions. Multiple definitions, methodologies
and metrics are applied. Energy accounting systems are utilized in the
literature often without a clear statement as to which system is being
used as noted by Lightfoot, 2007 and Martinot et al., 2007. An overview
of differences in primary energy accounting from different statistics has
been described (Macknick, 2009) and the implications of applying different
accounting systems in long-term scenario analysis were illustrated by
Nakicenovic et al., (1998).
Three alternative methods are predominantly used to report primary
energy. While the accounting of combustible sources, including all fossil
energy forms and biomass, is unambiguous and identical across the different
methods, they feature different conventions on how to calculate
primary energy supplied by non-combustible energy sources, i.e., nuclear
energy and all renewable energy sources except biomass.
These methods are:
• The physical energy content method adopted, for example, by
the Organisation for Economic Cooperation and Development
(OECD), the International Energy Agency (IEA) and Eurostat (IEA/
OECD/Eurostat, 2005),
i ×( + )n 1 i
=
( + )n 1 i –1
C ×Q= B× , or : C = (B )/Q Lev Lev ×
B +
C
Lev Q = × O&M
This report’s analysts have used three values of discount rates ( i = 3, 7
and 10%) for the cost evaluations. The discount rates may reflect typical
rates used, with the higher ones including a risk premium. The discount
rate is open to much discussion and no clear parameter or guideline
can be suggested as an appropriate risk premium. This discussion is not
addressed here; the goal is to provide an appropriate means of comparison
between projects, renewable energy types and new versus current
components of the energy system.
A.II.3.3 Levelized cost
Levelized costs are used in the appraisal of power generation investments,
where the outputs are quantifiable (MWh generated during the
lifetime of the investment). The levelized cost is the unique break-even
cost price where discounted revenues (price x quantities)2 are equal to
the discounted net expenses:
(3)
where
CLev = levelized cost
n = lifetime of the project
i = discount rate
A.II.3.4 Annuity factor or capital cost recovery factor
A very common practice is the conversion of a given sum of money at
moment 0 into a number n of constant annual amounts over the coming
n future years:
Let A = annual constant amount in payments over n years
Let B = cash amount to pay for the project in year 0
A is obtained from B using a slightly modified equation 2: the lender
wants to receive B back at the discount rate i. The NPV of the n times A
receipts in the future therefore must exactly equal B:
(4)
We can bring A before the summation because it is a constant (not
dependent on j).
The sum of the discount factors (a finite geometrical series) is deductible
as a particular number. When this number is calculated, A is found by
dividing B by this number. This is known as the Capital Recovery Factor
2 This is also referred to as Levelized Price. Note that, in this case, MWh would be
discounted.
Expensesj
n
Quantitiesj
j
n
CLev=
=
( i) j 1+
( i) j 1+
j = 0
0
j=1 j=1
B, or :
A
B
n
(1+ i ) j
n 1
= A =
(1+ i ) j
185
Annex II Methodology
• The substitution method, which is used in slightly different variants by
BP (2009) and the US Energy Information Administration (EIA online
glossary), each of which publish international energy statistics, and
• The direct equivalent method that is used by UN Statistics (2010) and
in multiple IPCC reports that deal with long-term energy and emission
scenarios (Nakicenovic and Swart, 2000; Morita et al., 2001; Fisher et
al., 2007).
For non-combustible energy sources, the physical energy content method
adopts the principle that the primary energy form should be the first
energy form used downstream in the production process for which multiple
energy uses are practical (IEA/OECD/Eurostat, 2005). This leads to
the choice of the following primary energy forms:
• Heat for nuclear, geothermal and solar thermal energy; and
• Electricity for hydro, wind, tide/wave/ocean and solar photovoltaic
(PV) energy.
Using this method, the primary energy equivalent of hydropower and
solar PV, for example, assumes a 100% conversion efficiency to ‘primary
electricity’, so that the gross energy input for the source is 3.6 MJ of
primary energy = 1 kWh electricity. Nuclear energy is calculated from the
gross generation by assuming a 33% thermal conversion efficiency,3 that
is, 1 kWh = (3.6 ÷ 0.33) = 10.9 MJ. For geothermal energy, if no countryspecific
information is available, the primary energy equivalent is
calculated using 10% conversion efficiency for geothermal electricity
(so 1 kWh = (3.6 ÷ 0.1) = 36 MJ), and 50% for geothermal heat.
The substitution method reports primary energy from non-combustible
sources as if they had been substituted for combustible energy. Note,
however, that different variants of the substitution method use somewhat
different conversion factors. For example, BP applies a 38%
conversion efficiency to electricity generated from nuclear and hydropower,
whereas the World Energy Council used 38.6% for nuclear and
non-combustible renewable sources (WEC, 1993) and the EIA uses
still different values. Macknick (2009) provides a more complete overview.
For useful heat generated from non-combustible energy sources,
other conversion efficiencies are used.
The direct equivalent method counts one unit of secondary energy provided
from non-combustible sources as one unit of primary energy, that
is, 1 kWh of electricity or heat is accounted for as 1 kWh = 3.6 MJ of
primary energy. This method is mostly used in the long-term scenarios
literature, including multiple IPCC reports (IPCC, 1995; Nakicenovic and
Swart, 2000; Morita et al., 2001; Fisher et al., 2007), because it deals
with fundamental transitions of energy systems that rely to a large
extent on low-carbon, non-combustible energy sources.
3 As the amount of heat produced in nuclear reactors is not always known, the IEA
estimates the primary energy equivalent from the electricity generation by assuming
an efficiency of 33%, which is the average for nuclear power plants in Europe (IEA,
2010b).
In this report, IEA data are utilized, but energy supply is reported using
the direct equivalent method. The major difference between this and the
physical energy content method will appear in the amount of primary
energy reported for electricity production by geothermal heat, concentrating
solar thermal, ocean temperature gradients or nuclear energy.
Table A.II.1 compares the amounts of global primary energy by source
and percentages using the physical energy content, the direct equivalent
and a variant of the substitution method for the year 2008 based on IEA
data (IEA, 2010a). In current statistical energy data, the main differences
in absolute terms appear when comparing nuclear and hydropower.
Since they both produced a comparable amount of electricity globally
in 2008, under both direct equivalent and substitution methods, their
share of meeting total final consumption is similar, whereas under the
physical energy content method, nuclear is reported at about three
times the primary energy of hydropower.
The alternative methods outlined above emphasize different aspects of primary
energy supply. Therefore, depending on the application, one method
may be more appropriate than another. However, none of them is superior
to the others in all facets. In addition, it is important to realize that total
primary energy supply does not fully describe an energy system, but is
merely one indicator amongst many. Energy balances as published by
the IEA (2010a) offer a much wider set of indicators, which allows
tracing the flow of energy from the resource to final energy use. For
instance, complementing total primary energy consumption with other
indicators, such as total final energy consumption and secondary energy
production (e.g., electricity, heat), using different sources helps link the
conversion processes with the final use of energy. See Figure 1.16 and
the associated discussion for a summary of this approach.
For the purpose of this report, the direct equivalent method is chosen for
the following reasons.
• It emphasizes the secondary energy perspective for non-combustible
sources, which is the main focus of the analyses in the technology
chapters (Chapters 2 through 7).
• All non-combustible sources are treated in an identical way by
using the amount of secondary energy they provide. This allows
the comparison of all non-CO2-emitting renewable and nuclear
energy sources on a common basis. Primary energy of fossil fuels
and biomass combines both the secondary energy and the thermal
energy losses from the conversion process. When fossil fuels
or biofuels are replaced by nuclear systems or other renewable
technologies than biomass, the total of reported primary energy
decreases substantially (Jacobson, 2009).
• Energy and CO2 emissions scenario literature that deals with fundamental
transitions of the energy system to avoid dangerous
anthropogenic interference with the climate system over the long
term (50 to 100 years) has used the direct equivalent method most
frequently (Nakicenovic and Swart, 2000; Fisher et al., 2007).
186
Methodology Annex II
Table A.II.2 shows the differences in the primary energy accounting
for the three methods for a scenario that would produce a 550 ppm
CO2eq stabilization by 2100.
While the differences between applying the three accounting methods
to current energy consumption are modest, differences grow
significantly when generating long-term lower CO2 emissions energy
scenarios where non-combustion technologies take on a larger relative
role (Table A.II.2). The accounting gap between the different methods
becomes bigger over time (Figure A.II.1). There are significant differences
in individual non-combustible sources in 2050 and even the
share of total renewable primary energy supply varies between 24 and
37% across the three methods (Table A.II.2). The biggest absolute gap
(and relative difference) for a single source is for geothermal energy,
with about 200 EJ difference between the direct equivalent and the
physical energy content method, and the gap between hydro and
nuclear primary energy remains considerable. The scenario presented
here is fairly representative and by no means extreme. The chosen 550
ppm stabilization target is not particularly stringent nor is the share of
non-combustible energy very high.
A.II.5 Lifecycle assessment and risk analysis
This section describes methods and underlying literature and assumptions
of analyses of energy payback times and energy ratios (A.II.5.1),
Table A.II.2 | Comparison of global total primary energy supply in 2050 using different primary energy accounting methods based on a 550 ppm CO2eq stabilization scenario
(Loulou et al., 2009).
Physical content method Direct equivalent method Substitution method
EJ % EJ % EJ %
Fossil fuels 581.6 55.2 581.56 72.47 581.6 61.7
Nuclear 81.1 7.7 26.76 3.34 70.4 7.8
Renewable: 390.1 37.1 194.15 24.19 290.4 30.8
Bioenergy 120.0 11.4 120.0 15.0 120.0 12.7
Solar 23.5 2.2 22.0 2.8 35.3 3.8
Geothermal 217.3 20.6 22.9 2.9 58.1 6.2
Hydro 23.8 2.3 23.8 3.0 62.6 6.6
Ocean 0.0 0.0 0.0 0.0 0.0 0.0
Wind 5.5 0.5 5.5 0.7 14.3 1.5
Total 1,052.8 100 802.5 100 942.4 100
Table A.II.1 | Comparison of global total primary energy supply in 2008 using different primary energy accounting methods (data from IEA, 2010a).
Physical content method Direct equivalent method Substitution method1
EJ % EJ % EJ %
Fossil fuels 418.15 81.41 418.15 85.06 418.15 79.14
Nuclear 29.82 5.81 9.85 2.00 25.90 4.90
Renewable: 65.61 12.78 63.58 12.93 84.27 15.95
Bioenergy2 50.33 9.80 50.33 10.24 50.33 9.53
Solar 0.51 0.10 0.50 0.10 0.66 0.12
Geothermal 2.44 0.48 0.41 0.08 0.82 0.16
Hydro 11.55 2.25 11.55 2.35 30.40 5.75
Ocean 0.00 0.00 0.00 0.00 0.01 0.00
Wind 0.79 0.15 0.79 0.16 2.07 0.39
Other 0.03 0.01 0.03 0.01 0.03 0.01
Total 513.61 100.00 491.61 100.00 528.35 100.00
Notes:
1 For the substitution method, conversion efficiencies of 38% for electricity and 85% for heat from non-combustible sources were used. BP uses the conversion value of 38% for
electricity generated from hydro and nuclear sources. BP does not report solar, wind and geothermal in its statistics; here, 38% for electricity and 85% for heat is used.
2 Note that IEA reports first-generation biofuels in secondary energy terms (the primary biomass used to produce the biofuel would be higher due to conversion losses, see Sections
2.3 and 2.4).
187
Annex II Methodology
readily understand the percentage or multiple connecting embodied
energy and energy output. Moreover, it has been argued (see Voorspools
et al., (2000, p. 326)) that in the absence of alternative technologies, electricity
would have to be generated by conventional means. We therefore
use kWhe/kWhprim in this report.
Applying the lifecycle energy metric to an energy supply system allows
defining an energy payback time. This is the time tPB that it takes the
system to supply an amount of energy that is equal to its own energy
requirement E. Once again, this energy is best measured in terms of the
primary energy equivalent E
R
PB
conv
of the system’s electricity output EPB
over the payback time. Voorspools et al. (2000, p. 326) note that were
the system to pay back its embodied primary energy in equal amounts
of electricity, energy payback times would be more than three times as
long.
Mathematically, the above condition reads
, and leads to
(which, for example, coincides with the standard German VDI 4600 definition).
Here, is the system’s annual net energy output
expressed in primary energy equivalents. It can be shown that the Energy
Ratio ER (or EROEI) and the energy payback time tPB can be converted
into each other according to
.
Note that the energy payback time is not dependent on the lifetime T,
because
.
Energy payback times have been partly converted from energy ratios
found in the literature (Lenzen, 1999, 2008; Lenzen and Munksgaard,
2002; Lenzen et al., 2006; Gagnon, 2008; Kubiszewski et al., 2010) based
on the assumed average lifetimes given in Table 9.8 (Chapter 9). Note
that energy payback as defined in the glossary (Annex I) and used in
some technology chapters refers to what is defined here as energy payback
time.
A.II.5.2 Review of lifecycle assessments of electricity
generation technologies
The National Renewable Energy Laboratory (NREL) carried out a
comprehensive review of published lifecycle assessments (LCAs) of
P× hy × t
E =
E
R R
PB
conv
PB
conv
8760 −1 ×
=
hy × −1 P ×
E E
E
R
tPB
Rconv conv
= =
8760 out annual
E
Rconv
out annual
= E T =
E
E T R
E R
t T PB
Rconv
Elife
Rconv
= conv
out annual T
P × h ×
t
PB y
E Rconv
=
8760 −1
Figure A.II.1 | Comparison of global total primary energy supply between 2010 and
2100 using different primary energy accounting methods based on a 550 ppm CO2eq
stabilization scenario (Loulou et al., 2009).
Substitution Method
Physical Content Method
Direct Equivalent Method
300
600
900
1,200
1,800
1,500
[EJ]
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
lifecycle GHG emissions (A.II.5.2), operational water use (A.II.5.3) and
hazards and risks (A.II.5.4) of energy technologies as presented in
Chapter 9. Results of the analysis carried out for lifecycle GHG emissions
are also included in Sections 2.5, 3.6, 4.5, 5.6, 6.5 and 7.6. Please
note that the literature bases for the reviews in A.II.5.2 and A.II.5.3 are
included as lists within the respective sections.
A.II.5.1 Energy payback time and energy ratio
The Energy Ratio, ER (also referred to as the energy payback ratio, or the
Energy Return on Energy Investment, EROEI; see Gagnon, 2008), of an
energy supply system of power rating P and load factor λ, is defined as
the ratio
E P× y ×
E E
ER
h = life
8760 × −1
=
T
of the lifetime electricity output Elife of the plant over its lifetime T, and
the total (gross) energy requirement E for construction, operation and
decommissioning (Gagnon, 2008). In calculating E, it is a convention to
a) exclude the energy from human labour, energy in the ground (fossil
and minerals), energy in the sun, and hydrostatic potential, and b) not
to discount future against present energy requirements (Perry et al., 1977;
Herendeen, 1988). Further, in computing the total energy requirement E,
all its constituents must be of the same energy quality (for example only
electricity, or only thermal energy, see the ‘valuation problem’ discussed
in Leach (1975), Huettner (1976), Herendeen (1988), and especially
Rotty et al. (1975, pp. 5-9 for the case of nuclear energy)). Whilst E may
include derived and primary energy forms (for example electricity and
thermal energy), it is usually expressed in terms of primary energy, with
the electricity component converted to primary energy equivalents using
the thermal efficiency Rconv 0.3 of a typical subcritical black-coal-fired
power station as the conversion factor. This report follows these conventions.
E is sometimes reported in units of kWhe/MJprim, and sometimes in
units of kWhe/kWhprim. Whilst the first option chooses the most common
units for either energy form, the second option allows the reader to
hy × −1 P ×
E E
E
R
tPB
Rconv conv
= =
8760 out annual
■
■
188
Methodology Annex II
electricity generation technologies. Of 2,165 references collected, 296
passed screens, described below, for quality and relevance and were
entered into a database. This database forms the basis for the assessment
of lifecycle greenhouse gas (GHG) emissions from electricity generation
technologies in this report. Based on estimates compiled in the database,
plots of published estimates of lifecycle GHG emissions appear in each
technology chapter of this report (Chapters 2 through 7) and in Chapters
1 and 9, where lifecycle GHG emissions from RE technologies are compared
to those from fossil and nuclear electricity generation technologies.
The following subchapters describe the methods applied in this review
(A.II.5.2.1), and list all references that are shown in the final results,
sorted by technology (A.II.5.2.2).
A.II.5.2.1 Review methodology
Broadly, the review followed guidelines for systematic reviews as commonly
performed, for instance, in the medical sciences (Neely et al.,
2010). The methods of reviews in the medical sciences differ somewhat
from those in the physical sciences, in that there is an emphasis on multiple,
independent reviews of each candidate reference using predefined
screening criteria; the formation of a review team composed of, in this
case, LCA experts, technology experts and literature search experts that
meets regularly to ensure consistent application of the screening criteria;
and an exhaustive search of published literature to ensure no bias
by, for instance, publication type (journal, report, etc.).
It is critical to note at the outset that this review did not alter (except
for unit conversion) or audit for accuracy the estimates of lifecycle GHG
emissions published in studies that pass the screening criteria. Additionally,
no attempt was made to identify or screen for outliers, or pass
judgment on the validity of input parameter assumptions. Because
estimates are plotted as published, considerable methodological inconsistency
is inherent, which limits comparability of the estimates both
within particular power generation technology categories and across
the technology categories. This limitation is partially counteracted by
the comprehensiveness of the literature search and the breadth and
depth of literature revealed. Few attempts have been made to broadly
review the LCA literature on electricity generation technologies. Those
that do exist tend to focus on individual technologies and are more limited
in comprehensiveness compared to the present review (e.g., Lenzen
and Munksgaard, 2002; Fthenakis and Kim, 2007; Lenzen, 2008; Sovacool,
2008b; Beerten et al., 2009; Kubiszewski et al., 2010).
The review procedure included the following steps: literature collection,
screening and analysis.
Literature collection
Starting in May of 2009, potentially relevant literature was identified
through multiple mechanisms, including searches in major bibliographic
databases (e.g., Web of Science, WorldCat) using a variety of search algorithms
and combinations of key words, review of reference lists of relevant
literature, and specialized searches on websites of known studies series
(e.g., European Union’s ExternE and its descendants) and known LCA literature
databases (e.g., the library contained within the SimaPro LCA software
package). All collected literature was first categorized by content (with key
information from every collected reference recorded in a database) and
added to a bibliographic database.
The literature collection methods described here apply to all classes of electricity
generation technologies reviewed in this report except for oil and
hydropower. LCA data for hydropower and oil were added at a later stage
to the NREL database and have therefore undergone a less comprehensive
literature collection process.
Literature screening
Collected references were independently subjected to three rounds of
screening by multiple experts to select references that met criteria for quality
and relevance. References often reported multiple GHG emission estimates
based on alternative scenarios. Where relevant, the screening criteria were
applied at the level of the scenario estimate, occasionally resulting in only a
subset of scenarios analyzed in a given reference passing the screens.
References having passed the first quality screen included peer-reviewed
journal articles, scientifically detailed conference proceedings, PhD theses,
and reports (authored by government agencies, academic institutions, nongovernmental
organizations, international institutions, or corporations)
published after 1980 and in English. Attempts were made to obtain English
versions of non-English publications and a few exceptions were translated.
The first screen also ensured that the accepted references were LCAs,
defined as analyzing two or more lifecycle phases (with exceptions for PV
and wind energy given that the literature demonstrates that the vast majority
of lifecycle GHG emissions occur in the manufacturing phase (Frankl et
al., 2005; Jungbluth et al., 2005)).
All references passing the first screen were then directly judged based on
more stringent quality and relevance criteria:
• Employed a currently accepted attributional LCA and GHG accounting
method (consequential LCAs were not included because their results
are fundamentally not comparable to results based on attributional LCA
methods; see Section 9.3.4 for further description of attributional and
consequential LCAs);
• Reported inputs, scenario/technology characteristics, important assumptions
and results in enough detail to trace and trust the results; and
• Evaluated a technology of modern or future relevance.
For the published results to be analyzed, estimates had to pass a final
set of criteria:
• To ensure accuracy in transcription, only GHG emission estimates that
were reported numerically (i.e., not only graphically) were included.
189
Annex II Methodology
• Estimates duplicating prior published work were not included.
• Results had to have been easily convertible to the functional unit
chosen for this study: grams of CO2eq per kWh generated.
Table A.II.3 reports the counts of references at each stage in the screening
process for the broad classes of electricity generation technologies
considered in this report.
Analysis of estimates
Estimates of lifecycle GHG emissions from studies passing both
screens were then analyzed and plotted. First, estimates were categorized
by technology within the broad classes considered in this
report, listed in Table A.II.3. Second, estimates were converted to
the common functional unit of g CO2eq per kWh generated. This
conversion was performed using no exogenous assumptions; if
any were required, that estimate was not included. Third, estimates
of total lifecycle GHG emissions that included contributions
from either land use change (LUC) or heat production (in cases
of cogeneration) were removed. This step required that studies
that considered LUC- or heat-related GHG emissions had to report
those contributions separately such that estimates included here
pertain to the generation of electricity alone. Finally, distributional
information required for display in box and whisker plots were
calculated: minimum, 25th percentile value, 50th percentile value,
75th percentile value and maximum. Technologies with data sets
composed of less than five estimates (e.g., geothermal) have been
plotted as discrete points rather than superimposing synthetic distributional
information.
The resulting values underlying Figure 9.8 are shown in Table A.II.4. Figures
displayed in technology chapters are based on the same data set,
yet displayed with a higher level of resolution regarding technology subcategories
(e.g., on- and offshore wind energy).
A.II.5.2.2 List of references
Below, all references for the review of lifecycle assessments of greenhouse
gas emissions from electricity generation that are shown in the final results
in this report are listed, sorted by technology and in alphabetical order.
Biomass-based power generation (52)
Beals, D., and D. Hutchinson (1993). Environmental Impacts of Alternative Electricity
Generation Technologies: Final Report. Beals and Associates, Guelph, Ontario,
Canada, 151 pp.
Beeharry, R.P. (2001). Carbon balance of sugarcane bioenergy systems. Biomass &
Bioenergy, 20(5), pp. 361-370.
Corti, A., and L. Lombardi (2004). Biomass integrated gasification combined cycle
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Table A.II.3 | Counts of LCAs of electricity generation technologies (‘references’) at each stage in the literature collection and screening process and numbers of scenarios
(‘estimates’) of lifecycle GHG emissions evaluated herein.
Technology category References reviewed
References passing
the first screen
References passing
the second screen
References providing
lifecycle GHG
emissions estimates
Estimates of lifecycle
GHG emissions
passing screens
Biopower 369 162 84 52 226
Coal 273 192 110 52 181
Concentrating solar power 125 45 19 13 42
Geothermal Energy 46 24 9 6 8
Hydropower 89 45 11 11 28
Natural gas 251 157 77 40 90
Nuclear Energy 249 196 64 32 125
Ocean energy 64 30 6 5 10
Oil 68 45 19 10 24
Photovoltaics 400 239 75 26 124
Wind Energy 231 174 72 49 126
TOTALS 2165 1309 546 296 984
% of total reviewed 60% 25% 14%
% of those passing first screen 42% 23%
% of those passing second screen 54%
Note: Some double counting is inherent in the totals given that some references investigated more than one technology.
190
Methodology Annex II
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Import Chains for “Green” Electricity Production. NW&S-E-2003-1, Universiteit
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Table A.II.4 | Aggregated results of literature review of LCAs of GHG emissions from electricity generation technologies as displayed in Figure 9.8 (g CO2eq/kWh).
Values
Biopower
Solar Geothermal
Energy
Hydropower
Ocean
Energy
Wind
Energy
Nuclear
Energy
Natural
Gas
Oil Coal
PV CSP
Minimum -633 5 7 6 0 2 2 1 290 510 675
25th percentile 360 29 14 20 3 6 8 8 422 722 877
50th
percentile
18 46 22 45 4 8 12 16 469 840 1001
75th
percentile
37 80 32 57 7 9 20 45 548 907 1130
Maximum 75 217 89 79 43 23 81 220 930 1170 1689
CCS min -1368 65 98
CCS max -594 245 396
Note: CCS = Carbon capture and storage, PV = Photovoltaic, CSP = Concentrating solar power.
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Forsberg, G. (2000). Biomass energy transport – Analysis of bioenergy transport
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Annex II Methodology
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Coal-fired power generation (52)
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Methodology Annex II
Pacca, S.A. (2003). Global Warming Effect Applied to Electricity Generation Technologies.
PhD Thesis, University of California, Berkeley, CA, USA, 191 pp.
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Voorspools, K.R., E.A. Brouwers, and W.D. D’Haeseleer (2000). Energy content
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Wind energy (49)
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199
Annex II Methodology
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A.II.5.3 Review of operational water use of electricity
generation technologies
This overview describes the methods of a comprehensive review of published
estimates of operational water withdrawal and consumption
intensity of electricity generation technologies. Results are discussed in
Section 9.3.4.4 and shown in Figure 9.14.
A.II.5.3.1 Review methodology
Lifecycle water consumption and withdrawal literature for electricity generating
technologies was reviewed, but due to lack of quality and breadth of
data, the review focused exclusively on operational water use. Lifecycle literature
considered here are studies that passed the screening process used
in this report’s review of lifecycle GHG emissions from electricity generation
technologies (see A II.5.2). Upstream water use for biofuel energy crops is
not subject of this section.
This review did not alter (except for unit conversion) or audit for accuracy
the estimates of water use published in studies that passed the screening
criteria. Also, because estimates are used as published, considerable
methodological inconsistency is inherent, which limits comparability. A few
attempts have been made to review the operational water use literature
for electricity generation technologies, though all of these were limited in
their comprehensiveness of either technologies or of primary literature considered
(Gleick, 1993; Inhaber, 2004; NETL, 2007a,b; WRA, 2008; Fthenakis
Pacca, S.A. (2003). Global Warming Effect Applied to Electricity Generation Technologies.
PhD Thesis, University of California, Berkeley, CA, USA, 191 pp.
Pacca, S.A., and A. Horvath (2002). Greenhouse gas emissions from building and
operating electric power plants in the upper Colorado River Basin. Environmental
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Vestas Wind Systems A/S (2006). Life Cycle Assessment of Electricity Produced
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Vestas, Randers, Denmark, 77 pp.
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200
Methodology Annex II
and Kim, 2010). The present review therefore informs the discourse of this
report in a unique way.
Literature collection
The identification of relevant literature started with a core library of references
held previously by the researchers, followed by searching in major
bibliographic databases using a variety of search algorithms and combinations
of key words, and then reviewing reference lists of every collected
reference. All collected literature was added to a bibliographic database.
The literature collection methods described here apply to all classes of electricity
generation technologies reviewed in this report.
Literature screening
Collected references were independently subjected to screening to select
references that met criteria for quality and relevance. Operational water use
studies must have been written in English, addressed operational water use
for facilities located in North America, provided sufficient information to
calculate a water use intensity factor (in cubic metres per megawatt-hour
generated), made estimates of water consumption that did not duplicate
others previously published, and have been in one of the following formats:
journal article, conference proceedings, or report (authored by government
agencies, nongovernmental organizations, international institutions, or corporations).
Estimates of national average water use intensity for particular
technologies, estimates of existing plant operational water use, and estimates
derived from laboratory experiments were considered equally. Given
the paucity of available estimates of water consumption for electricity generation
technologies and that the estimates that have been published are
being used in the policy context already, no additional screens based on
quality or completeness of reporting were applied.
Analysis of estimates
Estimates were categorized by fuel technology and cooling systems. Certain
aggregations of fuel technology types and cooling system types were
made to facilitate analysis. Concentrating solar power includes both parabolic
trough and power tower systems. Nuclear includes pressurized water
reactors and boiling water reactors. Coal includes subcritical and supercritical
technologies. For recirculating cooling technologies, no distinction is
made between natural draft and mechanical draft cooling tower systems.
Similarly, all pond-cooled systems are treated identically. Estimates were
converted to the common functional unit of cubic meters per MWh generated.
This conversion was performed using no exogenous assumptions; if
any were required, that estimate was not analyzed.
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Mann, M., and P. Spath (1997). Life Cycle Assessment of a Biomass Gasification
Combined-Cycle System. Technical Report-TP-430-23076, National Renewable
Energy Laboratory (NREL), Golden, CO, USA. Available at: www.nrel.gov/docs/
legosti/fy98/23076.pdf.
Meridian (1989). Energy System Emissions and Material Requirements. Meridian
Corporation Report to U.S. Department of Energy (DOE), Washington, DC, USA.
NETL (2007). Cost and Performance Baseline for Fossil Energy Plants-Volume
1: Bituminous Coal and Natural Gas to Electricity Final Report. DOE/NETL-
2007/1281, National Energy Technology Laboratory (NETL), Pittsburgh, PA, USA.
Available at www.netl.doe.gov/energy-analyses/pubs/BitBase_FinRep_2007.pdf.
NETL (2007). Power Plant Water Usage and Loss Study. 2007 Update. National Energy
Technology Laboratory (NETL), Pittsburgh, PA, USA. Available at: www.netl.doe.
gov/technologies/coalpower/gasification/pubs/pdf/WaterReport_Revised%20
May2007.pdf.
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NETL (2009). Estimating Freshwater Needs to Meet Future Thermoelectric Generation
Requirements. DOE/NETL-400/2009/1339, National Energy Technology
Laboratory (NETL), Pittsburgh, PA, USA. Available at: www.netl.doe.gov/energyanalyses/
pubs/2009%20Water%20Needs%20Analysis%20-%20Final%20
%289-30-2009%29.pdf.
NETL (2009). Existing Plants, Emissions and Capture – Setting Water-Energy R&D Program
Goals. DOE/NETL-2009/1372, National Energy Technology Laboratory (NETL),
Pittsburgh, PA, USA. Available at: www.netl.doe.gov/technologies/coalpower/ewr/
water/pdfs/EPEC%20water-energy%20R%26D%20goal%20update%20v.1%20
may09.pdf.
Sargent & Lundy (2003). Assessment of Parabolic Trough and Power Tower Solar
Technology Cost and Performance Forecasts. NREL/SR-550-34440, National
Renewable Energy Laboratory (NREL), Golden, CO, USA. Available at: www.nrel.
gov/docs/fy04osti/34440.pdf.
Stoddard, L., J. Abiecunas, and R.O. Connell (2006). Economic, Energy, and
Environmental Benefits of Concentrating Solar Power in California. NREL/
SR-550-39291, National Renewable Energy Laboratory (NREL), Golden, CO,
USA. Available at: www.nrel.gov/docs/fy06osti/39291.pdf.
Torcellini, P., N. Long, and R. Judkoff (2003). Consumptive Water Use for U.S.
Power Production. Technical Report-TP-550-33905, National Renewable Energy
Laboratory (NREL), Golden, CO, USA. Available at: www.nrel.gov/docs/fy04osti/
33905.pdf.
Turchi, C., M. Wagner, and C. Kutscher (2010). Water Use in Parabolic Trough Power
Plants: Summary Results from WorleyParsons’ Analyses. NREL/TP-5500-49468,
National Renewable Energy Laboratory (NREL), Golden, CO, USA. Available at:
www.nrel.gov/docs/fy11osti/49468.pdf.
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Water Consumption of Concentrating Solar Power Electricity Generation. Report
to Congress. U.S. Department of Energy (DOE), Washington, DC, USA.
Viebahn, P., S. Kronshage, F. Trieb, and Y. Lechon (2008). Final Report on Technical
Data, Costs, and Life Cycle Inventories of Solar Thermal Power Plants. Project
502687, New Energy Externalities Developments for Sustainability (NEEDS),
Brussels, Belgium, 95 pp. Available at: www.needs-project.org/RS1a/RS1a%20
D12.2%20Final%20report%20concentrating%20solar%20thermal%20
power%20plants.pdf.
WorleyParsons (2009). Analysis of Wet and Dry Condensing 125 MW Parabolic
Trough Power Plants. WorleyParsons Report No. NREL-2-ME-REP-0002-R0,
WorleyParsons Group, North Sydney, Australia.
WorleyParsons (2009). Beacon Solar Energy Project Dry Cooling Evaluation.
WorleyParsons Report No. FPLS-0-LI-450-0001, WorleyParsons Group, North
Sydney, Australia.
WorleyParsons (2010). Material Input for Life Cycle Assessment Task 5 Subtask 2:
O&M Schedules. WorleyParsons Report No. NREL-0-LS-019-0005, WorleyParsons
Group, North Sydney, Australia.
WorleyParsons (2010). Parabolic Trough Reference Plant for Cost Modeling with the
Solar Advisor Model. WorleyParsons Report, WorleyParsons Group, North Sydney,
Australia.
WRA (2008). A Sustainable Path: Meeting Nevada’s Water and Energy Demands.
Western Resource Advocates (WRA), Boulder, CO, USA, 43 pp. Available at: www.
westernresourceadvocates.org/water/NVenergy-waterreport.pdf.
Yang, X., and B. Dziegielewski (2007). Water use by thermoelectric power plants
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pp. 160-169.
A.II.5.4 Risk analysis
This section introduces the methods applied for the assessment of hazards
and risks of energy technologies presented in Section 9.3.4.7, and provides
references and central assumptions (Table A.II.5).
A large variety of definitions of the term risk exists, depending on the
field of application and the object under study (Haimes, 2009). In engineering
and natural sciences, risk is frequently defined in a quantitative
way: risk (R) = probability (p) × consequence (C). This definition does
not include subjective factors of risk perception and aversion, which
can also influence the decision-making process, that is, stakeholders
may make trade-offs between quantitative and qualitative risk factors
(Gregory and Lichtenstein, 1994; Stirling, 1999). Risk assessment
and evaluation is further complicated when certain risks significantly
transcend everyday levels; their handling posing a challenge for society
(WBGU, 2000). For example, Renn et al. (2001) assigned risks into three
categories or areas, namely (1) the normal area manageable by routine
operations and existing laws and regulations, (2) the intermediate
area, and (3) the intolerable area (area of permission). Kristensen et al.
(2006) proposed a modified classification scheme to further improve
the characterization of risk. Recently, additional aspects such as critical
infrastructure protection, complex interrelated systems and ‘unknown
unknowns’ have become a major focus (Samson et al., 2009; Aven and
Zio, 2011; Elahi, 2011).
The evaluation of the ‘hazards and risks’ of various energy technologies
as presented in Section 9.3.4.7 builds upon the approach of comparative
risk assessment as it has been established at the Paul Scherrer Institut
(PSI) since the 1990s;4 at the core of which is the Energy-Related Severe
Accident Database (ENSAD) (Hirschberg et al., 1998, 2003a; Burgherr
et al., 2004, 2008; Burgherr and Hirschberg, 2005). The consideration
of full energy chains is essential because an accident can happen in
any chain stage from exploration, extraction, processing and storage,
long distance transport, regional and local distribution, power and/or
heat generation, waste treatment, and disposal. However, not all these
stages are applicable to every energy chain. For fossil energy chains
(coal, oil, natural gas) and hydropower, extensive historical experience is
contained in ENSAD for the period 1970 to 2008. In the case of nuclear
power, Probabilistic Safety Assessment (PSA) is employed to address
hypothetical accidents (Hirschberg et al., 2004a). In contrast, consideration
of renewable energy technologies other than hydropower is based
on available accident statistics, literature review and expert judgment
because of limited or lacking historical experience. It should be noted
that available analyses have limited scope and do not include proba-
4 In a recent study, Felder (2009) compared the ENSAD database with another energy
accident compilation (Sovacool, 2008a). Despite numerous and partially substantial
differences between the two data sets, several interesting findings with regard to
methodological and policy aspects were addressed. However, the study was based
on the first official release of ENSAD (Hirschberg et al., 1998), and thus disregarded
all subsequent updates and extensions. Another study by Colli et al. (2009) took a
slightly different approach using a rather broad set of so-called Risk Characterization
Indicators, however the actual testing with illustrative examples was based on
ENSAD data.
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Methodology Annex II
bilistic modelling of hypothetical accidents. This may have bearing
particularly on results for solar PV.
No consensus definition of the term ‘severe accident’ exists in the literature.
Within the framework of PSI’s database ENSAD, an accident is
considered to be severe if it is characterized by one or several of the
following consequences:
• At least 5 fatalities or
• At least 10 injured or
• At least 200 evacuees or
• An extensive ban on consumption of food or
• Releases of hydrocarbons exceeding 10,000 metric tons or
• Enforced clean-up of land and water over an area of at least 25 km2
or
• Economic loss of at least 5 million USD2000
For large centralized energy technologies, results are given for three
major country aggregates, namely for OECD and non-OECD countries
as well as EU 27. Such a distinction is meaningful because of the substantial
differences in management, regulatory frameworks and general
safety culture between highly developed countries (i.e., OECD and EU
27) and the mostly less-developed non-OECD countries (Burgherr and
Hirschberg, 2008). In the case of China, coal chain data were only analyzed
for the years 1994 to 1999 when data on individual accidents from
the China Coal Industry Yearbook (CCIY) were available, indicating that
previous years were subject to substantial underreporting (Hirschberg
et al., 2003a,b). For the period 2000 to 2009, only annual totals of coal
chain fatalities from CCIY were available, which is why they were not
combined with the data from the previous period. For renewable energy
technologies except hydropower, estimates can be considered representative
for developed countries (e.g., OECD and EU 27).
Comparisons of the various energy chains were based on data normalized
to the unit of electricity production. For fossil energy chains the
thermal energy was converted to an equivalent electrical output using
a generic efficiency factor of 0.35. For nuclear, hydropower and new
renewable technologies the normalization is straightforward since the
generated product is electrical energy. The Gigawatt-electric-year
(GWe yr) was chosen because large individual plants have capacities
in the neighbourhood of 1 GW of electrical output (GWe ). This makes
the GWe yr a natural unit to use when presenting normalized indicators
generated within technology assessments.
A.II.6 Regional definitions and country
groupings
The IPCC SRREN uses the following regional definitions and country
groupings, largely based on the definitions of the World Energy Outlook
2009 (IEA, 2009). Grouping names and definitions vary in the published
literature, and in the SRREN in some instances there may be slight deviations
from the standard below. Alternative grouping names that are
used in the SRREN are given in parenthesis.
Africa
Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon,
Cape Verde, Central African Republic, Chad, Comoros, Congo, Democratic
Republic of Congo, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea,
Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau,
Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania,
Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Reunion,
Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone,
Somalia, South Africa, Sudan, Swaziland, United Republic of Tanzania,
Togo, Tunisia, Uganda, Zambia and Zimbabwe.
Annex I Parties to the United Nations Framework Convention on
Climate Change
Australia, Austria, Belarus, Belgium, Bulgaria, Canada, Croatia,
Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia, Liechtenstein, Lithuania,
Luxembourg, Monaco, Netherlands, New Zealand, Norway, Poland,
Portugal, Romania, Russian Federation, Slovak Republic, Slovenia, Spain,
Sweden, Switzerland, Turkey, Ukraine, United Kingdom and United
States.
Eastern Europe/Eurasia (also sometimes referred to as
‘Transition Economies’)
Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina,
Bulgaria, Croatia, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia,
Lithuania, the former Yugoslav Republic of Macedonia, the Republic
of Moldova, Romania, Russian Federation, Serbia, Slovenia, Tajikistan,
Turkmenistan, Ukraine, and Uzbekistan. For statistical reasons,
this region also includes Cyprus, Gibraltar and Malta.
European Union
Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia,
Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia,
Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania,
Slovak Republic, Slovenia, Spain, Sweden and United Kingdom.
G8
Canada, France, Germany, Italy, Japan, Russian Federation, United
Kingdom and United States.
Latin America
Antigua and Barbuda, Aruba, Argentina, Bahamas, Barbados, Belize,
Bermuda, Bolivia, Brazil, the British Virgin Islands, the Cayman Islands,
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Annex II Methodology
Table A.II.5 | Overview of data sources and assumptions for the calculation of fatality rates and maximum consequences.
Coal
• ENSAD database at PSI; severe (≥5 fatalities) accidents.1
• OECD: 1970-2008; 86 accidents; 2,239 fatalities. EU 27: 1970-2008; 45 accidents; 989 fatalities. Non-OECD without China: 1970-2008; 163 accidents; 5.808 fatalities
(Burgherr et al., 2011).
Previous studies: Hirschberg et al. (1998); Burgherr et al. (2004, 2008).
• China (1994-1999): 818 accidents; 11,302 fatalities (Hirschberg et al., 2003a; Burgherr and Hirschberg, 2007).
• China (2000-2009): for comparison, the fatality rate in the period 2000 to 2009 was calculated based on data reported by the State Administration of Work Safety
(SATW) of China.2 Annual values given by SATW correspond to total fatalities (i.e., severe and minor accidents). Thus for the fatality rate calculation it was assumed
that fatalities from severe accidents comprise 30% of total fatalities, as has been found in the China Energy Technology Program (Hirschberg et al., 2003a; Burgherr
and Hirschberg, 2007). Chinese fatality rate (2000-2009) = 3.14 fatalities/GWeyr.
Oil
• ENSAD database at PSI; severe (≥5 fatalities) accidents.1
• OECD: 1970-2008; 179 accidents; 3,383 fatalities. EU 27: 1970-2008; 64 accidents; 1,236 fatalities. Non-OECD: 1970-2008; 351 accidents; 19,376 fatalities (Burgherr
et al., 2011).
Previous studies: Hirschberg et al. (1998); Burgherr et al. (2004, 2008).
Natural Gas
• ENSAD database at PSI; severe (≥5 fatalities) accidents.1
• OECD: 1970-2008; 109 accidents; 1,257 fatalities. EU 27: 1970-2008; 37 accidents; 366 fatalities. Non-OECD: 1970-2008; 77 accidents; 1,549 fatalities (Burgherr et al., 2011).
Previous studies: Hirschberg et al. (1998); Burgherr et al. (2004, 2008); Burgherr and Hirschberg (2005).
Nuclear
• Generation II (Gen. II) - Pressurized Water Reactor, Switzerland; simplified Probabilistic Safety Assessment (PSA) (Roth et al., 2009).
• Generation III (Gen. III) - European Pressurized Reactor (EPR) 2030, Switzerland; simplified PSA (Roth et al., 2009).
Available results for the above described EPR point towards significantly lower fatality rates (early fatalities (EF): 3.83E-07 fatalities/GWeyr; latent fatalities (LF):
1.03E-05 fatalities/GWeyr; total fatalities (TF): 1.07E-05 fatalities/GWeyr) due to a range of advanced features, especially with respect to Severe Accident Management
(SAM) active and passive systems. However, maximum consequences of hypothetical accidents may increase (ca. 48,800 fatalities) due to the larger plant size
(1,600 MW) and the larger associated radioactive inventory.
• In the case of a severe accident in the nuclear chain, immediate or early (acute) fatalities are of minor importance and denote those fatalities that occur in a short time
period after exposure, whereas latent (chronic) fatalities due to cancer dominate total fatalities (Hirschberg et al., 1998). Therefore, the above estimates for Gen. II and
III include immediate and latent fatalities.
• Three Mile Island 2, TMI-2: The TMI-2 accident occurred as a result of equipment failures combined with human errors. Due to the small amount of radioactivity
released, the estimated collective effective dose to the public was about 40 person-sievert (Sv). The individual doses to members of the public were extremely low:
<1 mSv in the worst case. On the basis of the collective dose one extra cancer fatality was estimated. However, 144,000 people were evacuated from the area around
the plant. For more information, see Hirschberg et al. (1998).
• Chernobyl: 31 immediate fatalities; PSA-based estimate of 9,000 to 33,000 latent fatalities (Hirschberg et al., 1998).
• PSI’s Chernobyl estimates for latent fatalities range from about 9,000 for Ukraine, Russia and Belarus to about 33,000 for the entire northern hemisphere in the next
70 years (Hirschberg et al., 1998). According to a recent study by numerous United Nations organizations, up to 4,000 persons could die due to radiation exposure in
the most contaminated areas (Chernobyl Forum, 2005). This estimate is substantially lower than the upper limit of the PSI interval, which, however, was not restricted
to the most contaminated areas.
Hydro
• ENSAD Database at PSI; severe (≥5 fatalities) accidents.1
• OECD: 1970-2008; 1 accident; 14 fatalities (Teton dam failure, USA, 1976). EU 27: 1970-2008; 1 accident; 116 fatalities (Belci dam failure, Romania, 1991) (Burgherr et
al., 2011).
• Based on a theoretical model, maximum consequences for the total failure of a large Swiss dam range between 7,125 and 11,050 fatalities without pre-warning, but
can be reduced to 2 to 27 fatalities with 2 hours pre-warning time (Burgherr and Hirschberg, 2005, and references therein).
• Non-OECD: 1970-2008; 12 accidents; 30,007 fatalities. Non-OECD without Banqiao/Shimantan 1970-2008; 11 accidents; 4,007 fatalities; largest accident in China
(Banqiao/Shimantan dam failure, China, 1975) excluded (Burgherr et al., 2011).
• Previous studies: Hirschberg et al. (1998); Burgherr et al. (2004, 2008).
Photovoltaic (PV)
• Current estimates include only silicon (Si) technologies, weighted by their 2008 market shares, i.e., 86% for c-Si and 5.1% for a-Si/u-Si.
• The analysis covers risks of selected hazardous substances (chlorine, hydrochloric acid, silane and trichlorosilane) relevant in the Si PV life cycle.
• Accident data were collected for the USA (for which a good coverage exists), and for the years 2000 to 2008 to ensure that estimates are representative of currently
operating technologies.
• Database sources: Emergency Response Notification System, Risk Management Plan, Major Hazard Incident Data Service, Major Accidents Reporting System, Analysis
Research and Information on Accidents, Occupational Safety and Health Update.
• Since collected accidents were not only from the PV sector, the actual PV fatality share was estimated, based on the above substance amounts in the PV sector as a
share of the total USA production, as well as data from the ecoinvent database.
• Cumulated fatalities for the four above substances were then normalized to the unit of energy production using a generic load factor of 10% (Burgherr et al., 2008).
• Assumption that 1 out of 100 accidents is severe.3
• Current estimate for fatality rate: Burgherr et al. (2011).
• Maximum consequences represent an expert judgment due to limited historical experience (Burgherr et al., 2008).
• Previous studies: Hirschberg et al. (2004b); Burgherr et al. (2008); Roth et al. (2009).
• Other studies: Ungers et al. (1982); Fthenakis et al. (2006); Fthenakis and Kim (2010).
Continued next Page ➔
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Methodology Annex II
Chile, Colombia, Costa Rica, Cuba, Dominica, the Dominican Republic,
Ecuador, El Salvador, the Falkland Islands, French Guyana, Grenada,
Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique,
Montserrat, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru,
St. Kitts and Nevis, Saint Lucia, Saint Pierre et Miquelon, St. Vincent and
the Grenadines, Suriname, Trinidad and Tobago, the Turks and Caicos
Islands, Uruguay and Venezuela.
Middle East
Bahrain, the Islamic Republic of Iran, Iraq, Israel, Jordan, Kuwait,
Lebanon, Oman, Qatar, Saudi Arabia, Syrian Arab Republic, the United
Arab Emirates and Yemen. It includes the neutral zone between Saudi
Arabia and Iraq.
Wind Onshore
• Data sources: Windpower Death Database (Gipe, 2010) and Wind Turbine Accident Compilation (Caithness Windfarm Information Forum, 2010).
• Fatal accidents in Germany in the period 1975-2010; 10 accidents; 10 fatalities. 3 car accidents, where driver distraction from wind farm is given as reason, were
excluded from the analysis.
• Assumption that 1 out of 100 accidents is severe.3
• Current estimate for fatality rate: Burgherr et al. (2011).
• Maximum consequences represent an expert judgment due to limited historical experience (Roth et al., 2009).
• Previous study: Hirschberg et al. (2004b).
Wind Offshore
• Data sources: see onshore above.
• Up to now there were 2 fatal accidents during construction in the UK (2009 and 2010) with 2 fatalities, and 2 fatal accidents during research activities in the USA
(2008) with 2 fatalities.
• For the current estimate, only UK accidents were used, assuming a generic load factor of 0.43 (Roth et al., 2009) for the currently installed capacity of 1,340 MW
(Renewable UK, 2010).
• Assumption that 1 out of 100 accidents is severe.3
• Current estimate for fatality rate: Burgherr et al. (2011).
• Maximum consequences: see onshore above.
Biomass: Combined Heat and Power (CHP) Biogas
• ENSAD Database at PSI; severe (≥5 fatalities) accidents.1 Due to limited historical experience, the CHP Biogas fatality rate was approximated using natural gas
accident data from the local distribution chain stage.
• OECD: 1970-2008; 24 accidents; 260 fatalities (Burgherr et al., 2011).
• Maximum consequences represent an expert judgment due to limited historical experience (Burgherr et al., 2011).
• Previous studies: Roth et al. (2009).
Enhanced Geothermal System (EGS)
• For the fatality rate calculations, only well drilling accidents were considered. Due to limited historical experience, exploration accidents in the oil chain were used as a
rough approximation because of similar drilling equipment.
• ENSAD Database at PSI; severe (≥5 fatalities) accidents.1
• OECD: 1970-2008; oil exploration, 7 accidents; 63 fatalities (Burgherr, et al. 2011).
• For maximum consequences an induced seismic event was considered to be potentially most severe. Due to limited historical experience, the upper fatality boundary
from the seismic risk assessment of the EGS project in Basel (Switzerland) was taken as an approximation (Dannwolf and Ulmer, 2009).
• Previous studies: Roth et al. (2009).
Notes: 1. Fatality rates are normalized to the unit of energy production in the corresponding country aggregate. Maximum consequences correspond to the most deadly accident that
occurred in the observation period. 2. Data from SATW for the years 2000 to 2005 were reported in the China Labour News Flash No. 60 (2006-01-06) available at www.china-labour.
org.hk/en/node/19312 (accessed December 2010). SATW data for the years 2006 to 2009 were published by Reuters, available at www.reuters.com/article/idUSPEK206148 (2006),
uk.reuters.com/article/idUKPEK32921920080112 (2007), uk.reuters.com/article/idUKTOE61D00V20100214 (2008 and 2009), (all accessed December 2010). 3. For example, the rate
for natural gas in Germany is about 1 out of 10 (Burgherr and Hirschberg, 2005), and for coal in China about 1 out of 3 (Hirschberg et al., 2003b).
Non-OECD Asia (also sometimes referred to as ‘developing
Asia’)
Afghanistan, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China,
Chinese Taipei, the Cook Islands, East Timor, Fiji, French Polynesia, India,
Indonesia, Kiribati, the Democratic People’s Republic of Korea, Laos,
Macau, Malaysia, Maldives, Mongolia, Myanmar, Nepal, New Caledonia,
Pakistan, Papua New Guinea, the Philippines, Samoa, Singapore,
Solomon Islands, Sri Lanka, Thailand, Tonga, Vietnam and Vanuatu.
North Africa
Algeria, Egypt, Libyan Arab Jamahiriya, Morocco and Tunisia.
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Annex II Methodology
OECD – Organisation for Economic Cooperation and
Development
OECD Europe, OECD North America and OECD Pacific as listed below.
Countries that joined the OECD in 2010 (Chile, Estonia, Israel and
Slovenia) are not yet included in the statistics used in this report.
OECD Europe
Austria, Belgium, the Czech Republic, Denmark, Finland, France,
Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, the
Netherlands, Norway, Poland, Portugal, the Slovak Republic, Spain,
Sweden, Switzerland, Turkey and the United Kingdom.
OECD North America
Canada, Mexico and the United States.
OECD Pacific
Australia, Japan, Korea and New Zealand.
OPEC (Organization of Petroleum Exporting Countries)
Algeria, Angola, Ecuador, Islamic Republic of Iran, Iraq, Kuwait, Libya,
Nigeria, Qatar, Saudi Arabia, United Arab Emirates and Venezuela.
Sub-Saharan Africa
Africa regional grouping excluding the North African regional grouping
and South Africa.
A.II.7 General conversion factors for energy
Table A.II.6 provides conversion factors for a variety of energy-related
units.
Table A.II.6 | Conversion factors for energy units (IEA, 2010b).
To: TJ Gcal Mtoe MBtu GWh
From: multiply by:
TJ 1 238.8 2.388 x 10-5 947.8 0.2778
Gcal 4.1868 x 10-3 1 10-7 3.968 1.163 x 10-3
Mtoe 4.1868 x 104 107 1 3.968 x 107 11,630
MBtu 1.0551 x 10-3 0.252 2.52 x 10-8 1 2.931 x 10-4
GWh 3.6 860 8.6 x 10-5 3,412 1
Notes: MBtu: million British thermal unit; GWh: gigawatt hour; Gcal: gigacalorie;
TJ: terajoule; Mtoe: megatonne of oil equivalent.
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Methodology Annex II
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Recent Renewable Energy
Cost and Performance
Parameters III ANNEX
Lead Authors:
Thomas Bruckner (Germany), Helena Chum (USA/Brazil),
Arnulf Jäger-Waldau (Italy/Germany), Ånund Killingtveit (Norway),
Luis Gutiérrez-Negrín (Mexico), John Nyboer (Canada), Walter Musial (USA),
Aviel Verbruggen (Belgium), Ryan Wiser (USA)
Contributing Authors:
Dan Arvizu (USA), Richard Bain (USA), Jean-Michel Devernay (France), Don Gwinner (USA),
Gerardo Hiriart (Mexico), John Huckerby (New Zealand), Arun Kumar (India),
José Moreira (Brazil), Steffen Schlömer (Germany)
This annex should be cited as:
Bruckner, T., H. Chum, A. Jäger-Waldau, Å. Killingtveit, L. Gutiérrez-Negrín, J. Nyboer, W. Musial, A. Verbruggen,
R. Wiser, 2011: Annex III: Cost Table. In IPCC Special Report on Renewable Energy Sources and Climate Change
Mitigation [O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier,
G. Hansen, S. Schlömer, C. von Stechow (eds)], Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA.
209
210
Recent Renewable Energy Cost and Performance Parameters Annex III
The levelized cost of electricity (LCOE), heat (LCOH) and transport
fuels (LCOF)3 are calculated based on the data compiled here and the
methodology described in Annex II, using three different real discount
rates (3, 7 and 10%). They represent the full range of possible levelized
cost values resulting from the lower and upper bounds of input data in
this table. More precisely, the lower bound of the levelized cost ranges is
based on the low ends of the ranges of investment, operation and maintenance
(O&M) and (if applicable) feedstock cost and the high ends of
the ranges of capacity factors and lifetimes as well as (if applicable) the
high ends of the ranges of conversion efficiencies and by-product revenue
stated in this table. The higher bound of the levelized cost ranges
is accordingly based on the high end of the ranges of investment, O&M
and (if applicable) feedstock costs and the low end of the ranges of
capacity factors and lifetimes as well as (if applicable) the low ends of
the ranges of conversion efficiencies and by-product revenue.4
These levelized cost figures (violet parts of the tables) are discussed in
Sections 1.3.2 and 10.5.1 of the main report. Most technology chapters
(Chapters 2 through 7) provide more detail on the sensitivity of the levelized
costs to particular input parameters beyond discount rates (see
in particular Sections 2.7, 3.8, 4.7, 5.8, 6.7 and 7.8). These sensitivity
analyses provide additional insights into the relative weight of the large
number of parameters that determine the levelized costs under more
specific conditions.
In addition to the technology-specific sensitivity analysis in the respective
chapters (Chapters 2 through 7) and the discussions in Sections
1.3.2 and 10.5.1, Figures A.III.2 through A.III.4 (a, b) show the sensitivity
of the levelized cost in a complementary way using so-called tornado
graphs (Figures A.III.2 through A.III.4 a) as well as their ‘negatives’
(Figures A.III.2 through A.III.4 b).
Figures A.III.1a and A.III.1b show schematic versions of the tornado
graphs and their ‘negatives’, respectively, explaining how to read them
correctly.
3 The levelized cost represents the cost of an energy generating system over its lifetime.
It is calculated as the per unit price at which energy must be generated from
a specific source over its lifetime to break even. The levelized costs usually include
all private costs that accrue upstream in the value chain, but they do not include the
downstream cost of delivery to the final customer, the cost of integration, or external
environmental or other costs. Subsidies for RE generation and tax credits are not
included. However, indirect taxes and subsidies on inputs or commodities affecting
the prices of inputs and, hence, private cost, cannot be fully excluded.
4 This approach assumes that input parameters to the LCOE/LCOH/LCOF calculation
are independent from each other. This is a simplifying assumption that implies that
the lower ranges of LCOE/LCOH/LCOF (as a combination of best-case input values)
may in some cases be lower than is most often the case, while the upper range of
LCOE/LCOH/LCOFs (as a combination of worst-case input values) may in some cases
be higher than what is generally considered economically attractive from a private
investors’ perspective. The extent to which this approach introduces a structural bias
in the LCOE/LCOH/LCOF ranges, however, is reduced by taking a rather conservative
approach to the range of input values (partly involving expert judgement), that is, by
restricting input values roughly to the medium 80% range where possible.
Annex III Recent Renewable Energy Cost and
Performance Parameters
Annex III is intended to become a ‘living document’, which will be
updated in the light of new information in order to serve as an input to
the IPCC Fifth Assessment Report (AR5). Scientists that are interested in
supporting this process are invited to contact the IPCC WG III Technical
Support Unit (TSU) (using [email protected]) in order to get further
information concerning the submission process.1 Comments and
new data input will be considered for inclusion in Volume 3 of the IPCC
AR5 according to the procedures of the IPCC review system.
This Annex contains recent cost and performance parameter information
for currently commercially available renewable power generation
technologies (Table A.III.1), heating technologies (Table A.III.2) and biofuel
production processes (Table A.III.3). It summarizes information that
determines the levelized cost of energy or energy carriers supplied by
the respective technologies.
The input ranges are based on assessments of various studies by authors
of the respective technology chapters (Chapters 2 through 7). If not
stated otherwise, the data ranges provided here are worldwide aggregates.
Data are generally for 2008, but can be as recent as 2009. They
represent roughly the mid-80% of values found in the literature, hence,
excluding outliers. The availability and quality of different sources of
data varies significantly across individual technologies for a variety of
reasons.2 Some expert judgment is therefore required to determine data
ranges that are representative of particular classes of technologies and
specific periods of time and valid globally.
The references to specific information are quoted in the footnotes. If the
full dataset is based on one particular reference, it is included in the reference
column of the green part of the table. Further information on the
data reported in the table is provided in the footnotes and in Chapters
2 through 7 (see in particular Sections 2.7, 3.8, 4.7, 5.8, 6.7 and 7.8).
1 No individual responses can be guaranteed, but all emails as well as relevant material
attached to those emails will be archived and made available in appropriate form
to the authors involved in the AR5 process.
2 No standardized uncertainty language has been used in this report. Nonetheless, the
authors of this Annex have carefully assessed available data and highlighted data
limitations and uncertainties in the footnotes. A fair impression of the breadth of the
reference base can be deduced from the list of references in this Annex.
211
Annex III Recent Renewable Energy Cost and Performance Parameters
Figure A.III.1a | Tornado graph. Starting from the medium levelized cost value at a 7% interest rate, a broader range of levelized cost values becomes possible if individual parameters
are varied over the full of range of values that these parameters may take on under different conditions. If the LCOE/LCOH/LCOF of a technology is very sensitive to variation of a
particular parameter, then the corresponding bar will be broad. This means that a variation of that particular parameter may lead to LCOE/LCOH/LCOF values that can deviate strongly
from the medium LCOE/LCOH/LCOF value. If the LCOE/LCOH/LCOF of a technology is robust for variations of the respective parameter, the bars will be narrow and only slight deviations
from the medium LCOE/LCOH/LCOF value may result from variation of that parameter. Note, however, that no or narrow bars may also be the result of no or limited variation of
the input parameters.
Levelized Cost
of Electricity,
Heat or Fuels
Technology A
Medium Levelized Cost Value
of Technology A.
This is the value that results from
using the arithmetic averages of
the input parameter values stated
in the data tables and a 7% discount
rate to compute the levelized cost.
This is the range of possible levelized cost
values that results for technology A, if only the
dark red parameter is NOT set to its arithmetic
average, BUT varied from its lowest to its
highest value.
Figure A.III.1b | ‘Negative’ of tornado graph. Starting from the low and high bounds of the full range of levelized cost values at a 3% and 10% interest rate, respectively, a narrower
range of levelized cost values remains possible if individual parameters are fixed at their respective medium values. If the LCOE/LCOH/LCOF of a technology is very sensitive to variations
of a particular parameter, then the corresponding bar that remains will be narrowed to a large degree. Such parameters are of particular importance in determining the LCOE/
LCOH/LCOF under more specific conditions. If the LCOE/LCOH/LCOF of a technology is robust for variations of the respective parameter, the remaining range will remain close to the
full range of possible LCOE/LCOH/LCOF values. Such parameters are of less importance in determining the LCOE/LCOH/LCOF more precisely. Note, however, that no or small deviations
from the full range may also be the result of no or limited variation of the input parameters.
Levelized Cost
of Electricity,
Heat or Fuels
Technology A
This is the narrower range of
possible levelized cost values
that results for technology A, if
only the blue parameter is set to
its arithmetic average, while all
others vary freely.
This is the full range of
possible levelized cost
values for technology A.
=
212
Recent Renewable Energy Cost and Performance Parameters Annex III
Table A.III.1 | Cost-performance parameters for RE power generation technologies.i
Input data Output data
Resource Technology
Typical
size of the
device
(MW)ii
Investment
cost
(USD/kW)
O&M cost, fixed
annual (USD/kW)
and/or (non-feed)
variable (US¢/kWh)
By-product
revenue
(US¢/kWh)iii
Feedstock
cost
(USD/GJfeed, HHV
iv)
Feedstock
conversion
efficiencyel
(%)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOEv
(US¢/kWh)
Discount rate
3% 7% 10%
Bioenergy
Dedicated Biopower
CFBvi 25–100 2,700–4,100vii 87 USD/kW and
0.40 US¢/kWh
N/Aviii 1.25–5.0ix 28 70–80 20
McGowin (2008)
6.1–13 6.9–15 7.9–16
Dedicated Biopower
Stokerx See above 2,600–4,000vii 84 USD/kW and
0.34 US¢/kWh
N/Aviii See above 27 See above See above 5.6–13 6.7–15 7.7–16
Dedicated Biopower
(Stoker CHPxi)
See above 2,800–4,200vii 86 USD/kW and
0.35 US¢/kWh
1.0xii See above 24 See above See above 5.1–13 6.3–15 7.3–17
Co-firing: Co-feed 20–100 430–500xiii 12 USD/kW and
0.18 US¢/kWh
N/Aviii See above 36 See above See above McGowin (2008) 2.0–5.9 2.2–6.2 2.3–6.4
Co-firing: Separate
Feed
See above 760–900xiii 18 USD/kW N/Aviii See above 36 See above See above Bain (2011) 2.3–6.3 2.6–6.7 2.9–7.1
CHP (ORCxiv) 0.65–1.6 6,500–9,800
59–80 USD/kW and
4.3–5.1 US¢/kWh
7.7xv, xvi See above 14 55–68 See above
Obernberger et
al. (2008)
8.6–26 12–32 15–37
CHP (Steam Turbine) 2.5–10 4,100–6,200xvii 54 USD/kW and
3.5 US¢/kWh
5.4xv, xviii See above 18 See above See above 6.2–18 8.3–22 10–26
CHP (Gasification
ICE)xix 2.2–13 1,800–2,100
65–71 USD/kW and
1.1-1.9 US¢/kWh
1.0–4.5xv, xx See above 28–30 See above See above 2.1–11 3.0–13 3.8–14
Direct Solar
Energy
PV (Residential
Rooftop)
0.004–0.01 3,700–6,800xxi 19–110 USD/kWxxii N/Aviii N/Aviii N/Aviii 12–20xxiii 20–30
see Section 3.8
and footnotes
12–53 18–71 23–86
PV (Commercial
Rooftop)
0.02–0.5 3,500–6,600xxi 18–100 USD/kWxxii N/Aviii N/Aviii N/Aviii See above See above 11–52 17–69 22–83
PV (Utility Scale,
Fixed Tilt)
0.5–100xxiv 2,700–5,200xxi 14–69 USD/kWxxii N/Aviii N/Aviii N/Aviii 15–21xxiii See above 8.4–33 13–43 16–52
PV (Utility Scale,
One-Axis)
0.5–100xxiv 3,100–6,200xxi 16–75 USD/kWxxii N/Aviii N/Aviii N/Aviii 15–27xxiii See above 7.4–39 11–52 15–62
CSP 50–250xxv 6,000–7,300xxvi 60–82 USD/kWxxvii N/Aviii N/Aviii N/Aviii 35–42xxviii See above 11–19 16–25 20–31
Geothermal
Energy
Geothermal Energy
(Condensing-Flash
Plants)
10–100 1,800–3,600xxix 150–190 USD/kWxxx N/Aviii N/Aviii N/Aviii 60–90xxxi 25–30xxxii
see Section 4.7
and footnotes
3.1–8.4 3.8–11 4.5–13
Geothermal Energy
(Binary-Cycle Plants)
2–20 2,100–5,200xxix See above N/Aviii N/Aviii N/Aviii See above See above 3.3–11 4.1–14 4.9–17
Hydropower All
<0.1 –
>20,000xxxiii 1,000–3,000xxxiv 25–75 USD/kWxxxv N/Aviii N/Aviii N/Aviii 30–60xxxvi 40–80xxxvii see Chapter 5
and footnotes
1.1–7.8 1.8–11 2.4–15
Ocean Energy Tidal Rangexxxviii <1 – >250xxxix 4,500–5,000xxxviii
100 USD/kWxxxviii N/Aviii N/Aviii N/Aviii 22.5–28.5xl 40xli, xxxviii see Section 6.7
and footnotes
12–16 18–24 23–32
Continued next page
T
213
Annex III Recent Renewable Energy Cost and Performance Parameters
Input data Output data
Resource Technology
Typical
size of the
device
(MW)ii
Investment
cost
(USD/kW)
O&M cost, fixed
annual (USD/kW)
and/or (non-feed)
variable (US¢/kWh)
By-product
revenue
(US¢/kWh)iii
Feedstock
cost
(USD/GJfeed, HHV
iv)
Feedstock
conversion
efficiencyel
(%)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOEv
(US¢/kWh)
Discount rate
3% 7% 10%
Wind Energy
Wind Energy
(Onshore,Large
Turbines)
5–300xlii 1,200–2,100xliii 1.2–2.3 US¢/kWh N/Aviii N/Aviii N/Aviii 20–40xliv 20xlv
see Chapter 7
3.5–10 4.4–14 5.2–17
Wind Energy (Off-
Shore, Large Turbines)
20–120xlii 3,200–5,000xlvi 2.0–4.0 US¢/kWh N/Aviii N/Aviii N/Aviii 35–45xlii See above 7.5–15 9.7–19 12–23
General remarks/notes:
i All data are rounded to 2 significant digits. Most technology chapters (Chapters 2 through 7) provide additional and/or more detailed cost and performance information in the respective chapters’ sections on cost trends. Direct
comparison between levelized cost estimates taken directly from the literature should take the underlying assumptions into due consideration.
ii Device sizes are intended to be representative of current/recent sizes. If future sizes are expected to differ from these values, this is included in the footnotes to the relevant technologies.
iii For combined heat and power (CHP) plants, heat production is considered as a by-product in the calculation of the levelized cost of electricity providing full capital cost information as a stand-alone plant.
iv HHV: Higher heating value. LHV: Lower heating value.
v LCOE: Levelized cost of electricity. The levelized cost usually includes all private costs that accrue upstream in the value chain of electricity production, but they do not include the cost of transmission and distribution to the final
customer. Output subsidies for RE generation and tax credits are not included. However, indirect taxes and subsidies on inputs or commodities affecting the prices of inputs and, hence, private cost, cannot be fully excluded.
Depending on the context of discussion, LCOE may also stand for levelized cost of energy.
Bioenergy:
vi A circulating fluid bed (CFB) is a turbulent (high gas flow) fluid bed where solid particles are captured and returned to the bed. A fluid bed itself is a collection of small solid particles suspended and kept in motion by an upward flow of
fluid, typically a gas.
vii The reference data are for a 50 MW plant. Investment costs for larger and smaller plants have been rescaled according to the power law: Specific investment costsize 2 = Investment costsize 1 x (Size 2/Size 1)n-1, where the scaling factor n
= 0.7. Capital cost estimates include facilities for fuel handling and preparation, boiler and air quality control, steam turbine and auxiliaries, balance of plant, general facilities and engineering fee, project and process contingency,
allowance for funds used during construction, owner costs, and taxes and fees.
viii The abbreviation ‘N/A’ means here ‘not applicable’.
ix Feedstock is wood with HHV = 20.0 GJ/t, LHV = 18.6 GJ/t.
x A mechanical stoker is a machine or device that feeds fuel to a boiler.
xi CHP: Combined heat and power.
xii The calculation of the by-product revenue for the large-scale CHP plant assumes: heat output used for industrial applications is 5.38 GJ of heat per MWh electricity; steam is valued at USD2005 4.85/GJ (75% of US pulp and paper
purchased steam price) (EIA, 2009, Table 7.2); and 75% of heat output is sold.
xiii The reference data are for a 50 MW plant. Investment costs for larger and smaller plants have been rescaled according to the power law: Specific investment costsize 2 = Investment costsize 1 x (Size 2/Size 1)n-1, where the scaling factor n
= 0.9 (Peters et al., 2003). The cofiring investment costs estimates were developed for retrofits of existing coal-fired power plants in the USA and include facilities for fuel handling and preparation, additional expenditures for boiler
modifications, balance of plant, general facilities and engineering, project and process contingency, allowance for funds used during construction, owner costs, and taxes and fees. Cofiring cost estimate protocols in the USA do not
include prorated boiler costs.
xiv ORC: Organic Rankine Cycle.
xv For the calculation of the by-product revenue for small-scale CHP plants, hot water is valued at USD2005 12.51/GJ (average of Rauch (2010) and Skjoldborg (2010)), 33% of gross value is taken into account, because the operator can
only recover a portion of the value and because use of hot water is seasonal.
xvi Heat output used for hot water is 18.51 GJ of heat per MWh electricity.
xvii The reference data are for a 5 MW CHP plant. Investment costs for larger and smaller plants have been rescaled according to the power law: Specific investment costsize 2 = Investment costsize 1 x (Size 2/Size 1)n-1, where the scaling factor
n =0.7 (Peters et al., 2003).
Continued next page
1'
214
Recent Renewable Energy Cost and Performance Parameters Annex III
xviii Heat output used for hot water is 12.95 GJ of heat per MWh electricity.
xix ICE: Internal combustion engine.
xx Heat output used for hot water is in the range of 2.373 to 10.86 GJ/MWh.
Direct solar energy – photovoltaic (PV) systems:
xxi In 2009, wholesale factory PV module prices decreased by more than 50%. As a result, the market prices for installed PV systems in Germany, the most competitive market,
decreased by over 30% in 2009 compared to about 10% in 2008 (see Section 3.8.3). 2009 market price data from Germany is used as the lower bound for investment
costs of residential rooftop systems (Bundesverband Solarwirtschaft e.V., 2010) and for utility-scale fixed tilt systems (Bloomberg, 2010). Based on US market data for
2008 and 2009, larger, commercial rooftop systems are assumed to have a 5% lower investment cost than the smaller, residential rooftop systems (NREL, 2011b; see also
section 3.8.3). Tracking systems are assumed to have a 15-20% higher investment cost than the one-axis, non-tracking systems considered here (NREL, 2011a; see also
Section 3.8.3). Capacity-weighted averages of investment costs in the USA in 2009 (NREL, 2011b) are used as upper bound to capture the investment cost ranges typical of
roughly 80% of global installations in 2009 (see Section 3.4.1 and Section 3.8.3).
xxii O&M costs of PV systems are low and are given in a range between 0.5 and 1.5% annually of the initial investment costs (Breyer et al., 2009; IEA, 2010c).
xxiii The main parameter that influences the capacity factor of a PV system is the actual annual solar irradiation in kWh/m²/yr at a given location and the type of system. Capacity
factors of some recently installed systems are provided in Sharma (2011).
xxiv The upper limit of utility-scale PV systems represents current status. Much larger systems (up to 1 GW) are in the proposal and development phase and might be realized within
the next decade.
Direct solar energy – concentrating solar power (CSP):
xxv Project sizes of CSP plants can minimally match the size of a single power generating system (e.g., a 25 kW dish/engine system). However, the range provided is typical for
projects being built or proposed today. ‘Power Parks’ consisting of multiple CSP plants in a single location are also being proposed at sizes of up to or exceeding 1 GW (4 x
250 MW).
xxvi Cost ranges are for parabolic trough plants with six hours of thermal energy storage in 2009. Investment cost includes direct plus indirect costs where indirect costs include
engineering, procurement and construction mark-up, owner costs, land, and taxes. Investment costs are lower for plants without storage and higher for plants with larger
storage capacity. The IEA (2010a) estimates investment costs as low as USD2005 3,800/kW for plants without storage and as high as USD2005 7,600/kW for plants with large
storage (assumed currency base year: 2009). Capacity factors vary as well, if thermal storage is installed (see note xxviii).
xxvii The IEA (2010a) states O&M costs relative to energy output as US¢ 1.2 to 2.7/kWh (assumed currency base year: 2009). Depending on actual energy output this may result
in lower or higher annual O&M cost compared to the range stated here.
xxviii Capacity factor for a parabolic trough plant with six hours of thermal energy storage for solar resource classes typical of the southwest USA. Depending on the size of the
thermal storage capacity, capacity factors as well as investment costs vary substantially. Apart from the Solar Electric Generating Station plants in California, new CSP plants
only became operational from 2007 onwards, thus few actual performance data are available and most of the literature just gives estimated or predicted capacity factors.
Sharma (2011) reports multi-year (1998-2002) average capacity factors of 12.4 to 27.7% for plants without thermal storage, but with natural gas backup. The IEA (2010a)
states that plants in Spain with 15 hours of storage may produce up to 6,600 hours per year. This is equivalent to a 75% capacity factor, if production occurs at full capacity
during the 6,600 hours. Larger storage also increases investment costs (see note xxvi).
Geothermal energy:
xxix Investment cost includes: exploration and resource confirmation; drilling of production and injection wells; surface facilities and infrastructure; and the power plant. For
expansion projects (i.e., new plants in the same geothermal field) investment costs can be 10 to 15% lower (see Section 4.7.1). Investment cost ranges are based on
Bromley et al. (2010) (see also Figure 4.7).
xxx O&M costs are based on Hance (2005). In New Zealand, O&M costs range from US¢ 1 to 1.4/kWh for 20 to 50 MWe plant capacity (Barnett and Quinlivan, 2009), which are
equivalent to USD 83 to 117/kW/yr, i.e. considerably lower than those given by Hance (2005). For further information see Section 4.7.2.
xxxi The current (data for 2008-2009) worldwide capacity factor (CF) for condensing (flash) and binary-cycle plants in operation is 74.5%. Excluding some outliers, the lower and
upper bounds can be estimated as 60 and 90%. Typical CFs for new geothermal power plants are over 90% (Hance, 2005; DiPippo, 2008; Bertani, 2010). The worldwide
average CF for 2020 is projected to be 80%, and could be 85% in 2030 and as high as 90% in 2050 (see Sections 4.7.3 and 4.7.5).
xxxii 25 to 30 years is the common lifetime of geothermal power plants worldwide. This payback period allows for refurbishment or replacement of the aging surface plant at
the end of its lifetime, but is not equivalent to the economic resource lifetime of the geothermal reservoir, which is typically much longer (e.g., Larderello, Wairakei, The
Geysers: Section 4.7.3). In some reservoirs, however, the possibility of resource degradation over time is one of several factors that affect the economics of continuing plant
operation.
Hydropower:
xxxiii The mid-80% of project sizes is not well documented for hydropower. The range stated here is indicative of the full range of project sizes. Hydropower projects are always
site-specific as they are designed to use the flow and head at each site. Therefore, projects can be very small, down to a few kW in a small stream, and up to several
thousand MW, for example 18,000 MW for the Three Gorges project in China (which will be 22,400 MW when completed) (see Section 5.1.2). 90% of the installed
hydropower capacity and 94% of hydropower energy production today is in hydropower plants >10 MW in size (IJHD, 2010).
xxxiv The investment cost for hydropower projects can be as low as USD 400 to 500/kW but most realistic projects today lie in the range of USD 1,000 to 3,000/kW (Section
5.8.1).
xxxv O&M costs are usually given as a percentage of investment cost for hydropower projects. Typical values range from 1 to 4%, while the table relies on an average value of
2.5% applied to the range of investment costs. This will usually be sufficient to cover refurbishment of mechanical and electrical equipment like turbine overhaul, generator
rewinding and reinvestments in communication and control systems (Section 5.8.1).
Continued next page ➔
215
Annex III Recent Renewable Energy Cost and Performance Parameters
xxxvi Capacity factors (CF) will be determined by hydrological conditions, installed capacity and plant design, and the way the plant is operated (i.e., the degree of plant output
regulation). For power plant designs intended for maximum energy production (base-load) and with some regulation, CFs will often be from 30 to 60%. Figure 5.20 shows
average CFs for different world regions. For peaking-type power plants the CF will be much lower, down to 20%, as these stations are designed with much higher capacity
in order to meet peaking needs. CFs for run-of-river systems vary across a wide range (20 to 95%) depending on the geographical and climatological conditions, technology
and operational characteristics (see Section 5.8.3).
xxxvii Hydropower plants in general have very long physical lifetimes. There are many examples of hydropower plants that have been in operation for more than 100 years, with
regular upgrading of electrical and mechanical systems but no major upgrades of the most expensive civil structures (dams, tunnels, etc.). The IEA (2010d) reports that many
plants built 50 to 100 years ago are still operating today. For large hydropower plants, the lifetime can, hence, safely be set to at least 40 years, and an 80-year lifetime is
used as upper bound. For small-scale hydropower plants the typical lifetime can be set to 40 years, in some cases even less. The economic design lifetime may differ from
actual physical plant lifetimes, and will depend strongly on how hydropower plants are owned and financed (see Section 5.8.1).
Ocean Energy:
xxxviii The data supplied for tidal range power plants are based on a very small number of installations (see subsequent footnotes). Therefore, all data should be considered with
appropriate caution.
xxxix The only utility-scale tidal power station in the world is the 240 MW La Rance power station, which has been in successful operation since 1966. Other smaller projects have
been commissioned since then in China, Canada and Russia with 3.9 MW, 20 MW and 0.4 MW, respectively. The 254 MW Sihwa barrage is expected to be commissioned
in 2011 and will then become the largest tidal power station in the world. Numerous projects have been identified, some of them with very large capacities, including in the
UK (Severn Estuary, 9.3 GW), India (1.8 GW), Korea (740 MW) and Russia (the White Sea and Sea of Okhotsk, 28 GW). None have been considered to be economic yet and
many of them face environmental objections (Kerr, 2007). The projects at the Severn Estuary have been evaluated by the UK government and recently been deferred.
xl An earlier assessment suggests capacity factors in the range of 25 to 35% (Charlier, 2003).
xli Tidal barrages resemble hydropower plants, which in general have very long design lives. Many hydropower plants have been in operation for more than 100 years, with regular
upgrading of electro-mechanical systems but no major upgrades of the most expensive civil structures (dams, tunnels etc). Tidal barrages are therefore assumed to have a
similar economic design lifetime as large hydropower plants, which can safely be set to at least 40 years (see Chapter 5).
Wind energy:
xlii Typical size of the device is taken as the power plant (not turbine) size. For onshore wind energy, 5 to 300 MW plants were common from 2007 to 2009, though both smaller
and larger plants are prevalent. For offshore wind energy, 20 to 120 MW plants were common from 2007 to 2009, though much larger plant sizes are expected in the
future. As a modular technology, a wide range of plant sizes is common, driven by market and geographic conditions.
xliii The lowest cost onshore wind power plants have been installed in China, with higher costs experienced in the USA and Europe. The range reflects the majority of onshore wind
power plants installed worldwide in 2009 (the most recent year for which solid data exist as of writing), but plants installed in China have average costs that can be even
below this range (USD 1,000 to 1,350/kW is common in China). In most cases, the investment cost includes the cost of the turbines (turbines, transportation to site, and
installation), grid connection (cables, sub-station, interconnection, but not more general transmission expansion costs), civil works (foundations, roads, buildings), and other
costs (engineering, licensing, permitting, environmental assessments, and monitoring equipment).
xliv Capacity factors depend in part on the strength of the underlying wind resource, which varies by region and site, as well as by turbine design.
xlv Modern wind turbines that meet International Electrotechnical Commission standards are designed for a 20-year life, and turbine lifetimes may even exceed 20 years if O&M
costs remain at an acceptable level. Wind power plants are typically financed over a 20-year time period.
xlvi For offshore wind power plants, the range in investment costs includes the majority of offshore wind power plants installed in the most recent years (through 2009) as well
as those plants planned for completion in the early 2010s. Because costs have risen in recent years, using the cost of recent and planned projects reasonably reflects
the ‘current’ cost of offshore wind power plants. In most cases, the investment cost includes the cost of the turbines (turbines, transportation to site, and installation),
grid connection (cables, sub-station, interconnection, but not more general transmission expansion costs), civil works (foundations, roads, buildings), and other costs
(engineering, licensing, permitting, environmental assessments, and monitoring equipment).
216
Recent Renewable Energy Cost and Performance Parameters Annex III
Figure A.III.2a | Tornado graph for renewable power technologies. For further explanation see Figure A.III.1a.
[UScent2005 /kWh]
0
Bioenergy (Co-Firing)
Bioenergy (Small Scale CHP, ORC)
Bioenergy (Small Scale CHP, Steam Turbine)
Bioenergy (Small Scale CHP, Gasification ICE)
Solar PV (Residential Rooftop)
Solar PV (Commercial Rooftop)
Solar PV (Utility Scale, Fixed Tilt)
Solar PV (Utility Scale, 1-Axis)
Concentrating Solar Power
Geothermal Energy (Condensing-Flash Plants)
Geothermal Energy (Binary-Cycle Plants)
Hydropower
Ocean Energy (Tidal Range)
Wind Energy (Onshore, Large Turbines)
Wind Energy (Offshore, Large Turbines)
10 20 30 40 50 60 70 80 90
Bioenergy (Direct Dedicated & Stoker CHP)
Capacity Factor
Discount Rate
Investment Cost
Varied Parameter
Non-Fuel O&M Cost
Fuel Cost
l I : I
:I -
I I I
I I I
I I I
I I I
I I I
I I I
I I I
I I I
I I I
I I I
I I I
I I I
,
I
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I
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z
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217
Annex III Recent Renewable Energy Cost and Performance Parameters
Figure A.III.2b | ‘Negative’ of tornado graph for renewable power technologies. For further explanation see Figure A.III.1b.
Note: The upper bounds of both geothermal energy technologies are calculated based on an assumed construction time of 4 years. In the simplified approach used for the sensitivity
analysis shown here, this assumption was not taken into account, resulting in upper bounds that were below those based on the more accurate methodology. The ranges were rescaled,
however, to yield the same results as the more accurate approach.
[UScent2005 /kWh]
0
Bioenergy (Co-Firing)
Bioenergy (Small Scale CHP, ORC)
Bioenergy (Small Scale CHP, Steam Turbine)
Bioenergy (Small Scale CHP, Gasification ICE)
Solar PV (Residential Rooftop)
Solar PV (Commercial Rooftop)
Solar PV (Utility Scale, Fixed Tilt)
Solar PV (Utility Scale, 1-Axis)
Concentrating Solar Power
Geothermal Energy (Condensing-Flash Plants)
Geothermal energy (Binary-Cycle Plants)
Hydropower
Ocean Energy (Tidal Range)
Wind Energy (On-Shore, Large Turbines)
Wind Energy (Off-Shore, Large Turbines)
10 20 30 40 50 60 70 80 90
Bioenergy (Direct Dedicated & Stoker CHP)
Capacity Factor
Discount Rate
Investment Cost
Fixed Parameter
Non-Fuel O&M Cost
][ == ':Fuel Cost ]==
! =Lt
] :=--]=
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218
Recent Renewable Energy Cost and Performance Parameters Annex III
Continued next page
Table A.III.2 | Cost-performance parameters for RE heating technologies.i
Input data Output data
Resource Technology
Typical
size of
the device
(MWth)
Investment
cost
(USD/kWth)
O&M cost, fixed
annual (USD/kW)
and/or variable
(USD/GJ)
By-product
revenue
(USD/GJfeed)ii
Feedstock
cost
(USD/GJfeed)
(Feedstock )
conversion
efficiency
(%)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOHiii
(USD/GJ)
Discount rate
3% 7% 10%
Bioenergy
Biomass (DPHiv) 0.005–0.1v 310–1,200vi 13–43 USD/kWvii N/Aviii 10–20 86–95 13–29 10–20
IEA (2007b)
14–70 15–77 16–84
Biomass (MSWix,
CHPx)
1–10xi 370–3,000xii, xiii 15–130 USD/kWvii N/Aviii 0–3 20–40xiv 80–91 10–20 1.4–34 1.8–38 2.1–41
Biomass (Steam
Turbine, CHP)xv 12–14 370–1,000xii 1.2–2.5 USD/kWvii N/Aviii 3.7–6.2 10–40 63–74 10–20 10–69 11–70 11–72
Biomass (Anaerobic
Digestion, CHP)
0.5–5xi 170–1,000xii,xvi 37–140 USD/kWvii N/Aviii 2.5–3.7xvii 20–30xviii 68–91 15–25 10–29 10–30 10–32
Solar Energy
Solar Thermal Heating
(DHWxix, China)
0.0017–0.01xx 120–540xxi 1.5–10 USD/kWxxii N/Aviii N/Aviii 20–80xxiii 4.1–13xxiv 10–15xxv see Section 3.8.2
and footnotes
2.8–56 3.6–67 4.2–75
Solar Thermal
Heating (DHW,
Thermo-siphon,
Combi-systems)
0.0017–0.07xx 530–1,800 5.6–22 USD/kWxxii N/Aviii N/Aviii 20–80xxiii 4.1–13xxiv 15–25 IEA (2007b) 8.8–134 12–170 16–200
Geothermal
Energy
Geothermal (Building
Heating)
0.1–1 1,600–3,900xxvi 8.3–11 USD/GJxxvii N/Aviii N/Aviii N/Aviii 25–30 20
see Section 4.7.6
20–50 24–65 28–77
Geothermal (District
Heating)
3.8–35 600–1,600xxvi 8.3–11 USD/GJxxvii N/Aviii N/Aviii N/Aviii 25–30 25 12–24 14–31 15–38
Geothermal (Greenhouses)
2–5.5 500–1,000xxvi 5.6–8.3 USD/GJxxvii N/Aviii N/Aviii N/Aviii 50 20 7.7–13 8.6–14 9.3–16
Geothermal
(Aquaculture Ponds,
Uncovered)
5–14 50–100xxvi 8.3–11 USD/GJxxvii N/Aviii N/Aviii N/Aviii 60 20 8.5–11 8.6–12 8.6–12
Geothermal Heat
Pumps (GHP)
0.01–0.35 900–3,800xxvi 7.8–8.9 USD/GJxxvii N/Aviii N/Aviii N/Aviii 25–30 20 14–42 17–56 19–68
General remarks/notes:
i All data are rounded to 2 significant digits. Most technology chapters (Chapters 2 through 4) provide additional and/or more detailed cost and performance information in the respective chapters’ sections on cost trends. The
assumptions underlying some of the production cost estimates quoted directly from the literature may, however, not be as transparent as the data sets in this Annex and should therefore be considered with caution.
ii CHP plants produce both, heat and electricity. Calculating the levelized cost of one product only, that is, either heat or electricity, can be done in different ways. One way is to assign a (discounted) market value to the ‘by-product’ and
subtract this additional income from the remaining expenses. This has been done in the calculation of the LCOE of bioenergy CHP plants. The calculation of LCOH has been done in a different way according to the methodology used
in IEA (2007) which served as main reference for the input data: Instead of considering electricity as a ‘by-product’ and subtracting its value from the remaining expenses for the supply of heat, the total expenses over the lifetime of
the investment project were split according to the average heat/electricity output ratio and only the heat shares of investment and O&M costs were taken into account. For this reason no by-product revenue is stated in the heat table.
Both methodologies come with different advantages/disadvantages.
iii LCOH: Levelized cost of heat supply. The levelized cost does not include the cost of transmission and distribution in the case of district heating systems. Output subsidies for RE generation and tax credits are also excluded. However,
indirect taxes and subsidies on inputs or commodities affecting the prices of inputs and, hence, private cost, cannot be fully excluded.
1
219
Annex III Recent Renewable Energy Cost and Performance Parameters
Bioenergy:
iv DPH: Domestic pellet heating.
v This range is typical of a low-energy single family dwelling (5 kW) or an apartment building (100 kW).
vi Investment costs of a biomass pellet heating system for the combustion plant only (including controls) range from USD2005 100 to 640/kW. The higher range stated above
includes civil works and fuel and heat storage (IEA, 2007).
vii Fixed annual O&M costs include costs of auxiliary energy. Auxiliary energy needs are 10 to 20 kWh/kWth/yr. Electricity prices are assumed to be USD2005 0.1 to 0.3/kWh. O&M
costs for CHP options include heat share only.
viii The abbreviation ‘N/A’ means here ‘not applicable’.
ix MSW: Municipal solid waste.
x CHP: Combined heat and power.
xi Typical size based on expert judgment and cost data from IEA (2007).
xii Investment costs for CHP options include heat share only. The electricity data in Table A.III.1 provides examples of total investment cost (see Section 2.4.4).
xiii Investment costs of MSW installations are mainly determined by the cost of flue gas cleaning, which can be allocated to waste treatment rather than to heat production (IEA,
2007).
xiv Heat-only MSW incinerators (as used in Denmark and Sweden) could have a thermal efficiency of 70 to 80%, but are not considered (IEA, 2007).
xv The ranges provided in this category are mainly based on two plants in Denmark and Austria and have been taken from IEA (2007).
xvi Investment costs for anaerobic digestion are based on literature values provided relative to electric capacity. For conversion to thermal capacity an electric efficiency of 37% and
a thermal efficiency of 55% were used (IEA, 2007).
xvii For anaerobic digestion, fuel prices are based on a mix of green crop maize and manure feedstock. Other biogas feedstocks include source-separated wastes and landfill gas, but
are not considered here (IEA, 2007).
xviii Conversion efficiencies include auxiliary heat input (8 to 20% for process heat) as well as use of any co-substrate that might increase process efficiency. For source-separated
wastes, the efficiency would be lower (IEA, 2007).
Solar Energy:
xix DHW: Domestic hot water.
xx 1 m² of collector area is converted into 0.7 kWth of installed capacity (see Section 3.4.1).
xxi 70% of the 13.5 million m² sales volume in 2004 was sold below Yuan 1,500/m² (USD2005 ~190/kW) (Zhang et al., 2010). The lower bound is based on data collected during
standardized interviews in the Zhejiang Province, China, in 2008 (Han et al., 2010). The higher bound is based on Chang et al. (2011).
xxii Fixed annual operating cost is assumed to be 1 to 3% of investment cost (IEA, 2007) plus annual cost of auxiliary energy. Annual auxiliary energy needs are 2 to 10 kWh/m².
Electricity prices are assumed to be USD2005 0.1 to 0.3/kWh.
xxiii The conversion efficiency of a solar thermal system tends to be larger in regions with lower solar irradiance. This partly offsets the negative effect of lower solar irradiance on
cost as energy yields per m² of collector area will be similar (Harvey, 2006, p. 461). Conversion efficiencies, which affect the resulting capacity factor, have not been used in
LCOH calculations directly.
xxiv Capacity factors are based on an assumed annual energy yield of 250 to 800 kWh/m² (IEA, 2007).
xxv Expected design lifetimes for Chinese solar water heaters are in the range of 10 to 15 years (Han et al., 2010).
Geothermal energy:
xxvi For geothermal heat pumps (GHP) the bounds of investment costs include residential and commercial or institutional installations. For commercial and institutional installations,
costs are assumed to include drilling costs, but for residential installations drilling costs are not included.
xxvii Average O&M costs expressed in USD2005/kWhth are: 0.03 to 0.04 for building and district heating and for aquaculture uncovered ponds, 0.02 to 0.03 for greenhouses, and
0.028 to 0.032 for GHP.
220
Recent Renewable Energy Cost and Performance Parameters Annex III
[USD2005 /GJ]
0 50 100 150 200
Biomass (Domestic Pellet Heating)
Biomass (MSW, CHP)
Biomass (Steam Turbine, CHP)
Biomass (Anaerobic Digestion, CHP)
Solar Thermal Heating (DHW, China)
Solar Thermal Heating (DHW, Thermo-Siphon, Combi)
Geothermal (Building Heating)
Geothermal (District Heating)
Geothermal (Greenhouses)
Geothermal (Aquaculture Ponds, Uncovered)
Geothermal Heat Pumps (GHP)
Discount Rate
Capacity Factor
Conversion Efficiency
Investment Cost
Non-Fuel O&M Cost
Fuel Cost
Varied Parameter
Figure A.III.3a | Tornado graph for renewable heat technologies. For further explanation see Figure A.III.1a.
Note: It may be somewhat misleading that solar thermal and geothermal heat applications do not show any sensitivity to variations in conversion efficiencies. This is due to the fact
that the energy input for solar and geothermal has zero cost and that the effect of higher conversion efficiencies of the energy input on LCOH works solely via an increase in annual
output. Variations in annual output, in turn, are fully captured by varying the capacity factor.
I 7 ■ ]r I
I
: I •
I : i ] 4 I I I IT I I I I Tl I I I 7 I I I T I I I I i I I I I t I I I
I I I
221
Annex III Recent Renewable Energy Cost and Performance Parameters
Figure A.III.3b | ‘Negative’ of tornado graph for renewable heat technologies. For further explanation see Figure A.III.1b.
[USD2005 /GJ]
0 50 100 150 200
Biomass (Domestic Pellet Heating)
Biomass (MSW, CHP)
Biomass (Steam Turbine, CHP)
Biomass (Anaerobic Digestion, CHP)
Solar Thermal Heating (DHW, China)
Solar Thermal Heating (DHW, Thermo-Siphon, Combi)
Geothermal (Building heating)
Geothermal (District heating)
Geothermal (Greenhouses)
Geothermal (Aquaculture ponds, uncovered)
Geothermal Heat Pumps (GHP)
Discount Rate
Capacity Factor
Conversion Efficiency
Investment Cost
Non-Fuel O&M Cost
Fuel Cost
I Fixed Parameter ■
l = : l : = l ' [ ];= ' '
-=
222
Recent Renewable Energy Cost and Performance Parameters Annex III
Table A.III.3 | Cost-performance parameters for biofuels.i
Input data Output data
Feedstock Fuel, Region
Typical
size of the
device
(MWth)
Investment
cost
(USD/kWth)ii
O&M cost, fixed
annual (USD/kWth)
and non-feed
variable
(USD/GJfeed)
By-product
Revenue
(USD/GJfeed)
Feedstock
cost
(USD/GJfeed)
Feedstock
conversion
efficiencyiii
(%)
Product only
(product +
by-product)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOF iv
USD/GJHHV
v
Discount rate
3% 7% 10%
Sugarcane
Ethanol Co-product:
sugarvi
Overall 170–1,000 83–360
16–35 USD/kWth and
0.87 USD/GJfeed
4.3 2.1–7.1 17 (39) 50% 20
Alfstad (2008), Bain
(2007), Kline et al.
(2007)
2.4–39 3.5–42 4.5–46
Brazil, Case Avii See above 100–330
20–32 USD/kWth and
0.87 USD/GJfeed
See above 2.1–6.5viii See above See above See above
Bohlmann and Cesar
(2006), Oliverio (2006),
van den Wall Bake et
al. (2009)
2.4–38 3.5–41 4.5–44
Argentina See above 110–340
21–34 USD/kWth and
0.87 USD/GJfeed
See above 6.5ix See above See above See above
Oliverio and Riberio
(2006), see also row
‘Overall’ above
28–39 30–42 31–46
Caribbean
Basinx, xi See above 110–360
22–35 USD/kWth and
0.87 USD/GJfeed
See above 2.6–6.2 See above See above See above
Rosillo-Calle et al.
(2000) see also row
‘Overall’ above
6.4–38 7.7–42 8.8–46
Colombia See above 100–320
20–31 USD/kWth and
0.87 USD/GJfeed
See above 5.6 See above See above See above
McDonald and
Schrattenholzer (2001),
Goldemberg (1996), see
also row ‘Overall’ above
23–32 24–36 25–39
India See above 110–340
21–33 USD/kWth and
0.87 USD/GJfeed
See above 2.6–6.2 See above See above See above see row ‘Overall’ above 5.9–37 7.1–41 8.2–44
Mexico See above 83–260
16–25 USD/kWth and
0.87 USD/GJfeed
See above 5.2–7.1 See above See above See above see row ‘Overall’ above 19–37 19–40 20–42
USA See above 100–320
20–31 USD/kWth and
0.87 USD/GJfeed
See above 6.2 See above See above See above see row ‘Overall’ above 27–36 28–40 29–43
Continued next page
A
223
Annex III Recent Renewable Energy Cost and Performance Parameters
Input data Output data
Feedstock Fuel, Region
Typical
size of the
device
(MWth)
Investment
cost
(USD/kWth)ii
O&M cost, fixed
annual (USD/kWth)
and non-feed
variable
(USD/GJfeed)
By-product
Revenue
(USD/GJfeed)
Feedstock
cost
(USD/GJfeed)
Feedstock
conversion
efficiencyiii
(%)
Product only
(product +
by-product)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOF iv
USD/GJHHV
v
Discount rate
3% 7% 10%
Corn
Ethanol By-product:
DDGSxii
Overall N/A 160–310
9–27 USD/kWth and
1.98 USD/GJfeed
1.56 4.2–10xiii 54 (91) 95% 20
Alfstad (2008), Bain
(2007), Kline et al.
(2007)
9.3–22 9.5–22 10–23
USA 140–550xiv 160–240
9–18 USD/kWth and
1.98 USD/GJfeed
See above 4.2–10xv See above See above See above
Delta-T Corporation
(1997), Ibsen et al.
(2005), Jechura (2005),
see also row ‘Overall’
above
9.3–22 9.5–22 10–23
Argentina See above 170–260
9–17 USD/kWth and
1.98 USD/GJfeed
See above 7.5 See above See above See above
McAloon et al. (2000).
RFA (2011), University
of Illinois (2011), see
also row ‘Overall’ above
16–17 16–17 17–18
Canada See above 200–310
13–27 USD/kWth and
1.98 USD/GJfeed
See above 4.8–5.7 See above See above See above see row ‘Overall’ above 11–15 12–15 12–16
Wheat
Ethanol By-product:
DDGSxii
Overall 150–610 140–280xvi 8–25 USD/kWth and
1.41 USD/GJfeed
1.74 5.1–13 49 (91) 95% 20
Alfstad (2008), Bain
(2007), Kline et al.
(2007)
12–28 12–28 12-28
USA See above 140–220
8–17 USD/kWth and
1.41 USD/GJfeed
See above 6.3–13 See above See above See above
OECD (2002), Shapouri
and Salassi (2006),
USDA (2007), see also
‘Overall’
13–28 14–28 14–28
Argentina See above 150–230
8–16 USD/kWth and
1.41 USD/GJfeed
See above 6.5–7 See above See above See above see row ‘Overall’ above 14–16 14–16 14–17
Canada See above 190–280
12–25 USD/kWth and
1.41 USD/GJfeed
See above 5.1–6.9 See above See above See above see row ‘Overall’ above 12–16 12–17 12–17
Continued next page
1
224
Recent Renewable Energy Cost and Performance Parameters Annex III
Input data Output data
Feedstock Fuel, Region
Typical
size of the
device
(MWth)
Investment
cost
(USD/kWth)ii
O&M cost, fixed
annual (USD/kWth)
and non-feed
variable
(USD/GJfeed)
By-product
Revenue
(USD/GJfeed)
Feedstock
cost
(USD/GJfeed)
Feedstock
conversion
efficiencyiii
(%)
Product only
(product +
by-product)
Capacity
factor
(%)
Economic
design
lifetime
(years)
References
LCOF iv
USD/GJHHV
v
Discount rate
3% 7% 10%
Soy Oil
Biodieselxvii By-product:
Glycerinxviii
Overall 44–440 160–320
9–46 USD/kWth and
2.58 USD/GJfeed
0.58 7.0–24 103 (107)19 95% 20
Alfstad (2008), Bain
(2007), Kline et al.
(2007), Haas et al.
(2006), Sheehan et al.
(2006)
9.4–28 10–28 10–28
Argentina See above 170–320
12–42 USD/kWth and
2.58 USD/GJfeed
See above 14–16xx See above See above See above
Chicago Board of Trade
(2006), see also row
‘Overall’ above
16–19 16–19 17–20
Brazil See above 160–310
9–27 USD/kWth and
2.58 USD/GJfeed
See above 7.0–18xx See above See above See above
Chicago Board of Trade
(2006), see also row
‘Overall’ above
9.4–21 10–21 10–21
USA See above 160–300
12–46 USD/kWth and
2.58 USD/GJfeed
See above 9.7–24 See above See above See above
USDA (2006), see also
row ‘Overall’ above
12–28 12–28 12–28
Palm Oil
Biodiesel By-product:
Glycerinxviii
Overall 44–440 160–340
10–46 USD/kWth
and 2.58 USD/GJfeed
0.58 6.1–45 103 (107) 95% 20
Alfstad (2008), Bain
(2007), Kline et al.
(2007), Haas et al.
(2006), Sheehan et al.
(1998)
8.7–48 8.9–48 9.0–49
Colombia See above 160–300
10–34 USD/kWth and
2.58 USD/GJfeed
See above 6.1–45 See above See above See above see row ‘Overall’ above 8.7–48 8.8–48 9.0–49
Caribbean
Basinx See above 180- 340
13–46 USD/kWth and
2.58 USD/GJfeed
See above 11–45 See above See above See above see row ‘Overall’ above 14–48 14–48 14–48
Wood,
Bagasse,
other
Pyrolytic Fuel Oil By-product:
Electricityxxi
Overall 110–440 160–240
12–44 USD/kWth
and 0.42 USD/GJfeed
0.07 0.44–5.5xxii 67 (69) 95% 20 Ringer et al. (2006) 2.3–12 2.6–12 2.8–12
USA See above 160–230
19–44 USD/kWth and
0.42 USD/GJfeed
See above 1.4–5.5 See above See above See above see row ‘Overall’ above 4.0–12 4.3–12 4.5–12
Brazil See above 160–240
12–24 USD/kWth and
0.42 USD/GJfeed
See above 0.44–5.5 See above See above See above see row ‘Overall’ above 2.3–11 2.5–11 2.8–11
Continued next page
1
225
Annex III Recent Renewable Energy Cost and Performance Parameters
General remarks/notes:
i All data are rounded to two significant digits. Chapter 2 provides additional cost and performance information in the section on cost trends. The assumptions underlying some
of the production cost estimates quoted directly from the literature may, however, not be as transparent as the data sets in this Annex and should therefore be considered
with caution.
ii Investment cost is based on plant capacity factor and not at 100% stream factor, which is the normal convention.
iii The feedstock conversion efficiency measured in energy units of input relative to energy units of output is stated for biomass only. Conversion factors for a mixture of biomass
and fossil inputs are generally lower.
iv LCOF: Levelized Cost of Transport Fuels. The levelized costs of transport fuels include all private costs that accrue upstream in the bioenergy system, but do not include the cost
of transportation and distribution to the final customers. Output subsidies for RE generation and tax credits are also excluded. However, indirect taxes and subsidies on inputs
or commodities affecting the prices of inputs and, hence, private cost, cannot be fully excluded.
v HHV: Higher heating value. LHV: Lower heating value.
vi Price of / revenue from sugar assumed to be USD2005 22/GJsugar based on average 2005 to 2008 world refined sugar price.
vii A cane sucrose content of 14% is used in the calculations of case A with the additional assumption that 50% of the total sucrose is used for sugar production (97% extraction
efficiency) and the other 50% of the total sucrose is used for ethanol production (90% conversion efficiency). The bagasse content of cane used is 16%. The HHVs used are
bagasse: 18.6 GJ/t; sucrose: 17.0 GJ/t; and as received cane: 5.3 GJ/t.
viii Brazilian feedstock costs have declined by 60% in the time period of 1975 to 2005 (Hettinga et al, 2009). For a more detailed discussion of historical and future cost trends see
also Sections 2.7.2, 2.7.3 and 2.7.4.
ix 55.2% of feed used is bagasse. More detailed information on feedstock characteristics can, for instance, be found in Section 2.3.1.
x Caribbean Basin Initiative Countries: Guatemala, Honduras, Nicaragua, Dominican Republic, Costa Rica, El Salvador, Guyana, and others.
xi Mixed ethanol/sugar mill: 50/50. More detailed information on sugar mills can be found in Section 2.3.4.
xii DDGS: Distillers dried grains plus solubles.
xiii For international feed range, supply curves from Kline et al. (2007) were used. For more information on feedstock supply curves and other economic considerations in biomass
resource assessments see Chapter section 2.2.3.
xiv Plant size range (140-550 MW is the equivalent of 25-100 million gallons per year (mmgpy) of anhydrous ethanol) is representative of the US corn ethanol industry (RFA, 2011).
xv Corn prices in the USA have declined by 63% in the period from 1975 to 2005 (Hettinga et al., 2009). For a more detailed discussion of historical and future cost trends see
also Sections 2.7.2, 2.7.3 and 2.7.4.
xvi Based on corn mill costs, corrected for HHV, and distillers dried grain (DDG) yields for wheat. More detailed information on milling can be found in Section 2.3.4.
xvii Installation basis is soy oil, not soybeans. Crush spread is used to convert from soybean prices to soy oil price. HHV soy oil = 39.6 GJ/t.
xviii Glycerine is also referred to as glycerol and is a simple polyol compound (1,2,3-propanetriol), and is central to all lipids known as triglycerides. Glycerine is a by-product of
biodiesel production.
xix The yield is higher than 100% because methanol (or other alcohol) is incorporated into the product.
xx Soy oil prices are estimated from soybean prices (Kline et al., 2007) and crush spread (Chicago Board of Trade, 2006).
xxi Process-derived gas and residual solids (char) are used for process heat and power. Excess electricity is exported as a by-product.
xxii Feedstock cost range is based on bagasse residue and wood residue prices (Kline et al. 2007). High range is for wood-based pyrolysis, low range is typical of pyrolysis of
bagasse. For more information on pyrolysis see Section 2.3.3.2. For a discussion of historical and future cost trends see also Sections 2.7.2, 2.7.3 and 2.7.4.
226
Recent Renewable Energy Cost and Performance Parameters Annex III
Figure A.III.4a | Tornado graph for biofuels. For further explanation see Figure A.III.1a.
Sugarcane Ethanol
Corn Ethanol
Wheat Ethanol
Soy Biodiesel
Palm Oil Biodiesel
Pyrolytic Fuel Oil
0 5 10 15 20 25 30 35 40 45 50
[USD2005 /GJ]
Discount Rate
Investment Cost
Non-Fuel O&M Cost
Fuel Cost
Varied Parameter
Figure A.III.4b | ‘Negative’ of tornado graph for biofuels. For further explanation see Figure A.III.1b.
Note: Aggregation of input data over various regions and subsequent LCOF calculations leads to slightly larger LCOF ranges than those obtained if region-specific LCOF values are
calculated first and these regional LCOF values are subsequently aggregated. In order to allow for a broad sensitivity analysis the first approach was followed here. The broader ranges
were, however, rescaled to yield the same results as the latter approach, which is more accurate and is used in the remainder of the report.
[USD2005 /GJ]
0 5 10 15 20 25 30 35 40 45 50
Sugarcane Ethanol
Corn Ethanol
Wheat Ethanol
Soy Biodiesel
Palm Oil Biodiesel
Pyrolytic Fuel Oil
Discount Rate
Investment Cost
Non-Fuel O&M Cost
Fuel Cost
Fixed Parameter
227
Annex III Recent Renewable Energy Cost and Performance Parameters
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have served to cross-check the reliability of the results from the meta-analysis based on
the data sources listed here.
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RENEWABLE ENERGY SOURCES AND CLIMATE CHANGE MITIGATION
“The Mitigation of Climate Change is one of the major challenges of the 21st century. The transition of our
global energy system to one that supports a high share of renewable energy could be an integral part of
humankind’s answer to this challenge. This report provides important groundwork for such a transition.”
– Hartmut Graßl, Former Director of the World Climate Research Programme,
Max Planck Institute for Meteorology
“This report is a comprehensive and authoritative contribution to the debate about whether renewable energy
can solve the climate problem in an economically attractive fashion. It’s a blueprint for further development
of the renewables sector and sets out clearly its role in climate change mitigation.”
– Geoffrey Heal, Columbia Business School, Columbia University
“Renewable energy resources and the technologies to expand their use provide the key energy source to address
multiple challenges of national and global sustainability for all. This report is invaluable for the 21st century.”
– Thomas B. Johansson, Lund University, Sweden, and Global Energy Assessment, IIASA
“The IPCC has provided us with a well-researched, carefully-presented assessment of the costs, risks and
opportunities of renewable energy sources. It provides a systematic analysis and scientific assessment of the
current knowledge about one of the most promising options to cut emissions of greenhouse gases and to
mitigate climate change.”
– Lord Nicholas Stern, IG Patel Professor of Economics & Government,
London School of Economics and Political Science
“Renewable energy can drive global sustainable development. The Special Report comes at the right time
and offers insights and guidance to strongly facilitate the change of our industrial metabolism.”
– Klaus Töpfer, IASS Potsdam – Institute for Advanced Sustainability Studies
“There may be a number of ways to achieve a low-carbon economy, but no pathway has been as thoroughly
and comprehensively explored as the range of possible contributions of renewable energy sources towards
achieving that goal contained in this IPCC Special Report.”
– John P. Weyant, Stanford University
Climate change is one of the great challenges of the 21st century. Its most severe impacts may still be
avoided if efforts are made to transform current energy systems. Renewable energy sources have a large
potential to displace emissions of greenhouse gases from the combustion of fossil fuels and thereby to mitigate
climate change. If implemented properly, renewable energy sources can contribute to social and economic
development, to energy access, to a secure and sustainable energy supply, and to a reduction of negative
impacts of energy provision on the environment and human health.
This Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) impartially
assesses the scientific literature on the potential role of renewable energy in the mitigation of climate
change for policy makers, the private sector, academic researchers and civil society. It covers six renewable
energy sources – bioenergy, direct solar energy, geothermal energy, hydropower, ocean energy and wind
energy – as well as their integration into present and future energy systems. It considers the environmental
and social consequences associated with the deployment of these technologies, and presents strategies to
overcome technical as well as non-technical obstacles to their application and diffusion. The authors also
compare the levelized cost of energy from renewable energy sources to recent non-renewable energy costs.
The Intergovernmental Panel on Climate Change (IPCC) is the leading international body for the assessment
of climate change. It was established by the United Nations Environment Programme (UNEP) and the World
Meteorological Organization (WMO) to provide the world with a clear scientific view on the current state of
knowledge in climate change and its potential environmental and socioeconomic impacts.
The full Special Report is published by Cambridge University Press (www.cambridge.org) and the digital version
can be accessed via the website of the IPCC Secretariat (www.ipcc.ch) or obtained on CDRom from the IPCC
Secretariat. This brochure contains the Summary for Policymakers and the Technical Summary of the report.
SPECIAL REPORT OF THE
INTERGOVERNMENTAL PANEL
ON CLIMATE CHANGE
MANAGING THE RISKS OF EXTREME
EVENTS AND DISASTERS TO ADVANCE
CLIMATE CHANGE ADAPTATION
SUMMARY FOR POLICYMAKERS
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1
Drafting Authors:
Simon K. Allen (Switzerland), Vicente Barros (Argentina), Ian Burton (Canada),
Diarmid Campbell-Lendrum (UK), Omar-Dario Cardona (Colombia), Susan L. Cutter (USA),
O. Pauline Dube (Botswana), Kristie L. Ebi (USA), Christopher B. Field (USA),
John W. Handmer (Australia), Padma N. Lal (Australia), Allan Lavell (Costa Rica),
Katharine J. Mach (USA), Michael D. Mastrandrea (USA), Gordon A. McBean (Canada),
Reinhard Mechler (Germany), Tom Mitchell (UK), Neville Nicholls (Australia),
Karen L. O’Brien (Norway), Taikan Oki (Japan), Michael Oppenheimer (USA), Mark Pelling
(UK), Gian-Kasper Plattner (Switzerland), Roger S. Pulwarty (USA), Sonia I. Seneviratne
(Switzerland), Thomas F. Stocker (Switzerland), Maarten K. van Aalst (Netherlands),
Carolina S. Vera (Argentina), Thomas J. Wilbanks (USA)
This Summary for Policymakers should be cited as:
IPCC, 2012: Summary for Policymakers. In: Managing the Risks of Extreme Events and Disasters to Advance
Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea,
K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups
I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, and
New York, NY, USA, pp. 1-19.
SPM Summary
for Policymakers
2
A.
Summary for Policymakers
Context
This Summary for Policymakers presents key findings from the Special Report on Managing the Risks of Extreme
Events and Disasters to Advance Climate Change Adaptation (SREX). The SREX approaches the topic by assessing the
scientific literature on issues that range from the relationship between climate change and extreme weather and
climate events (‘climate extremes’) to the implications of these events for society and sustainable development. The
assessment concerns the interaction of climatic, environmental, and human factors that can lead to impacts and
disasters, options for managing the risks posed by impacts and disasters, and the important role that non-climatic
factors play in determining impacts. Box SPM.1 defines concepts central to the SREX.
The character and severity of impacts from climate extremes depend not only on the extremes themselves but also on
exposure and vulnerability. In this report, adverse impacts are considered disasters when they produce widespread
damage and cause severe alterations in the normal functioning of communities or societies. Climate extremes,
exposure, and vulnerability are influenced by a wide range of factors, including anthropogenic climate change, natural
climate variability, and socioeconomic development (Figure SPM.1). Disaster risk management and adaptation to
climate change focus on reducing exposure and vulnerability and increasing resilience to the potential adverse impacts
of climate extremes, even though risks cannot fully be eliminated (Figure SPM.2). Although mitigation of climate
change is not the focus of this report, adaptation and mitigation can complement each other and together can
significantly reduce the risks of climate change. [SYR AR4, 5.3]
Figure SPM.1 | Illustration of the core concepts of SREX. The report assesses how exposure and vulnerability to weather and climate events determine impacts and the likelihood
of disasters (disaster risk). It evaluates the influence of natural climate variability and anthropogenic climate change on climate extremes and other weather and climate events
that can contribute to disasters, as well as the exposure and vulnerability of human society and natural ecosystems. It also considers the role of development in trends in exposure
and vulnerability, implications for disaster risk, and interactions between disasters and development. The report examines how disaster risk management and adaptation to climate
change can reduce exposure and vulnerability to weather and climate events and thus reduce disaster risk, as well as increase resilience to the risks that cannot be eliminated.
Other important processes are largely outside the scope of this report, including the influence of development on greenhouse gas emissions and anthropogenic climate change,
and the potential for mitigation of anthropogenic climate change. [1.1.2, Figure 1-1]
Disaster
CLIMATE
Natural
Variability
Anthropogenic
Climate Change
Weather and
Cmate
Events
Vulnerability
Exposure
DEVELOPMENT
Disaster Risk
Climate Change
Adaptation
Greenhouse Gas Emissions
3
Summary for Policymakers
Box SPM.1 | Definitions Central to SREX
Core concepts defined in the SREX glossary1 and used throughout the report include:
Climate Change: A change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean
and/or the variability of its properties and that persists for an extended period, typically decades or longer. Climate change may be due
to natural internal processes or external forcings, or to persistent anthropogenic changes in the composition of the atmosphere or in
land use.2
Climate Extreme (extreme weather or climate event): The occurrence of a value of a weather or climate variable above (or below)
a threshold value near the upper (or lower) ends of the range of observed values of the variable. For simplicity, both extreme weather
events and extreme climate events are referred to collectively as ‘climate extremes.’ The full definition is provided in Section 3.1.2.
Exposure: The presence of people; livelihoods; environmental services and resources; infrastructure; or economic, social, or cultural
assets in places that could be adversely affected.
Vulnerability: The propensity or predisposition to be adversely affected.
Disaster: Severe alterations in the normal functioning of a community or a society due to hazardous physical events interacting with
vulnerable social conditions, leading to widespread adverse human, material, economic, or environmental effects that require immediate
emergency response to satisfy critical human needs and that may require external support for recovery.
Disaster Risk: The likelihood over a specified time period of severe alterations in the normal functioning of a community or a society
due to hazardous physical events interacting with vulnerable social conditions, leading to widespread adverse human, material,
economic, or environmental effects that require immediate emergency response to satisfy critical human needs and that may require
external support for recovery.
Disaster Risk Management: Processes for designing, implementing, and evaluating strategies, policies, and measures to improve the
understanding of disaster risk, foster disaster risk reduction and transfer, and promote continuous improvement in disaster preparedness,
response, and recovery practices, with the explicit purpose of increasing human security, well-being, quality of life, resilience, and
sustainable development.
Adaptation: In human systems, the process of adjustment to actual or expected climate and its effects, in order to moderate harm or
exploit beneficial opportunities. In natural systems, the process of adjustment to actual climate and its effects; human intervention may
facilitate adjustment to expected climate.
Resilience: The ability of a system and its component parts to anticipate, absorb, accommodate, or recover from the effects of a
hazardous event in a timely and efficient manner, including through ensuring the preservation, restoration, or improvement of its
essential basic structures and functions.
Transformation: The altering of fundamental attributes of a system (including value systems; regulatory, legislative, or bureaucratic
regimes; financial institutions; and technological or biological systems).
____________
1 Reflecting the diversity of the communities involved in this assessment and progress in science, several of the definitions used in this Special Report differ in breadth or
focus from those used in the Fourth Assessment Report and other IPCC reports.
2 This definition differs from that in the United Nations Framework Convention on Climate Change (UNFCCC), where climate change is defined as: “a change of climate
which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability
observed over comparable time periods.” The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric
composition, and climate variability attributable to natural causes.
4
Summary for Policymakers
This report integrates perspectives from several historically distinct research communities studying climate science,
climate impacts, adaptation to climate change, and disaster risk management. Each community brings different
viewpoints, vocabularies, approaches, and goals, and all provide important insights into the status of the knowledge
base and its gaps. Many of the key assessment findings come from the interfaces among these communities. These
interfaces are also illustrated in Table SPM.1. To accurately convey the degree of certainty in key findings, the report
relies on the consistent use of calibrated uncertainty language, introduced in Box SPM.2. The basis for substantive
paragraphs in this Summary for Policymakers can be found in the chapter sections specified in square brackets.
Exposure and vulnerability are key determinants of disaster risk and of impacts when risk is realized.
[1.1.2, 1.2.3, 1.3, 2.2.1, 2.3, 2.5] For example, a tropical cyclone can have very different impacts depending on where
and when it makes landfall. [2.5.1, 3.1, 4.4.6] Similarly, a heat wave can have very different impacts on different
populations depending on their vulnerability. [Box 4-4, 9.2.1] Extreme impacts on human, ecological, or physical
systems can result from individual extreme weather or climate events. Extreme impacts can also result from nonextreme
events where exposure and vulnerability are high [2.2.1, 2.3, 2.5] or from a compounding of events or their
impacts. [1.1.2, 1.2.3, 3.1.3] For example, drought, coupled with extreme heat and low humidity, can increase the risk
of wildfire. [Box 4-1, 9.2.2]
Extreme and non-extreme weather or climate events affect vulnerability to future extreme events by modifying
resilience, coping capacity, and adaptive capacity. [2.4.3] In particular, the cumulative effects of disasters at local
Figure SPM.2 | Adaptation and disaster risk management approaches for reducing and managing disaster risk in a changing climate. This report assesses a wide range of
complementary adaptation and disaster risk management approaches that can reduce the risks of climate extremes and disasters and increase resilience to remaining risks as they
change over time. These approaches can be overlapping and can be pursued simultaneously. [6.5, Figure 6-3, 8.6]
Adaptation and Disaster Risk Management Approaches for a Changing Climate
Prepare, Respond,
and Recover Transformation
5
B.
or sub-national levels can substantially affect
livelihood options and resources and the capacity
of societies and communities to prepare for and
respond to future disasters. [2.2, 2.7]
A changing climate leads to changes in the
frequency, intensity, spatial extent, duration,
and timing of extreme weather and climate
events, and can result in unprecedented
extreme weather and climate events. Changes
in extremes can be linked to changes in the mean,
variance, or shape of probability distributions, or all
of these (Figure SPM.3). Some climate extremes (e.g.,
droughts) may be the result of an accumulation of
weather or climate events that are not extreme
when considered independently. Many extreme
weather and climate events continue to be the
result of natural climate variability. Natural variability
will be an important factor in shaping future
extremes in addition to the effect of anthropogenic
changes in climate. [3.1]
Observations of
Exposure, Vulnerability,
Climate Extremes,
Impacts, and Disaster
Losses
The impacts of climate extremes and the potential
for disasters result from the climate extremes
themselves and from the exposure and vulnerability
of human and natural systems. Observed changes
in climate extremes reflect the influence of
anthropogenic climate change in addition to natural
climate variability, with changes in exposure and
vulnerability influenced by both climatic and nonclimatic
factors.
Exposure and Vulnerability
Exposure and vulnerability are dynamic, varying across temporal and spatial scales, and depend on
economic, social, geographic, demographic, cultural, institutional, governance, and environmental factors
(high confidence). [2.2, 2.3, 2.5] Individuals and communities are differentially exposed and vulnerable based on
inequalities expressed through levels of wealth and education, disability, and health status, as well as gender, age,
class, and other social and cultural characteristics. [2.5]
Settlement patterns, urbanization, and changes in socioeconomic conditions have all influenced observed
trends in exposure and vulnerability to climate extremes (high confidence). [4.2, 4.3.5] For example, coastal
Summary for Policymakers
Without climate change
With climate change
extreme cold cold hot extreme hot
Probability of Occurrence Probability of Occurrence Probability of Occurrence
less
extreme cold
weather
more
extreme cold
weather
less
cold
weather
near constant
extreme cold
weather
near constant
cold
weather
more
extreme hot
weather
more
extreme hot
weather
more
extreme hot
weather
more
cold
weather
more
hot
weather
more
hot
weather
more
hot
weather
a)
b)
c)
Shifted Mean
Increased Variability
Changed Symmetry
Mean:
without and with weather change
Figure SPM.3 | The effect of changes in temperature distribution on
extremes. Different changes in temperature distributions between present and
future climate and their effects on extreme values of the distributions:
(a) effects of a simple shift of the entire distribution toward a warmer climate;
(b) effects of an increase in temperature variability with no shift in the mean;
(c) effects of an altered shape of the distribution, in this example a change in
asymmetry toward the hotter part of the distribution. [Figure 1-2, 1.2.2]
6
Summary for Policymakers
settlements, including in small islands and megadeltas, and mountain settlements are exposed and vulnerable to
climate extremes in both developed and developing countries, but with differences among regions and countries.
[4.3.5, 4.4.3, 4.4.6, 4.4.9, 4.4.10] Rapid urbanization and the growth of megacities, especially in developing countries,
have led to the emergence of highly vulnerable urban communities, particularly through informal settlements and
inadequate land management (high agreement, robust evidence). [5.5.1] See also Case Studies 9.2.8 and 9.2.9.
Vulnerable populations also include refugees, internally displaced people, and those living in marginal areas. [4.2, 4.3.5]
Climate Extremes and Impacts
There is evidence from observations gathered since 1950 of change in some extremes. Confidence in
observed changes in extremes depends on the quality and quantity of data and the availability of studies
analyzing these data, which vary across regions and for different extremes. Assigning ‘low confidence’ in
observed changes in a specific extreme on regional or global scales neither implies nor excludes the
possibility of changes in this extreme. Extreme events are rare, which means there are few data available to make
assessments regarding changes in their frequency or intensity. The more rare the event the more difficult it is to identify
long-term changes. Global-scale trends in a specific extreme may be either more reliable (e.g., for temperature
extremes) or less reliable (e.g., for droughts) than some regional-scale trends, depending on the geographical uniformity
of the trends in the specific extreme. The following paragraphs provide further details for specific climate extremes
from observations since 1950. [3.1.5, 3.1.6, 3.2.1]
It is very likely that there has been an overall decrease in the number of cold days and nights,3 and an overall increase
in the number of warm days and nights,3 at the global scale, that is, for most land areas with sufficient data. It is likely
that these changes have also occurred at the continental scale in North America, Europe, and Australia. There is medium
confidence in a warming trend in daily temperature extremes in much of Asia. Confidence in observed trends in daily
temperature extremes in Africa and South America generally varies from low to medium depending on the region. In
many (but not all) regions over the globe with sufficient data, there is medium confidence that the length or number
of warm spells or heat waves3 has increased. [3.3.1, Table 3-2]
There have been statistically significant trends in the number of heavy precipitation events in some regions. It is likely
that more of these regions have experienced increases than decreases, although there are strong regional and
subregional variations in these trends. [3.3.2]
There is low confidence in any observed long-term (i.e., 40 years or more) increases in tropical cyclone activity (i.e.,
intensity, frequency, duration), after accounting for past changes in observing capabilities. It is likely that there has been
a poleward shift in the main Northern and Southern Hemisphere extratropical storm tracks. There is low confidence in
observed trends in small spatial-scale phenomena such as tornadoes and hail because of data inhomogeneities and
inadequacies in monitoring systems. [3.3.2, 3.3.3, 3.4.4, 3.4.5]
There is medium confidence that some regions of the world have experienced more intense and longer droughts, in
particular in southern Europe and West Africa, but in some regions droughts have become less frequent, less intense,
or shorter, for example, in central North America and northwestern Australia. [3.5.1]
There is limited to medium evidence available to assess climate-driven observed changes in the magnitude and
frequency of floods at regional scales because the available instrumental records of floods at gauge stations are
limited in space and time, and because of confounding effects of changes in land use and engineering. Furthermore,
there is low agreement in this evidence, and thus overall low confidence at the global scale regarding even the sign of
these changes. [3.5.2]
____________
3 See SREX Glossary for definition of these terms: cold days / cold nights, warm days / warm nights, and warm spell – heat wave.
7
Summary for Policymakers
It is likely that there has been an increase in extreme coastal high water related to increases in mean sea level.
[3.5.3]
There is evidence that some extremes have changed as a result of anthropogenic influences, including
increases in atmospheric concentrations of greenhouse gases. It is likely that anthropogenic influences have led
to warming of extreme daily minimum and maximum temperatures at the global scale. There is medium confidence
that anthropogenic influences have contributed to intensification of extreme precipitation at the global scale. It is
likely that there has been an anthropogenic influence on increasing extreme coastal high water due to an increase in
mean sea level. The uncertainties in the historical tropical cyclone records, the incomplete understanding of the physical
mechanisms linking tropical cyclone metrics to climate change, and the degree of tropical cyclone variability provide
only low confidence for the attribution of any detectable changes in tropical cyclone activity to anthropogenic
influences. Attribution of single extreme events to anthropogenic climate change is challenging. [3.2.2, 3.3.1, 3.3.2,
3.4.4, 3.5.3, Table 3-1]
Disaster Losses
Economic losses from weather- and climate-related disasters have increased, but with large spatial and
interannual variability (high confidence, based on high agreement, medium evidence). Global weather- and
climate-related disaster losses reported over the last few decades reflect mainly monetized direct damages to assets,
and are unequally distributed. Estimates of annual losses have ranged since 1980 from a few US$ billion to above
200 billion (in 2010 dollars), with the highest value for 2005 (the year of Hurricane Katrina). Loss estimates are lowerbound
estimates because many impacts, such as loss of human lives, cultural heritage, and ecosystem services, are
difficult to value and monetize, and thus they are poorly reflected in estimates of losses. Impacts on the informal or
undocumented economy as well as indirect economic effects can be very important in some areas and sectors, but are
generally not counted in reported estimates of losses. [4.5.1, 4.5.3, 4.5.4]
Economic, including insured, disaster losses associated with weather, climate, and geophysical events4 are
higher in developed countries. Fatality rates and economic losses expressed as a proportion of gross
domestic product (GDP) are higher in developing countries (high confidence). During the period from 1970 to
2008, over 95% of deaths from natural disasters occurred in developing countries. Middle-income countries with rapidly
expanding asset bases have borne the largest burden. During the period from 2001 to 2006, losses amounted to about
1% of GDP for middle-income countries, while this ratio has been about 0.3% of GDP for low-income countries and
less than 0.1% of GDP for high-income countries, based on limited evidence. In small exposed countries, particularly
small island developing states, losses expressed as a percentage of GDP have been particularly high, exceeding 1% in
many cases and 8% in the most extreme cases, averaged over both disaster and non-disaster years for the period from
1970 to 2010. [4.5.2, 4.5.4]
Increasing exposure of people and economic assets has been the major cause of long-term increases in
economic losses from weather- and climate-related disasters (high confidence). Long-term trends in economic
disaster losses adjusted for wealth and population increases have not been attributed to climate change,
but a role for climate change has not been excluded (high agreement, medium evidence). These conclusions
are subject to a number of limitations in studies to date. Vulnerability is a key factor in disaster losses, yet it is not well
accounted for. Other limitations are: (i) data availability, as most data are available for standard economic sectors in
developed countries; and (ii) type of hazards studied, as most studies focus on cyclones, where confidence in observed
trends and attribution of changes to human influence is low. The second conclusion is subject to additional limitations:
(iii) the processes used to adjust loss data over time, and (iv) record length. [4.5.3]
____________
4 Economic losses and fatalities described in this paragraph pertain to all disasters associated with weather, climate, and geophysical events.
8
C.
Summary for Policymakers
Disaster Risk Management and Adaptation to Climate
Change: Past Experience with Climate Extremes
Past experience with climate extremes contributes to understanding of effective disaster risk management and
adaptation approaches to manage risks.
The severity of the impacts of climate extremes depends strongly on the level of the exposure and
vulnerability to these extremes (high confidence). [2.1.1, 2.3, 2.5]
Trends in exposure and vulnerability are major drivers of changes in disaster risk (high confidence). [2.5]
Understanding the multi-faceted nature of both exposure and vulnerability is a prerequisite for determining how
weather and climate events contribute to the occurrence of disasters, and for designing and implementing effective
adaptation and disaster risk management strategies. [2.2, 2.6] Vulnerability reduction is a core common element of
adaptation and disaster risk management. [2.2, 2.3]
Development practice, policy, and outcomes are critical to shaping disaster risk, which may be increased
by shortcomings in development (high confidence). [1.1.2, 1.1.3] High exposure and vulnerability are generally
the outcome of skewed development processes such as those associated with environmental degradation, rapid and
unplanned urbanization in hazardous areas, failures of governance, and the scarcity of livelihood options for the poor.
[2.2.2, 2.5] Increasing global interconnectivity and the mutual interdependence of economic and ecological systems
can have sometimes contrasting effects, reducing or amplifying vulnerability and disaster risk. [7.2.1] Countries more
effectively manage disaster risk if they include considerations of disaster risk in national development and sector plans
and if they adopt climate change adaptation strategies, translating these plans and strategies into actions targeting
vulnerable areas and groups. [6.2, 6.5.2]
Data on disasters and disaster risk reduction are lacking at the local level, which can constrain improvements
in local vulnerability reduction (high agreement, medium evidence). [5.7] There are few examples of national
disaster risk management systems and associated risk management measures explicitly integrating knowledge of and
uncertainties in projected changes in exposure, vulnerability, and climate extremes. [6.6.2, 6.6.4]
Inequalities influence local coping and adaptive capacity, and pose disaster risk management and adaptation
challenges from the local to national levels (high agreement, robust evidence). These inequalities reflect
socioeconomic, demographic, and health-related differences and differences in governance, access to livelihoods,
entitlements, and other factors. [5.5.1, 6.2] Inequalities also exist across countries: developed countries are often better
equipped financially and institutionally to adopt explicit measures to effectively respond and adapt to projected
changes in exposure, vulnerability, and climate extremes than are developing countries. Nonetheless, all countries face
challenges in assessing, understanding, and responding to such projected changes. [6.3.2, 6.6]
Humanitarian relief is often required when disaster risk reduction measures are absent or inadequate
(high agreement, robust evidence). [5.2.1] Smaller or economically less-diversified countries face particular
challenges in providing the public goods associated with disaster risk management, in absorbing the losses caused by
climate extremes and disasters, and in providing relief and reconstruction assistance. [6.4.3]
Post-disaster recovery and reconstruction provide an opportunity for reducing weather- and climate-related
disaster risk and for improving adaptive capacity (high agreement, robust evidence). An emphasis on rapidly
rebuilding houses, reconstructing infrastructure, and rehabilitating livelihoods often leads to recovering in ways that
recreate or even increase existing vulnerabilities, and that preclude longer-term planning and policy changes for
enhancing resilience and sustainable development. [5.2.3] See also assessment in Sections 8.4.1 and 8.5.2.
Risk sharing and transfer mechanisms at local, national, regional, and global scales can increase resilience
to climate extremes (medium confidence). Mechanisms include informal and traditional risk sharing mechanisms,
9
micro-insurance, insurance, reinsurance, and national, regional, and global risk pools. [5.6.3, 6.4.3, 6.5.3, 7.4] These
mechanisms are linked to disaster risk reduction and climate change adaptation by providing means to finance relief,
recovery of livelihoods, and reconstruction; reducing vulnerability; and providing knowledge and incentives for reducing
risk. [5.5.2, 6.2.2] Under certain conditions, however, such mechanisms can provide disincentives for reducing disaster
risk. [5.6.3, 6.5.3, 7.4.4] Uptake of formal risk sharing and transfer mechanisms is unequally distributed across regions
and hazards. [6.5.3] See also Case Study 9.2.13.
