OF THE IPCC SIXTH ASSESSMENT REPORT (AR6)

Longer Report 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 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)

Date of Draft: 22 March 2023

Notes: SFs Compiled Version

Table of Contents

Section 1: Introduction 4 Section 2: Current Status and Trends 6

2.1 Observed Changes, Impacts and Attribution 6

2.1.a

2.1.1 Observed Warming and its Causes 6

2.1.b

2.1.2 Observed Climate System Changes and Impacts to Date 11

2.2 Responses Undertaken to Date 18

2.2.a

2.2.1 Global Policy Setting 18

2.2.b

2.2.2 Mitigation Actions to Date 19

2.2.c

2.2.3 Adaptation Actions to Date 21

2.3 Current Mitigation and Adaptation Actions and Policies are not Sufficient 23

2.3.a

2.3.1 The Gap Between Mitigation Policies, Pledges and Pathways that Limit Warming to 1.5 or Below 2°C 23

2.3.1.a Cross-Section Box.1: Understanding Net Zero CO2and Net Zero GHG Emissions 26

2.3.b

2.3.2 Adaptation Gaps and Barriers 27

2.3.c

2.3.3 Lack of Finance as a Barrier to Climate Action 28

2.3.3.a Cross-Section Box.2: Scenarios, Global Warming Levels, and Risks 29

2.3.3.b Section 3: Long-Term Climate and Development Futures 33

3.2 Long-term Adaptation Options and Limits 43

3.3 Mitigation Pathways 46

3.3.a

3.3.1 Remaining Carbon Budgets 46

3.3.b

3.3.2 Net Zero Emissions: Timing and Implications 50

3.3.c

3.3.3 Sectoral Contributions to Mitigation 51

3.3.d

3.3.4 Overshoot Pathways: Increased Risks and Other Implications 53

3.4 Long-Term Interactions Between Adaptation, Mitigation and Sustainable Development 53

3.4.a

3.4.1 Synergies and trade-offs, costs and benefits 53

3.4.b

3.4.2 Advancing Integrated Climate Action for Sustainable Development 55

3.4.2.a Section 4: Near-Term Responses in a Changing Climate 56

4.1 The Timing and Urgency of Climate Action 56

4.2 Benefits of Strengthening Near-Term Action 59

4.3 Near-Term Risks 62

4.4 Equity and Inclusion in Climate Change Action 66

4.5 Near-Term Mitigation and Adaptation Actions 68

4.5.a

4.5.1 Energy Systems 70

4.5.b

4.5.2 Industry 71

4.5.c

4.5.3 Cities, Settlements and Infrastructure 72

4.5.d

4.5.5 Health and Nutrition 74

4.5.e

4.5.6 Society, Livelihoods, and Economies 74

4.6 Co-Benefits of Adaptation and Mitigation for Sustainable Development Goals 75

4.7 Governance and Policy for Near-Term Climate Change Action 78

4.8 Strengthening the Response: Finance, International Cooperation and Technology 80

4.8.a

4.8.1 Finance for Mitigation and Adaptation Actions 80

4.8.b

4.8.2 International Cooperation and Coordination 82

4.8.c

4.8.3 Technology Innovation, Adoption, Diffusion and Transfer 83

4.9 Integration of Near-Term Actions Across Sectors and Systems 84

4.9.a

Section 1: Introduction

1. Introduction

1..a

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, based on the peer-reviewed scientific, technical and socio-economic literature since the publication of the IPCC’s Fifth Assessment Report (AR5) in 2014.

1..b

The assessment is undertaken within the context of the evolving international landscape, in particular, 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. It reflects the increasing diversity of those involved in climate action.

1..c

This report integrates the main findings of the AR6 Working Group reports1and the three AR6 Special Reports2. It 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. Building on multiple analytical frameworks, including those from the physical and social sciences, this report identifies opportunities for transformative action which are effective, feasible, just and equitable using concepts of systems transitions and resilient development pathways3. Different regional classification schemes4are used for physical, social and economic aspects, reflecting the underlying literature.