Attention to the temporal and spatial dynamics of exposure and vulnerability is particularly important
given that the design and implementation of adaptation and disaster risk management strategies and
policies can reduce risk in the short term, but may increase exposure and vulnerability over the longer
term (high agreement, medium evidence). For instance, dike systems can reduce flood exposure by offering
immediate protection, but also encourage settlement patterns that may increase risk in the long term. [2.4.2, 2.5.4,
2.6.2] See also assessment in Sections 1.4.3, 5.3.2, and 8.3.1.
National systems are at the core of countries’ capacity to meet the challenges of observed and projected
trends in exposure, vulnerability, and weather and climate extremes (high agreement, robust evidence).
Effective national systems comprise multiple actors from national and sub-national governments, the private sector,
research bodies, and civil society including community-based organizations, playing differential but complementary
roles to manage risk, according to their accepted functions and capacities. [6.2]
Closer integration of disaster risk management and climate change adaptation, along with the incorporation
of both into local, sub-national, national, and international development policies and practices, could provide
benefits at all scales (high agreement, medium evidence). [5.4, 5.5, 5.6, 6.3.1, 6.3.2, 6.4.2, 6.6, 7.4] Addressing
social welfare, quality of life, infrastructure, and livelihoods, and incorporating a multi-hazards approach into planning
and action for disasters in the short term, facilitates adaptation to climate extremes in the longer term, as is increasingly
recognized internationally. [5.4, 5.5, 5.6, 7.3] Strategies and policies are more effective when they acknowledge multiple
stressors, different prioritized values, and competing policy goals. [8.2, 8.3, 8.7]
Future Climate Extremes, Impacts, and Disaster Losses
Future changes in exposure, vulnerability, and climate extremes resulting from natural climate variability, anthropogenic
climate change, and socioeconomic development can alter the impacts of climate extremes on natural and human
systems and the potential for disasters.
Climate Extremes and Impacts
Confidence in projecting changes in the direction and magnitude of climate extremes depends on many
factors, including the type of extreme, the region and season, the amount and quality of observational
data, the level of understanding of the underlying processes, and the reliability of their simulation in
models. Projected changes in climate extremes under different emissions scenarios5 generally do not strongly diverge
in the coming two to three decades, but these signals are relatively small compared to natural climate variability over
this time frame. Even the sign of projected changes in some climate extremes over this time frame is uncertain. For
projected changes by the end of the 21st century, either model uncertainty or uncertainties associated with emissions
scenarios used becomes dominant, depending on the extreme. Low-probability, high-impact changes associated with
Summary for Policymakers
D.
____________
5 Emissions scenarios for radiatively important substances result from pathways of socioeconomic and technological development. This report uses
a subset (B1, A1B, A2) of the 40 scenarios extending to the year 2100 that are described in the IPCC Special Report on Emissions Scenarios
(SRES) and that did not include additional climate initiatives. These scenarios have been widely used in climate change projections and
encompass a substantial range of carbon dioxide equivalent concentrations, but not the entire range of the scenarios included in the SRES.
10
Summary for Policymakers
2 18
24
7
17
3
6
26
22
9
15
5
1
10
23
25
14
4
11
16
13 19
8
21
12
20
Full model range
Central 50%
intermodel range
Median
Scenarios: B1 A1B A2
2046−65 2081−00
1
2
5
10
20
Return period (Years)
Decrease in return period implies more frequent extreme temperature events (see caption)
Legend
2046−65 2081−00
1
2
5
10
20
22
Alaska/N.W. Canada - 1
2046−65 2081−00
1
2
5
10
20
E. Canada/Greenl./Icel. - 2
2046−65 2081−00
1
2
5
10
20
W. North America - 3
2046−65 2081−00
1
2
5
10
20
C. North America - 4
2046−65 2081−00
1
2
5
10
20
E. North America - 5
2046−65 2081−00
1
2
5
10
20
Central America/Mexico - 6
2046−65 2081−00
1
2
5
10
20
Amazon - 7
2046−65 2081−00
1
2
5
10
20
N.E. Brazil - 8
2046−65 2081−00
1
2
5
10
20
W. Coast South America - 9
2046−65 2081−00
1
2
5
10
20
S.E. South America - 10
2046−65 2081−00
1
2
5
10
20
31
24
23
N. Europe - 11
2046−65 2081−00
1
2
5
10
20
C. Europe - 12
2046−65 2081−00
1
2
5
10
20
S. Europe/Mediterranean - 13
2046−65 2081−00
1
2
5
10
20
Sahara - 14
2046−65 2081−00
1
2
5
10
20
W. Africa - 15
2046−65 2081−00
1
2
5
10
20
E. Africa - 16
2046−65 2081−00
1
2
5
10
20
S. Africa - 17
2046−65 2081−00
1
2
5
10
20
N. Asia - 18
2046−65 2081−00
1
2
5
10
20
E. Asia - 22
2046−65 2081−00
1
2
5
10
20
Tibetan Plateau - 21
2046−65 2081−00
1
2
5
10
20
C. Asia - 20
2046−65 2081−00
1
2
5
10
20
W. Asia - 19
2046−65 2081−00
1
2
5
10
20
S. Asia - 23
2046−65 2081−00
1
2
5
10
20
S.E. Asia - 24
2046−65 2081−00
1
2
5
10
20
N. Australia - 25
2046−65 2081−00
1
2
5
10
20
S. Australia/New Zealand - 26
2046−65 2081−00
1
2
5
10
20
Globe (Land only)
Figure SPM.4A | Projected return periods for the maximum daily temperature that was exceeded on average once during a 20-year period in the late 20th century (1981–2000). A decrease in return period implies more
frequent extreme temperature events (i.e., less time between events on average). The box plots show results for regionally averaged projections for two time horizons, 2046 to 2065 and 2081 to 2100, as compared to the late
20th century, and for three different SRES emissions scenarios (B1, A1B, A2) (see legend). Results are based on 12 global climate models (GCMs) contributing to the third phase of the Coupled Model Intercomparison Project
(CMIP3). The level of agreement among the models is indicated by the size of the colored boxes (in which 50% of the model projections are contained), and the length of the whiskers (indicating the maximum and minimum
projections from all models). See legend for defined extent of regions. Values are computed for land points only. The ‘Globe’ inset box displays the values computed using all land grid points. [3.3.1, Figure 3-1, Figure 3-5]
:
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11
the crossing of poorly understood climate thresholds cannot be excluded, given the transient and complex nature of
the climate system. Assigning ‘low confidence’ for projections of a specific extreme neither implies nor excludes the
possibility of changes in this extreme. The following assessments of the likelihood and/or confidence of projections are
generally for the end of the 21st century and relative to the climate at the end of the 20th century. [3.1.5, 3.1.7, 3.2.3,
Box 3-2]
Models project substantial warming in temperature extremes by the end of the 21st century. It is virtually
certain that increases in the frequency and magnitude of warm daily temperature extremes and decreases in cold
extremes will occur in the 21st century at the global scale. It is very likely that the length, frequency, and/or intensity
of warm spells or heat waves will increase over most land areas. Based on the A1B and A2 emissions scenarios, a
1-in-20 year hottest day is likely to become a 1-in-2 year event by the end of the 21st century in most regions, except
in the high latitudes of the Northern Hemisphere, where it is likely to become a 1-in-5 year event (see Figure SPM.4A).
Under the B1 scenario, a 1-in-20 year event would likely become a 1-in-5 year event (and a 1-in-10 year event in
Northern Hemisphere high latitudes). The 1-in-20 year extreme daily maximum temperature (i.e., a value that was
exceeded on average only once during the period 1981–2000) will likely increase by about 1°C to 3°C by the mid-21st
century and by about 2°C to 5°C by the late 21st century, depending on the region and emissions scenario (based on
the B1, A1B, and A2 scenarios). [3.3.1, 3.1.6, Table 3-3, Figure 3-5]
It is likely that the frequency of heavy precipitation or the proportion of total rainfall from heavy falls will
increase in the 21st century over many areas of the globe. This is particularly the case in the high latitudes and
tropical regions, and in winter in the northern mid-latitudes. Heavy rainfalls associated with tropical cyclones are likely
to increase with continued warming. There is medium confidence that, in some regions, increases in heavy precipitation
will occur despite projected decreases in total precipitation in those regions. Based on a range of emissions scenarios
(B1, A1B, A2), a 1-in-20 year annual maximum daily precipitation amount is likely to become a 1-in-5 to 1-in-15 year
event by the end of the 21st century in many regions, and in most regions the higher emissions scenarios (A1B and A2)
lead to a stronger projected decrease in return period. See Figure SPM.4B. [3.3.2, 3.4.4, Table 3-3, Figure 3-7]
Average tropical cyclone maximum wind speed is likely to increase, although increases may not occur in
all ocean basins. It is likely that the global frequency of tropical cyclones will either decrease or remain
essentially unchanged. [3.4.4]
There is medium confidence that there will be a reduction in the number of extratropical cyclones averaged
over each hemisphere. While there is low confidence in the detailed geographical projections of extratropical
cyclone activity, there is medium confidence in a projected poleward shift of extratropical storm tracks. There is low
confidence in projections of small spatial-scale phenomena such as tornadoes and hail because competing physical
processes may affect future trends and because current climate models do not simulate such phenomena. [3.3.2, 3.3.3,
3.4.5]
There is medium confidence that droughts will intensify in the 21st century in some seasons and areas, due
to reduced precipitation and/or increased evapotranspiration. This applies to regions including southern Europe
and the Mediterranean region, central Europe, central North America, Central America and Mexico, northeast Brazil,
and southern Africa. Elsewhere there is overall low confidence because of inconsistent projections of drought changes
(dependent both on model and dryness index). Definitional issues, lack of observational data, and the inability of models
to include all the factors that influence droughts preclude stronger confidence than medium in drought projections.
See Figure SPM.5. [3.5.1, Table 3-3, Box 3-3]
Projected precipitation and temperature changes imply possible changes in floods, although overall there
is low confidence in projections of changes in fluvial floods. Confidence is low due to limited evidence and
because the causes of regional changes are complex, although there are exceptions to this statement. There is medium
confidence (based on physical reasoning) that projected increases in heavy rainfall would contribute to increases in
local flooding in some catchments or regions. [3.5.2]
Summary for Policymakers
12
Summary for Policymakers
2 18
24
7
17
3
6
26
22
9
15
5
1
10
23
25
14
4
11
16
13 19
8
21
12
20
Full model range
Central 50%
intermodel range
Median
Scenarios: B1 A1B A2
Return period (Years)
2046−65 2081−00
3
5
10
20
50
Decrease in return period implies more frequent extreme precipitation events (see caption)
Legend
2046−65 2081−00
3
5
10
20
50
Globe (Land only)
2046−65 2081−00
3
5
10
20
50
S. Australia/New Zealand - 26
2046−65 2081−00
3
5
10
20
50
N. Australia - 25
2046−65 2081−00
3
5
10
20
50
2.4
S.E. Asia - 24
2046−65 2081−00
3
5
10
20
50
S. Asia - 23
2046−65 2081−00
3
5
10
20
50
53
W. Asia - 19
2046−65 2081−00
3
5
10
20
50
C. Asia - 20
2046−65 2081−00
3
5
10
20
50
Tibetan Plateau - 21
2046−65 2081−00
3
5
10
20
50
E. Asia - 22
2046−65 2081−00
3
5
10
20
50
N. Asia - 18
2046−65 2081−00
3
5
10
20
50
S. Africa - 17
2046−65 2081−00
3
5
10
20
50
E. Africa - 16
2046−65 2081−00
3
5
10
20
50
W. Africa - 15
2046−65 2081−00
3
5
10
20
50
64
56
Sahara - 14
2046−65 2081−00
3
5
10
20
50
S. Europe/Mediterranean - 13
2046−65 2081−00
3
5
10
20
50
C. Europe - 12
2046−65 2081−00
3
5
10
20
50
N. Europe - 11
2046−65 2081−00
3
5
10
20
50
S.E. South America - 10
2046−65 2081−00
3
5
10
20
50
53
61
W. Coast South America - 9
2046−65 2081−00
3
5
10
20
50
57
N.E. Brazil - 8
2046−65 2081−00
3
5
10
20
50
Amazon - 7
2046−65 2081−00
3
5
10
20
50
Central America/Mexico - 6
2046−65 2081−00
3
5
10
20
50
E. North America - 5
2046−65 2081−00
3
5
10
20
50
C. North America - 4
2046−65 2081−00
3
5
10
20
50
W. North America - 3
2046−65 2081−00
3
5
10
20
50
E. Canada/Greenl./Icel. - 2
2046−65 2081−00
3
5
10
20
50
2.4
Alaska/N.W. Canada - 1
Figure SPM.4B | Projected return periods for a daily precipitation event that was exceeded in the late 20th century on average once during a 20-year period (1981–2000). A decrease in return period implies more frequent
extreme precipitation events (i.e., less time between events on average). The box plots show results for regionally averaged projections for two time horizons, 2046 to 2065 and 2081 to 2100, as compared to the late 20th
century, and for three different SRES emissions scenarios (B1, A1B, A2) (see legend). Results are based on 14 GCMs contributing to the CMIP3. The level of agreement among the models is indicated by the size of the colored
boxes (in which 50% of the model projections are contained), and the length of the whiskers (indicating the maximum and minimum projections from all models). See legend for defined extent of regions. Values are computed
for land points only. The ‘Globe’ inset box displays the values computed using all land grid points. [3.3.2, Figure 3-1, Figure 3-7]
;
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L r:11
t
5:; 5 +
;
13
Summary for Policymakers
It is very likely that mean sea level rise will contribute to upward trends in extreme coastal high water
levels in the future. There is high confidence that locations currently experiencing adverse impacts such as coastal
erosion and inundation will continue to do so in the future due to increasing sea levels, all other contributing factors
being equal. The very likely contribution of mean sea level rise to increased extreme coastal high water levels, coupled
with the likely increase in tropical cyclone maximum wind speed, is a specific issue for tropical small island states.
[3.5.3, 3.5.5, Box 3-4]
There is high confidence that changes in heat waves, glacial retreat, and/or permafrost degradation will
affect high mountain phenomena such as slope instabilities, movements of mass, and glacial lake outburst
floods. There is also high confidence that changes in heavy precipitation will affect landslides in some regions. [3.5.6]
There is low confidence in projections of changes in large-scale patterns of natural climate variability.
Confidence is low in projections of changes in monsoons (rainfall, circulation) because there is little consensus in climate
models regarding the sign of future change in the monsoons. Model projections of changes in El Niño–Southern
-0.6 -0.2 0 0.2 0.6
Standard Deviation Standard Deviation
-0.4 0.4 -0.75 -0.50 -0.25 0 0.25 0.50 0.75
2046 - 2065
Change in consecutive dry days (CDD)
2046 - 2065
Soil moisture anomalies (SMA)
2081 - 2100
2081 - 2100
− Dryness + + Dryness −
Figure SPM.5 | Projected annual changes in dryness assessed from two indices. Left column: Change in annual maximum number of consecutive dry days (CDD: days with
precipitation <1 mm). Right column: Changes in soil moisture (soil moisture anomalies, SMA). Increased dryness is indicated with yellow to red colors; decreased dryness with
green to blue. Projected changes are expressed in units of standard deviation of the interannual variability in the three 20-year periods 1980–1999, 2046–2065, and 2081–2100.
The figures show changes for two time horizons, 2046–2065 and 2081–2100, as compared to late 20th-century values (1980–1999), based on GCM simulations under emissions
scenario SRES A2 relative to corresponding simulations for the late 20th century. Results are based on 17 (CDD) and 15 (SMA) GCMs contributing to the CMIP3. Colored shading
is applied for areas where at least 66% (12 out of 17 for CDD, 10 out of 15 for SMA) of the models agree on the sign of the change; stippling is added for regions where at least
90% (16 out of 17 for CDD, 14 out of 15 for SMA) of all models agree on the sign of the change. Grey shading indicates where there is insufficient model agreement (<66%).
[3.5.1, Figure 3-9]
E.
14
Summary for Policymakers
Oscillation variability and the frequency of El Niño episodes are not consistent, and so there is low confidence in
projections of changes in this phenomenon. [3.4.1, 3.4.2, 3.4.3]
Human Impacts and Disaster Losses
Extreme events will have greater impacts on sectors with closer links to climate, such as water, agriculture
and food security, forestry, health, and tourism. For example, while it is not currently possible to reliably project
specific changes at the catchment scale, there is high confidence that changes in climate have the potential to seriously
affect water management systems. However, climate change is in many instances only one of the drivers of future
changes, and is not necessarily the most important driver at the local scale. Climate-related extremes are also expected
to produce large impacts on infrastructure, although detailed analysis of potential and projected damages are limited
to a few countries, infrastructure types, and sectors. [4.3.2, 4.3.5]
In many regions, the main drivers of future increases in economic losses due to some climate extremes will
be socioeconomic in nature (medium confidence, based on medium agreement, limited evidence). Climate
extremes are only one of the factors that affect risks, but few studies have specifically quantified the effects of
changes in population, exposure of people and assets, and vulnerability as determinants of loss. However, the few
studies available generally underline the important role of projected changes (increases) in population and capital at
risk. [4.5.4]
Increases in exposure will result in higher direct economic losses from tropical cyclones. Losses will also
depend on future changes in tropical cyclone frequency and intensity (high confidence). Overall losses due to
extratropical cyclones will also increase, with possible decreases or no change in some areas (medium confidence).
Although future flood losses in many locations will increase in the absence of additional protection measures (high
agreement, medium evidence), the size of the estimated change is highly variable, depending on location, climate
scenarios used, and methods used to assess impacts on river flow and flood occurrence. [4.5.4]
Disasters associated with climate extremes influence population mobility and relocation, affecting host and
origin communities (medium agreement, medium evidence). If disasters occur more frequently and/or with greater
magnitude, some local areas will become increasingly marginal as places to live or in which to maintain livelihoods. In
such cases, migration and displacement could become permanent and could introduce new pressures in areas of
relocation. For locations such as atolls, in some cases it is possible that many residents will have to relocate. [5.2.2]
Managing Changing Risks
of Climate Extremes and Disasters
Adaptation to climate change and disaster risk management provide a range of complementary approaches for
managing the risks of climate extremes and disasters (Figure SPM.2). Effectively applying and combining approaches
may benefit from considering the broader challenge of sustainable development.
Measures that provide benefits under current climate and a range of future climate change scenarios,
called low-regrets measures, are available starting points for addressing projected trends in exposure,
vulnerability, and climate extremes. They have the potential to offer benefits now and lay the foundation
for addressing projected changes (high agreement, medium evidence). Many of these low-regrets strategies
produce co-benefits, help address other development goals, such as improvements in livelihoods, human well-being,
and biodiversity conservation, and help minimize the scope for maladaptation. [6.3.1, Table 6-1]
Potential low-regrets measures include early warning systems; risk communication between decisionmakers and local
citizens; sustainable land management, including land use planning; and ecosystem management and restoration.
15
Other low-regrets measures include improvements to health surveillance, water supply, sanitation, and irrigation and
drainage systems; climate-proofing of infrastructure; development and enforcement of building codes; and better
education and awareness. [5.3.1, 5.3.3, 6.3.1, 6.5.1, 6.5.2] See also Case Studies 9.2.11 and 9.2.14, and assessment in
Section 7.4.3.
Effective risk management generally involves a portfolio of actions to reduce and transfer risk and to
respond to events and disasters, as opposed to a singular focus on any one action or type of action (high
confidence). [1.1.2, 1.1.4, 1.3.3] Such integrated approaches are more effective when they are informed by and
customized to specific local circumstances (high agreement, robust evidence). [5.1] Successful strategies include a
combination of hard infrastructure-based responses and soft solutions such as individual and institutional capacity
building and ecosystem-based responses. [6.5.2]
Multi-hazard risk management approaches provide opportunities to reduce complex and compound hazards
(high agreement, robust evidence). Considering multiple types of hazards reduces the likelihood that risk reduction
efforts targeting one type of hazard will increase exposure and vulnerability to other hazards, in the present and
future. [8.2.5, 8.5.2, 8.7]
Opportunities exist to create synergies in international finance for disaster risk management and adaptation
to climate change, but these have not yet been fully realized (high confidence). International funding for
disaster risk reduction remains relatively low as compared to the scale of spending on international humanitarian
response. [7.4.2] Technology transfer and cooperation to advance disaster risk reduction and climate change adaptation
are important. Coordination on technology transfer and cooperation between these two fields has been lacking, which
has led to fragmented implementation. [7.4.3]
Stronger efforts at the international level do not necessarily lead to substantive and rapid results at the
local level (high confidence). There is room for improved integration across scales from international to local. [7.6]
Integration of local knowledge with additional scientific and technical knowledge can improve disaster
risk reduction and climate change adaptation (high agreement, robust evidence). Local populations document
their experiences with the changing climate, particularly extreme weather events, in many different ways, and this selfgenerated
knowledge can uncover existing capacity within the community and important current shortcomings. [5.4.4]
Local participation supports community-based adaptation to benefit management of disaster risk and climate
extremes. However, improvements in the availability of human and financial capital and of disaster risk and climate
information customized for local stakeholders can enhance community-based adaptation (medium agreement, medium
evidence). [5.6]
Appropriate and timely risk communication is critical for effective adaptation and disaster risk management
(high confidence). Explicit characterization of uncertainty and complexity strengthens risk communication. [2.6.3]
Effective risk communication builds on exchanging, sharing, and integrating knowledge about climate-related risks
among all stakeholder groups. Among individual stakeholders and groups, perceptions of risk are driven by psychological
and cultural factors, values, and beliefs. [1.1.4, 1.3.1, 1.4.2] See also assessment in Section 7.4.5.
An iterative process of monitoring, research, evaluation, learning, and innovation can reduce disaster risk
and promote adaptive management in the context of climate extremes (high agreement, robust evidence).
[8.6.3, 8.7] Adaptation efforts benefit from iterative risk management strategies because of the complexity, uncertainties,
and long time frame associated with climate change (high confidence). [1.3.2] Addressing knowledge gaps through
enhanced observation and research can reduce uncertainty and help in designing effective adaptation and risk
management strategies. [3.2, 6.2.5, Table 6-3, 7.5, 8.6.3] See also assessment in Section 6.6.
Table SPM.1 presents examples of how observed and projected trends in exposure, vulnerability, and
climate extremes can inform risk management and adaptation strategies, policies, and measures. The
Summary for Policymakers
16
Summary for Policymakers
Table SPM.1 | Illustrative examples of options for risk management and adaptation in the context of changes in exposure, vulnerability, and climate extremes. In each example, information is characterized at the
scale directly relevant to decisionmaking. Observed and projected changes in climate extremes at global and regional scales illustrate that the direction of, magnitude of, and/or degree of certainty for changes may
differ across scales.
The examples were selected based on availability of evidence in the underlying chapters, including on exposure, vulnerability, climate information, and risk management and adaptation options. They are intended
to reflect relevant risk management themes and scales, rather than to provide comprehensive information by region. The examples are not intended to reflect any regional differences in exposure and vulnerability, or in
experience in risk management.
The confidence in projected changes in climate extremes at local scales is often more limited than the confidence in projected regional and global changes. This limited confidence in changes places a focus on
low-regrets risk management options that aim to reduce exposure and vulnerability and to increase resilience and preparedness for risks that cannot be entirely eliminated. Higher-confidence projected changes in
climate extremes, at a scale relevant to adaptation and risk management decisions, can inform more targeted adjustments in strategies, policies, and measures. [3.1.6, Box 3-2, 6.3.1, 6.5.2]
Observed: Low confidence at global scale
regarding (climate-driven) observed changes in
the magnitude and frequency of floods.
Projected: Low confidence in projections of
changes in floods because of limited evidence
and because the causes of regional changes are
complex. However, medium confidence (based on
physical reasoning) that projected increases in
heavy precipitation will contribute to
rain-generated local flooding in some
catchments or regions.
[Table 3-1, 3.5.2]
Rapid expansion of poor people living
in informal settlements around
Nairobi has led to houses of weak
building materials being constructed
immediately adjacent to rivers and to
blockage of natural drainage areas,
increasing exposure and vulnerability.
[6.4.2, Box 6-2]
Observed: Low confidence regarding
trends in heavy precipitation in East
Africa, because of insufficient evidence.
Projected: Likely increase in heavy
precipitation indicators in East Africa.
[Table 3-2, Table 3-3, 3.3.2]
Limited ability to provide local flash
flood projections.
[3.5.2]
Low-regrets options that reduce exposure and
vulnerability across a range of hazard trends:
• Strengthening building design and regulation
• Poverty reduction schemes
• City-wide drainage and sewerage improvements
The Nairobi Rivers Rehabilitation and Restoration
Programme includes installation of riparian buffers,
canals, and drainage channels and clearance of existing
channels; attention to climate variability and change in
the location and design of wastewater infrastructure; and
environmental monitoring for flood early warning.
[6.3, 6.4.2, Box 6-2, Box 6-6]
Observed: Likely increase in extreme coastal
high water worldwide related to increases in
mean sea level.
Projected: Very likely that mean sea level rise
will contribute to upward trends in extreme
coastal high water levels.
High confidence that locations currently
experiencing coastal erosion and inundation will
continue to do so due to increasing sea level, in
the absence of changes in other contributing
factors.
Likely that the global frequency of tropical
cyclones will either decrease or remain
essentially unchanged.
Likely increase in average tropical cyclone
maximum wind speed, although increases may
not occur in all ocean basins.
[Table 3-1, 3.4.4, 3.5.3, 3.5.5]
Sparse regional and temporal coverage
of terrestrial-based observation
networks and limited in situ ocean
observing network, but with improved
satellite-based observations in recent
decades.
While changes in storminess may
contribute to changes in extreme coastal
high water levels, the limited
geographical coverage of studies to date
and the uncertainties associated with
storminess changes overall mean that a
general assessment of the effects of
storminess changes on storm surge is
not possible at this time.
[Box 3-4, 3.5.3]
Low-regrets options that reduce exposure and
vulnerability across a range of hazard trends:
• Maintenance of drainage systems
• Well technologies to limit saltwater contamination of
groundwater
• Improved early warning systems
• Regional risk pooling
• Mangrove conservation, restoration, and replanting
Specific adaptation options include, for instance,
rendering national economies more climate-independent
and adaptive management involving iterative learning. In
some cases there may be a need to consider relocation,
for example, for atolls where storm surges may
completely inundate them.
[4.3.5, 4.4.10, 5.2.2, 6.3.2, 6.5.2, 6.6.2, 7.4.4, 9.2.9,
9.2.11, 9.2.13]
Observed: Tides and El Niño–Southern
Oscillation have contributed to the more
frequent occurrence of extreme coastal
high water levels and associated
flooding experienced on some Pacific
Islands in recent years.
Projected: The very likely contribution
of mean sea level rise to increased
extreme coastal high water levels,
coupled with the likely increase in
tropical cyclone maximum wind speed, is
a specific issue for tropical small island
states.
See global changes column for
information on global projections for
tropical cyclones.
[Box 3-4, 3.4.4, 3.5.3]
Small island states in the Pacific,
Indian, and Atlantic Oceans, often
with low elevation, are particularly
vulnerable to rising sea levels and
impacts such as erosion, inundation,
shoreline change, and saltwater
intrusion into coastal aquifers. These
impacts can result in ecosystem
disruption, decreased agricultural
productivity, changes in disease
patterns, economic losses such as in
tourism industries, and population
displacement – all of which reinforce
vulnerability to extreme weather
events.
[3.5.5, Box 3-4, 4.3.5, 4.4.10, 9.2.9]
Flash floods in
informal
settlements in
Nairobi, Kenya
Options for risk management and
adaptation in the example
Exposure and vulnerability
at scale of risk management
in the example
Example GLOBAL
Observed (since 1950) and projected
(to 2100) global changes
REGIONAL
Observed (since 1950) and projected
(to 2100) changes in the example
SCALE OF RISK MANAGEMENT
Available information for the
example
Information on Climate Extreme Across Spatial Scales
Inundation related
to extreme sea
levels in tropical
small island
developing states
Continued next page
1'
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17
Summary for Policymakers
Table SPM.1 (continued)
Observed: Medium confidence that the length
or number of warm spells or heat waves has
increased since the middle of the 20th century, in
many (but not all) regions over the globe.
Very likely increase in number of warm days and
nights at the global scale.
Projected: Very likely increase in length,
frequency, and/or intensity of warm spells or
heat waves over most land areas.
Virtually certain increase in frequency and
magnitude of warm days and nights at the global
scale.
[Table 3-1, 3.3.1]
Observations and projections can
provide information for specific urban
areas in the region, with increased heat
waves expected due to regional trends
and urban heat island effects.
[3.3.1, 4.4.5]
Low-regrets options that reduce exposure and
vulnerability across a range of hazard trends:
• Early warning systems that reach particularly
vulnerable groups (e.g., the elderly)
• Vulnerability mapping and corresponding measures
• Public information on what to do during heat waves,
including behavioral advice
• Use of social care networks to reach vulnerable
groups
Specific adjustments in strategies, policies, and measures
informed by trends in heat waves include awareness
raising of heat waves as a public health concern; changes
in urban infrastructure and land use planning, for
example, increasing urban green space; changes in
approaches to cooling for public facilities; and
adjustments in energy generation and transmission
infrastructure.
[Table 6-1, 9.2.1]
Observed: Medium confidence in
increase in heat waves or warm spells in
Europe.
Likely overall increase in warm days and
nights over most of the continent.
Projected: Likely more frequent, longer,
and/or more intense heat waves or
warm spells in Europe.
Very likely increase in warm days and
nights.
[Table 3-2, Table 3-3, 3.3.1]
Factors affecting exposure and
vulnerability include age, pre-existing
health status, level of outdoor
activity, socioeconomic factors
including poverty and social isolation,
access to and use of cooling,
physiological and behavioral
adaptation of the population, and
urban infrastructure.
[2.5.2, 4.3.5, 4.3.6, 4.4.5, 9.2.1]
Observed: Low confidence in any observed
long-term (i.e., 40 years or more) increases in
tropical cyclone activity, after accounting for past
changes in observing capabilities.
Projected: Likely that the global frequency of
tropical cyclones will either decrease or remain
essentially unchanged.
Likely increase in average tropical cyclone
maximum wind speed, although increases may
not occur in all ocean basins.
Heavy rainfalls associated with tropical cyclones
are likely to increase.
Projected sea level rise is expected to further
compound tropical cyclone surge impacts.
[Table 3-1, 3.4.4]
Limited model capability to project
changes relevant to specific settlements
or other locations, due to the inability of
global models to accurately simulate
factors relevant to tropical cyclone
genesis, track, and intensity evolution.
[3.4.4]
Low-regrets options that reduce exposure and
vulnerability across a range of hazard trends:
• Adoption and enforcement of improved building
codes
• Improved forecasting capacity and implementation of
improved early warning systems (including
evacuation plans and infrastructures)
• Regional risk pooling
In the context of high underlying variability and
uncertainty regarding trends, options can include
emphasizing adaptive management involving learning
and flexibility (e.g., Cayman Islands National Hurricane
Committee).
[5.5.3, 6.5.2, 6.6.2, Box 6-7, Table 6-1, 7.4.4, 9.2.5,
9.2.11, 9.2.13]
See global changes column for global
projections.
Exposure and vulnerability are
increasing due to growth in
population and increase in property
values, particularly along the Gulf and
Atlantic coasts of the United States.
Some of this increase has been offset
by improved building codes.
[4.4.6]
Options for risk management and
adaptation in the example
Exposure and vulnerability
at scale of risk management
in the example
Example GLOBAL
Observed (since 1950) and projected
(to 2100) global changes
REGIONAL
Observed (since 1950) and projected
(to 2100) changes in the example
SCALE OF RISK MANAGEMENT
Available information for the
example
Information on Climate Extreme Across Spatial Scales
Impacts of heat
waves in urban
areas in Europe
Increasing losses
from hurricanes in
the USA and the
Caribbean
Observed: Medium confidence that some
regions of the world have experienced more
intense and longer droughts, but in some regions
droughts have become less frequent, less intense,
or shorter.
Projected: Medium confidence in projected
intensification of drought in some seasons and
areas. Elsewhere there is overall low confidence
because of inconsistent projections.
[Table 3-1, 3.5.1]
Less advanced agricultural practices
render region vulnerable to increasing
variability in seasonal rainfall,
drought, and weather extremes.
Vulnerability is exacerbated by
population growth, degradation of
ecosystems, and overuse of natural
resources, as well as poor standards
for health, education, and
governance.
[2.2.2, 2.3, 2.5, 4.4.2, 9.2.3]
Observed: Medium confidence in an
increase in dryness. Recent years
characterized by greater interannual
variability than previous 40 years, with
the western Sahel remaining dry and the
eastern Sahel returning to wetter
conditions.
Projected: Low confidence due
to inconsistent signal in model
projections.
[Table 3-2, Table 3-3, 3.5.1]
Sub-seasonal, seasonal, and interannual
forecasts with increasing uncertainty
over longer time scales.
Improved monitoring, instrumentation,
and data associated with early warning
systems, but with limited participation
and dissemination to at-risk populations.
[5.3.1, 5.5.3, 7.3.1, 9.2.3, 9.2.11]
Low-regrets options that reduce exposure and
vulnerability across a range of hazard trends:
• Traditional rain and groundwater harvesting and
storage systems
• Water demand management and improved irrigation
efficiency measures
• Conservation agriculture, crop rotation, and livelihood
diversification
• Increasing use of drought-resistant crop varieties
• Early warning systems integrating seasonal forecasts
with drought projections, with improved
communication involving extension services
• Risk pooling at the regional or national level
[2.5.4, 5.3.1, 5.3.3, 6.5, Table 6-3, 9.2.3, 9.2.11]
Droughts in the
context of food
security in West
Africa
I I I I
I I I I I I
18
Summary for Policymakers
importance of these trends for decisionmaking depends on their magnitude and degree of certainty at the temporal
and spatial scale of the risk being managed and on the available capacity to implement risk management options
(see Table SPM.1).
Implications for Sustainable Development
Actions that range from incremental steps to transformational changes are essential for reducing risk from
climate extremes (high agreement, robust evidence). Incremental steps aim to improve efficiency within existing
technological, governance, and value systems, whereas transformation may involve alterations of fundamental attributes
of those systems. Transformations, where they are required, are also facilitated through increased emphasis on adaptive
management and learning. Where vulnerability is high and adaptive capacity low, changes in climate extremes can
make it difficult for systems to adapt sustainably without transformational changes. Vulnerability is often concentrated
in lower-income countries or groups, although higher-income countries or groups can also be vulnerable to climate
extremes. [8.6, 8.6.3, 8.7]
Social, economic, and environmental sustainability can be enhanced by disaster risk management and
adaptation approaches. A prerequisite for sustainability in the context of climate change is addressing the
underlying causes of vulnerability, including the structural inequalities that create and sustain poverty and
constrain access to resources (medium agreement, robust evidence). This involves integrating disaster risk
management and adaptation into all social, economic, and environmental policy domains. [8.6.2, 8.7]
The most effective adaptation and disaster risk reduction actions are those that offer development benefits
in the relatively near term, as well as reductions in vulnerability over the longer term (high agreement,
medium evidence). There are tradeoffs between current decisions and long-term goals linked to diverse values,
interests, and priorities for the future. Short- and long-term perspectives on disaster risk management and adaptation
to climate change thus can be difficult to reconcile. Such reconciliation involves overcoming the disconnect between
local risk management practices and national institutional and legal frameworks, policy, and planning. [8.2.1, 8.3.1,
8.3.2, 8.6.1]
Progress toward resilient and sustainable development in the context of changing climate extremes can
benefit from questioning assumptions and paradigms and stimulating innovation to encourage new
patterns of response (medium agreement, robust evidence). Successfully addressing disaster risk, climate
change, and other stressors often involves embracing broad participation in strategy development, the capacity to
combine multiple perspectives, and contrasting ways of organizing social relations. [8.2.5, 8.6.3, 8.7]
The interactions among climate change mitigation, adaptation, and disaster risk management may have a
major influence on resilient and sustainable pathways (high agreement, limited evidence). Interactions
between the goals of mitigation and adaptation in particular will play out locally, but have global consequences.
[8.2.5, 8.5.2]
There are many approaches and pathways to a sustainable and resilient future. [8.2.3, 8.4.1, 8.6.1, 8.7] However, limits
to resilience are faced when thresholds or tipping points associated with social and/or natural systems are exceeded,
posing severe challenges for adaptation. [8.5.1] Choices and outcomes for adaptive actions to climate events must
reflect divergent capacities and resources and multiple interacting processes. Actions are framed by tradeoffs between
competing prioritized values and objectives, and different visions of development that can change over time. Iterative
approaches allow development pathways to integrate risk management so that diverse policy solutions can be
considered, as risk and its measurement, perception, and understanding evolve over time. [8.2.3, 8.4.1, 8.6.1, 8.7]
19
Summary for Policymakers
Box SPM.2 | Treatment of Uncertainty
Based on the Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties,6 this
Summary for Policymakers relies on two metrics for communicating the degree of certainty in key findings, which is based on author
teams’ evaluations of underlying scientific understanding:
• Confidence in the validity of a finding, based on the type, amount, quality, and consistency of evidence (e.g., mechanistic
understanding, theory, data, models, expert judgment) and the degree of agreement. Confidence is expressed qualitatively.
• Quantified measures of uncertainty in a finding expressed probabilistically (based on statistical analysis of observations or model
results, or expert judgment).
This Guidance Note refines the guidance provided to support the IPCC Third and Fourth Assessment Reports. Direct comparisons between
assessment of uncertainties in findings in this report and those in the IPCC Fourth Assessment Report are difficult if not impossible,
because of the application of the revised guidance note on uncertainties, as well as the availability of new information, improved
scientific understanding, continued analyses of data and models, and specific differences in methodologies applied in the assessed
studies. For some extremes, different aspects have been assessed and therefore a direct comparison would be inappropriate.
Each key finding is based on an author team’s evaluation of associated evidence and agreement. The confidence metric provides a
qualitative synthesis of an author team’s judgment about the validity of a finding, as determined through evaluation of evidence and
agreement. If uncertainties can be quantified probabilistically, an author team can characterize a finding using the calibrated likelihood
language or a more precise presentation of probability. Unless otherwise indicated, high or very high confidence is associated with
findings for which an author team has assigned a likelihood term.
The following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of
agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high. The
accompanying figure depicts summary statements for evidence and agreement and their relationship to confidence. There is flexibility in
this relationship; for a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of
evidence and degrees of agreement are correlated with increasing confidence.
The following terms indicate the assessed likelihood:
Term* Likelihood of the Outcome
Virtually certain 99–100% probability
Very likely 90–100% probability
Likely 66–100% probability
About as likely as not 33–66% probability
Unlikely 0–33% probability
Very unlikely 0–10% probability
Exceptionally unlikely 0–1% probability
* Additional terms that were used in limited circumstances in the Fourth
Assessment Report (extremely likely: 95–100% probability, more likely than
not: >50–100% probability, and extremely unlikely: 0–5% probability) may
also be used when appropriate.
____________
6 Mastrandrea, M.D., C.B. Field, T.F. Stocker, O. Edenhofer, K.L. Ebi, D.J. Frame, H. Held, E. Kriegler, K.J. Mach, P.R. Matschoss, G.-K. Plattner, G.W. Yohe, and F.W. Zwiers,
2010: Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties. Intergovernmental Panel on Climate Change
(IPCC), Geneva, Switzerland, www.ipcc.ch.
High agreement
Limited evidence
High agreement
Medium evidence
High agreement
Robust evidence
Medium agreement
Robust evidence
Medium agreement
Medium evidence
Medium agreement
Limited evidence
Low agreement
Limited evidence
Low agreement
Medium evidence
Low agreement
Robust evidence
Evidence (type, amount, quality, consistency)
Agreement
Confidence
Scale
A depiction of evidence and agreement statements and their relationship to
confidence. Confidence increases toward the top-right corner as suggested by the
increasing strength of shading. Generally, evidence is most robust when there are
multiple, consistent independent lines of high-quality evidence.
Summary for Policymakers
SPM
3
SPM
Drafting Authors:
Myles Allen (UK), Mustafa Babiker (Sudan), Yang Chen (China), Heleen de Coninck
(Netherlands/EU), Sarah Connors (UK), Renée van Diemen (Netherlands), Opha Pauline
Dube (Botswana), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Marion Ferrat
(UK/France), James Ford (UK/Canada), Piers Forster (UK), Sabine Fuss (Germany), Tania
Guillén Bolaños (Germany/Nicaragua), Jordan Harold (UK), Ove Hoegh-Guldberg (Australia),
Jean-Charles Hourcade (France), Daniel Huppmann (Austria), Daniela Jacob (Germany),
Kejun Jiang (China), Tom Gabriel Johansen (Norway), Mikiko Kainuma (Japan), Kiane de
Kleijne (Netherlands/EU), Elmar Kriegler (Germany), Debora Ley (Guatemala/Mexico),
Diana Liverman (USA), Natalie Mahowald (USA), Valérie Masson-Delmotte (France),
J. B. Robin Matthews (UK), Richard Millar (UK), Katja Mintenbeck (Germany), Angela Morelli
(Norway/Italy), Wilfran Moufouma-Okia (France/Congo), Luis Mundaca (Sweden/Chile),
Maike Nicolai (Germany), Chukwumerije Okereke (UK/Nigeria), Minal Pathak (India), Antony
Payne (UK), Roz Pidcock (UK), Anna Pirani (Italy), Elvira Poloczanska (UK/Australia), Hans-
Otto Pörtner (Germany), Aromar Revi (India), Keywan Riahi (Austria), Debra C. Roberts
(South Africa), Joeri Rogelj (Austria/Belgium), Joyashree Roy (India), Sonia I. Seneviratne
(Switzerland), Priyadarshi R. Shukla (India), James Skea (UK), Raphael Slade (UK), Drew
Shindell (USA), Chandni Singh (India), William Solecki (USA), Linda Steg (Netherlands),
Michael Taylor (Jamaica), Petra Tschakert (Australia/Austria), Henri Waisman (France),
Rachel Warren (UK), Panmao Zhai (China), Kirsten Zickfeld (Canada).
This Summary for Policymakers should be cited as:
IPCC, 2018: Summary for Policymakers. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts
of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways,
in the context of strengthening the global response to the threat of climate change, sustainable development,
and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla,
A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis,
E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. Cambridge University Press, Cambridge, UK and New
York, NY, USA, pp. 3-24. https://doi.org/10.1017/9781009157940.001.
Summary
SPM for Policymakers
SPM
Summary for Policymakers
4
Introduction
This Report responds to the invitation for IPCC ‘... to provide a Special Report in 2018 on the impacts of global warming of 1.5°C
above pre-industrial levels and related global greenhouse gas emission pathways’ contained in the Decision of the 21st Conference
of Parties of the United Nations Framework Convention on Climate Change to adopt the Paris Agreement.1
The IPCC accepted the invitation in April 2016, deciding to prepare this Special Report on the impacts of global warming of
1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global
response to the threat of climate change, sustainable development, and efforts to eradicate poverty.
This Summary for Policymakers (SPM) presents the key findings of the Special Report, based on the assessment of the available
scientific, technical and socio-economic literature2 relevant to global warming of 1.5°C and for the comparison between global
warming of 1.5°C and 2°C above pre-industrial levels. The level of confidence associated with each key finding is reported using
the IPCC calibrated language.3 The underlying scientific basis of each key finding is indicated by references provided to chapter
elements. In the SPM, knowledge gaps are identified associated with the underlying chapters of the Report.
A. Understanding Global Warming of 1.5°C4
A.1 Human activities are estimated to have caused approximately 1.0°C of global warming5 above
pre-industrial levels, with a likely range of 0.8°C to 1.2°C. Global warming is likely to reach 1.5°C
between 2030 and 2052 if it continues to increase at the current rate. (high confidence) (Figure
SPM.1) {1.2}
A.1.1 Reflecting the long-term warming trend since pre-industrial times, observed global mean surface temperature (GMST) for
the decade 2006–2015 was 0.87°C (likely between 0.75°C and 0.99°C)6 higher than the average over the 1850–1900
period (very high confidence). Estimated anthropogenic global warming matches the level of observed warming to within
±20% (likely range). Estimated anthropogenic global warming is currently increasing at 0.2°C (likely between 0.1°C and
0.3°C) per decade due to past and ongoing emissions (high confidence). {1.2.1, Table 1.1, 1.2.4}
A.1.2 Warming greater than the global annual average is being experienced in many land regions and seasons, including two to
three times higher in the Arctic. Warming is generally higher over land than over the ocean. (high confidence) {1.2.1, 1.2.2,
Figure 1.1, Figure 1.3, 3.3.1, 3.3.2}
A.1.3 Trends in intensity and frequency of some climate and weather extremes have been detected over time spans during which
about 0.5°C of global warming occurred (medium confidence). This assessment is based on several lines of evidence,
including attribution studies for changes in extremes since 1950. {3.3.1, 3.3.2, 3.3.3}
1 Decision 1/CP.21, paragraph 21.
2 The assessment covers literature accepted for publication by 15 May 2018.
3 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and
typeset in italics, for example, medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100%
probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely
95–100%, more likely than not >50–100%, more unlikely than likely 0–<50%, extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics,
for example, very likely. This is consistent with AR5.
4 See also Box SPM.1: Core Concepts Central to this Special Report.
5 Present level of global warming is defined as the average of a 30-year period centred on 2017 assuming the recent rate of warming continues.
6 This range spans the four available peer-reviewed estimates of the observed GMST change and also accounts for additional uncertainty due to possible short-term natural variability.
{1.2.1, Table 1.1}
SPM
Summary for Policymakers
5
A.2 Warming from anthropogenic emissions from the pre-industrial period to the present will persist for
centuries to millennia and will continue to cause further long-term changes in the climate system,
such as sea level rise, with associated impacts (high confidence), but these emissions alone are
unlikely to cause global warming of 1.5°C (medium confidence). (Figure SPM.1) {1.2, 3.3, Figure 1.5}
A.2.1 Anthropogenic emissions (including greenhouse gases, aerosols and their precursors) up to the present are unlikely to
cause further warming of more than 0.5°C over the next two to three decades (high confidence) or on a century time scale
(medium confidence). {1.2.4, Figure 1.5}
A.2.2 Reaching and sustaining net zero global anthropogenic CO2 emissions and declining net non-CO2 radiative forcing would
halt anthropogenic global warming on multi-decadal time scales (high confidence). The maximum temperature reached is
then determined by cumulative net global anthropogenic CO2 emissions up to the time of net zero CO2 emissions (high
confidence) and the level of non-CO2 radiative forcing in the decades prior to the time that maximum temperatures are
reached (medium confidence). On longer time scales, sustained net negative global anthropogenic CO2 emissions and/
or further reductions in non-CO2 radiative forcing may still be required to prevent further warming due to Earth system
feedbacks and to reverse ocean acidification (medium confidence) and will be required to minimize sea level rise (high
confidence). {Cross-Chapter Box 2 in Chapter 1, 1.2.3, 1.2.4, Figure 1.4, 2.2.1, 2.2.2, 3.4.4.8, 3.4.5.1, 3.6.3.2}
A.3 Climate-related risks for natural and human systems are higher for global warming of 1.5°C than
at present, but lower than at 2°C (high confidence). These risks depend on the magnitude and rate
of warming, geographic location, levels of development and vulnerability, and on the choices and
implementation of adaptation and mitigation options (high confidence). (Figure SPM.2) {1.3, 3.3,
3.4, 5.6}
A.3.1 Impacts on natural and human systems from global warming have already been observed (high confidence). Many land and
ocean ecosystems and some of the services they provide have already changed due to global warming (high confidence).
(Figure SPM.2) {1.4, 3.4, 3.5}
A.3.2 Future climate-related risks depend on the rate, peak and duration of warming. In the aggregate, they are larger if global
warming exceeds 1.5°C before returning to that level by 2100 than if global warming gradually stabilizes at 1.5°C, especially
if the peak temperature is high (e.g., about 2°C) (high confidence). Some impacts may be long-lasting or irreversible, such
as the loss of some ecosystems (high confidence). {3.2, 3.4.4, 3.6.3, Cross-Chapter Box 8 in Chapter 3}
A.3.3 Adaptation and mitigation are already occurring (high confidence). Future climate-related risks would be reduced by the
upscaling and acceleration of far-reaching, multilevel and cross-sectoral climate mitigation and by both incremental and
transformational adaptation (high confidence). {1.2, 1.3, Table 3.5, 4.2.2, Cross-Chapter Box 9 in Chapter 4, Box 4.2, Box
4.3, Box 4.6, 4.3.1, 4.3.2, 4.3.3, 4.3.4, 4.3.5, 4.4.1, 4.4.4, 4.4.5, 4.5.3}
SPM
Summary for Policymakers
6
60
50 3 000
2 000
1 000
40
30
20
10
0 0
3
2
1
0
Cumulative emissions of CO and future non-CO radiative forcing determine
the probability of limiting warming to 1.5°C
Billion tonnes CO per year (GtCO /yr) Billion tonnes CO (GtCO ) Watts per square metre (W/m)
b) Stylized net global CO emission pathways c) Cumulative net CO emissions d) Non-CO radiative forcing pathways
a) Observed global temperature change and modeled
responses to stylized anthropogenic emission and forcing pathways
Observed monthly global
mean surface temperature
Estimated anthropogenic
warming to date and
likely range
Faster immediate CO emission reductions
limit cumulative CO emissions shown in
panel (c).
Maximum temperature rise is determined by cumulative net CO emissions and net non-CO
radiative forcing due to methane, nitrous oxide, aerosols and other anthropogenic forcing agents.
Global warming relative to 1850-1900 (°C)
Cumulative CO
emissions in pathways
reaching net zero in
2055 and 2040
Non-CO radiative forcing
reduced aer 2030 or
not reduced aer 2030
1960
1980 2020 2060 2100 1980 2020 2060 2100 1980 2020 2060 2100
1980 2000 2020
2017
2040 2060 2080 2100
2.0
1.5
1.0
0.5
0
Likely range of modeled responses to stylized pathways
Faster CO reductions (blue in b & c) result in a higher
probability of limiting warming to 1.5°C
No reduction of net non-CO radiative forcing (purple in d)
results in a lower probability of limiting warming to 1.5°C
Global CO emissions reach net zero in 2055 while net
non-CO radiative forcing is reduced aer 2030 (grey in b, c & d)
Figure SPM.1 | Panel a: Observed monthly global mean surface temperature (GMST, grey line up to 2017, from the HadCRUT4, GISTEMP, Cowtan–Way, and
NOAA datasets) change and estimated anthropogenic global warming (solid orange line up to 2017, with orange shading indicating assessed likely range). Orange
dashed arrow and horizontal orange error bar show respectively the central estimate and likely range of the time at which 1.5°C is reached if the current rate
of warming continues. The grey plume on the right of panel a shows the likely range of warming responses, computed with a simple climate model, to a stylized
pathway (hypothetical future) in which net CO2 emissions (grey line in panels b and c) decline in a straight line from 2020 to reach net zero in 2055 and net non-
CO2 radiative forcing (grey line in panel d) increases to 2030 and then declines. The blue plume in panel a) shows the response to faster CO2 emissions reductions
(blue line in panel b), reaching net zero in 2040, reducing cumulative CO2 emissions (panel c). The purple plume shows the response to net CO2 emissions declining
to zero in 2055, with net non-CO2 forcing remaining constant after 2030. The vertical error bars on right of panel a) show the likely ranges (thin lines) and central
terciles (33rd – 66th percentiles, thick lines) of the estimated distribution of warming in 2100 under these three stylized pathways. Vertical dotted error bars in
panels b, c and d show the likely range of historical annual and cumulative global net CO2 emissions in 2017 (data from the Global Carbon Project) and of net
non-CO2 radiative forcing in 2011 from AR5, respectively. Vertical axes in panels c and d are scaled to represent approximately equal effects on GMST. {1.2.1, 1.2.3,
1.2.4, 2.3, Figure 1.2 and Chapter 1 Supplementary Material, Cross-Chapter Box 2 in Chapter 1}
c E: c
SPM
Summary for Policymakers
7
B. Projected Climate Change, Potential Impacts and Associated Risks
B.1 Climate models project robust7 differences in regional climate characteristics between present-day
and global warming of 1.5°C,8 and between 1.5°C and 2°C.8 These differences include increases
in: mean temperature in most land and ocean regions (high confidence), hot extremes in most
inhabited regions (high confidence), heavy precipitation in several regions (medium confidence),
and the probability of drought and precipitation deficits in some regions (medium confidence).
{3.3}
B.1.1 Evidence from attributed changes in some climate and weather extremes for a global warming of about 0.5°C supports
the assessment that an additional 0.5°C of warming compared to present is associated with further detectable changes in
these extremes (medium confidence). Several regional changes in climate are assessed to occur with global warming up
to 1.5°C compared to pre-industrial levels, including warming of extreme temperatures in many regions (high confidence),
increases in frequency, intensity, and/or amount of heavy precipitation in several regions (high confidence), and an increase
in intensity or frequency of droughts in some regions (medium confidence). {3.2, 3.3.1, 3.3.2, 3.3.3, 3.3.4, Table 3.2}
B.1.2 Temperature extremes on land are projected to warm more than GMST (high confidence): extreme hot days in mid-latitudes
warm by up to about 3°C at global warming of 1.5°C and about 4°C at 2°C, and extreme cold nights in high latitudes warm
by up to about 4.5°C at 1.5°C and about 6°C at 2°C (high confidence). The number of hot days is projected to increase in
most land regions, with highest increases in the tropics (high confidence). {3.3.1, 3.3.2, Cross-Chapter Box 8 in Chapter 3}
B.1.3 Risks from droughts and precipitation deficits are projected to be higher at 2°C compared to 1.5°C of global warming in
some regions (medium confidence). Risks from heavy precipitation events are projected to be higher at 2°C compared to
1.5°C of global warming in several northern hemisphere high-latitude and/or high-elevation regions, eastern Asia and
eastern North America (medium confidence). Heavy precipitation associated with tropical cyclones is projected to be
higher at 2°C compared to 1.5°C global warming (medium confidence). There is generally low confidence in projected
changes in heavy precipitation at 2°C compared to 1.5°C in other regions. Heavy precipitation when aggregated at global
scale is projected to be higher at 2°C than at 1.5°C of global warming (medium confidence). As a consequence of heavy
precipitation, the fraction of the global land area affected by flood hazards is projected to be larger at 2°C compared to
1.5°C of global warming (medium confidence). {3.3.1, 3.3.3, 3.3.4, 3.3.5, 3.3.6}
B.2 By 2100, global mean sea level rise is projected to be around 0.1 metre lower with global warming
of 1.5°C compared to 2°C (medium confidence). Sea level will continue to rise well beyond 2100
(high confidence), and the magnitude and rate of this rise depend on future emission pathways.
A slower rate of sea level rise enables greater opportunities for adaptation in the human and
ecological systems of small islands, low-lying coastal areas and deltas (medium confidence).
{3.3, 3.4, 3.6}
B.2.1 Model-based projections of global mean sea level rise (relative to 1986–2005) suggest an indicative range of 0.26 to 0.77
m by 2100 for 1.5°C of global warming, 0.1 m (0.04–0.16 m) less than for a global warming of 2°C (medium confidence).
A reduction of 0.1 m in global sea level rise implies that up to 10 million fewer people would be exposed to related risks,
based on population in the year 2010 and assuming no adaptation (medium confidence). {3.4.4, 3.4.5, 4.3.2}
B.2.2 Sea level rise will continue beyond 2100 even if global warming is limited to 1.5°C in the 21st century (high confidence).
Marine ice sheet instability in Antarctica and/or irreversible loss of the Greenland ice sheet could result in multi-metre rise
in sea level over hundreds to thousands of years. These instabilities could be triggered at around 1.5°C to 2°C of global
warming (medium confidence). (Figure SPM.2) {3.3.9, 3.4.5, 3.5.2, 3.6.3, Box 3.3}
7 Robust is here used to mean that at least two thirds of climate models show the same sign of changes at the grid point scale, and that differences in large regions are statistically
significant.
8 Projected changes in impacts between different levels of global warming are determined with respect to changes in global mean surface air temperature.
SPM
Summary for Policymakers
8
B.2.3 Increasing warming amplifies the exposure of small islands, low-lying coastal areas and deltas to the risks associated with
sea level rise for many human and ecological systems, including increased saltwater intrusion, flooding and damage to
infrastructure (high confidence). Risks associated with sea level rise are higher at 2°C compared to 1.5°C. The slower rate
of sea level rise at global warming of 1.5°C reduces these risks, enabling greater opportunities for adaptation including
managing and restoring natural coastal ecosystems and infrastructure reinforcement (medium confidence). (Figure SPM.2)
{3.4.5, Box 3.5}
B.3 On land, impacts on biodiversity and ecosystems, including species loss and extinction, are
projected to be lower at 1.5°C of global warming compared to 2°C. Limiting global warming to
1.5°C compared to 2°C is projected to lower the impacts on terrestrial, freshwater and coastal
ecosystems and to retain more of their services to humans (high confidence). (Figure SPM.2)
{3.4, 3.5, Box 3.4, Box 4.2, Cross-Chapter Box 8 in Chapter 3}
B.3.1 Of 105,000 species studied,9 6% of insects, 8% of plants and 4% of vertebrates are projected to lose over half of their
climatically determined geographic range for global warming of 1.5°C, compared with 18% of insects, 16% of plants and
8% of vertebrates for global warming of 2°C (medium confidence). Impacts associated with other biodiversity-related
risks such as forest fires and the spread of invasive species are lower at 1.5°C compared to 2°C of global warming (high
confidence). {3.4.3, 3.5.2}
B.3.2 Approximately 4% (interquartile range 2–7%) of the global terrestrial land area is projected to undergo a transformation
of ecosystems from one type to another at 1°C of global warming, compared with 13% (interquartile range 8–20%) at 2°C
(medium confidence). This indicates that the area at risk is projected to be approximately 50% lower at 1.5°C compared to
2°C (medium confidence). {3.4.3.1, 3.4.3.5}
B.3.3 High-latitude tundra and boreal forests are particularly at risk of climate change-induced degradation and loss, with woody
shrubs already encroaching into the tundra (high confidence) and this will proceed with further warming. Limiting global
warming to 1.5°C rather than 2°C is projected to prevent the thawing over centuries of a permafrost area in the range of
1.5 to 2.5 million km2 (medium confidence). {3.3.2, 3.4.3, 3.5.5}
B.4 Limiting global warming to 1.5°C compared to 2°C is projected to reduce increases in ocean
temperature as well as associated increases in ocean acidity and decreases in ocean oxygen levels
(high confidence). Consequently, limiting global warming to 1.5°C is projected to reduce risks
to marine biodiversity, fisheries, and ecosystems, and their functions and services to humans,
as illustrated by recent changes to Arctic sea ice and warm-water coral reef ecosystems (high
confidence). {3.3, 3.4, 3.5, Box 3.4, Box 3.5}
B.4.1 There is high confidence that the probability of a sea ice-free Arctic Ocean during summer is substantially lower at global
warming of 1.5°C when compared to 2°C. With 1.5°C of global warming, one sea ice-free Arctic summer is projected per
century. This likelihood is increased to at least one per decade with 2°C global warming. Effects of a temperature overshoot
are reversible for Arctic sea ice cover on decadal time scales (high confidence). {3.3.8, 3.4.4.7}
B.4.2 Global warming of 1.5°C is projected to shift the ranges of many marine species to higher latitudes as well as increase the
amount of damage to many ecosystems. It is also expected to drive the loss of coastal resources and reduce the productivity of
fisheries and aquaculture (especially at low latitudes). The risks of climate-induced impacts are projected to be higher at 2°C
than those at global warming of 1.5°C (high confidence). Coral reefs, for example, are projected to decline by a further 70–90%
at 1.5°C (high confidence) with larger losses (>99%) at 2°C (very high confidence). The risk of irreversible loss of many marine
and coastal ecosystems increases with global warming, especially at 2°C or more (high confidence). {3.4.4, Box 3.4}
9 Consistent with earlier studies, illustrative numbers were adopted from one recent meta-study.
SPM
Summary for Policymakers
9
10 Here, impacts on economic growth refer to changes in gross domestic product (GDP). Many impacts, such as loss of human lives, cultural heritage and ecosystem services, are difficult
to value and monetize.
B.4.3 The level of ocean acidification due to increasing CO2 concentrations associated with global warming of 1.5°C is projected to
amplify the adverse effects of warming, and even further at 2°C, impacting the growth, development, calcification, survival,
and thus abundance of a broad range of species, for example, from algae to fish (high confidence). {3.3.10, 3.4.4}
B.4.4 Impacts of climate change in the ocean are increasing risks to fisheries and aquaculture via impacts on the physiology,
survivorship, habitat, reproduction, disease incidence, and risk of invasive species (medium confidence) but are projected to
be less at 1.5°C of global warming than at 2°C. One global fishery model, for example, projected a decrease in global annual
catch for marine fisheries of about 1.5 million tonnes for 1.5°C of global warming compared to a loss of more than 3 million
tonnes for 2°C of global warming (medium confidence). {3.4.4, Box 3.4}
B.5 Climate-related risks to health, livelihoods, food security, water supply, human security, and
economic growth are projected to increase with global warming of 1.5°C and increase further with
2°C. (Figure SPM.2) {3.4, 3.5, 5.2, Box 3.2, Box 3.3, Box 3.5, Box 3.6, Cross-Chapter Box 6 in Chapter
3, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Chapter 5, 5.2}
B.5.1 Populations at disproportionately higher risk of adverse consequences with global warming of 1.5°C and beyond include
disadvantaged and vulnerable populations, some indigenous peoples, and local communities dependent on agricultural or
coastal livelihoods (high confidence). Regions at disproportionately higher risk include Arctic ecosystems, dryland regions,
small island developing states, and Least Developed Countries (high confidence). Poverty and disadvantage are expected
to increase in some populations as global warming increases; limiting global warming to 1.5°C, compared with 2°C, could
reduce the number of people both exposed to climate-related risks and susceptible to poverty by up to several hundred
million by 2050 (medium confidence). {3.4.10, 3.4.11, Box 3.5, Cross-Chapter Box 6 in Chapter 3, Cross-Chapter Box 9 in
Chapter 4, Cross-Chapter Box 12 in Chapter 5, 4.2.2.2, 5.2.1, 5.2.2, 5.2.3, 5.6.3}
B.5.2 Any increase in global warming is projected to affect human health, with primarily negative consequences (high confidence).
Lower risks are projected at 1.5°C than at 2°C for heat-related morbidity and mortality (very high confidence) and for
ozone-related mortality if emissions needed for ozone formation remain high (high confidence). Urban heat islands often
amplify the impacts of heatwaves in cities (high confidence). Risks from some vector-borne diseases, such as malaria and
dengue fever, are projected to increase with warming from 1.5°C to 2°C, including potential shifts in their geographic range
(high confidence). {3.4.7, 3.4.8, 3.5.5.8}
B.5.3 Limiting warming to 1.5°C compared with 2°C is projected to result in smaller net reductions in yields of maize, rice, wheat,
and potentially other cereal crops, particularly in sub-Saharan Africa, Southeast Asia, and Central and South America, and
in the CO2-dependent nutritional quality of rice and wheat (high confidence). Reductions in projected food availability are
larger at 2°C than at 1.5°C of global warming in the Sahel, southern Africa, the Mediterranean, central Europe, and the
Amazon (medium confidence). Livestock are projected to be adversely affected with rising temperatures, depending on the
extent of changes in feed quality, spread of diseases, and water resource availability (high confidence). {3.4.6, 3.5.4, 3.5.5,
Box 3.1, Cross-Chapter Box 6 in Chapter 3, Cross-Chapter Box 9 in Chapter 4}
B.5.4 Depending on future socio-economic conditions, limiting global warming to 1.5°C compared to 2°C may reduce the
proportion of the world population exposed to a climate change-induced increase in water stress by up to 50%, although
there is considerable variability between regions (medium confidence). Many small island developing states could
experience lower water stress as a result of projected changes in aridity when global warming is limited to 1.5°C, as
compared to 2°C (medium confidence). {3.3.5, 3.4.2, 3.4.8, 3.5.5, Box 3.2, Box 3.5, Cross-Chapter Box 9 in Chapter 4}
B.5.5 Risks to global aggregated economic growth due to climate change impacts are projected to be lower at 1.5°C than at
2°C by the end of this century10 (medium confidence). This excludes the costs of mitigation, adaptation investments and
the benefits of adaptation. Countries in the tropics and Southern Hemisphere subtropics are projected to experience the
largest impacts on economic growth due to climate change should global warming increase from 1.5°C to 2°C (medium
confidence). {3.5.2, 3.5.3}
SPM
Summary for Policymakers
10
B.5.6 Exposure to multiple and compound climate-related risks increases between 1.5°C and 2°C of global warming, with greater
proportions of people both so exposed and susceptible to poverty in Africa and Asia (high confidence). For global warming
from 1.5°C to 2°C, risks across energy, food, and water sectors could overlap spatially and temporally, creating new and
exacerbating current hazards, exposures, and vulnerabilities that could affect increasing numbers of people and regions
(medium confidence). {Box 3.5, 3.3.1, 3.4.5.3, 3.4.5.6, 3.4.11, 3.5.4.9}
B.5.7 There are multiple lines of evidence that since AR5 the assessed levels of risk increased for four of the five Reasons for
Concern (RFCs) for global warming to 2°C (high confidence). The risk transitions by degrees of global warming are now:
from high to very high risk between 1.5°C and 2°C for RFC1 (Unique and threatened systems) (high confidence); from
moderate to high risk between 1°C and 1.5°C for RFC2 (Extreme weather events) (medium confidence); from moderate to
high risk between 1.5°C and 2°C for RFC3 (Distribution of impacts) (high confidence); from moderate to high risk between
1.5°C and 2.5°C for RFC4 (Global aggregate impacts) (medium confidence); and from moderate to high risk between 1°C
and 2.5°C for RFC5 (Large-scale singular events) (medium confidence). (Figure SPM.2) {3.4.13; 3.5, 3.5.2}
B.6 Most adaptation needs will be lower for global warming of 1.5°C compared to 2°C (high confidence).
There are a wide range of adaptation options that can reduce the risks of climate change (high
confidence). There are limits to adaptation and adaptive capacity for some human and natural
systems at global warming of 1.5°C, with associated losses (medium confidence). The number and
availability of adaptation options vary by sector (medium confidence). {Table 3.5, 4.3, 4.5, Cross-
Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Chapter 5}
B.6.1 A wide range of adaptation options are available to reduce the risks to natural and managed ecosystems (e.g., ecosystembased
adaptation, ecosystem restoration and avoided degradation and deforestation, biodiversity management,
sustainable aquaculture, and local knowledge and indigenous knowledge), the risks of sea level rise (e.g., coastal defence
and hardening), and the risks to health, livelihoods, food, water, and economic growth, especially in rural landscapes
(e.g., efficient irrigation, social safety nets, disaster risk management, risk spreading and sharing, and communitybased
adaptation) and urban areas (e.g., green infrastructure, sustainable land use and planning, and sustainable water
management) (medium confidence). {4.3.1, 4.3.2, 4.3.3, 4.3.5, 4.5.3, 4.5.4, 5.3.2, Box 4.2, Box 4.3, Box 4.6, Cross-Chapter
Box 9 in Chapter 4}.
B.6.2 Adaptation is expected to be more challenging for ecosystems, food and health systems at 2°C of global warming than for
1.5°C (medium confidence). Some vulnerable regions, including small islands and Least Developed Countries, are projected
to experience high multiple interrelated climate risks even at global warming of 1.5°C (high confidence). {3.3.1, 3.4.5,
Box 3.5, Table 3.5, Cross-Chapter Box 9 in Chapter 4, 5.6, Cross-Chapter Box 12 in Chapter 5, Box 5.3}
B.6.3 Limits to adaptive capacity exist at 1.5°C of global warming, become more pronounced at higher levels of warming and
vary by sector, with site-specific implications for vulnerable regions, ecosystems and human health (medium confidence).
{Cross-Chapter Box 12 in Chapter 5, Box 3.5, Table 3.5}
SPM
Summary for Policymakers
11
10 Here, impacts on economic growth refer to changes in gross domestic product (GDP). Many impacts, such as loss of human lives, cultural heritage and ecosystem services, are difficult
to value and monetize.
1.0
1.5
2.0
0
1.0
1.5
2.0
0
Global mean surface temperature change
relative to pre-industrial levels (C)
Global mean surface temperature change
relative to pre-industrial levels (C)
2006-2015
How the level of global warming aects impacts and/or risks associated with
the Reasons for Concern (RFCs) and selected natural, managed and human
systems
Impacts and risks associated with the Reasons for Concern (RFCs)
Purple indicates very high
risks of severe impacts/risks
and the presence of
significant irreversibility or
the persistence of
climate-related hazards,
combined with limited
ability to adapt due to the
nature of the hazard or
impacts/risks.
Red indicates severe and
widespread impacts/risks.
Yellow indicates that
impacts/risks are detectable
and attributable to climate
change with at least medium
confidence.
White indicates that no
impacts are detectable and
attributable to climate
change.
Five Reasons For Concern (RFCs) illustrate the impacts and risks of
dierent levels of global warming for people, economies and ecosystems
across sectors and regions.
Heat-related
morbidity
and mortality
Level of additional
impact/risk due
to climate change
RFC1
Unique and
threatened
systems
RFC2
Extreme
weather
events
RFC4
Global
aggregate
impacts
RFC5
Large scale
singular
events
RFC3
Distribution
of impacts
Warm-water
corals
Terrestrial
ecosystems
Tourism
2006-2015
H
VH
VH
H
H
H
H
M
M-H
H
M
M
M
M
M
H
M
H
H
H
M
H
H
M
M
H
M
H
M
H
M
H
M
H
Impacts and risks for selected natural, managed and human systems
Confidence level for transition: L=Low, M=Medium, H=High and VH=Very high
Mangroves Small-scale
low-latitude
fisheries
Arctic
region
Coastal
flooding
Fluvial
flooding
Crop
yields
Undetectable
Moderate
High
Very high
Figure SPM.2 | Five integrative reasons for concern (RFCs) provide a framework for summarizing key impacts and risks across sectors and regions, and were
introduced in the IPCC Third Assessment Report. RFCs illustrate the implications of global warming for people, economies and ecosystems. Impacts and/or risks
for each RFC are based on assessment of the new literature that has appeared. As in AR5, this literature was used to make expert judgments to assess the levels
of global warming at which levels of impact and/or risk are undetectable, moderate, high or very high. The selection of impacts and risks to natural, managed and
human systems in the lower panel is illustrative and is not intended to be fully comprehensive. {3.4, 3.5, 3.5.2.1, 3.5.2.2, 3.5.2.3, 3.5.2.4, 3.5.2.5, 5.4.1, 5.5.3,
5.6.1, Box 3.4}
RFC1 Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and
have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its indigenous people, mountain glaciers and biodiversity hotspots.
RFC2 Extreme weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heat waves, heavy rain,
drought and associated wildfires, and coastal flooding.
RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards,
exposure or vulnerability.
RFC4 Global aggregate impacts: global monetary damage, global-scale degradation and loss of ecosystems and biodiversity.
RFC5 Large-scale singular events: are relatively large, abrupt and sometimes irreversible changes in systems that are caused by global warming. Examples
include disintegration of the Greenland and Antarctic ice sheets.
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SPM
Summary for Policymakers
12
11 References to pathways limiting global warming to 2°C are based on a 66% probability of staying below 2°C.
12 Non-CO2 emissions included in this Report are all anthropogenic emissions other than CO2 that result in radiative forcing. These include short-lived climate forcers, such as methane,
some fluorinated gases, ozone precursors, aerosols or aerosol precursors, such as black carbon and sulphur dioxide, respectively, as well as long-lived greenhouse gases, such as nitrous
oxide or some fluorinated gases. The radiative forcing associated with non-CO2 emissions and changes in surface albedo is referred to as non-CO2 radiative forcing. {2.2.1}
13 There is a clear scientific basis for a total carbon budget consistent with limiting global warming to 1.5°C. However, neither this total carbon budget nor the fraction of this budget
taken up by past emissions were assessed in this Report.
14 Irrespective of the measure of global temperature used, updated understanding and further advances in methods have led to an increase in the estimated remaining carbon budget of
about 300 GtCO2 compared to AR5. (medium confidence) {2.2.2}
15 These estimates use observed GMST to 2006–2015 and estimate future temperature changes using near surface air temperatures.
C. Emission Pathways and System Transitions Consistent with 1.5°C
Global Warming
C.1 In model pathways with no or limited overshoot of 1.5°C, global net anthropogenic CO2 emissions
decline by about 45% from 2010 levels by 2030 (40–60% interquartile range), reaching net zero
around 2050 (2045–2055 interquartile range). For limiting global warming to below 2°C11 CO2
emissions are projected to decline by about 25% by 2030 in most pathways (10–30% interquartile
range) and reach net zero around 2070 (2065–2080 interquartile range). Non-CO2 emissions in
pathways that limit global warming to 1.5°C show deep reductions that are similar to those in
pathways limiting warming to 2°C. (high confidence) (Figure SPM.3a) {2.1, 2.3, Table 2.4}
C.1.1 CO2 emissions reductions that limit global warming to 1.5°C with no or limited overshoot can involve different portfolios of
mitigation measures, striking different balances between lowering energy and resource intensity, rate of decarbonization,
and the reliance on carbon dioxide removal. Different portfolios face different implementation challenges and potential
synergies and trade-offs with sustainable development. (high confidence) (Figure SPM.3b) {2.3.2, 2.3.4, 2.4, 2.5.3}
C.1.2 Modelled pathways that limit global warming to 1.5°C with no or limited overshoot involve deep reductions in emissions
of methane and black carbon (35% or more of both by 2050 relative to 2010). These pathways also reduce most of the
cooling aerosols, which partially offsets mitigation effects for two to three decades. Non-CO2 emissions12 can be reduced
as a result of broad mitigation measures in the energy sector. In addition, targeted non-CO2 mitigation measures can
reduce nitrous oxide and methane from agriculture, methane from the waste sector, some sources of black carbon, and
hydrofluorocarbons. High bioenergy demand can increase emissions of nitrous oxide in some 1.5°C pathways, highlighting
the importance of appropriate management approaches. Improved air quality resulting from projected reductions in many
non-CO2 emissions provide direct and immediate population health benefits in all 1.5°C model pathways. (high confidence)
(Figure SPM.3a) {2.2.1, 2.3.3, 2.4.4, 2.5.3, 4.3.6, 5.4.2}
C.1.3 Limiting global warming requires limiting the total cumulative global anthropogenic emissions of CO2 since the preindustrial
period, that is, staying within a total carbon budget (high confidence).13 By the end of 2017, anthropogenic CO2
emissions since the pre-industrial period are estimated to have reduced the total carbon budget for 1.5°C by approximately
2200 ± 320 GtCO2 (medium confidence). The associated remaining budget is being depleted by current emissions of
42 ± 3 GtCO2 per year (high confidence). The choice of the measure of global temperature affects the estimated remaining
carbon budget. Using global mean surface air temperature, as in AR5, gives an estimate of the remaining carbon budget of
580 GtCO2 for a 50% probability of limiting warming to 1.5°C, and 420 GtCO2 for a 66% probability (medium confidence).14
Alternatively, using GMST gives estimates of 770 and 570 GtCO2, for 50% and 66% probabilities,15 respectively (medium
confidence). Uncertainties in the size of these estimated remaining carbon budgets are substantial and depend on several
factors. Uncertainties in the climate response to CO2 and non-CO2 emissions contribute ±400 GtCO2 and the level of historic
warming contributes ±250 GtCO2 (medium confidence). Potential additional carbon release from future permafrost thawing
and methane release from wetlands would reduce budgets by up to 100 GtCO2 over the course of this century and more
thereafter (medium confidence). In addition, the level of non-CO2 mitigation in the future could alter the remaining carbon
budget by 250 GtCO2 in either direction (medium confidence). {1.2.4, 2.2.2, 2.6.1, Table 2.2, Chapter 2 Supplementary
Material}
C.1.4 Solar radiation modification (SRM) measures are not included in any of the available assessed pathways. Although some
SRM measures may be theoretically effective in reducing an overshoot, they face large uncertainties and knowledge gaps
SPM
Summary for Policymakers
13
as well as substantial risks and institutional and social constraints to deployment related to governance, ethics, and impacts
on sustainable development. They also do not mitigate ocean acidification. (medium confidence) {4.3.8, Cross-Chapter
Box 10 in Chapter 4}
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
-20
-10
0
10
20
30
40
50
Black carbon emissions
Nitrous oxide emissions
Methane emissions
Emissions of non-CO
forcers are also reduced
or limited in pathways limiting global warming
to 1.5°C with no or limited overshoot, but
they do not reach zero globally.
Non-CO emissions relative to 2010
Billion tonnes of CO/yr
Global emissions pathway characteristics
General characteristics of the evolution of anthropogenic net emissions of CO
, and total emissions of
methane, black carbon, and nitrous oxide in model pathways that limit global warming to 1.5°C with no or
limited overshoot. Net emissions are defined as anthropogenic emissions reduced by anthropogenic
removals. Reductions in net emissions can be achieved through dierent portfolios of mitigation measures
illustrated in Figure SPM.3b.
Global total net CO emissions
2020 2040 2060 2080 2100
0
1
2020 2040 2060 2080 2100
0
1
2020 2040 2060 2080 2100
0
1
Four illustrative model pathways
In pathways limiting global warming to 1.5°C
with no or limited overshoot as well as in
pathways with a higher overshoot, CO emissions
are reduced to net zero globally around 2050.
P1
P2
P3
P4
Pathways with higher overshoot
Pathways limiting global warming below 2°C
(Not shown above)
Timing of net zero CO Pathways limiting global warming to 1.5°C with no or limited overshoot
Line widths depict the 5-95th
percentile and the 25-75th
percentile of scenarios
Figure SPM.3a | Global emissions pathway characteristics. The main panel shows global net anthropogenic CO2 emissions in pathways limiting global warming
to 1.5°C with no or limited (less than 0.1°C) overshoot and pathways with higher overshoot. The shaded area shows the full range for pathways analysed in this
Report. The panels on the right show non-CO2 emissions ranges for three compounds with large historical forcing and a substantial portion of emissions coming
from sources distinct from those central to CO2 mitigation. Shaded areas in these panels show the 5–95% (light shading) and interquartile (dark shading) ranges
of pathways limiting global warming to 1.5°C with no or limited overshoot. Box and whiskers at the bottom of the figure show the timing of pathways reaching
global net zero CO2 emission levels, and a comparison with pathways limiting global warming to 2°C with at least 66% probability. Four illustrative model pathways
are highlighted in the main panel and are labelled P1, P2, P3 and P4, corresponding to the LED, S1, S2, and S5 pathways assessed in Chapter 2. Descriptions and
characteristics of these pathways are available in Figure SPM.3b. {2.1, 2.2, 2.3, Figure 2.5, Figure 2.10, Figure 2.11}
l
l I
SPM
Summary for Policymakers
14
Breakdown of contributions to global net CO emissions in four illustrative model pathways
P1: A scenario in which social,
business and technological innovations
result in lower energy demand up to
2050 while living standards rise,
especially in the global South. A
downsized energy system enables
rapid decarbonization of energy supply.
Aorestation is the only CDR option
considered; neither fossil fuels with CCS
nor BECCS are used.
P2: A scenario with a broad focus on
sustainability including energy
intensity, human development,
economic convergence and
international cooperation, as well as
shis towards sustainable and healthy
consumption patterns, low-carbon
technology innovation, and
well-managed land systems with
limited societal acceptability for BECCS.
P3: A middle-of-the-road scenario in
which societal as well as technological
development follows historical
patterns. Emissions reductions are
mainly achieved by changing the way in
which energy and products are
produced, and to a lesser degree by
reductions in demand.
P4: A resource- and energy-intensive
scenario in which economic growth and
globalization lead to widespread
adoption of greenhouse-gas-intensive
lifestyles, including high demand for
transportation fuels and livestock
products. Emissions reductions are
mainly achieved through technological
means, making strong use of CDR
through the deployment of BECCS.
Fossil fuel and industry AFOLU BECCS
-20
0
20
40
2020 2060 2100
-20
0
20
40
2020 2060 2100
-20
0
20
40
2020 2060 2100
-20
0
20
40
2020 2060 2100
No or limited overshoot
-58
-93
-50
-82
-15
-32
60
77
-78
-97
-37
-87
-25
-74
59
150
-11
-16
430
833
0
0
0.2
-24
-33
5
6
Pathway classification
CO emission change in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
Kyoto-GHG emissions* in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
Final energy demand** in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
Renewable share in electricity in 2030 (%)
in 2050 (%)
Primary energy from coal in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
from oil in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
from gas in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
from nuclear in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
from biomass in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
from non-biomass renewables in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
Cumulative CCS until 2100 (GtCO)
of which BECCS (GtCO)
Land area of bioenergy crops in 2050 (million km)
Agricultural CH emissions in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
Agricultural NO emissions in 2030 (% rel to 2010)
in 2050 (% rel to 2010)
No or limited overshoot
-47
-95
-49
-89
-5
2
58
81
-61
-77
-13
-50
-20
-53
83
98
0
49
470
1327
348
151
0.9
-48
-69
-26
-26
No or limited overshoot
-41
-91
-35
-78
17
21
48
63
-75
-73
-3
-81
33
21
98
501
36
121
315
878
687
414
2.8
1
-23
15
0
Higher overshoot
4
-97
-2
-80
39
44
25
70
-59
-97
86
-32
37
-48
106
468
-1
418
110
1137
1218
1191
7.2
14
2
3
39
No or limited overshoot
(-58,-40)
(-107,-94)
(-51,-39)
(-93,-81)
(-12,7)
(-11,22)
(47,65)
(69,86)
(-78, -59)
(-95, -74)
(-34,3)
(-78,-31)
(-26,21)
(-56,6)
(44,102)
(91,190)
(29,80)
(123,261)
(245,436)
(576,1299)
(550,1017)
(364,662)
(1.5,3.2)
(-30,-11)
(-47,-24)
(-21,3)
(-26,1)
Characteristics of four illustrative model pathways
Dierent mitigation strategies can achieve the net emissions reductions that would be required to follow a
pathway that limits global warming to 1.5°C with no or limited overshoot. All pathways use Carbon Dioxide
Removal (CDR), but the amount varies across pathways, as do the relative contributions of Bioenergy with
Carbon Capture and Storage (BECCS) and removals in the Agriculture, Forestry and Other Land Use (AFOLU)
sector. This has implications for emissions and several other pathway characteristics.
P1 P2 P3 P4
P1 P2 P3 P4 Interquartile range
Billion tonnes CO per year (GtCO/yr)
Global indicators
Billion tonnes CO per year (GtCO/yr) Billion tonnes CO per year (GtCO/yr) Billion tonnes CO per year (GtCO/yr)
NOTE: Indicators have been selected to show global trends identified by the Chapter 2 assessment.
National and sectoral characteristics can dier substantially from the global trends shown above.
* Kyoto-gas emissions are based on IPCC Second Assessment Report GWP-100
** Changes in energy demand are associated with improvements in energy
eiciency and behaviour change
• •
»
t,
l,
t,
»
l,
t,
»
»
d»
•
SPM
Summary for Policymakers
15
Figure SPM.3b | Characteristics of four illustrative model pathways in relation to global warming of 1.5°C introduced in Figure SPM.3a. These pathways were
selected to show a range of potential mitigation approaches and vary widely in their projected energy and land use, as well as their assumptions about future
socio-economic developments, including economic and population growth, equity and sustainability. A breakdown of the global net anthropogenic CO2 emissions
into the contributions in terms of CO2 emissions from fossil fuel and industry; agriculture, forestry and other land use (AFOLU); and bioenergy with carbon capture
and storage (BECCS) is shown. AFOLU estimates reported here are not necessarily comparable with countries’ estimates. Further characteristics for each of these
pathways are listed below each pathway. These pathways illustrate relative global differences in mitigation strategies, but do not represent central estimates,
national strategies, and do not indicate requirements. For comparison, the right-most column shows the interquartile ranges across pathways with no or limited
overshoot of 1.5°C. Pathways P1, P2, P3 and P4 correspond to the LED, S1, S2 and S5 pathways assessed in Chapter 2 (Figure SPM.3a). {2.2.1, 2.3.1, 2.3.2,
2.3.3, 2.3.4, 2.4.1, 2.4.2, 2.4.4, 2.5.3, Figure 2.5, Figure 2.6, Figure 2.9, Figure 2.10, Figure 2.11, Figure 2.14, Figure 2.15, Figure 2.16, Figure 2.17, Figure 2.24,
Figure 2.25, Table 2.4, Table 2.6, Table 2.7, Table 2.9, Table 4.1}
C.2 Pathways limiting global warming to 1.5°C with no or limited overshoot would require rapid
and far-reaching transitions in energy, land, urban and infrastructure (including transport and
buildings), and industrial systems (high confidence). These systems transitions are unprecedented
in terms of scale, but not necessarily in terms of speed, and imply deep emissions reductions in all
sectors, a wide portfolio of mitigation options and a significant upscaling of investments in those
options (medium confidence). {2.3, 2.4, 2.5, 4.2, 4.3, 4.4, 4.5}
C.2.1 Pathways that limit global warming to 1.5°C with no or limited overshoot show system changes that are more rapid and
pronounced over the next two decades than in 2°C pathways (high confidence). The rates of system changes associated
with limiting global warming to 1.5°C with no or limited overshoot have occurred in the past within specific sectors,
technologies and spatial contexts, but there is no documented historic precedent for their scale (medium confidence).
{2.3.3, 2.3.4, 2.4, 2.5, 4.2.1, 4.2.2, Cross-Chapter Box 11 in Chapter 4}
C.2.2 In energy systems, modelled global pathways (considered in the literature) limiting global warming to 1.5°C with no or
limited overshoot (for more details see Figure SPM.3b) generally meet energy service demand with lower energy use,
including through enhanced energy efficiency, and show faster electrification of energy end use compared to 2°C (high
confidence). In 1.5°C pathways with no or limited overshoot, low-emission energy sources are projected to have a higher
share, compared with 2°C pathways, particularly before 2050 (high confidence). In 1.5°C pathways with no or limited
overshoot, renewables are projected to supply 70–85% (interquartile range) of electricity in 2050 (high confidence). In
electricity generation, shares of nuclear and fossil fuels with carbon dioxide capture and storage (CCS) are modelled to
increase in most 1.5°C pathways with no or limited overshoot. In modelled 1.5°C pathways with limited or no overshoot,
the use of CCS would allow the electricity generation share of gas to be approximately 8% (3–11% interquartile range)
of global electricity in 2050, while the use of coal shows a steep reduction in all pathways and would be reduced to close
to 0% (0–2% interquartile range) of electricity (high confidence). While acknowledging the challenges, and differences
between the options and national circumstances, political, economic, social and technical feasibility of solar energy, wind
energy and electricity storage technologies have substantially improved over the past few years (high confidence). These
improvements signal a potential system transition in electricity generation. (Figure SPM.3b) {2.4.1, 2.4.2, Figure 2.1, Table
2.6, Table 2.7, Cross-Chapter Box 6 in Chapter 3, 4.2.1, 4.3.1, 4.3.3, 4.5.2}
C.2.3 CO2 emissions from industry in pathways limiting global warming to 1.5°C with no or limited overshoot are projected to
be about 65–90% (interquartile range) lower in 2050 relative to 2010, as compared to 50–80% for global warming of
2°C (medium confidence). Such reductions can be achieved through combinations of new and existing technologies and
practices, including electrification, hydrogen, sustainable bio-based feedstocks, product substitution, and carbon capture,
utilization and storage (CCUS). These options are technically proven at various scales but their large-scale deployment
may be limited by economic, financial, human capacity and institutional constraints in specific contexts, and specific
characteristics of large-scale industrial installations. In industry, emissions reductions by energy and process efficiency
by themselves are insufficient for limiting warming to 1.5°C with no or limited overshoot (high confidence). {2.4.3, 4.2.1,
Table 4.1, Table 4.3, 4.3.3, 4.3.4, 4.5.2}
C.2.4 The urban and infrastructure system transition consistent with limiting global warming to 1.5°C with no or limited overshoot
would imply, for example, changes in land and urban planning practices, as well as deeper emissions reductions in transport
and buildings compared to pathways that limit global warming below 2°C (medium confidence). Technical measures
SPM
Summary for Policymakers
16
and practices enabling deep emissions reductions include various energy efficiency options. In pathways limiting global
warming to 1.5°C with no or limited overshoot, the electricity share of energy demand in buildings would be about 55–75%
in 2050 compared to 50–70% in 2050 for 2°C global warming (medium confidence). In the transport sector, the share of
low-emission final energy would rise from less than 5% in 2020 to about 35–65% in 2050 compared to 25–45% for 2°C
of global warming (medium confidence). Economic, institutional and socio-cultural barriers may inhibit these urban and
infrastructure system transitions, depending on national, regional and local circumstances, capabilities and the availability
of capital (high confidence). {2.3.4, 2.4.3, 4.2.1, Table 4.1, 4.3.3, 4.5.2}
C.2.5 Transitions in global and regional land use are found in all pathways limiting global warming to 1.5°C with no or limited
overshoot, but their scale depends on the pursued mitigation portfolio. Model pathways that limit global warming to 1.5°C
with no or limited overshoot project a 4 million km2 reduction to a 2.5 million km2 increase of non-pasture agricultural land
for food and feed crops and a 0.5–11 million km2 reduction of pasture land, to be converted into a 0–6 million km2 increase
of agricultural land for energy crops and a 2 million km2 reduction to 9.5 million km2 increase in forests by 2050 relative
to 2010 (medium confidence).16 Land-use transitions of similar magnitude can be observed in modelled 2°C pathways
(medium confidence). Such large transitions pose profound challenges for sustainable management of the various demands
on land for human settlements, food, livestock feed, fibre, bioenergy, carbon storage, biodiversity and other ecosystem
services (high confidence). Mitigation options limiting the demand for land include sustainable intensification of land-use
practices, ecosystem restoration and changes towards less resource-intensive diets (high confidence). The implementation
of land-based mitigation options would require overcoming socio-economic, institutional, technological, financing and
environmental barriers that differ across regions (high confidence). {2.4.4, Figure 2.24, 4.3.2, 4.3.7, 4.5.2, Cross-Chapter
Box 7 in Chapter 3}
C.2.6 Additional annual average energy-related investments for the period 2016 to 2050 in pathways limiting warming to
1.5°C compared to pathways without new climate policies beyond those in place today are estimated to be around 830
billion USD2010 (range of 150 billion to 1700 billion USD2010 across six models17). This compares to total annual average
energy supply investments in 1.5°C pathways of 1460 to 3510 billion USD2010 and total annual average energy demand
investments of 640 to 910 billion USD2010 for the period 2016 to 2050. Total energy-related investments increase by
about 12% (range of 3% to 24%) in 1.5°C pathways relative to 2°C pathways. Annual investments in low-carbon energy
technologies and energy efficiency are upscaled by roughly a factor of six (range of factor of 4 to 10) by 2050 compared to
2015 (medium confidence). {2.5.2, Box 4.8, Figure 2.27}
C.2.7 Modelled pathways limiting global warming to 1.5°C with no or limited overshoot project a wide range of global average
discounted marginal abatement costs over the 21st century. They are roughly 3-4 times higher than in pathways limiting
global warming to below 2°C (high confidence). The economic literature distinguishes marginal abatement costs from total
mitigation costs in the economy. The literature on total mitigation costs of 1.5°C mitigation pathways is limited and was
not assessed in this Report. Knowledge gaps remain in the integrated assessment of the economy-wide costs and benefits
of mitigation in line with pathways limiting warming to 1.5°C. {2.5.2; 2.6; Figure 2.26}
16 The projected land-use changes presented are not deployed to their upper limits simultaneously in a single pathway.
17 Including two pathways limiting warming to 1.5°C with no or limited overshoot and four pathways with higher overshoot.
SPM
Summary for Policymakers
17
C.3 All pathways that limit global warming to 1.5°C with limited or no overshoot project the use of
carbon dioxide removal (CDR) on the order of 100–1000 GtCO2 over the 21st century. CDR would
be used to compensate for residual emissions and, in most cases, achieve net negative emissions
to return global warming to 1.5°C following a peak (high confidence). CDR deployment of several
hundreds of GtCO2 is subject to multiple feasibility and sustainability constraints (high confidence).
Significant near-term emissions reductions and measures to lower energy and land demand can
limit CDR deployment to a few hundred GtCO2 without reliance on bioenergy with carbon capture
and storage (BECCS) (high confidence). {2.3, 2.4, 3.6.2, 4.3, 5.4}
C.3.1 Existing and potential CDR measures include afforestation and reforestation, land restoration and soil carbon sequestration,
BECCS, direct air carbon capture and storage (DACCS), enhanced weathering and ocean alkalinization. These differ widely
in terms of maturity, potentials, costs, risks, co-benefits and trade-offs (high confidence). To date, only a few published
pathways include CDR measures other than afforestation and BECCS. {2.3.4, 3.6.2, 4.3.2, 4.3.7}
C.3.2 In pathways limiting global warming to 1.5°C with limited or no overshoot, BECCS deployment is projected to range from
0–1, 0–8, and 0–16 GtCO2 yr−1 in 2030, 2050, and 2100, respectively, while agriculture, forestry and land-use (AFOLU)
related CDR measures are projected to remove 0–5, 1–11, and 1–5 GtCO2 yr−1 in these years (medium confidence). The
upper end of these deployment ranges by mid-century exceeds the BECCS potential of up to 5 GtCO2 yr−1 and afforestation
potential of up to 3.6 GtCO2 yr−1 assessed based on recent literature (medium confidence). Some pathways avoid BECCS
deployment completely through demand-side measures and greater reliance on AFOLU-related CDR measures (medium
confidence). The use of bioenergy can be as high or even higher when BECCS is excluded compared to when it is included
due to its potential for replacing fossil fuels across sectors (high confidence). (Figure SPM.3b) {2.3.3, 2.3.4, 2.4.2, 3.6.2,
4.3.1, 4.2.3, 4.3.2, 4.3.7, 4.4.3, Table 2.4}
C.3.3 Pathways that overshoot 1.5°C of global warming rely on CDR exceeding residual CO2 emissions later in the century to
return to below 1.5°C by 2100, with larger overshoots requiring greater amounts of CDR (Figure SPM.3b) (high confidence).
Limitations on the speed, scale, and societal acceptability of CDR deployment hence determine the ability to return global
warming to below 1.5°C following an overshoot. Carbon cycle and climate system understanding is still limited about the
effectiveness of net negative emissions to reduce temperatures after they peak (high confidence). {2.2, 2.3.4, 2.3.5, 2.6,
4.3.7, 4.5.2, Table 4.11}
C.3.4 Most current and potential CDR measures could have significant impacts on land, energy, water or nutrients if deployed
at large scale (high confidence). Afforestation and bioenergy may compete with other land uses and may have significant
impacts on agricultural and food systems, biodiversity, and other ecosystem functions and services (high confidence).
Effective governance is needed to limit such trade-offs and ensure permanence of carbon removal in terrestrial, geological
and ocean reservoirs (high confidence). Feasibility and sustainability of CDR use could be enhanced by a portfolio of options
deployed at substantial, but lesser scales, rather than a single option at very large scale (high confidence). (Figure SPM.3b)
{2.3.4, 2.4.4, 2.5.3, 2.6, 3.6.2, 4.3.2, 4.3.7, 4.5.2, 5.4.1, 5.4.2; Cross-Chapter Boxes 7 and 8 in Chapter 3, Table 4.11, Table
5.3, Figure 5.3}
C.3.5 Some AFOLU-related CDR measures such as restoration of natural ecosystems and soil carbon sequestration could provide
co-benefits such as improved biodiversity, soil quality, and local food security. If deployed at large scale, they would
require governance systems enabling sustainable land management to conserve and protect land carbon stocks and other
ecosystem functions and services (medium confidence). (Figure SPM.4) {2.3.3, 2.3.4, 2.4.2, 2.4.4, 3.6.2, 5.4.1, Cross-Chapter
Boxes 3 in Chapter 1 and 7 in Chapter 3, 4.3.2, 4.3.7, 4.4.1, 4.5.2, Table 2.4}
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D. Strengthening the Global Response in the Context of Sustainable
Development and Efforts to Eradicate Poverty
D.1 Estimates of the global emissions outcome of current nationally stated mitigation ambitions as
submitted under the Paris Agreement would lead to global greenhouse gas emissions18 in 2030
of 52–58 GtCO2eq yr−1 (medium confidence). Pathways reflecting these ambitions would not limit
global warming to 1.5°C, even if supplemented by very challenging increases in the scale and
ambition of emissions reductions after 2030 (high confidence). Avoiding overshoot and reliance
on future large-scale deployment of carbon dioxide removal (CDR) can only be achieved if global
CO2 emissions start to decline well before 2030 (high confidence). {1.2, 2.3, 3.3, 3.4, 4.2, 4.4, Cross-
Chapter Box 11 in Chapter 4}
D.1.1 Pathways that limit global warming to 1.5°C with no or limited overshoot show clear emission reductions by 2030 (high
confidence). All but one show a decline in global greenhouse gas emissions to below 35 GtCO2eq yr−1 in 2030, and half of
available pathways fall within the 25–30 GtCO2eq yr−1 range (interquartile range), a 40–50% reduction from 2010 levels
(high confidence). Pathways reflecting current nationally stated mitigation ambition until 2030 are broadly consistent
with cost-effective pathways that result in a global warming of about 3°C by 2100, with warming continuing afterwards
(medium confidence). {2.3.3, 2.3.5, Cross-Chapter Box 11 in Chapter 4, 5.5.3.2}
D.1.2 Overshoot trajectories result in higher impacts and associated challenges compared to pathways that limit global warming
to 1.5°C with no or limited overshoot (high confidence). Reversing warming after an overshoot of 0.2°C or larger during
this century would require upscaling and deployment of CDR at rates and volumes that might not be achievable given
considerable implementation challenges (medium confidence). {1.3.3, 2.3.4, 2.3.5, 2.5.1, 3.3, 4.3.7, Cross-Chapter Box 8 in
Chapter 3, Cross-Chapter Box 11 in Chapter 4}
D.1.3 The lower the emissions in 2030, the lower the challenge in limiting global warming to 1.5°C after 2030 with no or limited
overshoot (high confidence). The challenges from delayed actions to reduce greenhouse gas emissions include the risk of
cost escalation, lock-in in carbon-emitting infrastructure, stranded assets, and reduced flexibility in future response options
in the medium to long term (high confidence). These may increase uneven distributional impacts between countries at
different stages of development (medium confidence). {2.3.5, 4.4.5, 5.4.2}
D.2 The avoided climate change impacts on sustainable development, eradication of poverty and reducing
inequalities would be greater if global warming were limited to 1.5°C rather than 2°C, if mitigation
and adaptation synergies are maximized while trade-offs are minimized (high confidence). {1.1, 1.4,
2.5, 3.3, 3.4, 5.2, Table 5.1}
D.2.1 Climate change impacts and responses are closely linked to sustainable development which balances social well-being,
economic prosperity and environmental protection. The United Nations Sustainable Development Goals (SDGs), adopted in
2015, provide an established framework for assessing the links between global warming of 1.5°C or 2°C and development
goals that include poverty eradication, reducing inequalities, and climate action. (high confidence) {Cross-Chapter Box 4 in
Chapter 1, 1.4, 5.1}
D.2.2 The consideration of ethics and equity can help address the uneven distribution of adverse impacts associated with
1.5°C and higher levels of global warming, as well as those from mitigation and adaptation, particularly for poor and
disadvantaged populations, in all societies (high confidence). {1.1.1, 1.1.2, 1.4.3, 2.5.3, 3.4.10, 5.1, 5.2, 5.3. 5.4, Cross-
Chapter Box 4 in Chapter 1, Cross-Chapter Boxes 6 and 8 in Chapter 3, and Cross-Chapter Box 12 in Chapter 5}
D.2.3 Mitigation and adaptation consistent with limiting global warming to 1.5°C are underpinned by enabling conditions, assessed
in this Report across the geophysical, environmental-ecological, technological, economic, socio-cultural and institutional
18 GHG emissions have been aggregated with 100-year GWP values as introduced in the IPCC Second Assessment Report.
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dimensions of feasibility. Strengthened multilevel governance, institutional capacity, policy instruments, technological
innovation and transfer and mobilization of finance, and changes in human behaviour and lifestyles are enabling conditions
that enhance the feasibility of mitigation and adaptation options for 1.5°C-consistent systems transitions. (high confidence)
{1.4, Cross-Chapter Box 3 in Chapter 1, 2.5.1, 4.4, 4.5, 5.6}
D.3 Adaptation options specific to national contexts, if carefully selected together with enabling
conditions, will have benefits for sustainable development and poverty reduction with global
warming of 1.5°C, although trade-offs are possible (high confidence). {1.4, 4.3, 4.5}
D.3.1 Adaptation options that reduce the vulnerability of human and natural systems have many synergies with sustainable
development, if well managed, such as ensuring food and water security, reducing disaster risks, improving health
conditions, maintaining ecosystem services and reducing poverty and inequality (high confidence). Increasing investment
in physical and social infrastructure is a key enabling condition to enhance the resilience and the adaptive capacities
of societies. These benefits can occur in most regions with adaptation to 1.5°C of global warming (high confidence).
{1.4.3, 4.2.2, 4.3.1, 4.3.2, 4.3.3, 4.3.5, 4.4.1, 4.4.3, 4.5.3, 5.3.1, 5.3.2}
D.3.2 Adaptation to 1.5°C global warming can also result in trade-offs or maladaptations with adverse impacts for sustainable
development. For example, if poorly designed or implemented, adaptation projects in a range of sectors can increase
greenhouse gas emissions and water use, increase gender and social inequality, undermine health conditions, and encroach
on natural ecosystems (high confidence). These trade-offs can be reduced by adaptations that include attention to poverty
and sustainable development (high confidence). {4.3.2, 4.3.3, 4.5.4, 5.3.2; Cross-Chapter Boxes 6 and 7 in Chapter 3}
D.3.3 A mix of adaptation and mitigation options to limit global warming to 1.5°C, implemented in a participatory and integrated
manner, can enable rapid, systemic transitions in urban and rural areas (high confidence). These are most effective when
aligned with economic and sustainable development, and when local and regional governments and decision makers are
supported by national governments (medium confidence). {4.3.2, 4.3.3, 4.4.1, 4.4.2}
D.3.4 Adaptation options that also mitigate emissions can provide synergies and cost savings in most sectors and system
transitions, such as when land management reduces emissions and disaster risk, or when low-carbon buildings are also
designed for efficient cooling. Trade-offs between mitigation and adaptation, when limiting global warming to 1.5°C,
such as when bioenergy crops, reforestation or afforestation encroach on land needed for agricultural adaptation, can
undermine food security, livelihoods, ecosystem functions and services and other aspects of sustainable development. (high
confidence) {3.4.3, 4.3.2, 4.3.4, 4.4.1, 4.5.2, 4.5.3, 4.5.4}
D.4 Mitigation options consistent with 1.5°C pathways are associated with multiple synergies and tradeoffs
across the Sustainable Development Goals (SDGs). While the total number of possible synergies
exceeds the number of trade-offs, their net effect will depend on the pace and magnitude of changes,
the composition of the mitigation portfolio and the management of the transition. (high confidence)
(Figure SPM.4) {2.5, 4.5, 5.4}
D.4.1 1.5°C pathways have robust synergies particularly for the SDGs 3 (health), 7 (clean energy), 11 (cities and communities), 12
(responsible consumption and production) and 14 (oceans) (very high confidence). Some 1.5°C pathways show potential
trade-offs with mitigation for SDGs 1 (poverty), 2 (hunger), 6 (water) and 7 (energy access), if not managed carefully (high
confidence). (Figure SPM.4) {5.4.2; Figure 5.4, Cross-Chapter Boxes 7 and 8 in Chapter 3}
D.4.2 1.5°C pathways that include low energy demand (e.g., see P1 in Figure SPM.3a and SPM.3b), low material consumption,
and low GHG-intensive food consumption have the most pronounced synergies and the lowest number of trade-offs with
respect to sustainable development and the SDGs (high confidence). Such pathways would reduce dependence on CDR. In
modelled pathways, sustainable development, eradicating poverty and reducing inequality can support limiting warming to
1.5°C (high confidence). (Figure SPM.3b, Figure SPM.4) {2.4.3, 2.5.1, 2.5.3, Figure 2.4, Figure 2.28, 5.4.1, 5.4.2, Figure 5.4}
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Indicative linkages between mitigation options and sustainable
development using SDGs (The linkages do not show costs and benefits)
Mitigation options deployed in each sector can be associated with potential positive e ects (synergies) or
negative e ects (trade-o s) with the Sustainable Development Goals (SDGs). The degree to which this
potential is realized will depend on the selected portfolio of mitigation options, mitigation policy design,
and local circumstances and context. Particularly in the energy-demand sector, the potential for synergies is
larger than for trade-o s. The bars group individually assessed options by level of confidence and take into
account the relative strength of the assessed mitigation-SDG connections.
The overall size of the coloured bars depict the relative
potential for synergies and trade-o s between the sectoral
mitigation options and the SDGs.
Length shows strength of connection
Energy Supply Land
Trade-os Synergies Trade-os Synergies Trade-os Synergies
The shades depict the level of confidence of the
assessed potential for Trade-os/Synergies.
Very High Low
Shades show level of confidence
Energy Demand
SDG1
No Poverty
SDG2
Zero Hunger
SDG 3
Good Health
and Well-being
SDG 4
Quality
Education
SDG 5
Gender
Equality
SDG 6
Clean Water
and Sanitation
SDG 7
A ordable and
Clean Energy
SDG 8
Decent Work
and Economic
Growth
SDG 9
Industry,
Innovation and
Infrastructure
SDG 10
Reduced
Inequalities
SDG 11
Sustainable
Cities and
Communities
SDG 12
Responsible
Consumption
and Production
SDG 14
Life Below
Water
SDG 15
Life on Land
SDG 16
Peace, Justice
and Strong
Institutions
SDG 17
Partnerships for
the Goals
E □ I I I I
E I I I L D I
R I I D I
E I D D ■ I I
El I I
E3 [
fl I I L
'
! L I I C ii isl I I I D
E3 I I . EE' I I [
E I I I I D E □ I I
E D I I l' I I D
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D.4.3 1.5°C and 2°C modelled pathways often rely on the deployment of large-scale land-related measures like afforestation
and bioenergy supply, which, if poorly managed, can compete with food production and hence raise food security concerns
(high confidence). The impacts of carbon dioxide removal (CDR) options on SDGs depend on the type of options and the
scale of deployment (high confidence). If poorly implemented, CDR options such as BECCS and AFOLU options would lead
to trade-offs. Context-relevant design and implementation requires considering people’s needs, biodiversity, and other
sustainable development dimensions (very high confidence). (Figure SPM.4) {5.4.1.3, Cross-Chapter Box 7 in Chapter 3}
D.4.4 Mitigation consistent with 1.5°C pathways creates risks for sustainable development in regions with high dependency on
fossil fuels for revenue and employment generation (high confidence). Policies that promote diversification of the economy
and the energy sector can address the associated challenges (high confidence). {5.4.1.2, Box 5.2}
D.4.5 Redistributive policies across sectors and populations that shield the poor and vulnerable can resolve trade-offs for a range
of SDGs, particularly hunger, poverty and energy access. Investment needs for such complementary policies are only a small
fraction of the overall mitigation investments in 1.5°C pathways. (high confidence) {2.4.3, 5.4.2, Figure 5.5}
D.5 Limiting the risks from global warming of 1.5°C in the context of sustainable development and
poverty eradication implies system transitions that can be enabled by an increase of adaptation
and mitigation investments, policy instruments, the acceleration of technological innovation and
behaviour changes (high confidence). {2.3, 2.4, 2.5, 3.2, 4.2, 4.4, 4.5, 5.2, 5.5, 5.6}
D.5.1 Directing finance towards investment in infrastructure for mitigation and adaptation could provide additional resources.
This could involve the mobilization of private funds by institutional investors, asset managers and development or
investment banks, as well as the provision of public funds. Government policies that lower the risk of low-emission and
adaptation investments can facilitate the mobilization of private funds and enhance the effectiveness of other public
policies. Studies indicate a number of challenges, including access to finance and mobilization of funds. (high confidence)
{2.5.1, 2.5.2, 4.4.5}
D.5.2 Adaptation finance consistent with global warming of 1.5°C is difficult to quantify and compare with 2°C. Knowledge
gaps include insufficient data to calculate specific climate resilience-enhancing investments from the provision of currently
underinvested basic infrastructure. Estimates of the costs of adaptation might be lower at global warming of 1.5°C than for
2°C. Adaptation needs have typically been supported by public sector sources such as national and subnational government
budgets, and in developing countries together with support from development assistance, multilateral development banks,
and United Nations Framework Convention on Climate Change channels (medium confidence). More recently there is a
Figure SPM.4 | Potential synergies and trade-offs between the sectoral portfolio of climate change mitigation options and the Sustainable Development Goals
(SDGs). The SDGs serve as an analytical framework for the assessment of the different sustainable development dimensions, which extend beyond the time frame
of the 2030 SDG targets. The assessment is based on literature on mitigation options that are considered relevant for 1.5°C. The assessed strength of the SDG
interactions is based on the qualitative and quantitative assessment of individual mitigation options listed in Table 5.2. For each mitigation option, the strength of
the SDG-connection as well as the associated confidence of the underlying literature (shades of green and red) was assessed. The strength of positive connections
(synergies) and negative connections (trade-offs) across all individual options within a sector (see Table 5.2) are aggregated into sectoral potentials for the whole
mitigation portfolio. The (white) areas outside the bars, which indicate no interactions, have low confidence due to the uncertainty and limited number of studies
exploring indirect effects. The strength of the connection considers only the effect of mitigation and does not include benefits of avoided impacts. SDG 13 (climate
action) is not listed because mitigation is being considered in terms of interactions with SDGs and not vice versa. The bars denote the strength of the connection,
and do not consider the strength of the impact on the SDGs. The energy demand sector comprises behavioural responses, fuel switching and efficiency options in
the transport, industry and building sector as well as carbon capture options in the industry sector. Options assessed in the energy supply sector comprise biomass
and non-biomass renewables, nuclear, carbon capture and storage (CCS) with bioenergy, and CCS with fossil fuels. Options in the land sector comprise agricultural
and forest options, sustainable diets and reduced food waste, soil sequestration, livestock and manure management, reduced deforestation, afforestation and
reforestation, and responsible sourcing. In addition to this figure, options in the ocean sector are discussed in the underlying report. {5.4, Table 5.2, Figure 5.2}
Information about the net impacts of mitigation on sustainable development in 1.5°C pathways is available only for a limited number of SDGs and mitigation
options. Only a limited number of studies have assessed the benefits of avoided climate change impacts of 1.5°C pathways for the SDGs, and the co-effects
of adaptation for mitigation and the SDGs. The assessment of the indicative mitigation potentials in Figure SPM.4 is a step further from AR5 towards a more
comprehensive and integrated assessment in the future.
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Summary for Policymakers
22
growing understanding of the scale and increase in non-governmental organizations and private funding in some regions
(medium confidence). Barriers include the scale of adaptation financing, limited capacity and access to adaptation finance
(medium confidence). {4.4.5, 4.6}
D.5.3 Global model pathways limiting global warming to 1.5°C are projected to involve the annual average investment needs
in the energy system of around 2.4 trillion USD2010 between 2016 and 2035, representing about 2.5% of the world GDP
(medium confidence). {4.4.5, Box 4.8}
D.5.4 Policy tools can help mobilize incremental resources, including through shifting global investments and savings and
through market and non-market based instruments as well as accompanying measures to secure the equity of the
transition, acknowledging the challenges related with implementation, including those of energy costs, depreciation of
assets and impacts on international competition, and utilizing the opportunities to maximize co-benefits (high confidence).
{1.3.3, 2.3.4, 2.3.5, 2.5.1, 2.5.2, Cross-Chapter Box 8 in Chapter 3, Cross-Chapter Box 11 in Chapter 4, 4.4.5, 5.5.2}
D.5.5 The systems transitions consistent with adapting to and limiting global warming to 1.5°C include the widespread adoption
of new and possibly disruptive technologies and practices and enhanced climate-driven innovation. These imply enhanced
technological innovation capabilities, including in industry and finance. Both national innovation policies and international
cooperation can contribute to the development, commercialization and widespread adoption of mitigation and adaptation
technologies. Innovation policies may be more effective when they combine public support for research and development
with policy mixes that provide incentives for technology diffusion. (high confidence) {4.4.4, 4.4.5}.
D.5.6 Education, information, and community approaches, including those that are informed by indigenous knowledge and local
knowledge, can accelerate the wide-scale behaviour changes consistent with adapting to and limiting global warming to
1.5°C. These approaches are more effective when combined with other policies and tailored to the motivations, capabilities
and resources of specific actors and contexts (high confidence). Public acceptability can enable or inhibit the implementation
of policies and measures to limit global warming to 1.5°C and to adapt to the consequences. Public acceptability depends
on the individual’s evaluation of expected policy consequences, the perceived fairness of the distribution of these
consequences, and perceived fairness of decision procedures (high confidence). {1.1, 1.5, 4.3.5, 4.4.1, 4.4.3, Box 4.3, 5.5.3,
5.6.5}
D.6 Sustainable development supports, and often enables, the fundamental societal and systems
transitions and transformations that help limit global warming to 1.5°C. Such changes facilitate the
pursuit of climate-resilient development pathways that achieve ambitious mitigation and adaptation
in conjunction with poverty eradication and efforts to reduce inequalities (high confidence). {Box 1.1,
1.4.3, Figure 5.1, 5.5.3, Box 5.3}
D.6.1 Social justice and equity are core aspects of climate-resilient development pathways that aim to limit global warming to
1.5°C as they address challenges and inevitable trade-offs, widen opportunities, and ensure that options, visions, and values
are deliberated, between and within countries and communities, without making the poor and disadvantaged worse off
(high confidence). {5.5.2, 5.5.3, Box 5.3, Figure 5.1, Figure 5.6, Cross-Chapter Boxes 12 and 13 in Chapter 5}
D.6.2 The potential for climate-resilient development pathways differs between and within regions and nations, due to different
development contexts and systemic vulnerabilities (very high confidence). Efforts along such pathways to date have been
limited (medium confidence) and enhanced efforts would involve strengthened and timely action from all countries and
non-state actors (high confidence). {5.5.1, 5.5.3, Figure 5.1}
D.6.3 Pathways that are consistent with sustainable development show fewer mitigation and adaptation challenges and are
associated with lower mitigation costs. The large majority of modelling studies could not construct pathways characterized
by lack of international cooperation, inequality and poverty that were able to limit global warming to 1.5°C. (high
confidence) {2.3.1, 2.5.1, 2.5.3, 5.5.2}
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Summary for Policymakers
23
D.7 Strengthening the capacities for climate action of national and sub-national authorities, civil society,
the private sector, indigenous peoples and local communities can support the implementation of
ambitious actions implied by limiting global warming to 1.5°C (high confidence). International
cooperation can provide an enabling environment for this to be achieved in all countries and for all
people, in the context of sustainable development. International cooperation is a critical enabler for
developing countries and vulnerable regions (high confidence). {1.4, 2.3, 2.5, 4.2, 4.4, 4.5, 5.3, 5.4, 5.5,
5.6, 5, Box 4.1, Box 4.2, Box 4.7, Box 5.3, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 13 in
Chapter 5}
D.7.1 Partnerships involving non-state public and private actors, institutional investors, the banking system, civil society and
scientific institutions would facilitate actions and responses consistent with limiting global warming to 1.5°C (very high
confidence). {1.4, 4.4.1, 4.2.2, 4.4.3, 4.4.5, 4.5.3, 5.4.1, 5.6.2, Box 5.3}.
D.7.2 Cooperation on strengthened accountable multilevel governance that includes non-state actors such as industry, civil
society and scientific institutions, coordinated sectoral and cross-sectoral policies at various governance levels, gendersensitive
policies, finance including innovative financing, and cooperation on technology development and transfer can
ensure participation, transparency, capacity building and learning among different players (high confidence). {2.5.1, 2.5.2,
4.2.2, 4.4.1, 4.4.2, 4.4.3, 4.4.4, 4.4.5, 4.5.3, Cross-Chapter Box 9 in Chapter 4, 5.3.1, 5.5.3, Cross-Chapter Box 13 in Chapter
5, 5.6.1, 5.6.3}
D.7.3 International cooperation is a critical enabler for developing countries and vulnerable regions to strengthen their action for
the implementation of 1.5°C-consistent climate responses, including through enhancing access to finance and technology
and enhancing domestic capacities, taking into account national and local circumstances and needs (high confidence).
{2.3.1, 2.5.1, 4.4.1, 4.4.2, 4.4.4, 4.4.5, 5.4.1 5.5.3, 5.6.1, Box 4.1, Box 4.2, Box 4.7}.
D.7.4 Collective efforts at all levels, in ways that reflect different circumstances and capabilities, in the pursuit of limiting global
warming to 1.5°C, taking into account equity as well as effectiveness, can facilitate strengthening the global response to
climate change, achieving sustainable development and eradicating poverty (high confidence). {1.4.2, 2.3.1, 2.5.1, 2.5.2,
2.5.3, 4.2.2, 4.4.1, 4.4.2, 4.4.3, 4.4.4, 4.4.5, 4.5.3, 5.3.1, 5.4.1, 5.5.3, 5.6.1, 5.6.2, 5.6.3}
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Summary for Policymakers
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Box SPM.1: Core Concepts Central to this Special Report
Global mean surface temperature (GMST): Estimated global average of near-surface air temperatures over land and
sea ice, and sea surface temperatures over ice-free ocean regions, with changes normally expressed as departures from a
value over a specified reference period. When estimating changes in GMST, near-surface air temperature over both land
and oceans are also used.19 {1.2.1.1}
Pre-industrial: The multi-century period prior to the onset of large-scale industrial activity around 1750. The reference
period 1850–1900 is used to approximate pre-industrial GMST. {1.2.1.2}
Global warming: The estimated increase in GMST averaged over a 30-year period, or the 30-year period centred on a
particular year or decade, expressed relative to pre-industrial levels unless otherwise specified. For 30-year periods that
span past and future years, the current multi-decadal warming trend is assumed to continue. {1.2.1}
Net zero CO2 emissions: Net zero carbon dioxide (CO2) emissions are achieved when anthropogenic CO2 emissions are
balanced globally by anthropogenic CO2 removals over a specified period.
Carbon dioxide removal (CDR): Anthropogenic activities removing CO2 from the atmosphere and durably storing it in
geological, terrestrial, or ocean reservoirs, or in products. It includes existing and potential anthropogenic enhancement of
biological or geochemical sinks and direct air capture and storage, but excludes natural CO2 uptake not directly caused by
human activities.
Total carbon budget: Estimated cumulative net global anthropogenic CO2 emissions from the pre-industrial period
to the time that anthropogenic CO2 emissions reach net zero that would result, at some probability, in limiting global
warming to a given level, accounting for the impact of other anthropogenic emissions. {2.2.2}
Remaining carbon budget: Estimated cumulative net global anthropogenic CO2 emissions from a given start date to the
time that anthropogenic CO2 emissions reach net zero that would result, at some probability, in limiting global warming
to a given level, accounting for the impact of other anthropogenic emissions. {2.2.2}
Temperature overshoot: The temporary exceedance of a specified level of global warming.
Emission pathways: In this Summary for Policymakers, the modelled trajectories of global anthropogenic emissions over
the 21st century are termed emission pathways. Emission pathways are classified by their temperature trajectory over
the 21st century: pathways giving at least 50% probability based on current knowledge of limiting global warming to
below 1.5°C are classified as ‘no overshoot’; those limiting warming to below 1.6°C and returning to 1.5°C by 2100 are
classified as ‘1.5°C limited-overshoot’; while those exceeding 1.6°C but still returning to 1.5°C by 2100 are classified as
‘higher-overshoot’.
Impacts: Effects of climate change on human and natural systems. Impacts can have beneficial or adverse outcomes
for livelihoods, health and well-being, ecosystems and species, services, infrastructure, and economic, social and cultural
assets.
Risk: The potential for adverse consequences from a climate-related hazard for human and natural systems, resulting
from the interactions between the hazard and the vulnerability and exposure of the affected system. Risk integrates
the likelihood of exposure to a hazard and the magnitude of its impact. Risk also can describe the potential for adverse
consequences of adaptation or mitigation responses to climate change.
Climate-resilient development pathways (CRDPs): Trajectories that strengthen sustainable development at multiple
scales and efforts to eradicate poverty through equitable societal and systems transitions and transformations while
reducing the threat of climate change through ambitious mitigation, adaptation and climate resilience.
19 Past IPCC reports, reflecting the literature, have used a variety of approximately equivalent metrics of GMST change.
Summary for
Policymakers
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Summary for Policymakers
3
This Summary for Policymakers should be cited as:
IPCC, 2019: Summary for Policymakers. In: Climate Change and Land: an IPCC special report on climate change,
desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in
terrestrial ecosystems [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.- O. Pörtner, D. C. Roberts, P. Zhai,
R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P.
Vyas, E. Huntley, K. Kissick, M. Belkacemi, J. Malley, (eds.)]. https://doi.org/10.1017/9781009157988.001
Drafting Authors:
Almut Arneth (Germany), Humberto Barbosa (Brazil), Tim Benton (United Kingdom), Katherine
Calvin (The United States of America), Eduardo Calvo (Peru), Sarah Connors (United Kingdom),
Annette Cowie (Australia), Edouard Davin (France/Switzerland), Fatima Denton (The Gambia),
Renée van Diemen (The Netherlands/United Kingdom), Fatima Driouech (Morocco), Aziz Elbehri
(Morocco), Jason Evans (Australia), Marion Ferrat (France), Jordan Harold (United Kingdom),
Eamon Haughey (Ireland), Mario Herrero (Australia/Costa Rica), Joanna House (United Kingdom),
Mark Howden (Australia), Margot Hurlbert (Canada), Gensuo Jia (China), Tom Gabriel Johansen
(Norway), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Christopher Lennard (South
Africa), Soojeong Myeong (Republic of Korea), Nagmeldin Mahmoud (Sudan), Valérie Masson-
Delmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America),
Alisher Mirzabaev (Germany/Uzbekistan), Angela Morelli (Norway/Italy), Wilfran Moufouma-Okia
(France), Dalila Nedjraoui (Algeria), Suvadip Neogi (India), Johnson Nkem (Cameroon), Nathalie De
Noblet-Ducoudré (France), Lennart Olsson (Sweden), Minal Pathak (India), Jan Petzold (Germany),
Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom/Australia), Alexander Popp
(Germany), Hans-Otto Pörtner (Germany), Joana Portugal Pereira (United Kingdom), Prajal
Pradhan (Nepal/Germany), Andy Reisinger (New Zealand), Debra C. Roberts (South Africa),
Cynthia Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom/Germany),
Elena Shevliakova (The United States of America), Priyadarshi R. Shukla (India), Jim Skea (United
Kingdom), Raphael Slade (United Kingdom), Pete Smith (United Kingdom), Youba Sokona (Mali),
Denis Jean Sonwa (Cameroon), Jean-Francois Soussana (France), Francesco Tubiello (The United
States of America/Italy), Louis Verchot (The United States of America/Colombia), Koko Warner (The
United States of America/Germany), Nora M. Weyer (Germany), Jianguo Wu (China), Noureddine
Yassaa (Algeria), Panmao Zhai (China), Zinta Zommers (Latvia).
Summary
for Policymakers
4
SPM
Summary for Policymakers
Acknowledgements
The Special Report on Climate Change and Land broke new ground for IPCC. It was the first IPCC report to be produced by
all three Working Groups in collaboration with the Task Force on National Greenhouse Gas Inventories (TFI), and it was the
first IPCC report with more authors from developing countries than authors from developed countries. It was marked by an
inspiring degree of collaboration and interdisciplinarity, reflecting the wide scope of the mandate given to authors by the
Panel. It brought together authors not only from the IPCC’s traditional scientific communities, but also those from sister UN
organisations including the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the
Science-Policy Interface of the UN Convention to Combat Desertification (UNCCD) and the Food and Agriculture Organization
of the UN (FAO).
We must pay tribute to the 107 Coordinating Lead Authors, Lead Authors and Review Editors, from 52 countries, who were
responsible for the report. They gave countless hours of their time, on a voluntary basis, and attended four Lead Author
meetings in widely scattered parts of the globe. The constructive interplay between the authors, who draft the report, and
the Review Editors, who provide assurance that all comments are responded to, greatly helped the process. Throughout, all
demonstrated scientific rigour while at the same time maintaining good humour and a spirit of true collaboration. They did so
against a very tight timetable which allowed no scope for slippage. They were supported by input from 96 Contributing Authors.
We would like to acknowledge especially the support of the Chapter Scientists who took time out from their emerging careers
to support the production of the report. We thank Yuping Bai, Aliyu Barau, Erik Contreras, Abdoul Aziz Diouf, Baldur Janz,
Frances Manning, Dorothy Nampanzira, Chuck Chuan Ng, Helen Paulos, Xiyan Xu and Thobekile Zikhali. We very much hope
that the experience will help them in their future careers and that their vital role will be suitably recognised.
The production of the report was guided by a Steering Committee drawn from across the IPCC Bureau. We would like to thank
our colleagues who served on this committee including: the Co-Chairs of Working Groups and the TFI: Priyadarshi Shukla,
Jim Skea, Valérie Masson-Delmotte, Panmao Zhai, Hans-Otto Pörtner, Debra Roberts, Eduardo Calvo Buendía; Working Group
Vice-Chairs: Mark Howden, Nagmeldin Mahmoud, Ramón Pichs-Madruga, Andy Reisinger, Noureddine Yassaa; and Youba
Sokona, Vice-Chair of IPCC. Youba Sokona acted as champion for the report and his wise council was valued by all. Further
support came from IPCC Bureau members: Edvin Aldrian, Fatima Driouech, Gregory Flato, Jan Fuglestvedt, Muhammad Tariq
and Carolina Vera (Working Group I); Andreas Fischlin, Carlos Méndez, Joy Jacqueline Pereira, Roberto A. Sánchez-Rodríguez,
Sergey Semenov, Pius Yanda and Taha M. Zatari (Working Group II); and Amjad Abdulla, Carlo Carraro, Diriba Korecha Dadi
and Diana Ürge-Vorsatz (Working Group III).
Several governments and other bodies hosted and supported the scoping meeting, the four Lead Author meetings, and the
final IPCC Plenary. These were: the Government of Norway and the Norwegian Environment Agency, the Government of
New Zealand and the University of Canterbury, the Government of Ireland and the Environmental Protection Agency, the
Government of Colombia and the International Centre for Tropical Agriculture (CIAT), the Government of Switzerland and the
World Meteorological Organization.
The staff of the IPCC Secretariat based in Geneva provided a wide range of support for which we would like to thank Abdalah
Mokssit, Secretary of the IPCC, and his colleagues: Kerstin Stendahl, Jonathan Lynn, Sophie Schlingemann, Jesbin Baidya, Laura
Biagioni, Annie Courtin, Oksana Ekzarkho, Judith Ewa, Joelle Fernandez, Andrea Papucides Bach, Nina Peeva, Mxolisi Shongwe,
and Werani Zabula. Thanks are due to Elhousseine Gouaini who served as the conference officer for the 50th Session of the
IPCC.
5
SPM
Summary for Policymakers
A number of individuals provided support for the visual elements of the report and its communication. We would single out
Jordan Harold of the University of East Anglia, Susan Escott of Escott Hunt Ltd, Angela Morelli and Tom Gabriel Johansen of
Info Design Lab, and Polly Jackson, Ian Blenkinsop, Autumn Forecast, Francesca Romano and Alice Woodward of Soapbox
Communications Ltd.
The report was managed by the Technical Support Unit of IPCC Working Group III which has the generous financial support
of the UK Engineering and Physical Sciences Research Council (EPSRC) and the UK Government through its Department of
Business, Energy and Industrial Strategy (BEIS). In addition, the Irish Environmental Protection Agency provided support for
two secondees to the WG III Technical Support Unit, while the Norwegian Environment Agency enabled an expanded set of
communication activities. Without the support of all these bodies this report would not have been possible.
Our particular appreciation goes to the Working Group Technical Support Units whose tireless dedication, professionalism and
enthusiasm led the production of this Special Report. This Report could not have been prepared without the commitment of
members of the Working Group III Technical Support Unit, all new to the IPCC, who rose to the unprecedented Sixth Assessment
Report challenge and were pivotal in all aspects of the preparation of the Report: Raphael Slade, Lizzie Huntley, Katie Kissick,
Malek Belkacemi, Renée van Diemen, Marion Ferrat, Eamon Haughey, Bhushan Kankal, Géninha Lisboa, Sigourney Luz, Juliette
Malley, Suvadip Neogi, Minal Pathak, Joana Portugal Pereira and Purvi Vyas. Our warmest thanks go to the collegial and
collaborative support provided by Sarah Connors, Melissa Gomis, Robin Matthews, Wilfran Moufouma-Okia, Clotilde Péan,
Roz Pidcock, Anna Pirani, Tim Waterfield and Baiquan Zhou from the WG I Technical Support Unit, and Jan Petzold, Bard Rama,
Maike Nicolai, Elvira Poloczanska, Melinda Tignor and Nora Weyer from the WG II Technical Support Unit.
And a final deep thanks to family and friends who indirectly supported the work by tolerating the periods authors spent away
from home, the long hours and their absorption in the process of producing this report.
SIGNED
Valérie Masson-Delmotte Panmao Zhai
Co-Chair Working Group I Co-Chair Working Group I
Hans-Otto Pörtner Debra Roberts
Co-Chair Working Group II Co-Chair Working Group II
Jim Skea Eduardo Calvo Buendía Priyadarshi R. Shukla
Co-Chair Working Group III Co-Chair TFI Co-Chair Working Group III
%a.l'tu aero=
).. A 4u.ail 4.A,
6
SPM
Summary for Policymakers
Introduction
1 The terrestrial portion of the biosphere that comprises the natural resources (soil, near-surface air, vegetation and other biota, and water), the ecological processes, topography, and human
settlements and infrastructure that operate within that system.
2 The three Special reports are: Global Warming of 1.5°C: an IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas
emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty; Climate Change and
Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems; The
Ocean and Cryosphere in a Changing Climate.
3 Related proposals were: climate change and desertification; desertification with regional aspects; land degradation – an assessment of the interlinkages and integrated strategies for
mitigation and adaptation; agriculture, forestry and other land use; food and agriculture; and food security and climate change.
4 Sustainable land management is defined in this report as ‘the stewardship and use of land resources, including soils, water, animals and plants, to meet changing human needs, while
simultaneously ensuring the long-term productive potential of these resources and the maintenance of their environmental functions’.
5 Desertification is defined in this report as ‘land degradation in arid, semi-arid, and dry sub-humid areas resulting from many factors, including climatic variations and human activities’.
6 Land degradation is defined in this report as ‘a negative trend in land condition, caused by direct or indirect human induced processes, including anthropogenic climate change, expressed
as long-term reduction and as loss of at least one of the following: biological productivity; ecological integrity; or value to humans’.
7 Food security is defined in this report as ‘a situation that exists when all people, at all times, have physical, social, and economic access to sufficient, safe and nutritious food that meets
their dietary needs and food preferences for an active and healthy life’.
8 The assessment covers literature accepted for publication by 7th April 2019.
9 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and
typeset in italics, for example, medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability,
very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%,
more likely than not >50–100%, more unlikely than likely 0–<50%, extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, for example,
very likely. This is consistent with IPCC AR5.
This Special Report on Climate Change and Land1 responds to the Panel decision in 2016 to prepare three Special Reports2 during the
Sixth Assessment cycle, taking account of proposals from governments and observer organisations.3 This report addresses greenhouse
gas (GHG) fluxes in land-based ecosystems, land use and sustainable land management4 in relation to climate change adaptation and
mitigation, desertification5, land degradation6 and food security7. This report follows the publication of other recent reports, including the
IPCC Special Report on Global Warming of 1.5°C (SR15), the thematic assessment of the Intergovernmental Science-Policy Platform on
Biodiversity and Ecosystem Services (IPBES) on Land Degradation and Restoration, the IPBES Global Assessment Report on Biodiversity
and Ecosystem Services, and the Global Land Outlook of the UN Convention to Combat Desertification (UNCCD). This report provides
an updated assessment of the current state of knowledge8 while striving for coherence and complementarity with other recent reports.
This Summary for Policymakers (SPM) is structured in four parts: A) People, land and climate in a warming world; B) Adaptation and
mitigation response options; C) Enabling response options; and, D) Action in the near-term.
Confidence in key findings is indicated using the IPCC calibrated language; the underlying scientific basis of each key finding is indicated
by references to the main report.9
7
SPM
Summary for Policymakers
A. People, land and climate in a warming world
10 Land’s potential net primary production (NPP) is defined in this report as ‘the amount of carbon accumulated through photosynthesis minus the amount lost by plant respiration over
a specified time period that would prevail in the absence of land use’.
11 In its conceptual framework, IPBES uses ‘nature’s contribution to people’ in which it includes ecosystem goods and services.
12 I.e., estimated at $75 trillion for 2011, based on US dollars for 2007.
13 This statement is based on the most comprehensive data from national statistics available within FAOSTAT, which starts in 1961. This does not imply that the changes started in 1961.