1..d

After this introduction, Section 2, ‘ Current Status and Trends ’, opens with the assessment of observational evidence for our changing climate, historical and current drivers of human-induced climate change, and its impacts. It assesses the current implementation of adaptation and mitigation response options. Section 3, ‘ Long-Term Climate and Development Futures ’, provides a long-term assessment of climate change to 2100 and beyond in a broad range of socio-economic futures. It considers long-term characteristics, impacts, risks and costs in adaptation and mitigation pathways in the context of sustainable development. Section 4, ‘ Near- Term Responses in a Changing Climate ’, assesses opportunities for scaling up effective action in the period up to 2040, in the context of climate pledges, and commitments, and the pursuit of sustainable development.

1..e

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 language5. The scientific findings are drawn from the underlying reports and arise from their Summary for Policymakers (hereafter SPM), Technical Summary (hereafter TS), and underlying chapters and are indicated by {} brackets. Figure 1.1 shows the Synthesis Report Figures Key, a guide to visual icons that are used across multiple figures within this report.

1..f1The three Working Group contributions to AR6 are: Climate Change 2021: The Physical Science Basis; Climate Change 2022: Impacts, Adaptation and Vulnerability; and Climate Change 2022: Mitigation of Climate Change, respectively. Their assessments cover scientific literature accepted for publication respectively by 31 January 2021, 1 September 2021 and 11 October 2021.2The 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 2019.3The Glossary (Annex I) includes definitions of these, and other terms and concepts used in this report drawn from the AR6 joint Working Group Glossary.4Depending on the climate information context, geographical regions in AR6 may refer to larger areas, such as sub-continents and oceanic regions, or to typological regions, such as monsoon regions, coastlines, mountain ranges or cities. A new set of standard AR6 WGI reference land and ocean regions have been defined {1.4.5, 10.1, 11.9, 12.1–12.4, Atlas.1.3.3–1.3.4}. WGIII allocates countries to geographical regions, based on the UN Statistics Division Classification

Annex II WG III

.5Each 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%; more likely than not >50-100%; 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 also is typeset in italics: for example, very likely . This is consistent with

1..g Figure 1.1: The Synthesis Report figures key.

1..h

Section 4: Near-Term Responses in a Changing Climate

4.1 The Timing and Urgency of Climate Action

4.1.a Deep, rapid and sustained mitigation and accelerated implementation of adaptation reduces the risks of climate change for humans and ecosystems. In 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, global GHG emissions are projected to peak in the early 2020s followed by rapid and deep reductions.As adaptation options often have long implementation times, accelerated implementation of adaptation, particularly in this decade, is important to close adaptation gaps. (high confidence)

4.1.b The magnitude and rate of climate change and associated risks depend strongly on near-term mitigation and adaptation actions (very high confidence). Global warming is more likely than not to reach 1.5°C between 2021 and 2040 even under the very low GHG emission scenarios (SSP1-1.9), and likely or very likely to exceed 1.5°C under higher emissions scenarios84. Many adaptation options have medium or high feasibility up to 1.5°C ( medium to high confidence , depending on option), but hard limits to adaptation have already been reached in some ecosystems and the effectiveness of adaptation to reduce climate risk will decrease with increasing warming ( high confidence ). Societal choices and actions implemented in this decade determine the extent to which medium- and long-term pathways will deliver higher or lower climate resilient development ( high confidence ). 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 ). Without urgent, effective and equitable adaptation and mitigation actions, climate change increasingly threatens the health and livelihoods of people around the globe, ecosystem health, and biodiversity, with severe adverse consequences for current and future generations ( high confidence ).