Land use changes have been taking place from well before the pre-industrial period to the present.
A.1 Land provides the principal basis for human livelihoods and well-being including the supply of food,
freshwater and multiple other ecosystem services, as well as biodiversity. Human use directly affects
more than 70% (likely 69–76%) of the global, ice-free land surface (high confidence). Land also plays
an important role in the climate system. (Figure SPM.1) {1.1, 1.2, 2.3, 2.4}
A.1.1 People currently use one quarter to one third of land’s potential net primary production10 for food, feed, fibre, timber
and energy. Land provides the basis for many other ecosystem functions and services,11 including cultural and regulating
services, that are essential for humanity (high confidence). In one economic approach, the world’s terrestrial ecosystem
services have been valued on an annual basis to be approximately equivalent to the annual global Gross Domestic
Product12 (medium confidence). (Figure SPM.1) {1.1, 1.2, 3.2, 4.1, 5.1, 5.5}
A.1.2 Land is both a source and a sink of GHGs and plays a key role in the exchange of energy, water and aerosols between the
land surface and atmosphere. Land ecosystems and biodiversity are vulnerable to ongoing climate change, and weather and
climate extremes, to different extents. Sustainable land management can contribute to reducing the negative impacts of
multiple stressors, including climate change, on ecosystems and societies (high confidence). (Figure SPM.1) {1.1, 1.2, 3.2, 4.1,
5.1, 5.5}
A.1.3 Data available since 196113 show that global population growth and changes in per capita consumption of food, feed, fibre,
timber and energy have caused unprecedented rates of land and freshwater use (very high confidence) with agriculture
currently accounting for ca. 70% of global fresh-water use (medium confidence). Expansion of areas under agriculture and
forestry, including commercial production, and enhanced agriculture and forestry productivity have supported consumption
and food availability for a growing population (high confidence). With large regional variation, these changes have contributed
to increasing net GHG emissions (very high confidence), loss of natural ecosystems (e.g., forests, savannahs, natural grasslands
and wetlands) and declining biodiversity (high confidence). (Figure SPM.1) {1.1, 1.3, 5.1, 5.5}
A.1.4 Data available since 1961 shows the per capita supply of vegetable oils and meat has more than doubled and the supply
of food calories per capita has increased by about one third (high confidence). Currently, 25–30% of total food produced is
lost or wasted (medium confidence). These factors are associated with additional GHG emissions (high confidence). Changes
in consumption patterns have contributed to about two billion adults now being overweight or obese (high confidence). An
estimated 821 million people are still undernourished (high confidence). (Figure SPM.1) {1.1, 1.3, 5.1, 5.5}
A.1.5 About a quarter of the Earth’s ice-free land area is subject to human-induced degradation (medium confidence). Soil erosion
from agricultural fields is estimated to be currently 10 to 20 times (no tillage) to more than 100 times (conventional tillage)
higher than the soil formation rate (medium confidence). Climate change exacerbates land degradation, particularly in lowlying
coastal areas, river deltas, drylands and in permafrost areas (high confidence). Over the period 1961–2013, the annual
area of drylands in drought has increased, on average by slightly more than 1% per year, with large inter-annual variability. In
2015, about 500 (380-620) million people lived within areas which experienced desertification between the 1980s and 2000s.
The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa, and the
Middle East including the Arabian Peninsula (low confidence). Other dryland regions have also experienced desertification.
People living in already degraded or desertified areas are increasingly negatively affected by climate change (high confidence).
(Figure SPM.1) {1.1, 1.2, 3.1, 3.2, 4.1, 4.2, 4.3}
8
SPM
Summary for Policymakers
Land use and observed climate change
1
2
3
Prevalence of overweight + obese
4 Prevalence of underweight
Total calories per capita
Population
CHANGE in EMISSIONS since 1961
B. GHG emissions
An estimated 23% of total anthropogenic
greenhouse gas emissions (2007-2016)
derive from Agriculture, Forestry and
Other Land Use (AFOLU).
E. Food demand
Increases in production are linked to
consumption changes.
F. Desertification and
land degradation
Land-use change, land-use intensification
and climate change have contributed to
desertification and land degradation.
CHANGE in % rel. to 1961 and 1970
CHANGE in % rel. to 1961 and 1975
1
2
3 Inland wetland extent
Dryland areas in drought annually
Population in areas experiencing desertification
1
2
3
CHANGE in % rel. to 1961
1
2
3 Irrigation water volume
4 Total number of ruminant livestock
Cereal yields
Inorganic N fertiliser use
Intensive pasture 2%
1% (1 - 1%) 12% (12 - 14%) 37% (30 - 47%) 22% (16 - 23%) 28% (24 - 31%)
Used savannahs and
shrublands 16%
Plantation forests 2%
Forests managed for timber
and other uses 20%
Infrastructure 1% Irrigated cropland 2%
Non-irrigated cropland 10%
Unforested ecosystems with
minimal human use 7%
Forests (intact or primary)
with minimal human use 9%
Other land (barren, rock) 12%
Global ice-free land surface 100% (130 Mkm)
0
10
20
30
Net CO emissions from FOLU (GtCO yr-1)
NO emissions from Agriculture (GtCOeq yr-1)
CH emissions from Agriculture (GtCOeq yr-1)
A. Observed temperature change relative to 1850-1900
Since the pre-industrial period (1850-1900) the observed mean land surface air
temperature has risen considerably more than the global mean surface (land and ocean)
temperature (GMST).
C. Global land use
in circa 2015
The barchart depicts
shares of dierent uses
of the global, ice-free
land area. Bars are
ordered along a gradient
of decreasing land-use
intensity from le to right.
Extensive pasture 19%
D. Agricultural production
Land use change and rapid land use
intensification have supported the
increasing production of food, feed and
fibre. Since 1961, the total production of
food (cereal crops) has increased by 240%
(until 2017) because of land area
expansion and increasing yields. Fibre
production (cotton) increased by 162%
(until 2013).
2
1
3
%
%
50
-50
150
250
100
0
200
%
50
-50
150
250
100
0
200
1
2
3
4
4
1
2
3
1850 1880 1900 1920 1940 1960 1980 2000 2018
2
0
4
6
1
2
3
0.5
1.5
1
0
-0.5
2
CHANGE in TEMPERATURE rel. to 1850-1900 (°C)
Change in
surface air
temperature
over land (°C)
Change in global
(land-ocean)
mean surface
temperature
(GMST) (°C)
GtCOeq yr-1
1961 1980 2000 2016
1961 1980 2000 2017 1961 1980 2000 2017
50
-50
150
250
300
700
100
0
200
1961 1980 2000 2017
800
'I -•6 •
•••
••• • • ••• •••
9
SPM
Summary for Policymakers
Figure SPM.1: Land use and observed climate change | A representation of the land use and observed climate change covered in this assessment report. Panels
A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and
D-F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D-F are expressed
relative to the starting year of the time series (rebased to zero). Data sources and notes: A: The warming curves are averages of four datasets {2.1, Figure 2.2, Table 2.1}
B: N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires
since 1997). All values expressed in units of CO2-eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N2O=265; CH4=28).
(Table SPM.1) {1.1, 2.3} C: Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing
land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total percentage of the ice-free area covered, with
uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and
other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} D: Note that fertiliser use is shown on a split axis. The large
percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised
cropland and grassland to increase food production. {1.1, Figure 1.3} E: Overweight population is defined as having a body mass index (BMI) > 25 kg m-2; underweight is
defined as BMI < 18.5 kg m-2. {5.1, 5.2} F: Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980-2015) to identify areas
where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation
Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes
in local wetland area over time. {3.1, 4.2, 4.6}
A.2 Since the pre-industrial period, the land surface air temperature has risen nearly twice as much as
the global average temperature (high confidence). Climate change, including increases in frequency
and intensity of extremes, has adversely impacted food security and terrestrial ecosystems as well as
contributed to desertification and land degradation in many regions (high confidence). {2.2, 3.2, 4.2,
4.3, 4.4, 5.1, 5.2, Executive Summary Chapter 7, 7.2}
A.2.1 Since the pre-industrial period (1850-1900) the observed mean land surface air temperature has risen considerably more than
the global mean surface (land and ocean) temperature (GMST) (high confidence). From 1850-1900 to 2006-2015 mean land
surface air temperature has increased by 1.53°C (very likely range from 1.38°C to 1.68°C) while GMST increased by 0.87°C
(likely range from 0.75°C to 0.99°C). (Figure SPM.1) {2.2.1}
A.2.2 Warming has resulted in an increased frequency, intensity and duration of heat-related events, including heatwaves14 in
most land regions (high confidence). Frequency and intensity of droughts has increased in some regions (including the
Mediterranean, west Asia, many parts of South America, much of Africa, and north-eastern Asia) (medium confidence) and
there has been an increase in the intensity of heavy precipitation events at a global scale (medium confidence). {2.2.5, 4.2.3,
5.2}
A.2.3 Satellite observations15 have shown vegetation greening16 over the last three decades in parts of Asia, Europe, South America,
central North America, and southeast Australia. Causes of greening include combinations of an extended growing season,
nitrogen deposition, Carbon Dioxide (CO2) fertilisation17, and land management (high confidence). Vegetation browning18 has
been observed in some regions including northern Eurasia, parts of North America, Central Asia and the Congo Basin, largely
as a result of water stress (medium confidence). Globally, vegetation greening has occurred over a larger area than vegetation
browning (high confidence). {2.2.3, Box 2.3, 2.2.4, 3.2.1, 3.2.2, 4.3.1, 4.3.2, 4.6.2, 5.2.2}
A.2.4 The frequency and intensity of dust storms have increased over the last few decades due to land use and land cover changes
and climate-related factors in many dryland areas resulting in increasing negative impacts on human health, in regions such
as the Arabian Peninsula and broader Middle East, Central Asia (high confidence).19 {2.4.1, 3.4.2}
A.2.5 In some dryland areas, increased land surface air temperature and evapotranspiration and decreased precipitation amount, in
interaction with climate variability and human activities, have contributed to desertification. These areas include Sub-Saharan
Africa, parts of East and Central Asia, and Australia. (medium confidence) {2.2, 3.2.2, 4.4.1}
14 A heatwave is defined in this report as ‘a period of abnormally hot weather’. Heatwaves and warm spells have various and, in some cases, overlapping definitions.
15 The interpretation of satellite observations can be affected by insufficient ground validation and sensor calibration. In addition their spatial resolution can make it
difficult to resolve small-scale changes.
16 Vegetation greening is defined in this report as ‘an increase in photosynthetically active plant biomass which is inferred from satellite observations’.
17 CO2 fertilisation is defined in this report as ‘the enhancement of plant growth as a result of increased atmospheric carbon dioxide (CO2) concentration’. The
magnitude of CO2 fertilisation depends on nutrients and water availability.
18 Vegetation browning is defined in this report as ‘a decrease in photosynthetically active plant biomass which is inferred from satellite observations’.
19 Evidence relative to such trends in dust storms and health impacts in other regions is limited in the literature assessed in this report.
10
SPM
Summary for Policymakers
A.2.6 Global warming has led to shifts of climate zones in many world regions, including expansion of arid climate zones and
contraction of polar climate zones (high confidence). As a consequence, many plant and animal species have experienced
changes in their ranges, abundances, and shifts in their seasonal activities (high confidence). {2.2, 3.2.2, 4.4.1}
A.2.7 Climate change can exacerbate land degradation processes (high confidence) including through increases in rainfall intensity,
flooding, drought frequency and severity, heat stress, dry spells, wind, sea-level rise and wave action, and permafrost thaw
with outcomes being modulated by land management. Ongoing coastal erosion is intensifying and impinging on more regions
with sea-level rise adding to land use pressure in some regions (medium confidence). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6,
Table 4.1, 7.2.1, 7.2.2}
A.2.8 Climate change has already affected food security due to warming, changing precipitation patterns, and greater frequency
of some extreme events (high confidence). Studies that separate out climate change from other factors affecting crop yields
have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively
by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets)
have been affected positively over recent decades (high confidence). Climate change has resulted in lower animal growth
rates and productivity in pastoral systems in Africa (high confidence). There is robust evidence that agricultural pests and
diseases have already responded to climate change resulting in both increases and decreases of infestations (high confidence).
Based on indigenous and local knowledge, climate change is affecting food security in drylands, particularly those in Africa,
and high mountain regions of Asia and South America.20 {5.2.1, 5.2.2, 7.2.2}
A.3 Agriculture, Forestry and Other Land Use (AFOLU) activities accounted for around 13% of CO2,
44% of methane (CH4), and 81% of nitrous oxide (N2O) emissions from human activities globally
during 2007-2016, representing 23% (12.0 ± 2.9 GtCO2eq yr-1) of total net anthropogenic emissions
of GHGs (medium confidence).21 The natural response of land to human-induced environmental
change caused a net sink of around 11.2 GtCO2 yr-1 during 2007–2016 (equivalent to 29% of total
CO2 emissions) (medium confidence); the persistence of the sink is uncertain due to climate change
(high confidence). If emissions associated with pre- and post-production activities in the global food
system22 are included, the emissions are estimated to be 21–37% of total net anthropogenic GHG
emissions (medium confidence). {2.3, Table 2.2, 5.4}
A.3.1 Land is simultaneously a source and a sink of CO2 due to both anthropogenic and natural drivers, making it hard to separate
anthropogenic from natural fluxes (very high confidence). Global models estimate net CO2 emissions of 5.2 ± 2.6 GtCO2 yr-1
(likely range) from land use and land-use change during 2007–2016. These net emissions are mostly due to deforestation,
partly offset by afforestation/reforestation, and emissions and removals by other land use activities (very high confidence).23
There is no clear trend in annual emissions since 1990 (medium confidence). (Figure SPM.1, Table SPM.1) {1.1, 2.3, Table 2.2,
Table 2.3}
A.3.2 The natural response of land to human-induced environmental changes such as increasing atmospheric CO2 concentration,
nitrogen deposition, and climate change, resulted in global net removals of 11.2 ± 2.6 GtCO2 yr–1 (likely range) during 2007–
2016. The sum of the net removals due to this response and the AFOLU net emissions gives a total net land-atmosphere flux
that removed 6.0 ± 3.7 GtCO2 yr-1 during 2007–2016 (likely range). Future net increases in CO2 emissions from vegetation
and soils due to climate change are projected to counteract increased removals due to CO2 fertilisation and longer growing
seasons (high confidence). The balance between these processes is a key source of uncertainty for determining the future of
the land carbon sink. Projected thawing of permafrost is expected to increase the loss of soil carbon (high confidence). During
the 21st century, vegetation growth in those areas may compensate in part for this loss (low confidence). (Table SPM.1) {Box
2.3, 2.3.1, 2.5.3, 2.7, Table 2.3}
20 The assessment covered literature whose methodologies included interviews and surveys with indigenous peoples and local communities.
21 This assessment only includes CO2, CH4 and N2O.
22 Global food system in this report is defined as ‘all the elements (environment, people, inputs, processes, infrastructures, institutions, etc.) and activities that relate
to the production, processing, distribution, preparation and consumption of food, and the output of these activities, including socioeconomic and environmental
outcomes at the global level’. These emissions data are not directly comparable to the national inventories prepared according to the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories.
23 The net anthropogenic flux of CO2 from ‘bookkeeping’ or ‘carbon accounting’ models is composed of two opposing gross fluxes: gross emissions (about 20 GtCO2
yr-1) are from deforestation, cultivation of soils, and oxidation of wood products; gross removals (about 14 GtCO2 yr-1) are largely from forest growth following wood
harvest and agricultural abandonment (medium confidence).
11
SPM
Summary for Policymakers
A.3.3 Global models and national GHG inventories use different methods to estimate anthropogenic CO2 emissions and removals for
the land sector. Both produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation,
afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to
harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger
area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic,
while the global model approach (Table SPM.1) treats this response as part of the non-anthropogenic sink. For illustration,
from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO2 yr-1, while the mean
of two global bookkeeping models is 5.2 ± 2.6 GtCO2 yr-1 (likely range). Consideration of differences in methods can enhance
understanding of land sector net emission estimates and their applications. {2.4.1, 2.7.3, Fig 2.5, Box 2.2}
12
SPM
Summary for Policymakers
Net anthropogenic emissions due to Agriculture, Forestry, and other Land Use (AFOLU) and non-AFOLU (Panel 1)
and global food systems (average for 2007–2016)1 (Panel 2). Positive values represent emissions; negative values
represent removals.
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I13
SPM
Summary for Policymakers
Table SPM.1 | Data sources and notes:
1 Estimates are only given until 2016 as this is the latest date when data are available for all gases.
2 Net anthropogenic flux of CO2 due to land cover change such as deforestation and afforestation, and land management including wood harvest and regrowth, as well
as peatland burning, based on two bookkeeping models as used in the Global Carbon Budget and for AR5. Agricultural soil carbon stock change under the same land
use is not considered in these models. {2.3.1.2.1, Table 2.2, Box 2.2}
3 Estimates show the mean and assessed uncertainty of two databases, FAOSTAT and USEPA. 2012 {2.3, Table 2.2}
4 Based on FAOSTAT. Categories included in this value are ‘net forest conversion’ (net deforestation), drainage of organic soils (cropland and grassland), biomass burning
(humid tropical forests, other forests, organic soils). It excludes ‘forest land’ (forest management plus net forest expansion), which is primarily a sink due to afforestation.
Note: Total FOLU emissions from FAOSTAT are 2.8 (±1.4) GtCO2 yr-1 for the period 2007–2016. {Table 2.2, Table 5.4}
5 CO2 emissions induced by activities not included in the AFOLU sector, mainly from energy (e.g., grain drying), transport (e.g., international trade), and industry (e.g.,
synthesis of inorganic fertilisers) part of food systems, including agricultural production activities (e.g., heating in greenhouses), pre-production (e.g., manufacturing of
farm inputs) and post-production (e.g., agri-food processing) activities. This estimate is land based and hence excludes emissions from fisheries. It includes emissions from
fibre and other non-food agricultural products since these are not separated from food use in databases. The CO2 emissions related to the food system in sectors other
than AFOLU are 6–-13% of total anthropogenic CO2 emissions. These emissions are typically low in smallholder subsistence farming. When added to AFOLU emissions,
the estimated share of food systems in global anthropogenic emissions is 21–-37%. {5.4.5, Table 5.4}
6 Total non-AFOLU emissions were calculated as the sum of total CO2eq emissions values for energy, industrial sources, waste and other emissions with data from the
Global Carbon Project for CO2, including international aviation and shipping and from the PRIMAP database for CH4 and N2O averaged over 2007–2014 only as that
was the period for which data were available. {2.3, Table 2.2}.
7 The natural response of land to human-induced environmental changes is the response of vegetation and soils to environmental changes such as increasing atmospheric
CO2 concentration, nitrogen deposition, and climate change. The estimate shown represents the average from Dynamic Global Vegetation Models {2.3.1.2, Box 2.2,
Table 2.3}
8 All values expressed in units of CO2eq are based on AR5 100-year Global Warming Potential (GWP) values without climate-carbon feedbacks (N2O = 265; CH4 = 28).
Note that the GWP has been used across fossil fuel and biogenic sources of methane. If a higher GWP for fossil fuel CH4 (30 per AR5) were used, then total anthropogenic
CH4 emissions expressed in CO2eq would be 2% greater.
9 This estimate is land based and hence excludes emissions from fisheries and emissions from aquaculture (except emissions from feed produced on land and used
in aquaculture), and also includes non-food use (e.g. fibre and bioenergy) since these are not separated from food use in databases. It excludes non-CO2 emissions
associated with land use change (FOLU category) since these are from fires in forests and peatlands.
10 Emissions associated with food loss and waste are included implicitly, since emissions from the food system are related to food produced, including food consumed
for nutrition and to food loss and waste. The latter is estimated at 8–10% of total anthropogenic emissions in CO2eq. {5.5.2.5}
11 No global data are available for agricultural CO2 emissions.
A.3.4 Global AFOLU emissions of methane in the period 2007–2016 were 161 ± 43 MtCH4 yr-1 (4.5 ± 1.2 GtCO2eq yr-1) (medium
confidence). The globally averaged atmospheric concentration of CH4 shows a steady increase between the mid-1980s and
early 1990s, slower growth thereafter until 1999, a period of no growth between 1999–2006, followed by a resumption of
growth in 2007 (high confidence). Biogenic sources make up a larger proportion of emissions than they did before 2000 (high
confidence). Ruminants and the expansion of rice cultivation are important contributors to the rising concentration (high
confidence). (Figure SPM.1) {Table 2.2, 2.3.2, 5.4.2, 5.4.3}
A.3.5 Anthropogenic AFOLU N2O emissions are rising, and were 8.7 ± 2.5 MtN2O yr-1 (2.3 ± 0.7 GtCO2eq yr-1) during the period
2007-2016. Anthropogenic N2O emissions {Figure SPM.1, Table SPM.1} from soils are primarily due to nitrogen application
including inefficiencies (over-application or poorly synchronised with crop demand timings) (high confidence). Cropland soils
emitted around 3 MtN2O yr-1 (around 795 MtCO2 eq yr-1) during the period 2007–2016 (medium confidence). There has been
a major growth in emissions from managed pastures due to increased manure deposition (medium confidence). Livestock on
managed pastures and rangelands accounted for more than one half of total anthropogenic N2O emissions from agriculture
in 2014 (medium confidence). {Table 2.1, 2.3.3, 5.4.2, 5.4.3}
A.3.6 Total net GHG emissions from AFOLU emissions represent 12.0 ± 2.9 GtCO2eq yr-1 during 2007–2016. This represents 23%
of total net anthropogenic emissions {Table SPM.1}.24 Other approaches, such as global food system, include agricultural
emissions and land use change (i.e., deforestation and peatland degradation), as well as outside farm gate emissions from
energy, transport and industry sectors for food production. Emissions within farm gate and from agricultural land expansion
contributing to the global food system represent 16–27% of total anthropogenic emissions (medium confidence). Emissions
outside the farm gate represent 5–10% of total anthropogenic emissions (medium confidence). Given the diversity of food
systems, there are large regional differences in the contributions from different components of the food system (very high
confidence). Emissions from agricultural production are projected to increase (high confidence), driven by population and
income growth and changes in consumption patterns (medium confidence). {5.5, Table 5.4}
24 This assessment only includes CO2, CH4 and N2O.
14
SPM
Summary for Policymakers
A.4 Changes in land conditions,25 either from land-use or climate change, affect global and regional
climate (high confidence). At the regional scale, changing land conditions can reduce or accentuate
warming and affect the intensity, frequency and duration of extreme events. The magnitude and
direction of these changes vary with location and season (high confidence). {Executive Summary
Chapter 2, 2.3, 2.4, 2.5, 3.3}
A.4.1 Since the pre-industrial period, changes in land cover due to human activities have led to both a net release of CO2 contributing
to global warming (high confidence), and an increase in global land albedo26 causing surface cooling (medium confidence).
Over the historical period, the resulting net effect on globally averaged surface temperature is estimated to be small (medium
confidence). {2.4, 2.6.1, 2.6.2}
A.4.2 The likelihood, intensity and duration of many extreme events can be significantly modified by changes in land conditions,
including heat related events such as heatwaves (high confidence) and heavy precipitation events (medium confidence).
Changes in land conditions can affect temperature and rainfall in regions as far as hundreds of kilometres away (high
confidence). {2.5.1, 2.5.2, 2.5.4, 3.3, Cross-Chapter Box 4 in Chapter 2}
A.4.3 Climate change is projected to alter land conditions with feedbacks on regional climate. In those boreal regions where the
treeline migrates northward and/or the growing season lengthens, winter warming will be enhanced due to decreased snow
cover and albedo while warming will be reduced during the growing season because of increased evapotranspiration (high
confidence). In those tropical areas where increased rainfall is projected, increased vegetation growth will reduce regional
warming (medium confidence). Drier soil conditions resulting from climate change can increase the severity of heat waves,
while wetter soil conditions have the opposite effect (high confidence). {2.5.2, 2.5.3}
A.4.4 Desertification amplifies global warming through the release of CO2 linked with the decrease in vegetation cover (high
confidence). This decrease in vegetation cover tends to increase local albedo, leading to surface cooling (high confidence).
{3.3}
A.4.5 Changes in forest cover, for example from afforestation, reforestation and deforestation, directly affect regional surface
temperature through exchanges of water and energy (high confidence).27 Where forest cover increases in tropical regions
cooling results from enhanced evapotranspiration (high confidence). Increased evapotranspiration can result in cooler days
during the growing season (high confidence) and can reduce the amplitude of heat related events (medium confidence). In
regions with seasonal snow cover, such as boreal and some temperate regions, increased tree and shrub cover also has a
wintertime warming influence due to reduced surface albedo (high confidence).28 {2.3, 2.4.3, 2.5.1, 2.5.2, 2.5.4}
A.4.6 Both global warming and urbanisation can enhance warming in cities and their surroundings (heat island effect), especially
during heat related events, including heat waves (high confidence). Night-time temperatures are more affected by this effect
than daytime temperatures (high confidence). Increased urbanisation can also intensify extreme rainfall events over the city
or downwind of urban areas (medium confidence). {2.5.1, 2.5.2, 2.5.3, 4.9.1, Cross-Chapter Box 4 in Chapter 2}
25 Land conditions encompass changes in land cover (e.g., deforestation, afforestation, urbanisation), in land use (e.g., irrigation), and in land state (e.g., degree of
wetness, degree of greening, amount of snow, amount of permafrost).
26 Land with high albedo reflects more incoming solar radiation than land with low albedo.
27 The literature indicates that forest cover changes can also affect climate through changes in emissions of reactive gases and aerosols. {2.4, 2.5}
28 Emerging literature shows that boreal forest-related aerosols may counteract at least partly the warming effect of surface albedo. {2.4.3}
15
SPM
Summary for Policymakers
Box SPM. 1 | Shared Socio-economic Pathways (SSPs)
In this report the implications of future socio-economic development on climate change mitigation, adaptation and land-use
are explored using shared socio-economic pathways (SSPs). The SSPs span a range of challenges to climate change mitigation
and adaptation.
• SSP1 includes a peak and decline in population (~7 billion in 2100), high income and reduced inequalities, effective landuse
regulation, less resource intensive consumption, including food produced in low-GHG emission systems and lower
food waste, free trade and environmentally-friendly technologies and lifestyles. Relative to other pathways, SSP1 has low
challenges to mitigation and low challenges to adaptation (i.e., high adaptive capacity)
• SSP2 includes medium population growth (~9 billion in 2100), medium income, technological progress, production and
consumption patterns are a continuation of past trends, and only a gradual reduction in inequality occurs. Relative to
other pathways, SSP2 has medium challenges to mitigation and medium challenges to adaptation (i.e., medium adaptive
capacity).
• SSP3 includes high population growth (~13 billion in 2100), low income and continued inequalities, material-intensive
consumption and production, barriers to trade, and slow rates of technological change. Relative to other pathways, SSP3
has high challenges to mitigation and high challenges to adaptation (i.e., low adaptive capacity).
• SSP4 includes medium population growth (~9 billion in 2100), medium income, but significant inequality within and
across regions. Relative to other pathways, SSP4 has low challenges to mitigation, but high challenges to adaptation (i.e.,
low adaptive capacity).
• SSP5 includes a peak and decline in population (~7 billion in 2100), high income, reduced inequalities, and free trade. This
pathway includes resource-intensive production, consumption and lifestyles. Relative to other pathways, SSP5 has high
challenges to mitigation, but low challenges to adaptation (i.e., high adaptive capacity).
• The SSPs can be combined with Representative Concentration Pathways (RCPs) which imply different levels of mitigation,
with implications for adaptation. Therefore, SSPs can be consistent with different levels of global mean surface
temperature rise as projected by different SSP-RCP combinations. However, some SSP-RCP combinations are not possible;
for instance RCP2.6 and lower levels of future global mean surface temperature rise (e.g., 1.5ºC) are not possible in SSP3
in modelled pathways. {1.2.2, 6.1.4, Cross-Chapter Box 1 in Chapter 1, Cross-Chapter Box 9 in Chapter 6}
16
SPM
Summary for Policymakers
1.5°
5°
4°
3°
2°
1° 2006-2015
H
M
M
H
M
M
H
M
M
H
M
M
H
M
M
M
L
L
H
M
H
Tropical crop
yield decline
Food
supply instabilities
Dryland
water scarcity
Vegetation
loss
Wildfire
damage
Soil
erosion
Permafrost
degradation
Systems at risk:
Food
Livelihoods
Value of land
Human health
Ecosystem health
Infrastructure
L Low
M Medium
H High
H Example
Socio-economic choices can reduce or
exacerbate climate related risks as well as
influence the rate of temperature increase.
The SSP1 pathway illustrates a world with
low population growth, high income and
reduced inequalities, food produced in low
GHG emission systems, eective land use
regulation and high adaptive capacity. The
SSP3 pathway has the opposite trends.
Risks are lower in SSP1 compared with
SSP3 given the same level of GMST
increase.
Increases in global mean surface temperature (GMST), relative to pre-industrial levels, aect processes involved in desertification (water
scarcity), land degradation (soil erosion, vegetation loss, wildfire, permafrost thaw) and food security (crop yield and food supply
instabilities). Changes in these processes drive risks to food systems, livelihoods, infrastructure, the value of land, and human and
ecosystem health. Changes in one process (e.g. wildfire or water scarcity) may result in compound risks. Risks are location-specific and
dier by region.
A. Risks to humans and ecosystems from changes in land-based processes as a result
of climate change
B. Dierent socioeconomic pathways aect levels of climate related risks
GMST change
relative to levels in pre-industrial time (°C)
GMST change
relative to levels in pre-industrial time (°C)
GMST change
relative to levels in pre-industrial time (°C)
3°
2°
1°
1.5°
H H 2006-2015
L
M
M
H
M
M
H
M
M
M
M
M
SSP1 SSP3 SSP1 SSP3 SSP1 SSP3
Desertification Land degradation Food insecurity
(water scarcity in drylands) (habitat degr., wildfire, floods) (availability, access)
Legend: Level of impact/risk
Undetectable
Moderate
High
Very high
Legend: Confidence
level for
Purple: Very high probability of severe impacts/ risks transition
and the presence of significant irreversibility or the
persistence of climate-related hazards, combined with
limited ability to adapt due to the nature of the hazard
or impacts/risks.
Red: Significant and widespread impacts/risks.
Yellow: Impacts/risks are detectable and attributable
to climate change with at least medium confidence.
White: Impacts/risks are undetectable.
Risks
Impacts
5°
4°
3°
2°
1°
Wildfire damage
Over 100M
people
additionally
exposed
Over 50%
increase in
area burned in
Mediterranean
region
Increase in fire
weather season
5°
4°
3°
2°
1° H
M
M
Food supply instabilities
Sustained food
supply
disruptions
globally
Infrequent
price spikes
aect
individual
countries
Periodic food
shocks across
regions
H
M
M
Indicative example of transitions Indicative example of transitions
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17
SPM
Summary for Policymakers
Figure SPM.2: Risks to land-related human systems and ecosystems from global climate change, socio-economic development and mitigation
choices in terrestrial ecosystems. | As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming at
which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts of the underlying report. The Figure indicates
assessed risks at approximate warming levels which may be influenced by a variety of factors, including adaptation responses. The assessment considers adaptive
capacity consistent with the SSP pathways as described below. Panel A: Risks to selected elements of the land system as a function of global mean surface
temperature {2.1, Box 2.1, 3.5, 3.7.1.1, 4.4.1.1, 4.4.1.2, 4.4.1.3, 5.2.2, 5.2.3, 5.2.4, 5.2.5, 7.2, 7.3, Table SM7.1}. Links to broader systems are illustrative and
not intended to be comprehensive. Risk levels are estimated assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions
broadly consistent with an SSP2 pathway. {Table SM7.4} Panel B: Risks associated with desertification, land degradation and food security due to climate change
and patterns of socio-economic development. Increasing risks associated with desertification include population exposed and vulnerable to water scarcity in
drylands. Risks related to land degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks to food
security include availability and access to food, including population at risk of hunger, food price increases and increases in disability adjusted life years attributable
due to childhood underweight. Risks are assessed for two contrasted socio-economic pathways (SSP1 and SSP3 {Box SPM.1}) excluding the effects of targeted
mitigation policies. {3.5, 4.2.1.2, 5.2.2, 5.2.3, 5.2.4, 5.2.5, 6.1.4, 7.2, Table SM7.5} Risks are not indicated beyond 3°C because SSP1 does not exceed this level
of temperature change. All panels: As part of the assessment, literature was compiled and data extracted into a summary table. A formal expert elicitation
protocol (based on modified-Delphi technique and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multiround
elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus discussion. Further information on methods and
underlying literature can be found in Chapter 7 Supplementary Material.
29 Unprecedented climatic conditions are defined in this report as ‘not having occurred anywhere during the 20th century’. They are characterised by high temperature
with strong seasonality and shifts in precipitation. In the literature assessed, the effect of climatic variables other than temperature and precipitation were not
considered.
30 The supply of food is defined in this report as ‘encompassing availability and access (including price)’. Food supply instability refers to variability that influences food
security through reducing access.
A.5 Climate change creates additional stresses on land, exacerbating existing risks to livelihoods,
biodiversity, human and ecosystem health, infrastructure, and food systems (high confidence).
Increasing impacts on land are projected under all future GHG emission scenarios (high confidence).
Some regions will face higher risks, while some regions will face risks previously not anticipated (high
confidence). Cascading risks with impacts on multiple systems and sectors also vary across regions
(high confidence). (Figure SPM.2) {2.2, 3.5, 4.2, 4.4, 4.7, 5.1, 5.2, 5.8, 6.1, 7.2, 7.3, Cross-Chapter Box 9
in Chapter 6}
A.5.1 With increasing warming, the frequency, intensity and duration of heat related events including heatwaves are projected
to continue to increase through the 21st century (high confidence). The frequency and intensity of droughts are projected to
increase particularly in the Mediterranean region and southern Africa (medium confidence). The frequency and intensity of
extreme rainfall events are projected to increase in many regions (high confidence). {2.2.5, 3.5.1, 4.2.3, 5.2}
A.5.2 With increasing warming, climate zones are projected to further shift poleward in the middle and high latitudes (high confidence).
In high-latitude regions, warming is projected to increase disturbance in boreal forests, including drought, wildfire, and pest
outbreaks (high confidence). In tropical regions, under medium and high GHG emissions scenarios, warming is projected to
result in the emergence of unprecedented29 climatic conditions by the mid to late 21st century (medium confidence). {2.2.4,
2.2.5, 2.5.3, 4.3.2}
A.5.3 Current levels of global warming are associated with moderate risks from increased dryland water scarcity, soil erosion,
vegetation loss, wildfire damage, permafrost thawing, coastal degradation and tropical crop yield decline (high confidence).
Risks, including cascading risks, are projected to become increasingly severe with increasing temperatures. At around 1.5°C of
global warming the risks from dryland water scarcity, wildfire damage, permafrost degradation and food supply instabilities
are projected to be high (medium confidence). At around 2°C of global warming the risk from permafrost degradation and
food supply instabilities are projected to be very high (medium confidence). Additionally, at around 3°C of global warming
risk from vegetation loss, wildfire damage, and dryland water scarcity are also projected to be very high (medium confidence).
Risks from droughts, water stress, heat related events such as heatwaves and habitat degradation simultaneously increase
between 1.5°C and 3°C warming (low confidence). (Figure SPM.2) {7.2.2, Cross-Chapter Box 9 in Chapter 6, Chapter 7
Supplementary Material}
A.5.4 The stability of food supply30 is projected to decrease as the magnitude and frequency of extreme weather events that disrupt
food chains increases (high confidence). Increased atmospheric CO2 levels can also lower the nutritional quality of crops (high
confidence). In SSP2, global crop and economic models project a median increase of 7.6% (range of 1–23%) in cereal prices in
2050 due to climate change (RCP6.0), leading to higher food prices and increased risk of food insecurity and hunger (medium
18
SPM
Summary for Policymakers
SPM
Summary for Policymakers
confidence). The most vulnerable people will be more severely affected (high confidence). {5.2.3, 5.2.4, 5.2.5, 5.8.1, 7.2.2.2,
7.3.1}
A.5.5 In drylands, climate change and desertification are projected to cause reductions in crop and livestock productivity (high
confidence), modify the plant species mix and reduce biodiversity (medium confidence). Under SSP2, the dryland population
vulnerable to water stress, drought intensity and habitat degradation is projected to reach 178 million people by 2050 at 1.5°C
warming, increasing to 220 million people at 2°C warming, and 277 million people at 3°C warming (low confidence). {3.5.1,
3.5.2, 3.7.3}
A.5.6 Asia and Africa31 are projected to have the highest number of people vulnerable to increased desertification. North America,
South America, Mediterranean, southern Africa and central Asia may be increasingly affected by wildfire. The tropics and
subtropics are projected to be most vulnerable to crop yield decline. Land degradation resulting from the combination of
sea-level rise and more intense cyclones is projected to jeopardise lives and livelihoods in cyclone prone areas (very high
confidence). Within populations, women, the young, elderly and poor are most at risk (high confidence). {3.5.1, 3.5.2, 4.4,
Table 4.1, 5.2.2, 7.2.2, Cross-Chapter Box 3 in Chapter 2}
A.5.7 Changes in climate can amplify environmentally induced migration both within countries and across borders (medium
confidence), reflecting multiple drivers of mobility and available adaptation measures (high confidence). Extreme weather
and climate or slow-onset events may lead to increased displacement, disrupted food chains, threatened livelihoods (high
confidence), and contribute to exacerbated stresses for conflict (medium confidence). {3.4.2, 4.7.3, 5.2.3, 5.2.4, 5.2.5, 5.8.2,
7.2.2, 7.3.1}
A.5.8 Unsustainable land management has led to negative economic impacts (high confidence). Climate change is projected to
exacerbate these negative economic impacts (high confidence). {4.3.1, 4.4.1, 4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8, 5.2, 5.8.1,
7.3.4, 7.6.1, Cross-Chapter Box 10 in Chapter 7}
A.6 The level of risk posed by climate change depends both on the level of warming and on how
population, consumption, production, technological development, and land management patterns
evolve (high confidence). Pathways with higher demand for food, feed, and water, more resourceintensive
consumption and production, and more limited technological improvements in agriculture
yields result in higher risks from water scarcity in drylands, land degradation, and food insecurity
(high confidence). (Figure SPM.2b) {5.1.4, 5.2.3, 6.1.4, 7.2, Cross-Chapter Box 9 in Chapter 6}
A.6.1 Projected increases in population and income, combined with changes in consumption patterns, result in increased demand for
food, feed, and water in 2050 in all SSPs (high confidence). These changes, combined with land management practices, have
implications for land-use change, food insecurity, water scarcity, terrestrial GHG emissions, carbon sequestration potential,
and biodiversity (high confidence). Development pathways in which incomes increase and the demand for land conversion
is reduced, either through reduced agricultural demand or improved productivity, can lead to reductions in food insecurity
(high confidence). All assessed future socio-economic pathways result in increases in water demand and water scarcity (high
confidence). SSPs with greater cropland expansion result in larger declines in biodiversity (high confidence). {6.1.4}
A.6.2 Risks related to water scarcity in drylands are lower in pathways with low population growth, less increase in water demand,
and high adaptive capacity, as in SSP1. In these scenarios the risk from water scarcity in drylands is moderate even at global
warming of 3°C (low confidence). By contrast, risks related to water scarcity in drylands are greater for pathways with high
population growth, high vulnerability, higher water demand, and low adaptive capacity, such as SSP3. In SSP3 the transition
from moderate to high risk occurs between 1.2°C and 1.5°C (medium confidence). (Figure SPM.2b, Box SPM.1) {7.2}
A.6.3 Risks related to climate change driven land degradation are higher in pathways with a higher population, increased land-use
change, low adaptive capacity and other barriers to adaptation (e.g., SSP3). These scenarios result in more people exposed to
ecosystem degradation, fire, and coastal flooding (medium confidence). For land degradation, the projected transition from
moderate to high risk occurs for global warming between 1.8°C and 2.8°C in SSP1 (low confidence) and between 1.4°C and
2°C in SSP3 (medium confidence). The projected transition from high to very high risk occurs between 2.2°C and 2.8°C for
SSP3 (medium confidence). (Figure SPM.2b) {4.4, 7.2}
31 West Africa has a high number of people vulnerable to increased desertification and yield decline. North Africa is vulnerable to water scarcity.
19
SPM
Summary for Policymakers
SPM
A.6.4 Risks related to food security are greater in pathways with lower income, increased food demand, increased food prices
resulting from competition for land, more limited trade, and other challenges to adaptation (e.g., SSP3) (high confidence). For
food security, the transition from moderate to high risk occurs for global warming between 2.5°C and 3.5°C in SSP1 (medium
confidence) and between 1.3°C and 1.7°C in SSP3 (medium confidence). The transition from high to very high risk occurs
between 2°C and 2.7°C for SSP3 (medium confidence). (Figure SPM.2b) {7.2}
A.6.5 Urban expansion is projected to lead to conversion of cropland leading to losses in food production (high confidence). This
can result in additional risks to the food system. Strategies for reducing these impacts can include urban and peri-urban food
production and management of urban expansion, as well as urban green infrastructure that can reduce climate risks in cities32
(high confidence). (Figure SPM.3) {4.9.1, 5.5, 5.6, 6.3, 6.4, 7.5.6}
32 The land systems considered in this report do not include urban ecosystem dynamics in detail. Urban areas, urban expansion, and other urban processes and their
relation to land-related processes are extensive, dynamic, and complex. Several issues addressed in this report such as population, growth, incomes, food production
and consumption, food security, and diets have close relationships with these urban processes. Urban areas are also the setting of many processes related to landuse
change dynamics, including loss of ecosystem functions and services, that can lead to increased disaster risk. Some specific urban issues are assessed in this
report.
20
SPM
Summary for Policymakers
B. Adaptation and mitigation response options
B.1 Many land-related responses that contribute to climate change adaptation and mitigation can also
combat desertification and land degradation and enhance food security. The potential for landrelated
responses and the relative emphasis on adaptation and mitigation is context specific, including
the adaptive capacities of communities and regions. While land-related response options can make
important contributions to adaptation and mitigation, there are some barriers to adaptation and
limits to their contribution to global mitigation. (very high confidence) (Figure SPM.3) {2.6, 4.8, 5.6,
6.1, 6.3, 6.4}
B.1.1 Some land-related actions are already being taken that contribute to climate change adaptation, mitigation and sustainable
development. The response options were assessed across adaptation, mitigation, combating desertification and land
degradation, food security and sustainable development, and a select set of options deliver across all of these challenges.
These options include, but are not limited to, sustainable food production, improved and sustainable forest management,
soil organic carbon management, ecosystem conservation and land restoration, reduced deforestation and degradation, and
reduced food loss and waste (high confidence). These response options require integration of biophysical, socioeconomic and
other enabling factors. {6.3, 6.4.5, 7.5.6, Cross-Chapter Box 10 in Chapter 7}
B.1.2 While some response options have immediate impacts, others take decades to deliver measurable results. Examples of
response options with immediate impacts include the conservation of high-carbon ecosystems such as peatlands, wetlands,
rangelands, mangroves and forests. Examples that provide multiple ecosystem services and functions, but take more time to
deliver, include afforestation and reforestation as well as the restoration of high-carbon ecosystems, agroforestry, and the
reclamation of degraded soils (high confidence). {6.4.5, 7.5.6, Cross-Chapter Box 10 in Chapter 7}
B.1.3 The successful implementation of response options depends on consideration of local environmental and socio-economic
conditions. Some options such as soil carbon management are potentially applicable across a broad range of land use types,
whereas the efficacy of land management practices relating to organic soils, peatlands and wetlands, and those linked to
freshwater resources, depends on specific agro-ecological conditions (high confidence). Given the site-specific nature of climate
change impacts on food system components and wide variations in agroecosystems, adaptation and mitigation options and
their barriers are linked to environmental and cultural context at regional and local levels (high confidence). Achieving land
degradation neutrality depends on the integration of multiple responses across local, regional and national scales and across
multiple sectors including agriculture, pasture, forest and water (high confidence). {4.8, 6.2, 6.3, 6.4.4, 7.5.6}
B.1.4 Land-based options that deliver carbon sequestration in soil or vegetation, such as afforestation, reforestation, agroforestry,
soil carbon management on mineral soils, or carbon storage in harvested wood products, do not continue to sequester carbon
indefinitely (high confidence). Peatlands, however, can continue to sequester carbon for centuries (high confidence). When
vegetation matures or when vegetation and soil carbon reservoirs reach saturation, the annual removal of CO2 from the
atmosphere declines towards zero, while carbon stocks can be maintained (high confidence). However, accumulated carbon in
vegetation and soils is at risk from future loss (or sink reversal) triggered by disturbances such as flood, drought, fire, or pest
outbreaks, or future poor management (high confidence). {6.4.1}
B.2 Most of the response options assessed contribute positively to sustainable development and other
societal goals (high confidence). Many response options can be applied without competing for land
and have the potential to provide multiple co-benefits (high confidence). A further set of response
options has the potential to reduce demand for land, thereby enhancing the potential for other
response options to deliver across each of climate change adaptation and mitigation, combating
desertification and land degradation, and enhancing food security (high confidence). (Figure SPM.3)
{4.8, 6.2, 6.3.6, 6.4.3}
B.2.1 A number of land management options, such as improved management of cropland and grazing lands, improved and
sustainable forest management, and increased soil organic carbon content, do not require land use change and do not
create demand for more land conversion (high confidence). Further, a number of response options such as increased food
productivity, dietary choices and food losses, and waste reduction, can reduce demand for land conversion, thereby potentially
freeing land and creating opportunities for enhanced implementation of other response options (high confidence). Response
21
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Summary for Policymakers
options that reduce competition for land are possible and are applicable at different scales, from farm to regional (high
confidence). (Figure SPM.3) {4.8, 6.3.6, 6.4}
B.2.2 A wide range of adaptation and mitigation responses, e.g., preserving and restoring natural ecosystems such as peatland,
coastal lands and forests, biodiversity conservation, reducing competition for land, fire management, soil management, and
most risk management options (e.g., use of local seeds, disaster risk management, risk sharing instruments) have the potential
to make positive contributions to sustainable development, enhancement of ecosystem functions and services and other
societal goals (medium confidence). Ecosystem-based adaptation can, in some contexts, promote nature conservation while
alleviating poverty and can even provide co-benefits by removing GHGs and protecting livelihoods (e.g., mangroves) (medium
confidence). {6.4.3, 7.4.6.2}
B.2.3 Most of the land management-based response options that do not increase competition for land, and almost all options based
on value chain management (e.g., dietary choices, reduced post-harvest losses, reduced food waste) and risk management,
can contribute to eradicating poverty and eliminating hunger while promoting good health and wellbeing, clean water and
sanitation, climate action, and life on land (medium confidence). {6.4.3}
B.3 Although most response options can be applied without competing for available land, some can
increase demand for land conversion (high confidence). At the deployment scale of several GtCO2
yr-1, this increased demand for land conversion could lead to adverse side effects for adaptation,
desertification, land degradation and food security (high confidence). If applied on a limited share
of total land and integrated into sustainably managed landscapes, there will be fewer adverse sideeffects
and some positive co-benefits can be realised (high confidence). (Figure SPM.3) {4.5, 6.2, 6.4,
Cross-Chapter Box 7 in Chapter 6}
B.3.1 If applied at scales necessary to remove CO2 from the atmosphere at the level of several GtCO2 yr-1, afforestation, reforestation
and the use of land to provide feedstock for bioenergy with or without carbon capture and storage, or for biochar, could greatly
increase demand for land conversion (high confidence). Integration into sustainably managed landscapes at appropriate scale
can ameliorate adverse impacts (medium confidence). Reduced grassland conversion to croplands, restoration and reduced
conversion of peatlands, and restoration and reduced conversion of coastal wetlands affect smaller land areas globally, and
the impacts on land use change of these options are smaller or more variable (high confidence). (Figure SPM.3) {Cross-Chapter
Box 7 in Chapter 6, 6.4}
B.3.2 While land can make a valuable contribution to climate change mitigation, there are limits to the deployment of land-based
mitigation measures such as bioenergy crops or afforestation. Widespread use at the scale of several millions of km2 globally
could increase risks for desertification, land degradation, food security and sustainable development (medium confidence).
Applied on a limited share of total land, land-based mitigation measures that displace other land uses have fewer adverse sideeffects
and can have positive co-benefits for adaptation, desertification, land degradation or food security. (high confidence)
(Figure SPM.3) {4.2, 4.5, 6.4; Cross-Chapter Box 7 in Chapter 6}
B.3.3 The production and use of biomass for bioenergy can have co-benefits, adverse side-effects, and risks for land degradation,
food insecurity, GHG emissions and other environmental and sustainable development goals (high confidence). These impacts
are context specific and depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon
stocks, climatic region and management regime, and other land-demanding response options can have a similar range of
consequences (high confidence). The use of residues and organic waste as bioenergy feedstock can mitigate land use change
pressures associated with bioenergy deployment, but residues are limited and the removal of residues that would otherwise
be left on the soil could lead to soil degradation (high confidence). (Figure SPM.3) {2.6.1.5, Cross-Chapter Box 7 in Chapter 6}
B.3.4 For projected socioeconomic pathways with low population, effective land-use regulation, food produced in low-GHG emission
systems and lower food loss and waste (SSP1), the transition from low to moderate risk to food security, land degradation
and water scarcity in dry lands occur between 1 and 4 million km2 of bioenergy or bioenergy with carbon capture and storage
(BECCS) (medium confidence). By contrast, in pathways with high population, low income and slow rates of technological
change (SSP3), the transition from low to moderate risk occurs between 0.1 and 1 million km2 (medium confidence). (Box
SPM.1) {6.4, Table SM7.6, Cross-Chapter Box 7 in Chapter 6}
22
SPM
Summary for Policymakers
B.4 Many activities for combating desertification can contribute to climate change adaptation with
mitigation co-benefits, as well as to halting biodiversity loss with sustainable development cobenefits
to society (high confidence). Avoiding, reducing and reversing desertification would enhance
soil fertility, increase carbon storage in soils and biomass, while benefitting agricultural productivity
and food security (high confidence). Preventing desertification is preferable to attempting to restore
degraded land due to the potential for residual risks and maladaptive outcomes (high confidence).
{3.6.1, 3.6.2, 3.6.3, 3.6.4, 3.7.1, 3.7.2}
B.4.1 Solutions that help adapt to and mitigate climate change while contributing to combating desertification are site and
regionally specific and include inter alia: water harvesting and micro-irrigation, restoring degraded lands using droughtresilient
ecologically appropriate plants, agroforestry, and other agroecological and ecosystem-based adaptation practices
(high confidence). {3.3, 3.6.1, 3.7.2, 3.7.5, 5.2, 5.6}
B.4.2 Reducing dust and sand storms and sand dune movement can lessen the negative effects of wind erosion and improve air
quality and health (high confidence). Depending on water availability and soil conditions, afforestation, tree planting and
ecosystem restoration programs, which aim for the creation of windbreaks in the form of ‘green walls’ and ‘green dams’
using native and other climate resilient tree species with low water needs, can reduce sand storms, avert wind erosion, and
contribute to carbon sinks, while improving micro-climates, soil nutrients and water retention (high confidence). {3.3, 3.6.1,
3.7.2, 3.7.5}
B.4.3 Measures to combat desertification can promote soil carbon sequestration (high confidence). Natural vegetation restoration
and tree planting on degraded land enriches, in the long term, carbon in the topsoil and subsoil (medium confidence).
Modelled rates of carbon sequestration following the adoption of conservation agriculture practices in drylands depend on
local conditions (medium confidence). If soil carbon is lost, it may take a prolonged period of time for carbon stocks to recover.
{3.1.4, 3.3, 3.6.1, 3.6.3, 3.7.1, 3.7.2}
B.4.4 Eradicating poverty and ensuring food security can benefit from applying measures promoting land degradation neutrality
(including avoiding, reducing and reversing land degradation) in rangelands, croplands and forests, which contribute to
combating desertification, while mitigating and adapting to climate change within the framework of sustainable development.
Such measures include avoiding deforestation and locally suitable practices including management of rangeland and forest
fires (high confidence). {3.4.2, 3.6.1, 3.6.2, 3.6.3, 4.8.5}
B.4.5 Currently there is a lack of knowledge of adaptation limits and potential maladaptation to combined effects of climate change
and desertification. In the absence of new or enhanced adaptation options, the potential for residual risks and maladaptive
outcomes is high (high confidence). Even when solutions are available, social, economic and institutional constraints could
pose barriers to their implementation (medium confidence). Some adaptation options can become maladaptive due to their
environmental impacts, such as irrigation causing soil salinisation or over extraction leading to ground-water depletion
(medium confidence). Extreme forms of desertification can lead to the complete loss of land productivity, limiting adaptation
options or reaching the limits to adaptation (high confidence). {Executive Summary Chapter 3, 3.6.4, 3.7.5, 7.4.9}
B.4.6 Developing, enabling and promoting access to cleaner energy sources and technologies can contribute to adaptation and
mitigating climate change and combating desertification and forest degradation through decreasing the use of traditional
biomass for energy while increasing the diversity of energy supply (medium confidence). This can have socioeconomic and
health benefits, especially for women and children. (high confidence). The efficiency of wind and solar energy infrastructures
is recognised; the efficiency can be affected in some regions by dust and sand storms (high confidence). {3.5.3, 3.5.4, 4.4.4,
7.5.2, Cross-Chapter Box 12 in Chapter 7}
23
SPM
Summary for Policymakers
B.5 Sustainable land management,33 including sustainable forest management,34 can prevent and reduce
land degradation, maintain land productivity, and sometimes reverse the adverse impacts of climate
change on land degradation (very high confidence). It can also contribute to mitigation and adaptation
(high confidence). Reducing and reversing land degradation, at scales from individual farms to
entire watersheds, can provide cost effective, immediate, and long-term benefits to communities
and support several Sustainable Development Goals (SDGs) with co-benefits for adaptation (very
high confidence) and mitigation (high confidence). Even with implementation of sustainable land
management, limits to adaptation can be exceeded in some situations (medium confidence). {1.3.2,
4.1.5, 4.8, 7.5.6, Table 4.2}
B.5.1 Land degradation in agriculture systems can be addressed through sustainable land management, with an ecological and
socioeconomic focus, with co-benefits for climate change adaptation. Management options that reduce vulnerability to soil
erosion and nutrient loss include growing green manure crops and cover crops, crop residue retention, reduced/zero tillage,
and maintenance of ground cover through improved grazing management (very high confidence). {4.8}
B.5.2 The following options also have mitigation co-benefits. Farming systems such as agroforestry, perennial pasture phases and
use of perennial grains, can substantially reduce erosion and nutrient leaching while building soil carbon (high confidence).
The global sequestration potential of cover crops would be about 0.44 ± 0.11 GtCO2 yr-1 if applied to 25% of global cropland
(high confidence). The application of certain biochars can sequester carbon (high confidence), and improve soil conditions in
some soil types/climates (medium confidence). {4.8.1.1, 4.8.1.3, 4.9.2, 4.9.5, 5.5.1, 5.5.4, Cross-Chapter Box 6 in Chapter 5}
B.5.3 Reducing deforestation and forest degradation lowers GHG emissions (high confidence), with an estimated technical mitigation
potential of 0.4–5.8 GtCO2 yr-1. By providing long-term livelihoods for communities, sustainable forest management can
reduce the extent of forest conversion to non-forest uses (e.g., cropland or settlements) (high confidence). Sustainable forest
management aimed at providing timber, fibre, biomass, non-timber resources and other ecosystem functions and services, can
lower GHG emissions and can contribute to adaptation (high confidence). {2.6.1.2, 4.1.5, 4.3.2, 4.5.3, 4.8.1.3, 4.8.3, 4.8.4}
B.5.4 Sustainable forest management can maintain or enhance forest carbon stocks, and can maintain forest carbon sinks, including
by transferring carbon to wood products, thus addressing the issue of sink saturation (high confidence). Where wood carbon is
transferred to harvested wood products, these can store carbon over the long-term and can substitute for emissions-intensive
materials reducing emissions in other sectors (high confidence). Where biomass is used for energy, e.g., as a mitigation
strategy, the carbon is released back into the atmosphere more quickly (high confidence). (Figure SPM.3) {2.6.1, 2.7, 4.1.5,
4.8.4, 6.4.1, Cross-Chapter Box 7 in Chapter 6}
B.5.5 Climate change can lead to land degradation, even with the implementation of measures intended to avoid, reduce or reverse
land degradation (high confidence). Such limits to adaptation are dynamic, site-specific and are determined through the
interaction of biophysical changes with social and institutional conditions (very high confidence). In some situations, exceeding
the limits of adaptation can trigger escalating losses or result in undesirable transformational changes (medium confidence)
such as forced migration (low confidence), conflicts (low confidence) or poverty (medium confidence). Examples of climate
change induced land degradation that may exceed limits to adaptation include coastal erosion exacerbated by sea level rise
where land disappears (high confidence), thawing of permafrost affecting infrastructure and livelihoods (medium confidence),
and extreme soil erosion causing loss of productive capacity (medium confidence). {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}
B.6 Response options throughout the food system, from production to consumption, including food loss
and waste, can be deployed and scaled up to advance adaptation and mitigation (high confidence). The
total technical mitigation potential from crop and livestock activities, and agroforestry is estimated as
2.3 – 9.6 GtCO2eq yr-1 by 2050 (medium confidence). The total technical mitigation potential of dietary
changes is estimated as 0.7 – 8 GtCO2eq yr-1 by 2050 (medium confidence). {5.3, 5.5, 5.6}
33 Sustainable land management is defined in this report as ‘the stewardship and use of land resources, including soils, water, animals and plants, to meet changing
human needs, while simultaneously ensuring the long-term productive potential of these resources and the maintenance of their environmental functions’. Examples
of options include, inter alia, agroecology (including agroforestry), conservation agriculture and forestry practices, crop and forest species diversity, appropriate crop
and forest rotations, organic farming, integrated pest management, the conservation of pollinators, rain water harvesting, range and pasture management, and
precision agriculture systems.
34 Sustainable forest management is defined in this report as ‘the stewardship and use of forests and forest lands in a way, and at a rate, that maintains their
biodiversity, productivity, regeneration capacity, vitality, and their potential to fulfil now and in the future, relevant ecological, economic and social functions at local,
national and global levels and that does not cause damage to other ecosystems’.
24
SPM
Summary for Policymakers
B.6.1 Practices that contribute to climate change adaptation and mitigation in cropland include increasing soil organic matter,
erosion control, improved fertiliser management, improved crop management, for example paddy rice management, and
use of varieties and genetic improvements for heat and drought tolerance. For livestock, options include better grazing land
management, improved manure management, higher-quality feed, and use of breeds and genetic improvement. Different
farming and pastoral systems can achieve reductions in the emissions intensity of livestock products. Depending on the
farming and pastoral systems and level of development, reductions in the emissions intensity of livestock products may lead
to absolute reductions in GHG emissions (medium confidence). Many livestock related options can enhance the adaptive
capacity of rural communities, in particular, of smallholders and pastoralists. Significant synergies exist between adaptation
and mitigation, for example through sustainable land management approaches (high confidence). {4.8, 5.3.3, 5.5.1, 5.6}
B.6.2 Diversification in the food system (e.g., implementation of integrated production systems, broad-based genetic resources,
and diets) can reduce risks from climate change (medium confidence). Balanced diets, featuring plant-based foods, such as
those based on coarse grains, legumes, fruits and vegetables, nuts and seeds, and animal-sourced food produced in resilient,
sustainable and low-GHG emission systems, present major opportunities for adaptation and mitigation while generating
significant co-benefits in terms of human health (high confidence). By 2050, dietary changes could free several million km2
(medium confidence) of land and provide a technical mitigation potential of 0.7 to 8.0 GtCO2eq yr-1, relative to business
as usual projections (high confidence). Transitions towards low-GHG emission diets may be influenced by local production
practices, technical and financial barriers and associated livelihoods and cultural habits (high confidence). {5.3, 5.5.2, 5.5, 5.6}
B.6.3 Reduction of food loss and waste can lower GHG emissions and contribute to adaptation through reduction in the land area
needed for food production (medium confidence). During 2010-2016, global food loss and waste contributed 8 –10% of total
anthropogenic GHG emissions (medium confidence). Currently, 25 –30% of total food produced is lost or wasted (medium
confidence). Technical options such as improved harvesting techniques, on-farm storage, infrastructure, transport, packaging,
retail and education can reduce food loss and waste across the supply chain. Causes of food loss and waste differ substantially
between developed and developing countries, as well as between regions (medium confidence). By 2050, reduced food loss
and waste can free several million km2 of land (low confidence). {5.5.2, 6.3.6}
B.7 Future land use depends, in part, on the desired climate outcome and the portfolio of response
options deployed (high confidence). All assessed modelled pathways that limit warming to 1.5ºC or
well below 2°C require land-based mitigation and land-use change, with most including different
combinations of reforestation, afforestation, reduced deforestation, and bioenergy (high confidence).
A small number of modelled pathways achieve 1.5ºC with reduced land conversion (high confidence)
and thus reduced consequences for desertification, land degradation, and food security (medium
confidence). (Figure SPM.4) {2.6, 6.4, 7.4, 7.6, Cross-Chapter Box 9 in Chapter 6}
B.7.1 Modelled pathways limiting global warming to 1.5ºC35 include more land-based mitigation than higher warming level
pathways (high confidence), but the impacts of climate change on land systems in these pathways are less severe (medium
confidence). (Figure SPM.2, Figure SPM.4) {2.6, 6.4, 7.4, Cross-Chapter Box 9 in Chapter 6}
B.7.2 Modelled pathways limiting global warming to 1.5°C and 2ºC project a 2 million km2 reduction to a 12 million km2 increase in
forest area in 2050 relative to 2010 (medium confidence). 3ºC pathways project lower forest areas, ranging from a 4 million
km2 reduction to a 6 million km2 increase (medium confidence). (Figure SPM.3, Figure SPM.4) {2.5, 6.3, 7.3, 7.5, Cross-Chapter
Box 9 in Chapter 6}
B.7.3 The land area needed for bioenergy in modelled pathways varies significantly depending on the socio-economic pathway, the
warming level, and the feedstock and production system used (high confidence). Modelled pathways limiting global warming
to 1.5°C use up to 7 million km2 for bioenergy in 2050; bioenergy land area is smaller in 2°C (0.4 to 5 million km2) and 3°C
pathways (0.1 to 3 million km2) (medium confidence). Pathways with large levels of land conversion may imply adverse
side-effects impacting water scarcity, biodiversity, land degradation, desertification, and food security, if not adequately and
carefully managed, whereas best practice implementation at appropriate scales can have co-benefits, such as management
of dryland salinity, enhanced biocontrol and biodiversity and enhancing soil carbon sequestration (high confidence). (Figure
SPM.3) {2.6, 6.1, 6.4, 7.2, Cross-Chapter Box 7 in Chapter 6}
35 In this report references to pathways limiting global warming to a particular level are based on a 66% probability of staying below that temperature level in 2100
using the MAGICC model.
25
SPM
Summary for Policymakers
B.7.4 Most mitigation pathways include substantial deployment of bioenergy technologies. A small number of modelled pathways
limit warming to 1.5ºC with reduced dependence on bioenergy and BECCS (land area below <1 million km2 in 2050) and other
carbon dioxide removal (CDR) options (high confidence). These pathways have even more reliance on rapid and far-reaching
transitions in energy, land, urban systems and infrastructure, and on behavioural and lifestyle changes compared to other
1.5°C pathways. {2.6.2, 5.5.1, 6.4, Cross-Chapter Box 7 in Chapter 6}
B.7.5 These modelled pathways do not consider the effects of climate change on land or CO2 fertilisation. In addition, these pathways
include only a subset of the response options assessed in this report (high confidence); the inclusion of additional response
options in models could reduce the projected need for bioenergy or CDR that increases the demand for land. {6.4.4, Cross-
Chapter Box 9 in Chapter 6}
26
SPM
Summary for Policymakers
Gt CO-eq yr¯
Million people Million km Million km Million people
Mitigation Adaptation Desertification Land Degradation Food Security
Large
Large
Variable: Can be positive or negative
Moderate
Moderate
Small
Small
Negligible
More than 3
More than -3
0.3 to 3
-0.3 to -3
Less than 0.3
No eect
Less than -0.3
Positive for
more than 25
Positive for
more than 100
Positive for
more than 3
Positive for
more than 3
Negative for
more than 25
Negative for
more than 100
Negative for
more than 3
Negative for
more than 3
1 to 25
1 to 25
Less than 1
No eect
Less than 1
1 to 100
1 to 100
Less than 1
No eect
Less than 1
0.5 to 3
0.5 to 3
Less than 0.5
No eect
Less than 0.5
0.5 to 3
0.5 to 3
Less than 0.5
No eect
Less than 0.5
Key for criteria used to define magnitude of impact of each integrated response option Confidence level
Indicates confidence in the
estimate of magnitude category.
H High confidence
M Medium confidence
L Low confidence
Cost range
See technical caption for cost
ranges in US$ tCOe or US$ ha.
High cost
Medium cost
Low cost
no data not applicable Positive Negative no data na
Response options based on land management
Increased food productivity
Agro-forestry
Improved cropland management
Improved livestock management
Agricultural diversification
Improved grazing land management
Integrated water management
Reduced grassland conversion to cropland
Forest management
Reduced deforestation and forest degradation
Increased soil organic carbon content
Reduced soil erosion
Reduced soil salinization
Reduced soil compaction
Fire management
Reduced landslides and natural hazards
Reduced pollution including acidification
Response options based on value chain management
Response options based on risk management
Restoration & reduced conversion of coastal wetlands
Restoration & reduced conversion of peatlands
Reduced post-harvest losses
Dietary change
Reduced food waste (consumer or retailer)
Sustainable sourcing
Improved food processing and retailing
Improved energy use in food systems
Livelihood diversification
Management of urban sprawl
Risk sharing instruments
Supply Demand Other ecosystems Soils Forests Agriculture
Mitigation Adaptation Desertification Land Degradation Food Security Cost
L M L M H
M M M M L
M L L L L
M L L L L
L L L M L
M L L L L
L L L L L
L L L L
M L L L L
H L L L L
H L M M L
L L M M L
L L L L
L L L
M M M M L
L L L L L
M M L L L
M L M M L
M na M L
H M L L H
H L H H
H L M M
L L L
L L L
L L L
L L L L
Risk
L L L
L L M L
Options shown are those for which data are available to assess global potential for three or more land challenges.
The magnitudes are assessed independently for each option and are not additive.
Panel A shows response options that can be implemented without or with limited competition for land, including some that have the
potential to reduce the demand for land. Co-benefits and adverse side eects are shown quantitatively based on the high end of the
range of potentials assessed. Magnitudes of contributions are categorised using thresholds for positive or negative impacts. Letters
within the cells indicate confidence in the magnitude of the impact relative to the thresholds used (see legend). Confidence in the
direction of change is generally higher.
Potential global contribution of response options to mitigation, adaptation,
combating desertification and land degradation, and enhancing food security
I I
·1•·l
l•••I
II• I
·l· I ·el
·el I ·7··l
··7
l• I I1• I
« I I I
II I
I• I I I
I I
I I I I I
I I
I I
I I I
I I
« I ··7
l la Jee]
··) B B • I• I
27
SPM
Summary for Policymakers
Panel B shows response options that rely on additional land-use change and could have implications across three or more land
challenges under di
erent implementation contexts. For each option, the first row (high level implementation) shows a quantitative
assessment (as in Panel A) of implications for global implementation at scales delivering CO removals of more than 3 GtCO yr-1 using
the magnitude thresholds shown in Panel A. The red hatched cells indicate an increasing pressure but unquantified impact. For each
option, the second row (best practice implementation) shows qualitative estimates of impact if implemented using best practices in
appropriately managed landscape systems that allow for e
icient and sustainable resource use and supported by appropriate
governance mechanisms. In these qualitative assessments, green indicates a positive impact, grey indicates a neutral interaction.
Potential global contribution of response options to mitigation, adaptation,
combating desertification and land degradation, and enhancing food security
Mitigation Adaptation Desertification Land degradation Food security Cost
Mitigation Adaptation Desertification Land degradation Food security
Bioenergy and BECCS
High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts, assuming carbon dioxide removal by BECCS at
a scale of 11.3 GtCO yr-1 in 2050, and noting that bioenergy without CCS can also achieve emissions reductions of up to several GtCO yr-1 when it is a low carbon
energy source {2.6.1; 6.3.1}. Studies linking bioenergy to food security estimate an increase in the population at risk of hunger to up to 150 million people at this level
of implementation {6.3.5}. The red hatched cells for desertification and land degradation indicate that while up to 15 million km of additional land is required in 2100
in 2°C scenarios which will increase pressure for desertification and land degradation, the actual area a
ected by this additional pressure is not easily quantified
{6.3.3; 6.3.4}.
Best practice: The sign and magnitude of the e
ects of bioenergy and BECCS depends on the scale of deployment, the type of bioenergy feedstock, which other
response options are included, and where bioenergy is grown (including prior land use and indirect land use change emissions). For example, limiting bioenergy
production to marginal lands or abandoned cropland would have negligible e
ects on biodiversity, food security, and potentially co-benefits for land degradation;
however, the benefits for mitigation could also be smaller. {Table 6.58}
Mitigation Adaptation Desertification Land degradation Food security Cost
Mitigation Adaptation Desertification Land degradation Food security
Reforestation and forest restoration
High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of reforestation and
forest restoration (partly overlapping with a
orestation) at a scale of 10.1 GtCO yr-1 removal {6.3.1}. Large-scale a
orestation could cause increases in food prices of
80% by 2050, and more general mitigation measures in the AFOLU sector can translate into a rise in undernourishment of 80–300 million people; the impact of
reforestation is lower {6.3.5}.
Best practice: There are co-benefits of reforestation and forest restoration in previously forested areas, assuming small scale deployment using native species and
involving local stakeholders to provide a safety net for food security. Examples of sustainable implementation include, but are not limited to, reducing illegal logging
and halting illegal forest loss in protected areas, reforesting and restoring forests in degraded and desertified lands {Box6.1C; Table 6.6}.
Mitigation Adaptation Desertification Land degradation Food security Cost
Mitigation Adaptation Desertification Land degradation Food security
Aorestation
High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of a
orestation
(partly overlapping with reforestation and forest restoration) at a scale of 8.9 GtCO yr-1 removal {6.3.1}. Large-scale a
orestation could cause increases in food prices of
80% by 2050, and more general mitigation measures in the AFOLU sector can translate into a rise in undernourishment of 80–300 million people {6.3.5}.
Best practice: A
orestation is used to prevent desertification and to tackle land degradation. Forested land also o
ers benefits in terms of food supply, especially when
forest is established on degraded land, mangroves, and other land that cannot be used for agriculture. For example, food from forests represents a safety-net during
times of food and income insecurity {6.3.5}.
Mitigation Adaptation Desertification Land degradation Food security Cost
Mitigation Adaptation Desertification Land degradation Food security
Biochar addition to soil
High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of biochar at a scale
of 6.6 GtCO yr-1 removal {6.3.1}. Dedicated biomass crops required for feedstock production could occupy 0.4–2.6 Mkm of land, equivalent to around 20% of the global
cropland area, which could potentially have a large e
ect on food security for up to 100 million people {6.3.5}.
Best practice: When applied to land, biochar could provide moderate benefits for food security by improving yields by 25% in the tropics, but with more limited
impacts in temperate regions, or through improved water holding capacity and nutrient use e
iciency. Abandoned cropland could be used to supply biomass for
biochar, thus avoiding competition with food production; 5-9 Mkm of land is estimated to be available for biomass production without compromising food security
and biodiversity, considering marginal and degraded land and land released by pasture intensification {6.3.5}.
H L L
M M M M M
M M M L M
M X X L L
+720010001
'----------1 1 -------
1 •Z•••I
••
••
•••
28
SPM
Summary for Policymakers
Figure SPM.3: Potential global contribution of response options to mitigation, adaptation, combating desertification and land degradation, and
enhancing food security. | This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how response options are
implemented and the contexts in which they occur. Response options implemented differently at local to global scales could lead to different outcomes. Magnitude
of potential: For panel A, magnitudes are for the technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker
level as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the largest individual impacts (~3 GtCO2-eq yr-
1). The threshold for the ‘large’ magnitude category is set at this level. For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by
climate change and a carbon-based economy between 2010 and 2030. The threshold for the ‘large’ magnitude category represents 25% of this total. For desertification
and land degradation, magnitudes are set relative to the lower end of current estimates of degraded land, 10–60 million km2. The threshold for the ‘large’ magnitude
category represents 30% of the lower estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently undernourished.
The threshold for the ‘large’ magnitude category represents 12.5% of this total. For panel B, for the first row (high level implementation) for each response option, the
magnitude and thresholds are as defined for panel A. In the second row (best practice implementation) for each response option, the qualitative assessments that are
green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food production is assumed to be achieved through sustainable
intensification rather than through injudicious application of additional external inputs such as agrochemicals. Levels of confidence: Confidence in the magnitude
category (high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land degradation, and enhancing food security.
High confidence means that there is a high level of agreement and evidence in the literature to support the categorisation as high, medium or low magnitude. Low
confidence denotes that the categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in the magnitude
of response. Cost ranges: Cost estimates are based on aggregation of often regional studies and vary in the components of costs that are included. In panel B,
cost estimates are not provided for best practice implementation. One coin indicates low cost (<USD10 tCO2-eq-1 or <USD20 ha-1), two coins indicate medium cost
(USD10-USD100 tCO2-eq-1 or USD20 –USD200 ha-1), and three coins indicate high cost (>USD100 tCO2-eq-1 or USD200 ha-1). Thresholds in USD ha-1 are chosen to be
comparable, but precise conversions will depend on the response option. Supporting evidence: Supporting evidence for the magnitude of the quantitative potential
for land management-based response options can be found as follows: for mitigation Table’s 6.13 to 6.20, with further evidence in Section 2.7.1; for adaptation Table’s
6.21 to 6.28; for combating desertification Table’s 6.29 to 6.36, with further evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence
in Chapter 4; for enhancing food security Table’s 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here are discussed in Chapter
6. Additional supporting evidence for the qualitative assessments in the second row for each option in panel B can be found in the Table’s 6.6, 6.55, 6.56 and 6.58,
Section 6.3.5.1.3, and Box 6.1c.
29
SPM
Summary for Policymakers
C. Enabling response options
C.1 Appropriate design of policies, institutions and governance systems at all scales can contribute to
land-related adaptation and mitigation while facilitating the pursuit of climate-adaptive development
pathways (high confidence). Mutually supportive climate and land policies have the potential to
save resources, amplify social resilience, support ecological restoration, and foster engagement and
collaboration between multiple stakeholders (high confidence). (Figure SPM.1, Figure SPM.2, Figure
SPM.3) {3.6.2, 3.6.3, 4.8, 4.9.4, 5.7, 6.3, 6.4, 7.2.2, 7.3, 7.4, 7.4.7, 7.4.8, 7.5, 7.5.5, 7.5.6, 7.6.6, Cross-
Chapter Box 10 in Chapter 7}
C.1.1 Land-use zoning, spatial planning, integrated landscape planning, regulations, incentives (such as payment for ecosystem
services), and voluntary or persuasive instruments (such as environmental farm planning, standards and certification for
sustainable production, use of scientific, local and indigenous knowledge and collective action), can achieve positive
adaptation and mitigation outcomes (medium confidence). They can also contribute revenue and provide incentive to
rehabilitate degraded lands and adapt to and mitigate climate change in certain contexts (medium confidence). Policies
promoting the target of land degradation neutrality can also support food security, human wellbeing and climate change
adaptation and mitigation (high confidence). (Figure SPM.2) {3.4.2, 4.1.6, 4.7, 4.8.5, 5.1.2, 5.7.3, 7.3, 7.4.6, 7.4.7, 7.5}
C.1.2 Insecure land tenure affects the ability of people, communities and organisations to make changes to land that can advance
adaptation and mitigation (medium confidence). Limited recognition of customary access to land and ownership of land can
result in increased vulnerability and decreased adaptive capacity (medium confidence). Land policies (including recognition
of customary tenure, community mapping, redistribution, decentralisation, co-management, regulation of rental markets) can
provide both security and flexibility response to climate change (medium confidence). {3.6.1, 3.6.2, 5.3, 7.2.4, 7.6.4, Cross-
Chapter Box 6 in Chapter 5}
C.1.3 Achieving land degradation neutrality will involve a balance of measures that avoid and reduce land degradation, through
adoption of sustainable land management, and measures to reverse degradation through rehabilitation and restoration of
degraded land. Many interventions to achieve land degradation neutrality commonly also deliver climate change adaptation
and mitigation benefits. The pursuit of land degradation neutrality provides impetus to address land degradation and climate
change simultaneously (high confidence). {4.5.3, 4.8.5, 4.8.7, 7.4.5}
C.1.4 Due to the complexity of challenges and the diversity of actors involved in addressing land challenges, a mix of policies,
rather than single policy approaches, can deliver improved results in addressing the complex challenges of sustainable land
management and climate change (high confidence). Policy mixes can strongly reduce the vulnerability and exposure of human
and natural systems to climate change (high confidence). Elements of such policy mixes may include weather and health
insurance, social protection and adaptive safety nets, contingent finance and reserve funds, universal access to early warning
systems combined with effective contingency plans (high confidence). (Figure SPM.4) {1.2, 4.8, 4.9.2, 5.3.2, 5.6, 5.6.6, 5.7.2,
7.3.2, 7.4, 7.4.2, 7.4.6, 7.4.7, 7.4.8, 7.5.5, 7.5.6, 7.6.4}
C.2 Policies that operate across the food system, including those that reduce food loss and waste and
influence dietary choices, enable more sustainable land-use management, enhanced food security and
low emissions trajectories (high confidence). Such policies can contribute to climate change adaptation
and mitigation, reduce land degradation, desertification and poverty as well as improve public health
(high confidence). The adoption of sustainable land management and poverty eradication can be
enabled by improving access to markets, securing land tenure, factoring environmental costs into
food, making payments for ecosystem services, and enhancing local and community collective action
(high confidence). {1.1.2, 1.2.1, 3.6.3, 4.7.1, 4.7.2, 4.8, 5.5, 6.4, 7.4.6, 7.6.5}
C.2.1 Policies that enable and incentivise sustainable land management for climate change adaptation and mitigation include
improved access to markets for inputs, outputs and financial services, empowering women and indigenous peoples, enhancing
local and community collective action, reforming subsidies and promoting an enabling trade system (high confidence). Land
restoration and rehabilitation efforts can be more effective when policies support local management of natural resources,
while strengthening cooperation between actors and institutions, including at the international level. {3.6.3, 4.1.6, 4.5.4, 4.8.2,
4.8.4, 5.7, 7.2, 7.3}
30
SPM
Summary for Policymakers
C.2.2 Reflecting the environmental costs of land-degrading agricultural practices can incentivise more sustainable land management
(high confidence). Barriers to the reflection of environmental costs arise from technical difficulties in estimating these costs
and those embodied in foods. {3.6.3, 5.5.1, 5.5.2, 5.6.6, 5.7, 7.4.4, Cross-Chapter Box 10 in Chapter 7}
C.2.3 Adaptation and enhanced resilience to extreme events impacting food systems can be facilitated by comprehensive risk
management, including risk sharing and transfer mechanisms (high confidence). Agricultural diversification, expansion of
market access, and preparation for increasing supply chain disruption can support the scaling up of adaptation in food systems
(high confidence). {5.3.2, 5.3.3, 5.3.5}
C.2.4 Public health policies to improve nutrition, such as increasing the diversity of food sources in public procurement, health
insurance, financial incentives, and awareness-raising campaigns, can potentially influence food demand, reduce healthcare
costs, contribute to lower GHG emissions and enhance adaptive capacity (high confidence). Influencing demand for food,
through promoting diets based on public health guidelines, can enable more sustainable land management and contribute to
achieving multiple SDGs (high confidence). {3.4.2, 4.7.2, 5.1, 5.7, 6.3, 6.4}
C.3 Acknowledging co-benefits and trade-offs when designing land and food policies can overcome
barriers to implementation (medium confidence). Strengthened multi-level, hybrid and cross-sectoral
governance, as well as policies developed and adopted in an iterative, coherent, adaptive and flexible
manner can maximise co-benefits and minimise trade-offs, given that land management decisions
are made from farm level to national scales, and both climate and land policies often range across
multiple sectors, departments and agencies (high confidence). (Figure SPM.3) {4.8.5, 4.9, 5.6, 6.4, 7.3,
7.4.6, 7.4.8, 7.4.9, 7.5.6, 7.6.2}
C.3.1 Addressing desertification, land degradation, and food security in an integrated, coordinated and coherent manner can assist
climate resilient development and provides numerous potential co-benefits (high confidence). {3.7.5, 4.8, 5.6, 5.7, 6.4, 7.2.2,
7.3.1, 7.3.4, 7.4.7, 7.4.8, 7.5.6, 7.5.5}
C.3.2 Technological, biophysical, socio-economic, financial and cultural barriers can limit the adoption of many land-based response
options, as can uncertainty about benefits (high confidence). Many sustainable land management practices are not widely
adopted due to insecure land tenure, lack of access to resources and agricultural advisory services, insufficient and unequal
private and public incentives, and lack of knowledge and practical experience (high confidence). Public discourse, carefully
designed policy interventions, incorporating social learning and market changes can together help reduce barriers to
implementation (medium confidence). {3.6.1, 3.6.2, 5.3.5, 5.5.2, 5.6, 6.2, 6.4, 7.4, 7.5, 7.6}
C.3.3 The land and food sectors face particular challenges of institutional fragmentation and often suffer from a lack of engagement
between stakeholders at different scales and narrowly focused policy objectives (medium confidence). Coordination with
other sectors, such as public health, transportation, environment, water, energy and infrastructure, can increase co-benefits,
such as risk reduction and improved health (medium confidence). {5.6.3, 5.7, 6.2, 6.4.4, 7.1, 7.3, 7.4.8, 7.6.2, 7.6.3}
C.3.4 Some response options and policies may result in trade-offs, including social impacts, ecosystem functions and services damage,
water depletion, or high costs, that cannot be well-managed, even with institutional best practices (medium confidence).
Addressing such trade-offs helps avoid maladaptation (medium confidence). Anticipation and evaluation of potential tradeoffs
and knowledge gaps supports evidence-based policymaking to weigh the costs and benefits of specific responses for
different stakeholders (medium confidence). Successful management of trade-offs often includes maximising stakeholder
input with structured feedback processes, particularly in community-based models, use of innovative fora like facilitated
dialogues or spatially explicit mapping, and iterative adaptive management that allows for continuous readjustments in policy
as new evidence comes to light (medium confidence). {5.3.5, 6.4.2, 6.4.4, 6.4.5, 7.5.6, Cross-Chapter Box 9 in Chapter 7}
C.4 The effectiveness of decision-making and governance is enhanced by the involvement of local
stakeholders (particularly those most vulnerable to climate change including indigenous peoples
and local communities, women, and the poor and marginalised) in the selection, evaluation,
implementation and monitoring of policy instruments for land-based climate change adaptation and
mitigation (high confidence). Integration across sectors and scales increases the chance of maximising
co-benefits and minimising trade-offs (medium confidence). {1.4, 3.1, 3.6, 3.7, 4.8, 4.9, 5.1.3, Box 5.1,
7.4, 7.6}
31
SPM
Summary for Policymakers
C.4.1 Successful implementation of sustainable land management practices requires accounting for local environmental and socioeconomic
conditions (very high confidence). Sustainable land management in the context of climate change is typically
advanced by involving all relevant stakeholders in identifying land-use pressures and impacts (such as biodiversity decline,
soil loss, over-extraction of groundwater, habitat loss, land-use change in agriculture, food production and forestry) as well as
preventing, reducing and restoring degraded land (medium confidence). {1.4.1, 4.1.6, 4.8.7, 5.2.5, 7.2.4, 7.6.2, 7.6.4}
C.4.2 Inclusiveness in the measurement, reporting and verification of the performance of policy instruments can support sustainable
land management (medium confidence). Involving stakeholders in the selection of indicators, collection of climate data,
land modelling and land-use planning, mediates and facilitates integrated landscape planning and choice of policy (medium
confidence). {3.7.5, 5.7.4, 7.4.1, 7.4.4, 7.5.3, 7.5.4, 7.5.5, 7.6.4, 7.6.6}
C.4.3 Agricultural practices that include indigenous and local knowledge can contribute to overcoming the combined challenges of
climate change, food security, biodiversity conservation, and combating desertification and land degradation (high confidence).
Coordinated action across a range of actors including businesses, producers, consumers, land managers and policymakers in
partnership with indigenous peoples and local communities enable conditions for the adoption of response options (high
confidence) {3.1.3, 3.6.1, 3.6.2, 4.8.2, 5.5.1, 5.6.4, 5.7.1, 5.7.4, 6.2, 7.3, 7.4.6, 7.6.4}
C.4.4 Empowering women can bring synergies and co-benefits to household food security and sustainable land management (high
confidence). Due to women’s disproportionate vulnerability to climate change impacts, their inclusion in land management
and tenure is constrained. Policies that can address land rights and barriers to women’s participation in sustainable land
management include financial transfers to women under the auspices of anti-poverty programmes, spending on health,
education, training and capacity building for women, subsidised credit and program dissemination through existing women’s
community-based organisations (medium confidence). {1.4.1, 4.8.2, 5.1.3, Cross-Chapter Box 11 in Chapter 7}
32
SPM
Summary for Policymakers
-10
10
7.5
5
2.5
0
-2.5
-5
-7.5
-10
10
7.5
5
2.5
0
-2.5
-5
-7.5
-10
10
7.5
5
2.5
0
-2.5
-5
-7.5
2010 2025 2050 2075 2100 2010 2025 2050 2075 2100 2010 2025 2050 2075 2100
C
P
NL
BC
F
C
P
NL
BC
C
P
NL
BC
F
F
A. Sustainability-focused (SSP1)
Sustainability in land management,
agricultural intensification, production
and consumption patterns result in
reduced need for agricultural land,
despite increases in per capita food
consumption. This land can instead be
used for reforestation, aorestation, and
bioenergy.
B. Middle of the road (SSP2 )
Societal as well as technological
development follows historical patterns.
Increased demand for land mitigation
options such as bioenergy, reduced
deforestation or aorestation decreases
availability of agricultural land for food,
feed and fibre.
Socioeconomic development and land management influence the evolution of the land system including the relative amount of land
allocated to , ,
, , and . The lines show the median across Integrated
Assessment Models (IAMs) for three alternative shared socioeconomic pathways (SSP1, SSP2 and SSP5 at RCP1.9); shaded areas show
the range across models. Note that pathways illustrate the eects of climate change mitigation but not those of climate change impacts
or adaptation.
A. Pathways linking socioeconomic development, mitigation responses and land
C. Resource intensive (SSP5)
Resource-intensive production and
consumption patterns, results in high
baseline emissions. Mitigation focuses on
technological solutions including
substantial bioenergy and BECCS .
Intensification and competing land uses
contribute to declines in agricultural land.
SSP1 Sustainability-focused
Change in Land from 2010 (Mkm)
SSP2 Middle of the road
Change in Land from 2010 (Mkm)
SSP5 Resource intensive
Change in Land from 2010 (Mkm)
• • • • •
33
SPM
Summary for Policymakers
SSP1
Change in Pasture
from 2010
Mkm
Change in Forest
from 2010
Mkm
Change in Cropland
from 2010
Mkm
Change in Bioenergy
Cropland from 2010
Mkm
Change in Natural
Land from 2010
Mkm
B. Land use and land cover change in the SSPs
0.5 ( -4.9 , 1 )
0 ( -7.3 , 7.1 )
-0.9 ( -2.2 , 1.5 )
0.2 ( -3.5 , 1.1 )
0.5 ( -1 , 1.7 )
1.8 ( -1.7 , 6 )
0.3 ( -1.1 , 1.8 )
3.3 ( -0.3 , 5.9 )
5/5
5/5
5/5
5/5
2.1 ( 0.9 , 5 )
4.3 ( 1.5 , 7.2 )
1.3 ( 0.4 , 1.9 )
5.1 ( 1.6 , 6.3 )
0.8 ( 0.5 , 1.3 )
1.9 ( 1.4 , 3.7 )
0.5 ( 0.2 , 1.4 )
1.8 ( 1.4 , 2.4 )
RCP1.9 in 2050
2100
RCP2.6 in 2050
2100
RCP4.5 in 2050
2100
Baseline in 2050
2100
-1.2 ( -4.6 , -0.3 )
-5.2 ( -7.6 , -1.8 )
-1 ( -4.7 , 1 )
-3.2 ( -7.7 , -1.8 )
0.1 ( -3.2 , 1.5 )
-2.3 ( -6.4 , -1.6 )
0.2 ( -1.6 , 1.9 )
-1.5 ( -5.7 , -0.9 )
3.4 ( -0.1 , 9.4 )
7.5 ( 0.4 , 15.8 )
2.6 ( -0.1 , 8.4 )
6.6 ( -0.1 , 10.5 )
0.6 ( -0.7 , 4.2 )
3.9 ( 0.2 , 8.8 )
-0.1 ( -0.8 , 1.1 )
0.9 ( 0.3 , 3 )
-4.1 ( -5.6 , -2.5 )
-6.5 ( -12.2 , -4.8 )
-3 ( -4 , -2.4 )
-5.5 ( -9.9 , -4.2 )
-2.4 ( -3.3 , -0.9 )
-4.6 ( -7.3 , -2.7 )
-1.5 ( -2.9 , -0.2 )
-2.1 ( -7 , 0 )
Quantitative indicators
for the SSPs
Count of
models
included*
SSP2
-2.2 ( -7 , 0.6 )
-2.3 ( -9.6 , 2.7 )
-3.2 ( -4.2 , 0.1 )
-5.2 ( -7.2 , 0.5 )
-2.2 ( -2.2 , 0.7 )
-3.4 ( -4.7 , 1.5 )
-1.5 ( -2.6 , -0.2 )
-2.1 ( -5.9 , 0.3 )
4/5
5/5
5/5
5/5
4.5 ( 2.1 , 7 )
6.6 ( 3.6 , 11 )
2.2 ( 1.7 , 4.7 )
6.9 ( 2.3 , 10.8 )
1.5 ( 0.1 , 2.1 )
4.1 ( 0.4 , 6.3 )
0.7 ( 0 , 1.5 )
1.2 ( 0.1 , 2.4 )
RCP1.9 in 2050
2100
RCP2.6 in 2050
2100
RCP4.5 in 2050
2100
Baseline in 2050
2100
-1.2 ( -2 , 0.3 )
-2.9 ( -4 , 0.1 )
0.6 ( -1.9 , 1.9 )
-1.4 ( -4 , 0.8 )
1.2 ( -0.9 , 2.7 )
0.7 ( -2.6 , 3.1 )
1.3 ( 1 , 2.7 )
1.9 ( 0.8 , 2.8 )
3.4 ( -0.9 , 7 )
6.4 ( -0.8 , 9.5 )
1.6 ( -0.9 , 4.2 )
5.6 ( -0.9 , 5.9 )
-0.9 ( -2.5 , 2.9 )
-0.5 ( -3.1 , 5.9 )
-1.3 ( -2.5 , -0.4 )
-1.3 ( -2.7 , -0.2 )
-4.8 ( -6.2 , -0.4 )
-7.6 ( -11.7 , -1.3 )
-1.4 ( -3.7 , 0.4 )
-7.2 ( -8 , 0.5 )
-0.1 ( -2.5 , 1.6 )
-2.8 ( -5.3 , 1.9 )
-0.1 ( -1.2 , 1.6 )
-0.2 ( -1.9 , 2.1 )
SSP3
-3.4 ( -4.4 , -2 )
-6.2 ( -6.8 , -5.4 )
-3 ( -4.6 , -1.7 )
-5 ( -7.1 , -4.2 )
3/3
4/4
-
-
-
-
1.3 ( 1.3 , 2 )
4.6 ( 1.5 , 7.1 )
1 ( 0.2 , 1.5 )
1.1 ( 0.9 , 2.5 )
RCP1.9 in 2050
2100
RCP2.6 in 2050
2100
RCP4.5 in 2050
2100
Baseline in 2050
2100
-
-
-
-
2.3 ( 1.2 , 3 )
3.4 ( 1.9 , 4.5 )
2.5 ( 1.5 , 3 )
5.1 ( 3.8 , 6.1 )
-
-
-
-
-2.4 ( -4 , -1 )
-3.1 ( -5.5 , -0.3 )
-2.5 ( -4 , -1.5 )
-5.3 ( -6 , -2.6 )
-
-
-
-
2.1 ( -0.1 , 3.8 )
2 ( -2.5 , 4.4 )
2.4 ( 0.6 , 3.8 )
3.4 ( 0.9 , 6.4 )
SSP4
-4.5 ( -6 , -2.1 )
-5.8 ( -10.2 , -4.7 )
-2.7 ( -4.4 , -0.4 )
-2.8 ( -7.8 , -2 )
-2.8 ( -2.9 , -0.2 )
-2.4 ( -5 , -1 )
3/3
3/3
3/3
-
-
3.3 ( 1.5 , 4.5 )
2.5 ( 2.3 , 15.2 )
1.7 ( 1 , 1.9 )
2.7 ( 2.3 , 4.7 )
1.1 ( 0.7 , 2 )
1.7 ( 1.4 , 2.6 )
RCP1.9 in 2050
2100
RCP2.6 in 2050
2100
RCP4.5 in 2050
2100
Baseline in 2050
2100
-
-
0.5 ( -0.1 , 0.9 )
-0.8 ( -0.8 , 1.8 )
1.1 ( -0.1 , 1.7 )
1.1 ( 0.2 , 1.2 )
1.1 ( 0.7 , 1.8 )
1.2 ( 1.2 , 1.9 )
-
-
0.7 ( -0.3 , 2.2 )
1.4 ( -1.7 , 4.1 )
-1.8 ( -2.3 , 2.1 )
-0.7 ( -2.6 , 1 )
-1.8 ( -2.3 , -1 )
-2.4 ( -2.5 , -2 )
-
-
-0.6 ( -0.7 , 0.1 )
-1.2 ( -2.5 , -0.2 )
0.8 ( -0.5 , 1.5 )
1.4 ( -1 , 1.8 )
1.5 ( -0.5 , 2.1 )
1.3 ( -1 , 4.4 )
SSP5
-1.5 ( -3.9 , 0.9 )
-0.5 ( -4.2 , 3.2 )
-3.4 ( -6.9 , 0.3 )
-4.3 ( -8.4 , 0.5 )
-2.5 ( -3.7 , 0.2 )
-4.1 ( -4.6 , 0.7 )
-0.6 ( -3.8 , 0.4 )
-0.2 ( -2.4 , 1.8 )
2/4
4/4
4/4
4/4
6.7 ( 6.2 , 7.2 )
7.6 ( 7.2 , 8 )
4.8 ( 3.8 , 5.1 )
9.1 ( 7.7 , 9.2 )
1.7 ( 0.6 , 2.9 )
4.8 ( 2 , 8 )
0.8 ( 0 , 2.1 )
1 ( 0.2 , 2.3 )
RCP1.9 in 2050
2100
RCP2.6 in 2050
2100
RCP4.5 in 2050
2100
Baseline in 2050
2100
-1.9 ( -3.5 , -0.4 )
-3.4 ( -6.2 , -0.5 )
-2.1 ( -4 , 1 )
-3.3 ( -6.5 , -0.5 )
0.6 ( -3.3 , 1.9 )
-1 ( -5.5 , 1 )
1.5 ( -0.7 , 3.3 )
1 ( -2 , 2.5 )
3.1 ( -0.1 , 6.3 )
4.7 ( 0.1 , 9.4 )
3.9 ( -0.1 , 6.7 )
3.9 ( -0.1 , 9.3 )
-0.1 ( -1.7 , 6 )
-0.2 ( -1.4 , 9.1 )
-1.9 ( -3.4 , 0.5 )
-2.1 ( -3.4 , 1.1 )
-6.4 ( -7.7 , -5.1 )
-8.5 ( -10.7 , -6.2 )
-4.4 ( -5 , 0.2 )
-6.3 ( -9.1 , -1.4 )
-1.2 ( -2.6 , 2.3 )
-3 ( -5.2 , 2.1 )
-0.1 ( -1.5 , 2.9 )
-0.4 ( -2.4 , 2.8 )
Infeasible in all assessed models
* Count of models included / Count of models attempted. One model did not provide land data and is excluded from all entries.
** One model could reach RCP1.9 with SSP4, but did not provide land data
Infeasible in all assessed models
Infeasible in all assessed models**
»
»
»
»
l,
L,
»
l,
l,
l,
l,
l,
»
»
l,
»
L,
»
»
L,
34
SPM
Summary for Policymakers
Figure SPM.4: Pathways linking socioeconomic development, mitigation responses and land | Future scenarios provide a framework for understanding the
implications of mitigation and socioeconomics on land. The Shared Socioeconomic Pathways (SSPs) span a range of different socioeconomic assumptions (Box SPM.1).
They are combined with Representative Concentration Pathways (RCPs)36 which imply different levels of mitigation. The changes in cropland, pasture, bioenergy cropland,
forest, and natural land from 2010 are shown. For this Figure, Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area).
This category includes first generation non-forest bioenergy crops (e.g., corn for ethanol, sugar cane for ethanol, soybeans for biodiesel), but excludes second generation
bioenergy crops. Pasture includes categories of pasture land, not only high-quality rangeland, and is based on FAO definition of ‘permanent meadows and pastures’.
Bioenergy cropland includes land dedicated to second generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest includes managed and
unmanaged forest. Natural land includes other grassland, savannah, and shrubland. Panel A: This panel shows integrated assessment model (IAM)37 results for SSP1,
SSP2 and SSP5 at RCP1.9.38 For each pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9, SSP1, SSP2
and SSP5 results are from five, four and two IAMs respectively. Panel B: Land use and land cover change are indicated for various SSP-RCP combinations, showing
multi-model median and range (min, max). (Box SPM.1) {1.3.2, 2.7.2, 6.1, 6.4.4, 7.4.2, 7.4.4, 7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6, Cross-Chapter Box 1 in Chapter
1, Cross-Chapter Box 9 in Chapter 6}
36 Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and concentrations of the full suite of greenhouse gases (GHGs)
and aerosols and chemically active gases, as well as land use/land cover.
37 Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In this figure, IAMs are used to assess linkages
between economic, social and technological development and the evolution of the climate system.
38 The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5°C in 2100, but some of these pathways overshoot 1.5°C of warming
during the 21st century by >0.1°C.
35
SPM
Summary for Policymakers
D. Action in the near-term
D.1 Actions can be taken in the near-term, based on existing knowledge, to address desertification, land
degradation and food security while supporting longer-term responses that enable adaptation and
mitigation to climate change. These include actions to build individual and institutional capacity,
accelerate knowledge transfer, enhance technology transfer and deployment, enable financial
mechanisms, implement early warning systems, undertake risk management and address gaps in
implementation and upscaling (high confidence). {3.6.1, 3.6.2, 3.7.2, 4.8, 5.3.3, 5.5, 5.6.4, 5.7, 6.2, 6.4,
7.3, 7.4, 7.6, Cross-Chapter Box 10 in Chapter 7}
D.1.1 Near-term capacity-building, technology transfer and deployment, and enabling financial mechanisms can strengthen
adaptation and mitigation in the land sector. Knowledge and technology transfer can help enhance the sustainable use of
natural resources for food security under a changing climate (medium confidence). Raising awareness, capacity building
and education about sustainable land management practices, agricultural extension and advisory services, and expansion of
access to agricultural services to producers and land users can effectively address land degradation (medium confidence). {3.1,
5.7.4, 7.2, 7.3.4, 7.5.4}
D.1.2 Measuring and monitoring land use change including land degradation and desertification is supported by the expanded use of
new information and communication technologies (cell phone based applications, cloud-based services, ground sensors, drone
imagery), use of climate services, and remotely sensed land and climate information on land resources (medium confidence).
Early warning systems for extreme weather and climate events are critical for protecting lives and property and enhancing
disaster risk reduction and management (high confidence). Seasonal forecasts and early warning systems are critical for
food security (famine) and biodiversity monitoring including pests and diseases and adaptive climate risk management (high
confidence). There are high returns on investments in human and institutional capacities. These investments include access
to observation and early warning systems, and other services derived from in-situ hydro-meteorological and remote sensingbased
monitoring systems and data, field observation, inventory and survey, and expanded use of digital technologies (high
confidence). {1.2, 3.6.2, 4.2.2, 4.2.4, 5.3.1, 5.3.6, 6.4, 7.3.4, 7.4.3, 7.5.4, 7.5.5, 7.6.4, Cross-Chapter Box 5 in Chapter 3}
D.1.3 Framing land management in terms of risk management, specific to land, can play an important role in adaptation through
landscape approaches, biological control of outbreaks of pests and diseases, and improving risk sharing and transfer
mechanisms (high confidence). Providing information on climate-related risk can improve the capacity of land managers and
enable timely decision making (high confidence). {5.3.2, 5.3.5, 5.6.2, 5.6.3 5.6.5, 5.7.1, 5.7.2, 7.2.4, Cross-Chapter Box 6 in
Chapter 5}
D.1.4 Sustainable land management can be improved by increasing the availability and accessibility of data and information
relating to the effectiveness, co-benefits and risks of emerging response options and increasing the efficiency of land use
(high confidence). Some response options (e.g., improved soil carbon management) have been implemented only at smallscale
demonstration facilities and knowledge, financial, and institutional gaps and challenges exist with upscaling and the
widespread deployment of these options (medium confidence). {4.8, 5.5.1, 5.5.2, 5.6.1, 5.6.5, 5.7.5, 6.2, 6.4}
D.2 Near-term action to address climate change adaptation and mitigation, desertification, land
degradation and food security can bring social, ecological, economic and development co-benefits
(high confidence). Co-benefits can contribute to poverty eradication and more resilient livelihoods
for those who are vulnerable (high confidence). {3.4.2, 5.7, 7.5}
D.2.1 Near-term actions to promote sustainable land management will help reduce land and food-related vulnerabilities, and can
create more resilient livelihoods, reduce land degradation and desertification, and loss of biodiversity (high confidence). There
are synergies between sustainable land management, poverty eradication efforts, access to market, non-market mechanisms
and the elimination of low-productivity practices. Maximising these synergies can lead to adaptation, mitigation, and
development co-benefits through preserving ecosystem functions and services (medium confidence). {3.4.2, 3.6.3, Table 4.2,
4.7, 4.9, 4.10, 5.6, 5.7, 7.3, 7.4, 7.5, 7.6, Cross-Chapter Box 12 in Chapter 7}
D.2.2 Investments in land restoration can result in global benefits and in drylands can have benefit-cost ratios of between three
and six in terms of the estimated economic value of restored ecosystem services (medium confidence). Many sustainable
land management technologies and practices are profitable within three to ten years (medium confidence). While they can
36
SPM
Summary for Policymakers
require upfront investment, actions to ensure sustainable land management can improve crop yields and the economic value
of pasture. Land restoration and rehabilitation measures improve livelihood systems and provide both short-term positive
economic returns and longer-term benefits in terms of climate change adaptation and mitigation, biodiversity and enhanced
ecosystem functions and services (high confidence). {3.6.1, 3.6.3, 4.8.1, 7.2.4, 7.2.3, 7.3.1, 7.4.6, Cross-Chapter Box 10 in
Chapter 7}
D.2.3 Upfront investments in sustainable land management practices and technologies can range from about USD20 ha-1 to
USD5000 ha-1, with a median estimated to be around USD500 ha-1. Government support and improved access to credit can
help overcome barriers to adoption, especially those faced by poor smallholder farmers (high confidence). Near-term change
to balanced diets (SPM B6.2.) can reduce the pressure on land and provide significant health co-benefits through improving
nutrition (medium confidence). {3.6.3, 4.8, 5.3, 5.5, 5.6, 5.7, 6.4, 7.4.7, 7.5.5, Cross-Chapter Box 9 in Chapter 6}
D.3 Rapid reductions in anthropogenic GHG emissions across all sectors following ambitious mitigation
pathways reduce negative impacts of climate change on land ecosystems and food systems (medium
confidence). Delaying climate mitigation and adaptation responses across sectors would lead to
increasingly negative impacts on land and reduce the prospect of sustainable development (medium
confidence). (Box SPM.1, Figure SPM.2) {2.5, 2.7, 5.2, 6.2, 6.4, 7.2, 7.3.1, 7.4.7, 7.4.8, 7.5.6, Cross-Chapter
Box 9 in Chapter 6, Cross-Chapter Box 10 in Chapter 7}
D.3.1 Delayed action across sectors leads to an increasing need for widespread deployment of land-based adaptation and mitigation
options and can result in a decreasing potential for the array of these options in most regions of the world and limit their
current and future effectiveness (high confidence). Acting now may avert or reduce risks and losses, and generate benefits to
society (medium confidence). Prompt action on climate mitigation and adaptation aligned with sustainable land management
and sustainable development depending on the region could reduce the risk to millions of people from climate extremes,
desertification, land degradation and food and livelihood insecurity (high confidence). {1.3.5, 3.4.2, 3.5.2, 4.1.6, 4.7.1, 4.7.2,
5.2.3, 5.3.1, 6.3, 6.5, 7.3.1}
D.3.2 In future scenarios, deferral of GHG emissions reductions implies trade-offs leading to significantly higher costs and risks
associated with rising temperatures (medium confidence). The potential for some response options, such as increasing soil
organic carbon, decreases as climate change intensifies, as soils have reduced capacity to act as sinks for carbon sequestration
at higher temperatures (high confidence). Delays in avoiding or reducing land degradation and promoting positive ecosystem
restoration risk long-term impacts including rapid declines in productivity of agriculture and rangelands, permafrost
degradation and difficulties in peatland rewetting (medium confidence). {1.3.1, 3.6.2, 4.8, 4.9, 4.9.1, 5.5.2, 6.3, 6.4, 7.2, 7.3;
Cross-Chapter Box 10 in Chapter 7}
D.3.3 Deferral of GHG emissions reductions from all sectors implies trade-offs including irreversible loss in land ecosystem functions
and services required for food, health, habitable settlements and production, leading to increasingly significant economic
impacts on many countries in many regions of the world (high confidence). Delaying action as is assumed in high emissions
scenarios could result in some irreversible impacts on some ecosystems, which in the longer-term has the potential to lead to
substantial additional GHG emissions from ecosystems that would accelerate global warming (medium confidence). {1.3.1,
2.5.3, 2.7, 3.6.2, 4.9, 4.10.1, 5.4.2.4, 6.3, 6.4, 7.2, 7.3, Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 10 in Chapter 7}
Summary for
Policymakers
SPM
3
Summary
for Policymakers
Drafting Authors:
Nerilie Abram (Australia), Carolina Adler (Switzerland/Australia), Nathaniel L. Bindoff (Australia),
Lijing Cheng (China), So-Min Cheong (Republic of Korea), William W. L. Cheung (Canada),
Matthew Collins (UK), Chris Derksen (Canada), Alexey Ekaykin (Russian Federation), Thomas
Frölicher (Switzerland), Matthias Garschagen (Germany), Jean-Pierre Gattuso (France), Bruce
Glavovic (New Zealand), Stephan Gruber (Canada/Germany), Valeria Guinder (Argentina),
Robert Hallberg (USA), Sherilee Harper (Canada), Nathalie Hilmi (Monaco/France), Jochen Hinkel
(Germany), Yukiko Hirabayashi (Japan), Regine Hock (USA), Anne Hollowed (USA), Helene Jacot
Des Combes (Fiji), James Kairo (Kenya), Alexandre K. Magnan (France), Valérie Masson-Delmotte
(France), J.B. Robin Matthews (UK), Kathleen McInnes (Australia), Michael Meredith (UK),
Katja Mintenbeck (Germany), Samuel Morin (France), Andrew Okem (South Africa/Nigeria),
Michael Oppenheimer (USA), Ben Orlove (USA), Jan Petzold (Germany), Anna Pirani (Italy), Elvira
Poloczanska (UK/Australia), Hans-Otto Pörtner (Germany), Anjal Prakash (Nepal/India), Golam
Rasul (Nepal), Evelia Rivera-Arriaga (Mexico), Debra C. Roberts (South Africa), Edward A.G. Schuur
(USA), Zita Sebesvari (Hungary/Germany), Martin Sommerkorn (Norway/Germany), Michael
Sutherland (Trinidad and Tobago), Alessandro Tagliabue (UK), Roderik Van De Wal (Netherlands),
Phil Williamson (UK), Rong Yu (China), Panmao Zhai (China)
Draft Contributing Authors:
Andrés Alegría (Honduras), Robert M. DeConto (USA), Andreas Fischlin (Switzerland),
Shengping He (Norway/China), Miriam Jackson (Norway), Martin Künsting (Germany),
Erwin Lambert (Netherlands), Pierre-Marie Lefeuvre (Norway/France), Alexander Milner (UK),
Jess Melbourne-Thomas (Australia), Benoit Meyssignac (France), Maike Nicolai (Germany),
Hamish Pritchard (UK), Heidi Steltzer (USA), Nora M. Weyer (Germany)
This Summary for Policymakers should be cited as:
IPCC, 2019: Summary for Policymakers. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate
[H.-O. Pörtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría,
M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. Cambridge University Press, Cambridge, UK and
New York, NY, USA, pp. 3–35. https://doi.org/10.1017/9781009157964.001.
4
SPM
Summary for Policymakers
Introduction
This Special Report on the Ocean and Cryosphere1 in a Changing Climate (SROCC) was prepared following an IPCC Panel
decision in 2016 to prepare three Special Reports during the Sixth Assessment Cycle2. By assessing new scientific literature3,
the SROCC4 responds to government and observer organization proposals. The SROCC follows the other two Special Reports
on Global Warming of 1.5ºC (SR1.5) and on Climate Change and Land (SRCCL)5 and the Intergovernmental Science Policy
Platform on Biodiversity and Ecosystem Services (IPBES) Global Assessment Report on Biodiversity and Ecosystem Services.
This Summary for Policymakers (SPM) compiles key findings of the report and is structured in three parts: SPM.A: Observed
Changes and Impacts, SPM.B: Projected Changes and Risks, and SPM.C: Implementing Responses to Ocean and Cryosphere
Change. To assist navigation of the SPM, icons indicate where content can be found. Confidence in key findings is reported
using IPCC calibrated language6 and the underlying scientific basis for each key finding is indicated by references to sections
of the underlying report.
Key of icons to indicate content
High mountain cryosphere
Polar regions
Coasts and sea level rise
Ocean
1 The cryosphere is defined in this report (Annex I: Glossary) as the components of the Earth System at and below the land and ocean surface that are
frozen, including snow cover, glaciers, ice sheets, ice shelves, icebergs, sea ice, lake ice, river ice, permafrost, and seasonally frozen ground.
2 The decision to prepare a Special Report on Climate Change and Oceans and the Cryosphere was made at the Forty-Third Session of the IPCC in
Nairobi, Kenya, 11–13 April 2016.
3 Cut-off dates: 15 October 2018 for manuscript submission, 15 May 2019 for acceptance for publication.
4 The SROCC is produced under the scientific leadership of Working Group I and Working Group II. In line with the approved outline, mitigation options
(Working Group III) are not assessed with the exception of the mitigation potential of blue carbon (coastal ecosystems).
5 The full titles of these two Special Reports are: “Global Warming of 1.5ºC. An IPCC special report on the impacts of global warming of 1.5ºC above
pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of
climate change, sustainable development, and efforts to eradicate poverty”; “Climate Change and Land: an IPCC special report on climate change,
desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems”.
6 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low,
medium, high and very high, and typeset in italics, e.g., medium confidence. The following terms have been used to indicate the assessed likelihood of
an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%,
very unlikely 0–10%, exceptionally unlikely 0–1%. Assessed likelihood is typeset in italics, e.g., very likely. This is consistent with AR5 and the other
AR6 Special Reports. Additional terms (extremely likely 95–100%, more likely than not >50–100%, more unlikely than likely 0–<50%, extremely
unlikely 0–5%) are used when appropriate. This Report also uses the term ‘likely range’ or ‘very likely range’ to indicate that the assessed likelihood
of an outcome lies within the 17–83% or 5–95% probability range. {1.9.2, Figure 1.4}
5
SPM
Summary for Policymakers
Startup Box | The Importance of the Ocean and Cryosphere for People
7 High mountain areas include all mountain regions where glaciers, snow or permafrost are prominent features of the landscape. For a list of high
mountain regions covered in this report, see Chapter 2. Population in high mountain regions is calculated for areas less than 100 kilometres from
glaciers or permafrost in high mountain areas assessed in this report. {2.1} Projections for 2050 give the range of population in these regions across
all five of the Shared Socioeconomic Pathways. {Cross-Chapter Box 1 in Chapter 1}
8 Population in the low elevation coastal zone is calculated for land areas connected to the coast, including small island states, that are less than
10 metres above sea level. {Cross-Chapter Box 9} Projections for 2050 give the range of population in these regions across all five of the Shared
Socioeconomic Pathways. {Cross-Chapter Box 1 in Chapter 1}
All people on Earth depend directly or indirectly on the ocean and cryosphere. The global ocean covers 71% of the
Earth surface and contains about 97% of the Earth’s water. The cryosphere refers to frozen components of the Earth
system1. Around 10% of Earth’s land area is covered by glaciers or ice sheets. The ocean and cryosphere support
unique habitats, and are interconnected with other components of the climate system through global exchange of
water, energy and carbon. The projected responses of the ocean and cryosphere to past and current human-induced
greenhouse gas emissions and ongoing global warming include climate feedbacks, changes over decades to millennia
that cannot be avoided, thresholds of abrupt change, and irreversibility. {Box 1.1, 1.2}
Human communities in close connection with coastal environments, small islands (including Small Island Developing
States, SIDS), polar areas and high mountains7 are particularly exposed to ocean and cryosphere change, such as sea
level rise, extreme sea level and shrinking cryosphere. Other communities further from the coast are also exposed to
changes in the ocean, such as through extreme weather events. Today, around 4 million people live permanently in
the Arctic region, of whom 10% are Indigenous. The low-lying coastal zone8 is currently home to around 680 million
people (nearly 10% of the 2010 global population), projected to reach more than one billion by 2050. SIDS are home
to 65 million people. Around 670 million people (nearly 10% of the 2010 global population), including Indigenous
peoples, live in high mountain regions in all continents except Antarctica. In high mountain regions, population is
projected to reach between 740 and 840 million by 2050 (about 8.4–8.7% of the projected global population).
{1.1, 2.1, 3.1, Cross-Chapter Box 9, Figure 2.1}
In addition to their role within the climate system, such as the uptake and redistribution of natural and anthropogenic
carbon dioxide (CO2) and heat, as well as ecosystem support, services provided to people by the ocean and/or
cryosphere include food and water supply, renewable energy, and benefits for health and well-being, cultural values,
tourism, trade, and transport. The state of the ocean and cryosphere interacts with each aspect of sustainability
reflected in the United Nations Sustainable Development Goals (SDGs). {1.1, 1.2, 1.5}
6
SPM
Summary for Policymakers
A. Observed Changes and Impacts
Observed Physical Changes
A.1 Over the last decades, global warming has led to widespread shrinking of the cryosphere,
with mass loss from ice sheets and glaciers (very high confidence), reductions in snow cover
(high confidence) and Arctic sea ice extent and thickness (very high confidence), and increased
permafrost temperature (very high confidence). {2.2, 3.2, 3.3, 3.4, Figures SPM.1, SPM.2}
A.1.1 Ice sheets and glaciers worldwide have lost mass (very high confidence). Between 2006 and
2015, the Greenland Ice Sheet9 lost ice mass at an average rate of 278 ± 11 Gt yr–1 (equivalent to 0.77 ± 0.03 mm yr–1 of
global sea level rise)10, mostly due to surface melting (high confidence). In 2006–2015, the Antarctic Ice Sheet lost
mass at an average rate of 155 ± 19 Gt yr–1 (0.43 ± 0.05 mm yr–1), mostly due to rapid thinning and retreat of major
outlet glaciers draining the West Antarctic Ice Sheet (very high confidence). Glaciers worldwide outside Greenland
and Antarctica lost mass at an average rate of 220 ± 30 Gt yr–1 (equivalent to 0.61 ± 0.08 mm yr–1 sea level rise) in
2006–2015. {3.3.1, 4.2.3, Appendix 2.A, Figure SPM.1}
A.1.2 Arctic June snow cover extent on land declined by 13.4 ± 5.4% per decade from 1967
to 2018, a total loss of approximately 2.5 million km2, predominantly due to surface air temperature increase
(high confidence). In nearly all high mountain areas, the depth, extent and duration of snow cover have declined over
recent decades, especially at lower elevation (high confidence). {2.2.2, 3.4.1, Figure SPM.1}
A.1.3 Permafrost temperatures have increased to record high levels (1980s–present)
(very high confidence) including the recent increase by 0.29ºC ± 0.12ºC from 2007 to 2016 averaged across polar
and high mountain regions globally. Arctic and boreal permafrost contain 1460–1600 Gt organic carbon, almost twice
the carbon in the atmosphere (medium confidence). There is medium evidence with low agreement whether northern
permafrost regions are currently releasing additional net methane and CO2 due to thaw. Permafrost thaw and glacier
retreat have decreased the stability of high mountain slopes (high confidence). {2.2.4, 2.3.2, 3.4.1, 3.4.3, Figure SPM.1}
A.1.4 Between 1979 and 2018, Arctic sea ice extent has very likely decreased for all months of the
year. September sea ice reductions are very likely 12.8 ± 2.3% per decade. These sea ice changes in September are
likely unprecedented for at least 1000 years. Arctic sea ice has thinned, concurrent with a transition to younger ice:
between 1979 and 2018, the areal proportion of multi-year ice at least five years old has declined by approximately
90% (very high confidence). Feedbacks from the loss of summer sea ice and spring snow cover on land have
contributed to amplified warming in the Arctic (high confidence) where surface air temperature likely increased
by more than double the global average over the last two decades. Changes in Arctic sea ice have the potential to
influence mid-latitude weather (medium confidence), but there is low confidence in the detection of this influence
for specific weather types. Antarctic sea ice extent overall has had no statistically significant trend (1979–2018) due
to contrasting regional signals and large interannual variability (high confidence). {3.2.1, 6.3.1, Box 3.1, Box 3.2,
SPM A.1.2, Figures SPM.1, SPM.2}
9 Including peripheral glaciers.
10 360 Gt ice corresponds to 1 mm of global mean sea level.
■
■
7
SPM
Summary for Policymakers
high acidity
low acidity
Historical changes (observed and modelled) and projections under RCP2.6 and RCP8.5 for key indicators
Historical (observed) Historical (modelled) Projected (RCP2.6) Projected (RCP8.5)
−1
0
1
2
3
4
5 (a) Global mean surface air temperature
change relative to 1986−2005
−6
−4
−2
0
2
(i) Ocean oxygen (100−600 m depth)
%
(j) Arctic sea ice extent
(September)
%
1950 2000 2050 2100
(l) Near−surface permafrost area
year
1950 2000 2050 2100
year
ºC
%
Past and future changes in the ocean and cryosphere
change relative to 1986−2005
change relative to 1986−2005
change relative to 1986−2005
year
−1
0
1
2
3
4
5 (b) Global mean sea surface temperature
ºC
change relative to 1986−2005
0 1
5
10
15
20 (c) Marine heatwave days
multiplication factor
factor of change relative to 1986−2005
7.8
7.9
8.0
8.1
pH
(h) Surface ocean pH
0
0.1
0.2
0.3
metres
0
800
1600
2400
(d) Ocean heat content (0−2000 m depth)
1021 Joules
and sea level equivalent (right axis)
change relative to 1986−2005
0
0.1
0.2
0.3
(e) Greenland ice sheet mass loss
as sea level equivalent,
metres
0
0.1
0.2
0.3
(f) Antarctic ice sheet mass loss
as sea level equivalent,
metres
1950 2000 2050 2100
0
0.1
0.2
0.3
(g) Glacier mass loss
as sea level equivalent,
metres
year
change relative to 1986−2005
change relative to 1986−2005
change relative to 1986−2005
1950
metres
*
*
2000 2050 2100 2150 2200 2250 2300
0
1
2
3
4
5
primary drivers
(m) Global mean sea level
change relative to 1986−2005
−100
−50
0
50
−100
−50
0
50
100
−100
−50
0
50
(k) Arctic snow cover extent (June)
%
change relative to 1986−2005
0.43 m
0.84 m
Figure SPM.1 | Observed and modelled historical changes in the ocean and cryosphere since 195011, and projected future changes under low
(RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios. {Box SPM.1}
11 This does not imply that the changes started in 1950. Changes in some variables have occurred since the pre-industrial period.
7
- -
t=-:::;=_=:.-:::_::_-::_-=,-=;:-=--::=--=-=-d-
-------------------------------
lmH
8
SPM
Summary for Policymakers
Figure SPM.1 (continued): Changes are shown for: (a) Global mean surface air temperature change with likely range. {Box SPM.1, Cross-Chapter
Box 1 in Chapter 1} Ocean-related changes with very likely ranges for (b) Global mean sea surface temperature change {Box 5.1, 5.2.2}; (c)
Change factor in surface ocean marine heatwave days {6.4.1}; (d) Global ocean heat content change (0–2000 m depth). An approximate steric sea
level equivalent is shown with the right axis by multiplying the ocean heat content by the global-mean thermal expansion coefficient (ε ≈ 0.125 m per
1024 Joules)12 for observed warming since 1970 {Figure 5.1}; (h) Global mean surface pH (on the total scale). Assessed observational trends are
compiled from open ocean time series sites longer than 15 years {Box 5.1, Figure 5.6, 5.2.2}; and (i) Global mean ocean oxygen change (100–600
m depth). Assessed observational trends span 1970–2010 centered on 1996 {Figure 5.8, 5.2.2}. Sea level changes with likely ranges for (m) Global
mean sea level change. Hashed shading reflects low confidence in sea level projections beyond 2100 and bars at 2300 reflect expert elicitation on the
range of possible sea level change {4.2.3, Figure 4.2}; and components from (e,f) Greenland and Antarctic ice sheet mass loss {3.3.1}; and (g) Glacier
mass loss {Cross-Chapter Box 6 in Chapter 2, Table 4.1}. Further cryosphere-related changes with very likely ranges for (j) Arctic sea ice extent
change for September13 {3.2.1, 3.2.2 Figure 3.3}; (k) Arctic snow cover change for June (land areas north of 60ºN) {3.4.1, 3.4.2, Figure 3.10}; and
(l) Change in near-surface (within 3–4 m) permafrost area in the Northern Hemisphere {3.4.1, 3.4.2, Figure 3.10}. Assessments of projected changes
under the intermediate RCP4.5 and RCP6.0 scenarios are not available for all variables considered here, but where available can be found in the
underlying report. {For RCP4.5 see: 2.2.2, Cross-Chapter Box 6 in Chapter 2, 3.2.2, 3.4.2, 4.2.3, for RCP6.0 see Cross-Chapter Box 1 in Chapter 1}
Box SPM.1 | Use of Climate Change Scenarios in SROCC
12 This scaling factor (global-mean ocean expansion as sea level rise in metres per unit heat) varies by about 10% between different models, and it will
systematically increase by about 10% by 2100 under RCP8.5 forcing due to ocean warming increasing the average thermal expansion coefficient.
{4.2.1, 4.2.2, 5.2.2}
13 Antarctic sea ice is not shown here due to low confidence in future projections. {3.2.2}
14 CMIP5 is Phase 5 of the Coupled Model Intercomparison Project (Annex I: Glossary).
15 A pathway with lower emissions (RCP1.9), which would correspond to a lower level of projected warming than RCP2.6, was not part of CMIP5.
16 In some instances this report assesses changes relative to 2006–2015. The warming from the 1850–1900 period until 2006–2015 has been assessed
as 0.87ºC (0.75 to 0.99ºC likely range). {Cross-Chapter Box 1 in Chapter 1}
Assessments of projected future changes in this report are based largely on CMIP514 climate model projections using
Representative Concentration Pathways (RCPs). RCPs are scenarios that include time series of emissions
and concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as
land use / land cover. RCPs provide only one set of many possible scenarios that would lead to different levels of
global warming. {Annex I: Glossary}
This report uses mainly RCP2.6 and RCP8.5 in its assessment, reflecting the available literature. RCP2.6 represents
a low greenhouse gas emissions, high mitigation future, that in CMIP5 simulations gives a two in three chance of
limiting global warming to below 2ºC by 210015. By contrast, RCP8.5 is a high greenhouse gas emissions scenario
in the absence of policies to combat climate change, leading to continued and sustained growth in atmospheric
greenhouse gas concentrations. Compared to the total set of RCPs, RCP8.5 corresponds to the pathway with the
highest greenhouse gas emissions. The underlying chapters also reference other scenarios, including RCP4.5 and
RCP6.0 that have intermediate levels of greenhouse gas emissions and result in intermediate levels of warming.
{Annex I: Glossary, Cross-Chapter Box 1 in Chapter 1}
Table SPM.1 provides estimates of total warming since the pre-industrial period under four different RCPs for key
assessment intervals used in SROCC. The warming from the 1850–1900 period until 1986–2005 has been assessed
as 0.63ºC (0.57ºC to 0.69ºC likely range) using observations of near-surface air temperature over the ocean and over
land.16 Consistent with the approach in AR5, modelled future changes in global mean surface air temperature relative
to 1986–2005 are added to this observed warming. {Cross-Chapter Box 1 in Chapter 1}
Table SPM.1 | Projected global mean surface temperature change relative to 1850–1900 for two time periods under four RCPs15 {Cross-Chapter
Box 1 in Chapter 1}
Near-term: 2031–2050 End-of-century: 2081–2100
Scenario Mean (ºC) Likely range (ºC) Mean (ºC) Likely range (ºC)
RCP2.6 1.6 1.1 to 2.0 1.6 0.9 to 2.4
RCP4.5 1.7 1.3 to 2.2 2.5 1.7 to 3.3
RCP6.0 1.6 1.2 to 2.0 2.9 2.0 to 3.8
RCP8.5 2.0 1.5 to 2.4 4.3 3.2 to 5.4
9
SPM
Summary for Policymakers
A.2 It is virtually certain that the global ocean has warmed unabated since 1970 and has taken up
more than 90% of the excess heat in the climate system (high confidence). Since 1993, the rate
of ocean warming has more than doubled (likely). Marine heatwaves have very likely doubled
in frequency since 1982 and are increasing in intensity (very high confidence). By absorbing
more CO2, the ocean has undergone increasing surface acidification (virtually certain). A loss
of oxygen has occurred from the surface to 1000 m (medium confidence). {1.4, 3.2, 5.2, 6.4, 6.7,
Figures SPM.1, SPM.2}
A.2.1. The ocean warming trend documented in the IPCC Fifth Assessment Report (AR5) has
continued. Since 1993 the rate of ocean warming and thus heat uptake has more than doubled (likely) from 3.22
± 1.61 ZJ yr–1 (0–700 m depth) and 0.97 ± 0.64 ZJ yr–1 (700–2000 m) between 1969 and 1993, to 6.28 ± 0.48 ZJ
yr–1 (0–700 m) and 3.86 ± 2.09 ZJ yr–1 (700–2000 m) between 1993 and 2017 17, and is attributed to anthropogenic
forcing (very likely). {1.4.1, 5.2.2, Table 5.1, Figure SPM.1}
A.2.2 The Southern Ocean accounted for 35–43% of the total heat gain in the upper 2000
m global ocean between 1970 and 2017 (high confidence). Its share increased to 45–62% between 2005 and 2017
(high confidence). The deep ocean below 2000 m has warmed since 1992 (likely), especially in the Southern Ocean.
{1.4, 3.2.1, 5.2.2, Table 5.1, Figure SPM.2}
A.2.3 Globally, marine heat-related events have increased; marine heatwaves18, defined when
the daily sea surface temperature exceeds the local 99th percentile over the period 1982 to 2016, have doubled
in frequency and have become longer-lasting, more intense and more extensive (very likely). It is very likely that
between 84–90% of marine heatwaves that occurred between 2006 and 2015 are attributable to the anthropogenic
temperature increase. {Table 6.2, 6.4, Figures SPM.1, SPM.2}
A.2.4 Density stratification19 has increased in the upper 200 m of the ocean since 1970 (very likely).
Observed surface ocean warming and high latitude addition of freshwater are making the surface ocean less dense
relative to deeper parts of the ocean (high confidence) and inhibiting mixing between surface and deeper waters
(high confidence). The mean stratification of the upper 200 m has increased by 2.3 ± 0.1% (very likely range) from
the 1971–1990 average to the 1998–2017 average. {5.2.2}
A.2.5 The ocean has taken up between 20–30% (very likely) of total anthropogenic CO2 emissions
since the 1980s causing further ocean acidification. Open ocean surface pH has declined by a very likely range
of 0.017–0.027 pH units per decade since the late 1980s20, with the decline in surface ocean pH very likely to have
already emerged from background natural variability for more than 95% of the ocean surface area. {3.2.1, 5.2.2,
Box 5.1, Figures SPM.1, SPM.2}
17 ZJ is Zettajoule and is equal to 1021 Joules. Warming the entire ocean by 1ºC requires about 5500 ZJ; 144 ZJ would warm the top 100 m by about 1ºC.
18 A marine heatwave is a period of extreme warm near-sea surface temperature that persists for days to months and can extend up to thousands of
kilometres (Annex I: Glossary).
19 In this report density stratification is defined as the density contrast between shallower and deeper layers. Increased stratification reduces the vertical
exchange of heat, salinity, oxygen, carbon, and nutrients.
20 Based on in-situ records longer than fifteen years.
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Summary for Policymakers
A.2.6 Datasets spanning 1970–2010 show that the open ocean has lost oxygen by a very likely
range of 0.5–3.3% over the upper 1000 m, alongside a likely expansion of the volume of oxygen minimum zones
by 3–8% (medium confidence). Oxygen loss is primarily due to increasing ocean stratification, changing ventilation
and biogeochemistry (high confidence). {5.2.2, Figures SPM.1, SPM.2}
A.2.7 Observations, both in situ (2004–2017) and based on sea surface temperature reconstructions,
indicate that the Atlantic Meridional Overturning Circulation (AMOC)21 has weakened relative to 1850–1900
(medium confidence). There is insufficient data to quantify the magnitude of the weakening, or to properly attribute
it to anthropogenic forcing due to the limited length of the observational record. Although attribution is currently not
possible, CMIP5 model simulations of the period 1850–2015, on average, exhibit a weakening AMOC when driven by
anthropogenic forcing. {6.7}
A.3 Global mean sea level (GMSL) is rising, with acceleration in recent decades due to increasing
rates of ice loss from the Greenland and Antarctic ice sheets (very high confidence), as well as
continued glacier mass loss and ocean thermal expansion. Increases in tropical cyclone winds
and rainfall, and increases in extreme waves, combined with relative sea level rise, exacerbate
extreme sea level events and coastal hazards (high confidence). {3.3, 4.2, 6.2, 6.3, 6.8, Figures
SPM.1, SPM.2, SPM.4, SPM.5}
A.3.1 Total GMSL rise for 1902–2015 is 0.16 m (likely range 0.12–0.21 m). The rate of GMSL rise for
2006–2015 of 3.6 mm yr–1 (3.1–4.1 mm yr–1, very likely range), is unprecedented over the last century (high confidence),
and about 2.5 times the rate for 1901–1990 of 1.4 mm yr–1 (0.8– 2.0 mm yr–1, very likely range). The sum of ice
sheet and glacier contributions over the period 2006–2015 is the dominant source of sea level rise (1.8 mm yr–1, very
likely range 1.7–1.9 mm yr–1), exceeding the effect of thermal expansion of ocean water (1.4 mm yr–1, very likely
range 1.1–1.7 mm yr–1) 22 (very high confidence). The dominant cause of global mean sea level rise since 1970 is
anthropogenic forcing (high confidence). {4.2.1, 4.2.2, Figure SPM.1}
A.3.2 Sea level rise has accelerated (extremely likely) due to the combined increased ice loss from
the Greenland and Antarctic ice sheets (very high confidence). Mass loss from the Antarctic ice sheet over the period
2007–2016 tripled relative to 1997–2006. For Greenland, mass loss doubled over the same period (likely, medium
confidence). {3.3.1, Figures SPM.1, SPM.2, SPM A.1.1}
A.3.3 Acceleration of ice flow and retreat in Antarctica, which has the potential to lead to sea
level rise of several metres within a few centuries, is observed in the Amundsen Sea Embayment of West Antarctica
and in Wilkes Land, East Antarctica (very high confidence). These changes may be the onset of an irreversible23 ice
sheet instability. Uncertainty related to the onset of ice sheet instability arises from limited observations, inadequate
model representation of ice sheet processes, and limited understanding of the complex interactions between the
atmosphere, ocean and the ice sheet. {3.3.1, Cross-Chapter Box 8 in Chapter 3, 4.2.3}
A.3.4 Sea level rise is not globally uniform and varies regionally. Regional differences, within ±30%
of the global mean sea level rise, result from land ice loss and variations in ocean warming and circulation. Differences
from the global mean can be greater in areas of rapid vertical land movement including from local human activities
(e.g. extraction of groundwater). (high confidence) {4.2.2, 5.2.2, 6.2.2, 6.3.1, 6.8.2, Figure SPM.2}
21 The Atlantic Meridional Overturning Circulation (AMOC) is the main current system in the South and North Atlantic Oceans (Annex I: Glossary).
22 The total rate of sea level rise is greater than the sum of cryosphere and ocean contributions due to uncertainties in the estimate of landwater storage change.
23 The recovery time scale is hundreds to thousands of years (Annex I: Glossary).
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SPM
Summary for Policymakers
A.3.5 Extreme wave heights, which contribute to extreme sea level events, coastal erosion and
flooding, have increased in the Southern and North Atlantic Oceans by around 1.0 cm yr–1 and 0.8 cm yr–1 over the
period 1985–2018 (medium confidence). Sea ice loss in the Arctic has also increased wave heights over the period
1992–2014 (medium confidence). {4.2.2, 6.2, 6.3, 6.8, Box 6.1}
A.3.6 Anthropogenic climate change has increased observed precipitation (medium confidence),
winds (low confidence), and extreme sea level events (high confidence) associated with some tropical cyclones, which
has increased intensity of multiple extreme events and associated cascading impacts (high confidence). Anthropogenic
climate change may have contributed to a poleward migration of maximum tropical cyclone intensity in the western
North Pacific in recent decades related to anthropogenically-forced tropical expansion (low confidence). There is
emerging evidence for an increase in annual global proportion of Category 4 or 5 tropical cyclones in recent decades
(low confidence). {6.2, Table 6.2, 6.3, 6.8, Box 6.1}
Observed Impacts on Ecosystems
A.4 Cryospheric and associated hydrological changes have impacted terrestrial and freshwater
species and ecosystems in high mountain and polar regions through the appearance of land
previously covered by ice, changes in snow cover, and thawing permafrost. These changes have
contributed to changing the seasonal activities, abundance and distribution of ecologically,
culturally, and economically important plant and animal species, ecological disturbances, and
ecosystem functioning. (high confidence) {2.3.2, 2.3.3, 3.4.1, 3.4.3, Box 3.4, Figure SPM.2}
A.4.1 Over the last century some species of plants and animals have increased in abundance, shifted
their range, and established in new areas as glaciers receded and the snow-free season lengthened (high confidence).
Together with warming, these changes have increased locally the number of species in high mountains, as
lower-elevation species migrate upslope (very high confidence). Some cold-adapted or snow-dependent species
have declined in abundance, increasing their risk of extinction, notably on mountain summits (high confidence). In
polar and mountain regions, many species have altered seasonal activities especially in late winter and spring (high
confidence). {2.3.3, Box 3.4}
A.4.2 Increased wildfire and abrupt permafrost thaw, as well as changes in Arctic and mountain
hydrology have altered frequency and intensity of ecosystem disturbances (high confidence). This has included positive
and negative impacts on vegetation and wildlife such as reindeer and salmon (high confidence). {2.3.3, 3.4.1, 3.4.3}
A.4.3 Across tundra, satellite observations show an overall greening, often indicative of increased
plant productivity (high confidence). Some browning areas in tundra and boreal forest are indicative that productivity
has decreased (high confidence). These changes have negatively affected provisioning, regulating and cultural
ecosystem services, with also some transient positive impacts for provisioning services, in both high mountains
(medium confidence) and polar regions (high confidence). {2.3.1, 2.3.3, 3.4.1, 3.4.3, Annex I: Glossary}
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SPM
Summary for Policymakers
A.5 Since about 1950 many marine species across various groups have undergone shifts in
geographical range and seasonal activities in response to ocean warming, sea ice change and
biogeochemical changes, such as oxygen loss, to their habitats (high confidence). This has
resulted in shifts in species composition, abundance and biomass production of ecosystems,
from the equator to the poles. Altered interactions between species have caused cascading
impacts on ecosystem structure and functioning (medium confidence). In some marine
ecosystems species are impacted by both the effects of fishing and climate changes (medium
confidence). {3.2.3, 3.2.4, Box 3.4, 5.2.3, 5.3, 5.4.1, Figure SPM.2}
A.5.1 Rates of poleward shifts in distributions across different marine species since the 1950s
are 52 ± 33 km per decade and 29 ± 16 km per decade (very likely ranges) for organisms in the epipelagic
(upper 200 m from sea surface) and seafloor ecosystems, respectively. The rate and direction of observed shifts in
distributions are shaped by local temperature, oxygen, and ocean currents across depth, latitudinal and longitudinal
gradients (high confidence). Warming-induced species range expansions have led to altered ecosystem structure
and functioning such as in the North Atlantic, Northeast Pacific and Arctic (medium confidence). {5.2.3, 5.3.2, 5.3.6,
Box 3.4, Figure SPM.2}
A.5.2 In recent decades, Arctic net primary production has increased in ice-free waters
(high confidence) and spring phytoplankton blooms are occurring earlier in the year in response to sea ice change
and nutrient availability with spatially variable positive and negative consequences for marine ecosystems (medium
confidence). In the Antarctic, such changes are spatially heterogeneous and have been associated with rapid local
environmental change, including retreating glaciers and sea ice change (medium confidence). Changes in the
seasonal activities, production and distribution of some Arctic zooplankton and a southward shift in the distribution
of the Antarctic krill population in the South Atlantic are associated with climate-linked environmental changes
(medium confidence). In polar regions, ice associated marine mammals and seabirds have experienced habitat
contraction linked to sea ice changes (high confidence) and impacts on foraging success due to climate impacts on
prey distributions (medium confidence). Cascading effects of multiple climate-related drivers on polar zooplankton
have affected food web structure and function, biodiversity as well as fisheries (high confidence). {3.2.3, 3.2.4,
Box 3.4, 5.2.3, Figure SPM.2}
A.5.3 Eastern Boundary Upwelling Systems (EBUS) are amongst the most productive ocean
ecosystems. Increasing ocean acidification and oxygen loss are negatively impacting two of the four major upwelling
systems: the California Current and Humboldt Current (high confidence). Ocean acidification and decrease in oxygen
level in the California Current upwelling system have altered ecosystem structure, with direct negative impacts on
biomass production and species composition (medium confidence). {Box 5.3, Figure SPM.2}
A.5.4 Ocean warming in the 20th century and beyond has contributed to an overall decrease in
maximum catch potential (medium confidence), compounding the impacts from overfishing for some fish stocks
(high confidence). In many regions, declines in the abundance of fish and shellfish stocks due to direct and indirect
effects of global warming and biogeochemical changes have already contributed to reduced fisheries catches
(high confidence). In some areas, changing ocean conditions have contributed to the expansion of suitable habitat and/
or increases in the abundance of some species (high confidence). These changes have been accompanied by changes
in species composition of fisheries catches since the 1970s in many ecosystems (medium confidence). {3.2.3, 5.4.1,
Figure SPM.2}
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Summary for Policymakers
A.6 Coastal ecosystems are affected by ocean warming, including intensified marine heatwaves,
acidification, loss of oxygen, salinity intrusion and sea level rise, in combination with adverse
effects from human activities on ocean and land (high confidence). Impacts are already
observed on habitat area and biodiversity, as well as ecosystem functioning and services
(high confidence). {4.3.2, 4.3.3, 5.3, 5.4.1, 6.4.2, Figure SPM.2}
A.6.1 Vegetated coastal ecosystems protect the coastline from storms and erosion and help
buffer the impacts of sea level rise. Nearly 50% of coastal wetlands have been lost over the last 100 years, as
a result of the combined effects of localised human pressures, sea level rise, warming and extreme climate events
(high confidence). Vegetated coastal ecosystems are important carbon stores; their loss is responsible for the
current release of 0.04–1.46 GtC yr–1 (medium confidence). In response to warming, distribution ranges of seagrass
meadows and kelp forests are expanding at high latitudes and contracting at low latitudes since the late 1970s
(high confidence), and in some areas episodic losses occur following heatwaves (medium confidence). Large-scale
mangrove mortality that is related to warming since the 1960s has been partially offset by their encroachment into
subtropical saltmarshes as a result of increase in temperature, causing the loss of open areas with herbaceous plants
that provide food and habitat for dependent fauna (high confidence). {4.3.3, 5.3.2, 5.3.6, 5.4.1, 5.5.1, Figure SPM.2}
A.6.2 Increased sea water intrusion in estuaries due to sea level rise has driven upstream
redistribution of marine species (medium confidence) and caused a reduction of suitable habitats for estuarine
communities (medium confidence). Increased nutrient and organic matter loads in estuaries since the 1970s from
intensive human development and riverine loads have exacerbated the stimulating effects of ocean warming on
bacterial respiration, leading to expansion of low oxygen areas (high confidence). {5.3.1}
A.6.3 The impacts of sea level rise on coastal ecosystems include habitat contraction, geographical
shift of associated species, and loss of biodiversity and ecosystem functionality. Impacts are exacerbated by
direct human disturbances, and where anthropogenic barriers prevent landward shift of marshes and mangroves
(termed coastal squeeze) (high confidence). Depending on local geomorphology and sediment supply, marshes and
mangroves can grow vertically at rates equal to or greater than current mean sea level rise (high confidence).
{4.3.2, 4.3.3, 5.3.2, 5.3.7, 5.4.1}
A.6.4 Warm-water coral reefs and rocky shores dominated by immobile, calcifying (e.g., shell and
skeleton producing) organisms such as corals, barnacles and mussels, are currently impacted by extreme temperatures
and ocean acidification (high confidence). Marine heatwaves have already resulted in large-scale coral bleaching
events at increasing frequency (very high confidence) causing worldwide reef degradation since 1997, and recovery
is slow (more than 15 years) if it occurs (high confidence). Prolonged periods of high environmental temperature and
dehydration of the organisms pose high risk to rocky shore ecosystems (high confidence). {SR.1.5; 5.3.4, 5.3.5, 6.4.2,
Figure SPM.2}
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14
SPM
Summary for Policymakers
Upper water column
Coral
Kelp forest
Rocky shores
Fisheries
Tourism
Habitat services
Coastal carbon
sequestration
Deep sea
Polar benthos
Coastal wetlands
Temperature
Oxygen
Ocean pH
Sea ice extent
Sea level
Sea ice-associated
Transportation/shipping
Cultural services
Physical
changes
Greenhouse
Climate Change Gases Cryosphere Change Attribution Attribution
Physical changes
Systems
Human systems and
ecosystem services
Physical Ecosystems
changes
Human systems
and ecosystem
services
Ecosystems
Tundra
Forest
Agriculture
Tourism
Infrastructure
Migration 6
Water availability
Flood
Landslide
Avalanche
Ground subsidence
Cultural services
Lakes/ponds
Rivers/streams
Observed regional impacts from changes in the ocean and the cryosphere
Ocean
High mountain and
polar land regions
decrease
increase
increase and
decrease
negative
positive
positive and
negative
no
assessment
LEGEND
high
medium
low
Attribution
confidence
Himalaya,
Tibetan Plateau
and other
High Mountain
Asia 2 Caucasus
Scandinavia
4 Alaska 5
Western
Canada
and USA
Russian
Iceland Arctic
European
Alps and
Pyrenees
Southern
Andes
Low
Latitudes
3
New
Zealand Antarctica
Arctic
Canada and
Greenland
2 including Hindu Kush, Karakoram, Hengduan Shan, and Tien Shan; 3 tropical Andes, Mexico, eastern Africa, and Indonesia;
4 includes Finland, Norway, and Sweden; 5 includes adjacent areas in Yukon Territory and British Columbia, Canada; 6 Migration refers to an
increase or decrease in net migration, not to beneficial/adverse value.
Southern
Ocean
Tropical
Indian
Ocean
North
Atlantic
Tropical
Atlantic
Temperate
Indian
Ocean
South
Atlantic
South
Pacific
Tropical
EBUS 1 Pacific
North
Arctic Pacific
1 Eastern Boundary Upwelling Systems (Benguela Current, Canary Current, California Current, and Humboldt Current); {Box 5.3}
24 Marginal seas are not assessed individually as ocean regions in this report.
Figure SPM.2 | Synthesis of observed regional hazards and impacts in ocean24 (top) and high mountain and polar land regions (bottom) assessed
in SROCC. For each region, physical changes, impacts on key ecosystems, and impacts on human systems and ecosystem function and services are
shown. For physical changes, yellow/green refers to an increase/decrease, respectively, in amount or frequency of the measured variable. For impacts
on ecosystems, human systems and ecosystems services blue or red depicts whether an observed impact is positive (beneficial) or negative (adverse),
respectively, to the given system or service. Cells assigned ‘increase and decrease’ indicate that within that region, both increase and decrease of
physical changes are found, but are not necessarily equal; the same holds for cells showing ‘positive and negative’ attributable impacts. For ocean
regions, the confidence level refers to the confidence in attributing observed changes to changes in greenhouse gas forcing for physical changes and to
climate change for ecosystem, human systems, and ecosystem services. For high mountain and polar land regions, the level of confidence in attributing
physical changes and impacts at least partly to a change in the cryosphere is shown. No assessment means: not applicable, not assessed at regional
scale, or the evidence is insufficient for assessment. The physical changes in the ocean are defined as: Temperature change in 0–700 m layer of the
ocean except for Southern Ocean (0–2000 m) and Arctic Ocean (upper mixed layer and major inflowing branches); Oxygen in the 0–1200 m layer
or oxygen minimum layer; Ocean pH as surface pH (decreasing pH corresponds to increasing ocean acidification). Ecosystems in the ocean: Coral
refers to warm-water coral reefs and cold-water corals. The ‘upper water column’ category refers to epipelagic zone for all ocean regions except Polar
Regions, where the impacts on some pelagic organisms in open water deeper than the upper 200 m were included. Coastal wetland includes salt
marshes, mangroves and seagrasses. Kelp forests are habitats of a specific group of macroalgae. Rocky shores are coastal habitats dominated by
immobile calcified organisms such as mussels and barnacles. Deep sea is seafloor ecosystems that are 3000–6000 m deep. Sea-ice associated includes
ecosystems in, on and below sea ice. Habitat services refer to supporting structures and services (e.g., habitat, biodiversity, primary production).
Coastal Carbon Sequestration refers to the uptake and storage of carbon by coastal blue carbon ecosystems. Ecosystems on Land: Tundra refers to
tundra and alpine meadows, and includes terrestrial Antarctic ecosystems.
•• •-...._ - •• - •• •• - - - • • • • • • • • • • • ...... ... ... ... ... ... ... ... ... ... ... § •
• - - •• - •• •• - - - ••
ee • ... .. .. .. d • .. • .. • ... ... ... ... ¢ 4o .. .. ¢ •• .. .. .. § .. .. .. ... .. • • • • • • -
.d. •• ¢ o • □ ... • • • • • .. - • • • • • • • •• ee • .. .. • .. • .. .. .. .••. .•. .•. • ••• •• • • • • .. • •
15
SPM
Summary for Policymakers
Figure SPM.2 (continued): Migration refers to an increase or decrease in net migration, not to beneficial/adverse value. Impacts on tourism refer
to the operating conditions for the tourism sector. Cultural services include cultural identity, sense of home, and spiritual, intrinsic and aesthetic
values, as well as contributions from glacier archaeology. The underlying information is given for land regions in tables SM2.6, SM2.7, SM2.8, SM3.8,
SM3.9, and SM3.10, and for ocean regions in tables SM5.10, SM5.11, SM3.8, SM3.9, and SM3.10. {2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.3.5, 2.3.6, 2.3.7,
Figure 2.1, 3.2.1, 3.2.3, 3.2.4, 3.3.3, 3.4.1, 3.4.3, 3.5.2, Box 3.4, 4.2.2, 5.2.2, 5.2.3, 5.3.3, 5.4, 5.6, Figure 5.24, Box 5.3}
Observed Impacts on People and Ecosystem Services
A.7 Since the mid-20th century, the shrinking cryosphere in the Arctic and high mountain areas
has led to predominantly negative impacts on food security, water resources, water quality,
livelihoods, health and well-being, infrastructure, transportation, tourism and recreation, as
well as culture of human societies, particularly for Indigenous peoples (high confidence). Costs
and benefits have been unequally distributed across populations and regions. Adaptation
efforts have benefited from the inclusion of Indigenous knowledge and local knowledge
(high confidence). {1.1, 1.5, 1.6.2, 2.3, 2.4, 3.4, 3.5, Figure SPM.2}
A.7.1 Food and water security have been negatively impacted by changes in snow cover, lake and
river ice, and permafrost in many Arctic regions (high confidence). These changes have disrupted access to, and food
availability within, herding, hunting, fishing, and gathering areas, harming the livelihoods and cultural identity of
Arctic residents including Indigenous populations (high confidence). Glacier retreat and snow cover changes have
contributed to localized declines in agricultural yields in some high mountain regions, including Hindu Kush Himalaya
and the tropical Andes (medium confidence). {2.3.1, 2.3.7, Box 2.4, 3.4.1, 3.4.2, 3.4.3, 3.5.2, Figure SPM.2}
A.7.2 In the Arctic, negative impacts of cryosphere change on human health have included
increased risk of food- and waterborne diseases, malnutrition, injury, and mental health challenges especially among
Indigenous peoples (high confidence). In some high mountain areas, water quality has been affected by contaminants,
particularly mercury, released from melting glaciers and thawing permafrost (medium confidence). Health-related
adaptation efforts in the Arctic range from local to international in scale, and successes have been underpinned by
Indigenous knowledge (high confidence). {1.8, Cross-Chapter Box 4 in Chapter 1, 2.3.1, 3.4.3}
A.7.3 Arctic residents, especially Indigenous peoples, have adjusted the timing of activities to respond
to changes in seasonality and safety of land, ice, and snow travel conditions. Municipalities and industry are beginning
to address infrastructure failures associated with flooding and thawing permafrost and some coastal communities
have planned for relocation (high confidence). Limited funding, skills, capacity, and institutional support to engage
meaningfully in planning processes have challenged adaptation (high confidence). {3.5.2, 3.5.4, Cross-Chapter Box 9}
A.7.4 Summertime Arctic ship-based transportation (including tourism) increased over the past two
decades concurrent with sea ice reductions (high confidence). This has implications for global trade and economies
linked to traditional shipping corridors, and poses risks to Arctic marine ecosystems and coastal communities
(high confidence), such as from invasive species and local pollution. {3.2.1, 3.2.4, 3.5.4, 5.4.2, Figure SPM.2}
A.7.5 In past decades, exposure of people and infrastructure to natural hazards has increased due
to growing population, tourism and socioeconomic development (high confidence). Some disasters have been linked
to changes in the cryosphere, for example in the Andes, high mountain Asia, Caucasus and European Alps (medium
confidence). {2.3.2, Figure SPM.2}
A.7.6 Changes in snow and glaciers have changed the amount and seasonality of runoff and
water resources in snow dominated and glacier-fed river basins (very high confidence). Hydropower facilities have
experienced changes in seasonality and both increases and decreases in water input from high mountain areas, for
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example, in central Europe, Iceland, Western USA/Canada, and tropical Andes (medium confidence). However, there
is only limited evidence of resulting impacts on operations and energy production. {SPM B.1.4, 2.3.1}
A.7.7 High mountain aesthetic and cultural aspects have been negatively impacted by glacier
and snow cover decline (e.g. in the Himalaya, East Africa, the tropical Andes) (medium confidence). Tourism and
recreation, including ski and glacier tourism, hiking, and mountaineering, have also been negatively impacted in
many mountain regions (medium confidence). In some places, artificial snowmaking has reduced negative impacts
on ski tourism (medium confidence). {2.3.5, 2.3.6, Figure SPM.2}
A.8 Changes in the ocean have impacted marine ecosystems and ecosystem services with regionally
diverse outcomes, challenging their governance (high confidence). Both positive and negative
impacts result for food security through fisheries (medium confidence), local cultures and
livelihoods (medium confidence), and tourism and recreation (medium confidence). The
impacts on ecosystem services have negative consequences for health and well-being (medium
confidence), and for Indigenous peoples and local communities dependent on fisheries
(high confidence). {1.1, 1.5, 3.2.1, 5.4.1, 5.4.2, Figure SPM.2}
A.8.1 Warming-induced changes in the spatial distribution and abundance of some fish and
shellfish stocks have had positive and negative impacts on catches, economic benefits, livelihoods, and local
culture (high confidence). There are negative consequences for Indigenous peoples and local communities that are
dependent on fisheries (high confidence). Shifts in species distributions and abundance has challenged international
and national ocean and fisheries governance, including in the Arctic, North Atlantic and Pacific, in terms of
regulating fishing to secure ecosystem integrity and sharing of resources between fishing entities (high confidence).
{3.2.4, 3.5.3, 5.4.2, 5.5.2, Figure SPM.2}
A.8.2 Harmful algal blooms display range expansion and increased frequency in coastal areas
since the 1980s in response to both climatic and non-climatic drivers such as increased riverine nutrients run-off
(high confidence). The observed trends in harmful algal blooms are attributed partly to the effects of ocean warming,
marine heatwaves, oxygen loss, eutrophication and pollution (high confidence). Harmful algal blooms have had
negative impacts on food security, tourism, local economy, and human health (high confidence). The human
communities who are more vulnerable to these biological hazards are those in areas without sustained monitoring
programs and dedicated early warning systems for harmful algal blooms (medium confidence). {Box 5.4, 5.4.2, 6.4.2}
A.9 Coastal communities are exposed to multiple climate-related hazards, including tropical
cyclones, extreme sea levels and flooding, marine heatwaves, sea ice loss, and permafrost
thaw (high confidence). A diversity of responses has been implemented worldwide, mostly
after extreme events, but also some in anticipation of future sea level rise, e.g., in the case of
large infrastructure. {3.2.4, 3.4.3, 4.3.2, 4.3.3, 4.3.4, 4.4.2, 5.4.2, 6.2, 6.4.2, 6.8, Box 6.1, Cross
Chapter Box 9, Figure SPM.5}
A.9.1 Attribution of current coastal impacts on people to sea level rise remains difficult in
most locations since impacts were exacerbated by human-induced non-climatic drivers, such as land subsidence
(e.g., groundwater extraction), pollution, habitat degradation, reef and sand mining (high confidence). {4.3.2, 4.3.3}
A.9.2 Coastal protection through hard measures, such as dikes, seawalls, and surge barriers, is
widespread in many coastal cities and deltas. Ecosystem-based and hybrid approaches combining ecosystems and
built infrastructure are becoming more popular worldwide. Coastal advance, which refers to the creation of new
land by building seawards (e.g., land reclamation), has a long history in most areas where there are dense coastal
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populations and a shortage of land. Coastal retreat, which refers to the removal of human occupation of coastal areas,
is also observed, but is generally restricted to small human communities or occurs to create coastal wetland habitat.
The effectiveness of the responses to sea level rise are assessed in Figure SPM.5. {3.5.3, 4.3.3, 4.4.2, 6.3.3, 6.9.1,
Cross-Chapter Box 9}
B. Projected Changes and Risks
Projected Physical Changes25
B.1 Global-scale glacier mass loss, permafrost thaw, and decline in snow cover and Arctic sea ice
extent are projected to continue in the near-term (2031–2050) due to surface air temperature
increases (high confidence), with unavoidable consequences for river runoff and local hazards
(high confidence). The Greenland and Antarctic Ice Sheets are projected to lose mass at an
increasing rate throughout the 21st century and beyond (high confidence). The rates and
magnitudes of these cryospheric changes are projected to increase further in the second half
of the 21st century in a high greenhouse gas emissions scenario (high confidence). Strong
reductions in greenhouse gas emissions in the coming decades are projected to reduce further
changes after 2050 (high confidence). {2.2, 2.3, Cross-Chapter Box 6 in Chapter 2, 3.3, 3.4,
Figure SPM.1, SPM Box SPM.1}
B.1.1 Projected glacier mass reductions between 2015 and 2100 (excluding the ice sheets) range
from 18 ± 7% (likely range) for RCP2.6 to 36 ± 11% (likely range) for RCP8.5, corresponding to a sea level contribution
of 94 ± 25 mm (likely range) sea level equivalent for RCP2.6, and 200 ± 44 mm (likely range) for RCP8.5 (medium
confidence). Regions with mostly smaller glaciers (e.g., Central Europe, Caucasus, North Asia, Scandinavia, tropical
Andes, Mexico, eastern Africa and Indonesia), are projected to lose more than 80% of their current ice mass by 2100
under RCP8.5 (medium confidence), and many glaciers are projected to disappear regardless of future emissions
(very high confidence). {Cross-Chapter Box 6 in Chapter 2, Figure SPM.1}
B.1.2 In 2100, the Greenland Ice Sheet’s projected contribution to GMSL rise is 0.07 m (0.04–0.12 m,
likely range) under RCP2.6, and 0.15 m (0.08–0.27 m, likely range) under RCP8.5. In 2100, the Antarctic Ice Sheet
is projected to contribute 0.04 m (0.01–0.11 m, likely range) under RCP2.6, and 0.12 m (0.03–0.28 m, likely range)
under RCP8.5. The Greenland Ice Sheet is currently contributing more to sea level rise than the Antarctic Ice Sheet
(high confidence), but Antarctica could become a larger contributor by the end of the 21st century as a consequence
of rapid retreat (low confidence). Beyond 2100, increasing divergence between Greenland and Antarctica’s relative
contributions to GMSL rise under RCP8.5 has important consequences for the pace of relative sea level rise in the
Northern Hemisphere. {3.3.1, 4.2.3, 4.2.5, 4.3.3, Cross-Chapter Box 8 in Chapter 3, Figure SPM.1}
B.1.3 Arctic autumn and spring snow cover are projected to decrease by 5–10%, relative to
1986–2005, in the near-term (2031–2050), followed by no further losses under RCP2.6, but an additional 15–25%
loss by the end of century under RCP8.5 (high confidence). In high mountain areas, projected decreases in low
elevation mean winter snow depth, compared to 1986–2005, are likely 10–40% by 2031–2050, regardless of
emissions scenario (high confidence). For 2081–2100, this projected decrease is likely 10–40% for RCP2.6 and
50–90% for RCP8.5. {2.2.2, 3.3.2, 3.4.2, Figure SPM.1}
25 This report primarily uses RCP2.6 and RCP8.5 for the following reasons: These scenarios largely represent the assessed range for the topics covered
in this report; they largely represent what is covered in the assessed literature, based on CMIP5; and they allow a consistent narrative about projected
changes. RCP4.5 and RCP6.0 are not available for all topics addressed in the report. {Box SPM.1}
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B.1.4 Widespread permafrost thaw is projected for this century (very high confidence) and beyond.
By 2100, projected near-surface (within 3–4 m) permafrost area shows a decrease of 24 ± 16% (likely range) for
RCP2.6 and 69 ± 20% (likely range) for RCP8.5. The RCP8.5 scenario leads to the cumulative release of tens to
hundreds of billions of tons (GtC) of permafrost carbon as CO2
26 and methane to the atmosphere by 2100 with
the potential to exacerbate climate change (medium confidence). Lower emissions scenarios dampen the response
of carbon emissions from the permafrost region (high confidence). Methane contributes a small fraction of the
total additional carbon release but is significant because of its higher warming potential. Increased plant growth is
projected to replenish soil carbon in part, but will not match carbon releases over the long term (medium confidence).
{2.2.4, 3.4.2, 3.4.3, Figure SPM.1, Cross-Chapter Box 5 in Chapter 1}
B.1.5 In many high mountain areas, glacier retreat and permafrost thaw are projected to further
decrease the stability of slopes, and the number and area of glacier lakes will continue to increase (high confidence).
Floods due to glacier lake outburst or rain-on-snow, landslides and snow avalanches, are projected to occur also in
new locations or different seasons (high confidence). {2.3.2}
B.1.6 River runoff in snow-dominated or glacier-fed high mountain basins is projected to change
regardless of emissions scenario (very high confidence), with increases in average winter runoff (high confidence)
and earlier spring peaks (very high confidence). In all emissions scenarios, average annual and summer runoff from
glaciers are projected to peak at or before the end of the 21st century (high confidence), e.g., around mid-century in
High Mountain Asia, followed by a decline in glacier runoff. In regions with little glacier cover (e.g., tropical Andes,
European Alps) most glaciers have already passed this peak (high confidence). Projected declines in glacier runoff by
2100 (RCP8.5) can reduce basin runoff by 10% or more in at least one month of the melt season in several large river
basins, especially in High Mountain Asia during the dry season (low confidence). {2.3.1}
B.1.7 Arctic sea ice loss is projected to continue through mid-century, with differences thereafter
depending on the magnitude of global warming: for stabilised global warming of 1.5ºC the annual probability of
a sea ice-free September by the end of century is approximately 1%, which rises to 10–35% for stabilised global
warming of 2ºC (high confidence). There is low confidence in projections for Antarctic sea ice. {3.2.2, Figure SPM.1}
B.2 Over the 21st century, the ocean is projected to transition to unprecedented conditions with
increased temperatures (virtually certain), greater upper ocean stratification (very likely),
further acidification (virtually certain), oxygen decline (medium confidence), and altered net
primary production (low confidence). Marine heatwaves (very high confidence) and extreme
El Niño and La Niña events (medium confidence) are projected to become more frequent. The
Atlantic Meridional Overturning Circulation (AMOC) is projected to weaken (very likely). The
rates and magnitudes of these changes will be smaller under scenarios with low greenhouse
gas emissions (very likely). {3.2, 5.2, 6.4, 6.5, 6.7, Box 5.1, Figures SPM.1, SPM.3}
B.2.1 The ocean will continue to warm throughout the 21st century (virtually certain). By 2100,
the top 2000 m of the ocean are projected to take up 5–7 times more heat under RCP8.5 (or 2–4 times more
under RCP2.6) than the observed accumulated ocean heat uptake since 1970 (very likely). The annual mean density
stratification19 of the top 200 m, averaged between 60ºS and 60ºN, is projected to increase by 12–30% for RCP8.5
and 1–9% for RCP2.6, for 2081–2100 relative to 1986–2005 (very likely), inhibiting vertical nutrient, carbon and
oxygen fluxes. {5.2.2, Figure SPM.1}
26 For context, total annual anthropogenic CO2 emissions were 10.8 ± 0.8 GtC yr–1 (39.6 ± 2.9 GtCO2 yr–1) on average over the period 2008–2017.
Total annual anthropogenic methane emissions were 0.35 ± 0.01 GtCH4 yr–1, on average over the period 2003–2012. {5.5.1}
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B.2.2 By 2081–2100 under RCP8.5, ocean oxygen content (medium confidence), upper ocean nitrate
content (medium confidence), net primary production (low confidence) and carbon export (medium confidence) are
projected to decline globally by very likely ranges of 3–4%, 9–14%, 4–11% and 9–16% respectively, relative to
2006–2015. Under RCP2.6, globally projected changes by 2081–2100 are smaller compared to RCP8.5 for oxygen
loss (very likely), nutrient availability (about as likely as not) and net primary production (high confidence). {5.2.2,
Box 5.1, Figures SPM.1, SPM.3}
B.2.3 Continued carbon uptake by the ocean by 2100 is virtually certain to exacerbate ocean
acidification. Open ocean surface pH is projected to decrease by around 0.3 pH units by 2081–2100, relative to
2006–2015, under RCP8.5 (virtually certain). For RCP8.5, there are elevated risks for keystone aragonite shell-forming
species due to crossing an aragonite stability threshold year-round in the Polar and sub-Polar Oceans by 2081–2100
(very likely). For RCP2.6, these conditions will be avoided this century (very likely), but some eastern boundary
upwelling systems are projected to remain vulnerable (high confidence). {3.2.3, 5.2.2, Box 5.1, Box 5.3, Figure SPM.1}
B.2.4 Climate conditions, unprecedented since the preindustrial period, are developing in the
ocean, elevating risks for open ocean ecosystems. Surface acidification and warming have already emerged in the
historical period (very likely). Oxygen loss between 100 and 600 m depth is projected to emerge over 59–80% of
the ocean area by 2031–2050 under RCP8.5 (very likely). The projected time of emergence for five primary drivers of
marine ecosystem change (surface warming and acidification, oxygen loss, nitrate content and net primary production
change) are all prior to 2100 for over 60% of the ocean area under RCP8.5 and over 30% under RCP2.6 (very likely).
{Annex I: Glossary, Box 5.1, Box 5.1 Figure 1}
B.2.5 Marine heatwaves are projected to further increase in frequency, duration, spatial extent
and intensity (maximum temperature) (very high confidence). Climate models project increases in the frequency of
marine heatwaves by 2081–2100, relative to 1850–1900, by approximately 50 times under RCP8.5 and 20 times
under RCP2.6 (medium confidence). The largest increases in frequency are projected for the Arctic and the tropical
oceans (medium confidence). The intensity of marine heatwaves is projected to increase about 10-fold under RCP8.5
by 2081–2100, relative to 1850–1900 (medium confidence). {6.4, Figure SPM.1}
B.2.6 Extreme El Niño and La Niña events are projected to likely increase in frequency in the 21st
century and to likely intensify existing hazards, with drier or wetter responses in several regions across the globe.
Extreme El Niño events are projected to occur about as twice as often under both RCP2.6 and RCP8.5 in the 21st
century when compared to the 20th century (medium confidence). Projections indicate that extreme Indian Ocean
Dipole events also increase in frequency (low confidence). {6.5, Figures 6.5, 6.6}
B.2.7 The AMOC is projected to weaken in the 21st century under all RCPs (very likely), although
a collapse is very unlikely (medium confidence). Based on CMIP5 projections, by 2300, an AMOC collapse is about
as likely as not for high emissions scenarios and very unlikely for lower ones (medium confidence). Any substantial
weakening of the AMOC is projected to cause a decrease in marine productivity in the North Atlantic (medium
confidence), more storms in Northern Europe (medium confidence), less Sahelian summer rainfall (high confidence)
and South Asian summer rainfall (medium confidence), a reduced number of tropical cyclones in the Atlantic (medium
confidence), and an increase in regional sea level along the northeast coast of North America (medium confidence).
Such changes would be in addition to the global warming signal. {6.7, Figures 6.8–6.10}
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B.3 Sea level continues to rise at an increasing rate. Extreme sea level events that are historically
rare (once per century in the recent past) are projected to occur frequently (at least once
per year) at many locations by 2050 in all RCP scenarios, especially in tropical regions (high
confidence). The increasing frequency of high water levels can have severe impacts in many
locations depending on exposure (high confidence). Sea level rise is projected to continue
beyond 2100 in all RCP scenarios. For a high emissions scenario (RCP8.5), projections of global
sea level rise by 2100 are greater than in AR5 due to a larger contribution from the Antarctic
Ice Sheet (medium confidence). In coming centuries under RCP8.5, sea level rise is projected to
exceed rates of several centimetres per year resulting in multi-metre rise (medium confidence),
while for RCP2.6 sea level rise is projected to be limited to around 1 m in 2300 (low confidence).
Extreme sea levels and coastal hazards will be exacerbated by projected increases in tropical
cyclone intensity and precipitation (high confidence). Projected changes in waves and tides
vary locally in whether they amplify or ameliorate these hazards (medium confidence).
{Cross-Chapter Box 5 in Chapter 1, Cross-Chapter Box 8 in Chapter 3, 4.1, 4.2, 5.2.2, 6.3.1,
Figures SPM.1, SPM.4, SPM.5}
B.3.1 The global mean sea level (GMSL) rise under RCP2.6 is projected to be 0.39 m (0.26–0.53 m,
likely range) for the period 2081–2100, and 0.43 m (0.29–0.59 m, likely range) in 2100 with respect to 1986–2005. For
RCP8.5, the corresponding GMSL rise is 0.71 m (0.51–0.92 m, likely range) for 2081–2100 and 0.84 m (0.61–1.10 m,
likely range) in 2100. Mean sea level rise projections are higher by 0.1 m compared to AR5 under RCP8.5 in 2100, and
the likely range extends beyond 1 m in 2100 due to a larger projected ice loss from the Antarctic Ice Sheet (medium
confidence). The uncertainty at the end of the century is mainly determined by the ice sheets, especially in Antarctica.
{4.2.3, Figures SPM.1, SPM.5}
B.3.2 Sea level projections show regional differences around GMSL. Processes not driven by
recent climate change, such as local subsidence caused by natural processes and human activities, are important to
relative sea level changes at the coast (high confidence). While the relative importance of climate-driven sea level
rise is projected to increase over time, local processes need to be considered for projections and impacts of sea level
(high confidence). {SPM A.3.4, 4.2.1, 4.2.2, Figure SPM.5}
B.3.3 The rate of global mean sea level rise is projected to reach 15 mm yr–1 (10–20 mm yr–1, likely
range) under RCP8.5 in 2100, and to exceed several centimetres per year in the 22nd century. Under RCP2.6, the rate
is projected to reach 4 mm yr-1 (2–6 mm yr–1, likely range) in 2100. Model studies indicate multi-meter rise in sea
level by 2300 (2.3–5.4 m for RCP8.5 and 0.6–1.07 m under RCP2.6) (low confidence), indicating the importance of
reduced emissions for limiting sea level rise. Processes controlling the timing of future ice-shelf loss and the extent of
ice sheet instabilities could increase Antarctica’s contribution to sea level rise to values substantially higher than the
likely range on century and longer time-scales (low confidence). Considering the consequences of sea level rise that
a collapse of parts of the Antarctic Ice Sheet entails, this high impact risk merits attention. {Cross-Chapter Box 5 in
Chapter 1, Cross-Chapter Box 8 in Chapter 3, 4.1, 4.2.3}
B.3.4 Global mean sea level rise will cause the frequency of extreme sea level events at most
locations to increase. Local sea levels that historically occurred once per century (historical centennial events) are
projected to occur at least annually at most locations by 2100 under all RCP scenarios (high confidence). Many
low-lying megacities and small islands (including SIDS) are projected to experience historical centennial events at
least annually by 2050 under RCP2.6, RCP4.5 and RCP8.5. The year when the historical centennial event becomes
an annual event in the mid-latitudes occurs soonest in RCP8.5, next in RCP4.5 and latest in RCP2.6. The increasing
frequency of high water levels can have severe impacts in many locations depending on the level of exposure (high
confidence). {4.2.3, 6.3, Figures SPM.4, SPM.5}
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B.3.5 Significant wave heights (the average height from trough to crest of the highest one-third
of waves) are projected to increase across the Southern Ocean and tropical eastern Pacific (high confidence) and
Baltic Sea (medium confidence) and decrease over the North Atlantic and Mediterranean Sea under RCP8.5 (high
confidence). Coastal tidal amplitudes and patterns are projected to change due to sea level rise and coastal adaptation
measures (very likely). Projected changes in waves arising from changes in weather patterns, and changes in tides
due to sea level rise, can locally enhance or ameliorate coastal hazards (medium confidence). {6.3.1, 5.2.2}
B.3.6 The average intensity of tropical cyclones, the proportion of Category 4 and 5 tropical cyclones
and the associated average precipitation rates are projected to increase for a 2ºC global temperature rise above any
baseline period (medium confidence). Rising mean sea levels will contribute to higher extreme sea levels associated
with tropical cyclones (very high confidence). Coastal hazards will be exacerbated by an increase in the average
intensity, magnitude of storm surge and precipitation rates of tropical cyclones. There are greater increases projected
under RCP8.5 than under RCP2.6 from around mid-century to 2100 (medium confidence). There is low confidence in
changes in the future frequency of tropical cyclones at the global scale. {6.3.1}
Projected Risks for Ecosystems
B.4 Future land cryosphere changes will continue to alter terrestrial and freshwater ecosystems in
high mountain and polar regions with major shifts in species distributions resulting in changes
in ecosystem structure and functioning, and eventual loss of globally unique biodiversity
(medium confidence). Wildfire is projected to increase significantly for the rest of this
century across most tundra and boreal regions, and also in some mountain regions (medium
confidence). {2.3.3, Box 3.4, 3.4.3}
B.4.1 In high mountain regions, further upslope migration by lower-elevation species, range
contractions, and increased mortality will lead to population declines of many alpine species, especially glacier- or
snow-dependent species (high confidence), with local and eventual global species loss (medium confidence). The
persistence of alpine species and sustaining ecosystem services depends on appropriate conservation and adaptation
measures (high confidence). {2.3.3}
B.4.2 On Arctic land, a loss of globally unique biodiversity is projected as limited refugia exist for
some High-Arctic species and hence they are outcompeted by more temperate species (medium confidence). Woody
shrubs and trees are projected to expand to cover 24–52% of Arctic tundra by 2050 (medium confidence). The boreal
forest is projected to expand at its northern edge, while diminishing at its southern edge where it is replaced by lower
biomass woodland/shrublands (medium confidence). {3.4.3, Box 3.4}
B.4.3 Permafrost thaw and decrease in snow will affect Arctic and mountain hydrology and wildfire,
with impacts on vegetation and wildlife (medium confidence). About 20% of Arctic land permafrost is vulnerable to
abrupt permafrost thaw and ground subsidence, which is projected to increase small lake area by over 50% by 2100
for RCP8.5 (medium confidence). Even as the overall regional water cycle is projected to intensify, including increased
precipitation, evapotranspiration, and river discharge to the Arctic Ocean, decreases in snow and permafrost may
lead to soil drying with consequences for ecosystem productivity and disturbances (medium confidence). Wildfire is
projected to increase for the rest of this century across most tundra and boreal regions, and also in some mountain
regions, while interactions between climate and shifting vegetation will influence future fire intensity and frequency
(medium confidence). {2.3.3, 3.4.1, 3.4.2, 3.4.3, SPM B.1}
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B.5 A decrease in global biomass of marine animal communities, their production, and fisheries
catch potential, and a shift in species composition are projected over the 21st century in
ocean ecosystems from the surface to the deep seafloor under all emission scenarios (medium
confidence). The rate and magnitude of decline are projected to be highest in the tropics
(high confidence), whereas impacts remain diverse in polar regions (medium confidence) and
increase for high emissions scenarios. Ocean acidification (medium confidence), oxygen loss
(medium confidence) and reduced sea ice extent (medium confidence) as well as non-climatic
human activities (medium confidence) have the potential to exacerbate these warming-induced
ecosystem impacts. {3.2.3, 3.3.3, 5.2.2, 5.2.3, 5.2.4, 5.4.1, Figure SPM.3}
B.5.1 Projected ocean warming and changes in net primary production alter biomass, production
and community structure of marine ecosystems. The global-scale biomass of marine animals across the foodweb is
projected to decrease by 15.0 ± 5.9% (very likely range) and the maximum catch potential of fisheries by 20.5–24.1%
by the end of the 21st century relative to 1986–2005 under RCP8.5 (medium confidence). These changes are projected
to be very likely three to four times larger under RCP8.5 than RCP2.6. {3.2.3, 3.3.3, 5.2.2, 5.2.3, 5.4.1, Figure SPM.3}
B.5.2 Under enhanced stratification reduced nutrient supply is projected to cause tropical ocean
net primary production to decline by 7–16% (very likely range) for RCP8.5 by 2081–2100 (medium confidence). In
tropical regions, marine animal biomass and production are projected to decrease more than the global average
under all emissions scenarios in the 21st century (high confidence). Warming and sea ice changes are projected to
increase marine net primary production in the Arctic (medium confidence) and around Antarctica (low confidence),
modified by changing nutrient supply due to shifts in upwelling and stratification. Globally, the sinking flux of organic
matter from the upper ocean is projected to decrease, linked largely due to changes in net primary production
(high confidence). As a result, 95% or more of the deep sea (3000–6000 m depth) seafloor area and cold-water
coral ecosystems are projected to experience declines in benthic biomass under RCP8.5 (medium confidence).
{3.2.3, 5.2.2. 5.2.4, Figure SPM.1}
B.5.3 Warming, ocean acidification, reduced seasonal sea ice extent and continued loss of
multi-year sea ice are projected to impact polar marine ecosystems through direct and indirect effects on habitats,
populations and their viability (medium confidence). The geographical range of Arctic marine species, including
marine mammals, birds and fish is projected to contract, while the range of some sub-Arctic fish communities is
projected to expand, further increasing pressure on high-Arctic species (medium confidence). In the Southern Ocean,
the habitat of Antarctic krill, a key prey species for penguins, seals and whales, is projected to contract southwards
under both RCP2.6 and RCP8.5 (medium confidence). {3.2.2, 3.2.3, 5.2.3}
B.5.4 Ocean warming, oxygen loss, acidification and a decrease in flux of organic carbon from the
surface to the deep ocean are projected to harm habitat-forming cold-water corals, which support high biodiversity,
partly through decreased calcification, increased dissolution of skeletons, and bioerosion (medium confidence).
Vulnerability and risks are highest where and when temperature and oxygen conditions both reach values outside
species’ tolerance ranges (medium confidence). {Box 5.2, Figure SPM.3}
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23
SPM
Summary for Policymakers
1.5
2
3
4
5
present day
Abyssal
plains
Salt Estuaries
marshes
Mangrove
forests
Seagrass
meadows
Sandy
beaches
Warm water
corals
Rocky
shores
Kelp
forests
Epipelagic** Cold water
corals
(d) Impacts and risks to ocean ecosystems from climate change
1
2
3
4
Global mean sea surface temperature (SST)
change relative to pre-industrial levels (ºC)
Confidence level for transition
= Very high
= High
= Medium
= Low
= Transition range
Global mean surface temperature (GMST)
change relative to pre-industrial levels (ºC)
1
0 0
**see figure caption for definition
High Red: Significant and widespread impacts/risks.
Level of added impacts/risks
Very high
Undetectable White: Impacts/risks are undetectable.
Moderate Yellow: Impacts/risks are detectable and attributable to climate change with at least medium confidence.
Purple: Very high probability of severe impacts/risks and the presence of significant irreversibility
or the persistence of climate-related hazards, combined with limited ability to adapt due to the
nature of the hazard or impacts/risks.
(c) Maximum fisheries catch potential
(a) Simulated net primary production
(b) Simulated total animal biomass
Percent change
Average by 2081–2100, relative to 1986–2005
Projected changes, impacts and risks for ocean ecosystems
as a result of climate change
RCP2.6 RCP8.5
Value in normalized index (1986–2005)
Value in mol C m–2 yr–1 (1986–2005)
0 10 20 >25
Observed values in tonnes* (1986–2005)
model disagreement
0 0.15 55 >275,000
no data
0 0.5 1 > 3
* See figure caption for details
<–50 –40 –30 –20 –10 0 10 20 30 40 >50
Figure SPM.3 | Projected changes, impacts and risks for ocean regions and ecosystems.
"
we.+" r
..&Au:._Ng et.--
_.,,-""'"=----==-------'2: "' ,'-- ' -
n, •
7
- - - - - - - - - - -
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.. . .. 1
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24
SPM
Summary for Policymakers
Figure SPM.3 (continued): (a) depth integrated net primary production (NPP from CMIP527), (b) total animal biomass (depth integrated, including
fishes and invertebrates from FISHMIP28), (c) maximum fisheries catch potential and (d) impacts and risks for coastal and open ocean ecosystems. The
three left panels represent the simulated (a,b) and observed (c) mean values for the recent past (1986–2005), the middle and right panels represent
projected changes (%) by 2081–2100 relative to recent past under low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenario {Box SPM.1},
respectively. Total animal biomass in the recent past (b, left panel) represents the projected total animal biomass by each spatial pixel relative to the
global average. (c) *Average observed fisheries catch in the recent past (based on data from the Sea Around Us global fisheries database); projected
changes in maximum fisheries catch potential in shelf seas are based on the average outputs from two fisheries and marine ecosystem models. To
indicate areas of model inconsistency, shaded areas represent regions where models disagree in the direction of change for more than: (a) and (b)
3 out of 10 model projections, and (c) one out of two models. Although unshaded, the projected change in the Arctic and Antarctic regions in (b) total
animal biomass and (c) fisheries catch potential have low confidence due to uncertainties associated with modelling multiple interacting drivers and
ecosystem responses. Projections presented in (b) and (c) are driven by changes in ocean physical and biogeochemical conditions e.g., temperature,
oxygen level, and net primary production projected from CMIP5 Earth system models. **The epipelagic refers to the uppermost part of the ocean
with depth <200 m from the surface where there is enough sunlight to allow photosynthesis. (d) Assessment of risks for coastal and open ocean
ecosystems based on observed and projected climate impacts on ecosystem structure, functioning and biodiversity. Impacts and risks are shown in
relation to changes in Global Mean Surface Temperature (GMST) relative to pre-industrial level. Since assessments of risks and impacts are based
on global mean Sea Surface Temperature (SST), the corresponding SST levels are shown29. The assessment of risk transitions is described in Chapter
5 Sections 5.2, 5.3, 5.2.5 and 5.3.7 and Supplementary Materials SM5.3, Table SM5.6, Table SM5.8 and other parts of the underlying report. The
figure indicates assessed risks at approximate warming levels and increasing climate-related hazards in the ocean: ocean warming, acidification,
deoxygenation, increased density stratification, changes in carbon fluxes, sea level rise, and increased frequency and/or intensity of extreme events.
The assessment considers the natural adaptive capacity of the ecosystems, their exposure and vulnerability. Impact and risk levels do not consider
risk reduction strategies such as human interventions, or future changes in non-climatic drivers. Risks for ecosystems were assessed by considering
biological, biogeochemical, geomorphological and physical aspects. Higher risks associated with compound effects of climate hazards include
habitat and biodiversity loss, changes in species composition and distribution ranges, and impacts/risks on ecosystem structure and functioning,
including changes in animal/plant biomass and density, productivity, carbon fluxes, and sediment transport. As part of the assessment, literature was
compiled and data extracted into a summary table. A multi-round expert elicitation process was undertaken with independent evaluation of threshold
judgement, and a final consensus discussion. Further information on methods and underlying literature can be found in Chapter 5, Sections 5.2
and 5.3 and Supplementary Material. {3.2.3, 3.2.4, 5.2, 5.3, 5.2.5, 5.3.7, SM5.6, SM5.8, Figure 5.16, Cross Chapter Box 1 in Chapter 1 Table CCB1}
27 NPP is estimated from the Coupled Models Intercomparison Project 5 (CMIP5).
28 Total animal biomass is from the Fisheries and Marine Ecosystem Models Intercomparison Project (FISHMIP).
29 The conversion between GMST and SST is based on a scaling factor of 1.44 derived from changes in an ensemble of RCP8.5 simulations; this scaling
factor has an uncertainty of about 4% due to differences between the RCP2.6 and RCP8.5 scenarios. {Table SPM.1}
B.6 Risks of severe impacts on biodiversity, structure and function of coastal ecosystems are
projected to be higher for elevated temperatures under high compared to low emissions
scenarios in the 21st century and beyond. Projected ecosystem responses include losses
of species habitat and diversity, and degradation of ecosystem functions. The capacity of
organisms and ecosystems to adjust and adapt is higher at lower emissions scenarios (high
confidence). For sensitive ecosystems such as seagrass meadows and kelp forests, high risks
are projected if global warming exceeds 2ºC above pre-industrial temperature, combined with
other climate-related hazards (high confidence). Warm-water corals are at high risk already
and are projected to transition to very high risk even if global warming is limited to 1.5ºC
(very high confidence). {4.3.3, 5.3, 5.5, Figure SPM.3}
B.6.1 All coastal ecosystems assessed are projected to face increasing risk level, from moderate to
high risk under RCP2.6 to high to very high risk under RCP8.5 by 2100. Intertidal rocky shore ecosystems are projected
to be at very high risk by 2100 under RCP8.5 (medium confidence) due to exposure to warming, especially during
marine heatwaves, as well as to acidification, sea level rise, loss of calcifying species and biodiversity (high confidence).
Ocean acidification challenges these ecosystems and further limits their habitat suitability (medium confidence) by
inhibiting recovery through reduced calcification and enhanced bioerosion. The decline of kelp forests is projected to
continue in temperate regions due to warming, particularly under the projected intensification of marine heatwaves,
with high risk of local extinctions under RCP8.5 (medium confidence). {5.3, 5.3.5, 5.3.6, 5.3.7, 6.4.2, Figure SPM.3}
B.6.2 Seagrass meadows and saltmarshes and associated carbon stores are at moderate risk
at 1.5ºC global warming and increase with further warming (medium confidence). Globally, 20–90% of current coastal
wetlands are projected to be lost by 2100, depending on projected sea level rise, regional differences and wetland
types, especially where vertical growth is already constrained by reduced sediment supply and landward migration is
constrained by steep topography or human modification of shorelines (high confidence). {4.3.3, 5.3.2, Figure SPM.3,
SPM A.6.1}
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25
SPM
Summary for Policymakers
B.6.3 Ocean warming, sea level rise and tidal changes are projected to expand salinization and
hypoxia in estuaries (high confidence) with high risks for some biota leading to migration, reduced survival, and local
extinction under high emission scenarios (medium confidence). These impacts are projected to be more pronounced
in more vulnerable eutrophic and shallow estuaries with low tidal range in temperate and high latitude regions
(medium confidence). {5.2.2, 5.3.1, Figure SPM.3}
B.6.4 Almost all warm-water coral reefs are projected to suffer significant losses of area and
local extinctions, even if global warming is limited to 1.5ºC (high confidence). The species composition and diversity
of remaining reef communities is projected to differ from present-day reefs (very high confidence). {5.3.4, 5.4.1,
Figure SPM.3}
Projected Risks for People and Ecosystem Services
B.7 Future cryosphere changes on land are projected to affect water resources and their uses, such
as hydropower (high confidence) and irrigated agriculture in and downstream of high mountain
areas (medium confidence), as well as livelihoods in the Arctic (medium confidence). Changes
in floods, avalanches, landslides, and ground destabilization are projected to increase risk for
infrastructure, cultural, tourism, and recreational assets (medium confidence). {2.3, 2.3.1, 3.4.3}
B.7.1 Disaster risks to human settlements and livelihood options in high mountain areas and
the Arctic are expected to increase (medium confidence), due to future changes in hazards such as floods, fires,
landslides, avalanches, unreliable ice and snow conditions, and increased exposure of people and infrastructure (high
confidence). Current engineered risk reduction approaches are projected to be less effective as hazards change in
character (medium confidence). Significant risk reduction and adaptation strategies help avoid increased impacts
from mountain flood and landslide hazards as exposure and vulnerability are increasing in many mountain regions
during this century (high confidence). {2.3.2, 3.4.3, 3.5.2}
B.7.2 Permafrost thaw-induced subsidence of the land surface is projected to impact overlying
urban and rural communication and transportation infrastructure in the Arctic and in high mountain areas (medium
confidence). The majority of Arctic infrastructure is located in regions where permafrost thaw is projected to intensify
by mid-century. Retrofitting and redesigning infrastructure has the potential to halve the costs arising from permafrost
thaw and related climate-change impacts by 2100 (medium confidence). {2.3.4, 3.4.1, 3.4.3}
B.7.3 High mountain tourism, recreation and cultural assets are projected to be negatively affected
by future cryospheric changes (high confidence). Current snowmaking technologies are projected to be less effective
in reducing risks to ski tourism in a warmer climate in most parts of Europe, North America, and Japan, in particular
at 2ºC global warming and beyond (high confidence). {2.3.5, 2.3.6}
I
26
SPM
Summary for Policymakers
B.8 Future shifts in fish distribution and decreases in their abundance and fisheries catch potential
due to climate change are projected to affect income, livelihoods, and food security of marine
resource-dependent communities (medium confidence). Long-term loss and degradation of
marine ecosystems compromises the ocean’s role in cultural, recreational, and intrinsic values
important for human identity and well-being (medium confidence). {3.2.4, 3.4.3, 5.4.1, 5.4.2, 6.4}
B.8.1 Projected geographical shifts and decreases of global marine animal biomass and fish catch
potential are more pronounced under RCP8.5 relative to RCP2.6 elevating the risk for income and livelihoods of
dependent human communities, particularly in areas that are economically vulnerable (medium confidence). The
projected redistribution of resources and abundance increases the risk of conflicts among fisheries, authorities or
communities (medium confidence). Challenges to fisheries governance are widespread under RCP8.5 with regional
hotspots such as the Arctic and tropical Pacific Ocean (medium confidence). {3.5.2, 5.4.1, 5.4.2, 5.5.2, 5.5.3, 6.4.2,
Figure SPM.3}
B.8.2 The decline in warm-water coral reefs is projected to greatly compromise the services they
provide to society, such as food provision (high confidence), coastal protection (high confidence) and tourism
(medium confidence). Increases in the risks for seafood security (medium confidence) associated with decreases in
seafood availability are projected to elevate the risk to nutritional health in some communities highly dependent
on seafood (medium confidence), such as those in the Arctic, West Africa, and Small Island Developing States. Such
impacts compound any risks from other shifts in diets and food systems caused by social and economic changes and
climate change over land (medium confidence). {3.4.3, 5.4.2, 6.4.2}
B.8.3 Global warming compromises seafood safety (medium confidence) through human
exposure to elevated bioaccumulation of persistent organic pollutants and mercury in marine plants and animals
(medium confidence), increasing prevalence of waterborne Vibrio pathogens (medium confidence), and heightened
likelihood of harmful algal blooms (medium confidence). These risks are projected to be particularly large for human
communities with high consumption of seafood, including coastal Indigenous communities (medium confidence),
and for economic sectors such as fisheries, aquaculture, and tourism (high confidence). {3.4.3, 5.4.2, Box 5.3}
B.8.4 Climate change impacts on marine ecosystems and their services put key cultural dimensions
of lives and livelihoods at risk (medium confidence), including through shifts in the distribution or abundance of
harvested species and diminished access to fishing or hunting areas. This includes potentially rapid and irreversible
loss of culture and local knowledge and Indigenous knowledge, and negative impacts on traditional diets and food
security, aesthetic aspects, and marine recreational activities (medium confidence). {3.4.3, 3.5.3, 5.4.2}
27
SPM
Summary for Policymakers
B.9 Increased mean and extreme sea level, alongside ocean warming and acidification, are projected
to exacerbate risks for human communities in low-lying coastal areas (high confidence). In Arctic
human communities without rapid land uplift, and in urban atoll islands, risks are projected
to be moderate to high even under a low emissions scenario (RCP2.6) (medium confidence),
including reaching adaptation limits (high confidence). Under a high emissions scenario (RCP8.5),
delta regions and resource rich coastal cities are projected to experience moderate to high
risk levels after 2050 under current adaptation (medium confidence). Ambitious adaptation
including transformative governance is expected to reduce risk (high confidence), but with
context-specific benefits. {4.3.3, 4.3.4, SM4.3, 6.9.2, Cross-Chapter Box 9, Figure SPM.5}
B.9.1 In the absence of more ambitious adaptation efforts compared to today, and under current
trends of increasing exposure and vulnerability of coastal communities, risks, such as erosion and land loss, flooding,
salinization, and cascading impacts due to mean sea level rise and extreme events are projected to significantly
increase throughout this century under all greenhouse gas emissions scenarios (very high confidence). Under the
same assumptions, annual coastal flood damages are projected to increase by 2–3 orders of magnitude by 2100
compared to today (high confidence). {4.3.3, 4.3.4, Box 6.1, 6.8, SM.4.3, Figures SPM.4, SPM.5}
B.9.2 High to very high risks are approached for vulnerable communities in coral reef environments,
urban atoll islands and low-lying Arctic locations from sea level rise well before the end of this century in case of high
emissions scenarios. This entails adaptation limits being reached, which are the points at which an actor’s objectives
(or system needs) cannot be secured from intolerable risks through adaptive actions (high confidence). Reaching
adaptation limits (e.g., biophysical, geographical, financial, technical, social, political, and institutional) depends on the
emissions scenario and context-specific risk tolerance, and is projected to expand to more areas beyond 2100, due to the
long-term commitment of sea level rise (medium confidence). Some island nations are likely to become uninhabitable
due to climate-related ocean and cryosphere change (medium confidence), but habitability thresholds remain extremely
difficult to assess. {4.3.4, 4.4.2, 4.4.3, 5.5.2, Cross-Chapter Box 9, SM.4.3, SPM C.1, Glossary, Figure SPM.5}
B.9.3 Globally, a slower rate of climate-related ocean and cryosphere change provides greater
adaptation opportunities (high confidence). While there is high confidence that ambitious adaptation, including
governance for transformative change, has the potential to reduce risks in many locations, such benefits can vary
between locations. At global scale, coastal protection can reduce flood risk by 2–3 orders of magnitude during
the 21st century, but depends on investments on the order of tens to several hundreds of billions of US$ per year
(high confidence). While such investments are generally cost efficient for densely populated urban areas, rural and
poorer areas may be challenged to afford such investments with relative annual costs for some small island states
amounting to several percent of GDP (high confidence). Even with major adaptation efforts, residual risks and
associated losses are projected to occur (medium confidence), but context-specific limits to adaptation and residual
risks remain difficult to assess. {4.1.3, 4.2.2.4, 4.3.1, 4.3.2, 4.3.4., 4.4.3, 6.9.1, 6.9.2, Cross-Chapter Boxes 1–2 in
Chapter 1, SM.4.3, Figure SPM.5}
■
28
SPM
Summary for Policymakers
1/month
1/year
1/decade
1/century
1/month
1/year
1/decade
1/century
recent past future
mean sea level
mean sea level
sea
level
rise
2000
Year
2020 2040 2060 2080 2100
Time
Sea level height and recurrence frequency
HCE
Due to projected global mean sea level (GMSL) rise, local sea levels that historically occurred once per century
(historical centennial events, HCEs) are projected to become at least annual events at most locations during the
21st century. The height of a HCE varies widely, and depending on the level of exposure can already cause severe
impacts. Impacts can continue to increase with rising frequency of HCEs.
Historical Centennial extreme sea level
Events (HCEs) become more common
due to sea level rise
RCP8.5
RCP2.6
Black:
Locations where
HCEs already
recur annually
White:
Locations where
HCEs recur
annually after 2100
(b) Year when HCEs are projected to
recur once per year on average
(a) Schematic effect of regional sea level rise on
projected extreme sea level events (not to scale)
Difference
>10 years later
Difference
<10 years later
(c) Difference between RCP8.5 and RCP2.6
no relative sea level
rise before 2100
The difference map shows locations where the HCE
becomes annual at least 10 years later under RCP2.6
than under RCP8.5.
Extreme sea level events
Figure SPM.4 | The effect of regional sea level rise on extreme sea level events at coastal locations. (a) Schematic illustration of extreme sea level
events and their average recurrence in the recent past (1986–2005) and the future. As a consequence of mean sea level rise, local sea levels that
historically occurred once per century (historical centennial events, HCEs) are projected to recur more frequently in the future. (b) The year in which
HCEs are expected to recur once per year on average under RCP8.5 and RCP2.6, at the 439 individual coastal locations where the observational
record is sufficient. The absence of a circle indicates an inability to perform an assessment due to a lack of data but does not indicate absence of
exposure and risk. The darker the circle, the earlier this transition is expected. The likely range is ±10 years for locations where this transition is
expected before 2100. White circles (33% of locations under RCP2.6 and 10% under RCP8.5) indicate that HCEs are not expected to recur once per
year before 2100. (c) An indication at which locations this transition of HCEs to annual events is projected to occur more than 10 years later under
RCP2.6 compared to RCP8.5. As the scenarios lead to small differences by 2050 in many locations results are not shown here for RCP4.5 but they are
available in Chapter 4. {4.2.3, Figure 4.10, Figure 4.12}
_l _
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%
t
. .
( •. . e . . .. 9 ... ¢
o
9
e ==
."·
◊
29
SPM
Summary for Policymakers
C. Implementing Responses to Ocean and Cryosphere Change
Challenges
C.1 Impacts of climate-related changes in the ocean and cryosphere increasingly challenge current
governance efforts to develop and implement adaptation responses from local to global
scales, and in some cases pushing them to their limits. People with the highest exposure
and vulnerability are often those with lowest capacity to respond (high confidence). {1.5, 1.7,
Cross-Chapter Boxes 2–3 in Chapter 1, 2.3.1, 2.3.2, 2.3.3, 2.4, 3.2.4, 3.4.3, 3.5.2, 3.5.3, 4.1, 4.3.3,
4.4.3, 5.5.2, 5.5.3, 6.9}
C.1.1 The temporal scales of climate change impacts in ocean and cryosphere and their societal
consequences operate on time horizons which are longer than those of governance arrangements (e.g., planning cycles,
public and corporate decision making cycles, and financial instruments). Such temporal differences challenge the ability
of societies to adequately prepare for and respond to long-term changes including shifts in the frequency and intensity
of extreme events (high confidence). Examples include changing landslides and floods in high mountain regions and
risks to important species and ecosystems in the Arctic, as well as to low-lying nations and islands, small island nations,
other coastal regions and to coral reef ecosystems. {2.3.2, 3.5.2, 3.5.4, 4.4.3, 5.2, 5.3, 5.4, 5.5.1, 5.5.2, 5.5.3, 6.9}
C.1.2 Governance arrangements (e.g., marine protected areas, spatial plans and water management
systems) are, in many contexts, too fragmented across administrative boundaries and sectors to provide integrated
responses to the increasing and cascading risks from climate-related changes in the ocean and/or cryosphere (high
confidence). The capacity of governance systems in polar and ocean regions to respond to climate change impacts
has strengthened recently, but this development is not sufficiently rapid or robust to adequately address the scale
of increasing projected risks (high confidence). In high mountains, coastal regions and small islands, there are also
difficulties in coordinating climate adaptation responses, due to the many interactions of climatic and non-climatic
risk drivers (such as inaccessibility, demographic and settlement trends, or land subsidence caused by local activities)
across scales, sectors and policy domains (high confidence). {2.3.1, 3.5.3, 4.4.3, 5.4.2, 5.5.2, 5.5.3, Box 5.6, 6.9,
Cross-Chapter Box 3 in Chapter 1}
C.1.3 There are a broad range of identified barriers and limits for adaptation to climate change
in ecosystems (high confidence). Limitations include the space that ecosystems require, non-climatic drivers and
human impacts that need to be addressed as part of the adaptation response, the lowering of adaptive capacity
of ecosystems because of climate change, and the slower ecosystem recovery rates relative to the recurrence of
climate impacts, availability of technology, knowledge and financial support, and existing governance arrangements
(medium confidence). {3.5.4, 5.5.2}
C.1.4 Financial, technological, institutional and other barriers exist for implementing responses to
current and projected negative impacts of climate-related changes in the ocean and cryosphere, impeding resilience
building and risk reduction measures (high confidence). Whether such barriers reduce adaptation effectiveness or
correspond to adaptation limits depends on context specific circumstances, the rate and scale of climate changes
and on the ability of societies to turn their adaptive capacity into effective adaptation responses. Adaptive capacity
continues to differ between as well as within communities and societies (high confidence). People with highest
exposure and vulnerability to current and future hazards from ocean and cryosphere changes are often also those
with lowest adaptive capacity, particularly in low-lying islands and coasts, Arctic and high mountain regions with
development challenges (high confidence). {2.3.1, 2.3.2, 2.3.7, Box 2.4, 3.5.2, 4.3.4, 4.4.2, 4.4.3, 5.5.2, 6.9,
Cross-Chapter Boxes 2 and 3 in Chapter 1, Cross-Chapter Box 9}
30
SPM
Summary for Policymakers
Strengthening Response Options
C.2 The far-reaching services and options provided by ocean and cryosphere-related ecosystems
can be supported by protection, restoration, precautionary ecosystem-based management
of renewable resource use, and the reduction of pollution and other stressors (high
confidence). Integrated water management (medium confidence) and ecosystem-based
adaptation (high confidence) approaches lower climate risks locally and provide
multiple societal benefits. However, ecological, financial, institutional and governance
constraints for such actions exist (high confidence), and in many contexts ecosystem-based
adaptation will only be effective under the lowest levels of warming (high confidence).
{2.3.1, 2.3.3, 3.2.4, 3.5.2, 3.5.4, 4.4.2, 5.2.2, 5.4.2, 5.5.1, 5.5.2, Figure SPM.5}
C.2.1 Networks of protected areas help maintain ecosystem services, including carbon uptake
and storage, and enable future ecosystem-based adaptation options by facilitating the poleward and altitudinal
movements of species, populations, and ecosystems that occur in response to warming and sea level rise (medium
confidence). Geographic barriers, ecosystem degradation, habitat fragmentation and barriers to regional cooperation
limit the potential for such networks to support future species range shifts in marine, high mountain and polar land
regions (high confidence). {2.3.3, 3.2.3, 3.3.2, 3.5.4, 5.5.2, Box 3.4}
C.2.2 Terrestrial and marine habitat restoration, and ecosystem management tools such as assisted
species relocation and coral gardening, can be locally effective in enhancing ecosystem-based adaptation (high
confidence). Such actions are most successful when they are community-supported, are science-based whilst also
using local knowledge and Indigenous knowledge, have long-term support that includes the reduction or removal of
non-climatic stressors, and under the lowest levels of warming (high confidence). For example, coral reef restoration
options may be ineffective if global warming exceeds 1.5ºC, because corals are already at high risk (very high
confidence) at current levels of warming. {2.3.3, 4.4.2, 5.3.7, 5.5.1, 5.5.2, Box 5.5, Figure SPM.3}
C.2.3 Strengthening precautionary approaches, such as rebuilding overexploited or depleted
fisheries, and responsiveness of existing fisheries management strategies reduces negative climate change impacts
on fisheries, with benefits for regional economies and livelihoods (medium confidence). Fisheries management that
regularly assesses and updates measures over time, informed by assessments of future ecosystem trends, reduces risks
for fisheries (medium confidence) but has limited ability to address ecosystem change. {3.2.4, 3.5.2, 5.4.2, 5.5.2, 5.5.3,
Figure SPM.5}
C.2.4 Restoration of vegetated coastal ecosystems, such as mangroves, tidal marshes and seagrass
meadows (coastal ‘blue carbon’ ecosystems), could provide climate change mitigation through increased carbon
uptake and storage of around 0.5% of current global emissions annually (medium confidence). Improved protection
and management can reduce carbon emissions from these ecosystems. Together, these actions also have multiple
other benefits, such as providing storm protection, improving water quality, and benefiting biodiversity and fisheries
(high confidence). Improving the quantification of carbon storage and greenhouse gas fluxes of these coastal
ecosystems will reduce current uncertainties around measurement, reporting and verification (high confidence).
{Box 4.3, 5.4, 5.5.1, 5.5.2, Annex I: Glossary}
C.2.5 Ocean renewable energy can support climate change mitigation, and can comprise energy
extraction from offshore winds, tides, waves, thermal and salinity gradient and algal biofuels. The emerging demand
for alternative energy sources is expected to generate economic opportunities for the ocean renewable energy sector
(high confidence), although their potential may also be affected by climate change (low confidence). {5.4.2, 5.5.1,
Figure 5.23}
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Summary for Policymakers
C.2.6 Integrated water management approaches across multiple scales can be effective at
addressing impacts and leveraging opportunities from cryosphere changes in high mountain areas. These approaches
also support water resource management through the development and optimization of multi-purpose storage
and release of water from reservoirs (medium confidence), with consideration of potentially negative impacts to
ecosystems and communities. Diversification of tourism activities throughout the year supports adaptation in high
mountain economies (medium confidence). {2.3.1, 2.3.5}
C.3 Coastal communities face challenging choices in crafting context-specific and integrated
responses to sea level rise that balance costs, benefits and trade-offs of available options
and that can be adjusted over time (high confidence). All types of options, including
protection, accommodation, ecosystem-based adaptation, coastal advance and retreat,
wherever possible, can play important roles in such integrated responses (high confidence).
{4.4.2, 4.4.3, 4.4.4, 6.9.1, Cross-Chapter Box 9, Figure SPM.5}
C.3.1 The higher the sea levels rise, the more challenging is coastal protection, mainly due to
economic, financial and social barriers rather than due to technical limits (high confidence). In the coming decades,
reducing local drivers of exposure and vulnerability such as coastal urbanization and human-induced subsidence
constitute effective responses (high confidence). Where space is limited, and the value of exposed assets is high
(e.g., in cities), hard protection (e.g., dikes) is likely to be a cost-efficient response option during the 21st century
taking into account the specifics of the context (high confidence), but resource-limited areas may not be able to
afford such investments. Where space is available, ecosystem-based adaptation can reduce coastal risk and provide
multiple other benefits such as carbon storage, improved water quality, biodiversity conservation and livelihood
support (medium confidence). {4.3.2, 4.4.2, Box 4.1, Cross-Chapter Box 9, Figure SPM.5}
C.3.2 Some coastal accommodation measures, such as early warning systems and flood-proofing of
buildings, are often both low cost and highly cost-efficient under current sea levels (high confidence). Under projected
sea level rise and increase in coastal hazards some of these measures become less effective unless combined with
other measures (high confidence). All types of options, including protection, accommodation, ecosystem-based
adaptation, coastal advance and planned relocation, if alternative localities are available, can play important roles in
such integrated responses (high confidence). Where the community affected is small, or in the aftermath of a disaster,
reducing risk by coastal planned relocations is worth considering if safe alternative localities are available. Such
planned relocation can be socially, culturally, financially and politically constrained (very high confidence). {4.4.2,
Box 4.1, Cross-Chapter Box 9, SPM B.3}
C.3.3 Responses to sea level rise and associated risk reduction present society with profound
governance challenges, resulting from the uncertainty about the magnitude and rate of future sea level rise, vexing
trade-offs between societal goals (e.g., safety, conservation, economic development, intra- and inter-generational
equity), limited resources, and conflicting interests and values among diverse stakeholders (high confidence).
These challenges can be eased using locally appropriate combinations of decision analysis, land-use planning,
public participation, diverse knowledge systems and conflict resolution approaches that are adjusted over time as
circumstances change (high confidence). {Cross-Chapter Box 5 in Chapter 1, 4.4.3, 4.4.4, 6.9}
C.3.4 Despite the large uncertainties about the magnitude and rate of post 2050 sea level rise, many
coastal decisions with time horizons of decades to over a century are being made now (e.g., critical infrastructure,
coastal protection works, city planning) and can be improved by taking relative sea level rise into account, favouring
flexible responses (i.e., those that can be adapted over time) supported by monitoring systems for early warning
signals, periodically adjusting decisions (i.e., adaptive decision making), using robust decision-making approaches,
expert judgement, scenario-building, and multiple knowledge systems (high confidence). The sea level rise range
that needs to be considered for planning and implementing coastal responses depends on the risk tolerance of
I
32
SPM
Summary for Policymakers
stakeholders. Stakeholders with higher risk tolerance (e.g., those planning for investments that can be very easily
adapted to unforeseen conditions) often prefer to use the likely range of projections, while stakeholders with a lower
risk tolerance (e.g., those deciding on critical infrastructure) also consider global and local mean sea level above
the upper end of the likely range (globally 1.1 m under RCP8.5 by 2100) and from methods characterised by lower
confidence such as from expert elicitation. {1.8.1, 1.9.2, 4.2.3, 4.4.4, Figure 4.2, Cross-Chapter Box 5 in Chapter 1,
Figure SPM.5, SPM B.3}
Sea level rise risk and responses
(b) Benefits of responses to sea level rise and mitigation
Risk for illustrative geographies based on mean sea level changes (medium confidence)
The term response is used here instead of adaptation because some responses, such as retreat, may or may not be considered to be adaptation.
Present day Future
Level of
risk related
to sea level
Risk reduction
through mitigation
Total risk reduction
(mitigation + responses
to sea level rise)
Risk delay through
responses to sea level rise
Risk reduction
through responses
to sea level rise
Risk delay
through mitigation
0.5
1.0
0
In this assessment, the term response refers to in situ responses to sea level rise (hard engineered coastal defenses, restoration of degraded ecosystems,
subsidence limitation) and planned relocation. Planned relocation in this assessment refers to proactive managed retreat or resettlement only at a local scale, and
according to the specificities of a particular context (e.g., in urban atoll islands: within the island, in a neighbouring island or in artificially raised islands). Forced
displacement and international migration are not considered in this assessment.
The illustrative geographies are based on a limited number of case studies well covered by the peer reviewed literature. The realisation of risk will depend on
context specifities.
Sea level rise scenarios: RCP4.5 and RCP6.0 are not considered in this risk assessment because the literature underpinning this assessment is only available for
RCP2.6 and RCP8.5.
Arctic
communities
Urban
atoll islands
Resource-rich
coastal cities
Large tropical
agricultural deltas
Very high
High
Undetectable
Moderate
No-to-moderate
response
Maximum potential
response
Assessment
data (Chapter 4)
Interpolation
Low emission
scenario
(RCP2.6)
High emission
scenario
(RCP8.5)
Purple: Very high probability of severe impacts/risks
and the presence of significant irreversibility or the
persistence of climate-related hazards, combined with
limited ability to adapt due to the nature of the hazard
or impacts/risks.
Red: Significant and widespread impacts/risks.
Yellow: Impacts/risks are detectable and attributable
to climate change with at least medium confidence.
White: Impacts/risks are undetectable.
Total risk delay
(mitigation + responses
to sea level rise)
Global mean sea level rise in 2100 (metres)
Relative contribution of response options
to risk reduction (per geography)
(a) Risk in 2100 under different sea level rise and response scenarios
Levels of risk
Schematic illustration of risk reduction and the delay of
a given risk level through responses to sea level rise
and/or mitigation. The amount of risk reduction and
delay depends on sea level and response scenarios and
varies between contexts and localities.
= In situ
responses
= Planned
relocation
Figure SPM.5 | a, b
-
--- •
; '7 ii ' :% ; I E
; i
; ' #
('r p r -
le=.=
eel
33
SPM
Summary for Policymakers
Responses Potential
effectiveness
Hard
protection
Coral
conservation
Coral
restoration
Wetland
conservation
Wetland
restoration
Sediment–
based
protection
Advantages Co–benefits Drawbacks Economic
efficiency
Governance
challenges
Coastal
advance
Coastal
accommodation
in terms of reducing
sea level rise (SLR) risks
(technical/biophysical limits)
Often unaffordable for
poorer areas. Conflicts
between objectives
(e.g., conservation,
safety and tourism),
conflicts about the
distribution of public
budgets, lack of
finance {4.3.3.2,
4.4.2.2.6}
Permits for
implementation are
difficult to obtain. Lack
of finance. Lack of
enforcement of
conservation policies.
EbA options dismissed
due to short–term
economic interest,
availability of land
{4.4.2.3.6}
Often unaffordable for
poorer areas. Social
conflicts with regards
to access and
distribution of new
land {4.4.2.4.6}
Very high if land prices
are high as found in
many urban coasts
{4.4.2.4.7}
Groundwater salinisa–
tion, enhanced erosion
and loss of coastal
ecosystems and habitat
{4.4.2.4.5}
Generates land and
land sale revenues that
can be used to finance
adaptation {4.4.2.4.5}
Predictable levels of
safety {4.4.2.2.4}
Up to multiple metres
of SLR {4.4.2.2.4}
Early warning systems
require effective insti–
tutional arrangements
{4.4.2.6.6}
Very high for early
warning systems and
building–scale
measures {4.4.2.5.7}
Does not prevent
flooding/impacts
{4.4.2.5.5}
Maintains landscape
connectivity {4.4.2.5.5}
Mature technology;
sediments deposited
during floods can raise
elevation {4.4.2.5.5}
Very effective for small
SLR {4.4.2.5.4}
(Flood–proofing buildings,
early warning systems for
flood events, etc.)
Limited evidence on
benefit–cost ratios;
Depends on population
density and the
availability of land
{4.4.2.3.7}
Safety levels less
predictable,
development benefits
not realized {4.4.2.3.5,
4.4.2.3.2}
Long–term
effectiveness depends
on ocean warming,
acidification and
emission scenarios
{4.3.3.5.2., 4.4.2.3.2}
Safety levels less
predictable, a lot of
land required, barriers
for landward expan–
sion of ecosystems has
to be removed
{4.4.2.3.5, 4.4.2.3.2}
Habitat gain,
biodiversity, carbon
sequestration, income
from tourism,
enhanced fishery
productivity, improved
water quality.
Provision of food,
medicine, fuel, wood
and cultural benefits
{4.4.2.3.5}
Opportunity for
community
involvement,
{4.4.2.3.1}
Effective up to
0.5 cm yr–¹ SLR.
Strongly limited by
ocean warming and
acidification.
Constrained at 1.5°C
warming and lost at
2°C at many places.
{4.3.3.5.2, 4.4.2.3.2,
5.3.4}
Effective up to 0.5–1
cm yr–¹ SLR,
decreased at 2°C
{4.3.3.5.1, 4.4.2.3.2,
5.3.7}
(Marshes,
Mangroves)
(Marshes,
Mangroves)
High if the value
of assets behind
protection is high, as
found in many urban
and densely populated
coastal areas
{4.4.2.2.7}
Destruction of habitat
through coastal
squeeze, flooding &
erosion downdrift,
lock–in, disastrous
consequence in case
of defence failure
{4.3.2.4, 4.4.2.2.5}
Predictable levels of
safety {4.4.2.2.4}
Multifunctional dikes
such as for recreation,
or other land use
{4.4.2.2.5}
Up to multiple metres
of SLR {4.4.2.2.4}
Effective but depends
on sediment availability
{4.4.2.2.4}
High flexibility
{4.4.2.2.4}
Preservation of
beaches for recreation/
tourism {4.4.2.2.5}
Destruction of habitat,
where sediment is
sourced {4.4.2.2.5}
High if tourism
revenues are high
{4.4.2.2.7}
Conflicts about the
distribution of public
budgets {4.4.2.2.6}
Confidence levels (assessed for effectiveness):
The table illustrates responses and their characteristics. It is not exhaustive. Whether a response is applicable depends on geography and context.
= Very High = High = Medium = Low
(c) Responses to rising mean and extreme sea levels
Generic steps of adaptive decision making Enabling conditions
(d) Choosing and enabling sea level rise responses
Implementation Monitoring and
corrective action
Stage setting Dynamic plan • Long–term perspective
• Cross–scale coordination
• Address vulnerability and equity
• Inclusive public participation
• Capability to address complexity
Identify risks,
objectives, options,
uncertainties and
criteria for evaluating
options
Develop initial plan
(combinations of options over
time) plus corrective actions
to be carried out based on
observed situation
of initial plan and
monitoring system
for progressing
change and success
Monitor and take
corrective action upon
observed situation
Retreat Ecosystem based adaptation
Planned
relocation
Forced
displacement
Reconciling the
divergent interests
arising from relocating
people from point of
origin and destination
{4.4.2.6.6}
Raises complex
humanitarian
questions on
livelihoods, human
rights and equity
{4.4.2.6.6}
Limited evidence
[4.4.2.6.7}
Loss of social cohesion,
cultural identity and
well–being. Depressed
services (health,
education, housing),
job opportunities and
economic growth
{4.4.2.6.5}
Range from loss of life
to loss of livelihoods
and sovereignty
{4.4.2.6.5}
Access to improved
services (health,
education, housing),
job opportunities and
economic growth
{4.4.2.6.5}
Sea level risks at
origin can be
eliminated {4.4.2.6.4}
Effective if alternative
safe localities are
available {4.4.2.6.4}
Addresses only
immediate risk at place
of origin
Not applicable Not applicable Not applicable
(beyond risk reduction)
Figure SPM.5 | c, d
34
SPM
Summary for Policymakers
Figure SPM.5 | Sea level rise risks and responses. The term response is used here instead of adaptation because some responses, such as retreat,
may or may not be considered to be adaptation. (a) shows the combined risk of coastal flooding, erosion and salinization for illustrative geographies
in 2100, due to changing mean and extreme sea levels under RCP2.6 and RCP8.5 and under two response scenarios. Risks under RCPs 4.5 and 6.0
were not assessed due to a lack of literature for the assessed geographies. The assessment does not account for changes in extreme sea level beyond
those directly induced by mean sea level rise; risk levels could increase if other changes in extreme sea levels were considered (e.g., due to changes
in cyclone intensity). Panel a) considers a socioeconomic scenario with relatively stable coastal population density over the century. {SM4.3.2} Risks to
illustrative geographies have been assessed based on relative sea level changes projected for a set of specific examples: New York City, Shanghai and
Rotterdam for resource-rich coastal cities covering a wide range of response experiences; South Tarawa, Fongafale and Male’ for urban atoll islands;
Mekong and Ganges-Brahmaputra-Meghna for large tropical agricultural deltas; and Bykovskiy, Shishmaref, Kivalina, Tuktoyaktuk and Shingle Point
for Arctic communities located in regions remote from rapid glacio-isostatic adjustment. {4.2, 4.3.4, SM4.2} The assessment distinguishes between
two contrasting response scenarios. “No-to-moderate response” describes efforts as of today (i.e., no further significant action or new types of
actions). “Maximum potential response” represents a combination of responses implemented to their full extent and thus significant additional efforts
compared to today, assuming minimal financial, social and political barriers. The assessment has been conducted for each sea level rise and response
scenario, as indicated by the burning embers in the figure; in-between risk levels are interpolated. {4.3.3} The assessment criteria include exposure
and vulnerability (density of assets, level of degradation of terrestrial and marine buffer ecosystems), coastal hazards (flooding, shoreline erosion,
salinization), in-situ responses (hard engineered coastal defenses, ecosystem restoration or creation of new natural buffers areas, and subsidence
management) and planned relocation. Planned relocation refers to managed retreat or resettlement as described in Chapter 4, i.e., proactive and
local-scale measures to reduce risk by relocating people, assets and infrastructure. Forced displacement is not considered in this assessment. Panel (a)
also highlights the relative contributions of in-situ responses and planned relocation to the total risk reduction. (b) schematically illustrates the risk
reduction (vertical arrows) and risk delay (horizontal arrows) through mitigation and/or responses to sea level rise. (c) summarizes and assesses
responses to sea level rise in terms of their effectiveness, costs, co-benefits, drawbacks, economic efficiency and associated governance challenges.
{4.4.2} (d) presents generic steps of an adaptive decision-making approach, as well as key enabling conditions for responses to sea level rise.
{4.4.4, 4.4.5}
Enabling Conditions
C.4 Enabling climate resilience and sustainable development depends critically on urgent
and ambitious emissions reductions coupled with coordinated sustained and increasingly
ambitious adaptation actions (very high confidence). Key enablers for implementing effective
responses to climate-related changes in the ocean and cryosphere include intensifying
cooperation and coordination among governing authorities across spatial scales and planning
horizons. Education and climate literacy, monitoring and forecasting, use of all available
knowledge sources, sharing of data, information and knowledge, finance, addressing social
vulnerability and equity, and institutional support are also essential. Such investments
enable capacity-building, social learning, and participation in context-specific adaptation, as
well as the negotiation of trade-offs and realisation of co-benefits in reducing short-term
risks and building long-term resilience and sustainability. (high confidence). This report
reflects the state of science for ocean and cryosphere for low levels of global warming
(1.5ºC), as also assessed in earlier IPCC and IPBES reports. {1.1, 1.5, 1.8.3, 2.3.1, 2.3.2, 2.4,
Figure 2.7, 2.5, 3.5.2, 3.5.4, 4.4, 5.2.2, Box 5.3, 5.4.2, 5.5.2, 6.4.3, 6.5.3, 6.8, 6.9, Cross-Chapter
Box 9, Figure SPM.5}
C.4.1 In light of observed and projected changes in the ocean and cryosphere, many nations will
face challenges to adapt, even with ambitious mitigation (very high confidence). In a high emissions scenario, many
ocean- and cryosphere-dependent communities are projected to face adaptation limits (e.g. biophysical, geographical,
financial, technical, social, political and institutional) during the second half of the 21st century. Low emission
pathways, for comparison, limit the risks from ocean and cryosphere changes in this century and beyond and enable
more effective responses (high confidence), whilst also creating co-benefits. Profound economic and institutional
transformative change will enable Climate Resilient Development Pathways in the ocean and cryosphere context
(high confidence). {1.1, 1.4–1.7, Cross-Chapter Boxes 1–3 in Chapter 1, 2.3.1, 2.4, Box 3.2, Figure 3.4, Cross-Chapter
Box 7 in Chapter 3, 3.4.3, 4.2.2, 4.2.3, 4.3.4, 4.4.2, 4.4.3, 4.4.6, 5.4.2, 5.5.3, 6.9.2, Cross-Chapter Box 9, Figure
SPM.5}
C.4.2 Intensifying cooperation and coordination among governing authorities across scales,
jurisdictions, sectors, policy domains and planning horizons can enable effective responses to changes in the ocean,
cryosphere and to sea level rise (high confidence). Regional cooperation, including treaties and conventions, can
support adaptation action; however, the extent to which responding to impacts and losses arising from changes
35
SPM
Summary for Policymakers
in the ocean and cryosphere is enabled through regional policy frameworks is currently limited (high confidence).
Institutional arrangements that provide strong multiscale linkages with local and Indigenous communities benefit
adaptation (high confidence). Coordination and complementarity between national and transboundary regional
policies can support efforts to address risks to resource security and management, such as water and fisheries
(medium confidence). {2.3.1, 2.3.2, 2.4, Box 2.4, 2.5, 3.5.2, 3.5.3, 3.5.4, 4.4.4, 4.4.5, Table 4.9, 5.5.2, 6.9.2}
C.4.3 Experience to date – for example, in responding to sea level rise, water-related risks in some
high mountains, and climate change risks in the Arctic – also reveal the enabling influence of taking a long-term
perspective when making short-term decisions, explicitly accounting for uncertainty of context-specific risks
beyond 2050 (high confidence), and building governance capabilities to tackle complex risks (medium confidence).
{2.3.1, 3.5.4, 4.4.4, 4.4.5, Table 4.9, 5.5.2, 6.9, Figure SPM.5}
C.4.4 Investments in education and capacity building at various levels and scales facilitates
social learning and long-term capability for context-specific responses to reduce risk and enhance resilience (high
confidence). Specific activities include utilization of multiple knowledge systems and regional climate information
into decision making, and the engagement of local communities, Indigenous peoples, and relevant stakeholders in
adaptive governance arrangements and planning frameworks (medium confidence). Promotion of climate literacy and
drawing on local, Indigenous and scientific knowledge systems enables public awareness, understanding and social
learning about locality-specific risk and response potential (high confidence). Such investments can develop, and in
many cases transform existing institutions and enable informed, interactive and adaptive governance arrangements
(high confidence). {1.8.3, 2.3.2, Figure 2.7, Box 2.4, 2.4, 3.5.2, 3.5.4, 4.4.4, 4.4.5, Table 4.9, 5.5.2, 6.9}
C.4.5 Context-specific monitoring and forecasting of changes in the ocean and the cryosphere
informs adaptation planning and implementation, and facilitates robust decisions on trade-offs between short- and
long-term gains (medium confidence). Sustained long-term monitoring, sharing of data, information and knowledge
and improved context-specific forecasts, including early warning systems to predict more extreme El Niño/La Niña
events, tropical cyclones, and marine heatwaves, help to manage negative impacts from ocean changes such as losses
in fisheries, and adverse impacts on human health, food security, agriculture, coral reefs, aquaculture, wildfire, tourism,
conservation, drought and flood (high confidence). {2.4, 2.5, 3.5.2, 4.4.4, 5.5.2, 6.3.1, 6.3.3, 6.4.3, 6.5.3, 6.9}
C.4.6 Prioritising measures to address social vulnerability and equity underpins efforts to promote
fair and just climate resilience and sustainable development (high confidence), and can be helped by creating safe
community settings for meaningful public participation, deliberation and conflict resolution (medium confidence).
{Box 2.4, 4.4.4, 4.4.5, Table 4.9, Figure SPM.5}
C.4.7 This assessment of the ocean and cryosphere in a changing climate reveals the benefits of
ambitious mitigation and effective adaptation for sustainable development and, conversely, the escalating costs and
risks of delayed action. The potential to chart Climate Resilient Development Pathways varies within and among
ocean, high mountain and polar land regions. Realising this potential depends on transformative change. This
highlights the urgency of prioritising timely, ambitious, coordinated and enduring action (very high confidence).
{1.1, 1.8, Cross-Chapter Box 1 in Chapter 1, 2.3, 2.4, 3.5, 4.2.1, 4.2.2, 4.3.4, 4.4, Table 4.9, 5.5, 6.9, Cross-Chapter
Box 9, Figure SPM.5}
Summary for
Policymakers
SPM
3
Drafting Authors:
Richard P. Allan (United Kingdom), Paola A. Arias (Colombia), Sophie Berger (France/Belgium), Josep G.
Canadell (Australia), Christophe Cassou (France), Deliang Chen (Sweden), Annalisa Cherchi (Italy), Sarah
L. Connors (France/United Kingdom), Erika Coppola (Italy), Faye Abigail Cruz (Philippines), Aïda Diongue-
Niang (Senegal), Francisco J. Doblas-Reyes (Spain), Hervé Douville (France), Fatima Driouech (Morocco),
Tamsin L. Edwards (United Kingdom), François Engelbrecht (South Africa), Veronika Eyring (Germany),
Erich Fischer (Switzerland), Gregory M. Flato (Canada), Piers Forster (United Kingdom), Baylor Fox-
Kemper (United States of America), Jan S. Fuglestvedt (Norway), John C. Fyfe (Canada), Nathan P. Gillett
(Canada), Melissa I. Gomis (France/Switzerland), Sergey K. Gulev (Russian Federation), José Manuel
Gutiérrez (Spain), Rafiq Hamdi (Belgium), Jordan Harold (United Kingdom), Mathias Hauser (Switzerland),
Ed Hawkins (United Kingdom), Helene T. Hewitt (United Kingdom), Tom Gabriel Johansen (Norway),
Christopher Jones (United Kingdom), Richard G. Jones (United Kingdom), Darrell S. Kaufman (United
States of America), Zbigniew Klimont (Austria/Poland), Robert E. Kopp (United States of America), Charles
Koven (United States of America), Gerhard Krinner (France/Germany, France), June-Yi Lee (Republic of
Korea), Irene Lorenzoni (United Kingdom/Italy), Jochem Marotzke (Germany), Valérie Masson-Delmotte
(France), Thomas K. Maycock (United States of America), Malte Meinshausen (Australia/Germany), Pedro
M.S. Monteiro (South Africa), Angela Morelli (Norway/Italy), Vaishali Naik (United States of America),
Dirk Notz (Germany), Friederike Otto (United Kingdom/Germany), Matthew D. Palmer (United Kingdom),
Izidine Pinto (South Africa/Mozambique), Anna Pirani (Italy), Gian-Kasper Plattner (Switzerland),
Krishnan Raghavan (India), Roshanka Ranasinghe (The Netherlands/Sri Lanka, Australia), Joeri Rogelj
(United Kingdom/Belgium), Maisa Rojas (Chile), Alex C. Ruane (United States of America), Jean-Baptiste
Sallée (France), Bjørn H. Samset (Norway), Sonia I. Seneviratne (Switzerland), Jana Sillmann (Norway/
Germany), Anna A. Sörensson (Argentina), Tannecia S. Stephenson (Jamaica), Trude Storelvmo (Norway),
Sophie Szopa (France), Peter W. Thorne (Ireland/United Kingdom), Blair Trewin (Australia), Robert Vautard
(France), Carolina Vera (Argentina), Noureddine Yassaa (Algeria), Sönke Zaehle (Germany), Panmao Zhai
(China), Xuebin Zhang (Canada), Kirsten Zickfeld (Canada/Germany)
Contributing Authors:
Krishna M. AchutaRao (India), Bhupesh Adhikary (Nepal), Edvin Aldrian (Indonesia), Kyle Armour (United
States of America), Govindasamy Bala (India/United States of America), Rondrotiana Barimalala (South
Africa/Madagascar), Nicolas Bellouin (United Kingdom/France), William Collins (United Kingdom),
William D. Collins (United States of America), Susanna Corti (Italy), Peter M. Cox (United Kingdom),
Frank J. Dentener (EU/The Netherlands), Claudine Dereczynski (Brazil), Alejandro Di Luca (Australia,
Canada/Argentina), Alessandro Dosio (Italy), Leah Goldfarb (France/United States of America), Irina
V. Gorodetskaya (Portugal/Belgium, Russian Federation), Pandora Hope (Australia), Mark Howden
(Australia), A.K.M Saiful Islam (Bangladesh), Yu Kosaka (Japan), James Kossin (United States of America),
Svitlana Krakovska (Ukraine), Chao Li (China), Jian Li (China), Thorsten Mauritsen (Germany/Denmark),
Sebastian Milinski (Germany), Seung-Ki Min (Republic of Korea), Thanh Ngo Duc (Vietnam), Andy
Reisinger (New Zealand), Lucas Ruiz (Argentina), Shubha Sathyendranath (United Kingdom/Canada,
Overseas Citizen of India), Aimée B. A. Slangen (The Netherlands), Chris Smith (United Kingdom), Izuru
Takayabu (Japan), Muhammad Irfan Tariq (Pakistan), Anne-Marie Treguier (France), Bart van den Hurk
(The Netherlands), Karina von Schuckmann (France/Germany), Cunde Xiao (China)
This Summary for Policymakers should be cited as:
IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I
to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L.
Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K.
Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.
Summary for
Policymakers
4
SPM
Summary for Policymakers
Introduction
1 Decision IPCC/XLVI-2.
2 The three Special Reports are: Global Warming of 1.5°C: An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse
gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty (SR1.5);
Climate Change and Land: An IPCC Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in
terrestrial ecosystems (SRCCL); IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC).
3 The assessment covers scientific literature accepted for publication by 31 January 2021.
4 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high,
and typeset in italics, for example, medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or result: virtually certain 99–100%
probability; very likely 90–100%; likely 66–100%; about as likely as not 33–66%; unlikely 0–33%; very unlikely 0–10%; and exceptionally unlikely 0–1%. Additional terms
(extremely likely 95–100%; more likely than not >50–100%; and extremely unlikely 0–5%) are also used when appropriate. Assessed likelihood is typeset in italics, for example,
very likely. This is consistent with AR5. In this Report, unless stated otherwise, square brackets [x to y] are used to provide the assessed very likely range, or 90% interval.
5 The Interactive Atlas is available at https://interactive-atlas.ipcc.ch
6 Other GHG concentrations in 2019 were: perfluorocarbons (PFCs) – 109 parts per trillion (ppt) CF4 equivalent; sulphur hexafluoride (SF6) – 10 ppt; nitrogen trifluoride (NF3) – 2 ppt;
hydrofluorocarbons (HFCs) – 237 ppt HFC-134a equivalent; other Montreal Protocol gases (mainly chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs)) – 1032 ppt
CFC-12 equivalent). Increases from 2011 are 19 ppm for CO2, 63 ppb for CH4 and 8 ppb for N2O.
7 Land and ocean are not substantial sinks for other GHGs.
This Summary for Policymakers (SPM) presents key findings of the Working Group I (WGI) contribution to the Intergovernmental
Panel on Climate Change (IPCC) Sixth Assessment Report (AR6)1 on the physical science basis of climate change. The report builds
upon the 2013 Working Group I contribution to the IPCC’s Fifth Assessment Report (AR5) and the 2018–2019 IPCC Special Reports2
of the AR6 cycle and incorporates subsequent new evidence from climate science.3
This SPM provides a high-level summary of the understanding of the current state of the climate, including how it is changing and the
role of human influence, the state of knowledge about possible climate futures, climate information relevant to regions and sectors,
and limiting human-induced climate change.
Based on scientific understanding, key findings can be formulated as statements of fact or associated with an assessed level of
confidence indicated using the IPCC calibrated language.4
The scientific basis for each key finding is found in chapter sections of the main Report and in the integrated synthesis presented
in the Technical Summary (hereafter TS), and is indicated in curly brackets. The AR6 WGI Interactive Atlas facilitates exploration of
these key synthesis findings, and supporting climate change information, across the WGI reference regions.5
A. The Current State of the Climate
Since AR5, improvements in observationally based estimates and information from paleoclimate archives provide a comprehensive
view of each component of the climate system and its changes to date. New climate model simulations, new analyses, and methods
combining multiple lines of evidence lead to improved understanding of human influence on a wider range of climate variables,
including weather and climate extremes. The time periods considered throughout this section depend upon the availability of
observational products, paleoclimate archives and peer-reviewed studies.
A.1 It is unequivocal that human influence has warmed the atmosphere, ocean and land. Widespread and rapid
changes in the atmosphere, ocean, cryosphere and biosphere have occurred.
{2.2, 2.3, Cross-Chapter Box 2.3, 3.3, 3.4, 3.5, 3.6, 3.8, 5.2, 5.3, 6.4, 7.3, 8.3, 9.2, 9.3, 9.5, 9.6, Cross-Chapter
Box 9.1} (Figure SPM.1, Figure SPM.2)
A.1.1 Observed increases in well-mixed greenhouse gas (GHG) concentrations since around 1750 are unequivocally caused
by human activities. Since 2011 (measurements reported in AR5), concentrations have continued to increase in the
atmosphere, reaching annual averages of 410 parts per million (ppm) for carbon dioxide (CO2), 1866 parts per billion
(ppb) for methane (CH4), and 332 ppb for nitrous oxide (N2O) in 2019.6 Land and ocean have taken up a near-constant
proportion (globally about 56% per year) of CO2 emissions from human activities over the past six decades, with regional
differences (high confidence).7
{2.2, 5.2, 7.3, TS.2.2, Box TS.5}
5
SPM
Summary for Policymakers
A.1.2 Each of the last four decades has been successively warmer than any decade that preceded it since 1850. Global
surface temperature8 in the first two decades of the 21st century (2001–2020) was 0.99 [0.84 to 1.10] °C higher than
1850–1900.9 Global surface temperature was 1.09 [0.95 to 1.20] °C higher in 2011–2020 than 1850–1900, with larger
increases over land (1.59 [1.34 to 1.83] °C) than over the ocean (0.88 [0.68 to 1.01] °C). The estimated increase in
global surface temperature since AR5 is principally due to further warming since 2003–2012 (+0.19 [0.16 to 0.22] °C).
Additionally, methodological advances and new datasets contributed approximately 0.1°C to the updated estimate of
warming in AR6.10
{2.3, Cross-Chapter Box 2.3} (Figure SPM.1)
A.1.3 The likely range of total human-caused global surface temperature increase from 1850–1900 to 2010–201911 is 0.8°C to
1.3°C, with a best estimate of 1.07°C. It is likely that well-mixed GHGs contributed a warming of 1.0°C to 2.0°C, other
human drivers (principally aerosols) contributed a cooling of 0.0°C to 0.8°C, natural drivers changed global surface
temperature by –0.1°C to +0.1°C, and internal variability changed it by –0.2°C to +0.2°C. It is very likely that well-mixed
GHGs were the main driver12 of tropospheric warming since 1979 and extremely likely that human-caused stratospheric
ozone depletion was the main driver of cooling of the lower stratosphere between 1979 and the mid-1990s.
{3.3, 6.4, 7.3, TS.2.3, Cross-Section Box TS.1} (Figure SPM.2)
A.1.4 Globally averaged precipitation over land has likely increased since 1950, with a faster rate of increase since the 1980s
(medium confidence). It is likely that human influence contributed to the pattern of observed precipitation changes
since the mid-20th century and extremely likely that human influence contributed to the pattern of observed changes
in near-surface ocean salinity. Mid-latitude storm tracks have likely shifted poleward in both hemispheres since the
1980s, with marked seasonality in trends (medium confidence). For the Southern Hemisphere, human influence very likely
contributed to the poleward shift of the closely related extratropical jet in austral summer.
{2.3, 3.3, 8.3, 9.2, TS.2.3, TS.2.4, Box TS.6}
A.1.5 Human influence is very likely the main driver of the global retreat of glaciers since the 1990s and the decrease in Arctic
sea ice area between 1979–1988 and 2010–2019 (decreases of about 40% in September and about 10% in March). There
has been no significant trend in Antarctic sea ice area from 1979 to 2020 due to regionally opposing trends and large
internal variability. Human influence very likely contributed to the decrease in Northern Hemisphere spring snow cover
since 1950. It is very likely that human influence has contributed to the observed surface melting of the Greenland Ice
Sheet over the past two decades, but there is only limited evidence, with medium agreement, of human influence on the
Antarctic Ice Sheet mass loss.
{2.3, 3.4, 8.3, 9.3, 9.5, TS.2.5}
A.1.6 It is virtually certain that the global upper ocean (0–700 m) has warmed since the 1970s and extremely likely that human
influence is the main driver. It is virtually certain that human-caused CO2 emissions are the main driver of current global
acidification of the surface open ocean. There is high confidence that oxygen levels have dropped in many upper ocean
regions since the mid-20th century and medium confidence that human influence contributed to this drop.
{2.3, 3.5, 3.6, 5.3, 9.2, TS.2.4}
A.1.7 Global mean sea level increased by 0.20 [0.15 to 0.25] m between 1901 and 2018. The average rate of sea level rise was
1.3 [0.6 to 2.1] mm yr–1 between 1901 and 1971, increasing to 1.9 [0.8 to 2.9] mm yr–1 between 1971 and 2006, and
further increasing to 3.7 [3.2 to 4.2] mm yr–1 between 2006 and 2018 (high confidence). Human influence was very likely
the main driver of these increases since at least 1971.
{2.3, 3.5, 9.6, Cross-Chapter Box 9.1, Box TS.4}
8 The term ‘global surface temperature’ is used in reference to both global mean surface temperature and global surface air temperature throughout this SPM. Changes in these
quantities are assessed with high confidence to differ by at most 10% from one another, but conflicting lines of evidence lead to low confidence in the sign (direction) of any
difference in long-term trend. {Cross-Section Box TS.1}
9 The period 1850–1900 represents the earliest period of sufficiently globally complete observations to estimate global surface temperature and, consistent with AR5 and SR1.5, is
used as an approximation for pre-industrial conditions.
10 Since AR5, methodological advances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These
and other improvements have also increased the estimate of global surface temperature change by approximately 0.1°C, but this increase does not represent additional physical
warming since AR5.
11 The period distinction with A.1.2 arises because the attribution studies consider this slightly earlier period. The observed warming to 2010–2019 is 1.06 [0.88 to 1.21] °C.
12 Throughout this SPM, ‘main driver’ means responsible for more than 50% of the change.
6
SPM
Summary for Policymakers
A.1.8 Changes in the land biosphere since 1970 are consistent with global warming: climate zones have shifted poleward in
both hemispheres, and the growing season has on average lengthened by up to two days per decade since the 1950s
in the Northern Hemisphere extratropics (high confidence).
{2.3, TS.2.6}
Figure SPM.1 | History of global temperature change and causes of recent warming
Panel (a) Changes in global surface temperature reconstructed from paleoclimate archives (solid grey line, years 1–2000) and from direct
observations (solid black line, 1850–2020), both relative to 1850–1900 and decadally averaged. The vertical bar on the left shows the estimated temperature
(very likely range) during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago during the current interglacial
period (Holocene). The Last Interglacial, around 125,000 years ago, is the next most recent candidate for a period of higher temperature. These past warm periods
were caused by slow (multi-millennial) orbital variations. The grey shading with white diagonal lines shows the very likely ranges for the temperature reconstructions.
Panel (b) Changes in global surface temperature over the past 170 years (black line) relative to 1850–1900 and annually averaged, compared to
Coupled Model Intercomparison Project Phase 6 (CMIP6) climate model simulations (see Box SPM.1) of the temperature response to both human and natural
drivers (brown) and to only natural drivers (solar and volcanic activity, green). Solid coloured lines show the multi-model average, and coloured shades show the
very likely range of simulations. (See Figure SPM.2 for the assessed contributions to warming).
{2.3.1; Cross-Chapter Box 2.3; 3.3; TS.2.2; Cross-Section Box TS.1, Figure 1a}
Human influence has warmed the climate at a rate that is unprecedented
in at least the last 2000 years
Changes in global surface temperature relative to 1850–1900
1850 1900 1950 2000 2020
ºC
–0.5
0.0
0.5
1.0
1.5
2.0
observed
simulated
human &
natural
simulated
natural only
(solar &
volcanic)
(b) Change in global surface temperature (annual average) as observed and
simulated using human & natural and only natural factors (both 1850–2020)
(a) Change in global surface temperature (decadal average)
as reconstructed (1–2000) and observed (1850–2020)
Warmest multi-century
period in more than
100,000 years
Warming is unprecedented
in more than 2000 years
reconstructed
–0.5
–1
0.0
0.5
1.0
1.5
2.0
ºC
1 500 1000 1500 1850 2020
observed
1.0
0.2
\
. . I' I
7
SPM
Summary for Policymakers
Figure SPM.2 | Assessed contributions to observed warming in 2010–2019 relative to 1850–1900
Panel (a) Observed global warming (increase in global surface temperature). Whiskers show the very likely range.
Panel (b) Evidence from attribution studies, which synthesize information from climate models and observations. The panel shows temperature
change attributed to: total human influence; changes in well-mixed greenhouse gas concentrations; other human drivers due to aerosols, ozone and land-use
change (land-use reflectance); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges.
Panel (c) Evidence from the assessment of radiative forcing and climate sensitivity. The panel shows temperature changes from individual components
of human influence: emissions of greenhouse gases, aerosols and their precursors; land-use changes (land-use reflectance and irrigation); and aviation contrails.
Whiskers show very likely ranges. Estimates account for both direct emissions into the atmosphere and their effect, if any, on other climate drivers. For aerosols,
both direct effects (through radiation) and indirect effects (through interactions with clouds) are considered.
{Cross-Chapter Box 2.3, 3.3.1, 6.4.2, 7.3}
Observed warming is driven by emissions from human activities, with
greenhouse gas warming partly masked by aerosol cooling
ºC
–0.5
–1.0
0.0
0.5
1.0
1.5
2.0
ºC
–0.5
–1.0
0.0
0.5
1.0
1.5
2.0
ºC
–0.5
–1.0
0.0
0.5
1.0
1.5
2.0
Halogenated gases
Nitrogen oxides
Sulphur dioxide
Volatile organic compounds
and carbon monoxide
Organic carbon
Black carbon
Ammonia
Land-use reflectance
and irrigation
Aviation contrails
Total human influence
Well-mixed greenhouse gases
Other human drivers
Solar and volcanic drivers
Internal variability
Carbon dioxide
Methane
Nitrous oxide
Mainly contribute to
changes in
non-CO₂ greenhouse gases
Mainly contribute to
changes in
anthropogenic aerosols
(b) Aggregated contributions to
2010–2019 warming relative to
1850–1900, assessed from
attribution studies
(a) Observed warming
2010–2019 relative to
1850–1900
Observed warming Contributions to warming based on two complementary approaches
(c) Contributions to 2010–2019
warming relative to 1850–1900,
assessed from radiative
forcing studies
LJ
8
SPM
Summary for Policymakers
A.2 The scale of recent changes across the climate system as a whole – and the present state of many aspects of
the climate system – are unprecedented over many centuries to many thousands of years.
{2.2, 2.3, Cross-Chapter Box 2.1, 5.1} (Figure SPM.1)
A.2.1 In 2019, atmospheric CO2 concentrations were higher than at any time in at least 2 million years (high confidence), and
concentrations of CH4 and N2O were higher than at any time in at least 800,000 years (very high confidence). Since 1750,
increases in CO2 (47%) and CH4 (156%) concentrations far exceed – and increases in N2O (23%) are similar to – the natural
multi-millennial changes between glacial and interglacial periods over at least the past 800,000 years (very high confidence).
{2.2, 5.1, TS.2.2}
A.2.2 Global surface temperature has increased faster since 1970 than in any other 50-year period over at least the last 2000
years (high confidence). Temperatures during the most recent decade (2011–2020) exceed those of the most recent
multi-century warm period, around 6500 years ago13 [0.2°C to 1°C relative to 1850–1900] (medium confidence). Prior
to that, the next most recent warm period was about 125,000 years ago, when the multi-century temperature [0.5°C to
1.5°C relative to 1850–1900] overlaps the observations of the most recent decade (medium confidence).
{2.3, Cross-Chapter Box 2.1, Cross-Section Box TS.1} (Figure SPM.1)
A.2.3 In 2011–2020, annual average Arctic sea ice area reached its lowest level since at least 1850 (high confidence). Late
summer Arctic sea ice area was smaller than at any time in at least the past 1000 years (medium confidence). The global
nature of glacier retreat since the 1950s, with almost all of the world’s glaciers retreating synchronously, is unprecedented
in at least the last 2000 years (medium confidence).
{2.3, TS.2.5}
A.2.4 Global mean sea level has risen faster since 1900 than over any preceding century in at least the last 3000 years (high
confidence). The global ocean has warmed faster over the past century than since the end of the last deglacial transition
(around 11,000 years ago) (medium confidence). A long-term increase in surface open ocean pH occurred over the past
50 million years (high confidence). However, surface open ocean pH as low as recent decades is unusual in the last
2 million years (medium confidence).
{2.3, TS.2.4, Box TS.4}
A.3 Human-induced climate change is already affecting many weather and climate extremes in every region
across the globe. Evidence of observed changes in extremes such as heatwaves, heavy precipitation, droughts,
and tropical cyclones, and, in particular, their attribution to human influence, has strengthened since AR5.
{2.3, 3.3, 8.2, 8.3, 8.4, 8.5, 8.6, Box 8.1, Box 8.2, Box 9.2, 10.6, 11.2, 11.3, 11.4, 11.6, 11.7, 11.8, 11.9, 12.3}
(Figure SPM.3)
A.3.1 It is virtually certain that hot extremes (including heatwaves) have become more frequent and more intense across most
land regions since the 1950s, while cold extremes (including cold waves) have become less frequent and less severe, with
high confidence that human-induced climate change is the main driver14 of these changes. Some recent hot extremes
observed over the past decade would have been extremely unlikely to occur without human influence on the climate
system. Marine heatwaves have approximately doubled in frequency since the 1980s (high confidence), and human
influence has very likely contributed to most of them since at least 2006.
{Box 9.2, 11.2, 11.3, 11.9, TS.2.4, TS.2.6, Box TS.10} (Figure SPM.3)
A.3.2 The frequency and intensity of heavy precipitation events have increased since the 1950s over most land area for which
observational data are sufficient for trend analysis (high confidence), and human-induced climate change is likely the
main driver. Human-induced climate change has contributed to increases in agricultural and ecological droughts15 in some
regions due to increased land evapotranspiration16 (medium confidence).
{8.2, 8.3, 11.4, 11.6, 11.9, TS.2.6, Box TS.10} (Figure SPM.3)
13 As stated in section B.1, even under the very low emissions scenario SSP1-1.9, temperatures are assessed to remain elevated above those of the most recent decade until at least
2100 and therefore warmer than the century-scale period 6500 years ago.
14 As indicated in footnote 12, throughout this SPM, ‘main driver’ means responsible for more than 50% of the change.
15 Agricultural and ecological drought (depending on the affected biome): a period with abnormal soil moisture deficit, which results from combined shortage of precipitation
and excess evapotranspiration, and during the growing season impinges on crop production or ecosystem function in general (see Annex VII: Glossary). Observed changes in
meteorological droughts (precipitation deficits) and hydrological droughts (streamflow deficits) are distinct from those in agricultural and ecological droughts and are addressed in
the underlying AR6 material (Chapter 11).
16 The combined processes through which water is transferred to the atmosphere from open water and ice surfaces, bare soils and vegetation that make up the Earth’s surface (Glossary).
9
SPM
Summary for Policymakers
A.3.3 Decreases in global land monsoon precipitation17 from the 1950s to the 1980s are partly attributed to human-caused
Northern Hemisphere aerosol emissions, but increases since then have resulted from rising GHG concentrations and
decadal to multi-decadal internal variability (medium confidence). Over South Asia, East Asia and West Africa, increases
in monsoon precipitation due to warming from GHG emissions were counteracted by decreases in monsoon precipitation
due to cooling from human-caused aerosol emissions over the 20th century (high confidence). Increases in West African
monsoon precipitation since the 1980s are partly due to the growing influence of GHGs and reductions in the cooling
effect of human-caused aerosol emissions over Europe and North America (medium confidence).
{2.3, 3.3, 8.2, 8.3, 8.4, 8.5, 8.6, Box 8.1, Box 8.2, 10.6, Box TS.13}
A.3.4 It is likely that the global proportion of major (Category 3–5) tropical cyclone occurrence has increased over the last four
decades, and it is very likely that the latitude where tropical cyclones in the western North Pacific reach their peak intensity
has shifted northward; these changes cannot be explained by internal variability alone (medium confidence). There is low
confidence in long-term (multi-decadal to centennial) trends in the frequency of all-category tropical cyclones. Event
attribution studies and physical understanding indicate that human-induced climate change increases heavy precipitation
associated with tropical cyclones (high confidence), but data limitations inhibit clear detection of past trends on the
global scale.
{8.2, 11.7, Box TS.10}
A.3.5 Human influence has likely increased the chance of compound extreme events18 since the 1950s. This includes increases in
the frequency of concurrent heatwaves and droughts on the global scale (high confidence), fire weather in some regions
of all inhabited continents (medium confidence), and compound flooding in some locations (medium confidence).
{11.6, 11.7, 11.8, 12.3, 12.4, TS.2.6, Table TS.5, Box TS.10}
17 The global monsoon is defined as the area in which the annual range (local summer minus local winter) of precipitation is greater than 2.5 mm day–1 (Glossary). Global land monsoon
precipitation refers to the mean precipitation over land areas within the global monsoon.
18 Compound extreme events are the combination of multiple drivers and/or hazards that contribute to societal or environmental risk (Glossary). Examples are concurrent heatwaves
and droughts, compound flooding (e.g., a storm surge in combination with extreme rainfall and/or river flow), compound fire weather conditions (i.e., a combination of hot, dry and
windy conditions), or concurrent extremes at different locations.
10
SPM
Summary for Policymakers
Climate change is already affecting every inhabited region across the globe,
with human influence contributing to many observed changes in weather
and climate extremes
Increase (41)
Type of observed change
in hot extremes
Decrease (0)
Low agreement in the type of change (2)
Limited data and/or literature (2)
Type of observed change since the 1950s
Type of observed change since the 1950s
Type of observed change since the 1950s
(a) Synthesis of assessment of observed change in hot extremes and
con dence in human contribution to the observed changes in the world’s regions
Type of observed change
in agricultural and ecological drought
Type of observed change
in heavy precipitation
Increase (19)
Decrease (0)
Low agreement in the type of change (8)
Limited data and/or literature (18)
NWN NEN GIC
Africa
Asia
Australasia
North
America
Central
America
South
America
Europe NEU RAR
WNA CNA ENA WCE EEU WSB ESB RFE
NCA MED WCA ECA TIB EAS
SCA CAR SAH ARP SAS SEA
NWS NSA WAF CAF NEAF
NAU
SAM NES WSAF SEAF
CAU EAU
SWS SES ESAF
SAU NZ
SSA
MDG
(b) Synthesis of assessment of observed change in heavy precipitation and
con dence in human contribution to the observed changes in the world’s regions
Increase (12)
Decrease (1)
Low agreement in the type of change (28)
Limited data and/or literature (4)
NWN NEN GIC
Africa
Asia
Australasia
North
America
Central
America
South
America
Europe NEU RAR
WNA CNA ENA WCE EEU WSB ESB RFE
NCA MED WCA ECA TIB EAS
SCA CAR SAH ARP SAS SEA
NWS NSA WAF CAF NEAF
NAU
SAM NES WSAF SEAF
CAU EAU
SWS SES ESAF
SAU NZ
SSA
MDG
(c) Synthesis of assessment of observed change in agricultural and ecological drought
and con dence in human contribution to the observed changes in the world’s regions
NWN NEN GIC
Africa
Asia
Australasia
North
America
Central
America
South
America
Europe NEU RAR
WNA CNA ENA WCE EEU WSB ESB RFE
NCA MED WCA ECA TIB EAS
SCA CAR SAH ARP SAS SEA
NWS NSA WAF CAF NEAF
NAU
PAC
PAC
PAC
SAM NES WSAF SEAF
CAU EAU
SWS SES ESAF
SAU NZ
SSA
MDG
Small
Islands
Small
Islands
Small
Islands
Small
Islands
Small
Islands
Small
Islands
NWN
Each hexagon corresponds
to one of the IPCC AR6
WGI reference regions
IPCC AR6 WGI reference regions: North America: NWN (North-Western North America, NEN (North-Eastern North America), WNA
(Western North America), CNA (Central North America), ENA (Eastern North America), Central America: NCA (Northern Central America),
SCA (Southern Central America), CAR (Caribbean), South America: NWS (North-Western South America), NSA (Northern South America), NES
(North-Eastern South America), SAM (South American Monsoon), SWS (South-Western South America), SES (South-Eastern South America),
SSA (Southern South America), Europe: GIC (Greenland/Iceland), NEU (Northern Europe), WCE (Western and Central Europe), EEU (Eastern
Europe), MED (Mediterranean), Africa: MED (Mediterranean), SAH (Sahara), WAF (Western Africa), CAF (Central Africa), NEAF (North Eastern
Africa), SEAF (South Eastern Africa), WSAF (West Southern Africa), ESAF (East Southern Africa), MDG (Madagascar), Asia: RAR (Russian
Arctic), WSB (West Siberia), ESB (East Siberia), RFE (Russian Far East), WCA (West Central Asia), ECA (East Central Asia), TIB (Tibetan Plateau),
EAS (East Asia), ARP (Arabian Peninsula), SAS (South Asia), SEA (South East Asia), Australasia: NAU (Northern Australia), CAU (Central
Australia), EAU (Eastern Australia), SAU (Southern Australia), NZ (New Zealand), Small Islands: CAR (Caribbean), PAC (Pacific Small Islands)
North-Western
North America
High
Medium
Low due to limited agreement
Low due to limited evidence
Confidence in human contribution
to the observed change
High
Medium
Low due to limited agreement
Low due to limited evidence
Confidence in human contribution
to the observed change
High
Medium
Low due to limited agreement
Low due to limited evidence
Confidence in human contribution
to the observed change
... .. - . o.. ·
- ..
. •••
••
•
0
0
0
0
0
0
0
0
0
•••
••
•
0
. . -
. ..
-
- ...
.
0 . 7
0 -oo•o
0
0
0
0
•••
••
•
0
-
0 .
.. .
.
- .
0
11
SPM
Summary for Policymakers
Figure SPM.3 | Synthesis of assessed observed and attributable regional changes
19 Cumulative energy increase of 282 [177 to 387] ZJ over 1971–2006 (1 ZJ = 1021 joules).
20 Cumulative energy increase of 152 [100 to 205] ZJ over 2006–2018.
21 Understanding of climate processes, the instrumental record, paleoclimates and model-based emergent constraints (Glossary).
The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size in their approximate geographical location (see legend for regional acronyms).
All assessments are made for each region as a whole and for the 1950s to the present. Assessments made on different time scales or more local spatial scales might
differ from what is shown in the figure. The colours in each panel represent the four outcomes of the assessment on observed changes. Striped hexagons (white
and light-grey) are used where there is low agreement in the type of change for the region as a whole, and grey hexagons are used when there is limited data and/
or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium confidence in the observed change. The confidence
level for the human influence on these observed changes is based on assessing trend detection and attribution and event attribution literature, and it is indicated
by the number of dots: three dots for high confidence, two dots for medium confidence and one dot for low confidence (single, filled dot: limited agreement; single,
empty dot: limited evidence).
Panel (a) For hot extremes, the evidence is mostly drawn from changes in metrics based on daily maximum temperatures; regional studies using other indices
(heatwave duration, frequency and intensity) are used in addition. Red hexagons indicate regions where there is at least medium confidence in an observed increase
in hot extremes.
Panel (b) For heavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or five-day precipitation amounts using global and
regional studies. Green hexagons indicate regions where there is at least medium confidence in an observed increase in heavy precipitation.
Panel (c) Agricultural and ecological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented
by evidence on changes in surface soil moisture, water balance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric
evaporative demand. Yellow hexagons indicate regions where there is at least medium confidence in an observed increase in this type of drought, and green
hexagons indicate regions where there is at least medium confidence in an observed decrease in agricultural and ecological drought.
For all regions, Table TS.5 shows a broader range of observed changes besides the ones shown in this figure. Note that Southern South America (SSA) is the only
region that does not display observed changes in the metrics shown in this figure, but is affected by observed increases in mean temperature, decreases in frost
and increases in marine heatwaves.
{11.9, Atlas 1.3.3, Figure Atlas.2, Table TS.5; Box TS.10, Figure 1}
A.4 Improved knowledge of climate processes, paleoclimate evidence and the response of the climate system to
increasing radiative forcing gives a best estimate of equilibrium climate sensitivity of 3°C, with a narrower
range compared to AR5.
{2.2, 7.3, 7.4, 7.5, Box 7.2, 9.4, 9.5, 9.6, Cross-Chapter Box 9.1}
A.4.1 Human-caused radiative forcing of 2.72 [1.96 to 3.48] W m–2 in 2019 relative to 1750 has warmed the climate system. This
warming is mainly due to increased GHG concentrations, partly reduced by cooling due to increased aerosol concentrations.
The radiative forcing has increased by 0.43 W m–2 (19%) relative to AR5, of which 0.34 W m–2 is due to the increase in GHG
concentrations since 2011. The remainder is due to improved scientific understanding and changes in the assessment of
aerosol forcing, which include decreases in concentration and improvement in its calculation (high confidence).
{2.2, 7.3, TS.2.2, TS.3.1}
A.4.2 Human-caused net positive radiative forcing causes an accumulation of additional energy (heating) in the climate system,
partly reduced by increased energy loss to space in response to surface warming. The observed average rate of heating of
the climate system increased from 0.50 [0.32 to 0.69] W m–2 for the period 1971–200619 to 0.79 [0.52 to 1.06] W m–2 for
the period 2006–201820 (high confidence). Ocean warming accounted for 91% of the heating in the climate system, with
land warming, ice loss and atmospheric warming accounting for about 5%, 3% and 1%, respectively (high confidence).
{7.2, Box 7.2, TS.3.1}
A.4.3 Heating of the climate system has caused global mean sea level rise through ice loss on land and thermal expansion
from ocean warming. Thermal expansion explained 50% of sea level rise during 1971–2018, while ice loss from glaciers
contributed 22%, ice sheets 20% and changes in land-water storage 8%. The rate of ice-sheet loss increased by a factor
of four between 1992–1999 and 2010–2019. Together, ice-sheet and glacier mass loss were the dominant contributors to
global mean sea level rise during 2006–2018 (high confidence).
{9.4, 9.5, 9.6, Cross-Chapter Box 9.1}
A.4.4 The equilibrium climate sensitivity is an important quantity used to estimate how the climate responds to radiative
forcing. Based on multiple lines of evidence,21 the very likely range of equilibrium climate sensitivity is between 2°C (high
confidence) and 5°C (medium confidence). The AR6 assessed best estimate is 3°C with a likely range of 2.5°C to 4°C
(high confidence), compared to 1.5°C to 4.5°C in AR5, which did not provide a best estimate.
{7.4, 7.5, TS.3.2}
12
SPM
Summary for Policymakers
B. Possible Climate Futures
22 Throughout this Report, the five illustrative scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socio-economic Pathway or ‘SSP’ describing the socio-economic
trends underlying the scenario, and ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or W m–2) resulting from the scenario in the year 2100.
A detailed comparison to scenarios used in earlier IPCC reports is provided in Section TS.1.3, and Sections 1.6 and 4.6. The SSPs that underlie the specific forcing scenarios used to
drive climate models are not assessed by WGI. Rather, the SSPx-y labelling ensures traceability to the underlying literature in which specific forcing pathways are used as input to the
climate models. IPCC is neutral with regard to the assumptions underlying the SSPs, which do not cover all possible scenarios. Alternative scenarios may be considered or developed.
23 Net negative CO2 emissions are reached when anthropogenic removals of CO2 exceed anthropogenic emissions (Glossary).
A set of five new illustrative emissions scenarios is considered consistently across this Report to explore the climate response to
a broader range of greenhouse gas (GHG), land-use and air pollutant futures than assessed in AR5. This set of scenarios drives
climate model projections of changes in the climate system. These projections account for solar activity and background forcing
from volcanoes. Results over the 21st century are provided for the near term (2021–2040), mid-term (2041–2060) and long term
(2081–2100) relative to 1850–1900, unless otherwise stated.
Box SPM.1 | Scenarios, Climate Models and Projections
Box SPM.1.1: This Report assesses the climate response to five illustrative scenarios that cover the range of possible future
development of anthropogenic drivers of climate change found in the literature. They start in 2015, and include scenarios22
with high and very high GHG emissions (SSP3-7.0 and SSP5-8.5) and CO2 emissions that roughly double from current
levels by 2100 and 2050, respectively, scenarios with intermediate GHG emissions (SSP2-4.5) and CO2 emissions remaining
around current levels until the middle of the century, and scenarios with very low and low GHG emissions and CO2 emissions
declining to net zero around or after 2050, followed by varying levels of net negative CO2 emissions23 (SSP1-1.9 and
SSP1-2.6), as illustrated in Figure SPM.4. Emissions vary between scenarios depending on socio-economic assumptions,
levels of climate change mitigation and, for aerosols and non-methane ozone precursors, air pollution controls. Alternative
assumptions may result in similar emissions and climate responses, but the socio-economic assumptions and the feasibility
or likelihood of individual scenarios are not part of the assessment.
{1.6, Cross-Chapter Box 1.4, TS.1.3} (Figure SPM.4)
Box SPM.1.2: This Report assesses results from climate models participating in the Coupled Model Intercomparison Project
Phase 6 (CMIP6) of the World Climate Research Programme. These models include new and better representations of
physical, chemical and biological processes, as well as higher resolution, compared to climate models considered in previous
IPCC assessment reports. This has improved the simulation of the recent mean state of most large-scale indicators of climate
change and many other aspects across the climate system. Some differences from observations remain, for example in
regional precipitation patterns. The CMIP6 historical simulations assessed in this Report have an ensemble mean global
surface temperature change within 0.2°C of the observations over most of the historical period, and observed warming is
within the very likely range of the CMIP6 ensemble. However, some CMIP6 models simulate a warming that is either above
or below the assessed very likely range of observed warming.
{1.5, Cross-Chapter Box 2.2, 3.3, 3.8, TS.1.2, Cross-Section Box TS.1} (Figure SPM.1b, Figure SPM.2)
Box SPM.1.3: The CMIP6 models considered in this Report have a wider range of climate sensitivity than in CMIP5 models
and the AR6 assessed very likely range, which is based on multiple lines of evidence. These CMIP6 models also show
a higher average climate sensitivity than CMIP5 and the AR6 assessed best estimate. The higher CMIP6 climate sensitivity
values compared to CMIP5 can be traced to an amplifying cloud feedback that is larger in CMIP6 by about 20%.
{Box 7.1, 7.3, 7.4, 7.5, TS.3.2}
Box SPM.1.4: For the first time in an IPCC report, assessed future changes in global surface temperature, ocean warming
and sea level are constructed by combining multi-model projections with observational constraints based on past simulated
warming, as well as the AR6 assessment of climate sensitivity. For other quantities, such robust methods do not yet exist
to constrain the projections. Nevertheless, robust projected geographical patterns of many variables can be identified at
a given level of global warming, common to all scenarios considered and independent of timing when the global warming
level is reached.
{1.6, 4.3, 4.6, Box 4.1, 7.5, 9.2, 9.6, Cross-Chapter Box 11.1, Cross-Section Box TS.1}
13
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Summary for Policymakers
Box SPM.1 (continued)
Figure SPM.4 | Future anthropogenic emissions of key drivers of climate change and warming contributions by groups of drivers for
the five illustrative scenarios used in this report
The five scenarios are SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.
Panel (a) Annual anthropogenic (human-caused) emissions over the 2015–2100 period. Shown are emissions trajectories for carbon dioxide
(CO2) from all sectors (GtCO2/yr) (left graph) and for a subset of three key non-CO2 drivers considered in the scenarios: methane (CH4, MtCH4/yr, top-right
graph); nitrous oxide (N2O, MtN2O/yr, middle-right graph); and sulphur dioxide (SO2, MtSO2/yr, bottom-right graph, contributing to anthropogenic aerosols
in panel (b).
Future emissions cause future additional warming, with total warming
dominated by past and future CO₂ emissions
(a) Future annual emissions of CO₂ (left) and of a subset of key non-CO₂ drivers (right), across five illustrative scenarios
Methane (MtCH₄/yr)
Nitrous oxide (MtN₂O/yr)
Sulphur dioxide (MtSO₂/yr)
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
(b) Contribution to global surface temperature increase from different emissions, with a dominant role of CO₂ emissions
Change in global surface temperature in 2081–2100 relative to 1850–1900 (ºC)
0
200
400
600
800
0
10
20
0
40
80
120
2015 2050 2100
2015 2050 2100
2015 2050 2100
–20
0
20
40
60
80
100
120
140
2015 2050 2100
Carbon dioxide (GtCO₂/yr)
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
SSP1-1.9
–1
0
1
2
3
4
5
6
Total
(observed)
Aerosols
land use
Non-CO₂
GHGs
CO₂
ºC
–1
0
1
2
3
4
5
6
Total
(observed)
Aerosols
Land use
Non-CO₂
GHGs
CO₂
ºC
–1
0
1
2
3
4
5
6
Total
(observed)
Aerosols
Land use
Non-CO₂
GHGs
CO₂
ºC
–1
0
1
2
3
4
5
6
Total
(observed)
Aerosols
Land use
Non-CO₂
GHGs
CO₂
ºC
–1
0
1
2
3
4
5
6
Total
(observed)
Aerosols
Land use
Non-CO₂
GHGs
CO₂
ºC
SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5
Total warming (observed warming to date in darker shade), warming from CO₂, warming from non-CO₂ GHGs and cooling from changes in aerosols and land use
Selected contributors to non-CO₂ GHGs
One air pollutant and contributor to aerosols
T
I I I I I I I I I I I I I I I I I I I I
14
SPM
Summary for Policymakers
Panel (b) Warming contributions by groups of anthropogenic drivers and by scenario are shown as the change in global surface
temperature (°C) in 2081–2100 relative to 1850–1900, with indication of the observed warming to date. Bars and whiskers represent median values
and the very likely range, respectively. Within each scenario bar plot, the bars represent: total global warming (°C; ‘total’ bar) (see Table SPM.1); warming
contributions (°C) from changes in CO2 (‘CO2’ bar) and from non-CO2 greenhouse gases (GHGs; ‘non-CO2 GHGs’ bar: comprising well-mixed greenhouse
gases and ozone); and net cooling from other anthropogenic drivers (‘aerosols and land use’ bar: anthropogenic aerosols, changes in reflectance due to
land-use and irrigation changes, and contrails from aviation) (see Figure SPM.2, panel c, for the warming contributions to date for individual drivers). The
best estimate for observed warming in 2010–2019 relative to 1850–1900 (see Figure SPM.2, panel a) is indicated in the darker column in the ‘total’ bar.
Warming contributions in panel (b) are calculated as explained in Table SPM.1 for the total bar. For the other bars, the contribution by groups of drivers is
calculated with a physical climate emulator of global surface temperature that relies on climate sensitivity and radiative forcing assessments.
{Cross-Chapter Box 1.4; 4.6; Figure 4.35; 6.7; Figures 6.18, 6.22 and 6.24; 7.3; Cross-Chapter Box 7.1; Figure 7.7; Box TS.7; Figures TS.4 and TS.15}
B.1 Global surface temperature will continue to increase until at least mid-century under all emissions scenarios
considered. Global warming of 1.5°C and 2°C will be exceeded during the 21st century unless deep reductions
in CO2 and other greenhouse gas emissions occur in the coming decades.
{2.3, Cross-Chapter Box 2.3, Cross-Chapter Box 2.4, 4.3, 4.4, 4.5} (Figure SPM.1, Figure SPM.4, Figure SPM.8,
Table SPM.1, Box SPM.1)
B.1.1 Compared to 1850–1900, global surface temperature averaged over 2081–2100 is very likely to be higher by 1.0°C to
1.8°C under the very low GHG emissions scenario considered (SSP1-1.9), by 2.1°C to 3.5°C in the intermediate GHG
emissions scenario (SSP2-4.5) and by 3.3°C to 5.7°C under the very high GHG emissions scenario (SSP5-8.5).24 The last
time global surface temperature was sustained at or above 2.5°C higher than 1850–1900 was over 3 million years ago
(medium confidence).
{2.3, Cross-Chapter Box 2.4, 4.3, 4.5, Box TS.2, Box TS.4, Cross-Section Box TS.1} (Table SPM.1)
24 Changes in global surface temperature are reported as running 20-year averages, unless stated otherwise.
25 SSP1-1.9 and SSP1-2.6 are scenarios that start in 2015 and have very low and low GHG emissions, respectively, and CO2 emissions declining to net zero around or after 2050,
followed by varying levels of net negative CO2 emissions.
26 Crossing is defined here as having the assessed global surface temperature change, averaged over a 20-year period, exceed a particular global warming level.
Table SPM.1 | Changes in global surface temperature, which are assessed based on multiple lines of evidence, for selected 20-year time
periods and the five illustrative emissions scenarios considered. Temperature differences relative to the average global surface temperature of the
period 1850–1900 are reported in °C. This includes the revised assessment of observed historical warming for the AR5 reference period 1986–2005, which
in AR6 is higher by 0.08 [–0.01 to +0.12] °C than in AR5 (see footnote 10). Changes relative to the recent reference period 1995–2014 may be calculated
approximately by subtracting 0.85°C, the best estimate of the observed warming from 1850–1900 to 1995–2014.
{Cross-Chapter Box 2.3, 4.3, 4.4, Cross-Section Box TS.1}
Near term, 2021–2040 Mid-term, 2041–2060 Long term, 2081–2100
Scenario Best estimate (°C)
Very likely
range (°C)
Best estimate (°C)
Very likely
range (°C)
Best estimate (°C)
Very likely
range (°C)
SSP1-1.9 1.5 1.2 to 1.7 1.6 1.2 to 2.0 1.4 1.0 to 1.8
SSP1-2.6 1.5 1.2 to 1.8 1.7 1.3 to 2.2 1.8 1.3 to 2.4
SSP2-4.5 1.5 1.2 to 1.8 2.0 1.6 to 2.5 2.7 2.1 to 3.5
SSP3-7.0 1.5 1.2 to 1.8 2.1 1.7 to 2.6 3.6 2.8 to 4.6
SSP5-8.5 1.6 1.3 to 1.9 2.4 1.9 to 3.0 4.4 3.3 to 5.7
B.1.2 Based on the assessment of multiple lines of evidence, global warming of 2°C, relative to 1850–1900, would be exceeded
during the 21st century under the high and very high GHG emissions scenarios considered in this report (SSP3-7.0 and
SSP5-8.5, respectively). Global warming of 2°C would extremely likely be exceeded in the intermediate GHG emissions
scenario (SSP2-4.5). Under the very low and low GHG emissions scenarios, global warming of 2°C is extremely unlikely
to be exceeded (SSP1-1.9) or unlikely to be exceeded (SSP1-2.6).25 Crossing the 2°C global warming level in the midterm
period (2041–2060) is very likely to occur under the very high GHG emissions scenario (SSP5-8.5), likely to occur
under the high GHG emissions scenario (SSP3-7.0), and more likely than not to occur in the intermediate GHG emissions
scenario (SSP2-4.5).26
{4.3, Cross-Section Box TS.1} (Table SPM.1, Figure SPM.4, Box SPM.1)
15
SPM
Summary for Policymakers
B.1.3 Global warming of 1.5°C relative to 1850–1900 would be exceeded during the 21st century under the intermediate, high
and very high GHG emissions scenarios considered in this report (SSP2-4.5, SSP3-7.0 and SSP5-8.5, respectively). Under
the five illustrative scenarios, in the near term (2021–2040), the 1.5°C global warming level is very likely to be exceeded
under the very high GHG emissions scenario (SSP5-8.5), likely to be exceeded under the intermediate and high GHG
emissions scenarios (SSP2-4.5 and SSP3-7.0), more likely than not to be exceeded under the low GHG emissions scenario
(SSP1-2.6) and more likely than not to be reached under the very low GHG emissions scenario (SSP1-1.9).27 Furthermore, for
the very low GHG emissions scenario (SSP1-1.9), it is more likely than not that global surface temperature would decline
back to below 1.5°C toward the end of the 21st century, with a temporary overshoot of no more than 0.1°C above 1.5°C
global warming.
{4.3, Cross-Section Box TS.1} (Table SPM.1, Figure SPM.4)
B.1.4 Global surface temperature in any single year can vary above or below the long-term human-induced trend, due to
substantial natural variability.28 The occurrence of individual years with global surface temperature change above a certain
level, for example 1.5°C or 2°C, relative to 1850–1900 does not imply that this global warming level has been reached.29
{Cross-Chapter Box 2.3, 4.3, 4.4, Box 4.1, Cross-Section Box TS.1} (Table SPM.1, Figure SPM.1, Figure SPM.8)
B.2 Many changes in the climate system become larger in direct relation to increasing global warming. They
include increases in the frequency and intensity of hot extremes, marine heatwaves, heavy precipitation,
and, in some regions, agricultural and ecological droughts; an increase in the proportion of intense tropical
cyclones; and reductions in Arctic sea ice, snow cover and permafrost.
{4.3, 4.5, 4.6, 7.4, 8.2, 8.4, Box 8.2, 9.3, 9.5, Box 9.2, 11.1, 11.2, 11.3, 11.4, 11.6, 11.7, 11.9, Cross-Chapter Box
11.1, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.4, Atlas.5, Atlas.6, Atlas.7, Atlas.8, Atlas.9, Atlas.10, Atlas.11}
(Figure SPM.5, Figure SPM.6, Figure SPM.8)
B.2.1 It is virtually certain that the land surface will continue to warm more than the ocean surface (likely 1.4 to 1.7 times more).
It is virtually certain that the Arctic will continue to warm more than global surface temperature, with high confidence
above two times the rate of global warming.
{2.3, 4.3, 4.5, 4.6, 7.4, 11.1, 11.3, 11.9, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.4, Atlas.5, Atlas.6, Atlas.7, Atlas.8, Atlas.9,
Atlas.10, Atlas.11, Cross-Section Box TS.1, TS.2.6} (Figure SPM.5)
B.2.2 With every additional increment of global warming, changes in extremes continue to become larger. For example, every
additional 0.5°C of global warming causes clearly discernible increases in the intensity and frequency of hot extremes,
including heatwaves (very likely), and heavy precipitation (high confidence), as well as agricultural and ecological
droughts30 in some regions (high confidence). Discernible changes in intensity and frequency of meteorological droughts,
with more regions showing increases than decreases, are seen in some regions for every additional 0.5°C of global
warming (medium confidence). Increases in frequency and intensity of hydrological droughts become larger with
increasing global warming in some regions (medium confidence). There will be an increasing occurrence of some extreme
events unprecedented in the observational record with additional global warming, even at 1.5°C of global warming.
Projected percentage changes in frequency are larger for rarer events (high confidence).
{8.2, 11.2, 11.3, 11.4, 11.6, 11.9, Cross-Chapter Box 11.1, Cross-Chapter Box 12.1, TS.2.6} (Figure SPM.5, Figure SPM.6)
B.2.3 Some mid-latitude and semi-arid regions, and the South American Monsoon region, are projected to see the highest
increase in the temperature of the hottest days, at about 1.5 to 2 times the rate of global warming (high confidence). The
Arctic is projected to experience the highest increase in the temperature of the coldest days, at about three times the rate
of global warming (high confidence). With additional global warming, the frequency of marine heatwaves will continue
to increase (high confidence), particularly in the tropical ocean and the Arctic (medium confidence).
{Box 9.2, 11.1, 11.3, 11.9, Cross-Chapter Box 11.1, Cross-Chapter Box 12.1, 12.4, TS.2.4, TS.2.6} (Figure SPM.6)
27 The AR6 assessment of when a given global warming level is first exceeded benefits from the consideration of the illustrative scenarios, the multiple lines of evidence entering the
assessment of future global surface temperature response to radiative forcing, and the improved estimate of historical warming. The AR6 assessment is thus not directly comparable to
the SR1.5 SPM, which reported likely reaching 1.5°C global warming between 2030 and 2052, from a simple linear extrapolation of warming rates of the recent past. When considering
scenarios similar to SSP1-1.9 instead of linear extrapolation, the SR1.5 estimate of when 1.5°C global warming is first exceeded is close to the best estimate reported here.
28 Natural variability refers to climatic fluctuations that occur without any human influence, that is, internal variability combined with the response to external natural factors such as
volcanic eruptions, changes in solar activity and, on longer time scales, orbital effects and plate tectonics (Glossary).
29 The internal variability in any single year is estimated to be about ±0.25°C (5–95% range, high confidence).
30 Projected changes in agricultural and ecological droughts are primarily assessed based on total column soil moisture. See footnote 15 for definition and relation to precipitation
and evapotranspiration.
16
SPM
Summary for Policymakers
B.2.4 It is very likely that heavy precipitation events will intensify and become more frequent in most regions with additional global
warming. At the global scale, extreme daily precipitation events are projected to intensify by about 7% for each 1°C of global
warming (high confidence). The proportion of intense tropical cyclones (Category 4–5) and peak wind speeds of the most
intense tropical cyclones are projected to increase at the global scale with increasing global warming (high confidence).
{8.2, 11.4, 11.7, 11.9, Cross-Chapter Box 11.1, Box TS.6, TS.4.3.1} (Figure SPM.5, Figure SPM.6)
B.2.5 Additional warming is projected to further amplify permafrost thawing and loss of seasonal snow cover, of land ice and of
Arctic sea ice (high confidence). The Arctic is likely to be practically sea ice-free in September31 at least once before 2050
under the five illustrative scenarios considered in this report, with more frequent occurrences for higher warming levels.
There is low confidence in the projected decrease of Antarctic sea ice.
{4.3, 4.5, 7.4, 8.2, 8.4, Box 8.2, 9.3, 9.5, 12.4, Cross-Chapter Box 12.1, Atlas.5, Atlas.6, Atlas.8, Atlas.9, Atlas.11, TS.2.5}
(Figure SPM.8)
31 Monthly average sea ice area of less than 1 million km2, which is about 15% of the average September sea ice area observed in 1979–1988.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7
With every increment of global warming, changes get larger
in regional mean temperature, precipitation and soil moisture
(a) Annual mean temperature change (°C)
at 1°C global warming
(b) Annual mean temperature change (°C)
relative to 1850–1900
Across warming levels, land areas warm more than ocean areas, and the
Arctic and Antarctica warm more than the tropics.
Warming at 1°C affects all continents and
is generally larger over land than over the
oceans in both observations and models.
Across most regions, observed and
simulated patterns are consistent.
Simulated change at Simulated change at 1.5°C global warming 2°C global warming Simulated change at 4°C global warming
Observed change per 1°C global warming Simulated change at 1°C global warming
Change (°C)
Warmer
17
SPM
Summary for Policymakers
l a.
Figure SPM.5 | Changes in annual mean surface temperature, precipitation, and soil moisture
Panel (a) Comparison of observed and simulated annual mean surface temperature change. The left map shows the observed changes in annual
mean surface temperature in the period 1850–2020 per °C of global warming (°C). The local (i.e., grid point) observed annual mean surface temperature changes
are linearly regressed against the global surface temperature in the period 1850–2020. Observed temperature data are from Berkeley Earth, the dataset with
the largest coverage and highest horizontal resolution. Linear regression is applied to all years for which data at the corresponding grid point is available. The
regression method was used to take into account the complete observational time series and thereby reduce the role of internal variability at the grid point level.
White indicates areas where time coverage was 100 years or less and thereby too short to calculate a reliable linear regression. The right map is based on model
simulations and shows change in annual multi-model mean simulated temperatures at a global warming level of 1°C (20-year mean global surface temperature
change relative to 1850–1900). The triangles at each end of the colour bar indicate out-of-bound values, that is, values above or below the given limits.
Panel (b) Simulated annual mean temperature change (°C), panel (c) precipitation change (%), and panel (d) total column soil moisture change
(standard deviation of interannual variability) at global warming levels of 1.5°C, 2°C and 4°C (20-year mean global surface temperature change relative
to 1850–1900). Simulated changes correspond to Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model mean change (median change for soil
moisture) at the corresponding global warming level, that is, the same method as for the right map in panel (a).
In panel (c), high positive percentage changes in dry regions may correspond to small absolute changes. In panel (d), the unit is the standard deviation
of interannual variability in soil moisture during 1850–1900. Standard deviation is a widely used metric in characterizing drought severity. A projected
reduction in mean soil moisture by one standard deviation corresponds to soil moisture conditions typical of droughts that occurred about once every six years
during 1850–1900. In panel (d), large changes in dry regions with little interannual variability in the baseline conditions can correspond to small absolute
change. The triangles at each end of the colour bars indicate out-of-bound values, that is, values above or below the given limits. Results from all models
reaching the corresponding warming level in any of the five illustrative scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are averaged.
Maps of annual mean temperature and precipitation changes at a global warming level of 3°C are available in Figure 4.31 and Figure 4.32 in Section 4.6.
Corresponding maps of panels (b), (c) and (d), including hatching to indicate the level of model agreement at grid-cell level, are found in Figures 4.31, 4.32 and
11.19, respectively; as highlighted in Cross-Chapter Box Atlas.1, grid-cell level hatching is not informative for larger spatial scales (e.g., over AR6 reference regions)
where the aggregated signals are less affected by small-scale variability, leading to an increase in robustness.
{Figure 1.14, 4.6.1, Cross-Chapter Box 11.1, Cross-Chapter Box Atlas.1, TS.1.3.2, Figures TS.3 and TS.5}
(c) Annual mean precipitation change (%)
relative to 1850–1900
Change (%)
(d) Annual mean total column soil
moisture change (standard deviation)
–1.0 –0.5 0 0.5 1.0 1.5
Change (standard deviation
of interannual variability)
–1.5
Precipitation is projected to increase over high latitudes, the equatorial
Pacific and parts of the monsoon regions, but decrease over parts of the
subtropics and in limited areas of the tropics.
Relatively small absolute changes
may appear as large % changes in
regions with dry baseline conditions.
Relatively small absolute changes
may appear large when expressed
in units of standard deviation in dry
regions with little interannual
variability in baseline conditions.
Across warming levels, changes in soil moisture largely follow changes in
precipitation but also show some differences due to the influence of
evapotranspiration.
Simulated change at 1.5°C global warming Simulated change at 2°C global warming Simulated change at 4°C global warming
Simulated change at 1.5°C global warming Simulated change at 2°C global warming Simulated change at 4°C global warming
–40 –30 –20 –10 0 10 20 30 40
Drier Wetter
Drier Wetter
(- --
r
---)
-- -)
18
SPM
Summary for Policymakers
Figure SPM.6 | Projected changes in the intensity and frequency of hot temperature extremes over land, extreme precipitation over land,
and agricultural and ecological droughts in drying regions
Projected changes are shown at global warming levels of 1°C, 1.5°C, 2°C, and 4°C and are relative to 1850–1900,9 representing a climate without human
influence. The figure depicts frequencies and increases in intensity of 10- or 50-year extreme events from the base period (1850–1900) under different global
warming levels.
Hot temperature extremes are defined as the daily maximum temperatures over land that were exceeded on average once in a decade (10-year event) or once
in 50 years (50-year event) during the 1850–1900 reference period. Extreme precipitation events are defined as the daily precipitation amount over land that
Present 1°C Present 1°C
+6.7%
wetter
+10.5%
wetter
+14.0%
wetter
+30.2%
wetter
Future global warming levels
1850–1900 1.5°C 2°C 4°C
0%
+10%
+20%
+30%
+40%
+0.3 sd
drier
+0.5 sd
drier
+0.6 sd
drier
+1.0 sd
drier
Once now likely
occurs
1.7 times
(0.7–4.1)
will likely
occur
2.0 times
(1.0–5.1)
will likely
occur
2.4 times
(1.3–5.8)
will likely
occur
4.1 times
(1.7–7.2)
Future global warming levels
1850–1900 1.5°C 2°C 4°C
0 sd
+1 sd
+2 sd
Once now likely
occurs
1.3 times
(1.2–1.4)
will likely
occur
1.5 times
(1.4–1.7)
will likely
occur
1.7 times
(1.6–2.0)
will likely
occur
2.7 times
(2.3–3.6)
INTENSITY increase FREQUENCY per 10 years
INTENSITY increase FREQUENCY per 10 years
Projected changes in extremes are larger in frequency and intensity with
every additional increment of global warming
Frequency and increase in intensity of heavy 1-day
precipitation event that occurred once in 10 years on
average in a climate without human influence
Heavy precipitation over land
Frequency and increase in intensity of an agricultural and ecological
drought event that occurred once in 10 years on average across
drying regions in a climate without human influence
Agricultural & ecological droughts in drying regions
INTENSITY increase FREQUENCY per 50 years
Frequency and increase in intensity of extreme temperature
event that occurred once in 50 years on average
in a climate without human influence
Present 1°C
+1.2°C
hotter
+2.0°C
hotter
+2.7°C
hotter
+5.3°C
hotter
50-year event
Once now likely
occurs
4.8 times
(2.3–6.4)
will likely
occur
8.6 times
(4.3–10.7)
will likely
occur
13.9 times
(6.9–16.6)
will likely
occur
39.2 times
(27.0–41.4)
Future global warming levels
1850–1900 1.5°C 2°C 4°C
0°C
+1°C
+2°C
+3°C
+4°C
+5°C
+6°C
Hot temperature extremes over land
Frequency and increase in intensity of extreme temperature
event that occurred once in 10 years on average
in a climate without human influence
+1.2°C
hotter
+1.9°C
hotter
+2.6°C
hotter
+5.1°C
hotter
10-year event
10-year event 10-year event
INTENSITY increase FREQUENCY per 10 years
Future global warming levels
1850–1900 1.5°C 2°C 4°C
0°C
+1°C
+2°C
+3°C
+4°C
+5°C
+6°C
Present 1°C
Once now likely
occurs
2.8 times
(1.8–3.2)
will likely
occur
4.1 times
(2.8–4.7)
will likely
occur
5.6 times
(3.8–6.0)
will likely
occur
9.4 times
(8.3–9.6)
•• . • ·6? ·% • • •• $;· ·:?: .' ·'s 6·% • ·% ·
%° ·:it?: •%• °• 6•%•• •· ·• s z?? •• ·:5:: ·ea •• • •
ii
ll
l
i
i
°
i
I
·%°
I
ii
l II
i
f
II
l II
I
I
I
19
SPM
Summary for Policymakers
was exceeded on average once in a decade during the 1850–1900 reference period. Agricultural and ecological drought events are defined as the annual
average of total column soil moisture below the 10th percentile of the 1850–1900 base period. These extremes are defined on model grid box scale. For hot
temperature extremes and extreme precipitation, results are shown for the global land. For agricultural and ecological drought, results are shown for drying regions
only, which correspond to the AR6 regions in which there is at least medium confidence in a projected increase in agricultural and ecological droughts at the 2°C
warming level compared to the 1850–1900 base period in the Coupled Model Intercomparison Project Phase 6 (CMIP6). These regions include Western North
America, Central North America, Northern Central America, Southern Central America, Caribbean, Northern South America, North-Eastern South America, South
American Monsoon, South-Western South America, Southern South America, Western and Central Europe, Mediterranean, West Southern Africa, East Southern
Africa, Madagascar, Eastern Australia, and Southern Australia (Caribbean is not included in the calculation of the figure because of the too-small number of full land
grid cells). The non-drying regions do not show an overall increase or decrease in drought severity. Projections of changes in agricultural and ecological droughts
in the CMIP Phase 5 (CMIP5) multi-model ensemble differ from those in CMIP6 in some regions, including in parts of Africa and Asia. Assessments of projected
changes in meteorological and hydrological droughts are provided in Chapter 11.
In the ‘frequency’ section, each year is represented by a dot. The dark dots indicate years in which the extreme threshold is exceeded, while light dots are years
when the threshold is not exceeded. Values correspond to the medians (in bold) and their respective 5–95% range based on the multi-model ensemble from
simulations of CMIP6 under different Shared Socio-economic Pathway scenarios. For consistency, the number of dark dots is based on the rounded-up median.
In the ‘intensity’ section, medians and their 5–95% range, also based on the multi-model ensemble from simulations of CMIP6, are displayed as dark and
light bars, respectively. Changes in the intensity of hot temperature extremes and extreme precipitation are expressed as degree Celsius and percentage. As for
agricultural and ecological drought, intensity changes are expressed as fractions of standard deviation of annual soil moisture.
{11.1; 11.3; 11.4; 11.6; 11.9; Figures 11.12, 11.15, 11.6, 11.7, and 11.18}
B.3 Continued global warming is projected to further intensify the global water cycle, including its variability,
global monsoon precipitation and the severity of wet and dry events.
{4.3, 4.4, 4.5, 4.6, 8.2, 8.3, 8.4, 8.5, Box 8.2, 11.4, 11.6, 11.9, 12.4, Atlas.3} (Figure SPM.5, Figure SPM.6)
B.3.1 There is strengthened evidence since AR5 that the global water cycle will continue to intensify as global temperatures
rise (high confidence), with precipitation and surface water flows projected to become more variable over most land
regions within seasons (high confidence) and from year to year (medium confidence). The average annual global land
precipitation is projected to increase by 0–5% under the very low GHG emissions scenario (SSP1-1.9), 1.5–8% for the
intermediate GHG emissions scenario (SSP2-4.5) and 1–13% under the very high GHG emissions scenario (SSP5-8.5) by
2081–2100 relative to 1995–2014 (likely ranges). Precipitation is projected to increase over high latitudes, the equatorial
Pacific and parts of the monsoon regions, but decrease over parts of the subtropics and limited areas in the tropics
in SSP2-4.5, SSP3-7.0 and SSP5-8.5 (very likely). The portion of the global land experiencing detectable increases or
decreases in seasonal mean precipitation is projected to increase (medium confidence). There is high confidence in an
earlier onset of spring snowmelt, with higher peak flows at the expense of summer flows in snow-dominated regions
globally.
{4.3, 4.5, 4.6, 8.2, 8.4, Atlas.3, TS.2.6, TS.4.3, Box TS.6} (Figure SPM.5)
B.3.2 A warmer climate will intensify very wet and very dry weather and climate events and seasons, with implications for
flooding or drought (high confidence), but the location and frequency of these events depend on projected changes in
regional atmospheric circulation, including monsoons and mid-latitude storm tracks. It is very likely that rainfall variability
related to the El Niño–Southern Oscillation is projected to be amplified by the second half of the 21st century in the
SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios.
{4.3, 4.5, 4.6, 8.2, 8.4, 8.5, 11.4, 11.6, 11.9, 12.4, TS.2.6, TS.4.2, Box TS.6} (Figure SPM.5, Figure SPM.6)
B.3.3 Monsoon precipitation is projected to increase in the mid- to long term at the global scale, particularly over South and
South East Asia, East Asia and West Africa apart from the far west Sahel (high confidence). The monsoon season is
projected to have a delayed onset over North and South America and West Africa (high confidence) and a delayed retreat
over West Africa (medium confidence).
{4.4, 4.5, 8.2, 8.3, 8.4, Box 8.2, Box TS.13}
B.3.4 A projected southward shift and intensification of Southern Hemisphere summer mid-latitude storm tracks and associated
precipitation is likely in the long term under high GHG emissions scenarios (SSP3-7.0, SSP5-8.5), but in the near term
the effect of stratospheric ozone recovery counteracts these changes (high confidence). There is medium confidence in
a continued poleward shift of storms and their precipitation in the North Pacific, while there is low confidence in projected
changes in the North Atlantic storm tracks.
{4.4, 4.5, 8.4, TS.2.3, TS.4.2}
B.4 Under scenarios with increasing CO2 emissions, the ocean and land carbon sinks are projected to be less
effective at slowing the accumulation of CO2 in the atmosphere.
{4.3, 5.2, 5.4, 5.5, 5.6} (Figure SPM.7)
20
SPM
Summary for Policymakers
B.4.1 While natural land and ocean carbon sinks are projected to take up, in absolute terms, a progressively larger amount
of CO2 under higher compared to lower CO2 emissions scenarios, they become less effective, that is, the proportion of
emissions taken up by land and ocean decrease with increasing cumulative CO2 emissions. This is projected to result in
a higher proportion of emitted CO2 remaining in the atmosphere (high confidence).
{5.2, 5.4, Box TS.5} (Figure SPM.7)
B.4.2 Based on model projections, under the intermediate GHG emissions scenario that stabilizes atmospheric CO2 concentrations
this century (SSP2-4.5), the rates of CO2 taken up by the land and ocean are projected to decrease in the second half of
the 21st century (high confidence). Under the very low and low GHG emissions scenarios (SSP1-1.9, SSP1-2.6), where CO2
concentrations peak and decline during the 21st century, the land and ocean begin to take up less carbon in response
to declining atmospheric CO2 concentrations (high confidence) and turn into a weak net source by 2100 under SSP1-1.9
(medium confidence). It is very unlikely that the combined global land and ocean sink will turn into a source by 2100
under scenarios without net negative emissions (SSP2-4.5, SSP3-7.0, SSP5-8.5).32
{4.3, 5.4, 5.5, 5.6, Box TS.5, TS.3.3}
B.4.3 The magnitude of feedbacks between climate change and the carbon cycle becomes larger but also more uncertain
in high CO2 emissions scenarios (very high confidence). However, climate model projections show that the uncertainties in
atmospheric CO2 concentrations by 2100 are dominated by the differences between emissions scenarios (high confidence).
Additional ecosystem responses to warming not yet fully included in climate models, such as CO2 and CH4 fluxes from
wetlands, permafrost thaw and wildfires, would further increase concentrations of these gases in the atmosphere
(high confidence).
{5.4, Box TS.5, TS.3.2}
32 These projected adjustments of carbon sinks to stabilization or decline of atmospheric CO2 are accounted for in calculations of remaining carbon budgets.
Figure SPM.7 | Cumulative anthropogenic CO2 emissions taken up by land and ocean sinks by 2100 under the five illustrative scenarios
The cumulative anthropogenic (human-caused) carbon dioxide (CO2) emissions taken up by the land and ocean sinks under the five illustrative scenarios (SSP1-1.9,
SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are simulated from 1850 to 2100 by Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models in the
concentration-driven simulations. Land and ocean carbon sinks respond to past, current and future emissions; therefore, cumulative sinks from 1850 to 2100 are
presented here. During the historical period (1850–2019) the observed land and ocean sink took up 1430 GtCO2 (59% of the emissions).
The proportion of CO₂ emissions taken up by land and ocean carbon sinks
is smaller in scenarios with higher cumulative CO₂ emissions
Total cumulative CO₂ emissions taken up by land and ocean (colours) and remaining in the atmosphere (grey)
under the five illustrative scenarios from 1850 to 2100
…meaning that the proportion
of CO₂ emissions taken up by
land and ocean carbon sinks
from the atmosphere
is smaller in scenarios
with higher CO₂ emissions.
SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5
ATMOSPHERE
LAND OCEAN
LAND OCEAN
ATMOSPHERE
ATMOSPHERE
LAND OCEAN
LAND OCEAN
LAND OCEAN
ATMOSPHERE
ATMOSPHERE
70%
0
2000
4000
6000
8000
10,000
12,000
65% 54% 44% 38%
OCEAN
ATMOSPHERE
LAND
For scenarios with
higher cumulative
CO₂ emissions…
…the amount of CO₂ emissions
taken up by land and ocean
carbon sinks is larger,
but more of the emitted
CO₂ remains in the
atmosphere…
GtCO₂
OCEAN
ATMOSPHERE
LAND
OCEAN
ATMOSPHERE
LAND
OCEAN
ATMOSPHERE
LAND
OCEAN
ATMOSPHERE
LAND
+ [,
in iii l Ii «« t/ w w°
21
SPM
Summary for Policymakers
The bar chart illustrates the projected amount of cumulative anthropogenic CO2 emissions (GtCO2) between 1850 and 2100 remaining in the atmosphere (grey
part) and taken up by the land and ocean (coloured part) in the year 2100. The doughnut chart illustrates the proportion of the cumulative anthropogenic
CO2 emissions taken up by the land and ocean sinks and remaining in the atmosphere in the year 2100. Values in % indicate the proportion of the cumulative
anthropogenic CO2 emissions taken up by the combined land and ocean sinks in the year 2100. The overall anthropogenic carbon emissions are calculated by
adding the net global land-use emissions from the CMIP6 scenario database to the other sectoral emissions calculated from climate model runs with prescribed CO2
concentrations.33 Land and ocean CO2 uptake since 1850 is calculated from the net biome productivity on land, corrected for CO2 losses due to land-use change by
adding the land-use change emissions, and net ocean CO2 flux.
{5.2.1; Table 5.1; 5.4.5; Figure 5.25; Box TS.5; Box TS.5, Figure 1}
B.5 Many changes due to past and future greenhouse gas emissions are irreversible for centuries to millennia,
especially changes in the ocean, ice sheets and global sea level.
{2.3, Cross-Chapter Box 2.4, 4.3, 4.5, 4.7, 5.3, 9.2, 9.4, 9.5, 9.6, Box 9.4} (Figure SPM.8)
B.5.1 Past GHG emissions since 1750 have committed the global ocean to future warming (high confidence). Over the rest of
the 21st century, likely ocean warming ranges from 2–4 (SSP1-2.6) to 4–8 times (SSP5-8.5) the 1971–2018 change. Based
on multiple lines of evidence, upper ocean stratification (virtually certain), ocean acidification (virtually certain) and ocean
deoxygenation (high confidence) will continue to increase in the 21st century, at rates dependent on future emissions.
Changes are irreversible on centennial to millennial time scales in global ocean temperature (very high confidence),
deep-ocean acidification (very high confidence) and deoxygenation (medium confidence).
{4.3, 4.5, 4.7, 5.3, 9.2, TS.2.4} (Figure SPM.8)
B.5.2 Mountain and polar glaciers are committed to continue melting for decades or centuries (very high confidence). Loss of
permafrost carbon following permafrost thaw is irreversible at centennial time scales (high confidence). Continued ice
loss over the 21st century is virtually certain for the Greenland Ice Sheet and likely for the Antarctic Ice Sheet. There is
high confidence that total ice loss from the Greenland Ice Sheet will increase with cumulative emissions. There is limited
evidence for low-likelihood, high-impact outcomes (resulting from ice-sheet instability processes characterized by deep
uncertainty and in some cases involving tipping points) that would strongly increase ice loss from the Antarctic Ice Sheet
for centuries under high GHG emissions scenarios.34
{4.3, 4.7, 5.4, 9.4, 9.5, Box 9.4, Box TS.1, TS.2.5}
B.5.3 It is virtually certain that global mean sea level will continue to rise over the 21st century. Relative to 1995–2014, the likely
global mean sea level rise by 2100 is 0.28–0.55 m under the very low GHG emissions scenario (SSP1-1.9); 0.32–0.62 m
under the low GHG emissions scenario (SSP1-2.6); 0.44–0.76 m under the intermediate GHG emissions scenario (SSP2-4.5);
and 0.63–1.01 m under the very high GHG emissions scenario (SSP5-8.5); and by 2150 is 0.37–0.86 m under the very
low scenario (SSP1-1.9); 0.46–0.99 m under the low scenario (SSP1-2.6); 0.66–1.33 m under the intermediate scenario
(SSP2-4.5); and 0.98–1.88 m under the very high scenario (SSP5-8.5) (medium confidence).35 Global mean sea level rise
above the likely range – approaching 2 m by 2100 and 5 m by 2150 under a very high GHG emissions scenario (SSP5-8.5)
(low confidence) – cannot be ruled out due to deep uncertainty in ice-sheet processes.
{4.3, 9.6, Box 9.4, Box TS.4} (Figure SPM.8)
B.5.4 In the longer term, sea level is committed to rise for centuries to millennia due to continuing deep-ocean warming and
ice-sheet melt and will remain elevated for thousands of years (high confidence). Over the next 2000 years, global mean
sea level will rise by about 2 to 3 m if warming is limited to 1.5°C, 2 to 6 m if limited to 2°C and 19 to 22 m with 5°C of
warming, and it will continue to rise over subsequent millennia (low confidence). Projections of multi-millennial global
mean sea level rise are consistent with reconstructed levels during past warm climate periods: likely 5–10 m higher than
today around 125,000 years ago, when global temperatures were very likely 0.5°C–1.5°C higher than 1850–1900; and very
likely 5–25 m higher roughly 3 million years ago, when global temperatures were 2.5°C–4°C higher (medium confidence).
{2.3, Cross-Chapter Box 2.4, 9.6, Box TS.2, Box TS.4, Box TS.9}
33 The other sectoral emissions are calculated as the residual of the net land and ocean CO2 uptake and the prescribed atmospheric CO2 concentration changes in the CMIP6
simulations. These calculated emissions are net emissions and do not separate gross anthropogenic emissions from removals, which are included implicitly.
34 Low-likelihood, high-impact outcomes are those whose probability of occurrence is low or not well known (as in the context of deep uncertainty) but whose potential impacts on
society and ecosystems could be high. A tipping point is a critical threshold beyond which a system reorganizes, often abruptly and/or irreversibly. (Glossary) {1.4, Cross-Chapter Box
1.3, 4.7}
35 To compare to the 1986–2005 baseline period used in AR5 and SROCC, add 0.03 m to the global mean sea level rise estimates. To compare to the 1900 baseline period used in
Figure SPM.8, add 0.16 m.
22
SPM
Summary for Policymakers
Figure SPM.8 | Selected indicators of global climate change under the five illustrative scenarios used in this Report
The projections for each of the five scenarios are shown in colour. Shades represent uncertainty ranges – more detail is provided for each panel below. The black
curves represent the historical simulations (panels a, b, c) or the observations (panel d). Historical values are included in all graphs to provide context for the
projected future changes.
Human activities affect all the major climate system components, with
some responding over decades and others over centuries
(d) Global mean sea level change relative to 1900
Low-likelihood, high-impact storyline,
including ice-sheet instability
processes, under SSP5-8.5
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
1950 2000 2020 2050 2100
1
1.5
2
0.5
0
m
SSP1-1.9
(e) Global mean sea
level change in 2300
relative to 1900
2 m
3 m
4 m
5 m
6 m
7 m
8 m
9 m
1 m
0 m
Sea level rise greater than
15 m cannot be ruled out
with high emissions
2300
SSP1-2.6
SSP5-8.5
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
(c) Global ocean surface pH (a measure of acidity)
ocean
acidification
1950 2000 2015 2050 2100
7.6
7.8
7.7
7.9
8.0
8.1
8.2
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
(b) September Arctic sea ice area
0
4
6
8
10
106 km2
2
1950 2000 2015 2050 2100
Practically ice-free
°C
0
–1
1950 2000 2015 2050 2100
1
2
3
4
5
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
(a) Global surface temperature change relative to 1850–1900
T T r T
T T r r
I T T T
r r
r T T T Tr
23
SPM
Summary for Policymakers
Panel (a) Global surface temperature changes in °C relative to 1850–1900. These changes were obtained by combining Coupled Model Intercomparison
Project Phase 6 (CMIP6) model simulations with observational constraints based on past simulated warming, as well as an updated assessment of equilibrium climate
sensitivity (see Box SPM.1). Changes relative to 1850–1900 based on 20-year averaging periods are calculated by adding 0.85°C (the observed global surface
temperature increase from 1850–1900 to 1995–2014) to simulated changes relative to 1995–2014. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0.
Panel (b) September Arctic sea ice area in 106 km2 based on CMIP6 model simulations. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0. The Arctic is
projected to be practically ice-free near mid-century under intermediate and high GHG emissions scenarios.
Panel (c) Global ocean surface pH (a measure of acidity) based on CMIP6 model simulations. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0.
Panel (d) Global mean sea level change in metres, relative to 1900. The historical changes are observed (from tide gauges before 1992 and altimeters
afterwards), and the future changes are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models. Likely
ranges are shown for SSP1-2.6 and SSP3-7.0. Only likely ranges are assessed for sea level changes due to difficulties in estimating the distribution of deeply
uncertain processes. The dashed curve indicates the potential impact of these deeply uncertain processes. It shows the 83rd percentile of SSP5-8.5 projections that
include low-likelihood, high-impact ice-sheet processes that cannot be ruled out; because of low confidence in projections of these processes, this curve does not
constitute part of a likely range. Changes relative to 1900 are calculated by adding 0.158 m (observed global mean sea level rise from 1900 to 1995–2014) to
simulated and observed changes relative to 1995–2014.
Panel (e) Global mean sea level change at 2300 in metres relative to 1900. Only SSP1-2.6 and SSP5-8.5 are projected at 2300, as simulations that extend
beyond 2100 for the other scenarios are too few for robust results. The 17th–83rd percentile ranges are shaded. The dashed arrow illustrates the 83rd percentile
of SSP5-8.5 projections that include low-likelihood, high-impact ice-sheet processes that cannot be ruled out.
Panels (b) and (c) are based on single simulations from each model, and so include a component of internal variability. Panels (a), (d) and (e) are based on long-term
averages, and hence the contributions from internal variability are small.
{4.3; Figures 4.2, 4.8, and 4.11; 9.6; Figure 9.27; Figures TS.8 and TS.11; Box TS.4, Figure 1}
36 Climatic impact-drivers (CIDs) are physical climate system conditions (e.g., means, events, extremes) that affect an element of society or ecosystems. Depending on system tolerance,
CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions (Glossary). CID types include heat and cold, wet
and dry, wind, snow and ice, coastal and open ocean.
37 The main internal variability phenomena include El Niño–Southern Oscillation, Pacific Decadal Variability and Atlantic Multi-decadal Variability through their regional influence.
C. Climate Information for Risk Assessment
and Regional Adaptation
Physical climate information addresses how the climate system responds to the interplay between human influence, natural drivers
and internal variability. Knowledge of the climate response and the range of possible outcomes, including low-likelihood, high
impact outcomes, informs climate services, the assessment of climate-related risks, and adaptation planning. Physical climate
information at global, regional and local scales is developed from multiple lines of evidence, including observational products,
climate model outputs and tailored diagnostics.
C.1 Natural drivers and internal variability will modulate human-caused changes, especially at regional scales and
in the near term, with little effect on centennial global warming. These modulations are important to consider
in planning for the full range of possible changes.
{1.4, 2.2, 3.3, Cross-Chapter Box 3.1, 4.4, 4.6, Cross-Chapter Box 4.1, Box 7.2, 8.3, 8.5, 9.2, 10.3, 10.4, 10.6,
11.3, 12.5, Atlas.4, Atlas.5, Atlas.8, Atlas.9, Atlas.10, Atlas.11, Cross-Chapter Box Atlas.2}
C.1.1 The historical global surface temperature record highlights that decadal variability has both enhanced and masked
underlying human-caused long-term changes, and this variability will continue into the future (very high confidence). For
example, internal decadal variability and variations in solar and volcanic drivers partially masked human-caused surface
global warming during 1998–2012, with pronounced regional and seasonal signatures (high confidence). Nonetheless,
the heating of the climate system continued during this period, as reflected in both the continued warming of the global
ocean (very high confidence) and in the continued rise of hot extremes over land (medium confidence).
{1.4, 3.3, Cross-Chapter Box 3.1, 4.4, Box 7.2, 9.2, 11.3, Cross-Section Box TS.1} (Figure SPM.1)
C.1.2 Projected human-caused changes in mean climate and climatic impact-drivers (CIDs),36 including extremes, will be either
amplified or attenuated by internal variability (high confidence).37 Near-term cooling at any particular location with
respect to present climate could occur and would be consistent with the global surface temperature increase due to
human influence (high confidence).
{1.4, 4.4, 4.6, 10.4, 11.3, 12.5, Atlas.5, Atlas.10, Atlas.11, TS.4.2}
24
SPM
Summary for Policymakers
C.1.3 Internal variability has largely been responsible for the amplification and attenuation of the observed human-caused
decadal-to-multi-decadal mean precipitation changes in many land regions (high confidence). At global and regional
scales, near-term changes in monsoons will be dominated by the effects of internal variability (medium confidence).
In addition to the influence of internal variability, near-term projected changes in precipitation at global and regional
scales are uncertain because of model uncertainty and uncertainty in forcings from natural and anthropogenic aerosols
(medium confidence).
{1.4, 4.4, 8.3, 8.5, 10.3, 10.4, 10.5, 10.6, Atlas.4, Atlas.8, Atlas.9, Atlas.10, Atlas.11, Cross-Chapter Box Atlas.2, TS.4.2,
Box TS.6, Box TS.13}
C.1.4 Based on paleoclimate and historical evidence, it is likely that at least one large explosive volcanic eruption would occur
during the 21st century.38 Such an eruption would reduce global surface temperature and precipitation, especially over land,
for one to three years, alter the global monsoon circulation, modify extreme precipitation and change many CIDs (medium
confidence). If such an eruption occurs, this would therefore temporarily and partially mask human-caused climate change.
{2.2, 4.4, Cross-Chapter Box 4.1, 8.5, TS.2.1}
C.2 With further global warming, every region is projected to increasingly experience concurrent and multiple
changes in climatic impact-drivers. Changes in several climatic impact-drivers would be more widespread
at 2°C compared to 1.5°C global warming and even more widespread and/or pronounced for higher
warming levels.
{8.2, 9.3, 9.5, 9.6, Box 10.3, 11.3, 11.4, 11.5, 11.6, 11.7, 11.9, Box 11.3, Box 11.4, Cross-Chapter Box 11.1, 12.2,
12.3, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.4, Atlas.5, Atlas.6, Atlas.7, Atlas.8, Atlas.9, Atlas.10, Atlas.11}
(Table SPM.1, Figure SPM.9)
C.2.1 All regions39 are projected to experience further increases in hot climatic impact-drivers (CIDs) and decreases in cold
CIDs (high confidence). Further decreases are projected in permafrost; snow, glaciers and ice sheets; and lake and Arctic
sea ice (medium to high confidence).40 These changes would be larger at 2°C global warming or above than at 1.5°C
(high confidence). For example, extreme heat thresholds relevant to agriculture and health are projected to be exceeded
more frequently at higher global warming levels (high confidence).
{9.3, 9.5, 11.3, 11.9, Cross-Chapter Box 11.1, 12.3, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.4, Atlas.5, Atlas.6, Atlas.7,
Atlas.8, Atlas.9, Atlas.10, Atlas.11, TS.4.3} (Table SPM.1, Figure SPM.9)
C.2.2 At 1.5°C global warming, heavy precipitation and associated flooding are projected to intensify and be more frequent
in most regions in Africa and Asia (high confidence), North America (medium to high confidence)40 and Europe (medium
confidence). Also, more frequent and/or severe agricultural and ecological droughts are projected in a few regions in all
inhabited continents except Asia compared to 1850–1900 (medium confidence); increases in meteorological droughts are
also projected in a few regions (medium confidence). A small number of regions are projected to experience increases or
decreases in mean precipitation (medium confidence).
{11.4, 11.5, 11.6, 11.9, Atlas.4, Atlas.5, Atlas.7, Atlas.8, Atlas.9, Atlas.10, Atlas.11, TS.4.3} (Table SPM.1)
C.2.3 At 2°C global warming and above, the level of confidence in and the magnitude of the change in droughts and heavy
and mean precipitation increase compared to those at 1.5°C. Heavy precipitation and associated flooding events
are projected to become more intense and frequent in the Pacific Islands and across many regions of North America
and Europe (medium to high confidence).40 These changes are also seen in some regions in Australasia and Central and
South America (medium confidence). Several regions in Africa, South America and Europe are projected to experience an
increase in frequency and/or severity of agricultural and ecological droughts with medium to high confidence;40 increases
are also projected in Australasia, Central and North America, and the Caribbean with medium confidence. A small number
of regions in Africa, Australasia, Europe and North America are also projected to be affected by increases in hydrological
droughts, and several regions are projected to be affected by increases or decreases in meteorological droughts, with
more regions displaying an increase (medium confidence). Mean precipitation is projected to increase in all polar, northern
European and northern North American regions, most Asian regions and two regions of South America (high confidence).
{11.4, 11.6, 11.9, Cross-Chapter Box 11.1, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.5, Atlas.7, Atlas.8, Atlas.9, Atlas.11,
TS.4.3} (Table SPM.1, Figure SPM.5, Figure SPM.6, Figure SPM.9)
38 Based on 2500 year reconstructions, eruptions more negative than –1 W m–2 occur on average twice per century.
39 Regions here refer to the AR6 WGI reference regions used in this Report to summarize information in sub-continental and oceanic regions. Changes are compared to averages over
the last 20–40 years unless otherwise specified. {1.4, 12.4, Atlas.1}.
40 The specific level of confidence or likelihood depends on the region considered. Details can be found in the Technical Summary and the underlying Report.
25
SPM
Summary for Policymakers
C.2.4 More CIDs across more regions are projected to change at 2°C and above compared to 1.5°C global warming
(high confidence). Region-specific changes include intensification of tropical cyclones and/or extratropical storms
(medium confidence), increases in river floods (medium to high confidence),40 reductions in mean precipitation and
increases in aridity (medium to high confidence),40 and increases in fire weather (medium to high confidence).40 There
is low confidence in most regions in potential future changes in other CIDs, such as hail, ice storms, severe storms, dust
storms, heavy snowfall and landslides.
{11.7, 11.9, Cross-Chapter Box 11.1, 12.4, 12.5, Cross-Chapter Box 12.1, Atlas.4, Atlas.6, Atlas.7, Atlas.8, Atlas.10, TS.4.3.1,
TS.4.3.2, TS.5} (Table SPM.1, Figure SPM.9)
C.2.5 It is very likely to virtually certain40 that regional mean relative sea level rise will continue throughout the 21st century,
except in a few regions with substantial geologic land uplift rates. Approximately two-thirds of the global coastline has
a projected regional relative sea level rise within ±20% of the global mean increase (medium confidence). Due to relative
sea level rise, extreme sea level events that occurred once per century in the recent past are projected to occur at least
annually at more than half of all tide gauge locations by 2100 (high confidence). Relative sea level rise contributes to
increases in the frequency and severity of coastal flooding in low-lying areas and to coastal erosion along most sandy
coasts (high confidence).
{9.6, 12.4, 12.5, Cross-Chapter Box 12.1, Box TS.4, TS.4.3} (Figure SPM.9)
C.2.6 Cities intensify human-induced warming locally, and further urbanization together with more frequent hot extremes will
increase the severity of heatwaves (very high confidence). Urbanization also increases mean and heavy precipitation
over and/or downwind of cities (medium confidence) and resulting runoff intensity (high confidence). In coastal cities,
the combination of more frequent extreme sea level events (due to sea level rise and storm surge) and extreme rainfall/
riverflow events will make flooding more probable (high confidence).
{8.2, Box 10.3, 11.3, 12.4, Box TS.14}
C.2.7 Many regions are projected to experience an increase in the probability of compound events with higher global warming
(high confidence). In particular, concurrent heatwaves and droughts are likely to become more frequent. Concurrent
extremes at multiple locations, including in crop-producing areas, become more frequent at 2°C and above compared to
1.5°C global warming (high confidence).
{11.8, Box 11.3, Box 11.4, 12.3, 12.4, Cross-Chapter Box 12.1, TS.4.3} (Table SPM.1)
26
SPM
Summary for Policymakers
Figure SPM.9 | Synthesis of the number of AR6 WGI reference regions where climatic impact-drivers are projected to change
A total of 35 climatic impact-drivers (CIDs) grouped into seven types are shown: heat and cold; wet and dry; wind; snow and ice; coastal; open ocean; and other.
For each CID, the bar in the graph below displays the number of AR6 WGI reference regions where it is projected to change. The colours represent the direction
of change and the level of confidence in the change: purple indicates an increase while brown indicates a decrease; darker and lighter shades refer to high and
medium confidence, respectively. Lighter background colours represent the maximum number of regions for which each CID is broadly relevant.
Panel (a) shows the 30 CIDs relevant to the land and coastal regions, while panel (b) shows the five CIDs relevant to the open-ocean regions. Marine heatwaves
and ocean acidity are assessed for coastal ocean regions in panel (a) and for open-ocean regions in panel (b). Changes refer to a 20–30-year period centred around 2050
and/or consistent with 2°C global warming compared to a similar period within 1960–2014, except for hydrological drought and agricultural and ecological drought, which
is compared to 1850–1900. Definitions of the regions are provided in Sections 12.4 and Atlas.1 and the Interactive Atlas (see https://interactive-atlas.ipcc.ch/).
{11.9, 12.2, 12.4, Atlas.1, Table TS.5, Figures TS.22 and TS.25} (Table SPM.1)
Multiple climatic impact-drivers are projected to change in all regions
of the world
Number of land & coastal regions (a) and open-ocean regions (b) where each climatic impact-driver (CID) is projected
to increase or decrease with high confidence (dark shade) or medium confidence (light shade)
Climatic impact-drivers (CIDs) are physical climate system conditions (e.g., means, events, extremes) that affect an element
of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral,
or a mixture of each across interacting system elements and regions. The CIDs are grouped into seven types, which are
summarized under the icons in the figure. All regions are projected to experience changes in at least 5 CIDs. Almost all
(96%) are projected to experience changes in at least 10 CIDs and half in at least 15 CIDs. For many CID changes, there is
wide geographical variation, and so each region is projected to experience a specific set of CID changes. Each bar in the
chart represents a specific geographical set of changes that can be explored in the WGI Interactive Atlas.
Relative sea level
Coastal flood
Coastal erosion
Marine heatwave
Ocean acidity
Mean ocean temperature
Marine heatwave
Ocean acidity
Ocean salinity
Dissolved oxygen
Mean surface temperature
Extreme heat
Cold spell
Frost
Mean precipitation
River flood
Heavy precipitation and pluvial flood
Landslide
Aridity
Hydrological drought
Agricultural and ecological drought
Fire weather
Mean wind speed
Severe wind storm
Tropical cyclone
Sand and dust storm
Snow, glacier and ice sheet
Permafrost
Lake, river and sea ice
Heavy snowfall and ice storm
Hail
Snow avalanche
Air pollution weather
Atmospheric CO2 at surface
Radiation at surface
Heat and Cold Wet and Dry Wind Snow and Ice Other Coastal Open Ocean
5
5
15
15
5
5
15
15
25
25
35
35
45
45
55
55
NUMBER OF LAND & COASTAL REGIONS
NUMBER OF OPEN-OCEAN REGIONS
(a) (b)
Regions with high confidence increase
Regions with medium confidence increase
Regions with high confidence decrease
Regions with medium confidence decrease
Changes refer to a 20–30
year period centred around
2050 and/or consistent
with 2°C global warming
compared to a similar
period within 1960–2014
or 1850–1900.
interactive-atlas.ipcc.ch
The height of the lighter shaded ‘envelope’ behind each bar
represents the maximum number of regions for which each
CID is relevant. The envelope is symmetrical about the x-axis
showing the maximum possible number of relevant regions
for CID increase (upper part) or decrease (lower part).
BAR CHART LEGEND LIGHTER-SHADED ‘ENVELOPE’ LEGEND ASSESSED FUTURE CHANGES
I I
I
I I
e
00000000000000000000000000000
■■
■■
000
Ill
27
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Summary for Policymakers
C.3 Low-likelihood outcomes, such as ice-sheet collapse, abrupt ocean circulation changes, some compound
extreme events, and warming substantially larger than the assessed very likely range of future warming,
cannot be ruled out and are part of risk assessment.
{1.4, Cross-Chapter Box 1.3, 4.3, 4.4, 4.8, Cross-Chapter Box 4.1, 8.6, 9.2, Box 9.4, 11.8, Box 11.2, Cross-Chapter
Box 12.1} (Table SPM.1)
C.3.1 If global warming exceeds the assessed very likely range for a given GHG emissions scenario, including low GHG emissions
scenarios, global and regional changes in many aspects of the climate system, such as regional precipitation and other
CIDs, would also exceed their assessed very likely ranges (high confidence). Such low-likelihood, high-warming outcomes
are associated with potentially very large impacts, such as through more intense and more frequent heatwaves and heavy
precipitation, and high risks for human and ecological systems, particularly for high GHG emissions scenarios.
{Cross-Chapter Box 1.3, 4.3, 4.4, 4.8, Box 9.4, Box 11.2, Cross-Chapter Box 12.1, TS.1.4, Box TS.3, Box TS.4} (Table SPM.1)
C.3.2 Low-likelihood, high-impact outcomes34 could occur at global and regional scales even for global warming within the
very likely range for a given GHG emissions scenario. The probability of low-likelihood, high-impact outcomes increases
with higher global warming levels (high confidence). Abrupt responses and tipping points of the climate system, such as
strongly increased Antarctic ice-sheet melt and forest dieback, cannot be ruled out (high confidence).
{1.4, 4.3, 4.4, 4.8, 5.4, 8.6, Box 9.4, Cross-Chapter Box 12.1, TS.1.4, TS.2.5, Box TS.3, Box TS.4, Box TS.9} (Table SPM.1)
C.3.3 If global warming increases, some compound extreme events18 with low likelihood in past and current climate will become
more frequent, and there will be a higher likelihood that events with increased intensities, durations and/or spatial extents
unprecedented in the observational record will occur (high confidence).
{11.8, Box 11.2, Cross-Chapter Box 12.1, Box TS.3, Box TS.9}
C.3.4 The Atlantic Meridional Overturning Circulation is very likely to weaken over the 21st century for all emissions scenarios.
While there is high confidence in the 21st century decline, there is only low confidence in the magnitude of the trend.
There is medium confidence that there will not be an abrupt collapse before 2100. If such a collapse were to occur, it
would very likely cause abrupt shifts in regional weather patterns and water cycle, such as a southward shift in the
tropical rain belt, weakening of the African and Asian monsoons and strengthening of Southern Hemisphere monsoons,
and drying in Europe.
{4.3, 8.6, 9.2, TS2.4, Box TS.3}
C.3.5 Unpredictable and rare natural events not related to human influence on climate may lead to low-likelihood, high-impact
outcomes. For example, a sequence of large explosive volcanic eruptions within decades has occurred in the past, causing
substantial global and regional climate perturbations over several decades. Such events cannot be ruled out in the future,
but due to their inherent unpredictability they are not included in the illustrative set of scenarios referred to in this Report
{2.2, Cross-Chapter Box 4.1, Box TS.3} (Box SPM.1)
D. Limiting Future Climate Change
Since AR5, estimates of remaining carbon budgets have been improved by a new methodology first presented in SR1.5, updated
evidence, and the integration of results from multiple lines of evidence. A comprehensive range of possible future air pollution
controls in scenarios is used to consistently assess the effects of various assumptions on projections of climate and air pollution.
A novel development is the ability to ascertain when climate responses to emissions reductions would become discernible above
natural climate variability, including internal variability and responses to natural drivers.
D.1 From a physical science perspective, limiting human-induced global warming to a specific level requires
limiting cumulative CO2 emissions, reaching at least net zero CO2 emissions, along with strong reductions in
other greenhouse gas emissions. Strong, rapid and sustained reductions in CH4 emissions would also limit the
warming effect resulting from declining aerosol pollution and would improve air quality.
{3.3, 4.6, 5.1, 5.2, 5.4, 5.5, 5.6, Box 5.2, Cross-Chapter Box 5.1, 6.7, 7.6, 9.6} (Figure SPM.10, Table SPM.2)
28
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Summary for Policymakers
D.1.1 This Report reaffirms with high confidence the AR5 finding that there is a near-linear relationship between cumulative
anthropogenic CO2 emissions and the global warming they cause. Each 1000 GtCO2 of cumulative CO2 emissions is assessed
to likely cause a 0.27°C to 0.63°C increase in global surface temperature with a best estimate of 0.45°C.41 This is a narrower
range compared to AR5 and SR1.5. This quantity is referred to as the transient climate response to cumulative CO2 emissions
(TCRE). This relationship implies that reaching net zero anthropogenic CO2 emissions42 is a requirement to stabilize
human-induced global temperature increase at any level, but that limiting global temperature increase to a specific level
would imply limiting cumulative CO2 emissions to within a carbon budget.43 {5.4, 5.5, TS.1.3, TS.3.3, Box TS.5} (Figure SPM.10)
41 In the literature, units of °C per 1000 PgC (petagrams of carbon) are used, and the AR6 reports the TCRE likely range as 1.0°C to 2.3°C per 1000 PgC in the underlying report, with
a best estimate of 1.65°C.
42 The condition in which anthropogenic carbon dioxide (CO2) emissions are balanced by anthropogenic CO2 removals over a specified period (Glossary).
43 The term ‘carbon budget’ refers to the maximum amount of cumulative net global anthropogenic CO2 emissions that would result in limiting global warming to a given level with
a given probability, taking into account the effect of other anthropogenic climate forcers. This is referred to as the total carbon budget when expressed starting from the pre-industrial
period, and as the remaining carbon budget when expressed from a recent specified date (Glossary). Historical cumulative CO2 emissions determine to a large degree warming to
date, while future emissions cause future additional warming. The remaining carbon budget indicates how much CO2 could still be emitted while keeping warming below a specific
temperature level.
Figure SPM.10 | Near-linear relationship between cumulative CO2 emissions and the increase in global surface temperature
Top panel: Historical data (thin black line) shows observed global surface temperature increase in °C since 1850–1900 as a function of historical cumulative carbon
dioxide (CO2) emissions in GtCO2 from 1850 to 2019. The grey range with its central line shows a corresponding estimate of the historical human-caused surface
warming (see Figure SPM.2). Coloured areas show the assessed very likely range of global surface temperature projections, and thick coloured central lines show the
median estimate as a function of cumulative CO2 emissions from 2020 until year 2050 for the set of illustrative scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and
SSP5-8.5; see Figure SPM.4). Projections use the cumulative CO2 emissions of each respective scenario, and the projected global warming includes the contribution
from all anthropogenic forcers. The relationship is illustrated over the domain of cumulative CO2 emissions for which there is high confidence that the transient climate
response to cumulative CO2 emissions (TCRE) remains constant, and for the time period from 1850 to 2050 over which global CO2 emissions remain net positive under
all illustrative scenarios, as there is limited evidence supporting the quantitative application of TCRE to estimate temperature evolution under net negative CO2 emissions.
Bottom panel: Historical and projected cumulative CO2 emissions in GtCO2 for the respective scenarios.
{Section 5.5, Figure 5.31, Figure TS.18}
Every tonne of CO₂ emissions adds to global warming
Future cumulative
CO₂ emissions differ
across scenarios and
determine how much
warming we will
experience.
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
Cumulative CO₂ emissions between 1850 and 2019 Cumulative CO₂ emissions between 2020 and 2050
Historical global
warming
The near-linear relationship
between the cumulative
CO₂ emissions and global
warming for five illustrative
scenarios until year 2050
SSP1-1.9
SSP1-2.6
SSP2-4.5
SSP3-7.0
SSP5-8.5
1000 2000 3000 4000 4500
Cumulative CO₂ emissions since 1850
–0.5
0
0.5
1
1.5
2
2.5
3
Global surface temperature increase since 1850–1900 (OC) as a function of cumulative CO₂ emissions (GtCO₂)
OC
1850
time
1900
1950
2000
2020
2019
2030
2040
2050
HISTORICAL PROJECTIONS
GtCO₂
29
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Summary for Policymakers
D.1.2 Over the period 1850–2019, a total of 2390 ± 240 (likely range) GtCO2 of anthropogenic CO2 was emitted. Remaining
carbon budgets have been estimated for several global temperature limits and various levels of probability, based on the
estimated value of TCRE and its uncertainty, estimates of historical warming, variations in projected warming from non-
CO2 emissions, climate system feedbacks such as emissions from thawing permafrost, and the global surface temperature
change after global anthropogenic CO2 emissions reach net zero.
{5.1, 5.5, Box 5.2, TS.3.3} (Table SPM.2)
44 Compared to AR5, and when taking into account emissions since AR5, estimates in AR6 are about 300–350 GtCO2 larger for the remaining carbon budget consistent with limiting
warming to 1.5°C; for 2°C, the difference is about 400–500 GtCO2.
45 Potential negative and positive effects of CDR for biodiversity, water and food production are methods-specific and are often highly dependent on local context, management, prior
land use, and scale. IPCC Working Groups II and III assess the CDR potential and ecological and socio-economic effects of CDR methods in their AR6 contributions.
Table SPM.2 | Estimates of historical carbon dioxide (CO2) emissions and remaining carbon budgets. Estimated remaining carbon budgets are
calculated from the beginning of 2020 and extend until global net zero CO2 emissions are reached. They refer to CO2 emissions, while accounting for the global
warming effect of non-CO2 emissions. Global warming in this table refers to human-induced global surface temperature increase, which excludes the impact
of natural variability on global temperatures in individual years.
{Table 3.1, 5.5.1, 5.5.2, Box 5.2, Table 5.1, Table 5.7, Table 5.8, Table TS.3}
Global Warming Between
1850–1900 and 2010–2019 (°C)
Historical Cumulative CO2 Emissions from 1850 to 2019 (GtCO2)
1.07 (0.8–1.3; likely range) 2390 (± 240; likely range)
Approximate global
warming relative
to 1850–1900 until
temperature limit (°C)a
Additional global
warming relative to
2010–2019 until temperature
limit (°C)
Estimated remaining carbon budgets
from the beginning of 2020 (GtCO2)
Likelihood of limiting global warming
to temperature limitb
Variations in reductions
in non-CO2 emissionsc
17% 33% 50% 67% 83%
1.5 0.43 900 650 500 400 300
Higher or lower reductions in
accompanying non-CO2 emissions can
increase or decrease the values on
the left by 220 GtCO2 or more
1.7 0.63 1450 1050 850 700 550
2.0 0.93 2300 1700 1350 1150 900
a Values at each 0.1°C increment of warming are available in Tables TS.3 and 5.8.
b This likelihood is based on the uncertainty in transient climate response to cumulative CO2 emissions (TCRE) and additional Earth system feedbacks and provides the
probability that global warming will not exceed the temperature levels provided in the two left columns. Uncertainties related to historical warming (±550 GtCO2)
and non-CO2 forcing and response (±220 GtCO2) are partially addressed by the assessed uncertainty in TCRE, but uncertainties in recent emissions since 2015
(±20 GtCO2) and the climate response after net zero CO2 emissions are reached (±420 GtCO2) are separate.
c Remaining carbon budget estimates consider the warming from non-CO2 drivers as implied by the scenarios assessed in SR1.5. The Working Group III Contribution
to AR6 will assess mitigation of non-CO2 emissions.
D.1.3 Several factors that determine estimates of the remaining carbon budget have been re-assessed, and updates to these
factors since SR1.5 are small. When adjusted for emissions since previous reports, estimates of remaining carbon budgets
are therefore of similar magnitude compared to SR1.5 but larger compared to AR5 due to methodological improvements.44
{5.5, Box 5.2, TS.3.3} (Table SPM.2)
D.1.4 Anthropogenic CO2 removal (CDR) has the potential to remove CO2 from the atmosphere and durably store it in reservoirs
(high confidence). CDR aims to compensate for residual emissions to reach net zero CO2 or net zero GHG emissions or, if
implemented at a scale where anthropogenic removals exceed anthropogenic emissions, to lower surface temperature.
CDR methods can have potentially wide-ranging effects on biogeochemical cycles and climate, which can either weaken
or strengthen the potential of these methods to remove CO2 and reduce warming, and can also influence water availability
and quality, food production and biodiversity45 (high confidence).
{5.6, Cross-Chapter Box 5.1, TS.3.3}
D.1.5 Anthropogenic CO2 removal (CDR) leading to global net negative emissions would lower the atmospheric CO2 concentration
and reverse surface ocean acidification (high confidence). Anthropogenic CO2 removals and emissions are partially
30
SPM
Summary for Policymakers
compensated by CO2 release and uptake respectively, from or to land and ocean carbon pools (very high confidence).
CDR would lower atmospheric CO2 by an amount approximately equal to the increase from an anthropogenic emission of
the same magnitude (high confidence). The atmospheric CO2 decrease from anthropogenic CO2 removals could be up to
10% less than the atmospheric CO2 increase from an equal amount of CO2 emissions, depending on the total amount of
CDR (medium confidence).
{5.3, 5.6, TS.3.3}
D.1.6 If global net negative CO2 emissions were to be achieved and be sustained, the global CO2-induced surface temperature
increase would be gradually reversed but other climate changes would continue in their current direction for decades to
millennia (high confidence). For instance, it would take several centuries to millennia for global mean sea level to reverse
course even under large net negative CO2 emissions (high confidence).
{4.6, 9.6, TS.3.3}
D.1.7 In the five illustrative scenarios, simultaneous changes in CH4, aerosol and ozone precursor emissions, which also
contribute to air pollution, lead to a net global surface warming in the near and long term (high confidence). In the
long term, this net warming is lower in scenarios assuming air pollution controls combined with strong and sustained
CH4 emissions reductions (high confidence). In the low and very low GHG emissions scenarios, assumed reductions in
anthropogenic aerosol emissions lead to a net warming, while reductions in CH4 and other ozone precursor emissions
lead to a net cooling. Because of the short lifetime of both CH4 and aerosols, these climate effects partially counterbalance
each other, and reductions in CH4 emissions also contribute to improved air quality by reducing global surface ozone
(high confidence).
{6.7, Box TS.7} (Figure SPM.2, Box SPM.1)
D.1.8 Achieving global net zero CO2 emissions, with anthropogenic CO2 emissions balanced by anthropogenic removals of
CO2, is a requirement for stabilizing CO2-induced global surface temperature increase. This is different from achieving
net zero GHG emissions, where metric-weighted anthropogenic GHG emissions equal metric-weighted anthropogenic
GHG removals. For a given GHG emissions pathway, the pathways of individual GHGs determine the resulting climate
response,46 whereas the choice of emissions metric47 used to calculate aggregated emissions and removals of different
GHGs affects what point in time the aggregated GHGs are calculated to be net zero. Emissions pathways that reach and
sustain net zero GHG emissions defined by the 100-year global warming potential are projected to result in a decline in
surface temperature after an earlier peak (high confidence).
{4.6, 7.6, Box 7.3, TS.3.3}
D.2 Scenarios with very low or low GHG emissions (SSP1-1.9 and SSP1-2.6) lead within years to discernible effects
on greenhouse gas and aerosol concentrations and air quality, relative to high and very high GHG emissions
scenarios (SSP3-7.0 or SSP5-8.5). Under these contrasting scenarios, discernible differences in trends of global
surface temperature would begin to emerge from natural variability within around 20 years, and over longer
time periods for many other climatic impact-drivers (high confidence).
{4.6, 6.6, 6.7, Cross-Chapter Box 6.1, 9.6, 11.2, 11.4, 11.5, 11.6, Cross-Chapter Box 11.1, 12.4, 12.5} (Figure
SPM.8, Figure SPM.10)
D.2.1 Emissions reductions in 2020 associated with measures to reduce the spread of COVID-19 led to temporary but detectable
effects on air pollution (high confidence) and an associated small, temporary increase in total radiative forcing, primarily
due to reductions in cooling caused by aerosols arising from human activities (medium confidence). Global and regional
climate responses to this temporary forcing are, however, undetectable above natural variability (high confidence).
Atmospheric CO2 concentrations continued to rise in 2020, with no detectable decrease in the observed CO2 growth rate
(medium confidence).48
{Cross-Chapter Box 6.1, TS.3.3}
D.2.2 Reductions in GHG emissions also lead to air quality improvements. However, in the near term,49 even in scenarios with
strong reduction of GHGs, as in the low and very low GHG emissions scenarios (SSP1-2.6 and SSP1-1.9), these improvements
46 A general term for how the climate system responds to a radiative forcing (Glossary).
47 The choice of emissions metric depends on the purposes for which gases or forcing agents are being compared. This Report contains updated emissions metric values and assesses
new approaches to aggregating gases.
48 For other GHGs, there was insufficient literature available at the time of the assessment to assess detectable changes in their atmospheric growth rate during 2020.
49 Near term: 2021–2040.
31
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Summary for Policymakers
are not sufficient in many polluted regions to achieve air quality guidelines specified by the World Health Organization
(high confidence). Scenarios with targeted reductions of air pollutant emissions lead to more rapid improvements in air
quality within years compared to reductions in GHG emissions only, but from 2040, further improvements are projected
in scenarios that combine efforts to reduce air pollutants as well as GHG emissions, with the magnitude of the benefit
varying between regions (high confidence).
{6.6, 6.7, Box TS.7}.
D.2.3 Scenarios with very low or low GHG emissions (SSP1-1.9 and SSP1-2.6) would have rapid and sustained effects to limit
human-caused climate change, compared with scenarios with high or very high GHG emissions (SSP3-7.0 or SSP5-8.5),
but early responses of the climate system can be masked by natural variability. For global surface temperature, differences
in 20-year trends would likely emerge during the near term under a very low GHG emissions scenario (SSP1-1.9), relative
to a high or very high GHG emissions scenario (SSP3-7.0 or SSP5-8.5). The response of many other climate variables would
emerge from natural variability at different times later in the 21st century (high confidence).
{4.6, Cross-Section Box TS.1} (Figure SPM.8, Figure SPM.10)
D.2.4 Scenarios with very low and low GHG emissions (SSP1-1.9 and SSP1-2.6) would lead to substantially smaller changes
in a range of CIDs36 beyond 2040 than under high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5).
By the end of the century, scenarios with very low and low GHG emissions would strongly limit the change of several
CIDs, such as the increases in the frequency of extreme sea level events, heavy precipitation and pluvial flooding, and
exceedance of dangerous heat thresholds, while limiting the number of regions where such exceedances occur, relative
to higher GHG emissions scenarios (high confidence). Changes would also be smaller in very low compared to low GHG
emissions scenarios, as well as for intermediate (SSP2-4.5) compared to high or very high GHG emissions scenarios (high
confidence).
{9.6, 11.2, 11.3, 11.4, 11.5, 11.6, 11.9, Cross-Chapter Box 11.1, 12.4, 12.5, TS.4.3}
Summary for
Policymakers
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3
Summary for Policymakers
Drafting Authors: Hans-O. Pörtner (Germany), Debra C. Roberts (South Africa), Helen Adams
(UK), Carolina Adler (Switzerland/Chile/Australia), Paulina Aldunce (Chile), Elham Ali (Egypt),
Rawshan Ara Begum (Malaysia/Australia/Bangladesh), Richard Betts (UK), Rachel Bezner Kerr
(Canada/USA), Robbert Biesbroek (The Netherlands), Joern Birkmann (Germany), Kathryn Bowen
(Australia), Edwin Castellanos (Guatemala), Guéladio Cissé (Mauritania/Switzerland/France),
Andrew Constable (Australia), Wolfgang Cramer (France), David Dodman (Jamaica/UK), Siri
H. Eriksen (Norway), Andreas Fischlin (Switzerland), Matthias Garschagen (Germany), Bruce
Glavovic (New Zealand/South Africa), Elisabeth Gilmore (USA/Canada), Marjolijn Haasnoot (The
Netherlands), Sherilee Harper (Canada), Toshihiro Hasegawa (Japan), Bronwyn Hayward (New
Zealand), Yukiko Hirabayashi (Japan), Mark Howden (Australia), Kanungwe Kalaba (Zambia),
Wolfgang Kiessling (Germany), Rodel Lasco (Philippines), Judy Lawrence (New Zealand),
Maria Fernanda Lemos (Brazil), Robert Lempert (USA), Debora Ley (Mexico/Guatemala), Tabea
Lissner (Germany), Salvador Lluch-Cota (Mexico), Sina Loeschke (Germany), Simone Lucatello
(Mexico), Yong Luo (China), Brendan Mackey (Australia), Shobha Maharaj (Germany/Trinidad and
Tobago), Carlos Mendez (Venezuela), Katja Mintenbeck (Germany), Vincent Möller (Germany),
Mariana Moncassim Vale (Brazil), Mike D Morecroft (UK), Aditi Mukherji (India), Michelle Mycoo
(Trinidad and Tobago), Tero Mustonen (Finland), Johanna Nalau (Australia/Finland), Andrew
Okem (SouthAfrica/Nigeria), Jean Pierre Ometto (Brazil), Camille Parmesan (France/USA/UK),
Mark Pelling (UK), Patricia Pinho (Brazil), Elvira Poloczanska (UK/Australia), Marie-Fanny Racault
(UK/France), Diana Reckien (The Netherlands/Germany), Joy Pereira (Malaysia), Aromar Revi
(India), Steven Rose (USA), Roberto Sanchez-Rodriguez (Mexico), E. Lisa F. Schipper (Sweden/
UK), Daniela Schmidt (UK/Germany), David Schoeman (Australia), Rajib Shaw (Japan), Chandni
Singh (India), William Solecki (USA), Lindsay Stringer (UK), Adelle Thomas (Bahamas), Edmond
Totin (Benin), Christopher Trisos (South Africa), Maarten van Aalst (The Netherlands), David Viner
(UK), Morgan Wairiu (Solomon Islands), Rachel Warren (UK), Pius Yanda (Tanzania), Zelina Zaiton
Ibrahim (Malaysia)
Drafting Contributing Authors: Rita Adrian (Germany), Marlies Craig (South Africa),
Frode Degvold (Norway), Kristie L. Ebi (USA), Katja Frieler (Germany), Ali Jamshed (Germany/
Pakistan), Joanna McMillan (German/Australia), Reinhard Mechler (Austria), Mark New (South
Africa), Nicholas P. Simpson (South Africa/Zimbabwe), Nicola Stevens (South Africa)
Visual Conception and Information Design: Andrés Alegría (Germany/Honduras), Stefanie
Langsdorf (Germany)
This Summary for Policymakers should be cited as:
IPCC, 2022: Summary for Policymakers [H.-O. Pörtner, D.C. Roberts, E.S. Poloczanska, K. Mintenbeck, M. Tignor,
A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem (eds.)]. In: Climate Change 2022: Impacts, Adaptation
and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel
on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig,
S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press, Cambridge, UK and New York,
NY, USA, pp. 3–33, doi:10.1017/9781009325844.001.
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Summary for Policymakers
Table of Contents
A: Introduction ........................................................................................................................................................................................................................................................................ 5
Box SPM.1 | AR6 Common Climate Dimensions, Global Warming Levels and Reference Periods ............................................................ 7
B: Observed and Projected Impacts and Risks ............................................................................................................................................................................................. 8
Observed Impacts from Climate Change ........................................................................................................................................................................................................... 9
Vulnerability and Exposure of Ecosystems and People .......................................................................................................................................................................... 12
Risks in the near term (2021–2040) .................................................................................................................................................................................................................. 13
Mid to Long-term Risks (2041–2100) .............................................................................................................................................................................................................. 14
Complex, Compound and Cascading Risks ................................................................................................................................................................................................... 18
Impacts of Temporary Overshoot ......................................................................................................................................................................................................................... 19
C: Adaptation Measures and Enabling Conditions ................................................................................................................................................................................ 20
Current Adaptation and its Benefits .................................................................................................................................................................................................................. 20
Future Adaptation Options and their Feasibility ........................................................................................................................................................................................ 21
Limits to Adaptation .................................................................................................................................................................................................................................................... 26
Avoiding Maladaptation ........................................................................................................................................................................................................................................... 27
Enabling Conditions .................................................................................................................................................................................................................................................... 27
D: Climate Resilient Development ...................................................................................................................................................................................................................... 28
Conditions for Climate Resilient Development ........................................................................................................................................................................................... 29
Enabling Climate Resilient Development ....................................................................................................................................................................................................... 29
Climate Resilient Development for Natural and Human Systems ................................................................................................................................................... 31
Achieving Climate Resilient Development ..................................................................................................................................................................................................... 33
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A: Introduction
This Summary for Policymakers (SPM) presents key findings of the Working Group II (WGII) contribution to the Sixth Assessment Report (AR6) of
the IPCC1. The report builds on the WGII contribution to the Fifth Assessment Report (AR5) of the IPCC, three Special Reports2, and the Working
Group I (WGI) contribution to the AR6 cycle.
This report recognizes the interdependence of climate, ecosystems and biodiversity3, and human societies (Figure SPM.1) and integrates
knowledge more strongly across the natural, ecological, social and economic sciences than earlier IPCC assessments. The assessment of climate
change impacts and risks as well as adaptation is set against concurrently unfolding non-climatic global trends e.g., biodiversity loss, overall
unsustainable consumption of natural resources, land and ecosystem degradation, rapid urbanisation, human demographic shifts, social and
economic inequalities and a pandemic.
The scientific evidence for each key finding is found in the 18 chapters of the underlying report and in the 7 cross-chapter papers as well as the
integrated synthesis presented in the Technical Summary (hereafter TS) and referred to in curly brackets {}. Based on scientific understanding, key
findings can be formulated as statements of fact or associated with an assessed level of confidence using the IPCC calibrated language4. The WGII
Global to Regional Atlas (Annex I) facilitates exploration of key synthesis findings across the WGII regions.
The concept of risk is central to all three AR6 Working Groups. A risk framing and the concepts of adaptation, vulnerability, exposure, resilience,
equity and justice, and transformation provide alternative, overlapping, complementary, and widely used entry points to the literature assessed
in this WGII report.
Across all three AR6 working groups, risk5 provides a framework for understanding the increasingly severe, interconnected and often irreversible
impacts of climate change on ecosystems, biodiversity, and human systems; differing impacts across regions, sectors and communities; and
how to best reduce adverse consequences for current and future generations. In the context of climate change, risk can arise from the dynamic
interactions among climate-related hazards6 (see Working Group I), the exposure7 and vulnerability8 of affected human and ecological systems.
The risk that can be introduced by human responses to climate change is a new aspect considered in the risk concept. This report identifies 127
key risks9. {1.3, 16.5}
The vulnerability of exposed human and natural systems is a component of risk, but also, independently, an important focus in the literature.
Approaches to analysing and assessing vulnerability have evolved since previous IPCC assessments. Vulnerability is widely understood to differ
within communities and across societies, regions and countries, also changing through time.
Adaptation10 plays a key role in reducing exposure and vulnerability to climate change. Adaptation in ecological systems includes autonomous
adjustments through ecological and evolutionary processes. In human systems, adaptation can be anticipatory or reactive, as well as incremental
1 Decision IPCC/XLVI-3, The assessment covers scientific literature accepted for publication by 1 September 2021.
2 The three Special Reports are: ‘Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission
pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty (SR1.5)’; ‘Climate Change and Land. An IPCC
Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems (SRCCL)’; ‘IPCC Special Report
on the Ocean and Cryosphere in a Changing Climate (SROCC)’.
3 Biodiversity: Biodiversity or biological diversity means the variability among living organisms from all sources including, among other things, terrestrial, marine and other aquatic ecosystems, and the
ecological complexes of which they are part; this includes diversity within species, between species, and of ecosystems.
4 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and typeset in italics,
e.g., medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%,
as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Assessed likelihood is typeset in italics, e.g., very likely. This is consistent with AR5 and the other AR6 Reports.
5 Risk is defined as the potential for adverse consequences for human or ecological systems, recognising the diversity of values and objectives associated with such systems.
6 Hazard is defined as the potential occurrence of a natural or human-induced physical event or trend that may cause loss of life, injury, or other health impacts, as well as damage and loss to property,
infrastructure, livelihoods, service provision, ecosystems and environmental resources. Physical climate conditions that may be associated with hazards are assessed in Working Group I as climatic
impact-drivers.
7 Exposure is defined as the presence of people; livelihoods; species or ecosystems; environmental functions, services and resources; infrastructure; or economic, social or cultural assets in places and
settings that could be adversely affected.
8 Vulnerability in this report is defined as the propensity or predisposition to be adversely affected and encompasses a variety of concepts and elements, including sensitivity or susceptibility to harm and
lack of capacity to cope and adapt.
9 Key risks have potentially severe adverse consequences for humans and social-ecological systems resulting from the interaction of climate related hazards with vulnerabilities of societies and systems
exposed.
10 Adaptation is defined, in human systems, as the process of adjustment to actual or expected climate and its effects in order to moderate harm or take advantage of beneficial opportunities. In natural
systems, adaptation is the process of adjustment to actual climate and its effects; human intervention may facilitate this.
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Summary for Policymakers
Human Society
Limits to adaptation
Losses and damages
Climate Change
causes
Impacts and Risks
Human Systems
Transitions
Societal | Energy
Industry | Urban, Rural
& Infrastructure
Future Climate Change
Limiting Global Warming
s
ral
Ecosystems
Transitions
Land | Freshwater
Coastal | Ocean
Ecosystems and
their biodiversity
Ecosystems
including biodiversity
Limits to adaptation
Losses and damages
(a) Main interactions and trends
From climate risk to climate resilient development: climate, ecosystems (including biodiversity) and human society as coupled systems
n
s
includ
Lim
Risks
Vulnerability
The risk propeller shows that risk emerges from the overlap of:
...of human systems, ecosystems and their biodiversity
Climate hazard(s) Exposure
Governance
Finance
Knowledge and capacity
Catalysing conditions
Technologies
From urgent to
timely action
provision
Livelihoods, Ecosystem Services
adapt to, mitigate
impacts
impacts
Ecosystem based approaches
conserve, restore
impact
adapts to, mitigate s
Greenhouse gas emissions
provision
Livelihoods, Ecosystem Services
adapts, maladapts, mitigates
impacts
impacts
conserves, restores
impacts
adapt to, mitigate
Climate Resilient
Development
Human health & well-being
equity, justice
Ecosystem health
Planetary health
(b) Options to reduce climate risks and establish resilience
Figure SPM.1 | This report has a strong focus on the interactions among the coupled systems climate, ecosystems (including their biodiversity) and human society. These interactions are the basis of emerging risks
from climate change, ecosystem degradation and biodiversity loss and, at the same time, offer opportunities for the future.
(a) Human society causes climate change. Climate change, through hazards, exposure and vulnerability generates impacts and risks that can surpass limits to adaptation and result in losses and damages. Human society can adapt to,
maladapt and mitigate climate change, ecosystems can adapt and mitigate within limits. Ecosystems and their biodiversity provision livelihoods and ecosystem services. Human society impacts ecosystems and can restore and conserve them.
(b) Meeting the objectives of climate resilient development thereby supporting human, ecosystem and planetary health, as well as human well-being, requires society and ecosystems to move over (transition) to a more resilient state.
The recognition of climate risks can strengthen adaptation and mitigation actions and transitions that reduce risks. Taking action is enabled by governance, finance, knowledge and capacity building, technology and catalysing conditions.
Transformation entails system transitions strengthening the resilience of ecosystems and society (Section D). In a) arrow colours represent principle human society interactions (blue), ecosystem (including biodiversity) interactions (green)
and the impacts of climate change and human activities, including losses and damages, under continued climate change (red). In b) arrow colours represent human system interactions (blue), ecosystem (including biodiversity) interactions
(green) and reduced impacts from climate change and human activities (grey). {1.2, Figure 1.2, Figure TS. 2}
•
•
•
7
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Summary for Policymakers
and/ or transformational. The latter changes the fundamental attributes of a social-ecological system in anticipation of climate change and its
impacts. Adaptation is subject to hard and soft limits11.
Resilience12 in the literature has a wide range of meanings. Adaptation is often organized around resilience as bouncing back and returning to
a previous state after a disturbance. More broadly the term describes not just the ability to maintain essential function, identity and structure,
but also the capacity for transformation.
This report recognises the value of diverse forms of knowledge such as scientific, as well as Indigenous knowledge and local knowledge in
understanding and evaluating climate adaptation processes and actions to reduce risks from human-induced climate change. AR6 highlights
adaptation solutions which are effective, feasible13, and conform to principles of justice14. The term climate justice, while used in different ways in
different contexts by different communities, generally includes three principles: distributive justice which refers to the allocation of burdens and
benefits among individuals, nations and generations; procedural justice which refers to who decides and participates in decision-making; and
recognition which entails basic respect and robust engagement with and fair consideration of diverse cultures and perspectives.
Effectiveness refers to the extent to which an action reduces vulnerability and climate-related risk, increases resilience, and avoids maladaptation15.
This report has a particular focus on transformation16 and system transitions in energy; land, ocean, coastal and freshwater ecosystems; urban,
rural and infrastructure; and industry and society. These transitions make possible the adaptation required for high levels of human health and
well-being, economic and social resilience, ecosystem health17, and planetary health18 (Figure SPM.1). These system transitions are also important
for achieving the low global warming levels (Working Group III) that would avoid many limits to adaptation11. The report also assesses economic
and non-economic losses and damages19. This report labels the process of implementing mitigation and adaptation together in support of
sustainable development for all as climate resilient development20.
Box SPM.1 | AR6 Common Climate Dimensions, Global Warming Levels and Reference Periods
Assessments of climate risks consider possible future climate change, societal development and responses. This report assesses literature
including that based on climate model simulations that are part of the fifth and sixth Coupled Model Intercomparison Project Phase
(CMIP5, CMIP6) of the World Climate Research Programme. Future projections are driven by emissions and/or concentrations from
illustrative Representative Concentration Pathways (RCPs)21 and Shared Socioeconomic Pathways (SSPs)22 scenarios, respectively23.
Climate impacts literature is based primarily on climate projections assessed in AR5 or earlier, or assumed global warming levels, though
some recent impacts literature uses newer projections based on the CMIP6 exercise. Given differences in the impacts literature regarding
11 Adaptation limits: The point at which an actor’s objectives (or system needs) cannot be secured from intolerable risks through adaptive actions.
Hard adaptation limit—No adaptive actions are possible to avoid intolerable risks.
Soft adaptation limit—Options may exist but are currently not available to avoid intolerable risks through adaptive action.
12 Resilience in this report is defined as the capacity of social, economic and ecosystems to cope with a hazardous event or trend or disturbance, responding or reorganising in ways that maintain their
essential function, identity and structure as well as biodiversity in case of ecosystems while also maintaining the capacity for adaptation, learning and transformation. Resilience is a positive attribute
when it maintains such a capacity for adaptation, learning, and/or transformation.
13 Feasibility refers to the potential for an adaptation option to be implemented.
14 Justice is concerned with setting out the moral or legal principles of fairness and equity in the way people are treated, often based on the ethics and values of society. Social justice comprises just or
fair relations within society that seek to address the distribution of wealth, access to resources, opportunity and support according to principles of justice and fairness. Climate justice comprises justice
that links development and human rights to achieve a rights-based approach to addressing climate change.
15 Maladaptation refers to actions that may lead to increased risk of adverse climate-related outcomes, including via increased greenhouse gas emissions, increased or shifted vulnerability to climate
change, more inequitable outcomes, or diminished welfare, now or in the future. Most often, maladaptation is an unintended consequence.
16 Transformation refers to a change in the fundamental attributes of natural and human systems.
17 Ecosystem health: a metaphor used to describe the condition of an ecosystem, by analogy with human health. Note that there is no universally accepted benchmark for a healthy ecosystem. Rather,
the apparent health status of an ecosystem is judged on the ecosystem’s resilience to change, with details depending upon which metrics (such as species richness and abundance) are employed in
judging it and which societal aspirations are driving the assessment.
18 Planetary health: a concept based on the understanding that human health and human civilisation depend on ecosystem health and the wise stewardship of ecosystems.
19 In this report, the term ‘losses and damages’ refers to adverse observed impacts and/or projected risks and can be economic and/or non-economic.
20 In the WGII report, climate resilient development refers to the process of implementing greenhouse gas mitigation and adaptation measures to support sustainable development for all.
21 RCP-based scenarios are referred to as RCPy, where ‘y’ refers to the level of radiative forcing (in watts per square meter, or W m-2) resulting from the scenario in the year 2100.
22 SSP-based scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socioeconomic Pathway describing the socioeconomic trends underlying the scenarios, and ‘y’ refers to the level of
radiative forcing (in watts per square meter, or W m-2) resulting from the scenario in the year 2100.
23 IPCC is neutral with regard to the assumptions underlying the SSPs, which do not cover all possible scenarios. Alternative scenarios may be considered or developed.
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Summary for Policymakers
socioeconomic details and assumptions, WGII chapters contextualize impacts with respect to exposure, vulnerability and adaptation as
appropriate for their literature, this includes assessments regarding sustainable development and climate resilient development. There are
many emissions and socioeconomic pathways that are consistent with a given global warming outcome. These represent a broad range
of possibilities as available in the literature assessed that affect future climate change exposure and vulnerability. Where available, WGII
also assesses literature that is based on an integrative SSP-RCP framework where climate projections obtained under the RCP scenarios
are analysed against the backdrop of various illustrative SSPs22. The WGII assessment combines multiple lines of evidence including
impacts modelling driven by climate projections, observations, and process understanding. {1.2, 16.5, 18.2, CCB CLIMATE, WGI AR6
SPM.C, WGI AR6 Box SPM.1, WGI AR6 1.6, WGI AR6 12, AR5 WGI}
A common set of reference years and time periods are adopted for assessing climate change and its impacts and risks: the reference
period 1850–1900 approximates pre-industrial global surface temperature, and three future reference periods cover the near-term
(2021–2040), mid-term (2041–2060) and long-term (2081–2100). {CCB CLIMATE}
Common levels of global warming relative to 1850–1900 are used to contextualize and facilitate analysis, synthesis and communication
of assessed past, present and future climate change impacts and risks considering multiple lines of evidence. Robust geographical
patterns of many variables can be identified at a given level of global warming, common to all scenarios considered and independent of
timing when the global warming level is reached. {16.5, CCB CLIMATE, WGI AR6 Box SPM.1, WGI AR6 4.2, WGI AR6 CCB11.1}
WGI assessed the increase in global surface temperature is 1.09 [0.95 to 1.20]24 °C in 2011–2020 above 1850–1900. The estimated
increase in global surface temperature since AR5 is principally due to further warming since 2003–2012 (+0.19 [0.16 to 0.22] °C).25
Considering all five illustrative scenarios assessed by WGI, there is at least a greater than 50% likelihood that global warming will reach
or exceed 1.5°C in the near‐term, even for the very low greenhouse gas emissions scenario26. { WGI AR6 SPM A1.2, WGI AR6 SPM B1.3,
WGI AR6 Table SPM.1, WGI AR6 CCB 2.3}
B: Observed and Projected Impacts and Risks
Since AR5, the knowledge base on observed and projected impacts and risks generated by climate hazards, exposure and vulnerability has
increased with impacts attributed to climate change and key risks identified across the report. Impacts and risks are expressed in terms of their
damages, harms, economic, and non-economic losses. Risks from observed vulnerabilities and responses to climate change are highlighted.
Risks are projected for the near-term (2021–2040), the mid (2041–2060) and long term (2081–2100), at different global warming levels and
for pathways that overshoot 1.5°C global warming level for multiple decades27. Complex risks result from multiple climate hazards occurring
concurrently, and from multiple risks interacting, compounding overall risk and resulting in risks transmitting through interconnected systems
and across regions.
24 In the WGI report, square brackets [x to y] are used to provide the assessed very likely range, or 90% interval.
25 Since AR5, methodological advances and new datasets have provided a more complete spatial representation of changes in surface temperature, including in the Arctic. These and other improvements
have also increased the estimate of global surface temperature change by approximately 0.1°C, but this increase does not represent additional physical warming since AR5.
26 Global warming of 1.5°C relative to 1850–1900 would be exceeded during the 21st century under the intermediate, high and very high greenhouse gas emissions scenarios considered in this report
(SSP2-4.5, SSP3-7.0 and SSP5-8.5, respectively). Under the five illustrative scenarios, in the near term (2021–2040), the 1.5°C global warming level is very likely to be exceeded under the very high
greenhouse gas emissions scenario (SSP5-8.5), likely to be exceeded under the intermediate and high greenhouse gas emissions scenarios (SSP2-4.5 and SSP3-7.0), more likely than not to be exceeded
under the low greenhouse gas emissions scenario (SSP1-2.6) and more likely than not to be reached under the very low greenhouse gas emissions scenario (SSP1-1.9). Furthermore, for the very low
greenhouse gas emissions scenario (SSP1-1.9), it is more likely than not that global surface temperature would decline back to below 1.5°C toward the end of the 21st century, with a temporary
overshoot of no more than 0.1°C above 1.5°C global warming.
27 Overshoot: In this report, pathways that first exceed a specified global warming level (usually 1.5°C, by more than 0.1°C), and then return to or below that level again before the end of a specified
period of time (e.g., before 2100). Sometimes the magnitude and likelihood of the overshoot is also characterized. The overshoot duration can vary from at least one decade up to several decades.
Box SPM.1 (continued)
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Summary for Policymakers
Observed Impacts from Climate Change
28 Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assessment of confidence. {Annex II Glossary, CWGB ATTRIB}
29 Impacts of climate change are caused by slow onset and extreme events. Slow onset events are described among the climatic-impact drivers of the WGI AR6 and refer to the risks and impacts
associated with e.g., increasing temperature means, desertification, decreasing precipitation, loss of biodiversity, land and forest degradation, glacial retreat and related impacts, ocean acidification,
sea level rise and salinization (https://interactive-atlas.ipcc.ch).
30 Acute food insecurity can occur at any time with a severity that threatens lives, livelihoods or both, regardless of the causes, context or duration, as a result of shocks risking determinants of food
security and nutrition, and used to assess the need for humanitarian action.
B.1 Human-induced climate change, including more frequent and intense extreme events, has caused widespread adverse
impacts and related losses and damages to nature and people, beyond natural climate variability. Some development and
adaptation efforts have reduced vulnerability. Across sectors and regions the most vulnerable people and systems are observed
to be disproportionately affected. The rise in weather and climate extremes has led to some irreversible impacts as
natural and human systems are pushed beyond their ability to adapt. (high confidence) (Figure SPM.2) {TS B.1, Figure TS.5,
1.3, 2.3, 2.4, 2.6, 3.3, 3.4, 3.5, 4.2, 4.3, 5.2, 5.12, 6.2, 7.2, 8.2, 9.6, 9.8, 9.10, 9.11, 10.4, 11.3, 12.3, 12.4, 13.10, 14.4, 14.5,
15.3, 16.2, CCP1.2, CCP3.2, CCP4.1, CCP5.2, CCP6.2, CCP7.2, CCP7.3, CCB DISASTER, CCB EXTREMES, CCB ILLNESS, CCB
MIGRATE, CCB NATURAL, CCB SLR}
B.1.1 Widespread, pervasive impacts to ecosystems, people, settlements, and infrastructure have resulted from observed increases in the
frequency and intensity of climate and weather extremes, including hot extremes on land and in the ocean, heavy precipitation events,
drought and fire weather (high confidence). Increasingly since AR5, these observed impacts have been attributed28 to human-induced
climate change particularly through increased frequency and severity of extreme events. These include increased heat-related human
mortality (medium confidence), warm-water coral bleaching and mortality (high confidence), and increased drought-related tree
mortality (high confidence). Observed increases in areas burned by wildfires have been attributed to human-induced climate change
in some regions (medium to high confidence). Adverse impacts from tropical cyclones, with related losses and damages19, have
increased due to sea level rise and the increase in heavy precipitation (medium confidence). Impacts in natural and human systems
from slow-onset processes29 such as ocean acidification, sea level rise or regional decreases in precipitation have also been attributed
to human induced climate change (high confidence). {1.3, 2.3, 2.4, 2.5, 3.2, 3.4, 3.5, 3.6, 4.2, 5.2, 5.4, 5.6, 5.12, 7.2, 9.6, 9.7, 9.8, 9.11,
11.3, Box 11.1, Box 11.2, Table 11.9, 12.3, 12.4, 13.3, 13.5, 13.10, 14.2, 14.5, 15.7, 15.8, 16.2, CCP1.2, CCP2.2, Box CCP5.1, CCP7.3,
CCB DISASTER, CCB EXTREME, CCB ILLNESS, WGI AR6 SPM.3, WGI AR6 9, WGI AR6 11.3–11.8, SROCC Chapter 4}
B.1.2 Climate change has caused substantial damages, and increasingly irreversible losses, in terrestrial, freshwater and coastal and open
ocean marine ecosystems (high confidence). The extent and magnitude of climate change impacts are larger than estimated in previous
assessments (high confidence). Widespread deterioration of ecosystem structure and function, resilience and natural adaptive capacity,
as well as shifts in seasonal timing have occurred due to climate change (high confidence), with adverse socioeconomic consequences
(high confidence). Approximately half of the species assessed globally have shifted polewards or, on land, also to higher elevations
(very high confidence). Hundreds of local losses of species have been driven by increases in the magnitude of heat extremes (high
confidence), as well as mass mortality events on land and in the ocean (very high confidence) and loss of kelp forests (high confidence).
Some losses are already irreversible, such as the first species extinctions driven by climate change (medium confidence). Other impacts
are approaching irreversibility such as the impacts of hydrological changes resulting from the retreat of glaciers, or the changes in
some mountain (medium confidence) and Arctic ecosystems driven by permafrost thaw (high confidence). (Figure SPM.2a). { TS B.1,
Figure TS.5, 2.3, 2.4, 3.4, 3.5, 4.2, 4.3, 4.5, 9.6, 10.4, 11.3, 12.3, 12.8, 13.3, 13.4, 13.10, 14.4, 14.5, 14.6, 15.3, 16.2, CCP1.2, CCP3.2,
CCP4.1, CCP5.2, Figure CCP5.4, CCP6.1, CCP6.2, CCP7.2, CCP7.3, CCB EXTREMES, CCB ILLNESS, CCB MOVING PLATE, CCB NATURAL,
CCB PALEO, CCB SLR, SROCC 2.3}
B.1.3 Climate change including increases in frequency and intensity of extremes have reduced food and water security, hindering efforts
to meet Sustainable Development Goals (high confidence). Although overall agricultural productivity has increased, climate change
has slowed this growth over the past 50 years globally (medium confidence), related negative impacts were mainly in mid- and low
latitude regions but positive impacts occurred in some high latitude regions (high confidence). Ocean warming and ocean acidification
have adversely affected food production from shellfish aquaculture and fisheries in some oceanic regions (high confidence). Increasing
weather and climate extreme events have exposed millions of people to acute food insecurity30 and reduced water security, with the
largest impacts observed in many locations and/or communities in Africa, Asia, Central and South America, Small Islands and the Arctic
(high confidence). Jointly, sudden losses of food production and access to food compounded by decreased diet diversity have increased
malnutrition in many communities (high confidence), especially for Indigenous Peoples, small-scale food producers and low-income
households (high confidence), with children, elderly people and pregnant women particularly impacted (high confidence). Roughly half
of the world’s population currently experience severe water scarcity for at least some part of the year due to climatic and non-climatic
drivers (medium confidence). (Figure SPM.2b) {3.5, 4.3, 4.4, Box 4.1, 5.2, 5.4, 5.8, 5.9, 5.12, 7.1, 7.2, 9.8, 10.4, 11.3, 12.3, 13.5, 14.4,
14.5, 15.3, 16.2, CCP5.2, CCP6.2}
10
SPM
Summary for Policymakers
na
¹
not
assessed
not
assessed
not
assessed
not
assessed
Impacts of climate change are observed in many ecosystems and human systems worldwide
(a) Observed impacts of climate change on ecosystems
Confidence
in attribution
to climate change
High or very high
Medium
Low
(b) Observed impacts of climate change on human systems
Impacts
to human systems
in panel (b)
Africa
Biodiversity hotspots
Small Islands
North America
Australasia
Asia
Europe
Central and
South America
Deserts
Mountain regions
Arctic
Antarctic
Tropical forests
Mediterranean region
Changes in
ecosystem structure
Species
range shifts
/
Changes in timing
(phenology)
Ecosystems Terrestrial Freshwater Ocean Terrestrial Freshwater Ocean Terrestrial Freshwater Ocean
na na
na
na
na
na
na
na
na
na
na na
Global
Evidence limited,
insufficient
na Not applicable
not
assessed
Impacts on
water scarcity and food production
Impacts on
health and wellbeing
Impacts on
cities, settlements and infrastructure
Infectious
diseases Displacement
Water
scarcity
Agriculture/
crop
production
Fisheries
yields and
aquaculture
production
Inland
flooding and
associated
damages
Flood/storm
induced
damages in
coastal areas
Damages
to key
economic
sectors
Human
systems
Animal and
livestock
health and
productivity
Damages
to
infrastructure
Mental
health
Heat,
malnutrition
and other
Asia
Central and
South America
Australasia
Europe
Mediterranean region
Small Islands
Cities by the sea
Arctic
North America
Mountain regions
Africa
Global
Increasing
adverse
impacts
Increasing
adverse
and positive
impacts
Figure SPM.2 | Observed global and regional impacts on ecosystems and human systems attributed to climate change. Confidence levels reflect uncertainty
in attribution of the observed impact to climate change. Global assessments focus on large studies, multi-species, meta-analyses and large reviews. For that reason they can be
assessed with higher confidence than regional studies, which may often rely on smaller studies that have more limited data. Regional assessments consider evidence on impacts
across an entire region and do not focus on any country in particular.
(a) Climate change has already altered terrestrial, freshwater and ocean ecosystems at global scale, with multiple impacts evident at regional and local scales where there is
sufficient literature to make an assessment. Impacts are evident on ecosystem structure, species geographic ranges and timing of seasonal life cycles (phenology) (for methodology
and detailed references to chapters and cross-chapter papers see SMTS.1 and SMTS.1.1).
•• •• •• •• • •• • • • • • ) ••• •• ••• ••• •• ••• ••• ••• ••• ••• ••• ••• ••• •• ••• • •• ••• • • ••• • •
C• E•L IE• • • •• • •
••• •• ••• ••• • •• • ± •
r E7 c EE ,II,, g
0 o o o o e o o o o o
e o o eo o e o o e o
0 e0 o e o e o o e o e 0e eo e eo e o eo e ee eo
0 0 e 0 e e e e e e
0o 0o o 0o o oo o eo oo oo eo oo
0 e e e e o o e e 0 e e e oo eo o o e eo
0 0 o e o e e e o
11
SPM
Summary for Policymakers
B.1.4 Climate change has adversely affected physical health of people globally (very high confidence) and mental health of people in the
assessed regions (very high confidence). Climate change impacts on health are mediated through natural and human systems, including
economic and social conditions and disruptions (high confidence). In all regions extreme heat events have resulted in human mortality
and morbidity (very high confidence). The occurrence of climate-related food-borne and water-borne diseases has increased (very high
confidence). The incidence of vector-borne diseases has increased from range expansion and/or increased reproduction of disease vectors
(high confidence). Animal and human diseases, including zoonoses, are emerging in new areas (high confidence). Water and food-borne
disease risks have increased regionally from climate-sensitive aquatic pathogens, including Vibrio spp. (high confidence), and from toxic
substances from harmful freshwater cyanobacteria (medium confidence). Although diarrheal diseases have decreased globally, higher
temperatures, increased rain and flooding have increased the occurrence of diarrheal diseases, including cholera (very high confidence)
and other gastrointestinal infections (high confidence). In assessed regions, some mental health challenges are associated with increasing
temperatures (high confidence), trauma from weather and climate extreme events (very high confidence), and loss of livelihoods and culture
(high confidence). Increased exposure to wildfire smoke, atmospheric dust, and aeroallergens have been associated with climate-sensitive
cardiovascular and respiratory distress (high confidence). Health services have been disrupted by extreme events such as floods (high
confidence). {4.3, 5.12, 7.2, Box 7.3, 8.2, 8.3, Box 8.6, Figure 8.10, 9.10, Figure 9.33, Figure 9.34, 10.4, 11.3, 12.3, 13.7, 14.4, 14.5,
Figure 14.8, 15.3, 16.2, CCP5.2, Table CCP5.1, CCP6.2, Figure CCP6.3, Table CCB ILLNESS.1}
B.1.5 In urban settings, observed climate change has caused impacts on human health, livelihoods and key infrastructure (high confidence).
Multiple climate and non-climate hazards impact cities, settlements and infrastructure and sometimes coincide, magnifying damage
(high confidence). Hot extremes including heatwaves have intensified in cities (high confidence), where they have also aggravated
air pollution events (medium confidence) and limited functioning of key infrastructure (high confidence). Observed impacts are
concentrated amongst the economically and socially marginalized urban residents, e.g., in informal settlements (high confidence).
Infrastructure, including transportation, water, sanitation and energy systems have been compromised by extreme and slow-onset
events, with resulting economic losses, disruptions of services and impacts to well-being (high confidence). {4.3, 6.2, 7.1, 7.2, 9.9, 10.4,
11.3, 12.3, 13.6, 14.5, 15.3, CCP2.2, CCP4.2, CCP5.2}
B.1.6 Overall adverse economic impacts attributable to climate change, including slow-onset and extreme weather events, have been
increasingly identified (medium confidence). Some positive economic effects have been identified in regions that have benefited from
lower energy demand as well as comparative advantages in agricultural markets and tourism (high confidence). Economic damages
from climate change have been detected in climate-exposed sectors, with regional effects to agriculture, forestry, fishery, energy,
and tourism (high confidence), and through outdoor labour productivity (high confidence). Some extreme weather events, such as
tropical cyclones, have reduced economic growth in the short-term (high confidence). Non-climatic factors including some patterns
of settlement, and siting of infrastructure have contributed to the exposure of more assets to extreme climate hazards increasing the
magnitude of the losses (high confidence). Individual livelihoods have been affected through changes in agricultural productivity,
impacts on human health and food security, destruction of homes and infrastructure, and loss of property and income, with adverse
effects on gender and social equity (high confidence). {3.5, 4.2, 5.12, 6.2, 7.2, 8.2, 9.6, 10.4, 13.10, 14.5, Box 14.6, 16.2, Table 16.5,
18.3, CCP6.2, CCB GENDER, CWGB ECONOMICS}
B.1.7 Climate change is contributing to humanitarian crises where climate hazards interact with high vulnerability (high confidence). Climate
and weather extremes are increasingly driving displacement in all regions (high confidence), with Small Island States disproportionately
affected (high confidence). Flood and drought-related acute food insecurity and malnutrition have increased in Africa (high confidence)
and Central and South America (high confidence). While non-climatic factors are the dominant drivers of existing intrastate violent
conflicts, in some assessed regions extreme weather and climate events have had a small, adverse impact on their length, severity or
frequency, but the statistical association is weak (medium confidence). Through displacement and involuntary migration from extreme
weather and climate events, climate change has generated and perpetuated vulnerability (medium confidence). {4.2, 4.3, 5.4, 7.2, 9.8,
Box 9.9, Box 10.4, 12.3, 12.5, 16.2, CCB DISASTER, CCB MIGRATE}
(b) Climate change has already had diverse adverse impacts on human systems, including on water security and food production, health and well-being, and cities, settlements and
infrastructure. The + and – symbols indicate the direction of observed impacts, with a – denoting an increasing adverse impact and a ± denoting that, within a region or globally, both
adverse and positive impacts have been observed (e.g., adverse impacts in one area or food item may occur with positive impacts in another area or food item). Globally, ‘–’ denotes an
overall adverse impact; ‘Water scarcity’ considers, e.g., water availability in general, groundwater, water quality, demand for water, drought in cities. Impacts on food production were
assessed by excluding non-climatic drivers of production increases; Global assessment for agricultural production is based on the impacts on global aggregated production; ‘Reduced
animal and livestock health and productivity’ considers, e.g., heat stress, diseases, productivity, mortality; ‘Reduced fisheries yields and aquaculture production’ includes marine and
freshwater fisheries/production; ‘Infectious diseases’ include, e.g., water-borne and vector-borne diseases; ‘Heat, malnutrition and other’ considers, e.g., human heat-related morbidity
and mortality, labour productivity, harm from wildfire, nutritional deficiencies; ‘Mental health’ includes impacts from extreme weather events, cumulative events, and vicarious or
anticipatory events; ‘Displacement’ assessments refer to evidence of displacement attributable to climate and weather extremes; ‘Inland flooding and associated damages’ considers,
e.g., river overflows, heavy rain, glacier outbursts, urban flooding; ‘Flood/storm induced damages in coastal areas’ include damages due to, e.g., cyclones, sea level rise, storm surges.
Damages by key economic sectors are observed impacts related to an attributable mean or extreme climate hazard or directly attributed. Key economic sectors include standard
classifications and sectors of importance to regions (for methodology and detailed references to chapters and cross-chapter papers see SMTS.1 and SMTS.1.2).
12
SPM
Summary for Policymakers
Vulnerability and Exposure of Ecosystems and People
31 Governance: The structures, processes and actions through which private and public actors interact to address societal goals. This includes formal and informal institutions and the associated norms,
rules, laws and procedures for deciding, managing, implementing and monitoring policies and measures at any geographic or political scale, from global to local.
32 Balanced diets feature plant-based foods, such as those based on coarse grains, legumes fruits and vegetables, nuts and seeds, and animal-source foods produced in resilient, sustainable and
low-greenhouse gas emissions systems, as described in SRCCL.
B.2 Vulnerability of ecosystems and people to climate change differs substantially among and within regions (very high
confidence), driven by patterns of intersecting socioeconomic development, unsustainable ocean and land use, inequity,
marginalization, historical and ongoing patterns of inequity such as colonialism, and governance31 (high confidence).
Approximately 3.3 to 3.6 billion people live in contexts that are highly vulnerable to climate change (high confidence).
A high proportion of species is vulnerable to climate change (high confidence). Human and ecosystem vulnerability are
interdependent (high confidence). Current unsustainable development patterns are increasing exposure of ecosystems
and people to climate hazards (high confidence). {2.3, 2.4, 3.5, 4.3, 6.2, 8.2, 8.3, 9.4, 9.7, 10.4, 12.3, 14.5, 15.3, CCP5.2,
CCP6.2, CCP7.3, CCP7.4, CCB GENDER}
B.2.1 Since AR5 there is increasing evidence that degradation and destruction of ecosystems by humans increases the vulnerability of
people (high confidence). Unsustainable land-use and land cover change, unsustainable use of natural resources, deforestation, loss
of biodiversity, pollution, and their interactions, adversely affect the capacities of ecosystems, societies, communities and individuals
to adapt to climate change (high confidence). Loss of ecosystems and their services has cascading and long-term impacts on people
globally, especially for Indigenous Peoples and local communities who are directly dependent on ecosystems, to meet basic needs (high
confidence). {2.3, 2.5, 2.6, 3.5, 3.6, 4.2, 4.3, 4.6, 5.1, 5.4, 5.5, 5.7, 5.8, 7.2, 8.1, 8.2, 8.3, 8.4, 8.5, 9.6, 10.4, 11.3, 12.2, 12.5, 13.8, 14.4,
14.5, 15.3, CCP1.2, CCP1.3, CCP2.2, CCP3, CCP4.3, CCP5.2, CCP6.2, CCP7.2, CCP7.3, CCP7.4, CCB ILLNESS, CCB MOVING PLATE, CCB
SLR}
B.2.2 Non-climatic human-induced factors exacerbate current ecosystem vulnerability to climate change (very high confidence). Globally,
and even within protected areas, unsustainable use of natural resources, habitat fragmentation, and ecosystem damage by pollutants
increase ecosystem vulnerability to climate change (high confidence). Globally, less than 15% of the land, 21% of the freshwater and
8% of the ocean are protected areas. In most protected areas, there is insufficient stewardship to contribute to reducing damage from,
or increasing resilience to, climate change (high confidence). {2.4, 2.5, 2.6, 3.4, 3.6, 4.2, 4.3, 5.8, 9.6, 11.3, 12.3, 13.3, 13.4, 14.5, 15.3,
CCP1.2, Figure CCP1.15, CCP2.1, CCP2.2, CCP4.2, CCP5.2, CCP6.2, CCP7.2, CCP7.3, CCB NATURAL}
B.2.3 Future vulnerability of ecosystems to climate change will be strongly influenced by the past, present and future development of human
society, including from overall unsustainable consumption and production, and increasing demographic pressures, as well as persistent
unsustainable use and management of land, ocean, and water (high confidence). Projected climate change, combined with non-climatic
drivers, will cause loss and degradation of much of the world’s forests (high confidence), coral reefs and low-lying coastal wetlands
(very high confidence). While agricultural development contributes to food security, unsustainable agricultural expansion, driven in part
by unbalanced diets32, increases ecosystem and human vulnerability and leads to competition for land and/or water resources (high
confidence). {2.2, 2.3, 2.4, 2.6, 3.4, 3.5, 3.6, 4.3, 4.5, 5.6, 5.12, 5.13, 7.2, 12.3, 13.3, 13.4, 13.10, 14.5, CCP1.2, CCP2.2, CCP5.2, CCP6.2,
CCP7.2, CCP7.3, CCB HEALTH, CCB NATURAL}
B.2.4 Regions and people with considerable development constraints have high vulnerability to climatic hazards (high confidence). Global
hotspots of high human vulnerability are found particularly in West-, Central- and East Africa, South Asia, Central and South America,
Small Island Developing States and the Arctic (high confidence). Vulnerability is higher in locations with poverty, governance challenges
and limited access to basic services and resources, violent conflict and high levels of climate-sensitive livelihoods (e.g., smallholder
farmers, pastoralists, fishing communities) (high confidence). Between 2010–2020, human mortality from floods, droughts and storms
was 15 times higher in highly vulnerable regions, compared to regions with very low vulnerability (high confidence). Vulnerability
at different spatial levels is exacerbated by inequity and marginalization linked to gender, ethnicity, low income or combinations
thereof (high confidence), especially for many Indigenous Peoples and local communities (high confidence). Present development
challenges causing high vulnerability are influenced by historical and ongoing patterns of inequity such as colonialism, especially for
many Indigenous Peoples and local communities (high confidence). {4.2, 5.12, 6.2, 6.4, 7.1, 7.2, Box 7.1, 8.2, 8.3, Box 8.4, Figure 8.6,
Box 9.1, 9.4, 9.7, 9.9, 10.3, 10.4, 10.6, 12.3, 12.5, Box 13.2, 14.4, 15.3, 15.6, 16.2, CCP6.2, CCP7.4}
B.2.5 Future human vulnerability will continue to concentrate where the capacities of local, municipal and national governments,
communities and the private sector are least able to provide infrastructures and basic services (high confidence). Under the global
trend of urbanization, human vulnerability will also concentrate in informal settlements and rapidly growing smaller settlements (high
13
SPM
Summary for Policymakers
confidence). In rural areas vulnerability will be heightened by compounding processes including high emigration, reduced habitability and
high reliance on climate-sensitive livelihoods (high confidence). Key infrastructure systems including sanitation, water, health, transport,
communications and energy will be increasingly vulnerable if design standards do not account for changing climate conditions (high
confidence). Vulnerability will also rapidly rise in low-lying Small Island Developing States and atolls in the context of sea level rise and
in some mountain regions, already characterised by high vulnerability due to high dependence on climate-sensitive livelihoods, rising
population displacement, the accelerating loss of ecosystem services and limited adaptive capacities (high confidence). Future exposure
to climatic hazards is also increasing globally due to socioeconomic development trends including migration, growing inequality and
urbanization (high confidence). {4.5, 5.5, 6.2, 7.2, 8.3, 9.9, 9.11, 10.3, 10.4, 12.3, 12.5, 13.6, 14.5, 15.3, 15.4, 16.5, CCP2.3, CCP4.3,
CCP5.2, CCP5.3, CCP5.4, CCP6.2, CCB MIGRATE}
Risks in the near term (2021–2040)
B.3 Global warming, reaching 1.5°C in the near-term, would cause unavoidable increases in multiple climate hazards and
present multiple risks to ecosystems and humans (very high confidence). The level of risk will depend on concurrent nearterm
trends in vulnerability, exposure, level of socioeconomic development and adaptation (high confidence). Near-term
actions that limit global warming to close to 1.5°C would substantially reduce projected losses and damages related to
climate change in human systems and ecosystems, compared to higher warming levels, but cannot eliminate them all
(very high confidence). (Figure SPM.3, Box SPM.1) {16.4, 16.5, 16.6, CCP1.2, CCP5.3, CCB SLR, WGI AR6 SPM B1.3, WGI AR6
Table SPM.1}
B.3.1 Near-term warming and increased frequency, severity and duration of extreme events will place many terrestrial, freshwater, coastal
and marine ecosystems at high or very high risks of biodiversity loss (medium to very high confidence, depending on ecosystem).
Near-term risks for biodiversity loss are moderate to high in forest ecosystems (medium confidence), kelp and seagrass ecosystems
(high to very high confidence), and high to very high in Arctic sea-ice and terrestrial ecosystems (high confidence) and warm-water
coral reefs (very high confidence). Continued and accelerating sea level rise will encroach on coastal settlements and infrastructure
(high confidence) and commit low-lying coastal ecosystems to submergence and loss (medium confidence). If trends in urbanisation in
exposed areas continue, this will exacerbate the impacts, with more challenges where energy, water and other services are constrained
(medium confidence). The number of people at risk from climate change and associated loss of biodiversity will progressively increase
(medium confidence). Violent conflict and, separately, migration patterns, in the near-term will be driven by socioeconomic conditions
and governance more than by climate change (medium confidence). (Figure SPM.3) {2.5, 3.4, 4.6, 6.2, 7.3, 8.7, 9.2, 9.9, 11.6, 12.5, 13.6,
13.10, 14.6, 15.3, 16.5, 16.6, CCP1.2, CCP2.1, CCP2.2, CCP5.3, CCP6.2, CCP6.3, CCB MIGRATE, CCB SLR}
B.3.2 In the near term, climate-associated risks to natural and human systems depend more strongly on changes in their vulnerability and
exposure than on differences in climate hazards between emissions scenarios (high confidence). Regional differences exist, and risks
are highest where species and people exist close to their upper thermal limits, along coastlines, in close association with ice or seasonal
rivers (high confidence). Risks are also high where multiple non-climate drivers persist or where vulnerability is otherwise elevated
(high confidence). Many of these risks are unavoidable in the near-term, irrespective of emissions scenario (high confidence). Several
risks can be moderated with adaptation (high confidence). (Figure SPM.3, Section C) {2.5, 3.3, 3.4, 4.5, 6.2, 7.1, 7.3, 8.2, 11.6, 12.4,
13.6, 13.7, 13.10, 14.5, 16.4, 16.5, CCP2.2, CCP4.3, CCP5.3, CCB SLR, WGI AR6 Table SPM.1}
B.3.3 Levels of risk for all Reasons for Concern (RFC) are assessed to become high to very high at lower global warming levels than in
AR5 (high confidence). Between 1.2°C and 4.5°C global warming level very high risks emerge in all five RFCs compared to just two
RFCs in AR5 (high confidence). Two of these transitions from high to very high risk are associated with near-term warming: risks to
unique and threatened systems at a median value of 1.5 [1.2 to 2.0] °C (high confidence) and risks associated with extreme weather
events at a median value of 2.0 [1.8 to 2.5] °C (medium confidence). Some key risks contributing to the RFCs are projected to lead to
widespread, pervasive, and potentially irreversible impacts at global warming levels of 1.5–2°C if exposure and vulnerability are high
and adaptation is low (medium confidence). Near-term actions that limit global warming to close to 1.5°C would substantially reduce
projected losses and damages related to climate change in human systems and ecosystems, compared to higher warming levels, but
cannot eliminate them all (very high confidence). (Figure SPM.3b) {16.5, 16.6, CCB SLR}
14
SPM
Summary for Policymakers
Mid to Long-term Risks (2041–2100)
33 Numbers of species assessed are in the tens of thousands globally.
34 The term ‘very high risks of extinction’ is used here consistently with the IUCN categories and criteria and equates with ‘critically endangered’.
B.4 Beyond 2040 and depending on the level of global warming, climate change will lead to numerous risks to natural and
human systems (high confidence). For 127 identified key risks, assessed mid- and long-term impacts are up to multiple
times higher than currently observed (high confidence). The magnitude and rate of climate change and associated risks
depend strongly on near-term mitigation and adaptation actions, and projected adverse impacts and related losses and
damages escalate with every increment of global warming (very high confidence). (Figure SPM.3) {2.5, 3.4, 4.4, 5.2, 6.2,
7.3, 8.4, 9.2, 10.2, 11.6, 12.4, 13.2, 13.3, 13.4, 13.5, 13.6, 13.7, 13.8, 14.6, 15.3, 16.5, 16.6, CCP1.2, CCP2.2, CCP3.3, CCP4.3,
CCP5.3, CCP6.3, CCP7.3}
B.4.1 Biodiversity loss and degradation, damages to and transformation of ecosystems are already key risks for every region due to past
global warming and will continue to escalate with every increment of global warming (very high confidence). In terrestrial ecosystems,
3 to 14% of species assessed33 will likely face very high risk of extinction34 at global warming levels of 1.5°C, increasing up to 3 to
18% at 2°C, 3 to 29% at 3°C, 3 to 39% at 4°C, and 3 to 48% at 5°C. In ocean and coastal ecosystems, risk of biodiversity loss ranges
between moderate and very high by 1.5°C global warming level and is moderate to very high by 2°C but with more ecosystems at high
and very high risk (high confidence), and increases to high to very high across most ocean and coastal ecosystems by 3°C (medium
to high confidence, depending on ecosystem). Very high extinction risk for endemic species in biodiversity hotspots is projected to at
least double from 2% between 1.5°C and 2°C global warming levels and to increase at least tenfold if warming rises from 1.5°C to
3°C (medium confidence). (Figure SPM.3c, d, f) {2.4, 2.5, 3.4, 3.5,12.3, 12.5, Table 12.6, 13.4, 13.10, 16.4, 16.6, CCP1.2, Figure CCP1.6,
Figure CCP1.7, CCP5.3, CCP6.3, CCB PALEO}
B.4.2 Risks in physical water availability and water-related hazards will continue to increase by the mid- to long-term in all assessed regions,
with greater risk at higher global warming levels (high confidence). At approximately 2°C global warming, snowmelt water availability
for irrigation is projected to decline in some snowmelt dependent river basins by up to 20%, and global glacier mass loss of 18 ± 13%
is projected to diminish water availability for agriculture, hydropower, and human settlements in the mid- to long-term, with these
changes projected to double with 4°C global warming (medium confidence). In Small Islands, groundwater availability is threatened by
climate change (high confidence). Changes to streamflow magnitude, timing and associated extremes are projected to adversely impact
freshwater ecosystems in many watersheds by the mid- to long-term across all assessed scenarios (medium confidence). Projected
increases in direct flood damages are higher by 1.4 to 2 times at 2°C and 2.5 to 3.9 times at 3°C compared to 1.5°C global warming
without adaptation (medium confidence). At global warming of 4°C, approximately 10% of the global land area is projected to face
increases in both extreme high and low river flows in the same location, with implications for planning for all water use sectors (medium
confidence). Challenges for water management will be exacerbated in the near, mid and long term, depending on the magnitude, rate
and regional details of future climate change and will be particularly challenging for regions with constrained resources for water
management (high confidence). {2.3, 4.4, 4.5, Box 4.2, Figure 4.20, 15.3, CCP5.3, CCB DISASTER, SROCC 2.3}
B.4.3 Climate change will increasingly put pressure on food production and access, especially in vulnerable regions, undermining food security
and nutrition (high confidence). Increases in frequency, intensity and severity of droughts, floods and heatwaves, and continued sea
level rise will increase risks to food security (high confidence) in vulnerable regions from moderate to high between 1.5°C and 2°C
global warming level, with no or low levels of adaptation (medium confidence). At 2°C or higher global warming level in the mid-term,
food security risks due to climate change will be more severe, leading to malnutrition and micro-nutrient deficiencies, concentrated
in Sub-Saharan Africa, South Asia, Central and South America and Small Islands (high confidence). Global warming will progressively
weaken soil health and ecosystem services such as pollination, increase pressure from pests and diseases, and reduce marine animal
biomass, undermining food productivity in many regions on land and in the ocean (medium confidence). At 3°C or higher global warming
level in the long term, areas exposed to climate-related hazards will expand substantially compared with 2°C or lower global warming
level (high confidence), exacerbating regional disparity in food security risks (high confidence). (Figure SPM.3) {1.1, 3.3, 4.5, 5.2, 5.4, 5.5,
5.8, 5.9, 5.12, 7.3, 8.3, 9.11, 13.5, 15.3, 16.5, 16.6, CCB MOVING PLATE, CCB SLR}
15
SPM
Summary for Policymakers
B.4.4 Climate change and related extreme events will significantly increase ill health and premature deaths from the near- to long-term (high
confidence). Globally, population exposure to heatwaves will continue to increase with additional warming, with strong geographical
differences in heat-related mortality without additional adaptation (very high confidence). Climate-sensitive food-borne, water-borne,
and vector-borne disease risks are projected to increase under all levels of warming without additional adaptation (high confidence). In
particular, dengue risk will increase with longer seasons and a wider geographic distribution in Asia, Europe, Central and South America
and sub-Saharan Africa, potentially putting additional billions of people at risk by the end of the century (high confidence). Mental health
challenges, including anxiety and stress, are expected to increase under further global warming in all assessed regions, particularly for
children, adolescents, elderly, and those with underlying health conditions (very high confidence). {4.5, 5.12, Box 5.10, 7.3, Figure 7.9,
8.4, 9.10, Figure 9.32, Figure 9.35, 10.4, Figure 10.11, 11.3, 12.3, Figure 12.5, Figure 12.6, 13.7, Figure 13.23, Figure 13.24, 14.5, 15.3,
CCP6.2}
B.4.5 Climate change risks to cities, settlements and key infrastructure will rise rapidly in the mid- and long-term with further global
warming, especially in places already exposed to high temperatures, along coastlines, or with high vulnerabilities (high confidence).
Globally, population change in low-lying cities and settlements will lead to approximately a billion people projected to be at risk
from coastal-specific climate hazards in the mid-term under all scenarios, including in Small Islands (high confidence). The population
potentially exposed to a 100-year coastal flood is projected to increase by about 20% if global mean sea level rises by 0.15 m relative
to 2020 levels; this exposed population doubles at a 0.75 m rise in mean sea level and triples at 1.4 m without population change
and additional adaptation (medium confidence). Sea level rise poses an existential threat for some Small Islands and some low-lying
coasts (medium confidence). By 2100 the value of global assets within the future 1-in-100 year coastal floodplains is projected to
be between US$7.9 and US$12.7 trillion (2011 value) under RCP4.5, rising to between US$8.8 and US$14.2 trillion under RCP8.5
(medium confidence). Costs for maintenance and reconstruction of urban infrastructure, including building, transportation, and energy
will increase with global warming level (medium confidence), the associated functional disruptions are projected to be substantial
particularly for cities, settlements and infrastructure located on permafrost in cold regions and on coasts (high confidence). {6.2, 9.9,
10.4, 13.6, 13.10, 15.3, 16.5, CCP2.1, CCP2.2, CCP5.3, CCP6.2, CCB SLR, SROCC 2.3, SROCC CCB9}
B.4.6 Projected estimates of global aggregate net economic damages generally increase non-linearly with global warming levels (high
confidence).35 The wide range of global estimates, and the lack of comparability between methodologies, does not allow for identification
of a robust range of estimates (high confidence). The existence of higher estimates than assessed in AR5 indicates that global aggregate
economic impacts could be higher than previous estimates (low confidence).36 Significant regional variation in aggregate economic
damages from climate change is projected (high confidence) with estimated economic damages per capita for developing countries
often higher as a fraction of income (high confidence). Economic damages, including both those represented and those not represented
in economic markets, are projected to be lower at 1.5°C than at 3°C or higher global warming levels (high confidence). {4.4, 9.11, 11.5,
13.10, Box 14.6, 16.5, CWGB ECONOMIC}
B.4.7 In the mid- to long-term, displacement will increase with intensification of heavy precipitation and associated flooding, tropical cyclones,
drought and, increasingly, sea level rise (high confidence). At progressive levels of warming, involuntary migration from regions with
high exposure and low adaptive capacity would occur (medium confidence). Compared to other socioeconomic factors the influence of
climate on conflict is assessed as relatively weak (high confidence). Along long-term socioeconomic pathways that reduce non-climatic
drivers, risk of violent conflict would decline (medium confidence). At higher global warming levels, impacts of weather and climate
extremes, particularly drought, by increasing vulnerability will increasingly affect violent intrastate conflict (medium confidence). {TS
B.7.4, 7.3, 16.5, CCB MIGRATE }
35 The assessment found estimated rates of increase in projected global economic damages that were both greater than linear and less than linear as global warming level increases. There is evidence
that some regions could benefit from low levels of warming (high confidence). {CWGB ECONOMIC}
36 Low confidence assigned due to the assessed lack of comparability and robustness of global aggregate economic damage estimates. {CWGB ECONOMIC}
16
SPM
Summary for Policymakers
Global and regional risks for increasing levels of global warming
(a) Global surface temperature change
Increase relative to the period 1850–1900
(b) Reasons for Concern (RFC)
Impact and risk assessments assuming low to no adaptation
2
3
4
1.5
1
0
1950 2000 2050 2100
Projections for different scenarios
°C
SSP1-1.9
SSP1-2.6 (shade representing very likely range)
SSP2-4.5
SSP3-7.0 (shade representing very likely range)
SSP5-8.5
RFC4
Global
aggregate
impacts
RFC1
Unique and
threatened
systems
RFC2
Extreme
weather
events
RFC3
Distribution
of impacts
RFC5
Large scale
singular
events
••• •••• ••••
•• ••• ••••
•• •• •••
• •• •••
•• •• ••
5
Confidence level
assigned to
transition
range
Risk/impact
Low Very high
Very high
High
Moderate
Undetectable
•
•••
••
••••
Historical average
temperature increase
in 2011–2020 was
1.09°C (dashed line)
range 0.95–1.20°C
Transition range
0
2
3
4
1.5
1
•••
•••
•• ••
• •• ••
•• ••
•• •• •••
•• •• •••
Warm water
corals
(d) Impacts and risks
to ocean ecosystems
Kelp
forests
Seagrass
meadows
Epipelagic Salt
marshes
Rocky
shores
Structure
change
Biodiversity
loss
Carbon
loss
Wildfire
increase
Tree
mortality
(c) Impacts and risks to terrestrial
and freshwater ecosystems
•••
••••
••••
••• ••• •••
••• ••• ••••
•• •• •••
•• •• •••
• •• ••
Global surface temperature change (°C)
* Mortality projections include demographic trends but do not include future efforts to improve air quality that reduce ozone concentrations.
0
2
3
4
1.5
1
(e) Climate sensitive health outcomes under three adaptation scenarios
Global surface temperature change (°C)
Limited
adaptation
• ••• ••••
Limited
adaptation
•• ••• ••••
Limited
adaptation
• •• ••••
Limited
adaptation
•• ••• ••••
Heat-related morbidity
and mortality
Dengue and other diseases carried
Ozone-related mortality * Malaria by species of Aedes mosquitoes Scenario narratives
Limited adaptation:
Failure to proactively adapt;
low investment in health
systems
Incomplete adaptation:
Incomplete adaptation
planning; moderate
investment in health systems
Proactive adaptation:
Proactive adaptive
management; higher
Proactive investment in health systems
adaptation
••••
Proactive
adaptation
••••
Proactive
adaptation
••••
Incomplete
adaptation
••• ••••
Incomplete
adaptation
••• ••••
Incomplete
adaptation
•• ••••
Incomplete
adaptation
••• ••••
Proactive
adaptation
••••
5°C 5°C
•• □
I
' •
I I
I I
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I I I
''
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17
SPM
Summary for Policymakers
(f) Examples of regional key risks
4
0
2
3
1.5
1
Global surface temperature change (°C)
Sea-ice
ecosystems
from sea-ice
change in
the Arctic
•••••• ••
Changes in
fisheries catch
for Pollock
and
Pacific Cod
in the Arctic
•• •• •••
Costs
and losses
for key
infrastructure
in the Arctic
•• • •
Changes
in krill
fisheries
in the
Antarctic
••• •• ••
Sea-ice
dependent
ecosystems
in the
Antarctic
•• •• ••
0
2
3
4
1.5
1
Global surface temperature change (°C)
Cascading
impacts on
cities and
settlements
in Australasia
•••••• ••
Loss and
degradation of
coral reefs in
Australia
••••••••••
Reduced
viability of
tourismrelated
activities in
North
America
••• ••• •
Costs and
damages
related to
maintenance and
reconstruction of
transportation
infrastructure in
North America
••• •• •
Lyme
disease in
North
America
under
incomplete
adaptation
scenario
•••• •••
0
2
3
4
1.5
1
Global surface temperature change (°C)
Delayed
impacts of
sea level
rise in the
Mediterranean
• •• •••
Food
production
from crops,
fisheries and
livestock
in Africa
••• •• •••
Biodiversity
and
ecosystems
in Africa
••• ••• •••
Mortality and
morbidity
from heat and
infectious
disease
in Africa
•• ••• •••
0
2
3
4
1.5
1
Global surface temperature change (°C)
Heat stress,
mortality
and
morbidity
to people
in Europe
••• ••• ••
Coastal
flooding to
people
and
infrastructures
in Europe
•• •• ••
Water scarcity
to people in
southeastern
Europe
••• ••• ••
Water quality
and
availability
in the
Mediterranean
••• ••• •••
Health and
wellbeing
in the
Mediterranean •• ••• ••
Absence of risk diagrams does not imply absence of risks within a
region. The development of synthetic diagrams for Small Islands, Asia and Central and
South America was limited due to the paucity of adequately downscaled climate projections,
with uncertainty in the direction of change, the diversity of climatologies and socioeconomic
contexts across countries within a region, and the resulting few numbers of impact and risk
projections for different warming levels.
The risks listed are of at least medium confidence level:
Europe - Risks to people, economies and infrastructures due to coastal and inland flooding
- Stress and mortality to people due to increasing temperatures and heat extremes
- Marine and terrestrial ecosystems disruptions
- Water scarcity to multiple interconnected sectors
- Losses in crop production, due to compound heat and dry conditions, and extreme
weather
Small
Islands
- Loss of terrestrial, marine and coastal biodiversity and ecosystem services
- Loss of lives and assets, risk to food security and economic disruption due to
destruction of settlements and infrastructure
- Economic decline and livelihood failure of fisheries, agriculture, tourism and from
biodiversity loss from traditional agroecosystems
- Reduced habitability of reef and non-reef islands leading to increased displacement
- Risk to water security in almost every small island
Africa - Species extinction and reduction or irreversible loss of ecosystems and their
services, including freshwater, land and ocean ecosystems
- Risk to food security, risk of malnutrition (micronutrient deficiency), and loss of
livelihood due to reduced food production from crops, livestock and fisheries
- Risks to marine ecosystem health and to livelihoods in coastal communities
- Increased human mortality and morbidity due to increased heat and infectious
diseases (including vector-borne and diarrhoeal diseases)
- Reduced economic output and growth, and increased inequality and poverty rates
- Increased risk to water and energy security due to drought and heat
Australasia
- Degradation of tropical shallow coral reefs and associated biodiversity and
ecosystem service values
- Loss of human and natural systems in low-lying coastal areas due to sea level rise
- Impact on livelihoods and incomes due to decline in agricultural production
- Increase in heat-related mortality and morbidity for people and wildlife
- Loss of alpine biodiversity in Australia due to less snow
Asia - Urban infrastructure damage and impacts on human well-being and health due
to flooding, especially in coastal cities and settlements
- Biodiversity loss and habitat shifts as well as associated disruptions in
dependent human systems across freshwater, land, and ocean ecosystems
- More frequent, extensive coral bleaching and subsequent coral mortality
induced by ocean warming and acidification, sea level rise, marine heat waves
and resource extraction
- Decline in coastal fishery resources due to sea level rise, decrease in
precipitation in some parts and increase in temperature
- Risk to food and water security due to increased temperature extremes, rainfall
variability and drought
Central
and
South
America
- Risk to water security
- Severe health effects due to increasing epidemics, in particular vector-borne
diseases
- Coral reef ecosystems degradation due to coral bleaching
- Risk to food security due to frequent/extreme droughts
- Damages to life and infrastructure due to floods, landslides, sea level rise, storm
surges and coastal erosion
North
America
- Climate-sensitive mental health outcomes, human mortality and morbidity due
to increasing average temperature, weather and climate extremes, and
compound climate hazards
- Risk of degradation of marine, coastal and terrestrial ecosystems, including loss
of biodiversity, function, and protective services
- Risk to freshwater resources with consequences for ecosystems, reduced surface
water availability for irrigated agriculture, other human uses, and degraded
water quality
- Risk to food and nutritional security through changes in agriculture, livestock,
hunting, fisheries, and aquaculture productivity and access
- Risks to well-being, livelihoods and economic activities from cascading and
compounding climate hazards, including risks to coastal cities, settlements and
infrastructure from sea level rise
Figure SPM.3 | Synthetic diagrams of global and sectoral assessments and examples of regional key risks. Diagrams show the change in the levels of impacts and
risks assessed for global warming of 0–5°C global surface temperature change relative to pre-industrial period (1850–1900) over the range.
-I ' I ] LIL
I I I I I
I I I II II
. I
l I
I
I
I I ! I
II
18
SPM
Summary for Policymakers
Complex, Compound and Cascading Risks
B.5 Climate change impacts and risks are becoming increasingly complex and more difficult to manage. Multiple climate
hazards will occur simultaneously, and multiple climatic and non-climatic risks will interact, resulting in compounding
overall risk and risks cascading across sectors and regions. Some responses to climate change result in new impacts and
risks. (high confidence) {1.3, 2.4, Box 2.2, Box 9.5, 11.5, 13.5, 14.6, Box 15.1, CCP1.2, CCP2.2, CCB COVID, CCB DISASTER,
CCB INTEREG, CCB SRM, }
B.5.1 Concurrent and repeated climate hazards occur in all regions, increasing impacts and risks to health, ecosystems, infrastructure, livelihoods
and food (high confidence). Multiple risks interact, generating new sources of vulnerability to climate hazards, and compounding overall
risk (high confidence). Increasing concurrence of heat and drought events are causing crop production losses and tree mortality (high
confidence). Above 1.5°C global warming increasing concurrent climate extremes will increase risk of simultaneous crop losses of maize
in major food-producing regions, with this risk increasing further with higher global warming levels (medium confidence). Future sea
level rise combined with storm surge and heavy rainfall will increase compound flood risks (high confidence). Risks to health and food
production will be made more severe from the interaction of sudden food production losses from heat and drought, exacerbated by
heat-induced labour productivity losses (high confidence). These interacting impacts will increase food prices, reduce household incomes,
and lead to health risks of malnutrition and climate-related mortality with no or low levels of adaptation, especially in tropical regions
(high confidence). Risks to food safety from climate change will further compound the risks to health by increasing food contamination
of crops from mycotoxins and contamination of seafood from harmful algal blooms, mycotoxins, and chemical contaminants (high
confidence). {Figure TS.10c, 5.2, 5.4, 5.8, 5.9, 5.11, 5.12, 7.2, 7.3, 9.8, 9.11, 10.4, 11.3, 11.5, 12.3, 13.5, 14.5, 15.3, Box 15.1, 16.6, CCP1.2,
CCP6.2, , WGI AR6 SPM A.3.1, WGI AR6 SPM A.3.2, WGI AR6 SPM C.2.7}
B.5.2 Adverse impacts from climate hazards and resulting risks are cascading across sectors and regions (high confidence), propagating
impacts along coasts and urban centres (medium confidence) and in mountain regions (high confidence). These hazards and cascading
risks also trigger tipping points in sensitive ecosystems and in significantly and rapidly changing social-ecological systems impacted
by ice melt, permafrost thaw and changing hydrology in polar regions (high confidence). Wildfires, in many regions, have affected
ecosystems and species, people and their built assets, economic activity, and health (medium to high confidence). In cities and
(a) Global surface temperature changes in °C relative to 1850–1900. These changes were obtained by combining CMIP6 model simulations with observational constraints based
on past simulated warming, as well as an updated assessment of equilibrium climate sensitivity (Box SPM.1). Changes relative to 1850–1900 based on 20-year averaging periods
are calculated by adding 0.85°C (the observed global surface temperature increase from 1850–1900 to 1995–2014) to simulated changes relative to 1995–2014. Very likely ranges
are shown for SSP1-2.6 and SSP3-7.0 (WGI AR6 Figure SPM.8). Assessments were carried out at the global scale for (b), (c), (d) and (e).
(b) The Reasons for Concern (RFC) framework communicates scientific understanding about accrual of risk for five broad categories. Diagrams are shown for each RFC, assuming
low to no adaptation (i.e., adaptation is fragmented, localized and comprises incremental adjustments to existing practices). However, the transition to a very high risk level has an
emphasis on irreversibility and adaptation limits. Undetectable risk level (white) indicates no associated impacts are detectable and attributable to climate change; moderate risk
(yellow) indicates associated impacts are both detectable and attributable to climate change with at least medium confidence, also accounting for the other specific criteria for key
risks; high risk (red) indicates severe and widespread impacts that are judged to be high on one or more criteria for assessing key risks; and very high risk level (purple) indicates
very high risk of severe impacts and the presence of significant irreversibility or the persistence of climate-related hazards, combined with limited ability to adapt due to the nature
of the hazard or impacts/risks. The horizontal line denotes the present global warming of 1.09°C which is used to separate the observed, past impacts below the line from the future
projected risks above it. RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and
have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its Indigenous Peoples, mountain glaciers and biodiversity hotspots. RFC2: Extreme
weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildfires,
and coastal flooding. RFC3: Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards,
exposure or vulnerability. RFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric, such as monetary damages, lives
affected, species lost or ecosystem degradation at a global scale. RFC5: Large-scale singular events: relatively large, abrupt and sometimes irreversible changes in systems caused
by global warming, such as ice sheet disintegration or thermohaline circulation slowing. Assessment methods are described in SM16.6 and are identical to AR5, but are enhanced
by a structured approach to improve robustness and facilitate comparison between AR5 and AR6.
Risks for (c) terrestrial and freshwater ecosystems and (d) ocean ecosystems. For c) and d), diagrams shown for each risk assume low to no adaptation. The transition to a very high
risk level has an emphasis on irreversibility and adaptation limits.
(e) Climate-sensitive human health outcomes under three scenarios of adaptation effectiveness. The assessed projections were based on a range of scenarios, including SRES,
CMIP5, and ISIMIP, and, in some cases, demographic trends. The diagrams are truncated at the nearest whole ºC within the range of temperature change in 2100 under three SSP
scenarios in panel (a).
(f) Examples of regional key risks. Risks identified are of at least medium confidence level. Key risks are identified based on the magnitude of adverse consequences (pervasiveness
of the consequences, degree of change, irreversibility of consequences, potential for impact thresholds or tipping points, potential for cascading effects beyond system boundaries);
likelihood of adverse consequences; temporal characteristics of the risk; and ability to respond to the risk, e.g., by adaptation. The full set of 127 assessed global and regional key
risks is given in SM16.7. Diagrams are provided for some risks. The development of synthetic diagrams for Small Islands, Asia and Central and South America were limited by the
availability of adequately downscaled climate projections, with uncertainty in the direction of change, the diversity of climatologies and socioeconomic contexts across countries
within a region, and the resulting low number of impact and risk projections for different warming levels. Absence of risks diagrams does not imply absence of risks within a region.
(Box SPM.1) {Figure TS.4, Figure 2.11, Figure SM3.1, Figure 7.9, Figure 9.6, Figure 11.6, Figure 13.28, 16.5, 16.6, Figure 16.15, SM16.3, SM16.4, SM16.5, SM16.6 (methodologies),
SM16.7, Figure CCP4.8, Figure CCP4.10, Figure CCP6.5, WGI AR6 2, WGI AR6 SPM A.1.2, WGI AR6 Figure SPM.8}
19
SPM
Summary for Policymakers
settlements, climate impacts to key infrastructure are leading to losses and damages across water and food systems, and affect
economic activity, with impacts extending beyond the area directly impacted by the climate hazard (high confidence). In Amazonia,
and in some mountain regions, cascading impacts from climatic (e.g., heat) and non-climatic stressors (e.g., land use change) will result
in irreversible and severe losses of ecosystem services and biodiversity at 2°C global warming level and beyond (medium confidence).
Unavoidable sea level rise will bring cascading and compounding impacts resulting in losses of coastal ecosystems and ecosystem
services, groundwater salinisation, flooding and damages to coastal infrastructure that cascade into risks to livelihoods, settlements,
health, well-being, food and water security, and cultural values in the near to long-term (high confidence). (Figure SPM.3) {Figure TS.10,
2.5, 3.4, 3.5, Box 7.3, Box 8.7, Box 9.4, 11.5, Box 11.1, 12.3, 13.9, 14.6, 15.3, 16.5, 16.6, CCP1.2, CCP2.2, CCP5.2, CCP5.3, CCP6.2,
CCP6.3, Box CCP6.1, Box CCP6.2, CCB EXTREMES, WGI AR6 Figure SPM.8d}
B.5.3 Weather and climate extremes are causing economic and societal impacts across national boundaries through supply-chains, markets,
and natural resource flows, with increasing transboundary risks projected across the water, energy and food sectors (high confidence).
Supply chains that rely on specialized commodities and key infrastructure can be disrupted by weather and climate extreme events.
Climate change causes the redistribution of marine fish stocks, increasing risk of transboundary management conflicts among fisheries
users, and negatively affecting equitable distribution of food provisioning services as fish stocks shift from lower to higher latitude regions,
thereby increasing the need for climate-informed transboundary management and cooperation (high confidence). Precipitation and water
availability changes increases the risk of planned infrastructure projects, such as hydropower in some regions, having reduced productivity
for food and energy sectors including across countries that share river basins (medium confidence). {Figure TS.10e-f, 3.4, 3.5, 4.5, 5.8, 5.13,
6.2, 9.4, Box 9.5,14.5, Box 14.5, Box 14.6, CCP5.3, CCB DISASTER, CCB EXTREMES, CCB INTEREG, CCB MOVING PLATE}
B.5.4 Risks arise from some responses that are intended to reduce the risks of climate change, including risks from maladaptation and adverse
side effects of some emissions reduction and carbon dioxide removal measures (high confidence). Deployment of afforestation of
naturally unforested land, or poorly implemented bioenergy, with or without carbon capture and storage, can compound climate-related
risks to biodiversity, water and food security, and livelihoods, especially if implemented at large scales, especially in regions with insecure
land tenure (high confidence). {Box 2.2, 4.1, 4.7, 5.13, Table 5.18, Box 9.3, Box 13.2, CCB NATURAL, CWGB BIOECONOMY}
B.5.5 Solar radiation modification approaches, if they were to be implemented, introduce a widespread range of new risks to people and
ecosystems, which are not well understood (high confidence). Solar radiation modification approaches have potential to offset warming
and ameliorate some climate hazards, but substantial residual climate change or overcompensating change would occur at regional
scales and seasonal timescales (high confidence). Large uncertainties and knowledge gaps are associated with the potential of solar
radiation modification approaches to reduce climate change risks. Solar radiation modification would not stop atmospheric CO2
concentrations from increasing or reduce resulting ocean acidification under continued anthropogenic emissions (high confidence).
{CWGB SRM}
Impacts of Temporary Overshoot
37 In this report, overshoot pathways exceed 1.5°C global warming and then return to that level, or below, after several decades.
38 Despite limited evidence specifically on the impacts of a temporary overshoot of 1.5°C, a much broader evidence base from process understanding and the impacts of higher global warming levels
allows a high confidence statement on the irreversibility of some impacts that would be incurred following such an overshoot.
B.6 If global warming transiently exceeds 1.5°C in the coming decades or later (overshoot)37, then many human and natural
systems will face additional severe risks, compared to remaining below 1.5°C (high confidence). Depending on the magnitude
and duration of overshoot, some impacts will cause release of additional greenhouse gases (medium confidence)
and some will be irreversible, even if global warming is reduced (high confidence). (Box SPM.1, Figure SPM.3) {2.5, 3.4,
12.3, 16.6, CCB DEEP, CCB SLR}
B.6.1 While model-based assessments of the impacts of overshoot pathways are limited, observations and current understanding of processes
permit assessment of impacts from overshoot. Additional warming, e.g., above 1.5°C during an overshoot period this century, will
result in irreversible impacts on certain ecosystems with low resilience, such as polar, mountain, and coastal ecosystems, impacted
by ice-sheet, glacier melt, or by accelerating and higher committed sea level rise (high confidence).38 Risks to human systems will
increase, including those to infrastructure, low-lying coastal settlements, some ecosystem-based adaptation measures, and associated
livelihoods (high confidence), cultural and spiritual values (medium confidence). Projected impacts are less severe with shorter duration
and lower levels of overshoot (medium confidence). {2.5, 3.4, 12.3, 13.2, 16.5, 16.6, CCP1.2, CCP2.2, CCP5.3, CCP6.1, CCP6.2, CCB SLR,
WGI AR6 SPM B.5, WGI AR6 SPM C.3, SROCC 2.3, SROCC 5.4}
20
SPM
Summary for Policymakers
B.6.2 Risk of severe impacts increase with every additional increment of global warming during overshoot (high confidence). In high-carbon
ecosystems (currently storing 3,000 to 4,000 GtC)39 such impacts are already observed and are projected to increase with every
additional increment of global warming, such as increased wildfires, mass mortality of trees, drying of peatlands, and thawing of
permafrost, weakening natural land carbon sinks and increasing releases of greenhouse gases (medium confidence). The resulting
contribution to a potential amplification of global warming indicates that a return to a given global warming level or below would be
more challenging (medium confidence). {2.4, 2.5, CCP4.2, WGI AR6 SPM B.4.3, SROCC 5.4}
C: Adaptation Measures and Enabling Conditions
Adaptation, in response to current climate change, is reducing climate risks and vulnerability mostly via adjustment of existing systems. Many
adaptation options exist and are used to help manage projected climate change impacts, but their implementation depends upon the capacity and
effectiveness of governance and decision-making processes. These and other enabling conditions can also support climate resilient development
(Section D).
Current Adaptation and its Benefits
39 At the global scale, terrestrial ecosystems currently remove more carbon from the atmosphere (-3.4 ± 0.9 Gt yr-1) than they emit (+1.6 ± 0.7 Gt yr-1), a net sink of -1.9 ± 1.1 Gt yr-1. However, recent
climate change has shifted some systems in some regions from being net carbon sinks to net carbon sources.
40 Adaptation gaps are defined as the difference between actually implemented adaptation and a societally set goal, determined largely by preferences related to tolerated climate change impacts and
reflecting resource limitations and competing priorities.
C.1 Progress in adaptation planning and implementation has been observed across all sectors and regions, generating multiple
benefits (very high confidence). However, adaptation progress is unevenly distributed with observed adaptation gaps40 (high
confidence). Many initiatives prioritize immediate and near-term climate risk reduction which reduces the opportunity for
transformational adaptation (high confidence). {2.6, 5.14, 7.4, 10.4, 12.5, 13.11, 14.7, 16.3, 17.3, CCP5.2, CCP5.4}
C.1.1 Adaptation planning and implementation have continued to increase across all regions (very high confidence). Growing public and
political awareness of climate impacts and risks has resulted in at least 170 countries and many cities including adaptation in their
climate policies and planning processes (high confidence). Decision support tools and climate services are increasingly being used
(very high confidence). Pilot projects and local experiments are being implemented in different sectors (high confidence). Adaptation
can generate multiple additional benefits such as improving agricultural productivity, innovation, health and well-being, food security,
livelihood, and biodiversity conservation as well as reduction of risks and damages (very high confidence). {1.4, 2.6, 3.5, 3.6, 4.7, 4.8,
5.4, 5.6, 5.10, 6.4, 7.4, 8.5, 9.3, 9.6, 10.4, 12.5, 13.11, 15.5, 16.3, 17.2, 17.3, 17.5, CCP5.4, CCB ADAPT, CCB NATURAL}
C.1.2 Despite progress, adaptation gaps exist between current levels of adaptation and levels needed to respond to impacts and reduce
climate risks (high confidence). Most observed adaptation is fragmented, small in scale, incremental, sector-specific, designed to
respond to current impacts or near-term risks, and focused more on planning rather than implementation (high confidence). Observed
adaptation is unequally distributed across regions (high confidence), and gaps are partially driven by widening disparities between the
estimated costs of adaptation and documented finance allocated to adaptation (high confidence). The largest adaptation gaps exist
among lower income population groups (high confidence). At current rates of adaptation planning and implementation the adaptation
gap will continue to grow (high confidence). As adaptation options often have long implementation times, long-term planning and
accelerated implementation, particularly in the next decade, is important to close adaptation gaps, recognising that constraints remain
for some regions (high confidence). {1.1, 1.4, 5.6, 6.3, Figure 6.4, 7.4, 8.3, 10.4, 11.3, 11.7, 13.11, Box 13.1, 15.2, 15.5, 16.3, 16.5,
Box 16.1, Figure 16.4, Figure 16.5, 17.4, 18.2, CCP2.4, CCP5.4, CCB FINANCE, CCB SLR}
21
SPM
Summary for Policymakers
Future Adaptation Options and their Feasibility
41 In this report, feasibility refers to the potential for a mitigation or adaptation option to be implemented. Factors influencing feasibility are context-dependent, temporally dynamic, and may vary between
different groups and actors. Feasibility depends on geophysical, environmental-ecological, technological, economic, socio-cultural and institutional factors that enable or constrain the implementation
of an option. The feasibility of options may change when different options are combined and increase when enabling conditions are strengthened.
42 Effectiveness refers to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk.
43 In this report, the term natural forests describes those which are subject to little or no direct human intervention, whereas the term managed forests describes those where planting or other
management activities take place, including those managed for commodity production.
C.2 There are feasible41 and effective42 adaptation options which can reduce risks to people and nature. The feasibility of
implementing adaptation options in the near-term differs across sectors and regions (very high confidence). The effectiveness
of adaptation to reduce climate risk is documented for specific contexts, sectors and regions (high confidence)
and will decrease with increasing warming (high confidence). Integrated, multi-sectoral solutions that address social inequities,
differentiate responses based on climate risk and cut across systems, increase the feasibility and effectiveness of
adaptation in multiple sectors (high confidence). (Figure SPM.4) {Figure TS.6e, 1.4, 3.6, 4.7, 5.12, 6.3, 7.4, 11.3, 11.7, 13.2,
15.5, 17.6, CCP2.3, CCB FEASIB}
Land, Ocean and Ecosystems Transition
C.2.1 Adaptation to water-related risks and impacts make up the majority of all documented adaptation (high confidence). For inland
flooding, combinations of non-structural measures like early warning systems and structural measures like levees have reduced loss
of lives (medium confidence). Enhancing natural water retention such as by restoring wetlands and rivers, land use planning such
as no build zones or upstream forest management, can further reduce flood risk (medium confidence). On-farm water management,
water storage, soil moisture conservation and irrigation are some of the most common adaptation responses and provide economic,
institutional or ecological benefits and reduce vulnerability (high confidence). Irrigation is effective in reducing drought risk and climate
impacts in many regions and has several livelihood benefits, but needs appropriate management to avoid potential adverse outcomes,
which can include accelerated depletion of groundwater and other water sources and increased soil salinization (medium confidence).
Large scale irrigation can also alter local to regional temperature and precipitation patterns (high confidence), including both alleviating
and exacerbating temperature extremes (medium confidence). The effectiveness of most water-related adaptation options to reduce
projected risks declines with increasing warming (high confidence). {4.1, 4.6, 4.7, Box 4.3, Box 4.6, Box 4.7, Figure 4.22, Figure 4.28,
Figure 4.29, Table 4.9, 9.3, 9.7, 11.3, 12.5, 13.1, 13.2, 16.3, CCP5.4}
C.2.2 Effective adaptation options, together with supportive public policies enhance food availability and stability and reduce climate risk for
food systems while increasing their sustainability (medium confidence). Effective options include cultivar improvements, agroforestry,
community-based adaptation, farm and landscape diversification, and urban agriculture (high confidence). Institutional feasibility,
adaptation limits of crops and cost effectiveness also influence the effectiveness of the adaptation options (limited evidence, medium
agreement). Agroecological principles and practices, ecosystem-based management in fisheries and aquaculture, and other approaches
that work with natural processes support food security, nutrition, health and well-being, livelihoods and biodiversity, sustainability and
ecosystem services (high confidence). These services include pest control, pollination, buffering of temperature extremes, and carbon
sequestration and storage (high confidence). Trade-offs and barriers associated with such approaches include costs of establishment,
access to inputs and viable markets, new knowledge and management (high confidence) and their potential effectiveness varies by
socioeconomic context, ecosystem zone, species combinations and institutional support (medium confidence). Integrated, multi-sectoral
solutions that address social inequities and differentiate responses based on climate risk and local situation will enhance food security
and nutrition (high confidence). Adaptation strategies which reduce food loss and waste or support balanced diets33 (as described in the
IPCC Special Report on Climate Change and Land) contribute to nutrition, health, biodiversity and other environmental benefits (high
confidence). {3.2, 4.7, 4.6, Box 4.3, 5.4, 5.5, 5.6, 5.8, 5.9, 5.10, 5.11, 5.12, 5.13, 5.14, Box 5.10, Box 5.13, 6.3, 7.4, 10.4, 12.5, 13.5, 13.10,
14.5, CCP5.4, CCB FEASIB, CCB HEALTH, CCB MOVING PLATE, CCB NATURAL, CWGB BIOECONOMY}
C.2.3 Adaptation for natural forests43 includes conservation, protection and restoration measures. In managed forests43, adaptation options
include sustainable forest management, diversifying and adjusting tree species compositions to build resilience, and managing
increased risks from pests and diseases and wildfires. Restoring natural forests and drained peatlands and improving sustainability
of managed forests, generally enhances the resilience of carbon stocks and sinks. Cooperation, and inclusive decision making, with
local communities and Indigenous Peoples, as well as recognition of inherent rights of Indigenous Peoples, is integral to successful
forest adaptation in many areas. (high confidence) {2.6, Box 2.2, 5.6, 5.13, Table 5.23, 11.4, 12.5, 13.5, Box 14.1, Box 14.2, CCP7.5,
Box CCP7.1, CCB FEASIB, CCB INDIG, CCB NATURAL}
22
SPM
Summary for Policymakers
Climate responses1
and adaptation options
Climate services, including Early Warning Systems
Resilient power systems
Agroforestry
Energy reliability
Sustainable aquaculture and fisheries
Efficient livestock systems
Biodiversity management and ecosystem connectivity
Integrated coastal zone management
Water use efficiency and water resource management
Improved cropland management
Green infrastructure and ecosystem services
Sustainable land use and urban planning
Improve water use efficiency
Health and health systems adaptation
Livelihood diversification
Disaster risk management
Social safety nets
Risk spreading and sharing
Coastal defence and hardening
Human health
Peace and
human mobility
Living standards and equity
Coastal socioecological
systems
Terrestrial and
ocean ecosystem
services
Food
security
Critical
infrastructure,
networks
and services
Water security
Critical infrastructure,
networks and services
Water
security
Representative
key risks
Crosssectoral
System
transitions
Land and
ocean
ecosystems
Urban and
infrastructure
systems
Energy
systems
Other
cross-cutting
risks
High
Low
Medium
Dimensions of potential feasibility
1 The term response is used
here instead of adaptation
because some responses,
such as retreat, may or may
not be considered to be
adaptation.
2 Including sustainable forest
management, forest
conservation and restoration,
reforestation and
afforestation.
3 Migration, when voluntary,
safe and orderly, allows
reduction of risks to climatic
and non-climatic stressors.
Forest-based adaptation2
Planned relocation and resettlement
Human migration3
Feasibility level and
synergies with mitigation
/ Insufficient evidence
Confidence level
in potential feasibility and
in synergies with mitigation
Medium
High
Low
Sustainable urban water management
Economic
Institutional
Technological
Social
/
Geophysical
not applicable
not applicable
/
Environmental
Potential
feasibility
Synergies
with
mitigation
/
not assessed
Footnotes:
Dimensions of
potential feasibility
(a) Diverse feasible climate responses and adaptation options exist to respond to Representative Key Risks of climate change, with varying synergies with mitigation
Multidimensional feasibility and synergies with mitigation of climate responses and adaptation options relevant in the near-term, at global scale and up to 1.5°C of global warming
Figure SPM.4 | (a) Climate responses and adaptation options, organized by System Transitions and Representative Key Risks (RKRs), are assessed for their multidimensional feasibility at global scale, in the
near term and up to 1.5°C global warming. As literature above 1.5°C is limited, feasibility at higher levels of warming may change, which is currently not possible to assess robustly. Climate responses and adaptation options at global
scale are drawn from a set of options assessed in AR6 that have robust evidence across the feasibility dimensions. This figure shows the six feasibility dimensions (economic, technological, institutional, social, environmental and geophysical)
that are used to calculate the potential feasibility of climate responses and adaptation options, along with their synergies with mitigation. For potential feasibility and feasibility dimensions, the figure shows high, medium, or low feasibility.
Synergies with mitigation are identified as high, medium, and low. Insufficient evidence is denoted by a dash. {CCB FEASIB, Table SMCCB FEASIB.1.1, SR1.5 4.SM.4.3}
Ooo • ••
0 •••••• . .. .... • • ••••• «l • ·@@e ........... • • .... t •••••• • •• ••• ... . .. • • • •••
·el •· •·•• • • • • • • • •• • • • ·••·
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) •• •••• ••••••••••• • • • ••• Oll . .... . •. ••· ..... • • •
•• •••• . •· ........ • •••••
23
SPM
Summary for Policymakers
Footnotes: 1 The term response is used here instead of adaptation because some responses, such as retreat, may or may not be considered to be adaptation. 2 Including sustainable forest management, forest
conservation and restoration, reforestation and afforestation. 3 Migration, when voluntary, safe and orderly, allows reduction of risks to climatic and non-climatic stressors. 4 The Sustainable Development Goals
(SDGs) are integrated and indivisible, and efforts to achieve any goal in isolation may trigger synergies or trade-offs with other SDGs. 5 Relevant in the near-term, at global scale and up to 1.5°C of global warming.
Types of relation
Climate services, including Early Warning Systems
Forest-based adaptation2
Resilient power systems
Agroforestry
Energy reliability
Sustainable aquaculture and fisheries
Efficient livestock systems
Biodiversity management and ecosystem connectivity
Integrated coastal zone management
Water use efficiency and water resource management
Improved cropland management
Green infrastructure and ecosystem services
Sustainable land use and urban planning
Planned relocation and resettlement
Improve water use efficiency
Health and health systems adaptation
Livelihood diversification
Human migration3
Disaster risk management
Social safety nets
Risk spreading and sharing
Coastal defence and hardening
Observed relation with
sectors and groups at risk
Ethnic
groups
Gender
equity
Ecosystems
and their
services
Lowincome
groups
Crosssectoral
System
transitions
Land and
ocean
ecosystems
Urban and
infrastructure
systems
Energy
systems
Relation with
Sustainable Development Goals4, 5
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
+ + + • • • + + + +
+ • + + + + + + + + + +
+ + + + + + + +
+ + + + + + + + + + + +
+ + + + + + + +
+ + + + + + + + + + + +
+ + + • + + + +
+ + + + +
+ + + + + + + +
+ • + • • + + + •
+ + + + + + + + • + + + +
+ + + + + + +
+ + + + + +
•
+ + + + + + + + +
+ + + + + + + + + + + + + + +
+ + + + • • • • • – – • •
• • • + • + • • •
+ + + + • + • + + +
+ + + + + + +
+ + + • + • •
+ + – • • •
1: No Poverty
2: Zero Hunger
3: Good Health and Well-being
4: Quality Education
5: Gender Equality
7: Affordable and Clean Energy
8: Decent Work and Economic Growth
9: Industry, Innovation and Infrastructure
10: Reducing Inequality
11: Sustainable Cities and Communities
12: Responsible Consumption and Production
13: Climate Action
14: Life Below Water
15: Life On Land
16: Peace, Justice, and Strong Institutions
17: Partnerships for the Goals
6: Clean Water and Sanitation
–
–
– –
– –
+
+
+
+
+
+
+
+
+
+
+ +
+
+
+ +
+
+
+
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
/ /
/ /
/
/
/
/
•
not assessed
not assessed
not assessed
not assessed
not assessed
not assessed
+ With benefits
• Not clear or mixed
– With dis-benefits
/ Insufficient evidence
Related
Sustainable Development Goals
Confidence level
in type of relation with
sectors and groups at risk
Medium
High
Low
Climate responses¹
and adaptation options
+
Sustainable urban water management + + + + + +
+
+ / – +
not assessed
(b) Climate responses and adaptation options have benefits for ecosystems, ethnic groups, gender equity, low-income groups and the Sustainable Development Goals
Relations of sectors and groups at risk (as observed) and the SDGs (relevant in the near-term, at global scale and up to 1.5°C of global warming) with climate responses and adaptation options
+ + + +
•• •
- • • • • • --- •••••· ·•· · ••••• • •••• ••••• • --•••• •••••• •••• •••••••• •• •••••••• •• ••• •••••• • tr -• • •• •••••••• •••• i% " -• ••••• • • • • - • • •••••• •••••• ••••••••••• • • • •• - •••• ••• • •••• ••• -- •••· ··· •••••••••••••••• ••••• ••• - ••• •• • •••• ••••• - •••• •• • •••• •••••
8 • ': • • •• • • • •••• ': ••·
4"I -•• • •• • • •••• ••
.t, • •• • • •• • • ·i
- '' '' ' l <" ■ :• • •• •• • •••• :• '
24
SPM
Summary for Policymakers
C.2.4 Conservation, protection and restoration of terrestrial, freshwater, coastal and ocean ecosystems, together with targeted management
to adapt to unavoidable impacts of climate change, reduces the vulnerability of biodiversity to climate change (high confidence). The
resilience of species, biological communities and ecosystem processes increases with size of natural area, by restoration of degraded
areas and by reducing non-climatic stressors (high confidence). To be effective, conservation and restoration actions will increasingly
need to be responsive, as appropriate, to ongoing changes at various scales, and plan for future changes in ecosystem structure,
community composition and species’ distributions, especially as 1.5°C global warming is approached and even more so if it is exceeded
(high confidence). Adaptation options, where circumstances allow, include facilitating the movement of species to new ecologically
appropriate locations, particularly through increasing connectivity between conserved or protected areas, targeted intensive
management for vulnerable species and protecting refugial areas where species can survive locally (medium confidence). {2.3, 2,6,
Figure 2.1, Table 2.6, 3.3, 3.6, Box 3.4, 4.6, Box 4.6, Box 11.2, 12.3, 12.5, 13.4, 14.7, CCP5.4, CCB FEASIB}
C.2.5 Effective Ecosystem-based Adaptation44 reduces a range of climate change risks to people, biodiversity and ecosystem services with
multiple co-benefits (high confidence). Ecosystem-based Adaptation is vulnerable to climate change impacts, with effectiveness
declining with increasing global warming (high confidence). Urban greening using trees and other vegetation can provide local cooling
(very high confidence). Natural river systems, wetlands and upstream forest ecosystems reduce flood risk by storing water and slowing
water flow, in most circumstances (high confidence). Coastal wetlands protect against coastal erosion and flooding associated with
storms and sea level rise where sufficient space and adequate habitats are available until rates of sea level rise exceeds natural
adaptive capacity to build sediment (very high confidence). {2.4, 2.5, 2.6, Table 2.7, 3.4, 3.5, 3.6, Figure 3.26, 4.6, Box 4.6, Box 4.7, 5.5,
5.14, Box 5.11, 6.3, 6.4, Figure 6.6, 7.4, 8.5, 8.6, 9.6, 9.8, 9.9, 10.2, 11.3, 12.5, 13.3, 13.4, 13.5, 14.5, Box 14.7, 16.3, 18.3, CCP5.4, CCB
FEASIB.3, CCB HEALTH, CCB MOVING PLATE, CCB NATURAL, CWGB BIOECONOMY}
Urban, Rural and Infrastructure Transition
C.2.6 Considering climate change impacts and risks in the design and planning of urban and rural settlements and infrastructure is critical
for resilience and enhancing human well-being (high confidence). The urgent provision of basic services, infrastructure, livelihood
diversification and employment, strengthening of local and regional food systems and community-based adaptation enhance lives and
livelihoods, particularly of low-income and marginalised groups (high confidence). Inclusive, integrated and long-term planning at local,
municipal, sub-national and national scales, together with effective regulation and monitoring systems and financial and technological
resources and capabilities foster urban and rural system transition (high confidence). Effective partnerships between governments, civil
society, and private sector organizations, across scales provide infrastructure and services in ways that enhance the adaptive capacity
of vulnerable people (medium to high confidence). {5.12, 5.13, 5.14, 6.3, 6.4, Box 6.3, Box 6.6, Table 6.6, 7.4, 12.5, 13.6, 14.5, Box 14.4,
Box 17.4, CCP2.3, CCP2.4, CCP5.4, CCB FEASIB}
C.2.7 An increasing number of adaptation responses exist for urban systems, but their feasibility and effectiveness is constrained by
institutional, financial, and technological access and capacity, and depends on coordinated and contextually appropriate responses
across physical, natural and social infrastructure (high confidence). Globally, more financing is directed at physical infrastructure than
natural and social infrastructure (medium confidence) and there is limited evidence of investment in the informal settlements hosting
the most vulnerable urban residents (medium to high confidence). Ecosystem-based adaptation (e.g., urban agriculture and forestry,
river restoration) has increasingly been applied in urban areas (high confidence). Combined ecosystem-based and structural adaptation
responses are being developed, and there is growing evidence of their potential to reduce adaptation costs and contribute to flood
control, sanitation, water resources management, landslide prevention and coastal protection (medium confidence). {3.6, Box 4.6, 5.12,
6.3, 6.4, Table 6.8, 7.4, 9.7, 9.9, 10.4, Table 10.3, 11.3, 11.7, Box 11.6, 12.5, 13.2, 13.3, 13.6, 14.5, 15.5, 17.2, Box 17.4, CCP2.3, CCP
3.2, CCP5.4, CCB FEASIB, CCB SLR, SROCC SPM}
44 Ecosystem based Adaptation (EbA) is recognised internationally under the Convention on Biological Diversity (CBD14/5). A related concept is Nature-based Solutions (NbS), which includes a broader
range of approaches with safeguards, including those that contribute to adaptation and mitigation. The term ‘Nature-based Solutions’ is widely but not universally used in the scientific literature. The
term is the subject of ongoing debate, with concerns that it may lead to the misunderstanding that NbS on its own can provide a global solution to climate change.
Figure SPM.4 | (b) Climate responses and adaptation options, organized by System Transitions and Representative Key Risks, are assessed at global scale
for their likely ability to reduce risks for ecosystems and social groups at risk, as well as their relation with the 17 Sustainable Development Goals (SDGs).
Climate responses and adaptation options are assessed for observed benefits (+) to ecosystems and their services, ethnic groups, gender equity, and low-income groups, or observed
dis-benefits (-) for these systems and groups. Where there is highly diverging evidence of benefits/ dis-benefits across the scientific literature, e.g., based on differences between
regions, it is shown as not clear or mixed (•). Insufficient evidence is shown by a dash. The relation with the SDGs is assessed as having benefits (+), dis-benefits (-) or not clear or
mixed (•) based on the impacts of the climate response and adaptation option on each SDG. Areas not coloured indicate there is no evidence of a relation or no interaction with the
respective SDG. The climate responses and adaptation options are drawn from two assessments. For comparability of climate responses and adaptation options see Table SM17.5.
{17.2, 17.5, CCB FEASIB}
25
SPM
Summary for Policymakers
C.2.8 Sea level rise poses a distinctive and severe adaptation challenge as it implies dealing with slow onset changes and increased frequency
and magnitude of extreme sea level events which will escalate in the coming decades (high confidence). Such adaptation challenges
would occur much earlier under high rates of sea level rise, in particular if low-likelihood, high impact outcomes associated with
collapsing ice sheets occur (high confidence). Responses to ongoing sea level rise and land subsidence in low-lying coastal cities and
settlements and small islands include protection, accommodation, advance and planned relocation (high confidence)45. These responses
are more effective if combined and/or sequenced, planned well ahead, aligned with sociocultural values and development priorities,
and underpinned by inclusive community engagement processes (high confidence). { 6.2, 10.4, 11.7, Box 11.6, 13.2, 14.5, 15.5, CCP2.3,
CCB SLR, WGI AR6 SPM B.5, WGI AR6 SPM C.3, SROCC SPM C3.2}
C.2.9 Approximately 3.4 billion people globally live in rural areas around the world, and many are highly vulnerable to climate change.
Integrating climate adaptation into social protection programs, including cash transfers and public works programmes, is highly feasible
and increases resilience to climate change, especially when supported by basic services and infrastructure. Social safety nets are
increasingly being reconfigured to build adaptive capacities of the most vulnerable in rural and also urban communities. Social safety
nets that support climate change adaptation have strong co-benefits with development goals such as education, poverty alleviation,
gender inclusion and food security. (high confidence) {5.14, 9.4, 9.10, 9.11, 12.5, 14.5, CCP5.4, CCB FEASIB, CCB GENDER}
Energy System Transition
C.2.10 Within energy system transitions, the most feasible adaptation options support infrastructure resilience, reliable power systems
and efficient water use for existing and new energy generation systems (very high confidence). Energy generation diversification,
including with renewable energy resources and generation that can be decentralised depending on context (e.g., wind, solar, small
scale hydroelectric) and demand side management (e.g., storage, and energy efficiency improvements) can reduce vulnerabilities to
climate change, especially in rural populations (high confidence). Adaptations for hydropower and thermo-electric power generation
are effective in most regions up to 1.5°C to 2°C, with decreasing effectiveness at higher levels of warming (medium confidence).
Climate responsive energy markets, updated design standards on energy assets according to current and projected climate change,
smart-grid technologies, robust transmission systems and improved capacity to respond to supply deficits have high feasibility in the
medium- to long-term, with mitigation co-benefits (very high confidence). {4.6, 4.7, Figure 4.28, Figure 4.29, 10.4, Table 11.8, 13.6,
Figure 13.16, Figure 13.19, 18.3,CCP5.2, CCP5.4, CCB FEASIB, CWGB BIOECONOMY}
Cross-cutting Options
C.2.11 Strengthening the climate resiliency of health systems will protect and promote human health and well-being (high confidence). There
are multiple opportunities for targeted investments and finance to protect against exposure to climate hazards, particularly for those
at highest risk. Heat Health Action Plans that include early warning and response systems are effective adaptation options for extreme
heat (high confidence). Effective adaptation options for water-borne and food-borne diseases include improving access to potable
water, reducing exposure of water and sanitation systems to flooding and extreme weather events, and improved early warning systems
(very high confidence). For vector-borne diseases, effective adaptation options include surveillance, early warning systems, and vaccine
development (very high confidence). Effective adaptation options for reducing mental health risks under climate change include improving
surveillance, access to mental health care, and monitoring of psychosocial impacts from extreme weather events (high confidence). Health
and well-being would benefit from integrated adaptation approaches that mainstream health into food, livelihoods, social protection,
infrastructure, water and sanitation policies requiring collaboration and coordination at all scales of governance (very high confidence).
{5.12, 6.3, 7.4, 9.10, Box 9.7, 11.3, 12.5, 13.7, 14.5, CCB COVID, CCB FEASIB, CCB ILLNESS }
C.2.12 Increasing adaptive capacities minimises the negative impacts of climate-related displacement and involuntary migration for migrants
and sending and receiving areas (high confidence). This improves the degree of choice under which migration decisions are made,
ensuring safe and orderly movements of people within and between countries (high confidence). Some development reduces underlying
vulnerabilities associated with conflict, and adaptation contributes by reducing the impacts of climate change on climate sensitive
drivers of conflict (high confidence). Risks to peace are reduced, for example, by supporting people in climate-sensitive economic
activities (medium confidence) and advancing women’s empowerment (high confidence). {7.4, Box 9.8, Box 10.2, 12.5, CCB FEASIB,
CCB MIGRATE}
45 The term ‘response’ is used here instead of adaptation because some responses, such as retreat, may or may not be considered to be adaptation.
26
SPM
Summary for Policymakers
C.2.13 There are a range of adaptation options, such as disaster risk management, early warning systems, climate services and risk spreading
and sharing that have broad applicability across sectors and provide greater benefits to other adaptation options when combined (high
confidence). For example, climate services that are inclusive of different users and providers can improve agricultural practices, inform
better water use and efficiency, and enable resilient infrastructure planning (high confidence). {2.6, 3.6, 4.7, 5.4, 5.5, 5.6, 5.8, 5.9, 5.12,
5.14, 9.4, 9.8, 10.4, 12.5, 13.11, CCP5.4, CCB FEASIB, CCB MOVING PLATE}
Limits to Adaptation
46 Climate literacy encompasses being aware of climate change, its anthropogenic causes and implications.
C.3 Soft limits to some human adaptation have been reached, but can be overcome by addressing a range of constraints,
primarily financial, governance, institutional and policy constraints (high confidence). Hard limits to adaptation have been
reached in some ecosystems (high confidence). With increasing global warming, losses and damages will increase and
additional human and natural systems will reach adaptation limits (high confidence). {Figure TS.7, 1.4, 2.4, 2.5, 2.6, 3.4, 3.6,
4.7, Figure 4.30, 5.5, Table 8.6, Box 10.7, 11.7, Table 11.16, 12.5, 13.2, 13.5, 13.6, 13.10, 13.11, Figure 13.21, 14.5, 15.6, 16.4,
Figure 16.8, Table 16.3, Table 16.4, CCP1.2, CCP1.3, CCP2.3, CCP3.3, CCP5.2, CCP5.4, CCP6.3, CCP7.3, CCB SLR}
C.3.1 Soft limits to some human adaptation have been reached, but can be overcome by addressing a range of constraints, which primarily
consist of financial, governance, institutional and policy constraints (high confidence). For example, individuals and households in
low-lying coastal areas in Australasia and Small Islands and smallholder farmers in Central and South America, Africa, Europe and Asia
have reached soft limits (medium confidence). Inequity and poverty also constrain adaptation, leading to soft limits and resulting in
disproportionate exposure and impacts for most vulnerable groups (high confidence). Lack of climate literacy46 at all levels and limited
availability of information and data pose further constraints to adaptation planning and implementation (medium confidence). {1.4, 4.7,
5.4, 8.4, Table 8.6, 9.1, 9.4, 9.5, 9.8, 11.7, 12.5 13.5, 15.3, 15.5, 15.6, 16.4, Box 16.1, Figure 16.8, CCP5.2, CCP5.4, CCP6.3}
C.3.2 Financial constraints are important determinants of soft limits to adaptation across sectors and all regions (high confidence). Although
global tracked climate finance has shown an upward trend since AR5, current global financial flows for adaptation, including from
public and private finance sources, are insufficient for and constrain implementation of adaptation options especially in developing
countries (high confidence). The overwhelming majority of global tracked climate finance was targeted to mitigation while a small
proportion was targeted to adaptation (very high confidence). Adaptation finance has come predominantly from public sources (very
high confidence). Adverse climate impacts can reduce the availability of financial resources by incurring losses and damages and
through impeding national economic growth, thereby further increasing financial constraints for adaptation, particularly for developing
and least developed countries (medium confidence). {Figure TS.7, 1.4, 2.6, 3.6, 4.7, Figure 4.30, 5.14, 7.4, 8.4, Table 8.6, 9.4, 9.9, 9.11,
10.5, 12.5, 13.3, 13.11, Box 14.4, 15.6, 16.2, 16.4, Figure 16.8, Table 16.4, 17.4, 18.1, CCP2.4, CCP5.4, CCP6.3, CCB FINANCE}
C.3.3 Many natural systems are near the hard limits of their natural adaptation capacity and additional systems will reach limits with
increasing global warming (high confidence). Ecosystems already reaching or surpassing hard adaptation limits include some warm-water
coral reefs, some coastal wetlands, some rainforests, and some polar and mountain ecosystems (high confidence). Above 1.5°C
global warming level, some Ecosystem-based Adaptation measures will lose their effectiveness in providing benefits to people as these
ecosystems will reach hard adaptation limits (high confidence). (Figure SPM.4) {1.4, 2.4, 2.6, 3.4, 3.6, 9.6, Box 11.2, 13.4, 14.5, 15.5,
16.4, 16.6, 17.2, CCP1.2, CCP5.2, CCP6.3, CCP7.3, CCB SLR}
C.3.4 In human systems, some coastal settlements face soft adaptation limits due to technical and financial difficulties of implementing
coastal protection (high confidence). Above 1.5°C global warming level, limited freshwater resources pose potential hard limits for
Small Islands and for regions dependent on glacier and snow-melt (medium confidence). By 2°C global warming level, soft limits are
projected for multiple staple crops in many growing areas, particularly in tropical regions (high confidence). By 3°C global warming
level, soft limits are projected for some water management measures for many regions, with hard limits projected for parts of Europe
(medium confidence). Transitioning from incremental to transformational adaptation can help overcome soft adaptation limits (high
confidence). {1.4, 4.7, 5.4, 5.8, 7.2, 7.3, 8.4, Table 8.6, 9.8, 10.4, 12.5, 13.2, 13.6, 16.4, 17.2, CCP1.3. Box CCP1.1, CCP2.3, CCP3.3,
CCP4.4, CCP5.3, CCB SLR}
C.3.5 Adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. Losses
and damages are unequally distributed across systems, regions and sectors and are not comprehensively addressed by current financial,
governance and institutional arrangements, particularly in vulnerable developing countries. With increasing global warming, losses and
damages increase and become increasingly difficult to avoid, while strongly concentrated among the poorest vulnerable populations.
(high confidence) {1.4, 2.6, 3.4, 3.6, 6.3, Figure 6.4, 8.4, 13.2, 13.7, 13.10, 17.2, CCP2.3, CCP4.4, CCB LOSS, CCB SLR, CWGB ECONOMIC}
27
SPM
Summary for Policymakers
Avoiding Maladaptation
47 From AR5, an option that would generate net social and/or economic benefits under current climate change and a range of future climate change scenarios, and represent one example of robust
strategies.
C.4 There is increased evidence of maladaptation15 across many sectors and regions since the AR5. Maladaptive responses
to climate change can create lock-ins of vulnerability, exposure and risks that are difficult and expensive to change and
exacerbate existing inequalities. Maladaptation can be avoided by flexible, multi-sectoral, inclusive and long-term planning
and implementation of adaptation actions with benefits to many sectors and systems. (high confidence) {1.3, 1.4,
2.6, Box 2.2, 3.2, 3.6, 4.6, 4.7, Box 4.3, Box 4.5, Figure 4.29, 5.6, 5.13, 8.2, 8.3, 8.4, 8.6, 9.6, 9.7, 9.8, 9.9, 9.10, 9.11, Box 9.5,
Box 9.8, Box 9.9, Box 11.6, 13.11, 13.3, 13.4, 13.5, 14.5, 15.5, 15.6, 16.3, 17.2, 17.3, 17.4, 17.5, 17.6, CCP2.3, CCP2.3,
CCP5.4, CCB DEEP, CCB NATURAL, CCB SLR, CWGB BIOECONOMY}
C.4.1 Actions that focus on sectors and risks in isolation and on short-term gains often lead to maladaptation if long-term impacts of
the adaptation option and long-term adaptation commitment are not taken into account (high confidence). The implementation of
these maladaptive actions can result in infrastructure and institutions that are inflexible and/or expensive to change (high confidence).
For example, seawalls effectively reduce impacts to people and assets in the short-term but can also result in lock-ins and increase
exposure to climate risks in the long-term unless they are integrated into a long-term adaptive plan (high confidence). Adaptation
integrated with development reduces lock-ins and creates opportunities (e.g., infrastructure upgrading) (medium confidence). {1.4, 3.4,
3.6, 10.4, 11.7, Box 11.6, 13.2, 17.2, 17.5, 17.6, CCP 2.3, CCB DEEP, CCB SLR}
C.4.2 Biodiversity and ecosystem resilience to climate change are decreased by maladaptive actions, which also constrain ecosystem
services. Examples of these maladaptive actions for ecosystems include fire suppression in naturally fire-adapted ecosystems or hard
defences against flooding. These actions reduce space for natural processes and represent a severe form of maladaptation for the
ecosystems they degrade, replace or fragment, thereby reducing their resilience to climate change and the ability to provide ecosystem
services for adaptation. Considering biodiversity and autonomous adaptation in long-term planning processes reduces the risk of
maladaptation. (high confidence) {2.4, 2.6, Table 2.7, 3.4, 3.6, 4.7, 5.6, 5.13, Table 5.21, Table 5.23, Box 11.2, 13.2, Box 13.2, 17.2, 17.5,
CCP5.4}
C.4.3 Maladaptation especially affects marginalised and vulnerable groups adversely (e.g., Indigenous Peoples, ethnic minorities, low-income
households, informal settlements), reinforcing and entrenching existing inequities. Adaptation planning and implementation that do not
consider adverse outcomes for different groups can lead to maladaptation, increasing exposure to risks, marginalising people from certain
socioeconomic or livelihood groups, and exacerbating inequity. Inclusive planning initiatives informed by cultural values, Indigenous
knowledge, local knowledge, and scientific knowledge can help prevent maladaptation. (high confidence) (Figure SPM.4) {2.6, 3.6, 4.3,
4.6, 4.8, 5.12, 5.13, 5.14, 6.1, Box 7.1, 8.4, 11.4, 12.5, Box 13.2, 14.4, Box 14.1, 17.2, 17.5, 18.2, 17.2, CCP2.4}
C.4.4 To minimize maladaptation, multi-sectoral, multi-actor and inclusive planning with flexible pathways encourages low-regret47 and
timely actions that keep options open, ensure benefits in multiple sectors and systems and indicate the available solution space for
adapting to long-term climate change (very high confidence). Maladaptation is also minimized by planning that accounts for the time it
takes to adapt (high confidence), the uncertainty about the rate and magnitude of climate risk (medium confidence) and a wide range
of potentially adverse consequences of adaptation actions (high confidence). {1.4, 3.6, 5.12, 5.13, 5.14, 11.6, 11.7, 17.3, 17.6, CCP2.3,
CCP2.4, CCP5.4, CCB DEEP, CCB SLR}
Enabling Conditions
C.5 Enabling conditions are key for implementing, accelerating and sustaining adaptation in human systems and ecosystems.
These include political commitment and follow-through, institutional frameworks, policies and instruments with clear
goals and priorities, enhanced knowledge on impacts and solutions, mobilization of and access to adequate financial resources,
monitoring and evaluation, and inclusive governance processes. (high confidence) {1.4, 2.6, 3.6, 4.8, 6.4, 7.4, 8.5,
9.4, 10.5, 11.4, 11.7, 12.5, 13.11, 14.7, 15.6, 17.4, 18.4, CCP2.4, CCP5.4, CCB FINANCE, CCB INDIG}
C.5.1 Political commitment and follow-through across all levels of government accelerate the implementation of adaptation actions
(high confidence). Implementing actions can require large upfront investments of human, financial and technological resources
(high confidence), whilst some benefits could only become visible in the next decade or beyond (medium confidence). Accelerating
commitment and follow-through is promoted by rising public awareness, building business cases for adaptation, accountability and
transparency mechanisms, monitoring and evaluation of adaptation progress, social movements, and climate-related litigation in some
regions (medium confidence). {3.6, 4.8, 5.8, 6.4, 8.5, 9.4, 11.7, 12.5, 13.11, 17.4, 17.5, 18.4, CCP2.4, CCB COVID}
28
SPM
Summary for Policymakers
C.5.2 Institutional frameworks, policies and instruments that set clear adaptation goals and define responsibilities and commitments and that
are coordinated amongst actors and governance levels, strengthen and sustain adaptation actions (very high confidence). Sustained
adaptation actions are strengthened by mainstreaming adaptation into institutional budget and policy planning cycles, statutory
planning, monitoring and evaluation frameworks and into recovery efforts from disaster events (high confidence). Instruments that
incorporate adaptation such as policy and legal frameworks, behavioural incentives, and economic instruments that address market
failures, such as climate risk disclosure, inclusive and deliberative processes strengthen adaptation actions by public and private actors
(medium confidence). {1.4, 3.6, 4.8, 5.14, 6.3, 6.4, 7.4, 9.4, 10.4, 11.7, Box 11.6, Table 11.17, 13.10, 13.11, 14.7, 15.6, 17.3, 17.4, 17.5,
17.6, 18.4, CCP2.4, CCP5.4, CCP6.3, CCB DEEP}
C.5.3 Enhancing knowledge on risks, impacts, and their consequences, and available adaptation options promotes societal and policy
responses (high confidence). A wide range of top-down, bottom-up and co-produced processes and sources can deepen climate
knowledge and sharing, including capacity building at all scales, educational and information programmes, using the arts, participatory
modelling and climate services, Indigenous knowledge and local knowledge and citizen science (high confidence). These measures can
facilitate awareness, heighten risk perception and influence behaviours (high confidence). {1.3, 3.6, 4.8, 5.9, 5.14, 6.4, Table 6.8, 7.4,
9.4, 10.5, 11.1, 11.7, 12.5, 13.9, 13.11, 14.3, 15.6, 15.6, 17.4, 18.4, CCP2.4.1, CCB INDIG}
C.5.4 With adaptation finance needs estimated to be higher than those presented in AR5, enhanced mobilization of and access to financial
resources are essential for implementation of adaptation and to reduce adaptation gaps (high confidence). Building capacity and
removing some barriers to accessing finance is fundamental to accelerate adaptation, especially for vulnerable groups, regions and
sectors (high confidence). Public and private finance instruments include inter alia grants, guarantee, equity, concessional debt,
market debt, and internal budget allocation as well as savings in households and insurance. Public finance is an important enabler
of adaptation (high confidence). Public mechanisms and finance can leverage private sector finance for adaptation by addressing
real and perceived regulatory, cost and market barriers, for example via public-private partnerships (high confidence). Financial and
technological resources enable effective and ongoing implementation of adaptation, especially when supported by institutions with a
strong understanding of adaptation needs and capacity (high confidence). {4.8, 5.14, 6.4, Table 6.10, 7.4, 9.4, Table 11.17, 12.5, 13.11,
15.6, 17.4, 18.4, Box 18.9, CCP5.4, CCB FINANCE}
C.5.5 Monitoring and evaluation (M&E) of adaptation are critical for tracking progress and enabling effective adaptation (high confidence).
M&E implementation is currently limited (high confidence) but has increased since AR5 at local and national levels. Although most of
the monitoring of adaptation is focused towards planning and implementation, the monitoring of outcomes is critical for tracking the
effectiveness and progress of adaptation (high confidence). M&E facilitates learning on successful and effective adaptation measures,
and signals when and where additional action may be needed. M&E systems are most effective when supported by capacities and
resources and embedded in enabling governance systems (high confidence). {1.4, 2.6, 6.4, 7.4, 11.7, 11.8, 13.2, 13.11, 17.5, 18.4,
CCP2.4, CCB DEEP, CCB ILLNESS, CCB NATURAL, CCB PROGRESS}
C.5.6 Inclusive governance that prioritises equity and justice in adaptation planning and implementation leads to more effective and
sustainable adaptation outcomes (high confidence). Vulnerabilities and climate risks are often reduced through carefully designed and
implemented laws, policies, processes, and interventions that address context specific inequities such as based on gender, ethnicity,
disability, age, location and income (high confidence). These approaches, which include multi-stakeholder co-learning platforms,
transboundary collaborations, community-based adaptation and participatory scenario planning, focus on capacity-building, and
meaningful participation of the most vulnerable and marginalised groups, and their access to key resources to adapt (high confidence).
{1.4, 2.6, 3.6, 4.8, 5.4, 5.8, 5.9, 5.13, 6.4, 7.4, 8.5, 11.8, 12.5, 13.11, 14.7, 15.5, 15.7, 17.3, 17.5, 18.4, CCP2.4, CCP5.4, CCP6.4, CCB
GENDER, CCB HEALTH, CCB INDIG}
D: Climate Resilient Development
Climate resilient development integrates adaptation measures and their enabling conditions (Section C) with mitigation to advance sustainable
development for all. Climate resilient development involves questions of equity and system transitions in land, ocean and ecosystems; urban
and infrastructure; energy; industry; and society and includes adaptations for human, ecosystem and planetary health. Pursuing climate resilient
development focuses on both where people and ecosystems are co-located as well as the protection and maintenance of ecosystem function at
the planetary scale. Pathways for advancing climate resilient development are development trajectories that successfully integrate mitigation and
adaptation actions to advance sustainable development. Climate resilient development pathways may be temporarily coincident with any RCP
and SSP scenario used throughout AR6, but do not follow any particular scenario in all places and over all time.
29
SPM
Summary for Policymakers
Conditions for Climate Resilient Development
D.1 Evidence of observed impacts, projected risks, levels and trends in vulnerability, and adaptation limits, demonstrate that
worldwide climate resilient development action is more urgent than previously assessed in AR5. Comprehensive, effective,
and innovative responses can harness synergies and reduce trade-offs between adaptation and mitigation to advance
sustainable development. (very high confidence) {2.6, 3.4, 3.6, 4.2, 4.6, 7.2, 7.4, 8.3, 8.4, 9.3, 10.6, 13.3, 13.8, 13.10, 14.7,
17.2, 18.3, Box 18.1, Figure 18.1, Table 18.5}
D.1.1 There is a rapidly narrowing window of opportunity to enable climate resilient development. Multiple climate resilient development
pathways are still possible by which communities, the private sector, governments, nations and the world can pursue climate resilient
development – each involving and resulting from different societal choices influenced by different contexts and opportunities and
constraints on system transitions. Climate resilient development pathways are progressively constrained by every increment of
warming, in particular beyond 1.5°C, social and economic inequalities, the balance between adaptation and mitigation varying by
national, regional and local circumstances and geographies, according to capabilities including resources, vulnerability, culture and
values, past development choices leading to past emissions and future warming scenarios, bounding the climate resilient development
pathways remaining, and the ways in which development trajectories are shaped by equity, and social and climate justice. (very high
confidence) {Figure TS.14d, 2.6, 4.7, 4.8, 5.14, 6.4, 7.4, 8.3, 9.4, 9.3, 9.4, 9.5, 10.6, 11.8, 12.5, 13.10, 14.7, 15.3, 18.5, CCP2.3, CCP3.4,
CCP4.4, CCP5.3, CCP5.4, Table CCP5.2, CCP6.3, CCP7.5}
D.1.2 Opportunities for climate resilient development are not equitably distributed around the world (very high confidence). Climate impacts
and risks exacerbate vulnerability and social and economic inequities and consequently increase persistent and acute development
challenges, especially in developing regions and sub-regions, and in particularly exposed sites, including coasts, small islands, deserts,
mountains and polar regions. This in turn undermines efforts to achieve sustainable development, particularly for vulnerable and
marginalized communities (very high confidence). {2.5, 4.4, 4.7, 6.3, Box 6.4, Figure 6.5, 9.4, Table 18.5, CCP2.2, CCP3.2, CCP3.3,
CCP5.4, CCP6.2, CCB HEALTH, CWGB URBAN}
D.1.3 Embedding effective and equitable adaptation and mitigation in development planning can reduce vulnerability, conserve and restore
ecosystems, and enable climate resilient development. This is especially challenging in localities with persistent development gaps
and limited resources (high confidence). Dynamic trade-offs and competing priorities exist between mitigation, adaptation, and
development. Integrated and inclusive system-oriented solutions based on equity and social and climate justice reduce risks and enable
climate resilient development (high confidence). {1.4, 2.6, Box 2.2, 3.6, 4.7, 4.8, Box 4.5, Box 4.8, 5.13, 7.4, 8.5, 9.4, Box 9.3, 10.6, 12.5,
12.6, 13.3, 13.4, 13.10, 13.11, 14.7, 18.4, CCB DEEP, CCP2, CCP5.4, CCB HEALTH, SRCCL}
Enabling Climate Resilient Development
D.2 Climate resilient development is enabled when governments, civil society and the private sector make inclusive development
choices that prioritise risk reduction, equity and justice, and when decision-making processes, finance and
actions are integrated across governance levels, sectors and timeframes (very high confidence). Climate resilient development
is facilitated by international cooperation and by governments at all levels working with communities, civil
society, educational bodies, scientific and other institutions, media, investors and businesses; and by developing partnerships
with traditionally marginalised groups, including women, youth, Indigenous Peoples, local communities and ethnic
minorities (high confidence). These partnerships are most effective when supported by enabling political leadership,
institutions, resources, including finance, as well as climate services, information and decision support tools (high confidence).
(Figure SPM.5) {1.3, 1.4, 1.5, 2.7, 3.6, 4.8, 5.14, 6.4, 7.4, 8.5, 8.6, 9.4, 10.6, 11.8, 12.5, 13.11, 14.7, 15.6, 15.7, 17.4,
17.6, 18.4, 18.5, CCP2.4, CCP3.4, CCP4.4, CCP5.4, CCP6.4, CCP7.6, CCB DEEP, CCB GENDER, CCB HEALTH, CCB INDIG, CCB
NATURAL, CCB SLR}
D.2.1 Climate resilient development is advanced when actors work in equitable, just and enabling ways to reconcile divergent interests, values
and worldviews, toward equitable and just outcomes (high confidence). These practices build on diverse knowledges about climate
risk and chosen development pathways account for local, regional and global climate impacts, risks, barriers and opportunities (high
confidence). Structural vulnerabilities to climate change can be reduced through carefully designed and implemented legal, policy, and
process interventions from the local to global that address inequities based on gender, ethnicity, disability, age, location and income
(very high confidence). This includes rights-based approaches that focus on capacity-building, meaningful participation of the most
vulnerable groups, and their access to key resources, including financing, to reduce risk and adapt (high confidence). Evidence shows that
climate resilient development processes link scientific, Indigenous, local, practitioner and other forms of knowledge, and are more effective
and sustainable because they are locally appropriate and lead to more legitimate, relevant and effective actions (high confidence).
30
SPM
Summary for Policymakers
There is a rapidly narrowing window of opportunity to enable climate resilient development
(a) Societal choices about adaptation,
mitigation and sustainable development
made in arenas of engagement
2022
2100 &
beyond
IPCC
AR6
Present
situation
Sustainable
Development Goals
2030
(b) Illustrative development pathways
Illustrative climatic or non-climatic shock, e.g. COVID-19, drought or floods, that disrupts the development pathway
Past conditions
(emissions,
climate change,
development)
Warming limited to below 1.5°C;
adaptation enables
sustainable development
LOWER CLIMATE RESILIENT DEVELOPMENT HIGHER
(c) Actions and outcomes
characterizing development pathways
Opportunities missed for higher climate resilient development
Well-being
Low poverty
Ecosystem health
Equity and justice
Low global
warming levels
Low risk
Vulnerability
High poverty
Ecosystem degradation
Inequity and injustice
High global
warming levels
High risk
Sustainable development action System transitions Transformation
Adaptation Mitigation
Unsustainable development action Entrenched systems
Maladaptation Rising emissions
Narrowing window of
opportunity for higher CRD
Dimensions that enable actions towards
higher climate resilient development
Dimensions that result in actions tow ards
lower climate resilient development
Arenas of engagement:
Community
Socio-cultural
Political
Ecological
Knowledge + technology
Economic + financial
Equity and justice Inclusion
Arenas of engagement
Arenas of engagement
Ecosystem stewardship Knowledge diversity
Exclusion Inequity and injustice
Ecosystem degradation Singular knowledge
Increasing warming; path dependence and adaptation limits
undermine sustainable development
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31
SPM
Summary for Policymakers
Pathways towards climate resilient development overcome jurisdictional and organizational barriers, and are founded on societal
choices that accelerate and deepen key system transitions (very high confidence). Planning processes and decision analysis tools
can help identify ‘low regrets’ options47 that enable mitigation and adaptation in the face of change, complexity, deep uncertainty
and divergent views (medium confidence). {1.3, 1.4, 1.5, 2.7, 3.6, 4.8, 5.14, 6.4, 7.4, 8.5, 8.6, Box 8.7, 9.4, Box 9.2, 10.6, 11.8, 12.5,
13.11, 14.7, 15.6, 15.7, 17.2–17.6, 18.2–18.4, CCP2.3–2.4, CCP3.4, CCP4.4, CCP5.4, CCP6.4, CCP7.6, CCB DEEP, CCB HEALTH, CCB
INDIG, CCB NATURAL, CCB SLR}
D.2.2 Inclusive governance contributes to more effective and enduring adaptation outcomes and enables climate resilient development (high
confidence). Inclusive processes strengthen the ability of governments and other stakeholders to jointly consider factors such as the rate
and magnitude of change and uncertainties, associated impacts, and timescales of different climate resilient development pathways
given past development choices leading to past emissions and scenarios of future global warming (high confidence). Associated
societal choices are made continuously through interactions in arenas of engagement from local to international levels. The quality
and outcome of these interactions helps determine whether development pathways shift towards or away from climate resilient
development (medium confidence). (Figure SPM.5) {2.7, 3.6, 4.8, 5.14, 6.4, 7.4, 8.5, 8.6, 9.4, 10.6, 11.8, 12.5, 13.11, 14.7, 15.6, 15.7,
17.2–17.6, 18.2, 18.4, CCP2.3–2.4, CCP3.4, CCP4.4, CCP5.4, CCP6.4, CCP7.6, CCB GENDER, CCB HEALTH, CCB INDIG}
D.2.3 Governance for climate resilient development is most effective when supported by formal and informal institutions and practices that
are well-aligned across scales, sectors, policy domains and timeframes. Governance efforts that advance climate resilient development
account for the dynamic, uncertain and context-specific nature of climate-related risk, and its interconnections with non-climate
risks. Institutions48 that enable climate resilient development are flexible and responsive to emergent risks and facilitate sustained
and timely action. Governance for climate resilient development is enabled by adequate and appropriate human and technological
resources, information, capacities and finance. (high confidence) {2.7, 3.6, 4.8, 5.14, 6.3, 6.4, 7.4, 8.5, 8.6, 9.4, 10.6, 11.8, 12.5, 13.11,
14.7, 15.6, 15.7, 17.2-17.6, 18.2, 18.4, CCP2.3–2.4, CCP3.4, CCP4.4, CCP5.4, CCP6.4, CCP7.6, CCB DEEP, CCB GENDER, CCB HEALTH,
CCB INDIG, CCB NATURAL, CCB SLR}
Climate Resilient Development for Natural and Human Systems
48 Institutions: Rules, norms and conventions that guide, constrain or enable human behaviours and practices. Institutions can be formally established, for instance through laws and regulations, or
informally established, for instance by traditions or customs. Institutions may spur, hinder, strengthen, weaken or distort the emergence, adoption and implementation of climate action and climate
governance.
D.3 Interactions between changing urban form, exposure and vulnerability can create climate change-induced risks and losses
for cities and settlements. However, the global trend of urbanisation also offers a critical opportunity in the near-term,
to advance climate resilient development (high confidence). Integrated, inclusive planning and investment in everyday
decision-making about urban infrastructure, including social, ecological and grey/physical infrastructures, can significantly
increase the adaptive capacity of urban and rural settlements. Equitable outcomes contributes to multiple benefits for
health and well-being and ecosystem services, including for Indigenous Peoples, marginalised and vulnerable communities
(high confidence). Climate resilient development in urban areas also supports adaptive capacity in more rural places
through maintaining peri-urban supply chains of goods and services and financial flows (medium confidence). Coastal
cities and settlements play an especially important role in advancing climate resilient development (high confidence).
{6.2, 6.3, Table 6.6, 7.4, 8.6, Box 9.8, 18.3, CCP2.1. CCP2.2, CCP6.2, CWGB URBAN}
Figure SPM.5 | Climate resilient development (CRD) is the process of implementing greenhouse gas mitigation and adaptation measures to support sustainable
development. This figure builds on Figure SPM.9 in AR5 WGII (depicting climate resilient pathways) by describing how CRD pathways are the result of cumulative societal choices
and actions within multiple arenas.
Panel (a) Societal choices towards higher CRD (green cog) or lower CRD (red cog) result from interacting decisions and actions by diverse government, private sector
and civil society actors, in the context of climate risks, adaptation limits and development gaps. These actors engage with adaptation, mitigation and development actions in
political, economic and financial, ecological, socio-cultural, knowledge and technology, and community arenas from local to international levels. Opportunities for climate resilient
development are not equitably distributed around the world.
Panel (b) Cumulatively, societal choices, which are made continuously, shift global development pathways towards higher (green) or lower (red) climate resilient development.
Past conditions (past emissions, climate change and development) have already eliminated some development pathways towards higher CRD (dashed green line).
Panel (c) Higher CRD is characterised by outcomes that advance sustainable development for all. Climate resilient development is progressively harder to achieve with global
warming levels beyond 1.5°C. Inadequate progress towards the Sustainable Development Goals (SDGs) by 2030 reduces climate resilient development prospects. There is a
narrowing window of opportunity to shift pathways towards more climate resilient development futures as reflected by the adaptation limits and increasing climate risks, considering
the remaining carbon budgets. (Figure SPM.2, Figure SPM.3) {Figure TS.14b, 2.6, 3.6, 7.2, 7.3, 7.4, 8.3, 8.4, 8.5, 16.4, 16.5, 17.3, 17.4, 17.5, 18.1, 18.2, 18.3, 18.4, Box 18.1,
Figure 18.1, Figure 18.2, Figure 18.3, CCB COVID, CCB GENDER, CCB HEALTH, CCB INDIG, CCB SLR, WGI AR6 Table SPM.1, WGI AR6 Table SPM.2, SR1.5 Figure SPM.1}
32
SPM
Summary for Policymakers
D.3.1 Taking integrated action for climate resilience to avoid climate risk requires urgent decision making for the new built environment
and retrofitting existing urban design, infrastructure and land use. Based on socioeconomic circumstances, adaptation and
sustainable development actions will provide multiple benefits including for health and well-being, particularly when supported by
national governments, non-governmental organisations and international agencies that work across sectors in partnerships with
local communities. Equitable partnerships between local and municipal governments, the private sector, Indigenous Peoples, local
communities, and civil society can, including through international cooperation, advance climate resilient development by addressing
structural inequalities, insufficient financial resources, cross-city risks and the integration of Indigenous knowledge and local
knowledge. (high confidence) {6.2, 6.3, 6.4, Table 6.6, 7.4, 8.5, 9.4, 10.5. 12.5, 17.4, Table 17.8, 18.2, Box 18.1, CCP2.4, CCB FINANCE,
CCB GENDER, CCB INDIG, CWGB URBAN}
D.3.2 Rapid global urbanisation offers opportunities for climate resilient development in diverse contexts from rural and informal settlements
to large metropolitan areas (high confidence). Dominant models of energy intensive and market-led urbanisation, insufficient and
misaligned finance and a predominant focus on grey infrastructure in the absence of integration with ecological and social approaches,
risks missing opportunities for adaptation and locking in maladaptation (high confidence). Poor land use planning and siloed approaches
to health, ecological and social planning also exacerbates, vulnerability in already marginalised communities (medium confidence).
Urban climate resilient development is observed to be more effective if it is responsive to regional and local land use development
and adaptation gaps, and addresses the underlying drivers of vulnerability (high confidence). The greatest gains in well-being can be
achieved by prioritizing finance to reduce climate risk for low-income and marginalized residents including people living in informal
settlements (high confidence). {5.14, 6.1, 6.2, 6.3, 6.4, 6.5, Figure 6.5, Table 6.6, 7.4, 8.5, 8.6, 9.8, 9.9, 10.4, Table 17.8, 18.2, CCP2.2,
CCP5.4, CCB HEALTH, CWGB URBAN}
D.3.3 Urban systems are critical, interconnected sites for enabling climate resilient development, especially at the coast. Coastal cities and
settlements play a key role in moving toward higher climate resilient development given firstly, almost 11% of the global population –
896 million people – lived within the Low Elevation Coastal Zone49 in 2020, potentially increasing to beyond 1 billion people by 2050,
and these people, and associated development and coastal ecosystems, face escalating climate compounded risks, including sea level
rise. Secondly, these coastal cities and settlements make key contributions to climate resilient development through their vital role in
national economies and inland communities, global trade supply chains, cultural exchange, and centres of innovation. (high confidence)
{6.1, 6.2, 6.4, Table 6.6, Box 15.2, SMCCP Table 2.1, CCP2.2, CCP2.4, CCB SLR, XWGB URBAN, SROCC Chapter 4}
49 LECZ, coastal areas below 10 m of elevation above sea level that are hydrologically connected to the sea.
50 Ecosystem integrity refers to the ability of ecosystems to maintain key ecological processes, recover from disturbance, and adapt to new conditions.
D.4 Safeguarding biodiversity and ecosystems is fundamental to climate resilient development, in light of the threats climate
change poses to them and their roles in adaptation and mitigation (very high confidence). Recent analyses, drawing on a
range of lines of evidence, suggest that maintaining the resilience of biodiversity and ecosystem services at a global scale
depends on effective and equitable conservation of approximately 30% to 50% of Earth’s land, freshwater and ocean
areas, including currently near-natural ecosystems (high confidence). {2.4, 2.5, 2.6, 3.4, 3.5, 3.6, Box 3.4, 12.5, 13.3, 13.4,
13.5, 13.10, CCB INDIG, CCB NATURAL}
D.4.1 Building the resilience of biodiversity and supporting ecosystem integrity50 can maintain benefits for people, including livelihoods,
human health and well-being and the provision of food, fibre and water, as well as contributing to disaster risk reduction and climate
change adaptation and mitigation. {2.2, 2.5, 2.6, Table 2.6, Table 2.7, 3.5, 3.6, 5.8, 5.13, 5.14, Box 5.11, 12.5, CCP5.4, CCB COVID, CCB
GENDER, CCB ILLNESS, CCB INDIG, CCB MIGRATE, CCB NATURAL}
D.4.2 Protecting and restoring ecosystems is essential for maintaining and enhancing the resilience of the biosphere (very high
confidence). Degradation and loss of ecosystems is also a cause of greenhouse gas emissions and is at increasing risk of being
exacerbated by climate change impacts, including droughts and wildfire (high confidence). Climate resilient development
avoids adaptation and mitigation measures that damage ecosystems (high confidence). Documented examples of adverse impacts of
land-based measures intended as mitigation, when poorly implemented, include afforestation of grasslands, savannas and peatlands,
and risks from bioenergy crops at large scale to water supply, food security and biodiversity (high confidence). {2.4, 2.5, Box 2.2, 3.4,
3.5, Box 3.4, Box 9.3, CCP7.3, CCB NATURAL, CWGB BIOECONOMY}
33
SPM
Summary for Policymakers
D.4.3 Biodiversity and ecosystem services have limited capacity to adapt to increasing global warming levels, which will make climate resilient
development progressively harder to achieve beyond 1.5°C warming (very high confidence). Consequences of current and future
global warming for climate resilient development include reduced effectiveness of Ecosystem-based Adaptation and approaches to
climate change mitigation based on ecosystems and amplifying feedbacks to the climate system (high confidence). {Figure TS.14d, 2.4,
2.5, 2.6, 3.4, Box 3.4, 3.5, 3.6, Table 5.2, 12.5, 13.2, 13.3, 13.10, 14.5, 14.5, Box 14.3, 15.3, 17.3, 17.6, CCP5.3, CCP5.4, CCB EXTREMES,
CCB ILLNESS, CCB NATURAL, CCB SLR, SR1.5, SRCCL, SROCC}
Achieving Climate Resilient Development
D.5 It is unequivocal that climate change has already disrupted human and natural systems. Past and current development
trends (past emissions, development and climate change) have not advanced global climate resilient development (very
high confidence). Societal choices and actions implemented in the next decade determine the extent to which mediumand
long-term pathways will deliver higher or lower climate resilient development (high confidence). Importantly climate
resilient development prospects are increasingly limited if current greenhouse gas emissions do not rapidly decline, especially
if 1.5°C global warming is exceeded in the near-term (high confidence). These prospects are constrained by past
development, emissions and climate change, and enabled by inclusive governance, adequate and appropriate human and
technological resources, information, capacities and finance (high confidence). {Figure TS.14d, 1.2, 1.4, 1.5, 2.6, 2.7, 3.6,
4.7, 4.8, 5.14, 6.4, 7.4, 8.3, 8.5, 8.6, 9.3, 9.4, 9.5, 10.6, 11.8, 12.5, 13.10, 13.11, 14.7, 15.3, 15.6, 15.7, 16.2, 16.4, 16.5, 16.6,
17.2–17.6, 18.2–18.5, CCP2.3–2.4, CCP3.4, CCP4.4, CCP5.3, CCP5.4, Table CCP5.2, CCP6.3, CCP6.4, CCP7.5, CCP7.6, CCB
DEEP, CCB HEALTH, CCB INDIG, CCB NATURAL, CCB SLR}
D.5.1 Climate resilient development is already challenging at current global warming levels (high confidence). The prospects for climate
resilient development will be further limited if global warming levels exceeds 1.5°C (high confidence) and not be possible in some
regions and sub-regions if the global warming level exceeds 2°C (medium confidence). Climate resilient development is most
constrained in regions/subregions in which climate impacts and risks are already advanced, including low-lying coastal cities and
settlements, small islands, deserts, mountains and polar regions (high confidence). Regions and subregions with high levels of poverty,
water, food and energy insecurity, vulnerable urban environments, degraded ecosystems and rural environments, and/or few enabling
conditions, face many non-climate challenges that inhibit climate resilient development which are further exacerbated by climate
change (high confidence). {Figure TS.14d, 1.2, Box 6.6, 9.3, 9.4, 9.5, 10.6, 11.8, 12.5, 13.10, 14.7, 15.3, CCP2.3, CCP3.4, CCP4.4, CCP5.3,
Table CCP5.2, CCP6.3, CCP7.5}
D.5.2 Inclusive governance, investment aligned with climate resilient development, access to appropriate technology and rapidly
scaled-up finance, and capacity building of governments at all levels, the private sector and civil society enable climate resilient
development. Experience shows that climate resilient development processes are timely, anticipatory, integrative, flexible and action
focused. Common goals and social learning build adaptive capacity for climate resilient development. When implementing adaptation
and mitigation together, and taking trade-offs into account, multiple benefits and synergies for human well-being as well as ecosystem
and planetary health can be realised. Prospects for climate resilient development are increased by inclusive processes involving local
knowledge and Indigenous Knowledge as well as processes that coordinate across risks and institutions. Climate resilient development
is enabled by increased international cooperation including mobilising and enhancing access to finance, particularly for vulnerable
regions, sectors and groups. (high confidence) (Figure SPM.5) {2.7, 3.6, 4.8, 5.14, 6.4, 7.4, 8.5, 8.6, 9.4, 10.6, 11.8, 12.5, 13.11, 14.7,
15.6, 15.7, 17.2–17.6, 18.2–18.5, CCP2.3–2.4, CCP3.4, CCP4.4, CCP5.4, CCP6.4, CCP7.6, CCB DEEP, CCB HEALTH, CCB INDIG, CCB
NATURAL, CCB SLR}
D.5.3 The cumulative scientific evidence is unequivocal: Climate change is a threat to human well-being and planetary health. Any further
delay in concerted anticipatory global action on adaptation and mitigation will miss a brief and rapidly closing window of opportunity
to secure a liveable and sustainable future for all. (very high confidence) {1.2, 1.4, 1.5, 16.2, Table SM16.24, 16.4, 16.5, 16.6, 17.4, 17.5,
17.6, 18.3, 18.4, 18.5, CCB DEEP, CWGB URBAN, WGI AR6 SPM, SROCC SPM, SRCCL SPM}
i
WGIII
Mitigation of Climate Change
Summary for Policymakers
Climate Change 2022
Working Group III contribution to the
Sixth Assessment Report of the
Intergovernmental Panel on Climate Change
[I'IIIIIE.'ILL'III'I.TwTz.A 'RIIHT EDI[HHE]EE
Front cover photograph: Matt Bridgestock, Director and Architect at John Gilbert Architects
All International Energy Agency (IEA) Data, IEA Further Data and Derived Data has been
sourced from https://www.iea.org/data-and-statistics.
© 2022 Intergovernmental Panel on Climate Change.
Electronic copies of this Summary for Policymakers are available from the IPCC website www.ipcc.ch
ISBN 978-92-9169-160-9
Summary for
Policymakers
SPM
3
Summary for
Policymakers
Drafting Authors:
Jim Skea (United Kingdom), Priyadarshi R. Shukla (India), Andy Reisinger (New Zealand),
Raphael Slade (United Kingdom), Minal Pathak (India), Alaa Al Khourdajie (United Kingdom/Syria),
Renée van Diemen (the Netherlands/United Kingdom), Amjad Abdulla (Maldives), Keigo Akimoto
(Japan), Mustafa Babiker (Sudan/Saudi Arabia), Quan Bai (China), Igor A. Bashmakov (the Russian
Federation), Christopher Bataille (Canada), Göran Berndes (Sweden), Gabriel Blanco (Argentina),
Kornelis Blok (the Netherlands), Mercedes Bustamante (Brazil), Edward Byers (Austria/Ireland),
Luisa F. Cabeza (Spain), Katherine Calvin (the United States of America), Carlo Carraro (Italy),
Leon Clarke (the United States of America), Annette Cowie (Australia), Felix Creutzig (Germany),
Diriba Korecha Dadi (Ethiopia), Dipak Dasgupta (India), Heleen de Coninck (the Netherlands),
Fatima Denton (the Gambia), Shobhakar Dhakal (Nepal/Thailand), Navroz K. Dubash (India),
Oliver Geden (Germany), Michael Grubb (United Kingdom), Céline Guivarch (France),
Shreekant Gupta (India), Andrea N. Hahmann (Chile/Denmark), Kirsten Halsnaes (Denmark),
Paulina Jaramillo (the United States of America), Kejun Jiang (China), Frank Jotzo (Australia),
Tae Yong Jung (Republic of Korea), Suzana Kahn Ribeiro (Brazil), Smail Khennas (Algeria),
Şiir Kılkış (Turkey), Silvia Kreibiehl (Germany), Volker Krey (Germany/Austria), Elmar
Kriegler (Germany), William F. Lamb (Germany/United Kingdom), Franck Lecocq (France),
Shuaib Lwasa (Uganda), Nagmeldin Mahmoud (Sudan), Cheikh Mbow (Senegal), David
McCollum (the United States of America), Jan Christoph Minx (Germany), Catherine
Mitchell (United Kingdom), Rachid Mrabet (Morocco), Yacob Mulugetta (Ethiopia/
United Kingdom), Gert-Jan Nabuurs (the Netherlands), Gregory F. Nemet (the United States
of America/Canada), Peter Newman (Australia), Leila Niamir (Iran/Germany), Lars J. Nilsson
(Sweden), Sudarmanto Budi Nugroho (Indonesia), Chukwumerije Okereke (Nigeria/
United Kingdom), Shonali Pachauri (India), Anthony Patt (Switzerland), Ramón Pichs-Madruga
(Cuba), Joana Portugal-Pereira (Brazil), Lavanya Rajamani (India), Keywan Riahi (Austria),
Joyashree Roy (India/Thailand), Yamina Saheb (France/Algeria), Roberto Schaeffer (Brazil),
Karen C. Seto (the United States of America), Shreya Some (India), Linda Steg (the Netherlands),
Ferenc L. Toth (Austria/Hungary), Diana Ürge-Vorsatz (Hungary), Detlef P. van Vuuren
(the Netherlands), Elena Verdolini (Italy), Purvi Vyas (India), Yi-Ming Wei (China), Mariama
Williams (Jamaica/the United States of America), Harald Winkler (South Africa).
Contributing Authors:
Parth Bhatia (India), Sarah Burch (Canada), Jeremy Emmet-Booth (New Zealand),
Jan S. Fuglestvedt (Norway), Meredith Kelller (the United States of America), Jarmo Kikstra
(Austria/the Netherlands), Michael König (Germany), Malte Meinshausen (Australia/Germany),
Zebedee Nicholls (Australia), Kaj-Ivar van der Wijst (the Netherlands).
This Summary for Policymakers should be cited as:
IPCC, 2022: Summary for Policymakers. In: Climate Change 2022: Mitigation of Climate Change. Contribution of
Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla,
J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi,
A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY,
USA. doi: 10.1017/9781009157926.001
4
SPM
Summary for Policymakers
A. Introduction and Framing
1 The Report covers literature accepted for publication by 11 October 2021.
2 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers, typeset in italics: very low,
low, medium, high and very high. The assessed likelihood of an outcome or a result is described as: virtually certain 99–100% probability; very likely 90–100%; likely
66–100%; more likely than not 50–100%; about as likely as not 33–66%; unlikely 0–33%; very unlikely 0–10%; exceptionally unlikely 0–1%. Additional terms may
also be used when appropriate, consistent with the IPCC uncertainty guidance: https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf.
3 The three Special Reports are: Global Warming of 1.5°C: an IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related
global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts
to eradicate poverty (2018); Climate Change and Land: an IPCC Special Report on climate change, desertification, land degradation, sustainable land management,
food security, and greenhouse gas fluxes in terrestrial ecosystems (2019); IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (2019).
4 The term ‘temperature’ is used in reference to 'global surface temperatures' throughout this SPM as defined in footnote 8 of the AR6 WGI SPM (see note 14 of Table
SPM.2). Emission pathways and associated temperature changes are calculated using various forms of models, as summarised in Box SPM.1 and Chapter 3, and
discussed in Annex III.
5 Namely: Economic Benefits from Avoided Climate Impacts along Long-Term Mitigation Pathways {Cross-Working Group Box 1 in Chapter 3}; Urban: Cities and
Climate Change {Cross-Working Group Box 2 in Chapter 8}; and Mitigation and Adaptation via the Bioeconomy {Cross-Working Group Box 3 in Chapter 12}.
The Working Group III (WGIII) contribution to the IPCC’s Sixth Assessment Report (AR6) assesses literature on the scientific, technological,
environmental, economic and social aspects of mitigation of climate change.1 Levels of confidence2 are given in () brackets. Numerical
ranges are presented in square [] brackets. References to Chapters, Sections, Figures and Boxes in the underlying report and Technical
Summary (TS) are given in {} brackets.
The report reflects new findings in the relevant literature and builds on previous IPCC reports, including the WGIII contribution to the
IPCC’s Fifth Assessment Report (AR5), the WGI and WGII contributions to AR6 and the three Special Reports in the Sixth Assessment
cycle,3 as well as other UN assessments. Some of the main developments relevant for this report include {TS.1, TS.2}:
• An evolving international landscape. The literature reflects, among other factors: developments in the UN Framework Convention
on Climate Change (UNFCCC) process, including the outcomes of the Kyoto Protocol and the adoption of the Paris Agreement
{13, 14, 15, 16}; the UN 2030 Agenda for Sustainable Development including the Sustainable Development Goals (SDGs) {1, 3, 4, 17};
and the evolving roles of international cooperation {14}, finance {15} and innovation {16}.
• Increasing diversity of actors and approaches to mitigation. Recent literature highlights the growing role of non-state and
sub-national actors including cities, businesses, Indigenous Peoples, citizens including local communities and youth, transnational
initiatives, and public-private entities in the global effort to address climate change {5, 13, 14, 15, 16, 17}. Literature documents the
global spread of climate policies and cost declines of existing and emerging low emission technologies, along with varied types and
levels of mitigation efforts, and sustained reductions in greenhouse gas (GHG) emissions in some countries {2, 5, 6, 8, 12, 13, 16},
and the impacts of, and some lessons from, the COVID-19 pandemic. {1, 2, 3, 5, 13, 15, Box TS.1, Cross-Chapter Box 1 in Chapter 1}
• Close linkages between climate change mitigation, adaptation and development pathways. The development pathways
taken by countries at all stages of economic development impact GHG emissions and hence shape mitigation challenges and
opportunities, which vary across countries and regions. Literature explores how development choices and the establishment of
enabling conditions for action and support influence the feasibility and the cost of limiting emissions {1, 3, 4, 5, 13, 15, 16}.
Literature highlights that climate change mitigation action designed and conducted in the context of sustainable development,
equity, and poverty eradication, and rooted in the development aspirations of the societies within which they take place, will be
more acceptable, durable and effective {1, 3, 4, 5}. This report covers mitigation from both targeted measures, and from policies and
governance with other primary objectives.
• New approaches in the assessment. In addition to the sectoral and systems chapters {3, 6, 7, 8, 9, 10, 11, 12}, the report includes,
for the first time in a WGIII report, chapters dedicated to demand for services, and social aspects of mitigation {5, Box TS.11},
and to innovation, technology development and transfer {16}. The assessment of future pathways in this report covers near term
(to 2030), medium term (up to 2050), and long term (to 2100) time scales, combining assessment of existing pledges and actions
{4, 5}, with an assessment of emissions reductions, and their implications, associated with long-term temperature outcomes up
to the year 2100 {3}.4 The assessment of modelled global pathways addresses ways of shifting development pathways towards
sustainability. Strengthened collaboration between IPCC Working Groups is reflected in Cross-Working Group Boxes that integrate
physical science, climate risks and adaptation, and the mitigation of climate change.5
5
SPM
Summary for Policymakers
• Increasing diversity of analytic frameworks from multiple disciplines including social sciences. This report identifies
multiple analytic frameworks to assess the drivers of, barriers to and options for, mitigation action. These include: economic
efficiency, including the benefits of avoided impacts; ethics and equity; interlinked technological and social transition processes;
and socio-political frameworks, including institutions and governance {1, 3, 13, Cross-Chapter Box 12 in Chapter 16}. These help
to identify risks and opportunities for action, including co-benefits and just and equitable transitions at local, national and global
scales. {1, 3, 4, 5, 13, 14, 16, 17}
Section B of this Summary for Policymakers (SPM) assesses Recent developments and current trends, including data uncertainties and
gaps. Section C, System transformations to limit global warming, identifies emission pathways and alternative mitigation portfolios
consistent with limiting global warming to different levels, and assesses specific mitigation options at the sectoral and system level.
Section D addresses Linkages between mitigation, adaptation, and sustainable development. Section E, Strengthening the response,
assesses knowledge of how enabling conditions of institutional design, policy, finance, innovation and governance arrangements can
contribute to climate change mitigation in the context of sustainable development.
6
SPM
Summary for Policymakers
B. Recent Developments and Current Trends
6 Net GHG emissions in this report refer to releases of greenhouse gases from anthropogenic sources minus removals by anthropogenic sinks, for those species of
gases that are reported under the common reporting format of the United Nations Framework Convention on Climate Change (UNFCCC): CO2 from fossil fuel
combustion and industrial processes (CO2-FFI); net CO2 emissions from land use, land-use change and forestry (CO2-LULUCF); methane (CH4); nitrous oxide (N2O);
and fluorinated gases (F-gases) comprising hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6), as well as nitrogen trifluoride (NF3).
Different datasets for GHG emissions exist, with varying time horizons and coverage of sectors and gases, including some that go back to 1850. In this report,
GHG emissions are assessed from 1990, and CO2 sometimes also from 1850. Reasons for this include data availability and robustness, scope of the assessed
literature, and the differing warming impacts of non-CO2 gases over time.
7 GHG emission metrics are used to express emissions of different greenhouse gases in a common unit. Aggregated GHG emissions in this report are stated in
CO2-equivalent (CO2-eq) using the Global Warming Potential with a time horizon of 100 years (GWP100) with values based on the contribution of Working Group
I to the AR6. The choice of metric depends on the purpose of the analysis, and all GHG emission metrics have limitations and uncertainties, given that they simplify
the complexity of the physical climate system and its response to past and future GHG emissions. {Cross-Chapter Box 2 in Chapter 2, Supplementary Material
2.SM.3, Box TS.2; AR6 WGI Chapter 7 Supplementary Material}
8 In this SPM, uncertainty in historic GHG emissions is reported using 90% uncertainty intervals unless stated otherwise. GHG emission levels are rounded to two
significant digits; as a consequence, small differences in sums due to rounding may occur.
9 Global databases make different choices about which emissions and removals occurring on land are considered anthropogenic. Currently, net CO2 fluxes from land
reported by global bookkeeping models used here are estimated to be about 5.5 GtCO2 yr–1 higher than the aggregate global net emissions based on national GHG
inventories. This difference, which has been considered in the literature, mainly reflects differences in how anthropogenic forest sinks and areas of managed land are
defined. Other reasons for this difference, which are more difficult to quantify, can arise from the limited representation of land management in global models and
varying levels of accuracy and completeness of estimated LULUCF fluxes in national GHG inventories. Neither method is inherently preferable. Even when the same
methodological approach is applied, the large uncertainty of CO2-LULUCF emissions can lead to substantial revisions to estimated emissions. {Cross-Chapter Box 3
in Chapter 3, 7.2, SRCCL SPM A.3.3}
10 For consistency with WGI, historical cumulative CO2 emissions from 1850 to 2019 are reported using 68% confidence intervals.
B.1 Total net anthropogenic GHG emissions6 have continued to rise during the period 2010–2019, as have
cumulative net CO2 emissions since 1850. Average annual GHG emissions during 2010–2019 were
higher than in any previous decade, but the rate of growth between 2010 and 2019 was lower than
that between 2000 and 2009. (high confidence) (Figure SPM.1) {Figure 2.2, Figure 2.5, Table 2.1, 2.2,
Figure TS.2}
B.1.1 Global net anthropogenic GHG emissions were 59 ± 6.6 GtCO2-eq7,8 in 2019, about 12% (6.5 GtCO2-eq) higher than in 2010
and 54% (21 GtCO2-eq) higher than in 1990. The annual average during the decade 2010–2019 was 56 ± 6.0 GtCO2-eq,
9.1 GtCO2-eq yr–1 higher than in 2000–2009. This is the highest increase in average decadal emissions on record. The average
annual rate of growth slowed from 2.1% yr–1 between 2000 and 2009 to 1.3% yr–1 between 2010 and 2019. (high confidence)
(Figure SPM.1) {Figure 2.2, Figure 2.5, Table 2.1, 2.2, Figure TS.2}
B.1.2 Growth in anthropogenic emissions has persisted across all major groups of GHGs since 1990, albeit at different rates.
By 2019, the largest growth in absolute emissions occurred in CO2 from fossil fuels and industry followed by CH4, whereas the
highest relative growth occurred in fluorinated gases, starting from low levels in 1990 (high confidence). Net anthropogenic
CO2 emissions from land use, land-use change and forestry (CO2-LULUCF) are subject to large uncertainties and high annual
variability, with low confidence even in the direction of the long-term trend.9 (Figure SPM.1) {Figure 2.2, Figure 2.5, 2.2,
Figure TS.2}
B.1.3 Historical cumulative net CO2 emissions from 1850 to 2019 were 2400 ± 240 GtCO2 (high confidence). Of these, more than half
(58%) occurred between 1850 and 1989 [1400 ± 195 GtCO2], and about 42% between 1990 and 2019 [1000 ± 90 GtCO2]. About
17% of historical cumulative net CO2 emissions since 1850 occurred between 2010 and 2019 [410 ± 30 GtCO2].10 By comparison,
the current central estimate of the remaining carbon budget from 2020 onwards for limiting warming to 1.5°C with a probability
of 50% has been assessed as 500 GtCO2, and as 1150 GtCO2 for a probability of 67% for limiting warming to 2°C. Remaining
carbon budgets depend on the amount of non-CO2 mitigation (±220 GtCO2) and are further subject to geophysical uncertainties.
Based on central estimates only, cumulative net CO2 emissions between 2010 and 2019 compare to about four-fifths of the
size of the remaining carbon budget from 2020 onwards for a 50% probability of limiting global warming to 1.5°C, and about
one-third of the remaining carbon budget for a 67% probability to limit global warming to 2°C. Even when taking uncertainties
into account, historical emissions between 1850 and 2019 constitute a large share of total carbon budgets for these global
7
SPM
Summary for Policymakers
warming levels.11,12 Based on central estimates only, historical cumulative net CO2 emissions between 1850 and 2019 amount to
about four-fifths12 of the total carbon budget for a 50% probability of limiting global warming to 1.5°C (central estimate about
2900 GtCO2), and to about two thirds12 of the total carbon budget for a 67% probability to limit global warming to 2°C (central
estimate about 3550 GtCO2). {Figure 2.7, 2.2, Figure TS.3, WGI Table SPM.2}
B.1.4 Emissions of CO2-FFI dropped temporarily in the first half of 2020 due to responses to the COVID-19 pandemic (high confidence),
but rebounded by the end of the year (medium confidence). The annual average CO2-FFI emissions reduction in 2020 relative
to 2019 was about 5.8% [5.1–6.3%], or 2.2 [1.9–2.4] GtCO2 (high confidence). The full GHG emissions impact of the COVID-19
pandemic could not be assessed due to a lack of data regarding non-CO2 GHG emissions in 2020. {Cross-Chapter Box 1 in
Chapter 1, Figure 2.6, 2.2, Box TS.1, Box TS.1 Figure 1}
38Gt
+0.7% yr
–1 +2.1% yr
–1 +1.3% yr
–1
42Gt 53Gt 59Gt
CO2 from fossil
fuel and industry
(CO2-FFI)
Net CO2 from land
use, land-use
change, forestry
(CO2-LULUCF)
Methane (CH4)
Nitrous
oxide (N2O)
Fluorinated
gases (F-gases)
a. Global net anthropogenic GHG emissions 1990–2019 (5)
b. Global anthropogenic GHG emissions and uncertainties by gas – relative to 1990
Global net anthropogenic emissions have continued to rise across all major groups of greenhouse gases.
GHG emissions (%) GHG emissions (GtCO2-eq yr –1)
0
2019
59 ± 6.6 Gt
2019
emissions
(GtCO2-eq)
1990–2019
increase
(GtCO2-eq)
Emissions
in 2019,
relative
to 1990 (%)
CO2-FFI 38 ± 3 15 167
CO2-LULUCF 6.6 ± 4.6 1.6 133
CH4 11 ± 3.2 2.4 129
N2O 2.7 ± 1.6 0.65 133
F-gases 1.4 ± 0.41 0.97 354
Total 59 ± 6.6 21 154
The solid line indicates central estimate of emissions trends. The shaded area indicates the uncertainty range.
0
10
20
30
40
50
60
1990 2000 2010 2019
50
100
150
200
250
CO2-LULUCF
1990 2019
CH4
1990 2019
CO2-FFI
1990 2019
N2O
1990 2019
F-gases
0
1990 2019
100
200
300
500
400
21%
13%
59%
2%
5%
20%
12%
61%
2%
5%
18%
10%
65%
2%
4%
18%
11%
64%
1%
5%
Figure SPM.1 | Global net anthropogenic GHG emissions (GtCO2-eq yr–1) 1990–2019. Global net anthropogenic GHG emissions include CO2 from fossil fuel
combustion and industrial processes (CO2-FFI); net CO2 from land use, land-use change and forestry (CO2-LULUCF)9; methane (CH4); nitrous oxide (N2O); and fluorinated
gases (HFCs, PFCs, SF6, NF3).6 Panel a shows aggregate annual global net anthropogenic GHG emissions by groups of gases from 1990 to 2019 reported in GtCO2-eq
converted based on global warming potentials with a 100-year time horizon (GWP100-AR6) from the IPCC Sixth Assessment Report Working Group I (Chapter 7).
The fraction of global emissions for each gas is shown for 1990, 2000, 2010 and 2019; as well as the aggregate average annual growth rate between these decades.
At the right side of Panel a, GHG emissions in 2019 are broken down into individual components with the associated uncertainties (90% confidence interval) indicated by
the error bars: CO2-FFI ±8%; CO2-LULUCF ±70%; CH4 ±30%; N2O ±60%; F-gases ±30%; GHG ±11%. Uncertainties in GHG emissions are assessed in Supplementary
Material 2.2. The single-year peak of emissions in 1997 was due to higher CO2-LULUCF emissions from a forest and peat fire event in South East Asia. Panel b shows
global anthropogenic CO2-FFI, net CO2-LULUCF, CH4, N2O and F-gas emissions individually for the period 1990–2019, normalised relative to 100 in 1990. Note the
different scale for the included F-gas emissions compared to other gases, highlighting its rapid growth from a low base. Shaded areas indicate the uncertainty range.
Uncertainty ranges as shown here are specific for individual groups of greenhouse gases and cannot be compared. The table shows the central estimate for: absolute
emissions in 2019; the absolute change in emissions between 1990 and 2019; and emissions in 2019 expressed as a percentage of 1990 emissions. {2.2, Figure 2.5,
Supplementary Material 2.2, Figure TS.2}
11 The carbon budget is the maximum amount of cumulative net global anthropogenic CO2 emissions that would result in limiting global warming to a given level with
a given likelihood, taking into account the effect of other anthropogenic climate forcers. This is referred to as the ‘total carbon budget’ when expressed starting from
the pre-industrial period, and as the ‘remaining carbon budget’ when expressed from a recent specified date. The total carbon budgets reported here are the sum
of historical emissions from 1850 to 2019 and the remaining carbon budgets from 2020 onwards, which extend until global net zero CO2 emissions are reached.
{Annex I: Glossary; WGI SPM}
12 Uncertainties for total carbon budgets have not been assessed and could affect the specific calculated fractions.
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8
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Summary for Policymakers
B.2 Net anthropogenic GHG emissions have increased since 2010 across all major sectors globally. An
increasing share of emissions can be attributed to urban areas. Emissions reductions in CO2 from
fossil fuels and industrial processes (CO2-FFI), due to improvements in energy intensity of GDP and
carbon intensity of energy, have been less than emissions increases from rising global activity levels
in industry, energy supply, transport, agriculture and buildings. (high confidence) {2.2, 2.4, 6.3, 7.2, 8.3,
9.3, 10.1, 11.2}
B.2.1 In 2019, approximately 34% (20 GtCO2-eq) of total net anthropogenic GHG emissions came from the energy supply sector,
24% (14 GtCO2-eq) from industry, 22% (13 GtCO2-eq) from agriculture, forestry and other land use (AFOLU), 15% (8.7 GtCO2-eq)
from transport and 6% (3.3 GtCO2-eq) from buildings.13 If emissions from electricity and heat production are attributed to the
sectors that use the final energy, 90% of these indirect emissions are allocated to the industry and buildings sectors, increasing
their relative GHG emissions shares from 24% to 34%, and from 6% to 16%, respectively. After reallocating emissions from
electricity and heat production, the energy supply sector accounts for 12% of global net anthropogenic GHG emissions.
(high confidence) {Figure 2.12, 2.2, 6.3, 7.2, 9.3, 10.1, 11.2, Figure TS.6}
B.2.2 Average annual GHG emissions growth between 2010 and 2019 slowed compared to the previous decade in energy supply
(from 2.3% to 1.0%) and industry (from 3.4% to 1.4%), but remained roughly constant at about 2% yr–1 in the transport
sector (high confidence). Emissions growth in AFOLU, comprising emissions from agriculture (mainly CH4 and N2O) and
forestry and other land use (mainly CO2) is more uncertain than in other sectors due to the high share and uncertainty of
CO2-LULUCF emissions (medium confidence). About half of total net AFOLU emissions are from CO2-LULUCF, predominantly
from deforestation14 (medium confidence). {Figure 2.13, 2.2, 6.3, 7.2, Figure 7.3, 9.3, 10.1, 11.2, TS.3}
B.2.3 The global share of emissions that can be attributed to urban areas is increasing. In 2015, urban emissions were estimated
to be 25 GtCO2-eq (about 62% of the global share) and in 2020, 29 GtCO2-eq (67–72% of the global share).15 The drivers of
urban GHG emission are complex and include population size, income, state of urbanisation and urban form. (high confidence)
{8.1, 8.3}
B.2.4 Global energy intensity (total primary energy per unit GDP) decreased by 2% yr–1 between 2010 and 2019. Carbon intensity
(CO2 from fossil fuel combustion and industrial processes (CO2-FFI) per unit primary energy) decreased by 0.3% yr–1, with large
regional variations, over the same period mainly due to fuel switching from coal to gas, reduced expansion of coal capacity,
and increased use of renewables. This reversed the trend observed for 2000–2009. For comparison, the carbon intensity of
primary energy is projected to decrease globally by about 3.5% yr–1 between 2020 and 2050 in modelled scenarios that limit
warming to 2°C (>67%), and by about 7.7% yr–1 globally in scenarios that limit warming to 1.5°C (>50%) with no or limited
overshoot.16 (high confidence) {Figure 2.16, 2.2, 2.4, Table 3.4, 3.4, 6.3}
13 Sector definitions can be found in Annex II.9.1.
14 Land overall constituted a net sink of –6.6 (±4.6) GtCO2 yr–1 for the period 2010–2019, comprising a gross sink of –12.5 (±3.2) GtCO2 yr–1 resulting from responses
of all land to both anthropogenic environmental change and natural climate variability, and net anthropogenic CO2-LULUCF emissions +5.7 (±4.0) GtCO2 yr–1 based
on bookkeeping models. {Table 2.1, 7.2, Table 7.1}
15 This estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas
related to the production of electricity, goods and services consumed in cities. These estimates include all CO2 and CH4 emission categories except for aviation and
marine bunker fuels, land-use change, forestry and agriculture. {8.1, Annex I: Glossary}
16 See Box SPM.1 for the categorisation of modelled long-term emission scenarios based on projected temperature outcomes and associated probabilities adopted in
this report.
9
SPM
Summary for Policymakers
B.3 Regional contributions17 to global GHG emissions continue to differ widely. Variations in regional,
and national per capita emissions partly reflect different development stages, but they also vary
widely at similar income levels. The 10% of households with the highest per capita emissions
contribute a disproportionately large share of global household GHG emissions. At least 18 countries
have sustained GHG emission reductions for longer than 10 years. (high confidence) (Figure SPM.2)
{Figure 1.1, Figure 2.9, Figure 2.10, Figure 2.25, 2.2, 2.3, 2.4, 2.5, 2.6, Figure TS.4, Figure TS.5}
B.3.1 GHG emissions trends over 1990–2019 vary widely across regions and over time, and across different stages of development,
as shown in Figure SPM.2. Average global per capita net anthropogenic GHG emissions increased from 7.7 to 7.8 tCO2-eq,
ranging from 2.6 tCO2-eq to 19 tCO2-eq across regions. Least developed countries (LDCs) and Small Island Developing States
(SIDS) have much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq, respectively) than the global average (6.9 tCO2-eq),
excluding CO2-LULUCF.18 (high confidence) (Figure SPM.2) {Figure1.2, Figure 2.9, Figure 2.10, 2.2, Figure TS.4}
B.3.2 Historical contributions to cumulative net anthropogenic CO2 emissions between 1850 and 2019 vary substantially across
regions in terms of total magnitude, but also in terms of contributions to CO2-FFI (1650 ± 73 GtCO2-eq) and net CO2-LULUCF
(760 ± 220 GtCO2-eq) emissions.10 Globally, the major share of cumulative CO2-FFI emissions is concentrated in a few regions,
while cumulative CO2-LULUCF9 emissions are concentrated in other regions. LDCs contributed less than 0.4% of historical
cumulative CO2-FFI emissions between 1850 and 2019, while SIDS contributed 0.5%. (high confidence) (Figure SPM.2)
{Figure 2.10, 2.2, TS.3, Figure 2.7}
B.3.3 In 2019, around 48% of the global population lives in countries emitting on average more than 6 tCO2-eq per capita, excluding
CO2-LULUCF. 35% live in countries emitting more than 9 tCO2-eq per capita. Another 41% live in countries emitting less than
3 tCO2-eq per capita. A substantial share of the population in these low-emitting countries lack access to modern energy
services.19 Eradicating extreme poverty, energy poverty, and providing decent living standards20 to all in these regions in
the context of achieving sustainable development objectives, in the near-term, can be achieved without significant global
emissions growth. (high confidence) (Figure SPM.2) {Figure 1.2, 2.2, 2.4, 2.6, 3.7, 4.2, 6.7, Figure TS.4, Figure TS.5}
B.3.4 Globally, the 10% of households with the highest per capita emissions contribute 34–45% of global consumption-based
household GHG emissions,21 while the middle 40% contribute 40–53%, and the bottom 50% contribute 13–15%. (high
confidence) {2.6, Figure 2.25}
B.3.5 At least 18 countries have sustained production-based GHG and consumption-based CO2 emission reductions for longer than
10 years. Reductions were linked to energy supply decarbonisation, energy efficiency gains, and energy demand reduction,
which resulted from both policies and changes in economic structure. Some countries have reduced production-based GHG
emissions by a third or more since peaking, and some have achieved several years of consecutive reduction rates of around
4% yr–1, comparable to global reductions in scenarios limiting warming to 2°C (>67%) or lower. These reductions have only
partly offset global emissions growth. (high confidence) (Figure SPM.2) {Figure TS.4, 2.2, 1.3.2}
17 See Annex II, Part 1 for regional groupings adopted in this report.
18 In 2019, LDCs are estimated to have emitted 3.3% of global GHG emissions, and SIDS are estimated to have emitted 0.6% of global GHG emissions, excluding
CO2-LULUCF. These country groupings cut across geographic regions and are not depicted separately in Figure SPM.2. {Figure 2.10}
19 In this report, access to modern energy services is defined as access to clean, reliable and affordable energy services for cooking and heating, lighting, communications,
and productive uses. {Annex I: Glossary}
20 In this report, decent living standards are defined as a set of minimum material requirements essential for achieving basic human well-being, including nutrition,
shelter, basic living conditions, clothing, health care, education, and mobility. {5.1}
21 Consumption-based emissions refer to emissions released to the atmosphere to generate the goods and services consumed by a certain entity (e.g., a person, firm,
country, or region). The bottom 50% of emitters spend less than USD3 PPP (purchasing power parity) per capita per day. The top 10% of emitters (an open-ended
category) spend more than USD23 PPP per capita per day. The wide range of estimates for the contribution of the top 10% results from the wide range of spending
in this category and differing methods in the assessed literature. {2.6, Annex I: Glossary}
10
SPM
Summary for Policymakers
Fossil fuel and industry
(CO2-FFI)
All GHG emissions
Net CO2 from land
use, land-use
change, forestry
(CO2-LULUCF)
Other GHG emissions
a. Global net anthropogenic GHG emissions by region (1990–2019)
Emissions have grown in most regions but are distributed unevenly, both in the present day and
cumulatively since 1850.
1990 2000 2010 2019
10
20
30
0
40
50
60
GHG emissions (GtCO2-eq yr
–1)
c. Net anthropogenic GHG emissions per capita
and for total population, per region (2019)
d. Regional indicators (2019) and regional production vs consumption accounting (2018)
GHG emissions (tCO2-eq per capita)
Population (millions)
Eastern Asia
North America
Latin America and Caribbean
South-East Asia and Pacific
Africa
Southern Asia
Europe
Eastern Europe and West-Central Asia
Middle East
Australia, Japan and New Zealand
International shipping and aviation
27%
13%
16%
24%
12%
18%
19%
14%
10%
10%
11%
11%
9%
7%
7%
7%
9%
7%
8%
8%
8%
7%
8%
8%
Africa
Production-based emissions (tCO2-FFI per person, based on 2018 data) 1.2 10 8.4 9.2 6.5 2.8 8.7 16 2.6 1.6
Consumption-based emissions (tCO2-FFI per person, based on 2018 data) 0.84 11 6.7 6.2 7.8 2.8 7.6 17 2.5 1.5
% GHG contributions 9% 3% 27% 6% 8% 10% 5% 12% 9% 8%
Population (million persons, 2019) 1292 157 1471 291 620 646 252 366 674 1836
GHG per capita (tCO2-eq per person) 3.9 13 11 13 7.8 9.2 13 19 7.9 2.6
GDP per capita (USD1000ppp2017 per person)
1 5.0 43 17 20 43 15 20 61 12 6.2
Net GHG 2019
2 (production basis)
CO2-FFI, 2018, per person
GHG emissions intensity (tCO2-eq / USD1000ppp 2017) 0.78 0.30 0.62 0.64 0.18 0.61 0.64 0.31 0.65 0.42
Australia,
Japan,
New
Zealand
Eastern
Asia
Eastern
Europe,
West-
Central
Asia
Europe Latin
America
and
Caribbean
Middle
East
North
America
South-East
Asia and
Pacific
Southern
Asia
16%
14%
3%
5%
2%
2%
2%
2%
5%
8%
4%
7%
5%
4%
5%
3%
6%
13%
10%
8%
0 2000 4000 6000 8000
CO2 emissions (GtCO2)
Africa
Australia, Japan and New Zealand
Eastern Asia
Eastern Europe and West-Central Asia
Europe
International shipping and aviation
Latin America and Caribbean
Middle East
North America
South-East Asia and Pacific
Southern Asia
0 200 400 600
b. Historical cumulative net anthropogenic CO2 emissions
per region (1850–2019)
4%
1 GDP per capita in 2019 in USD2017 currency purchasing power basis.
2 Includes CO2-FFI, CO2-LULUCF and Other GHGs, excluding international aviation and shipping.
0
5
10
15
20
38Gt 42Gt 53Gt 59Gt
Middle East
Africa
Eastern Asia
South-East Asia and Pacific
Latin America and Caribbean
Europe
Southern
Asia
North America
Australia, Japan and New Zealand
Eastern Europe and West-Central Asia
The regional groupings used in this figure are for statistical purposes only and are described in Annex II, Part I.
16%
4%
2%
8%
12%
11%
10%
7%
2%
23%
Figure SPM.2 | Regional GHG emissions, and the regional proportion of total cumulative production-based CO2 emissions from 1850 to 2019.
--
I
I
J1
11
SPM
Summary for Policymakers
Figure SPM.2 (continued): Regional GHG emissions, and the regional proportion of total cumulative production-based CO2 emissions from 1850
to 2019. Panel a shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr–1 (GWP100-AR6)) for the time period 1990–2019.6 Percentage values
refer to the contribution of each region to total GHG emissions in each respective time period. The single-year peak of emissions in 1997 was due to higher CO2-LULUCF
emissions from a forest and peat fire event in South East Asia. Regions are as grouped in Annex II. Panel b shows the share of historical cumulative net anthropogenic
CO2 emissions per region from 1850 to 2019 in GtCO2. This includes CO2 from fossil fuel combustion and industrial processes (CO2-FFI) and net CO2 emissions from
land use, land-use change, forestry (CO2-LULUCF). Other GHG emissions are not included.6 CO2-LULUCF emissions are subject to high uncertainties, reflected by
a global uncertainty estimate of ±70% (90% confidence interval). Panel c shows the distribution of regional GHG emissions in tonnes CO2-eq per capita by region in
2019. GHG emissions are categorised into: CO2-FFI; net CO2-LULUCF; and other GHG emissions (methane, nitrous oxide, fluorinated gases, expressed in CO2-eq using
GWP100-AR6). The height of each rectangle shows per capita emissions, the width shows the population of the region, so that the area of the rectangles refers to the
total emissions for each region. Emissions from international aviation and shipping are not included. In the case of two regions, the area for CO2-LULUCF is below the
axis, indicating net CO2 removals rather than emissions. CO2-LULUCF emissions are subject to high uncertainties, reflected by a global uncertainty estimate of ±70%
(90% confidence interval). Panel d shows population, GDP per person, emission indicators by region in 2019 for percentage GHG contributions, total GHG per person,
and total GHG emissions intensity, together with production-based and consumption-based CO2-FFI data, which is assessed in this report up to 2018. Consumption-based
emissions are emissions released to the atmosphere in order to generate the goods and services consumed by a certain entity (e.g., region). Emissions from international
aviation and shipping are not included. {1.3, Figure 1.2, 2.2, Figure 2.9, Figure 2.10, Figure 2.11, Annex II}
B.4 The unit costs of several low-emission technologies have fallen continuously since 2010. Innovation
policy packages have enabled these cost reductions and supported global adoption. Both tailored
policies and comprehensive policies addressing innovation systems have helped overcome the
distributional, environmental and social impacts potentially associated with global diffusion of
low-emission technologies. Innovation has lagged in developing countries due to weaker enabling
conditions. Digitalisation can enable emission reductions, but can have adverse side effects unless
appropriately governed. (high confidence) (Figure SPM.3) {2.2, 6.3, 6.4, 7.2, 12.2, 16.2, 16.4, 16.5,
Cross-Chapter Box 11 in Chapter 16}
B.4.1 From 2010 to 2019, there have been sustained decreases in the unit costs of solar energy (85%), wind energy (55%), and
lithium-ion batteries (85%), and large increases in their deployment, e.g., >10× for solar and >100× for electric vehicles (EVs),
varying widely across regions (Figure SPM.3). The mix of policy instruments which reduced costs and stimulated adoption
includes public R&D, funding for demonstration and pilot projects, and demand pull instruments such as deployment subsidies
to attain scale. In comparison to modular small-unit size technologies, the empirical record shows that multiple large-scale
mitigation technologies, with fewer opportunities for learning, have seen minimal cost reductions and their adoption has
grown slowly. (high confidence) {1.3, 1.5, Figure 2.5, 2.5, 6.3, 6.4, 7.2, 11.3, 12.2, 12.3, 12.6, 13.6, 16.3, 16.4, 16.6}
B.4.2 Policy packages tailored to national contexts and technological characteristics have been effective in supporting low-emission
innovation and technology diffusion. Appropriately designed policies and governance have helped address distributional
impacts and rebound effects. Innovation has provided opportunities to lower emissions and reduce emission growth
and created social and environmental co-benefits (high confidence). Adoption of low-emission technologies lags in most
developing countries, particularly least developed ones, due in part to weaker enabling conditions, including limited finance,
technology development and transfer, and capacity. In many countries, especially those with limited institutional capacities,
several adverse side effects have been observed as a result of diffusion of low-emission technology, for example, low-value
employment, and dependency on foreign knowledge and suppliers. Low-emission innovation along with strengthened
enabling conditions can reinforce development benefits, which can, in turn, create feedbacks towards greater public support
for policy. (medium confidence) {9.9, 13.6, 13.7, 16.3, 16.4, 16.5, 16.6, Cross-Chapter Box 12 in Chapter 16, TS.3}
B.4.3 Digital technologies can contribute to mitigation of climate change and the achievement of several SDGs (high confidence).
For example, sensors, internet of things, robotics, and artificial intelligence can improve energy management in all sectors,
increase energy efficiency, and promote the adoption of many low-emission technologies, including decentralised renewable
energy, while creating economic opportunities (high confidence). However, some of these climate change mitigation gains can
be reduced or counterbalanced by growth in demand for goods and services due to the use of digital devices (high confidence).
Digitalisation can involve trade-offs across several SDGs, for example, increasing electronic waste, negative impacts on labour
markets, and exacerbating the existing digital divide. Digital technology supports decarbonisation only if appropriately
governed (high confidence). {5.3, 10, 12.6, 16.2, Cross-Chapter Box 11 in Chapter 16, TS.5, Box TS.14}
12
SPM
Summary for Policymakers
Adoption (millions of EVs)
Cost (USD2020/MWh)
Li-on battery packs (USD2020/kWh) Market cost
Adoption (note different scales) Fossil fuel cost (2020)
AR5 (2010)
Batteries for passenger
Photovoltaics (PV) electric vehicles (EVs)
Concentrating
Onshore wind Offshore wind solar power (CSP)
The unit costs of some forms of renewable energy and of batteries for passenger EVs have fallen,
and their use continues to rise.
1200
1600
800
400
0 0 0
150
300
450
2000 2020
600
150
300
450
600
150
300
450
600
150
300
450
600
2010 2000 2010 2020 2000 2010 2020
0
2000 2020
Adoption (GW)
0
200
400
600
800
2000 2010 2020
0
2000 2010 2020 2010
0
200
400
600
800
2000 2010 2020
0
10
20
30
40
2000 2010 2020
0
10
20
30
40
2000 2010 2020
0
2
4
6
8
2000 2010 2020
Share of electricity
produced in 2020: 3%
Share of electricity
produced in 2020: 6%
Share of electricity
produced in 2020: <1%
Share of electricity
produced in 2020: <1%
Share of passenger
vehicle fleet in 2020: 1%
Figure SPM.3 | Unit cost reductions and use in some rapidly changing mitigation technologies. The top panel shows global costs per unit of energy
(USD per MWh) for some rapidly changing mitigation technologies. Solid blue lines indicate average unit cost in each year. Light blue shaded areas show the range
between the 5th and 95th percentiles in each year. Grey shading indicates the range of unit costs for new fossil fuel (coal and gas) power in 2020 (corresponding
to USD55–148 per MWh). In 2020, the levelised costs of energy (LCOE) of the four renewable energy technologies could compete with fossil fuels in many places.
For batteries, costs shown are for 1 kWh of battery storage capacity; for the others, costs are LCOE, which includes installation, capital, operations, and maintenance costs
per MWh of electricity produced. The literature uses LCOE because it allows consistent comparisons of cost trends across a diverse set of energy technologies to be made.
However, it does not include the costs of grid integration or climate impacts. Further, LCOE does not take into account other environmental and social externalities that
may modify the overall (monetary and non-monetary) costs of technologies and alter their deployment. The bottom panel shows cumulative global adoption for each
technology, in GW of installed capacity for renewable energy and in millions of vehicles for battery-electric vehicles. A vertical dashed line is placed in 2010 to indicate
the change since AR5. Shares of electricity produced and share of passenger vehicle fleet are indicated in text for 2020 based on provisional data, i.e., percentage of
total electricity production (for PV, onshore wind, offshore wind, CSP) and of total stock of passenger vehicles (for EVs). The electricity production share reflects different
capacity factors; for example, for the same amount of installed capacity, wind produces about twice as much electricity as solar PV. {2.5, 6.4} Renewable energy and
battery technologies were selected as illustrative examples because they have recently shown rapid changes in costs and adoption, and because consistent data are
available. Other mitigation options assessed in the report are not included as they do not meet these criteria.
I hi
-
13
SPM
Summary for Policymakers
B.5 There has been a consistent expansion of policies and laws addressing mitigation since AR5. This
has led to the avoidance of emissions that would otherwise have occurred and increased investment
in low-GHG technologies and infrastructure. Policy coverage of emissions is uneven across sectors.
Progress on the alignment of financial flows towards the goals of the Paris Agreement remains slow
and tracked climate finance flows are distributed unevenly across regions and sectors. (high confidence)
{5.6, 13.2, 13.4, 13.5, 13.6, 13.9, 14.3, 14.4, 14.5, Cross-Chapter Box 10 in Chapter 14, 15.3, 15.5}
B.5.1 The Kyoto Protocol led to reduced emissions in some countries and was instrumental in building national and international
capacity for GHG reporting, accounting and emissions markets (high confidence). At least 18 countries that had Kyoto targets
for the first commitment period have had sustained absolute emission reductions for at least a decade from 2005, of which
two were countries with economies in transition (very high confidence). The Paris Agreement, with near universal participation,
has led to policy development and target-setting at national and sub-national levels, in particular in relation to mitigation, as
well as enhanced transparency of climate action and support (medium confidence). {14.3, 14.6}
B.5.2 The application of diverse policy instruments for mitigation at the national and sub-national levels has grown consistently
across a range of sectors (high confidence). By 2020, over 20% of global GHG emissions were covered by carbon taxes
or emissions trading systems, although coverage and prices have been insufficient to achieve deep reductions (medium
confidence). By 2020, there were ‘direct’ climate laws focused primarily on GHG reductions in 56 countries covering 53% of
global emissions (medium confidence). Policy coverage remains limited for emissions from agriculture and the production
of industrial materials and feedstocks (high confidence). {5.6, 7.6, 11.5, 11.6, 13.2, 13.6}
B.5.3 In many countries, policies have enhanced energy efficiency, reduced rates of deforestation and accelerated technology
deployment, leading to avoided and in some cases reduced or removed emissions (high confidence). Multiple lines of
evidence suggest that mitigation policies have led to avoided global emissions of several GtCO2-eq yr–1 (medium confidence).
At least 1.8 GtCO2-eq yr–1 can be accounted for by aggregating separate estimates for the effects of economic and regulatory
instruments. Growing numbers of laws and executive orders have impacted global emissions and were estimated to result in
5.9 GtCO2-eq yr–1 less emissions in 2016 than they otherwise would have been. (medium confidence) (Figure SPM.3) {2.2, 2.8,
6.7, 7.6, 9.9, 10.8, 13.6, Cross-chapter Box 10 in Chapter 14}
B.5.4 Annual tracked total financial flows for climate mitigation and adaptation increased by up to 60% between 2013/14 and
2019/20 (in USD2015), but average growth has slowed since 201822 (medium confidence). These financial flows remained
heavily focused on mitigation, are uneven, and have developed heterogeneously across regions and sectors (high confidence).
In 2018, public and publicly mobilised private climate finance flows from developed to developing countries were below
the collective goal under the UNFCCC and Paris Agreement to mobilise USD100 billion per year by 2020 in the context
of meaningful mitigation action and transparency on implementation (medium confidence). Public and private finance
flows for fossil fuels are still greater than those for climate adaptation and mitigation (high confidence). Markets for green
bonds, ESG (environmental, social and governance) and sustainable finance products have expanded significantly since AR5.
Challenges remain, in particular around integrity and additionality, as well as the limited applicability of these markets to
many developing countries. (high confidence) {Box 15.4, 15.3, 15.5, 15.6, Box 15.7}
22 Estimates of financial flows (comprising both private and public, domestic and international flows) are based on a single report which assembles data from multiple
sources and which has applied various changes to their methodology over the past years. Such data can suggest broad trends but is subject to uncertainties.
14
SPM
Summary for Policymakers
B.6 Global GHG emissions in 2030 associated with the implementation of Nationally Determined
Contributions (NDCs) announced prior to COP2623 would make it likely that warming will exceed 1.5°C
during the 21st century.24 Likely limiting warming to below 2°C would then rely on a rapid acceleration
of mitigation efforts after 2030. Policies implemented by the end of 202025 are projected to result in
higher global GHG emissions than those implied by NDCs. (high confidence) (Figure SPM.4) {3.3, 3.5,
4.2, Cross-Chapter Box 4 in Chapter 4}
B.6.1 Policies implemented by the end of 2020 are projected to result in higher global GHG emissions than those implied by NDCs,
indicating an implementation gap. A gap remains between global GHG emissions in 2030 associated with the implementation
of NDCs announced prior to COP26 and those associated with modelled mitigation pathways assuming immediate action
(for quantification see Table SPM.1).26 The magnitude of the emissions gap depends on the global warming level considered and
whether only unconditional or also conditional elements of NDCs27 are considered.28 (high confidence) {3.5, 4.2, Cross-Chapter
Box 4 in Chapter 4}
B.6.2 Global emissions in 2030 associated with the implementation of NDCs announced prior to COP26 are lower than the emissions
implied by the original NDCs29 (high confidence). The original emissions gap has fallen by about 20% to one-third relative to
pathways that limit warming to 2°C (>67%) with immediate action (category C3a in Table SPM.2), and by about 15–20%
relative to pathways limiting warming to 1.5°C (>50%) with no or limited overshoot (category C1 in Table SPM.2) (medium
confidence). (Figure SPM.4) {3.5, 4.2, Cross-Chapter Box 4 in Chapter 4}
23 NDCs announced prior to COP26 refer to the most recent Nationally Determined Contributions submitted to the UNFCCC up to the literature cut-off date of this
report, 11 October 2021, and revised NDCs announced by China, Japan and the Republic of Korea prior to October 2021 but only submitted thereafter. 25 NDC
updates were submitted between 12 October 2021 and the start of COP26.
24 This implies that mitigation after 2030 can no longer establish a pathway with less than 67% probability to exceed 1.5°C during the 21st century, a defining feature
of the class of pathways that limit warming to 1.5°C (>50%) with no or limited overshoot assessed in this report (category C1 in Table SPM.2). These pathways limit
warming to 1.6°C or lower throughout the 21st century with a 50% likelihood.
25 The policy cut-off date in studies used to project GHG emissions of ‘policies implemented by the end of 2020’ varies between July 2019 and November 2020. {Table 4.2}
26 Immediate action in modelled global pathways refers to the adoption between 2020 and at latest before 2025 of climate policies intended to limit global warming
to a given level. Modelled pathways that limit warming to 2°C (>67%) based on immediate action are summarised in category C3a in Table SPM.2. All assessed
modelled global pathways that limit warming to 1.5°C (>50%) with no or limited overshoot assume immediate action as defined here (Category C1 in Table SPM.2).
27 In this report, ‘unconditional’ elements of NDCs refer to mitigation efforts put forward without any conditions. ‘Conditional’ elements refer to mitigation efforts that
are contingent on international cooperation, for example bilateral and multilateral agreements, financing or monetary and/or technological transfers. This terminology
is used in the literature and the UNFCCC’s NDC Synthesis Reports, not by the Paris Agreement. {4.2.1, 14.3.2}
28 Two types of gaps are assessed: the implementation gap is calculated as the difference between the median of global emissions in 2030 implied by policies
implemented by the end of 2020 and those implied by NDCs announced prior to COP26. The emissions gap is calculated as the difference between GHG emissions
implied by the NDCs (minimum/maximum emissions in 2030) and the median of global GHG emissions in modelled pathways limiting warming to specific levels
based on immediate action and with stated likelihoods as indicated (Table SPM.2).
29 Original NDCs refer to those submitted to the UNFCCC in 2015 and 2016. Unconditional elements of NDCs announced prior to COP26 imply global GHG emissions
in 2030 that are 3.8 [3.0–5.3] GtCO2-eq yr–1 lower than those from the original NDCs, and 4.5 [2.7–6.3] GtCO2-eq yr–1 lower when conditional elements of NDCs
are included. NDC updates at or after COP26 could further change the implied emissions.
Table SPM.1 | Projected global emissions in 2030 associated with policies implemented by the end of 2020 and NDCs announced prior to COP26,
and associated emissions gaps. *Emissions projections for 2030 and absolute differences in emissions are based on emissions of 52–56 GtCO2-eq yr–1 in 2019 as
assumed in underlying model studies. (medium confidence) {4.2, Table 4.3, Cross-Chapter Box 4 in Chapter 4}
Implied by policies
implemented by
the end of 2020
(GtCO2-eq yr–1)
Implied by NDCs announced prior to COP26
Unconditional elements
(GtCO2-eq yr–1)
Including conditional
elements
(GtCO2-eq yr–1)
Median projected global emissions (min–max)* 57 [52–60] 53 [50–57] 50 [47–55]
Implementation gap between implemented policies
and NDCs (median)
4 7
Emissions gap between NDCs and pathways that limit
warming to 2°C (>67%) with immediate action
10–16 6–14
Emissions gap between NDCs and pathways that limit
warming to 1.5°C (>50%) with no or limited overshoot
with immediate action
19–26 16–23
15
SPM
Summary for Policymakers
B.6.3 Modelled global emission pathways consistent with NDCs announced prior to COP26 that limit warming to 2°C (>67%)
(category C3b in Table SPM.2) imply annual average global GHG emissions reduction rates of 0–0.7 GtCO2-eq yr–1 during the
decade 2020–2030, with an unprecedented acceleration to 1.4–2.0 GtCO2-eq yr–1 during 2030–2050 (medium confidence).
Continued investments in unabated high-emitting infrastructure and limited development and deployment of low-emitting
alternatives prior to 2030 would act as barriers to this acceleration and increase feasibility risks (high confidence). {3.3, 3.5,
3.8, Cross-Chapter Box 5 in Chapter 4}
B.6.4 Modelled global emission pathways consistent with NDCs announced prior to COP26 will likely exceed 1.5°C during the 21st
century. Those pathways that then return warming to 1.5°C by 2100 with a likelihood of 50% or greater imply a temperature
overshoot of 0.15°C–0.3°C (42 pathways in category C2 in Table SPM.2). In such pathways, global cumulative net-negative
CO2 emissions are –380 [–860 to –200] GtCO2
30 in the second half of the century, and there is a rapid acceleration of other
mitigation efforts across all sectors after 2030. Such overshoot pathways imply increased climate-related risk, and are subject to
increased feasibility concerns,31 and greater social and environmental risks, compared to pathways that limit warming to 1.5°C
(>50%) with no or limited overshoot. (high confidence) (Figure SPM.4, Table SPM.2) {3.3, 3.5, 3.8, 12.3; AR6 WGII SPM B.6}
a. Global GHG emissions b. 2030 c. 2050 d. 2100
Projected global GHG emissions from NDCs announced prior to COP26 would make it likely that
warming will exceed 1.5°C and also make it harder after 2030 to limit warming to below 2°C.
10
20
30
0
–10 –10
40
50
60
70
10
20
30
0
40
50
60
70
80 80
GHG emissions (GtCO2-eq yr
–1)
2010 2015 2020 2025 2030 2035 2040 2045 2050
Trend from implemented policies
Modelled pathways:
Limit warming to 2°C (>67%) or return warming to
1.5°C (>50%) after a high overshoot, NDCs until 2030
Limit warming to 1.5°C (>50%) with no or limited overshoot
Past GHG emissions and uncertainty for 2015 and 2019
(dot indicates the median)
Limit warming to 2°C (>67%)
Percentile:
95th
Median
5th
75th
25th
Policy
assessments
for 2030
Policies implemented by the end of 2020
Policy assessments for 2030:
NDCs prior to COP26,
including conditional elements
NDCs prior to COP26,
unconditional elements
88
Figure SPM.4 | Global GHG emissions of modelled pathways (funnels in Panel a, and associated bars in Panels b, c, d) and projected emission
outcomes from near-term policy assessments for 2030 (Panel b).
30 Median and very likely range [5th to 95th percentile].
31 Returning to below 1.5°C in 2100 from GHG emissions levels in 2030 associated with the implementation of NDCs is infeasible for some models due to model-specific
constraints on the deployment of mitigation technologies and the availability of net negative CO2 emissions.
I I '
I -_
i I I
I
I I I
ii
--¥-- I u I
a Ma ------,--- ------,--- ] - E:3
J.++--+]
16
SPM
Summary for Policymakers
Figure SPM.4 (continued): Global GHG emissions of modelled pathways (funnels in Panel a, and associated bars in Panels b, c, d) and projected
emission outcomes from near-term policy assessments for 2030 (Panel b). Panel a shows global GHG emissions over 2015–2050 for four types of assessed
modelled global pathways:
– Trend from implemented policies: Pathways with projected near-term GHG emissions in line with policies implemented until the end of 2020 and extended with
comparable ambition levels beyond 2030 (29 scenarios across categories C5–C7, Table SPM.2).
– Limit to 2°C (>67%) or return warming to 1.5°C (>50%) after a high overshoot, NDCs until 2030: Pathways with GHG emissions until 2030 associated with the
implementation of NDCs announced prior to COP26, followed by accelerated emissions reductions likely to limit warming to 2°C (C3b, Table SPM.2) or to return
warming to 1.5°C with a probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, Table SPM.2).
– Limit to 2°C (>67%) with immediate action: Pathways that limit warming to 2°C (>67%) with immediate action after 202026 (C3a, Table SPM.2).
– Limit to 1.5°C (>50%) with no or limited overshoot: Pathways limiting warming to 1.5°C with no or limited overshoot (C1, Table SPM.2 C1). All these pathways
assume immediate action after 2020.
Past GHG emissions for 2010–2015 used to project global warming outcomes of the modelled pathways are shown by a black line32 and past global GHG emissions in
2015 and 2019 as assessed in Chapter 2 are shown by whiskers. Panels b, c and d show snapshots of the GHG emission ranges of the modelled pathways in 2030,
2050, and 2100, respectively. Panel b also shows projected emissions outcomes from near-term policy assessments in 2030 from Chapter 4.2 (Tables 4.2 and 4.3; median
and full range). GHG emissions are in CO2-equivalent using GWP100 from AR6 WGI. {3.5, 4.2, Table 4.2, Table 4.3, Cross-Chapter Box 4 in Chapter 4}
B.7 Projected cumulative future CO2 emissions over the lifetime of existing and currently planned fossil
fuel infrastructure without additional abatement exceed the total cumulative net CO2 emissions in
pathways that limit warming to 1.5°C (>50%) with no or limited overshoot. They are approximately
equal to total cumulative net CO2 emissions in pathways that limit warming to 2°C (>67%). (high
confidence) {2.7, 3.3}
B.7.1 If historical operating patterns are maintained,33 and without additional abatement,34 estimated cumulative future CO2
emissions from existing fossil fuel infrastructure, the majority of which is in the power sector, would, from 2018 until the end
of its lifetime, amount to 660 [460–890] GtCO2. They would amount to 850 [600–1100] GtCO2 when unabated emissions from
currently planned infrastructure in the power sector is included. These estimates compare with cumulative global net CO2
emissions from all sectors of 510 [330–710] GtCO2 until the time of reaching net zero CO2 emissions35 in pathways that limit
warming to 1.5°C (>50%) with no or limited overshoot, and 890 [640–1160] GtCO2 in pathways that limit warming to 2°C
(>67%). (high confidence) (Table SPM.2) {2.7, Figure 2.26, Figure TS.8}
B.7.2 In modelled global pathways that limit warming to 2°C (>67%) or lower, most remaining fossil fuel CO2 emissions until
the time of global net zero CO2 emissions are projected to occur outside the power sector, mainly in industry and transport.
Decommissioning and reduced utilisation of existing fossil fuel-based power sector infrastructure, retrofitting existing
installations with CCS,36 switches to low-carbon fuels, and cancellation of new coal installations without CCS are major
options that can contribute to aligning future CO2 emissions from the power sector with emissions in the assessed global
modelled least-cost pathways. The most appropriate strategies will depend on national and regional circumstances, including
enabling conditions and technology availability. (high confidence) (Box SPM.1) {Table 2.7, 2.7, 3.4, 6.3, 6.5, 6.7}
32 See Box SPM.1 for a description of the approach to project global warming outcomes of modelled pathways and its consistency with the climate assessment in AR6 WGI.
33 Historical operating patterns are described by load factors and lifetimes of fossil fuel installations as observed in the past (average and range).
34 Abatement here refers to human interventions that reduce the amount of greenhouse gases that are released from fossil fuel infrastructure to the atmosphere.
35 Total cumulative CO2 emissions up to the time of global net zero CO2 emissions are similar but not identical to the remaining carbon budget for a given temperature
limit assessed by Working Group I. This is because the modelled emission scenarios assessed by Working Group III cover a range of temperature levels up to a specific
limit, and exhibit a variety of reductions in non-CO2 emissions that also contribute to overall warming. {Box 3.4}
36 In this context, capture rates of new installations with CCS are assumed to be 90–95%+ {11.3.5}. Capture rates for retrofit installations can be comparable, if plants
are specifically designed for CCS retrofits {11.3.6}.
17
SPM
Summary for Policymakers
C. System Transformations to Limit Global Warming
37 All reported warming levels are relative to the period 1850–1900. If not otherwise specified, ‘pathways’ always refer to pathways computed with a model.
Immediate action in the pathways refers to the adoption of climate policies between 2020 and at latest 2025 intended to limit global warming at a given level.
38 Long-term warming is calculated from all modelled pathways assuming mitigation efforts consistent with national policies that were implemented by the end of
2020 (scenarios that fall into policy category P1b of Chapter 3) and that pass through the 2030 GHG emissions ranges of such pathways assessed in Chapter 4
(see footnote 25). {3.2, Table 4.2}
39 Warming estimates refer to the 50th and [5th–95th] percentile across the modelled pathways and the median temperature change estimate of the probabilistic WGI
climate model emulators (see Table SPM.2 footnote a).
40 In this report, emissions reductions are reported relative to 2019 modelled emission levels, while in SR1.5 emissions reductions were calculated relative to 2010.
Between 2010 and 2019 global GHG and global CO2 emissions have grown by 12% (6.5 GtCO2-eq) and 13% (5.0 GtCO2) respectively. In global modelled
pathways assessed in this report that limit warming to 1.5°C (>50%) with no or limited overshoot, GHG emissions are projected to be reduced by 37% [28–57%]
in 2030 relative to 2010. In the same type of pathways assessed in SR1.5, reported GHG emissions reductions in 2030 were 39–51% (interquartile range) relative
to 2010. In absolute terms, the 2030 GHG emissions levels of pathways that limit warming to 1.5°C (>50%) with no or limited overshoot are higher in AR6
(31 [21–36] GtCO2-eq) than in SR1.5 (28 (26–31 interquartile range) GtCO2-eq). (Figure SPM.1, Table SPM.2) {3.3, SR1.5 Figure SPM.3b}
41 Scenarios in this category limit peak warming to 2°C throughout the 21st century with close to, or more than, 90% likelihood.
42 This category contains 91 scenarios with immediate action and 42 scenarios that are consistent with the NDCs until 2030.
43 These numbers for CH4, N2O, and F-gases are rounded to the nearest 5% except numbers below 5%.
C.1 Global GHG emissions are projected to peak between 2020 and at the latest before 2025 in global
modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot and in those that
limit warming to 2°C (>67%) and assume immediate action (see Table SPM.2 footnote i). 37 In both
types of modelled pathways, rapid and deep GHG emissions reductions follow throughout 2030, 2040
and 2050 (high confidence). Without a strengthening of policies beyond those that are implemented by
the end of 2020, GHG emissions are projected to rise beyond 2025, leading to a median global warming
of 3.2 [2.2 to 3.5] °C by 210038, 39 (medium confidence). (Table SPM.2, Figure SPM.4, Figure SPM.5)
{3.3, 3.4}
C.1.1 Net global GHG emissions are projected to fall from 2019 levels by 27% [13–45%] by 2030 and 63% [52–76%]40 by 2050 in
global modelled pathways that limit warming to 2°C (>67%) and assuming immediate action (category C3a, Table SPM.2).
This compares with reductions of 43% [34–60%] by 2030 and 84% [73–98%] by 2050 in pathways that limit warming to
1.5°C (>50%) with no or limited overshoot (C1, Table SPM.2) (high confidence).41 In modelled pathways that return warming
to 1.5°C (>50%) after a high overshoot,42 GHG emissions are reduced by 23% [0–44%] in 2030 and by 75% [62–91%] in
2050 (C2, Table SPM.2) (high confidence). Modelled pathways that are consistent with NDCs announced prior to COP26
until 2030 and assume no increase in ambition thereafter have higher emissions, leading to a median global warming of
2.8 [2.1–3.4] °C by 2100 (medium confidence).23 (Figure SPM.4) {3.3}
C.1.2 In modelled pathways that limit warming to 2°C (>67%) assuming immediate action, global net CO2 emissions are reduced
compared to modelled 2019 emissions by 27% [11–46%] in 2030 and by 52% [36–70%] in 2040; and global CH4 emissions are
reduced by 24% [9–53%] in 2030 and by 37% [20–60%] in 2040. In pathways that limit warming to 1.5°C (>50%) with no or
limited overshoot global net CO2 emissions are reduced compared to modelled 2019 emissions by 48% [36–69%] in 2030 and
by 80% [61–109%] in 2040; and global CH4 emissions are reduced by 34% [21–57%] in 2030 and 44% [31–63%] in 2040.
There are similar reductions of non-CO2 emissions by 2050 in both types of pathways: CH4 is reduced by 45% [25–70%];
N2O is reduced by 20% [–5 to +55%]; and F-gases are reduced by 85% [20–90%].43 Across most modelled pathways, this is the
maximum technical potential for anthropogenic CH4 reductions in the underlying models (high confidence). Further emissions
reductions, as illustrated by the IMP-SP pathway, may be achieved through changes in activity levels and/or technological
innovations beyond those represented in the majority of the pathways (medium confidence). Higher emissions reductions of
CH4 could further reduce peak warming. (high confidence) (Figure SPM.5) {3.3}
C.1.3 In modelled pathways consistent with the continuation of policies implemented by the end of 2020, GHG emissions continue to
rise, leading to global warming of 3.2 [2.2–3.5] °C by 2100 (within C5–C7, Table SPM.2) (medium confidence). Pathways that
exceed warming of >4°C (≥50%) (C8, SSP5-8.5, Table SPM.2) would imply a reversal of current technology and/or mitigation
policy trends (medium confidence). Such warming could occur in emission pathways consistent with policies implemented
by the end of 2020 if climate sensitivity is higher than central estimates (high confidence). (Table SPM.2, Figure SPM.4)
{3.3, Box 3.3}
18
SPM
Summary for Policymakers
Table SPM.2 | Key characteristics of the modelled global emissions pathways. Summary of projected CO2 and GHG emissions, projected net zero timings and the resulting global warming outcomes. Pathways are categorised
(rows), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels. Values shown are for the median [p50] and 5th–95th percentiles [p5–p95], noting
that not all pathways achieve net zero CO2 or GHGs.
p50
[p5–p95] a
GHG emissions
(GtCO2-eq yr–1) g
GHG emissions reductions
from 2019
(%) h
Emissions milestones i, j Cumulative CO2
emissions (GtCO2)
m
Cumulative
net-negative
CO2
emissions
(GtCO2)
Global mean
temperature changes
50% probability
(°C) n
Likelihood of peak global
warming staying below (%) o
Category b, c, d
[# pathways]
Category/subset label
WGI SSP
& WGIII
IPs/IMPs
alignmente, f
2030 2040 2050 2030 2040 2050
Peak CO2
emissions
(% peak
before 2100)
Peak GHG
emissions
(% peak
before 2100)
Net zero CO2
(% net zero
pathways)
Net zero
GHGs
(% net zero
pathways) k, l
2020 to
net zero
CO2
2020–2100
Year of
net zero CO2
to 2100
at peak
warming
2100 <1.5°C <2.0°C <3.0°C
Modelled global emissions pathways categorised
by projected global warming levels (GWL). Detailed
likelihood definitions are provided in SPM Box 1.
The five illustrative scenarios (SSPx-yy) considered by
AR6 WGI and the Illustrative (Mitigation) Pathways
assessed in WGIII are aligned with the temperature
categories and are indicated in a separate column.
Global emission pathways contain regionally
differentiated information. This assessment
focuses on their global characteristics.
Projected median annual GHG
emissions in the year across the
scenarios, with the 5th–95th
percentile in brackets.
Modelled GHG emissions in 2019:
55 [53–58] GtCO2-eq.
Projected median GHG emissions
reductions of pathways in the year
across the scenarios compared to
modelled 2019, with the 5th–95th
percentile in brackets. Negative
numbers indicate increase in
emissions compared to 2019.
Median 5-year intervals at
which projected CO2 & GHG
emissions peak, with the
5th–95th percentile interval in
square brackets. Percentage of
peaking pathways is denoted
in round brackets.
Three dots (…) denotes
emissions peak in 2100 or
beyond for that percentile.
Median 5-year intervals at
which projected CO2 & GHG
emissions of pathways in
this category reach net zero,
with the 5th–95th percentile
interval in square brackets.
Percentage of net zero
pathways is denoted in round
brackets.
Three dots (…) denotes
net zero not reached for
that percentile.
Median cumulative net
CO2 emissions across
the projected scenarios
in this category until
reaching net zero or until
2100, with the 5th–95th
percentile interval
in square brackets.
Median
cumulative
net-negative
CO2 emissions
between
the year of
net zero CO2
and 2100. More
net-negative
results in
greater
temperature
declines
after peak.
Projected temperature
change of pathways
in this category (50%
probability across
the range of climate
uncertainties), relative
to 1850–1900, at peak
warming and in 2100,
for the median value
across the scenarios
and the 5th–95th
percentile interval in
square brackets.
Median likelihood that the
projected pathways in this category
stay below a given global warming
level, with the 5th–95th percentile
interval in square brackets.
C1 [97]
limit warming to
1.5°C (>50%) with no
or limited overshoot
31
[21–36]
17
[6–23]
9
[1–15]
43
[34–60]
69
[58–90]
84
[73–98]
2020–2025 (100%)
[2020–2025]
2050–2055
(100%)
[2035–2070]
2095–2100
(52%)
[2050–...]
510
[330–710]
320
[–210 to
570]
–220
[–660 to –20]
1.6
[1.4–1.6]
1.3
[1.1–1.5]
38
[33–58]
90
[86–97]
100
[99–100]
C1a [50]
… with net zero
GHGs
SSP1–1.9,
SP
LD
33
[22–37]
18
[6–24]
8
[0–15]
41
[31–59]
66
[58–89]
85
[72–100]
2070–2075
(100%)
[2050–2090]
550
[340–760]
160
[–220 to
620]
–360
[–680 to
–140]
1.6
[1.4–1.6]
1.2
[1.1–1.4]
38
[34–60]
90
[85–98]
100
[99–100]
C1b [47]
… without net zero
GHGs
Ren
29
[21–36]
16
[7–21]
9
[4–13]
48
[35–61]
70
[62–87]
84
[76–93]
…–… [0%] 460
[320–590]
360
[10–540]
–60
[–440 to 0]
1.6
[1.5–1.6]
1.4
[1.3–1.5]
37
[33–56]
89
[87–96]
100
[…–…] [99–100]
C2 [133]
return warming to
1.5°C (>50%) after
a high overshoot
Neg
42
[31–55]
25
[17–34]
14
[5–21]
23
[0–44]
55
[40–71]
75
[62–91]
2020–2025 (100%)
2055–2060
(100%)
[2045–2070]
2070–2075
(87%)
[2055–...]
720
[530–930]
400
[–90 to
620]
–360
[–680 to –60]
1.7
[1.5–1.8]
1.4
[1.2–1.5]
24
[15–42]
82
[71–93]
100
[2020–2030] [2020–2025] [99–100]
C3 [311]
limit warming
to 2°C (>67%)
44
[32–55]
29
[20–36]
20
[13–26]
21
[1–42]
46
[34–63]
64
[53–77]
2020–2025 (100%)
2070–2075
(93%)
[2055–...]
...–... (30%)
[2075–...]
890
[640–1160]
800
[510–1140]
–40
[–290 to 0]
1.7
[1.6–1.8]
1.6
[1.5–1.8]
20
[13–41]
76
[68–91]
99
[98–100]
[2020–2030] [2020–2025]
C3a [204]
… with action
starting in 2020
SSP1–2.6
40
[30–49]
29
[21–36]
20
[14–27]
27
[13–45]
47
[35–63]
63
[52–76]
2020–2025 (100%)
[2020–2025]
2070–2075
(91%)
[2055–...]
...–... (24%)
[2080–...]
860
[640–1180]
790
[480–1150]
–30
[–280 to 0]
1.7
[1.6–1.8]
1.6
[1.5–1.8]
21
[14–42]
78
[69–91]
100
[98–100]
19
SPM
Summary for Policymakers
p50
[p5–p95] a
GHG emissions
(GtCO2-eq yr–1) g
GHG emissions reductions
from 2019
(%) h
Emissions milestones i, j Cumulative CO2
emissions (GtCO2)
m
Cumulative
net-negative
CO2
emissions
(GtCO2)
Global mean
temperature changes
50% probability
(°C) n
Likelihood of peak global
warming staying below (%) o
Category b, c, d
[# pathways]
Category/subset label
WGI SSP
& WGIII
IPs/IMPs
alignmente, f
2030 2040 2050 2030 2040 2050
Peak CO2
emissions
(% peak
before 2100)
Peak GHG
emissions
(% peak
before 2100)
Net zero CO2
(% net zero
pathways)
Net zero
GHGs
(% net zero
pathways) k, l
2020 to
net zero
CO2
2020–2100
Year of
net zero CO2
to 2100
at peak
warming
2100 <1.5°C <2.0°C <3.0°C
Modelled global emissions pathways categorised
by projected global warming levels (GWL). Detailed
likelihood definitions are provided in SPM Box 1.
The five illustrative scenarios (SSPx-yy) considered by
AR6 WGI and the Illustrative (Mitigation) Pathways
assessed in WGIII are aligned with the temperature
categories and are indicated in a separate column.
Global emission pathways contain regionally
differentiated information. This assessment
focuses on their global characteristics.
Projected median annual GHG
emissions in the year across the
scenarios, with the 5th–95th
percentile in brackets.
Modelled GHG emissions in 2019:
55 [53–58] GtCO2-eq.
Projected median GHG emissions
reductions of pathways in the year
across the scenarios compared to
modelled 2019, with the 5th–95th
percentile in brackets. Negative
numbers indicate increase in
emissions compared to 2019.
Median 5-year intervals at
which projected CO2 & GHG
emissions peak, with the
5th–95th percentile interval in
square brackets. Percentage of
peaking pathways is denoted
in round brackets.
Three dots (…) denotes
emissions peak in 2100 or
beyond for that percentile.
Median 5-year intervals at
which projected CO2 & GHG
emissions of pathways in
this category reach net zero,
with the 5th–95th percentile
interval in square brackets.
Percentage of net zero
pathways is denoted in round
brackets.
Three dots (…) denotes
net zero not reached for
that percentile.
Median cumulative net
CO2 emissions across
the projected scenarios
in this category until
reaching net zero or until
2100, with the 5th–95th
percentile interval
in square brackets.
Median
cumulative
net-negative
CO2 emissions
between
the year of
net zero CO2
and 2100. More
net-negative
results in
greater
temperature
declines
after peak.
Projected temperature
change of pathways
in this category (50%
probability across
the range of climate
uncertainties), relative
to 1850–1900, at peak
warming and in 2100,
for the median value
across the scenarios
and the 5th–95th
percentile interval in
square brackets.
Median likelihood that the
projected pathways in this category
stay below a given global warming
level, with the 5th–95th percentile
interval in square brackets.
C3b [97] … NDCs until 2030 GS
52
[47–56]
29
[20–36]
18
[10–25]
5
[0–14]
46
[34–63]
68
[56–82]
2020–2025 (100%)
[2020–2030]
2065–2070
(97%)
[2055–2090]
...–... (41%)
[2075–...]
910
[720–1150]
800
[560–1050]
–60
[–300 to 0]
1.8
[1.6–1.8]
1.6
[1.5–1.7]
17
[12–35]
73
[67–87]
99
[98–99]
C4 [159]
limit warming
to 2°C (>50%)
50
[41–56]
38
[28–44]
28
[19–35]
10
[0–27]
31
[20–50]
49
[35–65]
2080–2085
(86%)
[2065–...]
...–... (31%)
[2075–...]
1210
[970–1490]
1160
[700–1490]
–30
[–390 to 0]
1.9
[1.7–2.0]
1.8
[1.5–2.0]
11
[7–22]
59
[50–77]
98
[95–99]
C5 [212]
limit warming
to 2.5°C (>50%)
52
[46–56]
45
[37–53]
39
[30–49]
6
[–1 to 18]
18
[4–33]
29
[11–48]
...–... (41%)
[2080–...]
...–... (12%)
[2090–...]
1780
[1400–
2360]
1780
[1260–
2360]
0
[–160 to 0]
2.2
[1.9–2.5]
2.1
[1.9–2.5]
4
[0–10]
37
[18–59]
91
[83–98]
C6 [97]
limit warming
to 3°C (>50%)
SSP2–4.5
ModAct
54
[50–62]
53
[48–61]
52
[45–57]
2
[–10 to
11]
3
[–14 to
14]
5
[–2 to 18]
2030–2035
(96%)
2020–2025
(97%)
no net zero no net zero
2790
[2440–
3520]
no net zero
temperature
does not
peak by
2100
2.7
[2.4–2.9]
0
[0–0]
8
[2–18]
71
[53–88]
[2020–2090]
C7 [164]
limit warming
to 4°C (>50%)
SSP3–7.0
CurPol
62
[53–69]
67
[56–76]
70
[58–83]
–11
[–18 to 3]
–19
[–31 to 1]
–24
[–41 to
–2]
2085–2090
(57%)
2090–2095
(56%)
4220
[3160–
5000]
3.5
[2.8–3.9]
0
[0–0]
0
[0–2]
22
[7–60]
[2040–...]
C8 [29]
exceed warming
of 4°C (≥50%)
SSP5–8.5
71
[69–81]
80
[78–96]
88
[82–112]
–20
[–34 to
–17]
–35
[–65 to
–29]
–46
[–92 to
–36]
2080–2085 (90%)
[2070–...]
5600
4.2
[3.7–5.0]
0
[0–0]
0
[0–0]
4
[0–11]
[4910–
7450]
Table SPM.2 (continued):
20
SPM
Summary for Policymakers
Table SPM.2 (continued):
a Values in the table refer to the 50th and [5th–95th] percentile values across the pathways falling within a given category as defined in Box SPM.1. For emissions-related
columns these values relate to the distribution of all the pathways in that category. Harmonised emissions values are given for consistency with projected global
warming outcomes using climate emulators. Based on the assessment of climate emulators in AR6 WGI (WG1 Chapter 7, Box 7.1), two climate emulators are used for
the probabilistic assessment of the resulting warming of the pathways. For the ‘Temperature change’ and ‘Likelihood’ columns, the single upper-row values represent
the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model
emulator. For the bracketed ranges, the median warming for every pathway in that category is calculated for each of the two climate model emulators (MAGICC and
FaIR). Subsequently, the 5th and 95th percentile values across all pathways for each emulator are calculated. The coolest and warmest outcomes (i.e., the lowest p5 of
two emulators, and the highest p95, respectively) are shown in square brackets. These ranges therefore cover both the uncertainty of the emissions pathways as well as
the climate emulators’ uncertainty.
b For a description of pathways categories see Box SPM.1.
c All global warming levels are relative to 1850–1900. (See footnote n below and Box SPM.145 for more details.)
d C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in Figure SPM.4. Two pathways derived from a cost-benefit
analysis have been added to C3a, whilst 10 pathways with specifically designed near-term action until 2030, whose emissions fall below those implied by NDCs
announced prior to COP26, are not included in either of the two subsets.
e Alignment with the categories of the illustrative SSP scenarios considered in AR6 WGI, and the Illustrative (Mitigation) Pathways (IPs/IMPs) of WGIII. The IMPs have
common features such as deep and rapid emissions reductions, but also different combinations of sectoral mitigation strategies. See Box SPM.1 for an introduction of
the IPs and IMPs, and Chapter 3 for full descriptions. {3.2, 3.3, Annex III.II.4}
f The Illustrative Mitigation Pathway ‘Neg’ has extensive use of carbon dioxide removal (CDR) in the AFOLU, energy and the industry sectors to achieve net negative
emissions. Warming peaks around 2060 and declines to below 1.5°C (50% likelihood) shortly after 2100. Whilst technically classified as C3, it strongly exhibits the
characteristics of C2 high-overshoot pathways, hence it has been placed in the C2 category. See Box SPM.1 for an introduction of the IPs and IMPs.
g The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO2-eq] is within the uncertainty ranges of 2019 emissions assessed in Chapter 2
[53–66 GtCO2-eq].49 (Figure SPM.1, Figure SPM.2, Box SPM.1)
h Rates of global emission reduction in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019
rather than the global emissions reported in SPM Section B and Chapter 2; this ensures internal consistency in assumptions about emission sources and activities, as well
as consistency with temperature projections based on the physical climate science assessment by WGI.49 {Annex III.II.2.5}. Negative values (e.g., in C7, C8) represent an
increase in emissions.
i Emissions milestones are provided for five-year intervals in order to be consistent with the underlying five-year time-step data of the modelled pathways. Peak emissions
(CO2 and GHGs) are assessed for five-year reporting intervals starting in 2020. The interval 2020–2025 signifies that projected emissions peak as soon as possible
between 2020 and at latest before 2025. The upper five-year interval refers to the median interval within which the emissions peak or reach net zero. Ranges in
square brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile five-year interval and the upper bound of the
95th percentile five-year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones.
j Percentiles reported across all pathways in that category include those that do not reach net zero before 2100 (fraction of pathways reaching net zero is given in round
brackets). If the fraction of pathways that reach net zero before 2100 is lower than the fraction of pathways covered by a percentile (e.g., 0.95 for the 95th percentile),
the percentile is not defined and denoted with ‘…’. The fraction of pathways reaching net zero includes all with reported non-harmonised, and/or harmonised emissions
profiles that reach net zero. Pathways were counted when at least one of the two profiles fell below 100 MtCO2 yr–1 until 2100.
k The timing of net zero is further discussed in SPM C2.4 and Cross-Chapter Box 3 in Chapter 3 on net zero CO2 and net zero GHG emissions.
l For cases where models do not report all GHGs, missing GHG species are infilled and aggregated into a Kyoto basket of GHG emissions in CO2-eq defined by the
100-year global warming potential. For each pathway, reporting of CO2, CH4, and N2O emissions was the minimum required for the assessment of the climate response
and the assignment to a climate category. Emissions pathways without climate assessment are not included in the ranges presented here. {See Annex III.II.5}
m Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO2 emissions, ensuring
consistency with the WGI assessment of the remaining carbon budget.50 {Box 3.4}
n Global mean temperature change for category (at peak, if peak temperature occurs before 2100, and in 2100) relative to 1850–1900, based on the median global
warming for each pathway assessed using the probabilistic climate model emulators calibrated to the AR6 WGI assessment.12 (See also Box SPM.1) {Annex III.II.2.5;
WGI Cross-Chapter Box 7.1}
o Probability of staying below the temperature thresholds for the pathways in each category, taking into consideration the range of uncertainty from the climate model
emulators consistent with the AR6 WGI assessment. The probabilities refer to the probability at peak temperature. Note that in the case of temperature overshoot
(e.g., category C2 and some pathways in C1), the probabilities of staying below at the end of the century are higher than the probabilities at peak temperature.
21
SPM
Summary for Policymakers
C.1.4 Global modelled pathways falling into the lowest temperature category of the assessed literature (C1, Table SPM.2) are on
average associated with a higher median peak warming in AR6 compared to pathways in the same category in SR1.5. In the
modelled pathways in AR6, the likelihood of limiting warming to 1.5°C has on average declined compared to SR1.5. This is
because GHG emissions have risen since 2017, and many recent pathways have higher projected emissions by 2030, higher
cumulative net CO2 emissions and slightly later dates for reaching net zero CO2 or net zero GHG emissions. High mitigation
challenges, for example, due to assumptions of slow technological change, high levels of global population growth, and high
fragmentation as in the Shared Socio-economic Pathway SSP3, may render modelled pathways that limit warming to 2°C
(>67%) or lower infeasible. (medium confidence) (Table SPM.2, Box SPM.1) {3.3, 3.8, Annex III Figure II.1, Annex III Figure II.3}
Box SPM.1 | Assessment of Modelled Global Emission Scenarios
A wide range of modelled global emission pathways and scenarios from the literature is assessed in this report, including
pathways and scenarios with and without mitigation.44 Emissions pathways and scenarios project the evolution of GHG
emissions based on a set of internally consistent assumptions about future socio-economic conditions and related mitigation
measures.45 These are quantitative projections and are neither predictions nor forecasts. Around half of all modelled global
emission scenarios assume cost-effective approaches that rely on least-cost emission abatement options globally. The other
half look at existing policies and regionally and sectorally differentiated actions. Most do not make explicit assumptions about
global equity, environmental justice or intra-regional income distribution. Global emission pathways, including those based
on cost-effective approaches, contain regionally differentiated assumptions and outcomes, and have to be assessed with the
careful recognition of these assumptions. This assessment focuses on their global characteristics. The majority of the assessed
scenarios (about 80%) have become available since the SR1.5, but some were assessed in that report. Scenarios with and
without mitigation were categorised based on their projected global warming over the 21st century, following the same scheme
as in the SR1.5 for warming up to and including 2°C. {1.5, 3.2, 3.3, Annex III.II.2, Annex III.II.3}
Scenario categories are defined by their likelihood of exceeding global warming levels (at peak and in 2100) and referred
to in this report as follows:46,47
• Category C1 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a likelihood of greater than 50%,
and reach or exceed warming of 1.5°C during the 21st century with a likelihood of 67% or less. In this report, these scenarios
are referred to as scenarios that limit warming to 1.5°C (>50%) with no or limited overshoot. Limited overshoot refers to
exceeding 1.5°C global warming by up to about 0.1°C and for up to several decades.48
• Category C2 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a likelihood of greater than 50%,
and exceed warming of 1.5°C during the 21st century with a likelihood of greater than 67%. In this report, these scenarios
are also referred to as scenarios that return warming to 1.5°C (>50%) after a high overshoot. High overshoot refers to
temporarily exceeding 1.5°C global warming by 0.1°C–0.3°C for up to several decades.
• Category C3 comprises modelled scenarios that limit peak warming to 2°C throughout the 21st century with a likelihood of
greater than 67%. In this report, these scenarios are also referred to as scenarios that limit warming to 2°C (>67%).
• Categories C4, C5, C6 and C7 comprise modelled scenarios that limit warming to 2°C, 2.5°C, 3°C, 4°C, respectively,
throughout the 21st century with a likelihood of greater than 50%. In some scenarios in C4 and many scenarios in C5–C7,
warming continues beyond the 21st century.
44 In the literature, the terms ‘pathways’ and ‘scenarios’ are used interchangeably, with the former more frequently used in relation to climate goals. For this reason,
this SPM uses mostly the term (emissions and mitigation) pathways. {Annex III.II.1.1}
45 Key assumptions relate to technology development in agriculture and energy systems and socio-economic development, including demographic and economic
projections. IPCC is neutral with regard to the assumptions underlying the scenarios in the literature assessed in this report, which do not cover all possible
futures. Additional scenarios may be developed. The underlying population assumptions range from 8.5 to 9.7 billion in 2050 and 7.4 to 10.9 billion in 2100
(5–95th percentile) starting from 7.6 billion in 2019. The underlying assumptions on global GDP growth (ppp) range from 2.5 to 3.5% per year in the 2019–2050
period and 1.3 to 2.1% per year in the 2050–2100 (5–95th percentile). Many underlying assumptions are regionally differentiated. {1.5; 3.2; 3.3; Figure 3.9;
Annex III.II.1.4; Annex III.II.3}
46 The future scenario projections presented here are consistent with the total observed increase in global surface temperature between 1850–1900 and 1995–2014
as well as to 2011–2020 (with best estimates of 0.85°C and 1.09°C, respectively) assessed in WGI. The largest contributor to historical human-induced warming is CO2,
with historical cumulative CO2 emissions from 1850 to 2019 being 2400 ± 240 GtCO2. {WGI SPM A.1.2, WGI Table SPM.2, WGI Table 5.1, WGIII SPM Section B}.
47 In case no explicit likelihood is provided, the reported warming levels are associated with a likelihood of >50%.
48 Scenarios in this category are found to have simultaneous likelihood to limit peak global warming to 2°C throughout the 21st century of close to and more than 90%.
22
SPM
Summary for Policymakers
Box SPM.1 (continued)
• Category C8 comprises modelled scenarios that exceed warming of 4°C during the 21st century with a likelihood of 50% or
greater. In these scenarios warming continues to rise beyond the 21st century.
Categories of modelled scenarios are distinct and do not overlap; they do not contain categories consistent with lower levels of
global warming, for example, the category of C3 scenarios that limit warming to 2°C (>67%) does not include the C1 and C2
scenarios that limit or return warming to 1.5°C (>50%). Where relevant, scenarios belonging to the group of categories C1–C3
are referred to in this report as scenarios that limit warming to 2°C (>67%) or lower.
Methods to project global warming associated with the scenarios were updated to ensure consistency with the AR6 WGI
assessment of physical climate science.49 {3.2, Annex III.II.2.5; AR6 WGI Cross-Chapter Box 7.1}
49 This involved improved methodologies to use climate emulators (MAGICC7 and FAIR v1.6), which were evaluated and calibrated to closely match the global
warming response to emissions as assessed in AR6 WGI. It included harmonisation of global GHG emissions in 2015 in modelled scenarios (51–56 GtCO2-eq;
5th to 95th percentiles) with the corresponding emission value underlying the CMIP6 projected climate response assessed by WGI (54 GtCO2-eq), based on similar
data sources of historical emissions that are updated over time. The assessment of past GHG emissions in Chapter 2 of the report is based on a more recent
dataset providing emissions of 57 [±6.3] GtCO2-eq in 2015 (B.1). Differences are well within the assessed uncertainty range, and arise mainly from differences
in estimated CO2-LULUCF emissions, which are subject to large uncertainties, high annual variability and revisions over time. Projected rates of global emission
reduction in mitigation scenarios are reported relative to modelled global emissions in 2019 rather than the global emissions reported in Chapter 2; this ensures
internal consistency in assumptions about emission sources and activities, as well as consistency with temperature projections based on the physical climate science
assessment by WG I. {Annex III.II.2.5}
The range of assessed scenarios results in a range of 21st century projected global warming.
a. Median global warming across scenarios in categories C1 to C8
b. Peak and 2100 global warming across
scenario categories, IMPs and SSPx-y
scenarios considered by AR6 WGI
Global warming relative to 1850–1900 (°C)
Scenario categories, IMPs and SSPx-y scenarios
C1 C2
C3 C4
C5
C6
C8
2020 2030 2040 2050 2060 2070 2080 2090 2100
0
1
2
3
4
5
6
0
1
2
3
4
5
6
C1
C2
C3
C4
C5
C6
C7
C8
Scenario range within category:
5–95% across medians of scenarios
Median within category
IMP
SSPx-y
filled: Peak warming (over the 21st century)
open: 2100 warming
Climate & scenario uncertainty:
5–95% across scenarios
of 5–95% 2100 warming
Scenario range within
category: 5–95% across
medians of scenarios
C8
C7
C6
C5
C4
C3
C2
C1
IMP-SP
IMP-LD
IMP-Ren
SSP1-1.9
IMP-Neg
IMP-GS
SSP1-2.6
ModAct
SSP2-4.5
CurPol
SSP3-7.0
SSP5-8.5
C7
Box SPM.1, Figure 1 | Projected global mean warming of the ensemble of modelled scenarios included in the climate categories C1–C8
and IMPs (based on emulators calibrated to the WGI assessment), as well as five illustrative scenarios (SSPx-y) as considered by AR6 WGI.
Panel a shows the p5–p95 range of projected median warming across global modelled pathways within a category, with the category medians (line).
Panel b shows the peak and 2100 emulated temperature outcomes for the categories C1 to C8 and for IMPs, and the five illustrative scenarios (SSPx-y)
as considered by AR6 WGI. The boxes show the p5–p95 range within each scenario category, as in panel a. The combined p5–p95 range across scenarios and
the climate uncertainty for each category C1–C8 is also shown for 2100 warming (thin vertical lines). (Table SPM.2) {Figure 3.11; AR6 WGI Figure SPM.8}
E3
■ ■ ■• Cl
a
□- 0@
23
SPM
Summary for Policymakers
Box SPM.1 (continued)
These updated methods affect the categorisation of some scenarios. On average across scenarios, peak global warming is
projected to be lower by up to about 0.05 [±0.1] °C than if the same scenarios were evaluated using the SR1.5 methodology,
and global warming in 2100 is projected to be lower by about 0.1 [±0.1] °C. {Annex III.II.2.5.1, Annex III Figure II.3}
Resulting changes to the emission characteristics of scenario categories described in Table SPM.2 interact with changes in
the characteristics of the wider range of emission scenarios published since the SR1.5. Proportionally more scenarios assessed
in AR6 are designed to limit temperature overshoot and more scenarios limit large-scale net negative CO2 emissions than in
SR1.5. As a result, AR6 scenarios in the lowest temperature category (C1) generally reach net zero GHG emissions later in the
21st century than scenarios in the same category assessed in SR1.5, and about half do not reach net zero GHG by 2100. The rate
of decline of GHG emissions in the near term by 2030 in category C1 scenarios is very similar to the assessed rate in SR1.5, but
absolute GHG emissions of category C1 scenarios in AR6 are slightly higher in 2030 than in SR1.5, since the reductions start from
a higher emissions level in 2020. (Table SPM.2) {Annex III, 2.5, 3.2, 3.3}
The large number of global emissions scenarios assessed, including 1202 scenarios with projected global warming outcomes
using climate emulators, come from a wide range of modelling approaches. They include the five illustrative scenarios (Shared
Socio-economic Pathways; SSPs) assessed by WGI for their climate outcomes but cover a wider and more varied set in terms
of assumptions and modelled outcomes. For this assessment, Illustrative Mitigation Pathways (IMPs) were selected from this
larger set to illustrate a range of different mitigation strategies that would be consistent with different warming levels. The IMPs
illustrate pathways that achieve deep and rapid emissions reductions through different combinations of mitigation strategies.
The IMPs are not intended to be comprehensive and do not address all possible themes in the underlying report. They differ in
terms of their focus, for example, placing greater emphasis on renewables (IMP-Ren), deployment of carbon dioxide removal
that results in net negative global GHG emissions (IMP-Neg), and efficient resource use as well as shifts in consumption patterns
globally, leading to low demand for resources, while ensuring a high level of services and satisfying basic needs (IMP-LD) (Figure
SPM.5). Other IMPs illustrate the implications of a less rapid introduction of mitigation measures followed by a subsequent
gradual strengthening (IMP-GS), and how shifting global pathways towards sustainable development, including by reducing
inequality, can lead to mitigation (IMP-SP). The IMPs reach different climate goals as indicated in Table SPM.2 and Box SPM.1,
Figure 1. {1.5, 3.1, 3.2, 3.3, 3.6, Figure 3.7, Figure 3.8, Box 3.4, Annex III.II.2.4}
C.2 Global net zero CO2 emissions are reached in the early 2050s in modelled pathways that limit warming
to 1.5°C (>50%) with no or limited overshoot, and around the early 2070s in modelled pathways
that limit warming to 2°C (>67%). Many of these pathways continue to net negative CO2 emissions
after the point of net zero. These pathways also include deep reductions in other GHG emissions. The
level of peak warming depends on cumulative CO2 emissions until the time of net zero CO2 and the
change in non-CO2 climate forcers by the time of peaking. Deep GHG emissions reductions by 2030
and 2040, particularly reductions of methane emissions, lower peak warming, reduce the likelihood
of overshooting warming limits and lead to less reliance on net negative CO2 emissions that reverse
warming in the latter half of the century. Reaching and sustaining global net zero GHG emissions results
in a gradual decline in warming. (high confidence) (Table SPM.2) {3.3, 3.5, Box 3.4, Cross-Chapter Box 3
in Chapter 3, AR6 WGI SPM D1.8}
C.2.1 Modelled global pathways limiting warming to 1.5°C (>50%) with no or limited overshoot are associated with projected
cumulative net CO2 emissions50 until the time of net zero CO2 of 510 [330–710] GtCO2. Pathways limiting warming to 2°C
(>67%) are associated with 890 [640–1160] GtCO2 (Table SPM.2). (high confidence) {3.3, Box 3.4}
C.2.2 Modelled global pathways that limit warming to 1.5°C (>50%) with no or limited overshoot involve more rapid and deeper
near-term GHG emissions reductions through to 2030, and are projected to have less net negative CO2 emissions and less
carbon dioxide removal (CDR) in the longer term, than pathways that return warming to 1.5°C (>50%) after a high overshoot
(C2 category). Modelled pathways that limit warming to 2°C (>67%) have on average lower net negative CO2 emissions
compared to pathways that limit warming to 1.5°C (>50%) with no or limited overshoot and pathways that return warming
50 Cumulative net CO2 emissions from the beginning of the year 2020 until the time of net zero CO2 in assessed pathways are consistent with the remaining carbon
budgets assessed by WGI, taking account of the ranges in the WGIII temperature categories and warming from non-CO2 gases. {Box 3.4}
24
SPM
Summary for Policymakers
to 1.5°C (>50%) after a high overshoot (C1 and C2 categories respectively). Modelled pathways that return warming to
1.5°C (>50%) after a high overshoot (C2 category) show near-term GHG emissions reductions similar to pathways that
limit warming to 2°C (>67%) (C3 category). For a given peak global warming level, greater and more rapid near-term
GHG emissions reductions are associated with later net zero CO2 dates. (high confidence) (Table SPM.2) {3.3, Table 3.5,
Cross-Chapter Box 3 in Chapter 3, Annex I: Glossary}
C.2.3 Future non-CO2 warming depends on reductions in non-CO2 GHGs, aerosols and their precursors, and ozone precursor
emissions. In modelled global low-emission pathways, the projected reduction of cooling and warming aerosol emissions
over time leads to net warming in the near- to mid-term. In these mitigation pathways, the projected reductions of cooling
aerosols are mostly due to reduced fossil fuel combustion that was not equipped with effective air pollution controls. Non-CO2
GHG emissions at the time of net zero CO2 are projected to be of similar magnitude in modelled pathways that limit warming
to 2°C (>67%) or lower. These non-CO2 GHG emissions are about 8 [5–11] GtCO2-eq yr–1, with the largest fraction from CH4
(60% [55–80%]), followed by N2O (30% [20–35%]) and F-gases (3% [2–20%]).51 Due to the short lifetime of CH4 in the
atmosphere, projected deep reduction of CH4 emissions up until the time of net zero CO2 in modelled mitigation pathways
effectively reduces peak global warming. (high confidence) {3.3; AR6 WGI SPM D1.7}
C.2.4 At the time of global net zero GHG emissions, net negative CO2 emissions counterbalance metric-weighted non-CO2 GHG
emissions. Typical emissions pathways that reach and sustain global net zero GHG emissions based on the 100-year global
warming potential (GWP-100)7 are projected to result in a gradual decline of global warming. About half of the assessed
pathways that limit warming to 1.5°C (>50%) with no or limited overshoot (C1 category) reach net zero GHG emissions
during the second half of the 21st century. These pathways show greater reduction in global warming after the peak to
1.2 [1.1–1.4] °C by 2100 than modelled pathways in the same category that do not reach net zero GHG emissions before 2100
and that result in warming of 1.4 [1.3–1.5] °C by 2100. In modelled pathways that limit warming to 2°C (>67%) (C3 category),
there is no significant difference in warming by 2100 between those pathways that reach net zero GHGs (around 30%) and
those that do not (high confidence). In pathways that limit warming to 2°C (>67%) or lower and that do reach net zero GHG,
net zero GHG occurs around 10–40 years later than net zero CO2 emissions (medium confidence). {Cross-Chapter Box 2 in
Chapter 2, 3.3, Cross-Chapter Box 3 in Chapter 3; AR6 WGI SPM D1.8}
C.3 All global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, and
those that limit warming to 2°C (>67%), involve rapid and deep and in most cases immediate GHG
emission reductions in all sectors. Modelled mitigation strategies to achieve these reductions include
transitioning from fossil fuels without CCS to very low- or zero-carbon energy sources, such as renewables
or fossil fuels with CCS, demand side measures and improving efficiency, reducing non-CO2 emissions, and
deploying carbon dioxide removal (CDR) methods to counterbalance residual GHG emissions. Illustrative
Mitigation Pathways (IMPs) show different combinations of sectoral mitigation strategies consistent with
a given warming level. (high confidence) (Figure SPM.5) {3.2, 3.3, 3.4, 6.4, 6.6}
C.3.1 There is a variation in the contributions of different sectors in modelled mitigation pathways, as illustrated by the Illustrative
Mitigation Pathways (IMPs). However, modelled pathways that limit warming to 2°C (>67%) or lower share common
characteristics, including rapid and deep GHG emission reductions. Doing less in one sector needs to be compensated by
further reductions in other sectors if warming is to be limited. (high confidence) (Figure SPM.5) {3.2, 3.3, 3.4}
C.3.2 In modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, the global use of coal, oil
and gas in 2050 is projected to decline with median values of about 95%, 60% and 45% respectively, compared to 2019.
The interquartile ranges are (80 to 100%), (40 to 75%) and (20 to 60%) and the p5–p95 ranges are [60 to 100%], [25 to 90%]
and [–30 to +85%], respectively. In modelled pathways that limit warming to 2°C (>67%), these projected declines have
a median value and interquartile range of 85% (65 to 95%), 30% (15 to 50%) and 15% (–10 to +40%) respectively by
2050. The use of coal, oil and gas without CCS in modelled pathways that limit warming to 1.5°C (>50%) with no or limited
overshoot is projected to be reduced to a greater degree, with median values of about 100%, 60% and 70% in 2050 compared
to 2019. The interquartile ranges are (95 to 100%), (45 to 75%) and (60 to 80%) and the p5–p95 ranges about [85 to 100%],
[25 to 90%] and [35 to 90%] for coal, oil and gas respectively. In these global modelled pathways, in 2050 almost all
electricity is supplied from zero- or low-carbon sources, such as renewables or fossil fuels with CCS, combined with increased
51 All numbers here rounded to the closest 5%, except values below 5% (for F-gases).
25
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Summary for Policymakers
electrification of energy demand. As indicated by the ranges, choices in one sector can be compensated for by choices in
another while being consistent with assessed warming levels.52 (high confidence) {3.4, 3.5, Table 3.6, Figure 3.22, Figure 6.35}
C.3.3 In modelled pathways that reach global net zero CO2 emissions: at the point they reach net zero, 5–16 GtCO2 of emissions from
some sectors are compensated for by net negative CO2 emissions in other sectors. In most global modelled pathways that limit
warming to 2°C (>67%) or lower, the AFOLU sector, via reforestation and reduced deforestation, and the energy supply sector
reach net zero CO2 emissions earlier than the buildings, industry and transport sectors. (high confidence) (Figure SPM.5e,f) {3.4}
C.3.4 In modelled pathways that reach global net zero GHG emissions, at the point they reach net zero GHG, around 74% [54 to 90%]
of global emissions reductions are achieved by CO2 reductions in energy supply and demand, 13% [4 to 20%] by CO2 mitigation
options in the AFOLU sector, and 13% [10 to 18%] through the reduction of non-CO2 emissions from land-use, energy and
industry (medium confidence). (Figure SPM.5f) {3.3, 3.4}
C.3.5 Methods and levels of CDR deployment in global modelled mitigation pathways vary depending on assumptions about costs,
availability and constraints.53 In modelled pathways that report CDR and that limit warming to 1.5°C (>50%) with no or
limited overshoot, global cumulative CDR during 2020–2100 from bioenergy with carbon dioxide capture and storage (BECCS)
and direct air carbon dioxide capture and storage (DACCS) is 30–780 GtCO2 and 0–310 GtCO2, respectively. In these modelled
pathways, the AFOLU sector contributes 20–400 GtCO2 net negative emissions. Total cumulative net negative CO2 emissions
including CDR deployment across all options represented in these modelled pathways are 20–660 GtCO2. In modelled pathways
that limit warming to 2°C (>67%), global cumulative CDR during 2020–2100 from BECCS and DACCS is 170–650 GtCO2 and
0–250 GtCO2 respectively, the AFOLU sector contributes 10–250 GtCO2 net negative emissions, and total cumulative net
negative CO2 emissions are around 40 [0–290] GtCO2. (Table SPM.2) (high confidence) {Table 3.2, 3.3, 3.4}
C.3.6 All mitigation strategies face implementation challenges, including technology risks, scaling, and costs. Many challenges, such
as dependence on CDR, pressure on land and biodiversity (e.g., bioenergy) and reliance on technologies with high upfront
investments (e.g., nuclear), are significantly reduced in modelled pathways that assume using resources more efficiently
(e.g., IMP-LD) or that shift global development towards sustainability (e.g., IMP-SP). (high confidence) (Figure SPM.5) {3.2, 3.4,
3.7, 3.8, 4.3, 5.1}
52 Most but not all models include the use of fossil fuels for feedstock with varying underlying standards.
53 Aggregate levels of CDR deployment are higher than total net negative CO2 emissions given that some of the deployed CDR is used to counterbalance remaining
gross emissions. Total net negative CO2 emissions in modelled pathways might not match the aggregated net negative CO2 emissions attributed to individual CDR
methods. Ranges refer to the 5–95th percentile across modelled pathways that include the specific CDR method. Cumulative levels of CDR from AFOLU cannot be
quantified precisely given that: (i) some pathways assess CDR deployment relative to a baseline; and (ii) different models use different reporting methodologies that
in some cases combine gross emissions and removals in AFOLU. Total CDR from AFOLU equals or exceeds the net negative emissions mentioned.
26
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Summary for Policymakers
MtCH4 yr
–1
MtN2O yr
–1
–20
0
20
40
60
80
–20
0
20
40
60
80
0
100
200
300
400
500
0
5
10
15
20
Modelled mitigation pathways that limit warming to 1.5°C, and 2°C, involve deep, rapid and
sustained emissions reductions.
a. Net global GHG emissions b. Net global CO2 emissions
Year of net-zero GHG emissions Year of net-zero CO2 emissions
c. Net global CH4 emissions d. Net global N2O emissions
C3
C1
C3
C1
All climate categories
(very likely range)
Implemented policies and 2030 pledges
(very likely range)
CurPol (C7)
ModAct (C6)
IMP-GS (C3)
IMP-Neg (C2)
Limit warming to 2°C (>67%) (C3)
(very likely range)
Limit warming to 1.5°C (>50%)
with no or limited overshoot (C1)
(very likely range)
IMP-LD (C1)
IMP-Ren (C1)
IMP-SP (C1)
Past emissions (2000–2015)
Percentile of 2100 emission level:
95th
Median
5th
75th
25th
Model range for 2015 emissions
Past GHG emissions and uncertainty
for 2015 and 2019 (dot indicates the median)
2000 2020 2040 2060 2080 2100
2000 2020 2040 2060 2080 2100
2000 2020 2040 2060 2080 2100 2000 2020 2040 2060 2080 2100
2000 2020 2040 2060 2080 2100
2000 2020 2040 2060 2080 2100
CO2
comparison
GHG
comparison
GtCO2 yr
–1
GtCO2-eq yr
–1
GtCO2-eq yr
–1
0
5
10
15
GtCO2-eq yr
–1
0
2
3
1
4
5
–100%
–50%
Modelled
2019 level
+50%
NDC range
Figure SPM.5 | Illustrative Mitigation Pathways (IMPs) and net zero CO2 and GHG emissions strategies.
-= -1 H
-- -
- - - -
···•··· --•-·
a.
l·····+·····I
27
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Summary for Policymakers
GtCO2-eq yr
–1
–10
0
10
20
30
40
50
60
0%
20%
40%
60%
80%
100%
Net zero CO2 and net zero GHG emissionsare possible through different modelled mitigation pathways.
% of modelled 2019 emissions
e. Sectoral GHG emissions at the time of net-zero
CO2 emissions (compared to modelled 2019 emissions)
f. Contributions to reaching net zero GHG emissions
(for all scenarios reaching net-zero GHGs)
IMP-GS
IMP-Neg
IMP-LD
IMP-SP
IMP-Ren
Sources
Sinks
2019 At time of net-zero CO2
Direct
Indirect
2019
Contributions
by sector (CO2)
Total direct
and indirect
energy (CO2)
LULUCF (CO2)
and non-CO2
Direct:
Non-CO2 from
all sectors
LULUCF
Energy Supply (neg.)
Energy Supply (pos.)
Transport
Industry
Buildings
Total direct
energy emissions
Total indirect
energy emissions
(equals sum
of energy supply
emissions)
Indirect:
Figure SPM.5 (continued): Illustrative Mitigation Pathways (IMPs) and net zero CO2 and GHG emissions strategies. Panels a and b show the
development of global GHG and CO2 emissions in modelled global pathways (upper sub-panels) and the associated timing of when GHG and CO2 emissions reach net
zero (lower sub-panels). Panels c and d show the development of global CH4 and N2O emissions, respectively. Coloured ranges denote the 5th to 95th percentile across
pathways. The red ranges depict emissions pathways assuming policies that were implemented by the end of 2020 and pathways assuming implementation of NDCs
(announced prior to COP26). Ranges of modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot are shown in light blue (category C1) and
pathways that limit warming to 2°C (>67%) are shown in light purple (category C3). The grey range comprises all assessed pathways (C1–C8) from the 5th percentile
of the lowest warming category (C1) to the 95th percentile of the highest warming category (C8). The modelled pathway ranges are compared to the emissions from
two pathways illustrative of high emissions (CurPol and ModAct) and five IMPs: IMP-LD, IMP-Ren, IMP-SP, IMP-Neg and IMP-GS. Emissions are harmonised to the same
2015 base year. The vertical error bars in 2015 show the 5–95th percentile uncertainty range of the non-harmonised emissions across the pathways, and the uncertainty
range, and median value, in emission estimates for 2015 and 2019. The vertical error bars in 2030 (panel a) depict the assessed range of the NDCs, as announced prior
to COP26 (Figure SPM.4).23 Panel e shows the sectoral contributions of CO2 and non-CO2 emissions sources and sinks at the time when net zero CO2 emissions are
reached in the IMPs. Positive and negative emissions for different IMPs are compared to the GHG emissions from the year 2019. Energy supply (neg.) includes BECCS
and DACCS. DACCS features in only two of the five IMPs (IMP-REN and IMP-GS) and contributes <1% and 64%, respectively, to the net negative emissions in Energy
Supply (neg.). Panel f shows the contribution of different sectors and sources to the emissions reductions from a 2019 baseline for reaching net zero GHG emissions.
Bars denote the median emissions reductions for all pathways that reach net zero GHG emissions. The whiskers indicate the p5–p95 range. The contributions of the
service sectors (transport, buildings, industry) are split into direct (demand-side) as well as indirect (supply-side) CO2 emissions reductions. Direct emissions represent
demand-side emissions due to the fuel use in the respective demand sector. Indirect emissions represent upstream emissions due to industrial processes and energy
conversion, transmission and distribution. In addition, the contributions from the LULUCF sector and reductions from non-CO2 emissions sources (green and grey bars)
are displayed. {3.3, 3.4}
-- m-m - A -- - y -- -
28
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Summary for Policymakers
C.4 Reducing GHG emissions across the full energy sector requires major transitions, including a substantial
reduction in overall fossil fuel use, the deployment of low-emission energy sources, switching to
alternative energy carriers, and energy efficiency and conservation. The continued installation of
unabated fossil fuel54 infrastructure will ‘lock-in’ GHG emissions. (high confidence) {2.7, 6.6, 6.7, 16.4}
C.4.1 Net-zero CO2 energy systems entail: a substantial reduction in overall fossil fuel use, minimal use of unabated fossil fuels,
and use of CCS in the remaining fossil fuel system;54 electricity systems that emit no net CO2; widespread electrification of
the energy system including end uses; energy carriers such as sustainable biofuels, low-emissions hydrogen, and derivatives
in applications less amenable to electrification; energy conservation and efficiency; and greater physical, institutional, and
operational integration across the energy system. CDR will be needed to counterbalance residual emissions in the energy
sector. The most appropriate strategies depend on national and regional circumstances, including enabling conditions and
technology availability. (high confidence) {3.4, 6.6, 11.3, 16.4}
C.4.2 Unit cost reductions in key technologies, notably wind power, solar power, and storage, have increased the economic
attractiveness of low-emission energy sector transitions through 2030. Maintaining emission-intensive systems may, in some
regions and sectors, be more expensive than transitioning to low emission systems. Low-emission energy sector transitions
will have multiple co-benefits, including improvements in air quality and health. The long-term economic attractiveness of
deploying energy system mitigation options depends, inter alia, on policy design and implementation, technology availability
and performance, institutional capacity, equity, access to finance, and public and political support. (high confidence)
(Figure SPM.3) {3.4, 6.4, 6.6, 6.7, 13.7}
C.4.3 Electricity systems powered predominantly by renewables are becoming increasingly viable. Electricity systems in some
countries and regions are already predominantly powered by renewables. It will be more challenging to supply the entire
energy system with renewable energy. Even though operational, technological, economic, regulatory, and social challenges
remain, a variety of systemic solutions to accommodate large shares of renewables in the energy system have emerged. A broad
portfolio of options, such as integrating systems, coupling sectors, energy storage, smart grids, demand-side management,
sustainable biofuels, electrolytic hydrogen and derivatives, and others will ultimately be needed to accommodate large shares
of renewables in energy systems. (high confidence) {Box 6.8, 6.4, 6.6}
C.4.4 Limiting global warming to 2°C or below will leave a substantial amount of fossil fuels unburned and could strand considerable
fossil fuel infrastructure (high confidence). Depending on its availability, CCS could allow fossil fuels to be used longer, reducing
stranded assets (high confidence). The combined global discounted value of the unburned fossil fuels and stranded fossil fuel
infrastructure has been projected to be around USD1–4 trillion from 2015 to 2050 to limit global warming to approximately
2°C, and it will be higher if global warming is limited to approximately 1.5°C (medium confidence). In this context, coal assets
are projected to be at risk of being stranded before 2030, while oil and gas assets are projected to be more at risk of being
stranded towards mid-century. A low-emission energy sector transition is projected to reduce international trade in fossil fuels.
(high confidence) {6.7, Figure 6.35}
C.4.5 Global methane emissions from energy supply, primarily fugitive emissions from production and transport of fossil fuels,
accounted for about 18% [13–23%] of global GHG emissions from energy supply, 32% [22–42%] of global CH4 emissions,
and 6% [4–8%] of global GHG emissions in 2019 (high confidence). About 50–80% of CH4 emissions from these fossil fuels
could be avoided with currently available technologies at less than USD50 tCO2-eq–1 (medium confidence). {6.3, 6.4.2, Box 6.5,
11.3, 2.2.2, Table 2.1, Figure 2.5, Annex1: Glossary}
C.4.6 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources, provided geological storage
is available. When CO2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the
storage component of these CDR methods. CO2 capture and subsurface injection is a mature technology for gas processing
and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and
chemicals production, where it is a critical mitigation option. The technical geological CO2 storage capacity is estimated to be
on the order of 1000 GtCO2, which is more than the CO2 storage requirements through 2100 to limit global warming to 1.5°C,
although the regional availability of geological storage could be a limiting factor. If the geological storage site is appropriately
selected and managed, it is estimated that the CO2 can be permanently isolated from the atmosphere. Implementation of
CCS currently faces technological, economic, institutional, ecological-environmental and socio-cultural barriers. Currently,
global rates of CCS deployment are far below those in modelled pathways limiting global warming to 1.5°C or 2°C. Enabling
54 In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without interventions that substantially reduce the amount of GHG emitted throughout
the life cycle; for example, capturing 90% or more CO2 from power plants, or 50–80% of fugitive methane emissions from energy supply. {Box 6.5, 11.3}
29
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Summary for Policymakers
conditions such as policy instruments, greater public support and technological innovation could reduce these barriers. (high
confidence) {2.5, 6.3, 6.4, 6.7, 11.3, 11.4, Cross-Chapter Box 8 in Chapter 12, Figure TS.31; SRCCL Chapter 5}
C.5 Net zero CO2 emissions from the industrial sector are challenging but possible. Reducing industry
emissions will entail coordinated action throughout value chains to promote all mitigation options,
including demand management, energy and materials efficiency, circular material flows, as well as
abatement technologies and transformational changes in production processes. Progressing towards
net zero GHG emissions from industry will be enabled by the adoption of new production processes
using low- and zero-GHG electricity, hydrogen, fuels, and carbon management. (high confidence) {11.2,
11.3, 11.4, Box TS.4}
C.5.1 The use of steel, cement, plastics, and other materials is increasing globally, and in most regions. There are many
sustainable options for demand management, materials efficiency, and circular material flows that can contribute
to reduced emissions, but how these can be applied will vary across regions and different materials. These options
have a potential for being more used in industrial practice and would need more attention from industrial policy.
These options, as well as new production technologies, are generally not considered in recent global scenarios
nor in national economy-wide scenarios due to relative newness. As a consequence, the mitigation potential in
some scenarios is underestimated compared to bottom-up industry-specific models. (high confidence) {3.4, 5.3,
Figure 5.7, 11.2, Box 11.2, 11.3, 11.4, 11.5.2, 11.6}
C.5.2 For almost all basic materials – primary metals,55 building materials and chemicals – many low- to zero-GHG intensity
production processes are at the pilot to near-commercial and in some cases commercial stage but they are not yet established
industrial practice. Introducing new sustainable production processes for basic materials could increase production costs but,
given that only a small fraction of consumer costs are based on materials, such new processes are expected to translate into
minimal cost increases for final consumers. Hydrogen direct reduction for primary steelmaking is near-commercial in some
regions. Until new chemistries are mastered, deep reduction of cement process emissions will rely on already commercialised
cementitious material substitution and the availability of CCS. Reducing emissions from the production and use of chemicals
would need to rely on a life cycle approach, including increased plastics recycling, fuel and feedstock switching, and carbon
sourced through biogenic sources, and, depending on availability, carbon capture and use (CCU), direct air CO2 capture, as
well as CCS. Light industry, mining and manufacturing have the potential to be decarbonised through available abatement
technologies (e.g., material efficiency, circularity), electrification (e.g., electrothermal heating, heat pumps) and low- or
zero-GHG emitting fuels (e.g., hydrogen, ammonia, and bio-based and other synthetic fuels). (high confidence) {Table 11.4,
Box 11.2, 11.3, 11.4}
C.5.3 Action to reduce industry sector emissions may change the location of GHG-intensive industries and the organisation of value
chains. Regions with abundant low-GHG energy and feedstocks have the potential to become exporters of hydrogen-based
chemicals and materials processed using low-carbon electricity and hydrogen. Such reallocation will have global distributional
effects on employment and economic structure. (medium confidence) {Box 11.1}
C.5.4 Emissions-intensive and highly traded basic materials industries are exposed to international competition, and international
cooperation and coordination may be particularly important in enabling change. For sustainable industrial transitions, broad
and sequential national and sub-national policy strategies reflecting regional contexts will be required. These may combine
policy packages including: transparent GHG accounting and standards; demand management; materials and energy efficiency
policies; R&D and niche markets for commercialisation of low-emission materials and products; economic and regulatory
instruments to drive market uptake; high quality recycling, low-emissions energy and other abatement infrastructure (e.g., for
CCS); and socially inclusive phase-out plans of emissions-intensive facilities within the context of just transitions. The coverage
of mitigation policies could be expanded nationally and sub-nationally to include all industrial emission sources, and both
available and emerging mitigation options. (high confidence) {11.6}
55 Primary metals refers to virgin metals produced from ore.
30
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Summary for Policymakers
C.6 Urban areas can create opportunities to increase resource efficiency and significantly reduce GHG
emissions through the systemic transition of infrastructure and urban form through low-emission
development pathways towards net-zero emissions. Ambitious mitigation efforts for established,
rapidly growing and emerging cities will encompass (i) reducing or changing energy and material
consumption, (ii) electrification, and (iii) enhancing carbon uptake and storage in the urban environment.
Cities can achieve net-zero emissions, but only if emissions are reduced within and outside of their
administrative boundaries through supply chains, which will have beneficial cascading effects across
other sectors. (very high confidence) {8.2, 8.3, 8.4, 8.5, 8.6, Figure 8.21, 13.2}
C.6.1 In modelled scenarios, global consumption-based urban CO2 and CH4 emissions15 are projected to rise from 29 GtCO2-eq in 2020
to 34 GtCO2-eq in 2050 with moderate mitigation efforts (intermediate GHG emissions, SSP2-4.5), and up to 40 GtCO2-eq in
2050 with low mitigation efforts (high GHG emissions, SSP3-7.0). With ambitious and immediate mitigation efforts, including
high levels of electrification and improved energy and material efficiency, global consumption-based urban CO2 and CH4
emissions could be reduced to 3 GtCO2-eq in 2050 in the modelled scenario with very low GHG emissions (SSP1-1.9).56
(medium confidence) {8.3}
C.6.2 The potential and sequencing of mitigation strategies to reduce GHG emissions will vary depending on a city’s land use,
spatial form, development level, and state of urbanisation (high confidence). Strategies for established cities to achieve large
GHG emissions savings include efficiently improving, repurposing or retrofitting the building stock, targeted infilling, and
supporting non-motorised (e.g., walking, bicycling) and public transport. Rapidly growing cities can avoid future emissions
by co-locating jobs and housing to achieve compact urban form, and by leapfrogging or transitioning to low-emissions
technologies. New and emerging cities will have significant infrastructure development needs to achieve high quality of life,
which can be met through energy efficient infrastructures and services, and people-centred urban design (high confidence).
For cities, three broad mitigation strategies have been found to be effective when implemented concurrently: (i) reducing or
changing energy and material use towards more sustainable production and consumption; (ii) electrification in combination
with switching to low-emission energy sources; and (iii) enhancing carbon uptake and storage in the urban environment, for
example through bio-based building materials, permeable surfaces, green roofs, trees, green spaces, rivers, ponds and lakes.57
(very high confidence) {5.3, Figure 5.7, Supplementary Material Table 5.SM.2, 8.2, 8.4, 8.6, Figure 8.21, 9.4, 9.6, 10.2}
C.6.3 The implementation of packages of multiple city-scale mitigation strategies can have cascading effects across sectors
and reduce GHG emissions both within and outside a city’s administrative boundaries. The capacity of cities to develop and
implement mitigation strategies varies with the broader regulatory and institutional settings, as well as enabling conditions,
including access to financial and technological resources, local governance capacity, engagement of civil society, and municipal
budgetary powers. (very high confidence) {Figure 5.7, Supplementary Material Table 5.SM.2, 8.4, 8.5, 8.6, 13.2, 13.3, 13.5,
13.7, Cross-Chapter Box 9 in Chapter 13}
C.6.4 A growing number of cities are setting climate targets, including net-zero GHG targets. Given the regional and global reach
of urban consumption patterns and supply chains, the full potential for reducing consumption-based urban emissions to net
zero GHG can be met only when emissions beyond cities’ administrative boundaries are also addressed. The effectiveness of
these strategies depends on cooperation and coordination with national and sub-national governments, industry, and civil
society, and whether cities have adequate capacity to plan and implement mitigation strategies. Cities can play a positive role
in reducing emissions across supply chains that extend beyond cities’ administrative boundaries, for example through building
codes and the choice of construction materials. (very high confidence) {8.4, Box 8.4, 8.5, 9.6, 9.9, 13.5, 13.9}
56 These scenarios have been assessed by WGI to correspond to intermediate, high and very low GHG emissions.
57 These examples are considered to be a subset of nature-based solutions or ecosystem-based approaches.
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Summary for Policymakers
C.7. In modelled global scenarios, existing buildings, if retrofitted, and buildings yet to be built, are
projected to approach net zero GHG emissions in 2050 if policy packages, which combine ambitious
sufficiency, efficiency, and renewable energy measures, are effectively implemented and barriers to
decarbonisation are removed. Low ambition policies increase the risk of locking-in buildings’ carbon
for decades, while well-designed and effectively implemented mitigation interventions (in both new
buildings and existing ones if retrofitted), have significant potential to contribute to achieving SDGs in
all regions while adapting buildings to future climate. (high confidence) {9.1, 9.3, 9.4, 9.5, 9.6, 9.9}
C.7.1 In 2019, global direct and indirect GHG emissions from buildings and emissions from cement and steel use for building
construction and renovation were 12 GtCO2-eq. These emissions include indirect emissions from offsite generation of electricity
and heat, direct emissions produced onsite and emissions from cement and steel used for building construction and renovation.
In 2019, global direct and indirect emissions from non-residential buildings increased by about 55% and those from residential
buildings increased by about 50% compared to 1990. The latter increase, according to the decomposition analysis, was mainly
driven by the increase of the floor area per capita, population growth and the increased use of emission-intensive electricity
and heat while efficiency improvements have partly decreased emissions. There are great differences in the contribution of
each of these drivers to regional emissions. (high confidence) {9.3}
C.7.2 Integrated design approaches to the construction and retrofit of buildings have led to increasing examples of zero energy
or zero carbon buildings in several regions. However, the low renovation rates and low ambition of retrofitted buildings
have hindered the decrease of emissions. Mitigation interventions at the design stage include buildings typology, form,
and multi-functionality to allow for adjusting the size of buildings to the evolving needs of their users and repurposing
unused existing buildings to avoid using GHG-intensive materials and additional land. Mitigation interventions include: at the
construction phase, low-emission construction materials, highly efficient building envelope and the integration of renewable
energy solutions;58 at the use phase, highly efficient appliances/equipment, the optimisation of the use of buildings and their
supply with low-emission energy sources; and at the disposal phase, recycling and re-using construction materials. (high
confidence) {9.4, 9.5, 9.6, 9.7}
C.7.3 By 2050, bottom-up studies show that up to 61% (8.2 GtCO2) of global building emissions could be mitigated. Sufficiency
policies59 that avoid the demand for energy and materials contribute 10% to this potential, energy efficiency policies contribute
42%, and renewable energy policies 9%. The largest share of the mitigation potential of new buildings is available in
developing countries while in developed countries the highest mitigation potential is within the retrofit of existing buildings.
The 2020–2030 decade is critical for accelerating the learning of know-how, building the technical and institutional capacity,
setting the appropriate governance structures, ensuring the flow of finance, and in developing the skills needed to fully
capture the mitigation potential of buildings. (high confidence) {9.3, 9.4, 9.5, 9.6, 9.7, 9.9}
58 Integration of renewable energy solutions refers to the integration of solutions such as solar photovoltaics, small wind turbines, solar thermal collectors,
and biomass boilers.
59 Sufficiency policies are a set of measures and daily practices that avoid demand for energy, materials, land and water while delivering human well-being for all within
planetary boundaries.
32
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Summary for Policymakers
C.8 Demand-side options and low-GHG emissions technologies can reduce transport sector emissions
in developed countries and limit emissions growth in developing countries (high confidence).
Demand-focused interventions can reduce demand for all transport services and support the shift to
more energy efficient transport modes (medium confidence). Electric vehicles powered by low-emissions
electricity offer the largest decarbonisation potential for land-based transport, on a life cycle basis (high
confidence). Sustainable biofuels can offer additional mitigation benefits in land-based transport in
the short and medium term (medium confidence). Sustainable biofuels, low-emissions hydrogen, and
derivatives (including synthetic fuels) can support mitigation of CO2 emissions from shipping, aviation,
and heavy-duty land transport but require production process improvements and cost reductions
(medium confidence). Many mitigation strategies in the transport sector would have various co-benefits,
including air quality improvements, health benefits, equitable access to transportation services, reduced
congestion, and reduced material demand (high confidence). {10.2, 10.4, 10.5, 10.6, 10.7}
C.8.1 In scenarios that limit warming to 1.5°C (>50%) with no or limited overshoot, global transport-related CO2 emissions fall by
59% (42–68% interquartile range) by 2050 relative to modelled 2020 emissions, but with regionally differentiated trends (high
confidence). In global modelled scenarios that limit warming to 2°C (>67%), transport-related CO2 emissions are projected
to decrease by 29% [14–44% interquartile range] by 2050 compared to modelled 2020 emissions. In both categories of
scenarios, the transport sector likely does not reach zero CO2 emissions by 2100 so negative emissions are likely needed to
counterbalance residual CO2 emissions from the sector (high confidence). {3.4, 10.7}
C.8.2 Changes in urban form (e.g., density, land-use mix, connectivity, and accessibility) in combination with programmes that
encourage changes in consumer behaviour (e.g., transport pricing) could reduce transport-related greenhouse gas emissions in
developed countries and slow growth in emissions in developing countries (high confidence). Investments in public inter- and
intra-city transport and active transport infrastructure (e.g., bicycle and pedestrian pathways) can further support the shift to
less GHG-intensive transport modes (high confidence). Combinations of systemic changes, including teleworking, digitalisation,
dematerialisation, supply chain management, and smart and shared mobility may reduce demand for passenger and freight
services across land, air, and sea (high confidence). Some of these changes could lead to induced demand for transport and
energy services, which may decrease their GHG emissions reduction potential (medium confidence). {5.3, 10.2, 10.8}
C.8.3 Electric vehicles powered by low-GHG emissions electricity have large potential to reduce land-based transport GHG emissions,
on a life cycle basis (high confidence). Costs of electrified vehicles, including automobiles, two- and three-wheelers, and
buses, are decreasing and their adoption is accelerating, but they require continued investments in supporting infrastructure
to increase scale of deployment (high confidence). Advances in battery technologies could facilitate the electrification of
heavy-duty trucks and complement conventional electric rail systems (medium confidence). There are growing concerns
about critical minerals needed for batteries. Material and supply diversification strategies, energy and material efficiency
improvements, and circular material flows can reduce the environmental footprint and material supply risks for battery
production (medium confidence). Sourced sustainably and with low-GHG emissions feedstocks, bio-based fuels, blended or
unblended with fossil fuels, can provide mitigation benefits, particularly in the short and medium term (medium confidence).
Low-GHG emissions hydrogen and hydrogen derivatives, including synthetic fuels, can offer mitigation potential in some
contexts and land-based transport segments (medium confidence). {3.4, 6.3, 10.3, 10.4, 10.7, 10.8, Box 10.6}
C.8.4 While efficiency improvements (e.g., optimised aircraft and vessel designs, mass reduction, and propulsion system
improvements) can provide some mitigation potential, additional CO2 emissions mitigation technologies for aviation and
shipping will be required (high confidence). For aviation, such technologies include high energy density biofuels (high
confidence), and low-emission hydrogen and synthetic fuels (medium confidence). Alternative fuels for shipping include
low-emission hydrogen, ammonia, biofuels, and other synthetic fuels (medium confidence). Electrification could play a niche
role for aviation and shipping for short trips (medium confidence) and can reduce emissions from port and airport operations
(high confidence). Improvements to national and international governance structures would further enable the decarbonisation
of shipping and aviation (medium confidence). Such improvements could include, for example, the implementation of stricter
efficiency and carbon intensity standards for the sectors (medium confidence). {10.3. 10.5, 10.6, 10.7, 10.8, Box 10.5}
C.8.5 The substantial potential for GHG emissions reductions, both direct and indirect, in the transport sector largely depends on
power sector decarbonisation, and low-emissions feedstocks and production chains (high confidence). Integrated transport
and energy infrastructure planning and operations can enable sectoral synergies and reduce the environmental, social, and
economic impacts of decarbonising the transport and energy sectors (high confidence). Technology transfer and financing can
support developing countries leapfrogging or transitioning to low-emissions transport systems thereby providing multiple
co-benefits (high confidence). {10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8}
33
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C.9 AFOLU mitigation options, when sustainably implemented, can deliver large-scale GHG emission
reductions and enhanced removals, but cannot fully compensate for delayed action in other sectors.
In addition, sustainably sourced agricultural and forest products can be used instead of more
GHG-intensive products in other sectors. Barriers to implementation and trade-offs may result from the
impacts of climate change, competing demands on land, conflicts with food security and livelihoods,
the complexity of land ownership and management systems, and cultural aspects. There are many
country-specific opportunities to provide co-benefits (such as biodiversity conservation, ecosystem
services, and livelihoods) and avoid risks (for example, through adaptation to climate change). (high
confidence) {7.4, 7.6, 7.7, 12.5, 12.6}
C.9.1 The projected economic mitigation potential of AFOLU options between 2020 and 2050, at costs below USD100 tCO2-eq–1,
is 8–14 GtCO2-eq yr–1 60 (high confidence). 30–50% of this potential is available at less than USD20 tCO2-eq and could be upscaled
in the near term across most regions (high confidence). The largest share of this economic potential [4.2–7.4 GtCO2-eq yr–1]
comes from the conservation, improved management, and restoration of forests and other ecosystems (coastal wetlands,
peatlands, savannas and grasslands), with reduced deforestation in tropical regions having the highest total mitigation.
Improved and sustainable crop and livestock management, and carbon sequestration in agriculture (the latter including soil
carbon management in croplands and grasslands, agroforestry and biochar), can contribute 1.8–4.1 GtCO2-eq yr–1 reduction.
Demand-side and material substitution measures, such as shifting to balanced, sustainable healthy diets,61 reducing food loss
and waste, and using bio-materials, can contribute 2.1 [1.1–3.6] GtCO2-eq yr–1 reduction. In addition, demand-side measures
together with the sustainable intensification of agriculture can reduce ecosystem conversion and CH4 and N2O emissions,
and free up land for reforestation and restoration, and the production of renewable energy. The improved and expanded
use of wood products sourced from sustainably managed forests also has potential through the allocation of harvested
wood to longer-lived products, increasing recycling or material substitution. AFOLU mitigation measures cannot compensate
for delayed emission reductions in other sectors. Persistent and region-specific barriers continue to hamper the economic
and political feasibility of deploying AFOLU mitigation options. Assisting countries to overcome barriers will help to achieve
significant mitigation (medium confidence). (Figure SPM.6) {7.1, 7.4, 7.5, 7.6}
C.9.2 AFOLU carbon sequestration and GHG emission reduction options have both co-benefits and risks in terms of biodiversity and
ecosystem conservation, food and water security, wood supply, livelihoods and land tenure and land-use rights of Indigenous
Peoples, local communities and small land owners. Many options have co-benefits but those that compete for land and
land-based resources can pose risks. The scale of benefit or risk largely depends on the type of activity undertaken, deployment
strategy (e.g., scale, method), and context (e.g., soil, biome, climate, food system, land ownership) that vary geographically
and over time. Risks can be avoided when AFOLU mitigation is pursued in response to the needs and perspectives of multiple
stakeholders to achieve outcomes that maximize co-benefits while limiting trade-offs. (high confidence) {7.4, 7.6, 12.3}
C.9.3 Realising the AFOLU mitigation potential entails overcoming institutional, economic and policy constraints and managing
potential trade-offs (high confidence). Land-use decisions are often spread across a wide range of land owners; demand-side
measures depend on billions of consumers in diverse contexts. Barriers to the implementation of AFOLU mitigation include
insufficient institutional and financial support, uncertainty over long-term additionality and trade-offs, weak governance,
insecure land ownership, low incomes and the lack of access to alternative sources of income, and the risk of reversal. Limited
access to technology, data, and know-how is a barrier to implementation. Research and development are key for all measures.
For example, measures for the mitigation of agricultural CH4 and N2O emissions with emerging technologies show promising
results. However, the mitigation of agricultural CH4 and N2O emissions is still constrained by cost, the diversity and complexity
of agricultural systems, and by increasing demands to raise agricultural yields, and increasing demand for livestock products.
(high confidence) {7.4, 7.6}
C.9.4 Net costs of delivering 5–6 GtCO2 yr–1 of forest-related carbon sequestration and emission reduction as assessed with sectoral
models are estimated to reach to about USD400 billion yr–1 by 2050. The costs of other AFOLU mitigation measures are highly
context specific. Financing needs in AFOLU, and in particular in forestry, include both the direct effects of any changes in
60 The global top-down estimates and sectoral bottom-up estimates described here do not include the substitution of emissions from fossil fuels and GHG-intensive
materials. 8–14 GtCO2-eq yr–1 represents the mean of the AFOLU economic mitigation potential estimates from top-down estimates (lower bound of range) and
global sectoral bottom-up estimates (upper bound of range). The full range from top-down estimates is 4.1–17.3 GtCO2-eq yr–1 using a ‘no policy’ baseline. The full
range from global sectoral studies is 6.7–23.4 GtCO2-eq yr–1 using a variety of baselines. (high confidence)
61 ‘Sustainable healthy diets’ promote all dimensions of individuals’ health and well-being; have low environmental pressure and impact; are accessible, affordable,
safe and equitable; and are culturally acceptable, as described in FAO and WHO. The related concept of ‘balanced diets’ refers to diets that feature plant-based foods,
such as those based on coarse grains, legumes, fruits and vegetables, nuts and seeds, and animal-sourced food produced in resilient, sustainable and low-GHG
emission systems, as described in SRCCL.
34
SPM
Summary for Policymakers
activities as well as the opportunity costs associated with land-use change. Enhanced monitoring, reporting and verification
capacity, and the rule of law, are crucial for land-based mitigation in combination with policies also recognising interactions
with wider ecosystem services, could enable engagement by a wider array of actors, including private businesses, NGOs, and
Indigenous Peoples and local communities. (medium confidence) {7.6, 7.7}
C.9.5 Context specific policies and measures have been effective in demonstrating the delivery of AFOLU carbon sequestration and
GHG emission reduction options but the above-mentioned constraints hinder large scale implementation (medium confidence).
Deploying land-based mitigation can draw on lessons from experience with regulations, policies, economic incentives,
payments (e.g., for biofuels, control of nutrient pollution, water regulations, conservation and forest carbon, ecosystem
services, and rural livelihoods), and from diverse forms of knowledge such as Indigenous knowledge, local knowledge and
scientific knowledge. Indigenous Peoples, private forest owners, local farmers and communities manage a significant share of
global forests and agricultural land and play a central role in land-based mitigation options. Scaling successful policies and
measures relies on governance that emphasises integrated land-use planning and management framed by SDGs, with support
for implementation. (high confidence) {7.4, Box 7.2, 7.6}
C.10 Demand-side mitigation encompasses changes in infrastructure use, end-use technology adoption,
and socio-cultural and behavioural change. Demand-side measures and new ways of end-use service
provision can reduce global GHG emissions in end-use sectors by 40–70% by 2050 compared to baseline
scenarios, while some regions and socioeconomic groups require additional energy and resources.
Demand-side mitigation response options are consistent with improving basic well-being for all. (high
confidence) (Figure SPM.6) {5.3, 5.4, Figure 5.6, Figure 5.14, 8.2, 9.4, 10.2, 11.3, 11.4, 12.4, Figure TS.22}
C.10.1 Infrastructure design and access, and technology access and adoption, including information and communication
technologies, influence patterns of demand and ways of providing services, such as mobility, shelter, water, sanitation, and
nutrition. Illustrative global low-demand scenarios, accounting for regional differences, indicate that more efficient end-use
energy conversion can improve services while reducing the need for upstream energy by 45% by 2050 compared to 2020.
Demand-side mitigation potential differs between and within regions, and some regions and populations require additional
energy, capacity, and resources for human well-being. The lowest population quartile by income worldwide faces shortfalls in
shelter, mobility, and nutrition. (high confidence) {5.2, 5.3, 5.4, 5.5, Figure 5.6, Figure 5.10, Table 5.2, Figure TS.20, Figure TS.22}
C.10.2 By 2050, comprehensive demand-side strategies could reduce direct and indirect CO2 and non-CO2 GHG emissions in three
end-use sectors (buildings, land transport, and food) globally by 40%–70% compared to the 2050 emissions projection of two
scenarios consistent with policies announced by national governments until 2020. With policy support, socio-cultural options
and behavioural change can reduce global GHG emissions of end-use sectors by at least 5% rapidly, with most of the potential
in developed countries, and more until 2050, if combined with improved infrastructure design and access. Individuals with
high socio-economic status contribute disproportionately to emissions and have the highest potential for emissions reductions,
e.g., as citizens, investors, consumers, role models, and professionals. (high confidence) (Figure SPM.6) {5.2, 5.3, 5.4, 5.5, 5.6,
Supplementary Material Table 5.SM.2, 8.4, 9.9, 13.2, 13.5, 13.8, Figure TS.20}
C.10.3 A range of 5–30% of global annual GHG emissions from end-use sectors are avoidable by 2050, compared to 2050 emissions
projection of two scenarios consistent with policies announced by national governments until 2020, through changes in the
built environment, new and repurposed infrastructures and service provision through compact cities, co-location of jobs and
housing, more efficient use of floor space and energy in buildings, and reallocation of street space for active mobility (high
confidence). (Figure SPM.6) {5.3.1, 5.3.3, 5.4, Figure 5.7, Figure 5.13, Table 5.1, Table 5.5, Supplementary Material Table 5.
SM.2, 8.4, 9.5, 10.2, 11.3, 11.4, Table 11.6, Box TS.12}
C.10.4 Choice architecture62 can help end-users adopt, as relevant to consumers, culture and country contexts, low-GHG-intensive
options such as balanced, sustainable healthy diets61 acknowledging nutritional needs; food waste reduction; adaptive heating
and cooling choices for thermal comfort; building-integrated renewable energy; and electric light-duty vehicles, and shifts to
walking, cycling, shared pooled and public transit; and sustainable consumption by intensive use of longer-lived repairable
products (high confidence). Addressing inequality and many forms of status consumption63 and focusing on wellbeing
supports climate change mitigation efforts (high confidence). (Figure SPM.6) {2.4.3, 2.6.2, 4.2.5, 5.1, 5.2, 5.3, 5.4, Figure 5.4,
Figure 5.10, Table 5.2, Supplementary Material Table 5.SM.2, 7.4.5, 8.2, 8.4, 9.4, 10.2, 12.4, Figure TS.20}
62 ‘Choice architecture’ describes the presentation of choices to consumers, and the impact that presentation has on consumer decision-making.
63 ‘Status consumption’ refers to the consumption of goods and services which publicly demonstrates social prestige.
35
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Summary for Policymakers
Demand-side mitigation can be achieved through changes in socio-cultural factors, infrastructure
design and use, and end-use technology adoption by 2050.
15
10
5
0
GtCO2-eq yr
–1
Direct reduction of food
related emissions, excluding
reforestation of freed up land
AFOLU
End-use
sectors
Services for
well-being
3
1 The presentation of choices to consumers, and the impact of that presentation on consumer decision-making.
2 Load management refers to demand-side flexibility that cuts across all sectors and can be achieved through incentive design like time of use pricing/monitoring
by artificial intelligence, diversification of storage facilities, etc.
The impact of demand-side mitigation on electricity sector emissions depends on the baseline carbon intensity of electricity supply, which is scenario dependent.
Emissions that cannot be
avoided or reduced through
demand-side options are
assumed to be addressed
by supply-side options
Total emissions 2050
Infrastructure use
Socio-cultural factors
End-use technology
adoption
Industry
Add. electrification
Buildings
Land transport
Load management
GtCO2 yr
–1
15
10
5
0
GtCO2 yr
–1
15
10
5
0
c. Electricity: indicative impacts
of change in service demand
Electricity
Additional emissions from increased
electricity generation to enable the
end-use sectors’ substitution of electricity
for fossil fuels, e.g. via heat pumps and
electric cars {Table SM5.3; 6.6}
Additional electrification (+60%)
Industry
Land transport
Buildings
Load management2
Reduced emissions through demand-side
mitigation options (in end-use sectors:
buildings, industry and land transport)
which has potential to reduce
electricity demand3
Demand-side
measures
–73%
a. Nutrition
Nutrition
Food
Socio-cultural factors
Dietary shift (shifting to balanced,
sustainable healthy diets),
avoidance of food waste
and over-consumption
Infrastructure use
Choice architecture1 and
information to guide dietary
choices; financial incentives;
waste management;
recycling infrastructure
End-use technology adoption
Currently estimates are not
available (for lab-based meat and
similar options – no quantitative
literature available, overall potential
considered in socio-cultural factors)
b. Manufactured products, mobility, shelter
Human settlements
Manufactured products Mobility Shelter
Industry Land transport Buildings
Shift in demand towards
sustainable consumption,
such as intensive use
of longer-lived
repairable products
Teleworking or
telecommuting; active
mobility through
walking and cycling
Social practices resulting
in energy saving; lifestyle
and behavioural changes
Socio-cultural factors
Networks established
for recycling, repurposing,
remanufacturing and
reuse of metals, plastics
and glass; labelling lowemissions
materials
and products
Public transport; shared
mobility; compact cities;
spatial planning
Compact cities;
rationalisation of living
floor space; architectural
design; urban planning
(e.g., green roof, cool
roof, urban green
spaces etc.)
Infrastructure use
Green procurement to
access material-efficient
products and services;
access to energy-efficient
and CO2 neutral materials
Electric vehicles;
shift to more
efficient vehicles
Energy efficient
building envelopes
and appliances;
shift to renewables
End-use technology adoption
Total emissions 2050: Mean IEA-STEPS IP_ModAct
Figure SPM.6 | Indicative potential of demand-side mitigation options by 2050. Figure SPM.6 covers the indicative potential of demand-side options for the
year 2050. Figure SPM.7 covers cost and potentials for the year 2030. Demand-side mitigation response options are categorised into three broad domains: ‘socio-cultural
factors’, associated with individual choices, behaviour, lifestyle changes, social norms, and culture; ‘infrastructure use’, related to the design and use of supporting hard
and soft infrastructure that enables changes in individual choices and behaviour; and ‘end-use technology adoption’, referring to the uptake of technologies by end-users.
Demand-side mitigation is a central element of the IMP-LD and IMP-SP scenarios (Figure SPM.5). Panel a (Nutrition) demand-side potentials in 2050 assessment is
based on bottom-up studies and is estimated following the 2050 baseline for the food sector presented in peer-reviewed literature (more information in Supplementary
Material 5.II, and Section 7.4.5). Panel b (Manufactured products, mobility, shelter) the assessment of potentials for total emissions in 2050 are estimated based on
approximately 500 bottom-up studies representing all global regions (detailed list is in Supplementary Material Table 5.SM.2). Baseline is provided by the sectoral mean
GHG emissions in 2050 of the two scenarios consistent with policies announced by national governments until 2020. The heights of the coloured columns represent the
potentials represented by the median value. These are based on a range of values available in the case studies from literature shown in Supplementary Material 5.SM.II.
The range is shown by the dots connected by dotted lines representing the highest and the lowest potentials reported in the literature. Panel a shows the demand-side
potential of socio-cultural factors and infrastructure use. The median value of direct emissions (mostly non-CO2) reduction through socio-cultural factors is 1.9 GtCO2-eq
without considering land-use change through reforestation of freed up land. If changes in land-use pattern enabled by this change in food demand are considered,
the indicative potential could reach 7 GtCO2-eq. Panel b illustrates mitigation potential in industry, land transport and buildings end-use sectors through demand-side
options. Key options are presented in the summary table below the figure and the details are in Supplementary Material Table 5.SM.2. Panel c visualises how sectoral
demand-side mitigation options (presented in panel b) change demand on the electricity distribution system. Electricity accounts for an increasing proportion of final
energy demand in 2050 (additional electricity bar) in line with multiple bottom-up studies (detailed list is in Supplementary Material Table 5.SM.3), and Chapter 6
(Section 6.6). These studies are used to compute the impact of end-use electrification which increases overall electricity demand. Some of the projected increase in
electricity demand can be avoided through demand-side mitigation options in the domains of socio-cultural factors and infrastructure use in end-use electricity use
in buildings, industry, and land transport found in literature based on bottom-up assessments. Dark grey columns show the emissions that cannot be avoided through
demand-side mitigation options. {5.3, Figure 5.7, Supplementary Material 5.SM.II}
■
■
■
■
■
■
■
■
■
■
I
- ----
■ - -----
36
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Summary for Policymakers
C.11 The deployment of carbon dioxide removal (CDR) to counterbalance hard-to-abate residual emissions is
unavoidable if net zero CO2 or GHG emissions are to be achieved. The scale and timing of deployment will
depend on the trajectories of gross emission reductions in different sectors. Upscaling the deployment
of CDR depends on developing effective approaches to address feasibility and sustainability constraints
especially at large scales. (high confidence) {3.4, 7.4, 12.3, Cross-Chapter Box 8 in Chapter 12}
C.11.1 CDR refers to anthropogenic activities that remove CO2 from the atmosphere and store it durably in geological, terrestrial, or
ocean reservoirs, or in products. CDR methods vary in terms of their maturity, removal process, time scale of carbon storage,
storage medium, mitigation potential, cost, co-benefits, impacts and risks, and governance requirements (high confidence).
Specifically, maturity ranges from lower maturity (e.g., ocean alkalinisation) to higher maturity (e.g., reforestation); removal
and storage potential ranges from lower potential (<1 GtCO2 yr–1, e.g., blue carbon management) to higher potential
(>3 GtCO2 yr–1, e.g., agroforestry); costs range from lower cost (e.g., USD-45–100 per tCO2 for soil carbon sequestration) to
higher cost (e.g., USD100–300 per tCO2 for DACCS) (medium confidence). Estimated storage time scales vary from decades
to centuries for methods that store carbon in vegetation and through soil carbon management, to 10,000 years or more
for methods that store carbon in geological formations (high confidence). The processes by which CO2 is removed from the
atmosphere are categorised as biological, geochemical or chemical. Afforestation, reforestation, improved forest management,
agroforestry and soil carbon sequestration are currently the only widely practiced CDR methods (high confidence). {7.4, 7.6,
12.3, Table 12.6, Cross-Chapter Box 8 in Chapter 12, Table TS.7; AR6 WGI 5.6}
C.11.2 The impacts, risks and co-benefits of CDR deployment for ecosystems, biodiversity and people will be highly variable
depending on the method, site-specific context, implementation and scale (high confidence). Reforestation, improved forest
management, soil carbon sequestration, peatland restoration and blue carbon management are examples of methods that
can enhance biodiversity and ecosystem functions, employment and local livelihoods, depending on context (high confidence).
In contrast, afforestation or production of biomass crops for BECCS or biochar, when poorly implemented, can have adverse
socio-economic and environmental impacts, including on biodiversity, food and water security, local livelihoods and on the
rights of Indigenous Peoples, especially if implemented at large scales and where land tenure is insecure (high confidence).
Ocean fertilisation, if implemented, could lead to nutrient redistribution, restructuring of ecosystems, enhanced oxygen
consumption and acidification in deeper waters (medium confidence). {7.4, 7.6, 12.3, 12.5}
C.11.3 The removal and storage of CO2 through vegetation and soil management can be reversed by human or natural disturbances;
it is also prone to climate change impacts. In comparison, CO2 stored in geological and ocean reservoirs (via BECCS, DACCS,
ocean alkalinisation) and as carbon in biochar is less prone to reversal. (high confidence) {6.4, 7.4, 12.3}
C.11.4 In addition to deep, rapid, and sustained emission reductions CDR can fulfil three different complementary roles globally or at
country level: lowering net CO2 or net GHG emissions in the near term; counterbalancing ‘hard-to-abate’ residual emissions
(e.g., emissions from agriculture, aviation, shipping, industrial processes) in order to help reach net zero CO2 or net zero GHG
emissions in the mid-term; and achieving net negative CO2 or GHG emissions in the long term if deployed at levels exceeding
annual residual emissions. (high confidence) {3.3, 7.4, 11.3, 12.3, Cross-Chapter Box 8 in Chapter 12}
C.11.5 Rapid emission reductions in all sectors interact with future scale of deployment of CDR methods, and their associated risks,
impacts and co-benefits. Upscaling the deployment of CDR methods depends on developing effective approaches to address
sustainability and feasibility constraints, potential impacts, co-benefits and risks. Enablers of CDR include accelerated research,
development and demonstration, improved tools for risk assessment and management, targeted incentives and development
of agreed methods for measurement, reporting and verification of carbon flows. (high confidence) {3.4, 7.6, 12.3}
37
SPM
Summary for Policymakers
C.12 Mitigation options costing USD100 tCO2-eq–1 or less could reduce global GHG emissions by at least half
the 2019 level by 2030 (high confidence). Global GDP continues to grow in modelled pathways64 but,
without accounting for the economic benefits of mitigation action from avoided damages from climate
change nor from reduced adaptation costs, it is a few percent lower in 2050 compared to pathways
without mitigation beyond current policies. The global economic benefit of limiting warming to 2°C
is reported to exceed the cost of mitigation in most of the assessed literature (medium confidence).
(Figure SPM.7) {3.6, 3.8, Cross-Working Group Box 1 in Chapter 3, 12.2, Box TS.7}
C.12.1 Based on a detailed sectoral assessment of mitigation options, it is estimated that mitigation options costing USD100 tCO2-eq–1
or less could reduce global GHG emissions by at least half of the 2019 level by 2030 (options costing less than USD20 tCO2-eq–1
are estimated to make up more than half of this potential).65 For a smaller part of the potential, deployment leads to net
cost savings. Large contributions with costs less than USD20 tCO2-eq–1 come from solar and wind energy, energy efficiency
improvements, reduced conversion of natural ecosystems, and CH4 emissions reductions (coal mining, oil and gas, waste).
The mitigation potentials and mitigation costs of individual technologies in a specific context or region may differ greatly
from the provided estimates. The assessment of the underlying literature suggests that the relative contribution of the various
options could change beyond 2030. (medium confidence) (Figure SPM.7) {12.2}
C.12.2 The aggregate effects of climate change mitigation on global GDP are small compared to global projected GDP growth
in assessed modelled global scenarios that quantify the macroeconomic implications of climate change mitigation, but
that do not account for damages from climate change nor adaptation costs (high confidence). For example, compared to
pathways that assume the continuation of policies implemented by the end of 2020, assessed global GDP reached in 2050
is reduced by 1.3–2.7% in modelled pathways assuming coordinated global action starting between now and 2025 at the
latest to limit warming to 2°C (>67%). The corresponding average reduction in annual global GDP growth over 2020–2050
is 0.04–0.09 percentage points. In assessed modelled pathways, regardless of the level of mitigation action, global GDP is
projected to at least double (increase by at least 100%) over 2020–2050. For modelled global pathways in other temperature
categories, the reductions in global GDP in 2050 compared to pathways that assume the continuation of policies implemented
by the end of 2020 are as follows: 2.6–4.2% (C1), 1.6–2.8% (C2), 0.8–2.1% (C4), 0.5–1.2% (C5). The corresponding reductions
in average annual global GDP growth over 2020–2050, in percentage points, are as follows: 0.09–0.14 (C1), 0.05–0.09 (C2),
0.03–0.07 (C4), 0.02–0.04 (C5).66 There are large variations in the modelled effects of mitigation on GDP across regions,
depending notably on economic structure, regional emissions reductions, policy design and level of international cooperation67
(high confidence). Country-level studies also show large variations in the effect of mitigation on GDP depending notably on
the level of mitigation and on the way it is achieved (high confidence). Macroeconomic implications of mitigation co-benefits
and trade-offs are not quantified comprehensively across the above scenarios and depend strongly on mitigation strategies
(high confidence). {3.6, 4.2, Box TS.7, Annex III.I.2, Annex III.I.9, Annex III.I.10 and Annex III.II.3}
C.12.3 Estimates of aggregate economic benefits from avoiding damages from climate change, and from reduced adaptation costs,
increase with the stringency of mitigation (high confidence). Models that incorporate the economic damages from climate
change find that the global cost of limiting warming to 2°C over the 21st century is lower than the global economic benefits
of reducing warming, unless: (i) climate damages are towards the low end of the range; or, (ii) future damages are discounted
at high rates (medium confidence).68 Modelled pathways with a peak in global emissions between now and 2025 at the latest,
compared to modelled pathways with a later peak in global emissions, entail more rapid near-term transitions and higher
up-front investments, but bring long-term gains for the economy, as well as earlier benefits of avoided climate change impacts
(high confidence). The precise magnitude of these gains and benefits is difficult to quantify. {1.7, 3.6, Cross-Working Group
Box 1 in Chapter 3, Box TS.7; AR6 WGII SPM B.4}
64 In modelled pathways that limit warming to 2°C (>67%) or lower.
65 The methodology underlying the assessment is described in the caption to Figure SPM.7.
66 These estimates are based on 311 pathways that report effects of mitigation on GDP and that could be classified in temperature categories, but that do not account
for damages from climate change nor adaptation costs and that mostly do not reflect the economic impacts of mitigation co-benefits and trade-offs. The ranges
given are interquartile ranges. The macroeconomic implications quantified vary largely depending on technology assumptions, climate/emissions target formulation,
model structure and assumptions, and the extent to which pre-existing inefficiencies are considered. Models that produced the pathways classified in temperature
categories do not represent the full diversity of existing modelling paradigms, and there are in the literature models that find higher mitigation costs, or conversely
lower mitigation costs and even gains. {1.7, 3.2, 3.6, Annex III.I.2, Annex III.I.9, Annex III.I.10 and Annex III.II.3}
67 In modelled cost-effective pathways with a globally uniform carbon price, without international financial transfers or complementary policies, carbon intensive
and energy exporting countries are projected to bear relatively higher mitigation costs because of a deeper transformation of their economies and changes in
international energy markets. {3.6}
68 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5°C.
38
SPM
Summary for Policymakers
0 2 4 6
Potential contribution to net emission reduction, 2030 (GtCO2-eq yr–1)
0 2 4 6
GtCO2-eq yr–1
Mitigation options
Many options available now in all sectors are estimated to offer substantial potential to reduce
net emissions by 2030. Relative potentials and costs will vary across countries and in the longer
term compared to 2030.
Energy
Wind energy
Solar energy
Nuclear energy
Bioelectricity
Hydropower
Geothermal energy
Carbon capture and storage (CCS)
Bioelectricity with CCS
Reduce CH4 emission from coal mining
Reduce CH4 emission from oil and gas
AFOLU
Improved sustainable forest management
Carbon sequestration in agriculture
Reduce CH4 and N2O emission in agriculture
Reduced conversion of forests and other ecosystems
Ecosystem restoration, afforestation, reforestation
Reduce food loss and food waste
Shift to balanced, sustainable healthy diets
Buildings
Avoid demand for energy services
Efficient lighting, appliances and equipment
New buildings with high energy performance
Onsite renewable production and use
Improvement of existing building stock
Enhanced use of wood products
Transport
Fuel-efficient light-duty vehicles
Electric light-duty vehicles
Shift to public transportation
Shift to bikes and e-bikes
Fuel-efficient heavy-duty vehicles
Electric heavy-duty vehicles, incl. buses
Shipping – efficiency and optimisation
Aviation – energy efficiency
Biofuels
Industry
Reduction of non-CO2 emissions
Energy efficiency
Material efficiency
Enhanced recycling
Fuel switching (electr, nat. gas, bio-energy, H2)
Feedstock decarbonisation, process change
Carbon capture with utilisation (CCU) and CCS
Cementitious material substitution
Other
Reduce emission of fluorinated gas
Reduce CH4 emissions from solid waste
Reduce CH4 emissions from wastewater
Costs are lower than the reference
0–20 (USD tCO2-eq–1)
20–50 (USD tCO2-eq–1)
50–100 (USD tCO2-eq–1)
100–200 (USD tCO2-eq–1)
Cost not allocated due to high
variability or lack of data
Uncertainty range applies to
the total potential contribution
to emission reduction. The
individual cost ranges are also
associated with uncertainty
Net lifetime cost of options:
Figure SPM.7 | Overview of mitigation options and their estimated ranges of costs and potentials in 2030.
----- -
39
SPM
Summary for Policymakers
Figure SPM.7 (continued): Overview of mitigation options and their estimated ranges of costs and potentials in 2030. Costs shown are net lifetime
costs of avoided greenhouse gas emissions. Costs are calculated relative to a reference technology. The assessments per sector were carried out using a common
methodology, including definition of potentials, target year, reference scenarios, and cost definitions. The mitigation potential (shown in the horizontal axis) is the
quantity of net GHG emission reductions that can be achieved by a given mitigation option relative to a specified emission baseline. Net GHG emission reductions are
the sum of reduced emissions and/or enhanced sinks. The baseline used consists of current policy (around 2019) reference scenarios from the AR6 scenarios database
(25/75 percentile values). The assessment relies on approximately 175 underlying sources, that together give a fair representation of emission reduction potentials across
all regions. The mitigation potentials are assessed independently for each option and are not necessarily additive. {12.2.1, 12.2.2} The length of the solid bars represents
the mitigation potential of an option. The error bars display the full ranges of the estimates for the total mitigation potentials. Sources of uncertainty for the cost estimates
include assumptions on the rate of technological advancement, regional differences, and economies of scale, among others. Those uncertainties are not displayed in
the figure. Potentials are broken down into cost categories, indicated by different colours (see legend). Only discounted lifetime monetary costs are considered. Where
a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such as geographical location,
resource availability, and regional circumstances, and the colours indicate the range of estimates. Costs were taken directly from the underlying studies (mostly in the
period 2015–2020) or recent datasets. No correction for inflation was applied, given the wide cost ranges used. The cost of the reference technologies were also taken
from the underlying studies and recent datasets. Cost reductions through technological learning are taken into account.69
– When interpreting this figure, the following should be taken into account:
– The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) being displaced, the rate of new technology adoption,
and several other factors.
– Cost and mitigation potential estimates were extrapolated from available sectoral studies. Actual costs and potentials would vary by place, context and time.
– Beyond 2030, the relative importance of the assessed mitigation options is expected to change, in particular while pursuing long-term mitigation goals, recognising
also that the emphasis for particular options will vary across regions (for specific mitigation options see SPM Sections C4.1, C5.2, C7.3, C8.3 and C9.1).
– Different options have different feasibilities beyond the cost aspects, which are not reflected in the figure (compare with SPM Section E.1).
– The potentials in the cost range USD100–200 tCO2-eq–1 may be underestimated for some options.
– Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included
because of complexities in attributing such costs to individual technology options.
– Cost range categories are ordered from low to high. This order does not imply any sequence of implementation.
– Externalities are not taken into account. {12.2, Table 12.3, 6.4, Table 7.3, Supplementary Material Table 9.SM.2, Supplementary Material Table 9.SM.3, 10.6, 11.4,
Figure 11.13, Supplementary Material 12.SM.1.2.3}
69 For nuclear energy, modelled costs for long-term storage of radioactive waste are included.
40
SPM
Summary for Policymakers
D. Linkages between Mitigation, Adaptation,
and Sustainable Development
70 Potential risks, knowledge gaps due to the relative immaturity of use of biochar as a soil amendment and unknown impacts of widespread application,
and co-benefits of biochar are reviewed in Section 7.4.3.2.
D.1 Accelerated and equitable climate action in mitigating, and adapting to, climate change impacts is
critical to sustainable development. Climate change actions can also result in some trade-offs. The
trade-offs of individual options could be managed through policy design. The Sustainable Development
Goals (SDGs) adopted under the UN 2030 Agenda for Sustainable Development can be used as a basis
for evaluating climate action in the context of sustainable development. (high confidence) (Figure
SPM.8) {1.6, 3.7, 17.3, Figure TS.29}
D.1.1 Human-induced climate change is a consequence of more than a century of net GHG emissions from unsustainable energy
use, land-use and land use change, lifestyle and patterns of consumption and production. Without urgent, effective and
equitable mitigation actions, climate change increasingly threatens the health and livelihoods of people around the globe,
ecosystem health and biodiversity. There are both synergies and trade-offs between climate action and the pursuit of other
SDGs. Accelerated and equitable climate action in mitigating, and adapting to, climate change impacts is critical to sustainable
development. (high confidence) {1.6, Cross-Chapter Box 5 in Chapter 4, 7.2, 7.3, 17.3; AR6 WGI SPM.A, Figure SPM.2;
AR6 WGII SPM.B2, Figure SPM.3, Figure SPM.4b, Figure SPM.5}
D.1.2 Synergies and trade-offs depend on the development context including inequalities, with consideration of climate justice.
They also depend on means of implementation, intra- and inter-sectoral interactions, cooperation between countries and
regions, the sequencing, timing and stringency of mitigation actions, governance, and policy design. Maximising synergies
and avoiding trade-offs pose particular challenges for developing countries, vulnerable populations, and Indigenous Peoples
with limited institutional, technological and financial capacity, and with constrained social, human, and economic capital.
Trade-offs can be evaluated and minimised by giving emphasis to capacity building, finance, governance, technology transfer,
investments, and development and social equity considerations with meaningful participation of Indigenous Peoples and
vulnerable populations. (high confidence) {1.6, 1.7, 3.7, 5.2, 5.6, 7.4, 7.6, 17.4}
D.1.3 There are potential synergies between sustainable development and energy efficiency, renewable energy, urban planning
with more green spaces, reduced air pollution, and demand-side mitigation including shifts to balanced, sustainable healthy
diets (high confidence). Electrification combined with low-GHG energy, and shifts to public transport can enhance health,
employment, and can elicit energy security and deliver equity (high confidence). In industry, electrification and circular
material flows contribute to reduced environmental pressures and increased economic activity and employment. However,
some industrial options could impose high costs (medium confidence). (Figure SPM.8) {5.2, 8.2, 11.3, 11.5, 17.3, Figure TS.29}
D.1.4 Land-based options such as reforestation and forest conservation, avoided deforestation, restoration and conservation of
natural ecosystems and biodiversity, improved sustainable forest management, agroforestry, soil carbon management and
options that reduce CH4 and N2O emissions in agriculture from livestock and soil, can have multiple synergies with the SDGs.
These include enhancing sustainable agricultural productivity and resilience, food security, providing additional biomass for
human use, and addressing land degradation. Maximising synergies and managing trade-offs depend on specific practices,
scale of implementation, governance, capacity building, integration with existing land use, and the involvement of local
communities and Indigenous Peoples and through benefit-sharing, supported by frameworks such as Land Degradation
Neutrality within the UNCCD. (high confidence) {3.7, 7.4, 12.5, 17.3}
D.1.5 Trade-offs in terms of employment, water use, land-use competition and biodiversity, as well as access to, and the affordability
of, energy, food, and water can be avoided by well-implemented land-based mitigation options, especially those that do
not threaten existing sustainable land uses and land rights, though more frameworks for integrated policy implementation
are required. The sustainability of bioenergy and other bio-based products is influenced by feedstock, land management
practice, climatic region, the context of existing land management, and the timing, scale and speed of deployment. (medium
confidence) {3.5, 3.7, 7.4, 12.4, 12.5, 17.1}
D.1.6 CDR methods such as soil carbon sequestration and biochar70 can improve soil quality and food production capacity. Ecosystem
restoration and reforestation sequester carbon in plants and soil, and can enhance biodiversity and provide additional
41
SPM
Summary for Policymakers
biomass, but can displace food production and livelihoods, which calls for integrated approaches to land-use planning, to
meet multiple objectives including food security. However, due to limited application of some of the options today, there are
some uncertainties about potential benefits. (high confidence) {3.7, 7.4, 7.6, 12.5, 17.3, Table TS.7}
Type of relations:
1 No poverty
2 Zero hunger
3 Good health and wellbeing
4 Quality education
5 Gender equality
6 Clean water and sanitation
7 Affordable and clean energy
8 Decent work and economic growth
9 Industry, innovation and infrastructure
14 Life below water
15 Life on land
16 Peace, justice and strong institutions
17 Partnership for the goals
Confidence level:
High confidence
Medium confidence
Low confidence
Deforestation, loss and
degradation of peatlands
and coastal wetlands
2
Soil carbon management
in cropland and grasslands,
agroforestry, biochar
1
Lower of the two confidence
levels has been reported
4
3 Timber, biomass, agri. feedstock
Related Sustainable Development Goals:
Not assessed due
to limited literature
5
Sectoral and system mitigation options Chapter source
Relation with Sustainable Development Goals
1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17
Urban systems
Urban land use and spatial planning Sections 8.2, 8.4, 8.6
Electrification of the urban energy system Sections 8.2, 8.4, 8.6
District heating and cooling networks Sections 8.2, 8.4, 8.6
Urban green and blue infrastructure Sections 8.2, 8.4, 8.6
Waste prevention, minimisation and management Sections 8.2, 8.4, 8.6
Integrating sectors, strategies and innovations Sections 8.2, 8.4, 8.6
Transport
Fuel efficiency – light-duty vehicle Sections 10.3, 10.4, 10.8
Electric light-duty vehicles Sections 10.3, 10.4, 10.8
Shift to public transport Sections 10.2, 10.8, Table 10.3
Shift to bikes, e-bikes and non motorised transport Sections 10.2, 10.8, Table 10.3
Fuel efficiency – heavy-duty vehicle Sections 10.3, 10.4, 10.8
Fuel shift (including electricity) – heavy-duty vehicle Sections 10.3, 10.4, 10.8
Shipping efficiency, logistics optimisation, new fuels Sections 10.6, 10.8
Aviation – energy efficiency, new fuels Sections 10.5, 10.8
Biofuels Sections 10.3, 10.4, 10.5, 10.6, 10.8
Industry
Energy efficiency Section 11.5.3
Material efficiency and demand reduction Section 11.5.3
Circular material flows Section 11.5.3
Electrification Sections 11.5.3, 6.7.7
CCS and carbon capture and utilisation (CCU) Section 11.5.3
Agriculture, forestry and
other land use (AFOLU)
Carbon sequestration in agriculture
1 Sections 7.3, 7.4, 7.6
Reduce CH4 and N2O emission in agriculture Section 7.4
Reduced conversion of forests and other ecosystems
2 Section 7.4
Improved sustainable forest management Section 7.4
Reduce food loss and food waste Section 7.5
Shift to balanced, sustainable healthy diets Section 7.4
Renewables supply
3 Section 7.6
Ecosystem restoration, reforestation, afforestation Section 7.4
Energy systems
Wind energy Sections 6.4.2, 6.7.7
Solar energy Sections 6.4.2, 6.7.7
Hydropower Section 6.4.2
Geothermal energy Section 6.4.2
Carbon capture and storage (CCS) Section 6.4.2, 6.7.7
Bioenergy Sections 6.4.2, 12.5, Box 6.1
Nuclear power Section 6.4.2, Figure 6.18
10 Reduced inequalities
11 Sustainable cities and communities
12 Responsible consumption and production
13 Climate action
Buildings
Demand-side management Section 9.8, Table 9.5
Highly energy efficient building envelope Section 9.8, Table 9.5
Efficient heating, ventilation and air conditioning (HVAC) Section 9.8, Table 9.5
Efficient appliances Section 9.8, Table 9.5
Building design and performance Section 9.8, Table 9.5
Change in construction methods and circular economy Sections 9.4, 9.5
Change in construction materials Section 9.4
On-site and nearby production and use of renewables Section 9.8, Table 9.5
Synergies
Trade-offs
Both synergies and trade-offs
4
Blanks represent no assessment
5
Mitigation options have synergies with many Sustainable Development Goals, but some options
can also have trade-offs. The synergies and trade-offs vary dependent on context and scale.
Figure SPM.8 | Synergies and trade-offs between sectoral and system mitigation options and the SDGs.
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42
SPM
Summary for Policymakers
Figure SPM.8 (continued): Synergies and trade-offs between sectoral and system mitigation options and the SDGs. The sectoral chapters (Chapters 6–11)
include qualitative assessments of synergies and trade-offs between sectoral mitigation options and the SDGs. Figure SPM.8 presents a summary of the chapter-level
assessment for selected mitigation options (see Supplementary Material Table 17.SM.1 for the underlying assessment). The last column provides a line of sight to the
sectoral chapters, which provide details on context specificity and dependence of interactions on the scale of implementation. Blank cells indicate that interactions have not
been assessed due to limited literature. They do not indicate the absence of interactions between mitigation options and the SDGs. Confidence levels depend on the quality
of evidence and level of agreement in the underlying literature assessed by the sectoral chapters. Where both synergies and trade-offs exist, the lower of the confidence
levels for these interactions is used. Some mitigation options may have applications in more than one sector or system. The interactions between mitigation options and the
SDGs might differ depending on the sector or system, and also on the context and the scale of implementation. Scale of implementation particularly matters when there
is competition for scarce resources. {6.3, 6.4, 6.7, 7.3, 7.4, 7.5, 7.6, 8.2, 8.4, 8.6, Figure 8.4, Supplementary Material Table 8.SM.1, Supplementary Material Table 8.SM.2,
9.4, 9.5, 9.8, Table 9.5, 10.3, 10.4, 10.5, 10.6, 10.8, Table 10.3, 11.5, 12.5, 17.3, Figure 17.1, Supplementary Material Table 17.SM.1, Annex II.IV.12}
D.2 There is a strong link between sustainable development, vulnerability and climate risks. Limited
economic, social and institutional resources often result in high vulnerability and low adaptive
capacity, especially in developing countries (medium confidence). Several response options deliver
both mitigation and adaptation outcomes, especially in human settlements, land management, and
in relation to ecosystems. However, land and aquatic ecosystems can be adversely affected by some
mitigation actions, depending on their implementation (medium confidence). Coordinated cross-sectoral
policies and planning can maximise synergies and avoid or reduce trade-offs between mitigation and
adaptation (high confidence). {3.7, 4.4, 13.8, 17.3; AR6 WGII}
D.2.1 Sustainable urban planning and infrastructure design including green roofs and facades, networks of parks and open spaces,
management of urban forests and wetlands, urban agriculture, and water-sensitive design can deliver both mitigation and
adaptation benefits in settlements (medium confidence). These options can also reduce flood risks, pressure on urban sewer
systems, urban heat island effects, and can deliver health benefits from reduced air pollution (high confidence). There could
also be trade-offs. For example, increasing urban density to reduce travel demand, could imply high vulnerability to heat waves
and flooding (high confidence). (Figure SPM.8) {3.7, 8.2, 8.4, 12.5, 13.8, 17.3}
D.2.2 Land-related mitigation options with potential co-benefits for adaptation include agroforestry, cover crops, intercropping,
perennial plants, restoring natural vegetation and rehabilitating degraded land. These can enhance resilience by maintaining
land productivity and protecting and diversifying livelihoods. Restoration of mangroves and coastal wetlands sequesters
carbon, while also reducing coastal erosion and protecting against storm surges, thus, reducing the risks from sea level rise
and extreme weather. (high confidence) {4.4, 7.4, 7.6, 12.5, 13.8}
D.2.3 Some mitigation options can increase competition for scarce resources including land, water and biomass. Consequently,
these can also reduce adaptive capacity, especially if deployed at larger scale and with high expansion rates thus exacerbating
existing risks, in particular where land and water resources are very limited. Examples include the large-scale or poorly
planned deployment of bioenergy, biochar, and afforestation of naturally unforested land. (high confidence) {12.5, 17.3}
D.2.4 Coordinated policies, equitable partnerships and integration of adaptation and mitigation within and across sectors can
maximise synergies and minimise trade-offs and thereby enhance the support for climate action (medium confidence). Even if
extensive global mitigation efforts are implemented, there will be a large need for financial, technical, and human resources
for adaptation. Absence or limited resources in social and institutional systems can lead to poorly coordinated responses, thus
reducing the potential for maximising mitigation and adaptation benefits, and increasing risk (high confidence). {12.6, 13.8,
17.1, 17.3}
43
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Summary for Policymakers
D.3 Enhanced mitigation and broader action to shift development pathways towards sustainability will
have distributional consequences within and between countries. Attention to equity and broad and
meaningful participation of all relevant actors in decision-making at all scales can build social trust,
and deepen and widen support for transformative changes. (high confidence) {3.6, 4.2, 4.5, 5.2, 13.2,
17.3, 17.4}
D.3.1 Countries at all stages of economic development seek to improve the well-being of people, and their development priorities
reflect different starting points and contexts. Different contexts include social, economic, environmental, cultural, or political
conditions, resource endowment, capabilities, international environment, and history. The enabling conditions for shifting
development pathways towards increased sustainability will therefore also differ, giving rise to different needs. (high
confidence) (Figure SPM.2) {1.6, 1.7, 2.4, 2.6, Cross-Chapter Box 5 in Chapter 4, 4.3.2, 17.4}
D.3.2 Ambitious mitigation pathways imply large and sometimes disruptive changes in economic structure, with significant
distributional consequences, within and between countries. Equity remains a central element in the UN climate regime,
notwithstanding shifts in differentiation between states over time and challenges in assessing fair shares. Distributional
consequences within and between countries include shifting of income and employment during the transition from
high- to low-emissions activities. While some jobs may be lost, low-emissions development can also open more opportunities
to enhance skills and create more jobs that last, with differences across countries and sectors. Integrated policy packages can
improve the ability to integrate considerations of equity, gender equality and justice. (high confidence) {1.4, 1.6, 3.6, 4.2, 5.2,
Box 11.1, 14.3, 15.2, 15.5, 15.6}
D.3.3 Inequalities in the distribution of emissions and in the impacts of mitigation policies within countries affect social cohesion
and the acceptability of mitigation and other environmental policies. Equity and just transitions can enable deeper ambitions
for accelerated mitigation. Applying just transition principles and implementing them through collective and participatory
decision-making processes is an effective way of integrating equity principles into policies at all scales, in different ways
depending on national circumstances (medium confidence). This is already taking place in many countries and regions, as
national just transition commissions or task forces, and related national policies, have been established in several countries.
A multitude of actors, networks, and movements are engaged (high confidence). {1.6, 1.7, 2.4, 2.6, 4.5, 13.2, 13.9, 14.3, 14.5}
D.3.4 Broadening equitable access to domestic and international finance, technologies that facilitate mitigation, and capacity, while
explicitly addressing needs can further integrate equity and justice into national and international policies and act as a catalyst
for accelerating mitigation and shifting development pathways (medium confidence). The consideration of ethics and equity
can help address the uneven distribution of adverse impacts associated with 1.5°C and higher levels of global warming,
in all societies (high confidence). Consideration of climate justice can help to facilitate shifting development pathways
towards sustainability, including through equitable sharing of benefits and burdens of mitigation, increasing resilience to the
impacts of climate change, especially for vulnerable countries and communities, and equitably supporting those in need (high
confidence). {1.4, 1.6, 1.7, 3.6, 4.2, 4.5, Box 5.10, 13.4, 13.8, 13.9, 14.3, 14.5, 15.2, 15.5, 15.6, 16.5, 17.3, 17.4; SR1.5 SPM,
AR6 WGII Chapter 18}
44
SPM
Summary for Policymakers
E. Strengthening the Response
71 In this report, the term ‘feasibility’ refers to the potential for a mitigation or adaptation option to be implemented. Factors influencing feasibility are context-dependent
and may change over time. Feasibility depends on geophysical, environmental-ecological, technological, economic, socio-cultural and institutional factors that enable
or constrain the implementation of an option. The feasibility of options may change when different options are combined and increase when enabling conditions
are strengthened.
72 In this report, the term ‘enabling conditions’ refers to conditions that enhance the feasibility of adaptation and mitigation options. Enabling conditions include
finance, technological innovation, strengthening policy instruments, institutional capacity, multi-level governance, and changes in human behaviour and lifestyles.
73 The future feasibility challenges described in the modelled pathways may differ from the real-world feasibility experiences of the past.
E.1 There are mitigation options which are feasible71 to deploy at scale in the near term. Feasibility
differs across sectors and regions, and according to capacities and the speed and scale of
implementation. Barriers to feasibility would need to be reduced or removed, and enabling conditions72
strengthened to deploy mitigation options at scale. These barriers and enablers include geophysical,
environmental-ecological, technological, and economic factors, and especially institutional and
socio-cultural factors. Strengthened near-term action beyond the NDCs (announced prior to UNFCCC
COP26) can reduce and/or avoid long-term feasibility challenges of global modelled pathways that
limit warming to 1.5°C (>50%) with no or limited overshoot. (high confidence) {3.8, 6.4, 8.5, 9.9, 10.8,
12.3, Figure TS.31, Annex II.IV.11}
E.1.1 Several mitigation options, notably solar energy, wind energy, electrification of urban systems, urban green infrastructure,
energy efficiency, demand-side management, improved forest- and crop/grassland management, and reduced food waste and
loss, are technically viable, are becoming increasingly cost effective, and are generally supported by the public. This enables
deployment in many regions (high confidence). While many mitigation options have environmental co-benefits, including
improved air quality and reducing toxic waste, many also have adverse environmental impacts, such as reduced biodiversity,
when applied at very large scale, for example very large scale bioenergy or large scale use of battery storage, that would
have to be managed (medium confidence). Almost all mitigation options face institutional barriers that need to be addressed
to enable their application at scale (medium confidence). {6.4, Figure 6.19, 7.4, 8.5, Figure 8.19, 9.9, Figure 9.20, 10.8,
Figure 10.23, 12.3, Figure 12.4, Figure TS.31}
E.1.2 The feasibility of mitigation options varies according to context and time. For example, the institutional capacity to support
deployment varies across countries; the feasibility of options that involve large-scale land-use changes varies across regions;
spatial planning has a higher potential at early stages of urban development; the potential of geothermal is site specific;
and capacities, cultural and local conditions can either inhibit or enable demand-side responses. The deployment of solar
and wind energy has been assessed to become increasingly feasible over time. The feasibility of some options can increase
when combined or integrated, such as using land for both agriculture and centralised solar production. (high confidence)
{6.4, 6.6, Supplementary Material Table 6.SM, 7.4, 8.5, Supplementary Material Table 8.SM.2, 9.9, Supplementary Material
Table 9.SM.1, 10.8, Appendix 10.3, 12.3, Tables 12.SM.2.1 to 12.SM.2.6}
E.1.3 Feasibility depends on the scale and speed of implementation. Most options face barriers when they are implemented rapidly
at a large scale, but the scale at which barriers manifest themselves varies. Strengthened and coordinated near-term actions in
cost-effective modelled global pathways that limit warming to 2°C (>67%) or lower, reduce the overall risks to the feasibility
of the system transitions, compared to modelled pathways with relatively delayed or uncoordinated action.73 (high confidence)
{3.8, 6.4, 10.8, 12.3}
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Summary for Policymakers
E.2 In all countries, mitigation efforts embedded within the wider development context can increase the
pace, depth and breadth of emissions reductions (medium confidence). Policies that shift development
pathways towards sustainability can broaden the portfolio of available mitigation responses, and
enable the pursuit of synergies with development objectives (medium confidence). Actions can be
taken now to shift development pathways and accelerate mitigation and transitions across systems
(high confidence). {4.3, 4.4, Cross-Chapter Box 5 in Chapter 4, 5.2, 5.4, 13.9, 14.5, 15.6, 16.3, 16.4, 16.5}
E.2.1 Current development pathways may create behavioural, spatial, economic and social barriers to accelerated mitigation at all
scales (high confidence). Choices made by policymakers, citizens, the private sector and other stakeholders influence societies’
development pathways (high confidence). Actions that steer, for example, energy and land systems transitions, economy-wide
structural change, and behaviour change, can shift development pathways towards sustainability74 (medium confidence).
{4.3, Cross-Chapter Box 5 in Chapter 4, 5.4, 13.9}
E.2.2 Combining mitigation with policies to shift development pathways, such as broader sectoral policies, policies that induce
lifestyle or behaviour changes, financial regulation, or macroeconomic policies can overcome barriers and open up a broader
range of mitigation options (high confidence). It can also facilitate the combination of mitigation and other development goals
(high confidence). For example, measures promoting walkable urban areas combined with electrification and renewable energy
can create health co-benefits from cleaner air and benefits from enhanced mobility (high confidence). Coordinated housing
policies that broaden relocation options can make mitigation measures in transport more effective (medium confidence).
{3.2, 4.3, 4.4, Cross-Chapter Box 5 in Chapter 4, 5.3, 8.2, 8.4}
E.2.3 Institutional and regulatory capacity, innovation, finance, improved governance and collaboration across scales, and
multi-objective policies enable enhanced mitigation and shifts in development pathways. Such interventions can be mutually
reinforcing and establish positive feedback mechanisms, resulting in accelerated mitigation. (high confidence) {4.4, 5.4,
Figure 5.14, 5.6, 9.9, 13.9, 14.5, 15.6, 16.3, 16.4, 16.5, Cross-Chapter Box 12 in Chapter 16}
E.2.4 Enhanced action on all the above enabling conditions can be taken now (high confidence). In some situations, such as with
innovation in technology at an early stage of development and some changes in behaviour towards low emissions, because
the enabling conditions may take time to be established, action in the near term can yield accelerated mitigation in the
mid-term (medium confidence). In other situations, the enabling conditions can be put in place and yield results in a relatively
short time frame, for example the provision of energy related information, advice and feedback to promote energy saving
behaviour (high confidence). {4.4, 5.4, Figure 5.14, 5.6, 6.7, 9.9, 13.9, 14.5, 15.6, 16.3, 16.4, 16.5, Cross-Chapter Box 12
in Chapter 16}
E.3 Climate governance, acting through laws, strategies and institutions, based on national circumstances,
supports mitigation by providing frameworks through which diverse actors interact, and a basis for
policy development and implementation (medium confidence). Climate governance is most effective
when it integrates across multiple policy domains, helps realise synergies and minimise trade-offs,
and connects national and sub-national policymaking levels (high confidence). Effective and equitable
climate governance builds on engagement with civil society actors, political actors, businesses, youth,
labour, media, Indigenous Peoples and local communities (medium confidence). {5.4, 5.6, 8.5, 9.9, 13.2,
13.7, 13.9}
E.3.1 Climate governance enables mitigation by providing an overall direction, setting targets, mainstreaming climate action
across policy domains, enhancing regulatory certainty, creating specialised organisations and creating the context to mobilise
finance (medium confidence). These functions can be promoted by climate-relevant laws, which are growing in number, or
climate strategies, among others, based on national and sub-national context (medium confidence). Framework laws set
an overarching legal basis, either operating through a target and implementation approach, or a sectoral mainstreaming
approach, or both, depending on national circumstance (medium confidence). Direct national and sub-national laws that
explicitly target mitigation and indirect laws that impact emissions through mitigation-related policy domains have both been
shown to be relevant to mitigation outcomes (medium confidence). {13.2}
74 Sustainability may be interpreted differently in various contexts as societies pursue a variety of sustainable development objectives.
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E.3.2 Effective national climate institutions address coordination across sectors, scales and actors, build consensus for action
among diverse interests, and inform strategy setting (medium confidence). These functions are often accomplished through
independent national expert bodies, and high-level coordinating bodies that transcend departmental mandates. Complementary
sub-national institutions tailor mitigation actions to local context and enable experimentation but can be limited by inequities
and resource and capacity constraints (high confidence). Effective governance requires adequate institutional capacity at all
levels (high confidence). {4.4, 8.5, 9.9, 11.3, 11.5, 11.6, 13.2, 13.5, 13.7, 13.9}
E.3.3 The extent to which civil society actors, political actors, businesses, youth, labour, media, Indigenous Peoples, and local
communities are engaged influences political support for climate change mitigation and eventual policy outcomes. Structural
factors of national circumstances and capabilities (e.g., economic and natural endowments, political systems and cultural
factors and gender considerations) affect the breadth and depth of climate governance. Mitigation options that align with
prevalent ideas, values and beliefs are more easily adopted and implemented. Climate-related litigation, for example by
governments, private sector, civil society and individuals, is growing - with a large number of cases in some developed
countries, and with a much smaller number in some developing countries - and in some cases, has influenced the outcome
and ambition of climate governance. (medium confidence) {5.2, 5.4, 5.5, 5.6, 9.9, 13.3, 13.4}
E.4 Many regulatory and economic instruments have already been deployed successfully. Instrument
design can help address equity and other objectives. These instruments could support deep emissions
reductions and stimulate innovation if scaled up and applied more widely (high confidence). Policy
packages that enable innovation and build capacity are better able to support a shift towards
equitable low-emission futures than are individual policies (high confidence). Economy-wide packages,
consistent with national circumstances, can meet short-term economic goals while reducing emissions
and shifting development pathways towards sustainability (medium confidence). {Cross-Chapter Box 5
in Chapter 4, 13.6, 13.7, 13.9, 16.3, 16.4, 16.6}
E.4.1 A wide range of regulatory instruments at the sectoral level have proven effective in reducing emissions. These instruments,
and broad-based approaches including relevant economic instruments,75 are complementary (high confidence). Regulatory
instruments that are designed to be implemented with flexibility mechanisms can reduce costs (medium confidence). Scaling
up and enhancing the use of regulatory instruments, consistent with national circumstances, could improve mitigation
outcomes in sectoral applications, including but not limited to renewable energy, land use and zoning, building codes, vehicle
and energy efficiency, fuel standards, and low-emissions industrial processes and materials (high confidence). {6.7, 7.6, 8.4,
9.9, 10.4, 11.5, 11.6, 13.6}
E.4.2 Economic instruments have been effective in reducing emissions, complemented by regulatory instruments mainly at the
national and also sub-national and regional level (high confidence). Where implemented, carbon pricing instruments have
incentivised low-cost emissions reduction measures, but have been less effective, on their own and at prevailing prices during
the assessment period, in promoting the higher-cost measures necessary for further reductions (medium confidence). Equity and
distributional impacts of such carbon pricing instruments can be addressed by using revenue from carbon taxes or emissions
trading to support low-income households, among other approaches (high confidence). Practical experience has informed
instrument design and helped to improve predictability, environmental effectiveness, economic efficiency, distributional goals
and social acceptance (high confidence). Removing fossil fuel subsidies would reduce emissions, improve public revenue and
macroeconomic performance, and yield other environmental and sustainable development benefits; subsidy removal may
have adverse distributional impacts especially on the most economically vulnerable groups which, in some cases can be
mitigated by measures such as redistributing revenue saved, all of which depend on national circumstances (high confidence);
fossil fuel subsidy removal is projected by various studies to reduce global CO2 emissions by 1–4%, and GHG emissions by up
to 10% by 2030, varying across regions (medium confidence). {6.3, 13.6}
E.4.3 Low-emission technological innovation is strengthened through the combination of dedicated technology-push policies and
investments (e.g., for scientific training, R&D, demonstration), with tailored demand-pull policies (e.g., standards, feed-in
tariffs, taxes), which create incentives and market opportunities. Developing countries’ abilities to deploy low-emission
technologies, seize socio-economic benefits and manage trade-offs would be enhanced with increased financial resources
and capacity for innovation which are currently concentrated in developed countries, alongside technology transfer. (high
confidence) {16.2, 16.3, 16.4, 16.5}
75 Economic instruments are structured to provide a financial incentive to reduce emissions and include, among others, market- and price-based instruments.
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E.4.4 Effective policy packages would be comprehensive in coverage, harnessed to a clear vision for change, balanced across objectives,
aligned with specific technology and system needs, consistent in terms of design and tailored to national circumstances.
They are better able to realise synergies and avoid trade-offs across climate and development objectives. Examples include:
emissions reductions from buildings through a mix of efficiency targets, building codes, appliance performance standards,
information provision, carbon pricing, finance and technical assistance; and industrial GHG emissions reductions through
innovation support, market creation and capacity building. (high confidence) {4.4, 6.7, 9.9, 11.6, 13.7, 13.9, 16.3, 16.4}
E.4.5 Economy-wide packages that support mitigation and avoid negative environmental outcomes include: long-term public
spending commitments; pricing reform; and investment in education and training, natural capital, R&D and infrastructure (high
confidence). They can meet short-term economic goals while reducing emissions and shifting development pathways towards
sustainability (medium confidence). Infrastructure investments can be designed to promote low-emissions futures that meet
development needs (medium confidence). {Cross-Chapter Box 5 in Chapter 4, 5.4, 5.6, 8.5, 13.6, 13.9, 16.3, 16.5, 16.6}
E.4.6 National policies to support technology development and diffusion, and participation in international markets for emission
reduction, can bring positive spillover effects for other countries (medium confidence), although reduced demand for fossil
fuels could result in costs to exporting countries (high confidence). There is no consistent evidence that current emission
trading systems have led to significant emissions leakage, which can be attributed to design features aimed at minimising
competitiveness effects, among other reasons (medium confidence). {13.6, 13.7, 13.8, 16.2, 16.3, 16.4}
E.5 Tracked financial flows fall short of the levels needed to achieve mitigation goals across all sectors
and regions. The challenge of closing gaps is largest in developing countries as a whole. Scaling up
mitigation financial flows can be supported by clear policy choices and signals from governments
and the international community (high confidence). Accelerated international financial cooperation is
a critical enabler of low-GHG and just transitions, and can address inequities in access to finance and
the costs of, and vulnerability to, the impacts of climate change (high confidence). {15.2, 15.3, 15.4,
15.5, 15.6}
E.5.1 Average annual modelled investment requirements for 2020 to 2030 in scenarios that limit warming to 2°C or 1.5°C are a factor
of three to six greater than current levels, and total mitigation investments (public, private, domestic and international) would
need to increase across all sectors and regions (medium confidence). Mitigation investment gaps are wide for all sectors,
and widest for the AFOLU sector in relative terms and for developing countries76 (high confidence). Financing and investment
requirements for adaptation, reduction of losses and damages, general infrastructure, regulatory environment and capacity
building, and climate-responsive social protection further exacerbate the magnitude of the challenges for developing countries
to attract financing (high confidence). {3.2, 14.4, 15.1, 15.2, 15.3, 15.4, 15.5}
E.5.2 There is sufficient global capital and liquidity to close global investment gaps, given the size of the global financial system,
but there are barriers to redirect capital to climate action both within and outside the global financial sector, and in
the macroeconomic headwinds facing developing regions. Barriers to the deployment of commercial finance from within the
financial sector as well as macroeconomic considerations include: inadequate assessment of climate-related risks and
investment opportunities; regional mismatch between available capital and investment needs; home bias factors; country
indebtedness levels; economic vulnerability; and limited institutional capacities (high confidence). Challenges from outside
the financial sector include: limited local capital markets; unattractive risk-return profiles, in particular due to missing or weak
regulatory environments consistent with ambition levels; limited institutional capacity to ensure safeguards; standardisation,
aggregation, scalability and replicability of investment opportunities and financing models; and, a pipeline ready for commercial
investments. (high confidence) {15.2, 15.3, 15.5, 15.6}
E.5.3 Accelerated financial support for developing countries from developed countries and other sources is a critical enabler to
enhance mitigation action and address inequities in access to finance, including its costs, terms and conditions, and economic
vulnerability to climate change for developing countries (high confidence). Scaled-up public grants for mitigation and
adaptation funding for vulnerable regions, especially in Sub-Saharan Africa, would be cost-effective and have high social
returns in terms of access to basic energy (high confidence). Options for scaling up mitigation in developing regions include:
increased levels of public finance and publicly mobilised private finance flows from developed to developing countries in the
context of the USD100 billion-a-year goal; increase the use of public guarantees to reduce risks and leverage private flows
76 In modelled pathways, regional investments are projected to occur when and where they are most cost-effective to limit global warming. The model quantifications
help to identify high-priority areas for cost-effective investments, but do not provide any indication on who would finance the regional investments.
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at lower cost; local capital markets development; and building greater trust in international cooperation processes (high
confidence). A coordinated effort to make the post-pandemic recovery sustainable and increased flows of financing over the
next decade can accelerate climate action, including in developing regions and countries facing high debt costs, debt distress
and macroeconomic uncertainty (high confidence). {15.2, 15.3, 15.4, 15.5, 15.6, Box 15.6}
E.5.4 Clear signalling by governments and the international community, including a stronger alignment of public sector finance and
policy, and higher levels of public sector climate finance, reduces uncertainty and transition risks for the private sector. Depending
on national contexts, investors and financial intermediaries, central banks, and financial regulators can support climate action
and can shift the systemic underpricing of climate-related risk by increasing awareness, transparency and consideration of
climate-related risk, and investment opportunities. Financial flows can also be aligned with funding needs through: greater
support for technology development; a continued role for multilateral and national climate funds and development banks;
lowering financing costs for underserved groups through entities such as green banks existing in some countries, funds and
risk-sharing mechanisms; economic instruments which consider economic and social equity and distributional impacts;
gender-responsive and women-empowerment programmes as well as enhanced access to finance for local communities and
Indigenous Peoples and small land owners; and greater public-private cooperation. (high confidence) {15.2, 15.5, 15.6}
E.6 International cooperation is a critical enabler for achieving ambitious climate change mitigation goals.
The UNFCCC, Kyoto Protocol, and Paris Agreement are supporting rising levels of national ambition and
encouraging development and implementation of climate policies, although gaps remain. Partnerships,
agreements, institutions and initiatives operating at the sub-global and sectoral levels and engaging
multiple actors are emerging, with mixed levels of effectiveness. (high confidence) {8.5, 14.2, 14.3,
14.5, 14.6, 15.6, 16.5}
E.6.1 Internationally agreed processes and goals, such as those in the UNFCCC, Kyoto Protocol, and Paris Agreement – including
transparency requirements for national reporting on emissions, actions and support, and tracking progress towards the
achievement of Nationally Determined Contributions – are enhancing international cooperation, national ambition and policy
development. International financial, technology and capacity building support to developing countries will enable greater
implementation and encourage ambitious Nationally Determined Contributions over time. (medium confidence) {14.3}
E.6.2 International cooperation on technology development and transfer accompanied by capacity building, knowledge sharing,
and technical and financial support can accelerate the global diffusion of mitigation technologies, practices and policies at
national and sub-national levels, and align these with other development objectives (high confidence). Challenges in and
opportunities to enhance innovation cooperation exist, including in the implementation of elements of the UNFCCC and the
Paris Agreement as per the literature assessed, such as in relation to technology development and transfer, and finance (high
confidence). International cooperation on innovation works best when tailored to specific institutional and capability contexts,
when it benefits local value chains, when partners collaborate equitably and on voluntary and mutually agreed terms, when
all relevant voices are heard, and when capacity building is an integral part of the effort (medium confidence). Support to
strengthen technological innovation systems and innovation capabilities, including through financial support in developing
countries would enhance engagement in and improve international cooperation on innovation (high confidence). {4.4, 14.2,
14.4, 16.3, 16.5, 16.6}
E.6.3 Transnational partnerships can stimulate policy development, low-emissions technology diffusion and emission reductions by
linking sub-national and other actors, including cities, regions, non-governmental organisations and private sector entities, and
by enhancing interactions between state and non-state actors. While this potential of transnational partnerships is evident,
uncertainties remain over their costs, feasibility, and effectiveness. Transnational networks of city governments are leading to
enhanced ambition and policy development and a growing exchange of experience and best practices (medium confidence).
{8.5, 11.6, 14.5, 16.5, Cross-Chapter Box 12 in Chapter 16}
E.6.4 International environmental and sectoral agreements, institutions, and initiatives are helping, and in some cases may help, to
stimulate low-GHG emissions investment and reduce emissions. Agreements addressing ozone depletion and transboundary
air pollution are contributing to mitigation, and in other areas, such as atmospheric emissions of mercury, may contribute to
mitigation (high confidence). Trade rules have the potential to stimulate international adoption of mitigation technologies
and policies, but may also limit countries’ ability to adopt trade-related climate policies (medium confidence). Current sectoral
levels of ambition vary, with emission reduction aspirations in international aviation and shipping lower than in many other
sectors (medium confidence). {14.5, 14.6}
Approved Summary for Policymakers IPCC AR6 SYR
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SYNTHESIS REPORT
OF THE IPCC SIXTH ASSESSMENT REPORT (AR6)
Summary for Policymakers
Core Writing Team: Hoesung Lee (Chair), Katherine Calvin (USA), Dipak Dasgupta (India/USA), Gerhard
Krinner (France/Germany), Aditi Mukherji (India), Peter Thorne (Ireland/United Kingdom), Christopher
Trisos (South Africa), José Romero (Switzerland), Paulina Aldunce (Chile), Ko Barrett (USA), Gabriel Blanco
(Argentina), William W. L. Cheung (Canada), Sarah L. Connors (France/United Kingdom), Fatima Denton
(The Gambia), Aïda Diongue-Niang (Senegal), David Dodman (Jamaica/United Kingdom/Netherlands),
Matthias Garschagen (Germany), Oliver Geden (Germany), Bronwyn Hayward (New Zealand), Christopher
Jones (United Kingdom), Frank Jotzo (Australia), Thelma Krug (Brazil), Rodel Lasco (Philippines), June-Yi
Lee (Republic of Korea), Valérie Masson-Delmotte (France), Malte Meinshausen (Australia/Germany), Katja
Mintenbeck (Germany), Abdalah Mokssit (Morocco), Friederike E. L. Otto (United Kingdom/Germany), Minal
Pathak (India), Anna Pirani (Italy), Elvira Poloczanska (UK/Australia), Hans-Otto Pörtner (Germany), Aromar
Revi (India), Debra C. Roberts (South Africa), Joyashree Roy (India/Thailand), Alex C. Ruane (USA), Jim Skea
(United Kingdom), Priyadarshi R. Shukla (India), Raphael Slade (United Kingdom), Aimée Slangen (The
Netherlands), Youba Sokona (Mali), Anna A. Sörensson (Argentina), Melinda Tignor (USA/Germany), Detlef
van Vuuren (The Netherlands), Yi-Ming Wei (China), Harald Winkler (South Africa), Panmao Zhai (China),
Zinta Zommers (Latvia)
Extended Writing Team: Jean-Charles Hourcade (France), Francis X. Johnson (Thailand/Sweden), Shonali
Pachauri (Austria/India), Nicholas P. Simpson (South Africa/Zimbabwe), Chandni Singh (India), Adelle
Thomas (Bahamas), Edmond Totin (Benin)
Contributing Authors: Andrés Alegría (Germany/Honduras), Kyle Armour (USA), Birgit Bednar-Friedl
(Austria), Kornelis Blok (The Netherlands) Guéladio Cissé (Switzerland/Mauritania/France), Frank Dentener
(EU/Netherlands), Siri Eriksen (Norway), Erich Fischer (Switzerland), Gregory Garner (USA), Céline Guivarch
(France), Marjolijn Haasnoot (The Netherlands), Gerrit Hansen (Germany), Matthias Hauser (Switzerland), Ed
Hawkins (UK), Tim Hermans (The Netherlands), Robert Kopp (USA), Noëmie Leprince-Ringuet (France),
Debora Ley (Mexico/Guatemala), Jared Lewis (Australia/New Zealand), Chloé Ludden (Germany/France),
Zebedee Nicholls (Australia), Leila Niamir (Iran/The Netherlands/Austria), Shreya Some (India/Thailand),
Sophie Szopa (France), Blair Trewin (Australia), Kaj-Ivar van der Wijst (The Netherlands), Gundula Winter
(The Netherlands/Germany), Maximilian Witting (Germany)
Review Editors: Paola Arias (Colombia), Mercedes Bustamante (Brazil), Ismail Elgizouli (Sudan), Gregory
Flato (Canada), Mark Howden (Australia), Carlos Méndez (Venezuela), Joy Pereira (Malaysia), Ramón Pichs-
Madruga (Cuba), Steven K Rose (USA), Yamina Saheb (Algeria/France), Roberto Sánchez (Mexico), Diana
Ürge-Vorsatz (Hungary), Cunde Xiao (China), Noureddine Yassaa (Algeria)
Scientific Steering Committee: Hoesung Lee (Chair, IPCC), Amjad Abdulla (Maldives), Edvin Aldrian
(Indonesia), Ko Barrett (United States of America), Eduardo Calvo (Peru), Carlo Carraro (Italy), Fatima
Driouech (Morocco), Andreas Fischlin (Switzerland), Jan Fuglestvedt (Norway), Diriba Korecha Dadi
(Ethiopia), Thelma Krug (Brazil), Nagmeldin G.E. Mahmoud (Sudan), Valérie Masson-Delmotte (France),
Carlos Méndez (Venezuela), Joy Jacqueline Pereira (Malaysia), Ramón Pichs-Madruga (Cuba), Hans-Otto
Pörtner (Germany), Andy Reisinger (New Zealand), Debra Roberts (South Africa), Sergey Semenov (Russian
Federation), Priyadarshi Shukla (India), Jim Skea (United Kingdom), Youba Sokona (Mali), Kiyoto Tanabe
(Japan), Muhammad Irfan Tariq (Pakistan), Diana Ürge-Vorsatz (Hungary), Carolina Vera (Argentina), Pius
Yanda (United Republic of Tanzania), Noureddine Yassaa (Algeria), Taha M. Zatari (Saudi Arabia), Panmao
Zhai (China)
Visual Conception and Information Design: Arlene Birt (USA), Meeyoung Ha (Republic of Korea)
Notes: TSU Compiled Version
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Table of Contents
Introduction ..................................................................................................................................................... 3
A. Current Status and Trends..................................................................................................................... 4
Box SPM.1 Scenarios and pathways.............................................................................................................. 9
B. Future Climate Change, Risks, and Long-Term Responses.............................................................. 12
C. Responses in the Near Term................................................................................................................. 25
Sources cited in this Summary for Policymakers (SPM)
References for material contained in this report are given in curly brackets {} at the end of each paragraph.
In the Summary for Policymakers, the references refer to the numbers of the Sections, figures, tables and
boxes in the underlying Longer Report of the Synthesis Report, or to other sections of the SPM itself (in
round brackets).
Other IPCC reports cited in this Synthesis Report:
AR5 Fifth Assessment Report
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Introduction
This Synthesis Report (SYR) of the IPCC Sixth Assessment Report (AR6) summarises the state of knowledge
of climate change, its widespread impacts and risks, and climate change mitigation and adaptation. It integrates
the main findings of the Sixth Assessment Report (AR6) based on contributions from the three Working
Groups1, and the three Special Reports2. The summary for Policymakers (SPM) is structured in three parts:
SPM.A Current Status and Trends, SPM.B Future Climate Change, Risks, and Long-Term Responses, and
SPM.C Responses in the Near Term3.
This report recognizes the interdependence of climate, ecosystems and biodiversity, and human societies; the
value of diverse forms of knowledge; and the close linkages between climate change adaptation, mitigation,
ecosystem health, human well-being and sustainable development, and reflects the increasing diversity of actors
involved in climate action.
Based on scientific understanding, key findings can be formulated as statements of fact or associated with an
assessed level of confidence using the IPCC calibrated language4.
1 The three Working Group contributions to AR6 are: AR6 Climate Change 2021: The Physical Science Basis; AR6 Climate Change
2022: Impacts, Adaptation and Vulnerability; and AR6 Climate Change 2022: Mitigation of Climate Change. Their assessments cover
scientific literature accepted for publication respectively by 31 January 2021, 1 September 2021 and 11 October 2021.
2 The three Special Reports are: Global Warming of 1.5°C (2018): an IPCC Special Report on the impacts of global warming of 1.5°C
above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to
the threat of climate change, sustainable development, and efforts to eradicate poverty (SR1.5); Climate Change and Land (2019): an
IPCC Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse
gas fluxes in terrestrial ecosystems (SRCCL); and The Ocean and Cryosphere in a Changing Climate (2019) (SROCC). The Special
Reports cover scientific literature accepted for publication respectively by 15 May 2018, 7 April 2019 and 15 May 2019.
3 In this report, the near term is defined as the period until 2040. The long term is defined as the period beyond 2040.
4 Each finding is grounded in an evaluation of underlying evidence and agreement. The IPCC calibrated language uses five qualifiers to
express a level of confidence: very low, low, medium, high and very high, and typeset in italics, for example, medium confidence. The
following terms are used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely
90–100%, likely 66–100%, more likely than not >50–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%,
exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%; more likely than not >50–100%; and extremely unlikely 0–
5%) are also used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely. This is consistent with AR5 and the other
AR6 Reports.
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A. Current Status and Trends
Observed Warming and its Causes
A.1 Human activities, principally through emissions of greenhouse gases, have unequivocally caused
global warming, with global surface temperature reaching 1.1°C above 1850–1900 in 2011–2020. Global
greenhouse gas emissions have continued to increase, with unequal historical and ongoing contributions
arising from unsustainable energy use, land use and land-use change, lifestyles and patterns of
consumption and production across regions, between and within countries, and among individuals (high
confidence). {2.1, Figure 2.1, Figure 2.2}
A.1.1 Global surface temperature was 1.09°C [0.95°C–1.20°C]5 higher in 2011–2020 than 1850–19006, with
larger increases over land (1.59°C [1.34°C–1.83°C]) than over the ocean (0.88°C [0.68°C–1.01°C]). Global
surface temperature in the first two decades of the 21st century (2001-2020) was 0.99 [0.84 to 1.10]°C higher
than 1850-1900. Global surface temperature has increased faster since 1970 than in any other 50-year period
over at least the last 2000 years (high confidence). {2.1.1, Figure 2.1}
A.1.2 The likely range of total human-caused global surface temperature increase from 1850–1900 to 2010–
20197 is 0.8°C–1.3°C, with a best estimate of 1.07°C. Over this period, it is likely that well-mixed greenhouse
gases (GHGs) contributed a warming of 1.0°C–2.0°C8, and other human drivers (principally aerosols)
contributed a cooling of 0.0°C–0.8°C, natural (solar and volcanic) drivers changed global surface temperature
by –0.1°C to +0.1°C, and internal variability changed it by –0.2°C to +0.2°C. {2.1.1, Figure 2.1}
A.1.3 Observed increases in well-mixed GHG concentrations since around 1750 are unequivocally caused by
GHG emissions from human activities over this period. Historical cumulative net CO2 emissions from 1850 to
2019 were 2400±240 GtCO2 of which more than half (58%) occurred between 1850 and 1989, and about 42%
occurred between 1990 and 2019 (high confidence). In 2019, atmospheric CO2 concentrations (410 parts per
million) were higher than at any time in at least 2 million years (high confidence), and concentrations of methane
(1866 parts per billion) and nitrous oxide (332 parts per billion) were higher than at any time in at least 800,000
years (very high confidence). {2.1.1, Figure 2.1}
A.1.4 Global net anthropogenic GHG emissions have been estimated to be 59±6.6 GtCO2-eq9 in 2019, about
12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) higher than in 1990, with the largest share
and growth in gross GHG emissions occurring in CO2 from fossil fuels combustion and industrial processes
(CO2-FFI) followed by methane, whereas the highest relative growth occurred in fluorinated gases (F-gases),
starting from low levels in 1990. Average annual GHG emissions during 2010-2019 were higher than in any
previous decade on record, while the rate of growth between 2010 and 2019 (1.3% year-1) was lower than that
between 2000 and 2009 (2.1% year-1). In 2019, approximately 79% of global GHG emissions came from the
sectors of energy, industry, transport and buildings together and 22%10 from agriculture, forestry and other land
use (AFOLU). Emissions reductions in CO2-FFI due to improvements in energy intensity of GDP and carbon
intensity of energy, have been less than emissions increases from rising global activity levels in industry, energy
supply, transport, agriculture and buildings. (high confidence) {2.1.1}
5 Ranges given throughout the SPM represent very likely ranges (5–95% range) unless otherwise stated.
6 The estimated increase in global surface temperature since AR5 is principally due to further warming since 2003–2012 (+0.19°C
[0.16°C–0.22°C]). Additionally, methodological advances and new datasets have provided a more complete spatial representation of
changes in surface temperature, including in the Arctic. These and other improvements have also increased the estimate of global surface
temperature change by approximately 0.1°C, but this increase does not represent additional physical warming since AR5.
7 The period distinction with A.1.1 arises because the attribution studies consider this slightly earlier period. The observed warming to
2010–2019 is 1.06°C [0.88°C–1.21°C].
8 Contributions from emissions to the 2010-2019 warming relative to 1850-1900 assessed from radiative forcing studies are: CO2 0.8
[0.5 to 1.2]°C; methane 0.5 [0.3 to 0.8]°C; nitrous oxide 0.1 [0.0 to 0.2]°C and fluorinated gases 0.1 [0.0 to 0.2]°C. {2.1.1}
9 GHG emission metrics are used to express emissions of different greenhouse gases in a common unit. Aggregated GHG emissions in
this report are stated in CO2-equivalents (CO2-eq) using the Global Warming Potential with a time horizon of 100 years (GWP100) with
values based on the contribution of Working Group I to the AR6. The AR6 WGI and WGIII reports contain updated emission metric
values, evaluations of different metrics with regard to mitigation objectives, and assess new approaches to aggregating gases. The choice
of metric depends on the purpose of the analysis and all GHG emission metrics have limitations and uncertainties, given that they
simplify the complexity of the physical climate system and its response to past and future GHG emissions. {2.1.1}
10 GHG emission levels are rounded to two significant digits; as a consequence, small differences in sums due to rounding may occur.
{2.1.1}
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A.1.5 Historical contributions of CO2 emissions vary substantially across regions in terms of total magnitude,
but also in terms of contributions to CO2-FFI and net CO2 emissions from land use, land-use change and forestry
(CO2-LULUCF). In 2019, around 35% of the global population live in countries emitting more than 9 tCO2-eq
per capita11 (excluding CO2-LULUCF) while 41% live in countries emitting less than 3 tCO2-eq per capita; of
the latter a substantial share lacks access to modern energy services. Least developed countries (LDCs) and
Small Island Developing States (SIDS) have much lower per capita emissions (1.7 tCO2-eq and 4.6 tCO2-eq,
respectively) than the global average (6.9 tCO2-eq), excluding CO2-LULUCF. The 10% of households with the
highest per capita emissions contribute 34–45% of global consumption-based household GHG emissions, while
the bottom 50% contribute 13–15%. (high confidence) {2.1.1, Figure 2.2}
Observed Changes and Impacts
A.2 Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have
occurred. Human-caused climate change is already affecting many weather and climate extremes in
every region across the globe. This has led to widespread adverse impacts and related losses and
damages to nature and people (high confidence). Vulnerable communities who have historically
contributed the least to current climate change are disproportionately affected (high confidence). {2.1,
Table 2.1, Figure 2.2 and 2.3} (Figure SPM.1)
A.2.1 It is unequivocal that human influence has warmed the atmosphere, ocean and land. Global mean sea
level increased by 0.20 [0.15–0.25] m between 1901 and 2018. The average rate of sea level rise was 1.3 [0.6
to 2.1]mm yr-1 between 1901 and 1971, increasing to 1.9 [0.8 to 2.9] mm yr-1 between 1971 and 2006, and
further increasing to 3.7 [3.2 to 4.2] mm yr-1 between 2006 and 2018 (high confidence). Human influence was
very likely the main driver of these increases since at least 1971. Evidence of observed changes in extremes such
as heatwaves, heavy precipitation, droughts, and tropical cyclones, and, in particular, their attribution to human
influence, has further strengthened since AR5. Human influence has likely increased the chance of compound
extreme events since the 1950s, including increases in the frequency of concurrent heatwaves and droughts
(high confidence). {2.1.2, Table 2.1, Figure 2.3, Figure 3.4} (Figure SPM.1)
A.2.2 Approximately 3.3–3.6 billion people live in contexts that are highly vulnerable to climate change. Human
and ecosystem vulnerability are interdependent. Regions and people with considerable development constraints
have high vulnerability to climatic hazards. Increasing weather and climate extreme events have exposed
millions of people to acute food insecurity12 and reduced water security, with the largest adverse impacts
observed in many locations and/or communities in Africa, Asia, Central and South America, LDCs, Small
Islands and the Arctic, and globally for Indigenous Peoples, small-scale food producers and low-income
households. Between 2010 and 2020, human mortality from floods, droughts and storms was 15 times higher
in highly vulnerable regions, compared to regions with very low vulnerability. (high confidence) {2.1.2, 4.4}
(Figure SPM.1)
A.2.3 Climate change has caused substantial damages, and increasingly irreversible losses, in terrestrial,
freshwater, cryospheric, and coastal and open ocean ecosystems (high confidence). Hundreds of local losses of
species have been driven by increases in the magnitude of heat extremes (high confidence) with mass mortality
events recorded on land and in the ocean (very high confidence). Impacts on some ecosystems are approaching
irreversibility such as the impacts of hydrological changes resulting from the retreat of glaciers, or the changes
in some mountain (medium confidence) and Arctic ecosystems driven by permafrost thaw (high confidence).
{2.1.2, Figure 2.3} (Figure SPM.1)
A.2.4 Climate change has reduced food security and affected water security, hindering efforts to meet
Sustainable Development Goals (high confidence). Although overall agricultural productivity has increased,
climate change has slowed this growth over the past 50 years globally (medium confidence), with related
negative impacts mainly in mid- and low latitude regions but positive impacts in some high latitude regions
(high confidence). Ocean warming and ocean acidification have adversely affected food production from
11 Territorial emissions.
12 Acute food insecurity can occur at any time with a severity that threatens lives, livelihoods or both, regardless of the causes, context
or duration, as a result of shocks risking determinants of food security and nutrition, and is used to assess the need for humanitarian
action {2.1}.
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fisheries and shellfish aquaculture in some oceanic regions (high confidence). Roughly half of the world’s
population currently experience severe water scarcity for at least part of the year due to a combination of climatic
and non-climatic drivers (medium confidence). {2.1.2, Figure 2.3} (Figure SPM.1)
A.2.5 In all regions increases in extreme heat events have resulted in human mortality and morbidity (very high
confidence). The occurrence of climate-related food-borne and water-borne diseases (very high confidence) and
the incidence of vector-borne diseases (high confidence) have increased. In assessed regions, some mental health
challenges are associated with increasing temperatures (high confidence), trauma from extreme events (very
high confidence), and loss of livelihoods and culture (high confidence). Climate and weather extremes are
increasingly driving displacement in Africa, Asia, North America (high confidence), and Central and South
America (medium confidence), with small island states in the Caribbean and South Pacific being
disproportionately affected relative to their small population size (high confidence). {2.1.2, Figure 2.3} (Figure
SPM.1)
A.2.6 Climate change has caused widespread adverse impacts and related losses and damages13 to nature and
people that are unequally distributed across systems, regions and sectors. Economic damages from climate
change have been detected in climate-exposed sectors, such as agriculture, forestry, fishery, energy, and tourism.
Individual livelihoods have been affected through, for example, destruction of homes and infrastructure, and
loss of property and income, human health and food security, with adverse effects on gender and social equity.
(high confidence) {2.1.2} (Figure SPM.1)
A.2.7 In urban areas, observed climate change has caused adverse impacts on human health, livelihoods and
key infrastructure. Hot extremes have intensified in cities. Urban infrastructure, including transportation, water,
sanitation and energy systems have been compromised by extreme and slow-onset events14, with resulting
economic losses, disruptions of services and negative impacts to well-being. Observed adverse impacts are
concentrated amongst economically and socially marginalised urban residents. (high confidence) {2.1.2}
[START FIGURE SPM.1 HERE]
13 In this report, the term ‘losses and damages’ refer to adverse observed impacts and/or projected risks and can be economic and/or noneconomic.
(See Annex I: Glossary)
14 Slow-onset events are described among the climatic-impact drivers of the WGI AR6 and refer to the risks and impacts associated with
e.g., increasing temperature means, desertification, decreasing precipitation, loss of biodiversity, land and forest degradation, glacial
retreat and related impacts, ocean acidification, sea level rise and salinization. {2.1.2}
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Figure SPM.1: (a) Climate change has already caused widespread impacts and related losses and damages on
human systems and altered terrestrial, freshwater and ocean ecosystems worldwide. Physical water availability
includes balance of water available from various sources including ground water, water quality and demand for
water. Global mental health and displacement assessments reflect only assessed regions. Confidence levels
reflect the assessment of attribution of the observed impact to climate change. (b) Observed impacts are
connected to physical climate changes including many that have been attributed to human influence such as the
selected climatic impact-drivers shown. Confidence and likelihood levels reflect the assessment of attribution
Adverse impacts from human-caused
climate change will continue to intensify
a) Observed widespread and substantial impacts and
related losses and damages attributed to climate change
Water availability and food production Health and well-being
00 0oO@ €
Cities, settlements and infrastructure Biodiversity and ecosystems
Physical
water
availability
Agriculture/
crop
production
Animal and
livestock
health and
productivity
Fisheries
yields and
aquaculture
production
Infectious
diseases
Heat,
malnutrition
and harm
from wildfire
Mental
health
Displacement
Key
Observed increase in climate impacts
to human systems and ecosystems
assessed at global level
@±ere impacts
@Adverse and positive impacts
•
Climate-driven changes observed,
no global assessment of impact direction
Kia Foodistom
flooding and induced
associated damages in
damages coastal areas
Damages
to infrastructure
Damages
to key
economic
sectors
Terrestrial Freshwater Ocean
ecosystems ecosystems ecosystems
Includes changes in ecosystem structure,
species ranges and seasonal timing
Confidence in attribution
to climate change
••• High or very high confidence
• Medi u m confidence
• Low confidence
b) Impacts are driven by changes in multiple physical climate
conditions, which are increasingly attributed to human influence
Attribution of observed physical climate changes to human influence:
Medium confidence Likely Very likely Virtually certain
+I3E3% r;i • G p z c-al G - Increase in Increase Increase in Increase Glacier Global sea Upper Increase
agricultural in fire compound in heavy retreat level rise ocean in hot « olgg! weather flooding precipacidification
extremes
drought taton
c) The extent to which current and future generations will experience a
hotter and different world depends on choices now and in the near-term
C Global temperature change above 1850-1900 levels
2020 future experiences depend on
Future emissions 4' how we a~ddress climate change
scenarios: 2(lo0 2100Dw"'"''"9
continues
beond intermediate 2100
high
very high
2011-2020 was
oround 1.1"C wormer)_ than 1850-1900
1980
25 3.5 4
born
in 1950
1940
0 0.5 I 5
1900
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of the observed climatic impact-driver to human influence. (c) Observed (1900–2020) and projected (2021–
2100) changes in global surface temperature (relative to 1850–1900), which are linked to changes in climate
conditions and impacts, illustrate how the climate has already changed and will change along the lifespan of
three representative generations (born in 1950, 1980 and 2020). Future projections (2021–2100) of changes in
global surface temperature are shown for very low (SSP1-1.9), low (SSP1-2.6), intermediate (SSP2-4.5), high
(SSP3-7.0) and very high (SSP5-8.5) GHG emissions scenarios. Changes in annual global surface temperatures
are presented as ‘climate stripes’, with future projections showing the human-caused long-term trends and
continuing modulation by natural variability (represented here using observed levels of past natural variability).
Colours on the generational icons correspond to the global surface temperature stripes for each year, with
segments on future icons differentiating possible future experiences. {2.1, 2.1.2, Figure 2.1, Table 2.1, Figure
2.3, Cross-Section Box.2, 3.1, Figure 3.3, 4.1, 4.3} (Box SPM.1)
[END FIGURE SPM.1 HERE]
Current Progress in Adaptation and Gaps and Challenges
A.3 Adaptation planning and implementation has progressed across all sectors and regions, with
documented benefits and varying effectiveness. Despite progress, adaptation gaps exist, and will
continue to grow at current rates of implementation. Hard and soft limits to adaptation have been
reached in some ecosystems and regions. Maladaptation is happening in some sectors and regions.
Current global financial flows for adaptation are insufficient for, and constrain implementation of,
adaptation options, especially in developing countries (high confidence). {2.2, 2.3}
A.3.1 Progress in adaptation planning and implementation has been observed across all sectors and regions,
generating multiple benefits (very high confidence). Growing public and political awareness of climate impacts
and risks has resulted in at least 170 countries and many cities including adaptation in their climate policies and
planning processes (high confidence). {2.2.3}
A.3.2 Effectiveness15 of adaptation in reducing climate risks16 is documented for specific contexts, sectors and
regions (high confidence). Examples of effective adaptation options include: cultivar improvements, on-farm
water management and storage, soil moisture conservation, irrigation, agroforestry, community-based
adaptation, farm and landscape level diversification in agriculture, sustainable land management approaches,
use of agroecological principles and practices and other approaches that work with natural processes (high
confidence). Ecosystem-based adaptation17 approaches such as urban greening, restoration of wetlands and
upstream forest ecosystems have been effective in reducing flood risks and urban heat (high confidence).
Combinations of non-structural measures like early warning systems and structural measures like levees have
reduced loss of lives in case of inland flooding (medium confidence). Adaptation options such as disaster risk
management, early warning systems, climate services and social safety nets have broad applicability across
multiple sectors (high confidence). {2.2.3}
A.3.3 Most observed adaptation responses are fragmented, incremental18, sector-specific and unequally
distributed across regions. Despite progress, adaptation gaps exist across sectors and regions, and will continue
to grow under current levels of implementation, with the largest adaptation gaps among lower income groups.
(high confidence) {2.3.2}
A.3.4 There is increased evidence of maladaptation in various sectors and regions (high confidence).
Maladaptation especially affects marginalised and vulnerable groups adversely (high confidence). {2.3.2}
A.3.5 Soft limits to adaptation are currently being experienced by small-scale farmers and households along
some low-lying coastal areas (medium confidence) resulting from financial, governance, institutional and policy
constraints (high confidence). Some tropical, coastal, polar and mountain ecosystems have reached hard
15 Effectiveness refers here to the extent to which an adaptation option is anticipated or observed to reduce climate-related risk. {2.2.3}
16 See Annex I: Glossary {2.2.3}
17 Ecosystem based Adaptation (EbA) is recognized internationally under the Convention on Biological Diversity (CBD14/5). A related
concept is Nature-based Solutions (NbS), see Annex I: Glossary.
18 Incremental adaptations to change in climate are understood as extensions of actions and behaviours that already reduce the losses or
enhance the benefits of natural variations in extreme weather/climate events. {2.3.2}
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adaptation limits (high confidence). Adaptation does not prevent all losses and damages, even with effective
adaptation and before reaching soft and hard limits (high confidence). {2.3.2}
A.3.6 Key barriers to adaptation are limited resources, lack of private sector and citizen engagement, insufficient
mobilization of finance (including for research), low climate literacy, lack of political commitment, limited
research and/or slow and low uptake of adaptation science, and low sense of urgency. There are widening
disparities between the estimated costs of adaptation and the finance allocated to adaptation (high confidence).
Adaptation finance has come predominantly from public sources, and a small proportion of global tracked
climate finance was targeted to adaptation and an overwhelming majority to mitigation (very high confidence).
Although global tracked climate finance has shown an upward trend since AR5, current global financial flows
for adaptation, including from public and private finance sources, are insufficient and constrain implementation
of adaptation options, especially in developing countries (high confidence). Adverse climate impacts can reduce
the availability of financial resources by incurring losses and damages and through impeding national economic
growth, thereby further increasing financial constraints for adaptation, particularly for developing and least
developed countries (medium confidence). {2.3.2; 2.3.3}
[START BOX SPM.1 HERE]
Box SPM.1 The use of scenarios and modelled pathways in the AR6 Synthesis Report
Modelled scenarios and pathways19 are used to explore future emissions, climate change, related impacts and
risks, and possible mitigation and adaptation strategies and are based on a range of assumptions, including socioeconomic
variables and mitigation options. These are quantitative projections and are neither predictions nor
forecasts. Global modelled emission pathways, including those based on cost effective approaches contain
regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of
these assumptions. Most do not make explicit assumptions about global equity, environmental justice or intraregional
income distribution. IPCC is neutral with regard to the assumptions underlying the scenarios in the
literature assessed in this report, which do not cover all possible futures.20 {Cross-Section Box.2}
WGI assessed the climate response to five illustrative scenarios based on Shared Socio-economic Pathways
(SSPs)21 that cover the range of possible future development of anthropogenic drivers of climate change found
in the literature. High and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.522) have CO2 emissions
that roughly double from current levels by 2100 and 2050, respectively. The intermediate GHG emissions
scenario (SSP2-4.5) has CO2 emissions remaining around current levels until the middle of the century. The
very low and low GHG emissions scenarios (SSP1-1.9 and SSP1-2.6) have CO2 emissions declining to net zero
around 2050 and 2070, respectively, followed by varying levels of net negative CO2 emissions. In addition,
Representative Concentration Pathways (RCPs)23 were used by WGI and WGII to assess regional climate
changes, impacts and risks. In WGIII, a large number of global modelled emissions pathways were assessed, of
which 1202 pathways were categorised based on their assessed global warming over the 21st century; categories
range from pathways that limit warming to 1.5°C with more than 50% likelihood (noted >50% in this report)
with no or limited overshoot (C1) to pathways that exceed 4°C (C8). (Box SPM.1, Table 1). {Cross-Section
Box.2}
19 In the literature, the terms pathways and scenarios are used interchangeably, with the former more frequently used in relation to climate
goals. WGI primarily used the term scenarios and WGIII mostly used the term modelled emission and mitigation pathways. The SYR
primarily uses scenarios when referring to WGI and modelled emission and mitigation pathways when referring to WGIII.
20 Around half of all modelled global emission pathways assume cost-effective approaches that rely on least-cost mitigation/abatement
options globally. The other half looks at existing policies and regionally and sectorally differentiated actions.
21 SSP-based scenarios are referred to as SSPx-y, where ‘SSPx’ refers to the Shared Socioeconomic Pathway describing the
socioeconomic trends underlying the scenarios, and ‘y’ refers to the level of radiative forcing (in watts per square metre, or Wm-2)
resulting from the scenario in the year 2100. {Cross-Section Box.2}
22 Very high emissions scenarios have become less likely but cannot be ruled out. Warming levels >4°C may result from very high
emissions scenarios, but can also occur from lower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than
the best estimate. {3.1.1}
23 RCP-based scenarios are referred to as RCPy, where ‘y’ refers to the level of radiative forcing (in watts per square metre, or Wm-2)
resulting from the scenario in the year 2100. The SSP scenarios cover a broader range of greenhouse gas and air pollutant futures than
the RCPs. They are similar but not identical, with differences in concentration trajectories. The overall effective radiative forcing tends
to be higher for the SSPs compared to the RCPs with the same label (medium confidence). {Cross-Section Box.2}
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Global warming levels (GWLs) relative to 1850–1900 are used to integrate the assessment of climate change
and related impacts and risks since patterns of changes for many variables at a given GWL are common to all
scenarios considered and independent of timing when that level is reached. {Cross-Section Box.2}
[START BOX SPM.1, TABLE 1 HERE]
Box SPM.1, Table 1: Description and relationship of scenarios and modelled pathways considered across AR6
Working Group reports. {Cross-Section Box.2, Figure 1}
* See footnote 27 for the SSPx-y terminology.
** See footnote 28 for the RCPy terminology.
*** Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C, high overshoot by 0.1°C-0.3°C, in both cases
for up to several decades.
[END BOX SPM.1, TABLE 1 HERE]
[END BOX SPM.1 HERE]
Current Mitigation Progress, Gaps and Challenges
A.4 Policies and laws addressing mitigation have consistently expanded since AR5. Global GHG
emissions in 2030 implied by nationally determined contributions (NDCs) announced by October 2021
make it likely that warming will exceed 1.5°C during the 21st century and make it harder to limit
warming below 2°C. There are gaps between projected emissions from implemented policies and those
from NDCs and finance flows fall short of the levels needed to meet climate goals across all sectors and
regions. (high confidence) {2.2, 2.3, Figure 2.5, Table 2.2}
A.4.1 The UNFCCC, Kyoto Protocol, and the Paris Agreement are supporting rising levels of national ambition.
The Paris Agreement, adopted under the UNFCCC, with near universal participation, has led to policy
development and target-setting at national and sub-national levels, in particular in relation to mitigation, as well
as enhanced transparency of climate action and support (medium confidence). Many regulatory and economic
instruments have already been deployed successfully (high confidence). In many countries, policies have
enhanced energy efficiency, reduced rates of deforestation and accelerated technology deployment, leading to
avoided and in some cases reduced or removed emissions (high confidence). Multiple lines of evidence suggest
that mitigation policies have led to several24 Gt CO2-eq yr-1 of avoided global emissions (medium confidence).
At least 18 countries have sustained absolute production-based GHG and consumption-based CO2 reductions25
for longer than 10 years. These reductions have only partly offset global emissions growth (high confidence).
{2.2.1, 2.2.2}
24At least 1.8 GtCO2-eq yr–1 can be accounted for by aggregating separate estimates for the effects of economic and regulatory
instruments. Growing numbers of laws and executive orders have impacted global emissions and were estimated to result in 5.9 GtCO2-
eq yr–1 less emissions in 2016 than they otherwise would have been. (medium confidence) {2.2.2}
25 Reductions were linked to energy supply decarbonisation, energy efficiency gains, and energy demand reduction, which resulted from
both policies and changes in economic structure (high confidence). {2.2.2}
Category Category description G HG emissions scenarios inWGIII (SSPx-y) in WGI & WGI RCPy in WGI & WGII
C1 wlimitiht wnoa romr ilnimg ittoed 1 .o5v°eCr s(h>o5o0t% ) Very low (SSP1-1.9}
C2 return warming to 1.5°C (>50%)
after a high overshoot
C3 limit wanning to 2°C (>67%)
C4 limit warming to 2°C (>50%)
C5 limit warming to 2.5°C (>50%)
C6 limit warming to 3°C (>50%) Intermediate (SSP2-4.5} RCP 4.5
C7 limit warming to 4°C (>50%) High (55P3-7.0)
C8 II exceed warming of 4°C (>50%) I Very high (5SP5-8.5) I RCP 8.5
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A.4.2 Several mitigation options, notably solar energy, wind energy, electrification of urban systems, urban
green infrastructure, energy efficiency, demand-side management, improved forest- and crop/grassland
management, and reduced food waste and loss, are technically viable, are becoming increasingly cost effective
and are generally supported by the public. From 2010– 2019 there have been sustained decreases in the unit
costs of solar energy (85%), wind energy (55%), and lithium ion batteries (85%), and large increases in their
deployment, e.g., >10x for solar and >100x for electric vehicles (EVs), varying widely across regions. The mix
of policy instruments that reduced costs and stimulated adoption includes public R&D, funding for
demonstration and pilot projects, and demand pull instruments such as deployment subsidies to attain scale.
Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than transitioning
to low emission systems. (high confidence) {2.2.2, Figure 2.4}
A.4.3 A substantial ‘emissions gap’ exists between global GHG emissions in 2030 associated with the
implementation of NDCs announced prior to COP2626 and those associated with modelled mitigation pathways
that limit warming to 1.5°C (>50%) with no or limited overshoot or limit warming to 2°C (>67%) assuming
immediate action (high confidence). This would make it likely that warming will exceed 1.5°C during the 21st
century (high confidence). Global modelled mitigation pathways that limit warming to 1.5°C (>50%) with no
or limited overshoot or limit warming to 2°C (>67%) assuming immediate action imply deep global GHG
emissions reductions this decade (high confidence) (see SPM Box 1, Table 1, B.6)27. Modelled pathways that
are consistent with NDCs announced prior to COP26 until 2030 and assume no increase in ambition thereafter
have higher emissions, leading to a median global warming of 2.8 [2.1–3.4]°C by 2100 (medium confidence).
Many countries have signalled an intention to achieve net-zero GHG or net-zero CO2 by around mid-century
but pledges differ across countries in terms of scope and specificity, and limited policies are to date in place to
deliver on them. {2.3.1, Table 2.2, Figure 2.5; Table 3.1; 4.1}
A.4.4 Policy coverage is uneven across sectors (high confidence). Policies implemented by the end of 2020 are
projected to result in higher global GHG emissions in 2030 than emissions implied by NDCs, indicating an
‘implementation gap’ (high confidence). Without a strengthening of policies, global warming of 3.2 [2.2–3.5]°C
is projected by 2100 (medium confidence). {2.2.2, 2.3.1, 3.1.1, Figure 2.5} (Box SPM.1, Figure SPM.5)
A.4.5 The adoption of low-emission technologies lags in most developing countries, particularly least developed
ones, due in part to limited finance, technology development and transfer, and capacity (medium confidence).
The magnitude of climate finance flows has increased over the last decade and financing channels have
broadened but growth has slowed since 2018 (high confidence). Financial flows have developed
heterogeneously across regions and sectors (high confidence). Public and private finance flows for fossil fuels
are still greater than those for climate adaptation and mitigation (high confidence). The overwhelming majority
of tracked climate finance is directed towards mitigation, but nevertheless falls short of the levels needed to
limit warming to below 2°C or to 1.5°C across all sectors and regions (see C7.2) (very high confidence). In
2018, public and publicly mobilised private climate finance flows from developed to developing countries were
below the collective goal under the UNFCCC and Paris Agreement to mobilise USD100 billion per year by
2020 in the context of meaningful mitigation action and transparency on implementation (medium confidence).
{2.2.2, 2.3.1, 2.3.3}
26 Due to the literature cutoff date of WGIII, the additional NDCs submitted after 11 October 2021 are not assessed here. {Footnote 32
in Longer Report}
27 Projected 2030 GHG emissions are 50 (47–55) GtCO2-eq if all conditional NDC elements are taken into account. Without conditional
elements, the global emissions are projected to be approximately similar to modelled 2019 levels at 53 (50–57) GtCO2-eq. {2.3.1, Table
2.2}
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B. Future Climate Change, Risks, and Long-Term Responses
Future Climate Change
B.1 Continued greenhouse gas emissions will lead to increasing global warming, with the best estimate
of reaching 1.5°C in the near term in considered scenarios and modelled pathways. Every increment of
global warming will intensify multiple and concurrent hazards (high confidence). Deep, rapid, and
sustained reductions in greenhouse gas emissions would lead to a discernible slowdown in global
warming within around two decades, and also to discernible changes in atmospheric composition within
a few years (high confidence). {Cross-Section Boxes 1 and 2, 3.1, 3.3, Table 3.1, Figure 3.1, 4.3} (Figure
SPM.2, Box SPM.1)
B.1.1 Global warming28 will continue to increase in the near term (2021-2040) mainly due to increased
cumulative CO2 emissions in nearly all considered scenarios and modelled pathways. In the near term, global
warming is more likely than not to reach 1.5°C even under the very low GHG emission scenario (SSP1-1.9) and
likely or very likely to exceed 1.5°C under higher emissions scenarios. In the considered scenarios and modelled
pathways, the best estimates of the time when the level of global warming of 1.5°C is reached lie in the near
term29. Global warming declines back to below 1.5°C by the end of the 21st century in some scenarios and
modelled pathways (see B.7). The assessed climate response to GHG emissions scenarios results in a best
estimate of warming for 2081–2100 that spans a range from 1.4°C for a very low GHG emissions scenario
(SSP1-1.9) to 2.7°C for an intermediate GHG emissions scenario (SSP2-4.5) and 4.4°C for a very high GHG
emissions scenario (SSP5-8.5)30, with narrower uncertainty ranges31 than for corresponding scenarios in AR5.
{Cross-Section Boxes 1 and 2, 3.1.1, 3.3.4, Table 3.1, 4.3} (Box SPM.1)
B.1.2 Discernible differences in trends of global surface temperature between contrasting GHG emissions
scenarios (SSP1-1.9 and SSP1-2.6 vs. SSP3-7.0 and SSP5-8.5) would begin to emerge from natural variability32
within around 20 years. Under these contrasting scenarios, discernible effects would emerge within years for
GHG concentrations, and sooner for air quality improvements, due to the combined targeted air pollution
controls and strong and sustained methane emissions reductions. Targeted reductions of air pollutant emissions
lead to more rapid improvements in air quality within years compared to reductions in GHG emissions only,
but in the long term, further improvements are projected in scenarios that combine efforts to reduce air pollutants
as well as GHG emissions33. (high confidence) {3.1.1} (Box SPM.1)
B.1.3 Continued emissions will further affect all major climate system components. With every additional
increment of global warming, changes in extremes continue to become larger. Continued global warming is
projected to further intensify the global water cycle, including its variability, global monsoon precipitation, and
very wet and very dry weather and climate events and seasons (high confidence). In scenarios with increasing
CO2 emissions, natural land and ocean carbon sinks are projected to take up a decreasing proportion of these
emissions (high confidence). Other projected changes include further reduced extents and/or volumes of almost
28 Global warming (see Annex I: Glossary) is here reported as running 20-year averages, unless stated otherwise, relative to 1850–1900.
Global surface temperature in any single year can vary above or below the long-term human-caused trend, due to natural variability. The
internal variability of global surface temperature in a single year is estimated to be about ±0.25°C (5–95% range, high confidence). The
occurrence of individual years with global surface temperature change above a certain level does not imply that this global warming
level has been reached. {4.3, Cross-Section Box.2}
29 Median five-year interval at which a 1.5°C global warming level is reached (50% probability) in categories of modelled pathways
considered in WGIII is 2030-2035. By 2030, global surface temperature in any individual year could exceed 1.5°C relative to 1850-1900
with a probability between 40% and 60%, across the five scenarios assessed in WGI (medium confidence). In all scenarios considered
in WGI except the very high emissions scenario (SSP5-8.5), the midpoint of the first 20-year running average period during which the
assessed average global surface temperature change reaches 1.5°C lies in the first half of the 2030s. In the very high GHG emissions
scenario, the midpoint is in the late 2020s. {3.1.1, 3.3.1, 4.3} (Box SPM.1)
30 The best estimates [and very likely ranges] for the different scenarios are: 1.4°C [1.0°C–1.8°C] (SSP1-1.9); 1.8°C [1.3°C–2.4°C]
(SSP1-2.6); 2.7°C [2.1°C–3.5°C] (SSP2-4.5)); 3.6°C [2.8°C–4.6°C] (SSP3-7.0); and 4.4°C [3.3°C–5.7°C] (SSP5-8.5). {3.1.1} (Box
SPM.1)
31 Assessed future changes in global surface temperature have been constructed, for the first time, by combining multi-model projections
with observational constraints and the assessed equilibrium climate sensitivity and transient climate response. The uncertainty range is
narrower than in the AR5 thanks to improved knowledge of climate processes, paleoclimate evidence and model-based emergent
constraints. {3.1.1}
32 See Annex I: Glossary. Natural variability includes natural drivers and internal variability. The main internal variability phenomena
include El Niño-Southern Oscillation, Pacific Decadal Variability and Atlantic Multi-decadal Variability. {4.3}
33 Based on additional scenarios.
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all cryospheric elements34 (high confidence), further global mean sea level rise (virtually certain), and increased
ocean acidification (virtually certain) and deoxygenation (high confidence). {3.1.1, 3.3.1, Figure 3.4} (Figure
SPM.2)
B.1.4 With further warming, every region is projected to increasingly experience concurrent and multiple
changes in climatic impact-drivers. Compound heatwaves and droughts are projected to become more frequent,
including concurrent events across multiple locations (high confidence). Due to relative sea level rise, current
1-in-100 year extreme sea level events are projected to occur at least annually in more than half of all tide gauge
locations by 2100 under all considered scenarios (high confidence). Other projected regional changes include
intensification of tropical cyclones and/or extratropical storms (medium confidence), and increases in aridity
and fire weather (medium to high confidence) {3.1.1, 3.1.3}
B.1.5 Natural variability will continue to modulate human-caused climate changes, either attenuating or
amplifying projected changes, with little effect on centennial-scale global warming (high confidence). These
modulations are important to consider in adaptation planning, especially at the regional scale and in the near
term. If a large explosive volcanic eruption were to occur35, it would temporarily and partially mask humancaused
climate change by reducing global surface temperature and precipitation for one to three years (medium
confidence). {4.3}
[START FIGURE SPM.2 HERE]
34 Permafrost, seasonal snow cover, glaciers, the Greenland and Antarctic Ice Sheets, and Arctic Sea ice.
35 Based on 2500-year reconstructions, eruptions with a radiative forcing more negative than -1 Wm-2, related to the radiative effect of
volcanic stratospheric aerosols in the literature assessed in this report, occur on average twice per century. {4.3}
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Figure SPM.2: Projected changes of annual maximum daily maximum temperature, annual mean total column soil
moisture and annual maximum 1-day precipitation at global warming levels of 1.5°C, 2°C, 3°C, and 4°C relative to
1850–1900. Projected (a) annual maximum daily temperature change (°C), (b) annual mean total column soil moisture
(standard deviation), (c) annual maximum 1-day precipitation change (%). The panels show CMIP6 multi-model median
changes. In panels (b) and (c), large positive relative changes in dry regions may correspond to small absolute changes. In
panel (b), the unit is the standard deviation of interannual variability in soil moisture during 1850–1900. Standard deviation
is a widely used metric in characterising drought severity. A projected reduction in mean soil moisture by one standard
deviation corresponds to soil moisture conditions typical of droughts that occurred about once every six years during 1850–
1900. The WGI Interactive Atlas (https://interactive-atlas.ipcc.ch/ ) can be used to explore additional changes in the climate
system across the range of global warming levels presented in this figure. {Figure 3.1, Cross-Section Box.2}
[END FIGURE SPM.2 HERE]
With every increment of global warming, regional changes in mean
climate and extremes become more widespread and pronounced
c
The world at 1
the last time global surface temperature was sustained
at or above 2.5C was over 3 million ears a90
The world at The world at
+1.5C +2C
Global warming level (GWL) above 1850-1900
2011-2020 was
around 1,1€ warmer
than 1850-1900 11 0
urbanisation
further intensifies
heat extremes
Annual hottest day temperature is projected to increase most
(1.5-2 times the GWI) in some mid-latitude and semi-arid
regions, and in the South American Monsoon region.
I a)
Annual hottest-day temperature change
<J> arose eo 0 1 2 3 4 5 6 7
I $5 1s I small
absolute
changes may
appear large as
%or o changes
in dry regio
Annual wettest day precipitation is projected to increase
in almost all continental regions, even in regions where
projected annual mean change (%) soil moisture decline.
-40 -30 -20 -10 0 10 20 30 40
I rs rt» .
7 TY
c) Annual wettest-day precipitation change
b) Annual mean total column soil moisture change Projections of annual mean soil moisture largely follow
I> chahn ge( o( ) ) projecdtiioftne s in anndu al meatnhe 'pfrec ipitationt but also show. 1.5 T@05 05 To i5 some titterences lue to the influence ot evapotranspiration.
I la r7sif 2isF# rz± ;erst I
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Climate Change Impacts and Climate-Related Risks
B.2 For any given future warming level, many climate-related risks are higher than assessed in AR5,
and projected long-term impacts are up to multiple times higher than currently observed (high
confidence). Risks and projected adverse impacts and related losses and damages from climate change
escalate with every increment of global warming (very high confidence). Climatic and non-climatic risks
will increasingly interact, creating compound and cascading risks that are more complex and difficult
to manage (high confidence). {Cross-Section Box.2, 3.1, 4.3, Figure 3.3, Figure 4.3} (Figure SPM.3,
Figure SPM.4)
B.2.1 In the near term, every region in the world is projected to face further increases in climate hazards (medium
to high confidence, depending on region and hazard), increasing multiple risks to ecosystems and humans (very
high confidence). Hazards and associated risks expected in the near-term include an increase in heat-related
human mortality and morbidity (high confidence), food-borne, water-borne, and vector-borne diseases (high
confidence), and mental health challenges36 (very high confidence), flooding in coastal and other low-lying cities
and regions (high confidence), biodiversity loss in land, freshwater and ocean ecosystems (medium to very high
confidence, depending on ecosystem), and a decrease in food production in some regions (high confidence).
Cryosphere-related changes in floods, landslides, and water availability have the potential to lead to severe
consequences for people, infrastructure and the economy in most mountain regions (high confidence). The
projected increase in frequency and intensity of heavy precipitation (high confidence) will increase raingenerated
local flooding (medium confidence). {Figure 3.2, Figure 3.3, 4.3, Figure 4.3} (Figure SPM.3, Figure
SPM.4)
B.2.2 Risks and projected adverse impacts and related losses and damages from climate change will escalate
with every increment of global warming (very high confidence). They are higher for global warming of 1.5°C
than at present, and even higher at 2°C (high confidence). Compared to the AR5, global aggregated risk levels37
(Reasons for Concern38) are assessed to become high to very high at lower levels of global warming due to
recent evidence of observed impacts, improved process understanding, and new knowledge on exposure and
vulnerability of human and natural systems, including limits to adaptation(high confidence). Due to unavoidable
sea level rise (see also B.3), risks for coastal ecosystems, people and infrastructure will continue to increase
beyond 2100 (high confidence). {3.1.2, 3.1.3, Figure 3.4, Figure 4.3} (Figures SPM.3, Figure SPM.4)
B.2.3 With further warming, climate change risks will become increasingly complex and more difficult to
manage. Multiple climatic and non-climatic risk drivers will interact, resulting in compounding overall risk and
risks cascading across sectors and regions. Climate-driven food insecurity and supply instability, for example,
are projected to increase with increasing global warming, interacting with non-climatic risk drivers such as
competition for land between urban expansion and food production, pandemics and conflict. (high confidence)
{3.1.2, 4.3, Figure 4.3}
B.2.4 For any given warming level, the level of risk will also depend on trends in vulnerability and exposure of
humans and ecosystems. Future exposure to climatic hazards is increasing globally due to socio-economic
development trends including migration, growing inequality and urbanisation. Human vulnerability will
concentrate in informal settlements and rapidly growing smaller settlements. In rural areas vulnerability will be
heightened by high reliance on climate-sensitive livelihoods. Vulnerability of ecosystems will be strongly
influenced by past, present, and future patterns of unsustainable consumption and production, increasing
36 In all assessed regions.
37 Undetectable risk level indicates no associated impacts are detectable and attributable to climate change; moderate risk indicates
associated impacts are both detectable and attributable to climate change with at least medium confidence, also accounting for the other
specific criteria for key risks; high risk indicates severe and widespread impacts that are judged to be high on one or more criteria for
assessing key risks; and very high risk level indicates very high risk of severe impacts and the presence of significant irreversibility or
the persistence of climate-related hazards, combined with limited ability to adapt due to the nature of the hazard or impacts/risks. {3.1.2}
38 The Reasons for Concern (RFC) framework communicates scientific understanding about accrual of risk for five broad categories.
RFC1: Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climaterelated
conditions and have high endemism or other distinctive properties. RFC2: Extreme weather events: risks/impacts to human
health, livelihoods, assets and ecosystems from extreme weather events. RFC3: Distribution of impacts: risks/impacts that
disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability.
RFC4: Global aggregate impacts: impacts to socio-ecological systems that can be aggregated globally into a single metric. RFC5: Largescale
singular events: relatively large, abrupt and sometimes irreversible changes in systems caused by global warming. See also Annex
I: Glossary. {3.1.2, Cross-Section Box.2}
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demographic pressures, and persistent unsustainable use and management of land, ocean, and water. Loss of
ecosystems and their services has cascading and long-term impacts on people globally, especially for Indigenous
Peoples and local communities who are directly dependent on ecosystems, to meet basic needs. (high
confidence) {Cross-Section Box.2, Figure 1c, 3.1.2, 4.3}
[START FIGURE SPM.3 HERE]
Figure SPM.3: Projected risks and impacts of climate change on natural and human systems at different global warming
levels (GWLs) relative to 1850-1900 levels. Projected risks and impacts shown on the maps are based on outputs from
different subsets of Earth system and impact models that were used to project each impact indicator without additional
adaptation. WGII provides further assessment of the impacts on human and natural systems using these projections and
Future climate change is projected to increase the severity of impacts
across natural and human systems and will increase regional differences
Examples of impacts without additional adaptation
a) Risk of ,(. 0% 0.1
species losses
Percentage of animal
species and seagrasses
exposed to potentially
dangerous temperature
conditions 1• 2
1.5°C
Includes 30,652 species of birds,
mammals, reptiles, amphibians, marine
fish, benthic marine invertebrates, krill,
cephalopods, corals, and seagrasses.
10 20 40 60 80 100%
Projected temperature conditions above
the estimated historical (1850-2005)
maximum mean annual temperature
experienced by each species, assuming
no species relocation.
$6 .fl•
b) Heat-humidity
risks to
human health «ea 0 days 10 50 100
3.0€
150 200 250
4.0°C
300 365 days
Historical 1991-2005
Days per year where
combined temperature and
humidity conditions pose a risk
of mortality to individuals3
1.7 2.3C 2.4 3.1C 4.25.4C
Projected regional impacts utilize a global threshold beyond which daily mean surface air temperature and relative humidity may induce
hyperthermia that poses a risk of mortality. The duration and intensity of heatwaves are not presented here. Heat-related health outcomes
vary by location and are highly moderated by socio-economic, occupational and other non-dimatic determinants of individual health and
socio-economic vulnerability. The threshold used in these maps is based on a single study that synthesized data from 783 cases to
determine the relationship between heat-humidity conditions and mortality drawn largely from observations in temperate climates.
c) Food production
impacts
c1) Maize yield'
Changes (%) in yield
-35% -30 -25 -20 -15 -10 -3 +3 +10 +15 +20 +25 +30 +35%
7 ee7cs
7.4 kt » gvs,. er: $ "',t< 2#° - ·?f : ." ' r R €.
% ' :J:j '
1.6 2.4C 3.3 4.8C 3.96.0C
Projected regional impacts reflect biophysical responses to changing temperature, precipitation, solar radiation, humidity, wind, and CO
enhancement of growth and water retention in currently cultivated areas. Models assume that irrigated areas are not water-limited.
Models do not represent pests, diseases, future agro-technological changes and some extreme dimate responses.
d»
c2) Fisheries yield'
Changes (%) in
maximum catch
potential
Areas with little or no
production, or not assessed
/// // Areas with model disagreement
0.92.0C 3.45.2C
Projected regional impacts reflect fisheries and marine ecosystem responses to ocean physical and bi0geochemical conditions such as
temperature, oxygen level and net primary production. Models do not represent changes in fishing activities and some extreme climatic
conditions. Projected changes in thea Arctic regions have low confidence due to uncertainties associated with modelling multiple interacting
drivers and ecosystem responses.
Approved Summary for Policymakers IPCC AR6 SYR
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additional lines of evidence. (a) Risks of species losses as indicated by the percentage of assessed species exposed to
potentially dangerous temperature conditions, as defined by conditions beyond the estimated historical (1850-2005)
maximum mean annual temperature experienced by each species, at GWLs of 1.5oC, 2oC,3oC and 4oC. Underpinning
projections of temperature are from 21 Earth system models and do not consider extreme events impacting ecosystems
such as the Arctic. (b) Risks to human health as indicated by the days per year of population exposure to hyperthermic
conditions that pose a risk of mortality from surface air temperature and humidity conditions for historical period (1991-
2005) and at GWLs of 1.7°C–2.3°C (mean = 1.9°C; 13 climate models), 2.4°C–3.1°C (2.7°C; 16 climate models) and
4.2°C–5.4°C (4.7°C; 15 climate models). Interquartile ranges of GWLs by 2081–2100 under RCP2.6, RCP4.5 and RCP8.5.
The presented index is consistent with common features found in many indices included within WGI and WGII assessments
(c) Impacts on food production: (c1) Changes in maize yield by 2080–2099 relative to 1986–2005 at projected GWLs of
1.6°C–2.4oC (2.0°C), 3.3°C–4.8oC (4.1°C) and 3.9°C–6.0oC (4.9°C). Median yield changes from an ensemble of 12 crop
models, each driven by bias-adjusted outputs from 5 Earth system models, from the Agricultural Model Intercomparison
and Improvement Project (AgMIP) and the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Maps depict
2080–2099 compared to 1986–2005 for current growing regions (>10 ha), with the corresponding range of future global
warming levels shown under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively. Hatching indicates areas where <70% of the
climate-crop model combinations agree on the sign of impact. (c2) Change in maximum fisheries catch potential by 2081–
2099 relative to 1986–2005 at projected GWLs of 0.9°C–2.0°C (1.5°C) and 3.4°C–5.2°C (4.3°C). GWLs by 2081–2100
under RCP2.6 and RCP8.5. Hatching indicates where the two climate-fisheries models disagree in the direction of change.
Large relative changes in low yielding regions may correspond to small absolute changes. Biodiversity and fisheries in
Antarctica were not analysed due to data limitations. Food security is also affected by crop and fishery failures not presented
here.{3.1.2, Figure 3.2, Cross-Section Box.2} (Box SPM.1)
[END FIGURE SPM.3 HERE]
[START FIGURE SPM.4 HERE]
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Figure SPM.4: Subset of assessed climate outcomes and associated global and regional climate risks. The burning
embers result from a literature based expert elicitation. Panel (a): Left – Global surface temperature changes in °C relative
to 1850–1900. These changes were obtained by combining CMIP6 model simulations with observational constraints based
on past simulated warming, as well as an updated assessment of equilibrium climate sensitivity. Very likely ranges are
shown for the low and high GHG emissions scenarios (SSP1-2.6 and SSP3-7.0) (Cross-Section Box 2); Right – Global
Reasons for Concern (RFC), comparing AR6 (thick embers) and AR5 (thin embers) assessments. Risk transitions have
generally shifted towards lower temperatures with updated scientific understanding. Diagrams are shown for each RFC,
assuming low to no adaptation. Lines connect the midpoints of the transitions from moderate to high risk across AR5 and
AR6. Panel (b): Selected global risks for land and ocean ecosystems, illustrating general increase of risk with global
warming levels with low to no adaptation. Panel (c): Left - Global mean sea level change in centimetres, relative to 1900.
Risks are increasing with every increment of warming
a) High risks are now assessed to occur at lower global warming levels risk is the potential for
\ adverse consequences
Risk/impact
veoh+on
o»
Moderate
Undetectable
]Transition range
Confidence level
assigned to
transition range
:
:a
_midpoint of transition
AR5 AR6
Large scale
singular
events
AR5 AR6 ARS AR6
Distribution Global
of impacts aggregate
impacts
AR5 AR6
Extreme
weather
events
Global Reasons for Concern (RFCs)
in AR5 (2014) vs. AR6 (2022)
Unique 8
threatened
systems
4
ic5 very high
high
2000 2015 2050 2100
shading represents the
uncertainty ranqes for
the low and high
emissions scenarios
intermediate
-low
very low 1.5
-------,::,-=---"'""-,-0-11-- , o-20 was _/ 1
around 1,1€ warmer
0 than 1850-1900
4
-1
1950
Global surface temperature change
relative to 1850-1900
ic5
fl Wildfire Permafrost Biodiversity Dryland Tree Carbon
damage degradation loss water mortality loss
scar0ty
Ocean/coastal ecosystems I I·
I· 1, I I·
I=
l:
l 11 lr l ii ! It
!
Warm-water Kelp Seagrass Epipelagic Rody Salt
corals forests meadows shores marshes
I=
e.g. coral
reefs decline
99%
1!· I· e.g. coral
reefs decline
I; ; ; by 70-90%
Land-based systems
b) Risks differ by system
ic5
°g, over 10o million
additional people 4
exposed
l :
e.g. increase in the 1.5 It ! length of fire season ;
I!
Risks are
assessed with
medium confidence
0 No-to-moderate
response
@
Maximum potential
response
Resource-rich
coastal cities
Large tropical
agricultural
deltas
cm
very high 100
high
r ediate 75
low
very low so
25
1986-2005
baseline 0 Urban Arctic 2000 2050 2100 atoll islands communities
, f
low-(kelihood, high impact ,
storyline, including ice-sheet
instability processes P
Global mean sea level rise relative to 1900
cm
100
75
so
25
0
1950
c) Risks to coastal geographies increase with sea level rise and depend on responses
@ @ @ @
d) Adaptation and
socio-economic pathways
affect levels of climate
related risks
Limited adaptation (failure to proactively
adapt; low investment in health systems);
incomplete adaptation (incomplete
adaptation planning; moderate investment
in health systems); proactive adaptation
(proactive adaptation management; higher
investment in health systems)
Heat-related morbidity and mortality
ic4
1.5
o _
Limited Incomplete Proactive
adaptation adaptation adaptation
Food insecurity
(availability, access)
55P3 55P1 •I· ol•
": I=
high » low
Challenges to Adaptation
The SSPl pathway illustrates
a world with low population
growth, high income, and
reduced inequalities, food
produced in low GHG
emission systems, effective
land use regulation and high
adaptive capacity (i.e., low
challenges to adaptation).
The SSP3 pathway has the
opposite trends.
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The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. The future changes to
2100 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP,
ice-sheet, and glacier models, and likely ranges are shown for SSP1-2.6 and SSP3-7.0. Right - Assessment of the combined
risk of coastal flooding, erosion and salinization for four illustrative coastal geographies in 2100, due to changing mean
and extreme sea levels, under two response scenarios, with respect to the SROCC baseline period (1986-2005). The
assessment does not account for changes in extreme sea level beyond those directly induced by mean sea level rise; risk
levels could increase if other changes in extreme sea levels were considered (e.g., due to changes in cyclone intensity).
“No-to-moderate response” describes efforts as of today (i.e. no further significant action or new types of actions).
“Maximum potential response” represent a combination of responses implemented to their full extent and thus significant
additional efforts compared to today, assuming minimal financial, social and political barriers. (In this context, ‘today’
refers to 2019.) The assessment criteria include exposure and vulnerability, coastal hazards, in-situ responses and planned
relocation. Planned relocation refers to managed retreat or resettlements. The term response is used here instead of
adaptation because some responses, such as retreat, may or may not be considered to be adaptation. Panel (d): Selected
risks under different socio-economic pathways, illustrating how development strategies and challenges to adaptation
influence risk. Left - Heat-sensitive human health outcomes under three scenarios of adaptation effectiveness. The
diagrams are truncated at the nearest whole ºC within the range of temperature change in 2100 under three SSP scenarios.
Right - Risks associated with food security due to climate change and patterns of socio-economic development. Risks to
food security include availability and access to food, including population at risk of hunger, food price increases and
increases in disability adjusted life years attributable to childhood underweight. Risks are assessed for two contrasted socioeconomic
pathways (SSP1 and SSP3) excluding the effects of targeted mitigation and adaptation policies. {Figure 3.3}
(Box SPM.1)
[END FIGURE SPM.4 HERE]
Likelihood and Risks of Unavoidable, Irreversible or Abrupt Changes
B.3 Some future changes are unavoidable and/or irreversible but can be limited by deep, rapid and
sustained global greenhouse gas emissions reduction. The likelihood of abrupt and/or irreversible
changes increases with higher global warming levels. Similarly, the probability of low-likelihood
outcomes associated with potentially very large adverse impacts increases with higher global warming
levels. (high confidence) {3.1}
B.3.1 Limiting global surface temperature does not prevent continued changes in climate system components
that have multi-decadal or longer timescales of response (high confidence). Sea level rise is unavoidable for
centuries to millennia due to continuing deep ocean warming and ice sheet melt, and sea levels will remain
elevated for thousands of years (high confidence). However, deep, rapid and sustained GHG emissions
reductions would limit further sea level rise acceleration and projected long-term sea level rise commitment.
Relative to 1995–2014, the likely global mean sea level rise under the SSP1-1.9 GHG emissions scenario is
0.15–0.23 m by 2050 and 0.28–0.55 m by 2100; while for the SSP5-8.5 GHG emissions scenario it is 0.20–0.29
m by 2050 and 0.63–1.01 m by 2100 (medium confidence). Over the next 2000 years, global mean sea level will
rise by about 2–3 m if warming is limited to 1.5°C and 2–6 m if limited to 2°C (low confidence). {3.1.3, Figure
3.4} (Box SPM.1)
B.3.2 The likelihood and impacts of abrupt and/or irreversible changes in the climate system, including changes
triggered when tipping points are reached, increase with further global warming (high confidence). As warming
levels increase, so do the risks of species extinction or irreversible loss of biodiversity in ecosystems including
forests (medium confidence), coral reefs (very high confidence) and in Arctic regions (high confidence). At
sustained warming levels between 2°C and 3°C, the Greenland and West Antarctic ice sheets will be lost almost
completely and irreversibly over multiple millennia, causing several metres of sea level rise (limited evidence).
The probability and rate of ice mass loss increase with higher global surface temperatures (high confidence).
{3.1.2, 3.1.3}
B.3.3 The probability of low-likelihood outcomes associated with potentially very large impacts increases with
higher global warming levels (high confidence). Due to deep uncertainty linked to ice-sheet processes, global
mean sea level rise above the likely range – approaching 2 m by 2100 and in excess of 15 m by 2300 under the
very high GHG emissions scenario (SSP5-8.5) (low confidence) – cannot be excluded. There is medium
confidence that the Atlantic Meridional Overturning Circulation will not collapse abruptly before 2100, but if it
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were to occur, it would very likely cause abrupt shifts in regional weather patterns, and large impacts on
ecosystems and human activities. {3.1.3} (Box SPM.1)
Adaptation Options and their Limits in a Warmer World
B.4 Adaptation options that are feasible and effective today will become constrained and less effective
with increasing global warming. With increasing global warming, losses and damages will increase
and additional human and natural systems will reach adaptation limits. Maladaptation can be
avoided by flexible, multi-sectoral, inclusive, long-term planning and implementation of adaptation
actions, with co-benefits to many sectors and systems. (high confidence) {3.2, 4.1, 4.2, 4.3}
B.4.1 The effectiveness of adaptation, including ecosystem-based and most water-related options, will decrease
with increasing warming. The feasibility and effectiveness of options increase with integrated, multi-sectoral
solutions that differentiate responses based on climate risk, cut across systems and address social inequities. As
adaptation options often have long implementation times, long-term planning increases their efficiency. (high
confidence) {3.2, Figure 3.4, 4.1, 4.2}
B.4.2 With additional global warming, limits to adaptation and losses and damages, strongly concentrated
among vulnerable populations, will become increasingly difficult to avoid (high confidence). Above 1.5°C of
global warming, limited freshwater resources pose potential hard adaptation limits for small islands and for
regions dependent on glacier and snow melt (medium confidence). Above that level, ecosystems such as some
warm-water coral reefs, coastal wetlands, rainforests, and polar and mountain ecosystems will have reached or
surpassed hard adaptation limits and as a consequence, some Ecosystem-based Adaptation measures will also
lose their effectiveness (high confidence). {2.3.2, 3.2, 4.3}
B.4.3 Actions that focus on sectors and risks in isolation and on short-term gains often lead to maladaptation
over the long-term, creating lock-ins of vulnerability, exposure and risks that are difficult to change. For
example, seawalls effectively reduce impacts to people and assets in the short-term but can also result in lockins
and increase exposure to climate risks in the long-term unless they are integrated into a long-term adaptive
plan. Maladaptive responses can worsen existing inequities especially for Indigenous Peoples and marginalised
groups and decrease ecosystem and biodiversity resilience. Maladaptation can be avoided by flexible, multisectoral,
inclusive, long-term planning and implementation of adaptation actions, with co-benefits to many
sectors and systems. (high confidence) {2.3.2, 3.2}
Carbon Budgets and Net Zero Emissions
B.5 Limiting human-caused global warming requires net zero CO2 emissions. Cumulative carbon
emissions until the time of reaching net-zero CO2 emissions and the level of greenhouse gas emission
reductions this decade largely determine whether warming can be limited to 1.5°C or 2°C (high
confidence). Projected CO2 emissions from existing fossil fuel infrastructure without additional
abatement would exceed the remaining carbon budget for 1.5°C (50%) (high confidence). {2.3, 3.1,
3.3, Table 3.1}
B.5.1 From a physical science perspective, limiting human-caused global warming to a specific level requires
limiting cumulative CO2 emissions, reaching at least net zero CO2 emissions, along with strong reductions in
other greenhouse gas emissions. Reaching net zero GHG emissions primarily requires deep reductions in CO2,
methane, and other GHG emissions, and implies net-negative CO2 emissions39. Carbon dioxide removal (CDR)
will be necessary to achieve net-negative CO2 emissions (see B.6). Net zero GHG emissions, if sustained, are
projected to result in a gradual decline in global surface temperatures after an earlier peak. (high confidence)
{3.1.1, 3.3.1, 3.3.2, 3.3.3, Table 3.1, Cross-Section Box 1}
B.5.2 For every 1000 GtCO2 emitted by human activity, global surface temperature rises by 0.45°C (best
estimate, with a likely range from 0.27 to 0.63°C). The best estimates of the remaining carbon budgetsfrom the
39 Net zero GHG emissions defined by the 100-year global warming potential. See footnote 9.
Approved Summary for Policymakers IPCC AR6 SYR
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beginning of 2020 are 500 GtCO2 for a 50% likelihood of limiting global warming to 1.5°C and 1150 GtCO2
for a 67% likelihood of limiting warming to 2°C40. The stronger the reductions in non-CO2 emissions the lower
the resulting temperatures are for a given remaining carbon budget or the larger remaining carbon budget for
the same level of temperature change41. {3.3.1}
B.5.3 If the annual CO2 emissions between 2020–2030 stayed, on average, at the same level as 2019, the
resulting cumulative emissions would almost exhaust the remaining carbon budget for 1.5°C (50%), and deplete
more than a third of the remaining carbon budget for 2°C (67%). Estimates of future CO2 emissions from
existing fossil fuel infrastructures without additional abatement42 already exceed the remaining carbon budget
for limiting warming to 1.5°C (50%) (high confidence). Projected cumulative future CO2 emissions over the
lifetime of existing and planned fossil fuel infrastructure, if historical operating patterns are maintained and
without additional abatement43, are approximately equal to the remaining carbon budget for limiting warming
to 2°C with a likelihood of 83%44 (high confidence). {2.3.1, 3.3.1, Figure 3.5}
B.5.4 Based on central estimates only, historical cumulative net CO2 emissions between 1850 and 2019 amount
to about four-fifths45 of the total carbon budget for a 50% probability of limiting global warming to 1.5°C
(central estimate about 2900 GtCO2), and to about two thirds46 of the total carbon budget for a 67% probability
to limit global warming to 2°C (central estimate about 3550 GtCO2). {3.3.1, Figure 3.5}
Mitigation Pathways
B.6 All global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot,
and those that limit warming to 2°C (>67%), involve rapid and deep and, in most cases, immediate
greenhouse gas emissions reductions in all sectors this decade. Global net zero CO2 emissions are
reached for these pathway categories, in the early 2050s and around the early 2070s, respectively.
(high confidence) {3.3, 3.4, 4.1, 4.5, Table 3.1} (Figure SPM.5, Box SPM.1)
B.6.1 Global modelled pathways provide information on limiting warming to different levels; these pathways,
particularly their sectoral and regional aspects, depend on the assumptions described in Box SPM.1. Global
modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot or limit warming to 2°C
(>67%) are characterized by deep, rapid and, in most cases, immediate GHG emissions reductions. Pathways
that limit warming to 1.5C (>50%) with no or limited overshoot reach net zero CO2 in the early 2050s, followed
by net negative CO2 emissions. Those pathways that reach net zero GHG emissions do so around the 2070s.
Pathways that limit warming to 2C (>67%) reach net zero CO2 emissions in the early 2070s. Global GHG
emissions are projected to peak between 2020 and at the latest before 2025 in global modelled pathways that
limit warming to 1.5°C (>50%) with no or limited overshoot and in those that limit warming to 2°C (>67%) and
assume immediate action. (high confidence) {3.3.2, 3.3.4, 4.1, Table 3.1, Figure 3.6} (Table XX)
[START TABLE XX]
40 Global databases make different choices about which emissions and removals occurring on land are considered anthropogenic. Most
countries report their anthropogenic land CO2 fluxes including fluxes due to human-caused environmental change (e.g., CO2 fertilisation)
on ‘managed’ land in their national GHG inventories. Using emissions estimates based on these inventories, the remaining carbon
budgets must be correspondingly reduced. {3.3.1}
41 For example, remaining carbon budgets could be 300 or 600 GtCO2 for 1.5°C (50%), respectively for high and low non-CO2 emissions,
compared to 500 GtCO2 in the central case. {3.3.1}
42 Abatement here refers to human interventions that reduce the amount of greenhouse gases that are released from fossil fuel
infrastructure to the atmosphere.
43 Ibid.
44 WGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as
50%, 67% or 83%. {3.3.1}
45 Uncertainties for total carbon budgets have not been assessed and could affect the specific calculated fractions.
46 Ibid.
Approved Summary for Policymakers IPCC AR6 SYR
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Table XX: Greenhouse gas and CO2 emission reductions from 2019, median and 5-95 percentiles {3.3.1; 4.1;
Table 3.1; Figure 2.5; Box SPM1}
Reductions from 2019 emission levels (%)
2030 2035 2040 2050
Limit warming to1.5°C (>50%) with no or
limited overshoot
GHG 43 [34-60] 60 [49-77] 69 [58-90] 84 [73-98]
CO2 48 [36-69] 65 [50-96] 80 [61-109] 99 [79-119]
Limit warming to 2°C (>67%)
GHG 21 [1-42] 35 [22-55] 46 [34-63] 64 [53-77]
CO2 22 [1-44] 37 [21-59] 51 [36-70] 73 [55-90]
[END TABLE XX]
B.6.2 Reaching net zero CO2 or GHG emissions primarily requires deep and rapid reductions in gross emissions
of CO2, as well as substantial reductions of non-CO2 GHG emissions (high confidence). For example, in
modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, global methane emissions
are reduced by 34 [21–57]% by 2030 relative to 2019. However, some hard-to-abate residual GHG emissions
(e.g., some emissions from agriculture, aviation, shipping, and industrial processes) remain and would need to
be counterbalanced by deployment of carbon dioxide removal (CDR) methods to achieve net zero CO2 or GHG
emissions (high confidence). As a result, net zero CO2 is reached earlier than net zero GHGs (high confidence).
{3.3.2, 3.3.3, Table 3.1, Figure 3.5} (Figure SPM.5)
B.6.3 Global modelled mitigation pathways reaching net zero CO2 and GHG emissions include transitioning
from fossil fuels without carbon capture and storage (CCS) to very low- or zero-carbon energy sources, such as
renewables or fossil fuels with CCS, demand-side measures and improving efficiency, reducing non-CO2 GHG
emissions, and CDR47. In most global modelled pathways, land-use change and forestry (via reforestation and
reduced deforestation) and the energy supply sector reach net zero CO2 emissions earlier than the buildings,
industry and transport sectors. (high confidence) {3.3.3, 4.1, 4.5, Figure 4.1} (Figure SPM.5, Box SPM.1)
B.6.4 Mitigation options often have synergies with other aspects of sustainable development, but some options
can also have trade-offs. There are potential synergies between sustainable development and, for instance,
energy efficiency and renewable energy. Similarly, depending on the context48, biological CDR methods like
reforestation, improved forest management, soil carbon sequestration, peatland restoration and coastal blue
carbon management can enhance biodiversity and ecosystem functions, employment and local livelihoods.
However, afforestation or production of biomass crops can have adverse socio-economic and environmental
impacts, including on biodiversity, food and water security, local livelihoods and the rights of Indigenous
Peoples, especially if implemented at large scales and where land tenure is insecure. Modelled pathways that
assume using resources more efficiently or that shift global development towards sustainability include fewer
challenges, such as less dependence on CDR and pressure on land and biodiversity. (high confidence) {3.4.1}
[START FIGURE SPM.5 HERE]
47 CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources provided geological storage is
available. When CO2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the storage
component of these CDR methods. CO2 capture and subsurface injection is a mature technology for gas processing and enhanced oil
recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production,
where it is a critical mitigation option. The technical geological storage capacity is estimated to be on the order of 1000 GtCO2, which
is more than the CO2 storage requirements through 2100 to limit global warming to 1.5°C, although the regional availability of geological
storage could be a limiting factor. If the geological storage site is appropriately selected and managed, it is estimated that the CO2 can
be permanently isolated from the atmosphere. Implementation of CCS currently faces technological, economic, institutional, ecologicalenvironmental
and socio-cultural barriers. Currently, global rates of CCS deployment are far below those in modelled pathways limiting
global warming to 1.5°C to 2°C. Enabling conditions such as policy instruments, greater public support and technological innovation
could reduce these barriers. (high confidence) {3.3.3}
48 The impacts, risks, and co-benefits of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on
the method, site-specific context, implementation and scale (high confidence).
Approved Summary for Policymakers IPCC AR6 SYR
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Figure SPM.5: Global emissions pathways consistent with implemented policies and mitigation strategies. Panel (a),
(b) and (c) show the development of global GHG, CO2 and methane emissions in modelled pathways, while panel (d)
shows the associated timing of when GHG and CO2 emissions reach net zero. Coloured ranges denote the 5th to 95th
percentile across the global modelled pathways falling within a given category as described in Box SPM.1. The red ranges
depict emissions pathways assuming policies that were implemented by the end of 2020. Ranges of modelled pathways
that limit warming to 1.5°C (>50%) with no or limited overshoot are shown in light blue (category C1) and pathways that
Limiting warming to 1.5C and 2°C involves rapid, deep and
in most cases immediate greenhouse gas emission reductions
Net zero CO, and net zero GHG emissions can be achieved through strong reductions across all sectors
a) Net global greenhouse
80 gas (GHG) emissions
2019 emissions were
-I 12% higher than 2010
N Implemented policies - --• 60/t,.;L- .. ,N;,a;; t i;:o:na: l yDe:t::: , m:l;:n:e:d ... ..;,.. _ l l Contributions (NDCs) .!. range in 2030
E 4o q
Implemented policies result in projected
emissions that lead to warming of 3.2C, with
a range 0f2.2€to 3.5C (medium confidence)
Key
Implemented policies
(median, with percentiles 25-75% and 5-95%)
Limit warming to 2°C (>67%)
Limit warming to 1.5°C (50%)
with no or limited overshoot
Past emissions (2000-2015)
T Model range for 2015 emissions
Past GHG emissions and uncertainty for
_ 2015 and 2019 (dot indicates the median)
-20
2000 2020 2040 2060 2080 2100
these are deferent
ways to achieve
net-zero CO,
Illustrative Mitigation
Pathways (IMPs)
e) Greenhouse gas emissions by
sector at the time of net zero
CO,, compared to 2019
60
-20
2040 2060 2080 2100
t. %
f 20
um«oSo,urces ] ?
Sinks]
2020
+net zero
80 b) Net global CO, emissions
60
-20
2000
,o _,-l s5 20 ""
c) Global methane (CH,) emissions
s "le
%
Key Non-CO, emissions
transport, industry and buildings
l Energy supply (including electricity)
- Land-use change and forestry
ff
2000 2020 2040 2060 2080 2100
d) Net zero CO, will be reached
before net zero GHG emissions
2€
1.5C
2000 2020 2040
co,
2060
co,
2080
GHG
GHG
2100
Year of net zero emissions
Approved Summary for Policymakers IPCC AR6 SYR
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limit warming to 2°C (>67%) are shown in green (category C3). Global emission pathways that would limit warming to
1.5°C (>50%) with no or limited overshoot and also reach net zero GHG in the second half of the century do so between
2070-2075. Panel (e) shows the sectoral contributions of CO2 and non-CO2 emissions sources and sinks at the time when
net zero CO2 emissions are reached in illustrative mitigation pathways (IMPs) consistent with limiting warming to 1.5°C
with a high reliance on net negative emissions (IMP-Neg) (“high overshoot”), high resource efficiency (IMP-LD), a focus
on sustainable development (IMP-SP), renewables (IMP-Ren) and limiting warming to 2°C with less rapid mitigation
initially followed by a gradual strengthening (IMP-GS). Positive and negative emissions for different IMPs are compared
to GHG emissions from the year 2019. Energy supply (including electricity) includes bioenergy with carbon dioxide
capture and storage and direct air carbon dioxide capture and storage. CO2 emissions from land-use change and forestry
can only be shown as a net number as many models do not report emissions and sinks of this category separately. {Figure
3.6, 4.1} (Box SPM.1)
[END FIGURE SPM.5 HERE]
Overshoot: Exceeding a Warming Level and Returning
B.7 If warming exceeds a specified level such as 1.5°C, it could gradually be reduced again by
achieving and sustaining net negative global CO2 emissions. This would require additional
deployment of carbon dioxide removal, compared to pathways without overshoot, leading to greater
feasibility and sustainability concerns. Overshoot entails adverse impacts, some irreversible, and
additional risks for human and natural systems, all growing with the magnitude and duration of
overshoot. (high confidence) {3.1, 3.3, 3.4, Table 3.1, Figure 3.6}
B.7.1 Only a small number of the most ambitious global modelled pathways limit global warming to 1.5°C
(>50%) by 2100 without exceeding this level temporarily. Achieving and sustaining net negative global CO2
emissions, with annual rates of CDR greater than residual CO2 emissions, would gradually reduce the warming
level again (high confidence). Adverse impacts that occur during this period of overshoot and cause additional
warming via feedback mechanisms, such as increased wildfires, mass mortality of trees, drying of peatlands,
and permafrost thawing, weakening natural land carbon sinks and increasing releases of GHGs would make the
return more challenging (medium confidence). {3.3.2, 3.3.4, Table 3.1, Figure 3.6} (Box SPM.1)
B.7.2 The higher the magnitude and the longer the duration of overshoot, the more ecosystems and societies are
exposed to greater and more widespread changes in climatic impact-drivers, increasing risks for many natural
and human systems. Compared to pathways without overshoot, societies would face higher risks to
infrastructure, low-lying coastal settlements, and associated livelihoods. Overshooting 1.5°C will result in
irreversible adverse impacts on certain ecosystems with low resilience, such as polar, mountain, and coastal
ecosystems, impacted by ice-sheet, glacier melt, or by accelerating and higher committed sea level rise. (high
confidence) {3.1.2, 3.3.4}
B.7.3 The larger the overshoot, the more net negative CO2 emissions would be needed to return to 1.5°C by
2100. Transitioning towards net zero CO2 emissions faster and reducing non-CO2 emissions such as methane
more rapidly would limit peak warming levels and reduce the requirement for net negative CO2 emissions,
thereby reducing feasibility and sustainability concerns, and social and environmental risks associated with
CDR deployment at large scales. (high confidence) {3.3.3, 3.3.4, 3.4.1, Table 3.1}
Approved Summary for Policymakers IPCC AR6 SYR
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C. Responses in the Near Term
Urgency of Near-Term Integrated Climate Action
C.1 Climate change is a threat to human well-being and planetary health (very high confidence). There
is a rapidly closing window of opportunity to secure a liveable and sustainable future for all (very high
confidence). Climate resilient development integrates adaptation and mitigation to advance sustainable
development for all, and is enabled by increased international cooperation including improved access to
adequate financial resources, particularly for vulnerable regions, sectors and groups, and inclusive
governance and coordinated policies (high confidence). The choices and actions implemented in this
decade will have impacts now and for thousands of years (high confidence). {3.1, 3.3, 4.1, 4.2, 4.3, 4.4,
4.7, 4.8, 4.9, Figure 3.1, Figure 3.3, Figure 4.2} (Figure SPM.1; Figure SPM.6)
C.1.1 Evidence of observed adverse impacts and related losses and damages, projected risks, levels and trends
in vulnerability and adaptation limits, demonstrate that worldwide climate resilient development action is more
urgent than previously assessed in AR5. Climate resilient development integrates adaptation and GHG
mitigation to advance sustainable development for all. Climate resilient development pathways have been
constrained by past development, emissions and climate change and are progressively constrained by every
increment of warming, in particular beyond 1.5°C. (very high confidence) {3.4; 3.4.2; 4.1}
C.1.2 Government actions at sub-national, national and international levels, with civil society and the private
sector, play a crucial role in enabling and accelerating shifts in development pathways towards sustainability
and climate resilient development (very high confidence). Climate resilient development is enabled when
governments, civil society and the private sector make inclusive development choices that prioritize risk
reduction, equity and justice, and when decision-making processes, finance and actions are integrated across
governance levels, sectors, and timeframes (very high confidence). Enabling conditions are differentiated by
national, regional and local circumstances and geographies, according to capabilities, and include: political
commitment and follow-through, coordinated policies, social and international cooperation, ecosystem
stewardship, inclusive governance, knowledge diversity, technological innovation, monitoring and evaluation,
and improved access to adequate financial resources, especially for vulnerable regions, sectors and communities
(high confidence). {3.4; 4.2, 4.4, 4.5, 4.7, 4.8} (Figure SPM.6)
C.1.3 Continued emissions will further affect all major climate system components, and many changes will be
irreversible on centennial to millennial time scales and become larger with increasing global warming. Without
urgent, effective, and equitable mitigation and adaptation actions, climate change increasingly threatens
ecosystems, biodiversity, and the livelihoods, health and wellbeing of current and future generations. (high
confidence) {3.1.3; 3.3.3; 3.4.1, Figure 3.4; 4.1, 4.2, 4.3, 4.4} (Figure SPM.1, Figure SPM.6).
[START FIGURE SPM.6 HERE]
Approved Summary for Policymakers IPCC AR6 SYR
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Figure SPM.6: The illustrative development pathways (red to green) and associated outcomes (right panel) show that there
is a rapidly narrowing window of opportunity to secure a liveable and sustainable future for all. Climate resilient
development is the process of implementing greenhouse gas mitigation and adaptation measures to support sustainable
development. Diverging pathways illustrate that interacting choices and actions made by diverse government, private sector
and civil society actors can advance climate resilient development, shift pathways towards sustainability, and enable lower
emissions and adaptation. Diverse knowledge and values include cultural values, Indigenous Knowledge, local knowledge,
and scientific knowledge. Climatic and non-climatic events, such as droughts, floods or pandemics, pose more severe
shocks to pathways with lower climate resilient development (red to yellow) than to pathways with higher climate resilient
development (green). There are limits to adaptation and adaptive capacity for some human and natural systems at global
warming of 1.5°C, and with every increment of warming, losses and damages will increase. The development pathways
taken by countries at all stages of economic development impact GHG emissions and mitigation challenges and
opportunities, which vary across countries and regions. Pathways and opportunities for action are shaped by previous
actions (or inactions and opportunities missed; dashed pathway) and enabling and constraining conditions (left panel), and
take place in the context of climate risks, adaptation limits and development gaps. The longer emissions reductions are
delayed, the fewer effective adaptation options. {Figure 4.2; 3.1; 3.2; 3.4; 4.2; 4.4; 4.5; 4.6; 4.9}
[END FIGURE SPM.6 HERE]
There is a rapidly narrowing window of opportunity
to enable climate resilient development
Multiple interacting choices and actions can shift
development pathways towards sustainability
Illustrative 'shock' that
disrupts development
Low emissions
System transitions
Transformation
Low climate risk
Equity and justice
50G achievement
High emissions
Entrenched systems
Adaptation limits
Maladaptation
Increasing climate risk
Reduced options
for development Ecostem al
Outcomes characterising
development pathways
2100
& beyond
Prospects for dimate
resilient development will
be further limited if global
warming exceeds 15°C and
if progress towards the SDGs
is inadequate
2030
IPCC AR6
Early aon and enabling
conditic s create future
opportupities for dimate
resilient development
Sustainable Development
Goal (5DG) achievement
(.)
Past cot itions
(emissions, dimate
change, relopment)
have increased warming
and devel pment gaps persist
Past
conditions
• Economic, institutional, social
and capacity barriers
• Siloed responses
• Lack of finance, and barriers
to finance and technology
• Tradeoffs with SDGs
• Inclusive governance
• Diverse knowledges and values
• Finance and innovation
• Integration across sectors
and time scales
• Ecosystem stewardship
• Synergies between dimate
and development actions
• Behavioural change supported
by policy, infrastructure and
socio-cultural factors
Governments 2A
ii E ii f piate
society sector
Conditions that enable
individual and collective actions
Approved Summary for Policymakers IPCC AR6 SYR
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The Benefits of Near-Term Action
C.2 Deep, rapid and sustained mitigation and accelerated implementation of adaptation actions in
this decade would reduce projected losses and damages for humans and ecosystems (very high
confidence), and deliver many co-benefits, especially for air quality and health (high confidence).
Delayed mitigation and adaptation action would lock-in high-emissions infrastructure, raise risks of
stranded assets and cost-escalation, reduce feasibility, and increase losses and damages (high
confidence). Near-term actions involve high up-front investments and potentially disruptive changes
that can be lessened by a range of enabling policies (high confidence). {2.1, 2.2, 3.1, 3.2, 3.3, 3.4, 4.1,
4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8}
C.2.1 Deep, rapid, and sustained mitigation and accelerated implementation of adaptation actions in this decade
would reduce future losses and damages related to climate change for humans and ecosystems (very high
confidence). As adaptation options often have long implementation times, accelerated implementation of
adaptation in this decade is important to close adaptation gaps (high confidence). Comprehensive, effective, and
innovative responses integrating adaptation and mitigation can harness synergies and reduce trade-offs between
adaptation and mitigation (high confidence). {4.1, 4.2, 4.3}.
C.2.2 Delayed mitigation action will further increase global warming and losses and damages will rise and
additional human and natural systems will reach adaptation limits (high confidence). Challenges from delayed
adaptation and mitigation actions include the risk of cost escalation, lock-in of infrastructure, stranded assets,
and reduced feasibility and effectiveness of adaptation and mitigation options (high confidence). Without rapid,
deep and sustained mitigation and accelerated adaptation actions, losses and damages will continue to increase,
including projected adverse impacts in Africa, LDCs, SIDS, Central and South America49, Asia and the Arctic,
and will disproportionately affect the most vulnerable populations (high confidence). {2.1.2; 3.1.2, 3.2, 3.3.1,
3.3.3; 4.1, 4.2, 4.3} (Figure SPM.3, Figure SPM.4)
C.2.3 Accelerated climate action can also provide co-benefits (see also C.4). Many mitigation actions would
have benefits for health through lower air pollution, active mobility (e.g., walking, cycling), and shifts to
sustainable healthy diets. Strong, rapid and sustained reductions in methane emissions can limit near-term
warming and improve air quality by reducing global surface ozone. (high confidence) Adaptation can generate
multiple additional benefits such as improving agricultural productivity, innovation, health and wellbeing, food
security, livelihood, and biodiversity conservation (very high confidence). {4.2, 4.5.4, 4.5.5, 4.6}
C.2.4 Cost-benefit analysis remains limited in its ability to represent all avoided damages from climate change
(high confidence). The economic benefits for human health from air quality improvement arising from
mitigation action can be of the same order of magnitude as mitigation costs, and potentially even larger (medium
confidence). Even without accounting for all the benefits of avoiding potential damages the global economic
and social benefit of limiting global warming to 2°C exceeds the cost of mitigation in most of the assessed
literature (medium confidence).50 More rapid climate change mitigation, with emissions peaking earlier,
increases co-benefits and reduces feasibility risks and costs in the long-term, but requires higher up-front
investments (high confidence). {3.4.1, 4.2}
C.2.5 Ambitious mitigation pathways imply large and sometimes disruptive changes in existing economic
structures, with significant distributional consequences within and between countries. To accelerate climate
action, the adverse consequences of these changes can be moderated by fiscal, financial, institutional and
regulatory reforms and by integrating climate actions with macroeconomic policies through (i) economy-wide
packages, consistent with national circumstances, supporting sustainable low-emission growth paths; (ii)
climate resilient safety nets and social protection; and (iii) improved access to finance for low-emissions
infrastructure and technologies, especially in developing countries. (high confidence) {4.2, 4.4, 4.7, 4.8.1}
49 The southern part of Mexico is included in the climactic subregion South Central America (SCA) for WGI. Mexico is assessed as part
of North America for WGII. The climate change literature for the SCA region occasionally includes Mexico, and in those cases WGII
assessment makes reference to Latin America. Mexico is considered part of Latin America and the Caribbean for WGIII.
50 The evidence is too limited to make a similar robust conclusion for limiting warming to 1.5°C. Limiting global warming to 1.5°C
instead of 2°C would increase the costs of mitigation, but also increase the benefits in terms of reduced impacts and related risks, and
reduced adaptation needs (high confidence).
Approved Summary for Policymakers IPCC AR6 SYR
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[START FIGURE SPM.7 HERE]
There are multiple opportunities for scaling up climate action
Climate responses and
adaptation options
a) Feasibility of climate responses and adaptation, and potential of mitigation options in the near-term
options costing 100 USD tCO,-eq or
less could reduce .e g E global emissions b atlas~haFofi~ii9ievelby 2o3o f@ E s Mitigation options Potential contribution to
5g iz net emission reduction, 2030 e 6c0eh
0 1 2 3 4 5
Solar
@eye($,g m Wind
diversification, access, stability Reduce methane from coal, oil and gas
Resilient power systems mm Bioelectricity (includes BECCS) • Improve water use efficiency - Geothermal and hydropower
Nudear
Fossil Carbon Capture and Storage (CCS) - Efficient livestock systems - Improved cropland management EE Reduce conversion of natural ecosystems
Water use efficiency and water -- resource management Carbon sequestration in agriculture
Biodiversity management and mm €cystem restoration,
ecosystem connectivity afforestation, reforestation
Agroforestry mm Shift to sustainable healthy diets = Sustainable aquaculture and fisheries -- Improved sustainable forest management
Forest-based adaptation mm Reduce methane and N,O in agriculture
Integrated coastal zone management m Reduce food loss and food waste
Coastal defence and hardening L assessed
Sustainable urban water management - Efficient buildings = Fuel efficient vehicles
Sustainable land use and urban planning -- Electric vehides
Green infrastructure and EE Efficient lighting, appliances - ecosystem services and equipment
Public transport and bicycling = Biofuels for transport
Efficient shipping and aviation
Enhanced health services -- Avoid demand for energy services (e.g. WASH, nutrition and diets) =
Onsite renewables
Risk spreading and sharing - Fuel switching
Social safety nets - Reduce emission of fluorinated gas
Climate services, including m l Energy efficiency
Early Warning Systems Material efficiency
Disaster risk management mm Reduce methane from
Human migration - . Construction matweraisatlse /swuabsstteitwutaitoenr Planned relocation and resettlement Enhanced recycling =
Livelihood diversification -- Carbon epture with ■ utilisation (CC ) and CCS
••
l
Feasibility level and synergies
with mitigation
High I Medium Low
Insufficient evidence
Confidence level in potential feasibility
and in synergies with mitigation
... High •• Medium • low
Net lifetime cost of options: costs are lower than the reference
o-2o(so per «co+ea)
zo-so (so per «co+ea
5o-1oo(us0 per tcore)
1oo-200 (so per1co+eo) ■ Cost not allocated due to high
variability or lack of data
Food
Industry
Electricity
29%
Additional electrification (+60%)
73% reduction {before
additional electrification)
66%
10
10
67%
6 G1CO+eq/yr 20
• 44%
0 6 GCOyt 20
b) Potential of demand-side 0
mitigation options by 2050 {
the range of GHG emissions :{:2:./:./go traars»o
Key Buildings
Total emissions (2050)
•% Percentage of possible reduction
Demand-side mitigation potential
Potential range
Approved Summary for Policymakers IPCC AR6 SYR
Subject to Copyedit p.29
Figure SPM.7: Multiple Opportunities for scaling up climate action. Panel (a) presents selected mitigation and
adaptation options across different systems. The left hand side of panel a shows climate responses and adaptation options
assessed for their multidimensional feasibility at global scale, in the near term and up to 1.5°C global warming. As literature
above 1.5°C is limited, feasibility at higher levels of warming may change, which is currently not possible to assess
robustly. The term response is used here in addition to adaptation because some responses, such as migration, relocation
and resettlement may or may not be considered to be adaptation. Forest based adaptation includes sustainable forest
management, forest conservation and restoration, reforestation and afforestation. WASH refers to water, sanitation and
hygiene. Six feasibility dimensions (economic, technological, institutional, social, environmental and geophysical) were
used to calculate the potential feasibility of climate responses and adaptation options, along with their synergies with
mitigation. For potential feasibility and feasibility dimensions, the figure shows high, medium, or low feasibility. Synergies
with mitigation are identified as high, medium, and low.
The right hand side of Panel a provides an overview of selected mitigation options and their estimated costs and potentials
in 2030. Costs are net lifetime discounted monetary costs of avoided GHG emissions calculated relative to a reference
technology. Relative potentials and costs will vary by place, context and time and in the longer term compared to 2030.
The potential (horizontal axis) is the net GHG emission reduction (sum of reduced emissions and/or enhanced sinks) broken
down into cost categories (coloured bar segments) relative to an emission baseline consisting of current policy (around
2019) reference scenarios from the AR6 scenarios database. The potentials are assessed independently for each option and
are not additive. Health system mitigation options are included mostly in settlement and infrastructure (e.g., efficient
healthcare buildings) and cannot be identified separately. Fuel switching in industry refers to switching to electricity,
hydrogen, bioenergy and natural gas. Gradual colour transitions indicate uncertain breakdown into cost categories due to
uncertainty or heavy context dependency. The uncertainty in the total potential is typically 25–50%.
Panel (b) displays the indicative potential of demand-side mitigation options for 2050. Potentials are estimated based on
approximately 500 bottom-up studies representing all global regions. The baseline (white bar) is provided by the sectoral
mean GHG emissions in 2050 of the two scenarios (IEA-STEPS and IP_ModAct) consistent with policies announced by
national governments until 2020. The green arrow represents the demand-side emissions reductions potentials. The range
in potential is shown by a line connecting dots displaying the highest and the lowest potentials reported in the literature.
Food shows demand-side potential of socio-cultural factors and infrastructure use, and changes in land-use patterns enabled
by change in food demand. Demand-side measures and new ways of end-use service provision can reduce global GHG
emissions in end-use sectors (buildings, land transport, food) by 40–70% by 2050 compared to baseline scenarios, while
some regions and socioeconomic groups require additional energy and resources. The last row shows how demand-side
mitigation options in other sectors can influence overall electricity demand. The dark grey bar shows the projected increase
in electricity demand above the 2050 baseline due to increasing electrification in the other sectors. Based on a bottom-up
assessment, this projected increase in electricity demand can be avoided through demand-side mitigation options in the
domains of infrastructure use and socio-cultural factors that influence electricity usage in industry, land transport, and
buildings (green arrow). {Figure 4.4}
[END FIGURE SPM.7 HERE]
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Mitigation and Adaptation Options across Systems
C.3 Rapid and far-reaching transitions across all sectors and systems are necessary to achieve deep
and sustained emissions reductions and secure a liveable and sustainable future for all. These system
transitions involve a significant upscaling of a wide portfolio of mitigation and adaptation options.
Feasible, effective, and low-cost options for mitigation and adaptation are already available, with
differences across systems and regions. (high confidence) {4.1, 4.5, 4.6} (Figure SPM.7)
C.3.1 The systemic change required to achieve rapid and deep emissions reductions and transformative
adaptation to climate change is unprecedented in terms of scale, but not necessarily in terms of speed (medium
confidence). Systems transitions include: deployment of low- or zero-emission technologies; reducing and
changing demand through infrastructure design and access, socio-cultural and behavioural changes, and
increased technological efficiency and adoption; social protection, climate services or other services; and
protecting and restoring ecosystems (high confidence). Feasible, effective, and low-cost options for mitigation
and adaptation are already available (high confidence). The availability, feasibility and potential of mitigation
and adaptation options in the near-term differs across systems and regions (very high confidence). {4.1, 4.5.1–
4.5.6}(Figure SPM.7)
Energy Systems
C.3.2 Net zero CO2 energy systems entail: a substantial reduction in overall fossil fuel use, minimal use of
unabated fossil fuels51, and use of carbon capture and storage in the remaining fossil fuel systems; electricity
systems that emit no net CO2; widespread electrification; alternative energy carriers in applications less
amenable to electrification; energy conservation and efficiency; and greater integration across the energy system
(high confidence). Large contributions to emissions reductions with costs less than USD 20 tCO2-eq-1 come
from solar and wind energy, energy efficiency improvements, and methane emissions reductions (coal mining,
oil and gas, waste) (medium confidence). There are feasible adaptation options that support infrastructure
resilience, reliable power systems and efficient water use for existing and new energy generation systems (very
high confidence). Energy generation diversification (e.g., via wind, solar, small scale hydropower) and demand
side management (e.g., storage and energy efficiency improvements) can increase energy reliability and reduce
vulnerabilities to climate change (high confidence). Climate responsive energy markets, updated design
standards on energy assets according to current and projected climate change, smart-grid technologies, robust
transmission systems and improved capacity to respond to supply deficits have high feasibility in the mediumto
long-term, with mitigation co-benefits (very high confidence). {4.5.1} (Figure SPM.7)
Industry and Transport
C.3.3 Reducing industry GHG emissions entails coordinated action throughout value chains to promote all
mitigation options, including demand management, energy and materials efficiency, circular material flows, as
well as abatement technologies and transformational changes in production processes (high confidence). In
transport, sustainable biofuels, low-emissions hydrogen, and derivatives (including ammonia and synthetic
fuels) can support mitigation of CO2 emissions from shipping, aviation, and heavy-duty land transport but
require production process improvements and cost reductions (medium confidence). Sustainable biofuels can
offer additional mitigation benefits in land-based transport in the short and medium term (medium confidence).
Electric vehicles powered by low-GHG emissions electricity have large potential to reduce land-based transport
GHG emissions, on a life cycle basis (high confidence). Advances in battery technologies could facilitate the
electrification of heavy-duty trucks and compliment conventional electric rail systems (medium confidence).
The environmental footprint of battery production and growing concerns about critical minerals can be
addressed by material and supply diversification strategies, energy and material efficiency improvements, and
circular material flows (medium confidence). 4.5.2, 4.5.3} (Figure SPM.7)
51 In this context, ‘unabated fossil fuels’ refers to fossil fuels produced and used without interventions that substantially reduce the
amount of GHG emitted throughout the life cycle; for example, capturing 90% or more CO2 from power plants, or 50–80% of fugitive
methane emissions from energy supply.
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Cities, Settlements and Infrastructure
C.3.4 Urban systems are critical for achieving deep emissions reductions and advancing climate resilient
development (high confidence). Key adaptation and mitigation elements in cities include considering climate
change impacts and risks (e.g. through climate services) in the design and planning of settlements and
infrastructure; land use planning to achieve compact urban form, co-location of jobs and housing; supporting
public transport and active mobility (e.g., walking and cycling); the efficient design, construction, retrofit, and
use of buildings; reducing and changing energy and material consumption; sufficiency52; material substitution;
and electrification in combination with low emissions sources (high confidence). Urban transitions that offer
benefits for mitigation, adaptation, human health and well-being, ecosystem services, and vulnerability
reduction for low-income communities are fostered by inclusive long-term planning that takes an integrated
approach to physical, natural and social infrastructure (high confidence). Green/natural and blue infrastructure
supports carbon uptake and storage and either singly or when combined with grey infrastructure can reduce
energy use and risk from extreme events such as heatwaves, flooding, heavy precipitation and droughts, while
generating co-benefits for health, well-being and livelihoods (medium confidence). {4.5.3}
Land, Ocean, Food, and Water
C.3.5 Many agriculture, forestry, and other land use (AFOLU) options provide adaptation and mitigation
benefits that could be upscaled in the near-term across most regions. Conservation, improved management, and
restoration of forests and other ecosystems offer the largest share of economic mitigation potential, with reduced
deforestation in tropical regions having the highest total mitigation potential. Ecosystem restoration,
reforestation, and afforestation can lead to trade-offs due to competing demands on land. Minimizing trade-offs
requires integrated approaches to meet multiple objectives including food security. Demand-side measures
(shifting to sustainable healthy diets53 and reducing food loss/waste) and sustainable agricultural intensification
can reduce ecosystem conversion, and methane and nitrous oxide emissions, and free up land for reforestation
and ecosystem restoration. Sustainably sourced agricultural and forest products, including long-lived wood
products, can be used instead of more GHG-intensive products in other sectors. Effective adaptation options
include cultivar improvements, agroforestry, community-based adaptation, farm and landscape diversification,
and urban agriculture. These AFOLU response options require integration of biophysical, socioeconomic and
other enabling factors. Some options, such as conservation of high-carbon ecosystems (e.g., peatlands, wetlands,
rangelands, mangroves and forests), deliver immediate benefits, while others, such as restoration of high-carbon
ecosystems, take decades to deliver measurable results. {4.5.4} (Figure SPM.7)
C.3.6 Maintaining the resilience of biodiversity and ecosystem services at a global scale depends on effective
and equitable conservation of approximately 30% to 50% of Earth’s land, freshwater and ocean areas, including
currently near-natural ecosystems (high confidence). Conservation, protection and restoration of terrestrial,
freshwater, coastal and ocean ecosystems, together with targeted management to adapt to unavoidable impacts
of climate change reduces the vulnerability of biodiversity and ecosystem services to climate change (high
confidence), reduces coastal erosion and flooding (high confidence), and could increase carbon uptake and
storage if global warming is limited (medium confidence). Rebuilding overexploited or depleted fisheries
reduces negative climate change impacts on fisheries (medium confidence) and supports food security,
biodiversity, human health and well-being (high confidence). Land restoration contributes to climate change
mitigation and adaptation with synergies via enhanced ecosystem services and with economically positive
returns and co-benefits for poverty reduction and improved livelihoods (high confidence). Cooperation, and
inclusive decision making, with Indigenous Peoples and local communities, as well as recognition of inherent
rights of Indigenous Peoples, is integral to successful adaptation and mitigation across forests and other
ecosystems (high confidence). {4.5.4, 4.6} (Figure SPM.7)
52 A set of measures and daily practices that avoid demand for energy, materials, land, and water while delivering human well-being for
all within planetary boundaries {4.5.3}
53 ‘Sustainable healthy diets’ promote all dimensions of individuals’ health and well-being; have low environmental pressure and impact;
are accessible, affordable, safe and equitable; and are culturally acceptable, as described in FAO and WHO. The related concept of
‘balanced diets’ refers to diets that feature plant-based foods, such as those based on coarse grains, legumes, fruits and vegetables, nuts
and seeds, and animal-sourced food produced in resilient, sustainable and low-GHG emission systems, as described in SRCCL.
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Health and Nutrition
C.3.7 Human health will benefit from integrated mitigation and adaptation options that mainstream health into
food, infrastructure, social protection, and water policies (very high confidence). Effective adaptation options
exist to help protect human health and wellbeing, including: strengthening public health programs related to
climate-sensitive diseases, increasing health systems resilience, improving ecosystem health, improving access
to potable water, reducing exposure of water and sanitation systems to flooding, improving surveillance and
early warning systems, vaccine development (very high confidence), improving access to mental healthcare,
and Heat Health Action Plans that include early warning and response systems (high confidence). Adaptation
strategies which reduce food loss and waste or support balanced, sustainable healthy diets contribute to nutrition,
health, biodiversity and other environmental benefits (high confidence). {4.5.5} (Figure SPM.7)
Society, Livelihoods, and Economies
C.3.8 Policy mixes that include weather and health insurance, social protection and adaptive social safety nets,
contingent finance and reserve funds, and universal access to early warning systems combined with effective
contingency plans, can reduce vulnerability and exposure of human systems. Disaster risk management, early
warning systems, climate services and risk spreading and sharing approaches have broad applicability across
sectors. Increasing education including capacity building, climate literacy, and information provided through
climate services and community approaches can facilitate heightened risk perception and accelerate behavioural
changes and planning. (high confidence) {4.5.6}
Synergies and Trade-Offs with Sustainable Development
C.4 Accelerated and equitable action in mitigating and adapting to climate change impacts is critical
to sustainable development. Mitigation and adaptation actions have more synergies than trade-offs
with Sustainable Development Goals. Synergies and trade-offs depend on context and scale of
implementation. (high confidence) {3.4, 4.2, 4.4, 4.5, 4.6, 4.9, Figure 4.5}
C.4.1 Mitigation efforts embedded within the wider development context can increase the pace, depth and
breadth of emission reductions (medium confidence). Countries at all stages of economic development seek to
improve the well-being of people, and their development priorities reflect different starting points and contexts.
Different contexts include but are not limited to social, economic, environmental, cultural, political
circumstances, resource endowment, capabilities, international environment, and prior development (high
confidence). In regions with high dependency on fossil fuels for, among other things, revenue and employment
generation, mitigating risk for sustainable development requires policies that promote economic and energy
sector diversification and considerations of just transitions principles, processes and practices (high confidence).
Eradicating extreme poverty, energy poverty, and providing decent living standards in low-emitting countries /
regions in the context of achieving sustainable development objectives, in the near term, can be achieved without
significant global emissions growth (high confidence). {4.4, 4.6, Annex I: Glossary}
C.4.2 Many mitigation and adaptation actions have multiple synergies with Sustainable Development Goals
(SDGs) and sustainable development generally, but some actions can also have trade-offs. Potential synergies
with SDGs exceed potential trade-offs; synergies and trade-offs depend on the pace and magnitude of change
and the development context including inequalities with consideration of climate justice. Trade-offs can be
evaluated and minimised by giving emphasis to capacity building, finance, governance, technology transfer,
investments, development, context specific gender-based and other social equity considerations with
meaningful participation of Indigenous Peoples, local communities and vulnerable populations. (high
confidence) {3.4.1, 4.6, Figure 4.5, 4.9}
C.4.3 Implementing both mitigation and adaptation actions together and taking trade-offs into account supports
co-benefits and synergies for human health and well-being. For example, improved access to clean energy
sources and technologies generate health benefits especially for women and children; electrification combined
with low-GHG energy, and shifts to active mobility and public transport can enhance air quality, health,
employment, and can elicit energy security and deliver equity. (high confidence) {4.2, 4.5.3, 4.5.5, 4.6, 4.9}
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Equity and Inclusion
C.5 Prioritising equity, climate justice, social justice, inclusion and just transition processes can
enable adaptation and ambitious mitigation actions and climate resilient development. Adaptation
outcomes are enhanced by increased support to regions and people with the highest vulnerability to
climatic hazards. Integrating climate adaptation into social protection programs improves resilience.
Many options are available for reducing emission-intensive consumption, including through
behavioural and lifestyle changes, with co-benefits for societal well-being. (high confidence) {4.4, 4.5}
C.5.1 Equity remains a central element in the UN climate regime, notwithstanding shifts in differentiation
between states over time and challenges in assessing fair shares. Ambitious mitigation pathways imply large
and sometimes disruptive changes in economic structure, with significant distributional consequences, within
and between countries. Distributional consequences within and between countries include shifting of income
and employment during the transition from high- to low-emissions activities. (high confidence) {4.4}
C.5.2 Adaptation and mitigation actions, that prioritise equity, social justice, climate justice, rights-based
approaches, and inclusivity, lead to more sustainable outcomes, reduce trade-offs, support transformative
change and advance climate resilient development. Redistributive policies across sectors and regions that shield
the poor and vulnerable, social safety nets, equity, inclusion and just transitions, at all scales can enable deeper
societal ambitions and resolve trade-offs with sustainable development goals. Attention to equity and broad and
meaningful participation of all relevant actors in decision making at all scales can build social trust which builds
on equitable sharing of benefits and burdens of mitigation that deepen and widen support for transformative
changes. (high confidence) {4.4}
C.5.3 Regions and people (3.3 to 3.6 billion in number) with considerable development constraints have high
vulnerability to climatic hazards (see A.2.2). Adaptation outcomes for the most vulnerable within and across
countries and regions are enhanced through approaches focusing on equity, inclusivity and rights-based
approaches. Vulnerability is exacerbated by inequity and marginalisation linked to e.g., gender, ethnicity, low
incomes, informal settlements, disability, age, and historical and ongoing patterns of inequity such as
colonialism, especially for many Indigenous Peoples and local communities. Integrating climate adaptation into
social protection programs, including cash transfers and public works programs, is highly feasible and increases
resilience to climate change, especially when supported by basic services and infrastructure. The greatest gains
in well-being in urban areas can be achieved by prioritising access to finance to reduce climate risk for lowincome
and marginalised communities including people living in informal settlements. (high confidence). {4.4,
4.5.3, 4.5.5, 4.5.6}
C.5.4 The design of regulatory instruments and economic instruments and consumption-based approaches, can
advance equity. Individuals with high socio-economic status contribute disproportionately to emissions, and
have the highest potential for emissions reductions. Many options are available for reducing emission-intensive
consumption while improving societal well-being. Socio-cultural options, behaviour and lifestyle changes
supported by policies, infrastructure, and technology can help end-users shift to low-emissions-intensive
consumption, with multiple co-benefits. A substantial share of the population in low-emitting countries lack
access to modern energy services. Technology development, transfer, capacity building and financing can
support developing countries/ regions leapfrogging or transitioning to low-emissions transport systems thereby
providing multiple co-benefits. Climate resilient development is advanced when actors work in equitable, just
and inclusive ways to reconcile divergent interests, values and worldviews, toward equitable and just outcomes.
(high confidence) {2.1, 4.4}
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Governance and Policies
C.6 Effective climate action is enabled by political commitment, well-aligned multilevel governance,
institutional frameworks, laws, policies and strategies and enhanced access to finance and technology.
Clear goals, coordination across multiple policy domains, and inclusive governance processes
facilitate effective climate action. Regulatory and economic instruments can support deep emissions
reductions and climate resilience if scaled up and applied widely. Climate resilient development
benefits from drawing on diverse knowledge. (high confidence) {2.2, 4.4, 4.5, 4.7}
C.6.1 Effective climate governance enables mitigation and adaptation. Effective governance provides overall
direction on setting targets and priorities and mainstreaming climate action across policy domains and levels,
based on national circumstances and in the context of international cooperation. It enhances monitoring and
evaluation and regulatory certainty, prioritising inclusive, transparent and equitable decision-making, and
improves access to finance and technology (see C.7). (high confidence) {2.2.2, 4.7}
C.6.2 Effective local, municipal, national and subnational institutions build consensus for climate action among
diverse interests, enable coordination and inform strategy setting but require adequate institutional capacity.
Policy support is influenced by actors in civil society, including businesses, youth, women, labour, media,
Indigenous Peoples, and local communities. Effectiveness is enhanced by political commitment and
partnerships between different groups in society. (high confidence) {2.2; 4.7}
C.6.3 Effective multilevel governance for mitigation, adaptation, risk management, and climate resilient
development is enabled by inclusive decision processes that prioritise equity and justice in planning and
implementation, allocation of appropriate resources, institutional review, and monitoring and evaluation.
Vulnerabilities and climate risks are often reduced through carefully designed and implemented laws, policies,
participatory processes, and interventions that address context specific inequities such as those based on gender,
ethnicity, disability, age, location and income. (high confidence) {4.4, 4.7}
C.6.4 Regulatory and economic instruments could support deep emissions reductions if scaled up and applied
more widely (high confidence). Scaling up and enhancing the use of regulatory instruments can improve
mitigation outcomes in sectoral applications, consistent with national circumstances (high confidence). Where
implemented, carbon pricing instruments have incentivized low-cost emissions reduction measures but have
been less effective, on their own and at prevailing prices during the assessment period, to promote higher-cost
measures necessary for further reductions (medium confidence). Equity and distributional impacts of such
carbon pricing instruments, e.g., carbon taxes and emissions trading, can be addressed by using revenue to
support low-income households, among other approaches. Removing fossil fuel subsidies would reduce
emissions54 and yield benefits such as improved public revenue, macroeconomic and sustainability
performance; subsidy removal can have adverse distributional impacts, especially on the most economically
vulnerable groups which, in some cases can be mitigated by measures such as redistributing revenue saved, all
of which depend on national circumstances (high confidence). Economy-wide policy packages, such as public
spending commitments, pricing reforms, can meet short-term economic goals while reducing emissions and
shifting development pathways towards sustainability (medium confidence). Effective policy packages would
be comprehensive, consistent, balanced across objectives, and tailored to national circumstances (high
confidence). {2.2.2, 4.7}
C.6.5 Drawing on diverse knowledges and cultural values, meaningful participation and inclusive engagement
processes—including Indigenous Knowledge, local knowledge, and scientific knowledge—facilitates climate
resilient development, builds capacity and allows locally appropriate and socially acceptable solutions. (high
confidence) {4.4, 4.5.6, 4.7}
54 Fossil fuel subsidy removal is projected by various studies to reduce global CO2 emission by 1-4%, and GHG emissions by up to 10%
by 2030, varying across regions (medium confidence).
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Finance, Technology and International Cooperation
C.7 Finance, technology and international cooperation are critical enablers for accelerated climate
action. If climate goals are to be achieved, both adaptation and mitigation financing would need to
increase many-fold. There is sufficient global capital to close the global investment gaps but there are
barriers to redirect capital to climate action. Enhancing technology innovation systems is key to
accelerate the widespread adoption of technologies and practices. Enhancing international
cooperation is possible through multiple channels. (high confidence) {2.3, 4.8}
C.7.1 Improved availability of and access to finance55 would enable accelerated climate action (very high
confidence). Addressing needs and gaps and broadening equitable access to domestic and international finance,
when combined with other supportive actions, can act as a catalyst for accelerating adaptation and mitigation,
and enabling climate resilient development (high confidence). If climate goals are to be achieved, and to address
rising risks and accelerate investments in emissions reductions, both adaptation and mitigation finance would
need to increase many-fold (high confidence). {4.8.1}
C.7.2 Increased access to finance can build capacity and address soft limits to adaptation and avert rising risks,
especially for developing countries, vulnerable groups, regions and sectors (high confidence). Public finance is
an important enabler of adaptation and mitigation, and can also leverage private finance (high confidence).
Average annual modelled mitigation investment requirements for 2020 to 2030 in scenarios that limit warming
to 2°C or 1.5°C are a factor of three to six greater than current levels56, and total mitigation investments (public,
private, domestic and international) would need to increase across all sectors and regions (medium confidence).
Even if extensive global mitigation efforts are implemented, there will be a need for financial, technical, and
human resources for adaptation (high confidence). {4.3, 4.8.1}
C.7.3 There is sufficient global capital and liquidity to close global investment gaps, given the size of the global
financial system, but there are barriers to redirect capital to climate action both within and outside the global
financial sector and in the context of economic vulnerabilities and indebtedness facing developing countries.
Reducing financing barriers for scaling up financial flows would require clear signalling and support by
governments, including a stronger alignment of public finances in order to lower real and perceived regulatory,
cost and market barriers and risks and improving the risk-return profile of investments. At the same time,
depending on national contexts, financial actors, including investors, financial intermediaries, central banks and
financial regulators can shift the systemic underpricing of climate-related risks, and reduce sectoral and regional
mismatches between available capital and investment needs. (high confidence) {4.8.1}
C.7.4 Tracked financial flows fall short of the levels needed for adaptation and to achieve mitigation goals
across all sectors and regions. These gaps create many opportunities and the challenge of closing gaps is largest
in developing countries. Accelerated financial support for developing countries from developed countries and
other sources is a critical enabler to enhance adaptation and mitigation actions and address inequities in access
to finance, including its costs, terms and conditions, and economic vulnerability to climate change for
developing countries. Scaled-up public grants for mitigation and adaptation funding for vulnerable regions,
especially in Sub-Saharan Africa, would be cost-effective and have high social returns in terms of access to
basic energy. Options for scaling up mitigation in developing countries include: increased levels of public
finance and publicly mobilised private finance flows from developed to developing countries in the context of
the USD 100 billion-a-year goal; increased use of public guarantees to reduce risks and leverage private flows
at lower cost; local capital markets development; and building greater trust in international cooperation
processes. A coordinated effort to make the post-pandemic recovery sustainable over the longer-term can
accelerate climate action, including in developing regions and countries facing high debt costs, debt distress and
macroeconomic uncertainty. (high confidence) {4.8.1}
55 Finance originates from diverse sources: public or private, local, national or international, bilateral or multilateral, and alternative
sources. It can take the form of grants, technical assistance, loans (concessional and non-concessional), bonds, equity, risk insurance and
financial guarantees (of different types).
56 These estimates rely on scenario assumptions.
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C.7.5 Enhancing technology innovation systems can provide opportunities to lower emissions growth, create
social and environmental co-benefits, and achieve other SDGs. Policy packages tailored to national contexts
and technological characteristics have been effective in supporting low-emission innovation and technology
diffusion. Public policies can support training and R&D, complemented by both regulatory and market-based
instruments that create incentives and market opportunities. Technological innovation can have trade-offs such
as new and greater environmental impacts, social inequalities, overdependence on foreign knowledge and
providers, distributional impacts and rebound effects57, requiring appropriate governance and policies to
enhance potential and reduce trade-offs. Innovation and adoption of low-emission technologies lags in most
developing countries, particularly least developed ones, due in part to weaker enabling conditions, including
limited finance, technology development and transfer, and capacity building. (high confidence) {4.8.3}
C.7.6 International cooperation is a critical enabler for achieving ambitious climate change mitigation,
adaptation, and climate resilient development (high confidence). Climate resilient development is enabled by
increased international cooperation including mobilising and enhancing access to finance, particularly for
developing countries, vulnerable regions, sectors and groups and aligning finance flows for climate action to be
consistent with ambition levels and funding needs (high confidence). Enhancing international cooperation on
finance, technology and capacity building can enable greater ambition and can act as a catalyst for accelerating
mitigation and adaptation, and shifting development pathways towards sustainability (high confidence). This
includes support to NDCs and accelerating technology development and deployment (high confidence).
Transnational partnerships can stimulate policy development, technology diffusion, adaptation and mitigation,
though uncertainties remain over their costs, feasibility and effectiveness (medium confidence). International
environmental and sectoral agreements, institutions and initiatives are helping, and in some cases may help, to
stimulate low GHG emissions investments and reduce emissions (medium confidence). {2.2.2, 4.8.2}
57 Leading to lower net emission reductions or even emission increases.
PART III (A): Reports of the Intergovernmental Panel on Climate Change (IPCC)