WGI SPM B.1.3 WGI SPM B.5.1 WGI SPM B.5.2 WGII SPM A WGII SPM B.4 WGII SPM C.2 WGII SPM C.3.3 WGII Figure SPM.4 WGII SPM D.1 WGII SPM D.5 WGIII SPM D.1.1 SR1.5 SPM D.2.2

. (Cross-Section Box.2, Figure 2.1, Figure 2.3)

4.1.c In 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%), assuming immediate actions, global GHG emissions are projected to peak in the early 2020s followed by rapid and deep GHG emissions reductions (high confidence)85. In pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, net global GHG emissions are projected to fall by 43% [34–60%]86below 2019 levels by 2030,60% [49–77%] by 2035, 69% [58-90%] by 2040 and 84% [73-98%] ( high confidence ) (Section 2.3.1, Table 2.2, Figure 2.5, Table 3.1)87. Global modelled pathways that limit warming to 2°C (>67%) have reductions in GHG emissions below 2019 levels of 21% [1–42]% by 2030, 35% [22–55%] by 2035, 46% [34-63%] by 2040 and 64% [53-77%] by 205088( high confidence ). Global GHG emissions associated with NDCs announced prior to COP26 would make it likely that warming would exceed 1.5°C ( high confidence ) and limiting warming to 2°C (>67%) would then imply a rapid acceleration of emission reductions during 2030–2050, around 70% faster than in pathways where immediate action is taken to limit warming to 2°C (>67%) ( medium confidence ) (Section 2.3.1) Continued investments in unabated high-emitting infrastructure89and limited development and deployment of low- emitting alternatives prior to 2030 would act as barriers to this acceleration and increase feasibility risks ( high confidence ). {WGIII SPM B.6.3, WGIII Chapter 3.5.2, WGIII SPM B.6, WGIII SPM B.6., WGIII SPM C.1, WGIII SPM C1.1, Table SPM.2 } (Cross-Section Box.2)

4.1.d84In 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, 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). The best estimates [and very likely ranges] of global warming for the different scenarios in the near-term are: 1.5°C [1.2°C–1.7°C] (SSP1-1.9); 1.5°C [1.2°C–1.8°C] (SSP1-2.6); 1.5°C [1.2°C–1.8°C] (SSP2-4.5); 1.5°C [1.2°C–1.8°C] (SSP3-7.0); and 1.6°C [1.3°C–1.9°C] (SSP5-8.5).

WGI SPM B.1.3 WGI Table SPM.1

(Cross-Section Box.2)85Values in parentheses indicate the likelihood of limiting warming to the level specified (see Cross-Section Box.2).86Median and very likely range [5th to 95th percentile]

WGIII SPM footnote 30

.87These numbers for CO2 are 48% [36-69] in 2030, 65% [50-96%] in 2035, 80% [61-109%] in 2040 and 99 [79-119%] in 2050.88These numbers for CO2 are 22% [1-44] in 2030, 37% [21-59%] in 2035, 51% [36-70%] in 2040 and 73 [55-90%] in 205089In 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 CO2from power plants, or 50–80% of fugitive both net CO 2emissions and non-CO2emissions (see Figure 3.6) (high confidence). For example, in pathways that limit warming to 1.5°C (>50%) with no or limited overshoot, global CH4(methane) emissions are reduced by 34% [21–57%] below 2019 levels by 2030 and by 44% [31–63%] in 2040 ( high confidence ). Global CH4emissions are reduced by 24% [9–53%] below 2019 levels by 2030 and by 37% [20–60%] in 2040 in modelled pathways that limit warming to 2°C with action starting in 2020 (>67%) ( high confidence ).

WGIII SPM C1.2 WGIII Table SPM.2 WGIII Chapter 3.3 SR1.5 SPM C.1 SR1.5 SPM C.1.2

(Cross-Section Box.2)

4.1.e All global modelled pathways that limit warming to 2°C (>67%) or lower by 2100 involve GHG emission reductions in all sectors (high confidence). The contributions of different sectors vary across modelled mitigation pathways. In most global modelled mitigation pathways, emissions from land-use, land-use change and forestry, via reforestation and reduced deforestation, and from the energy supply sector reach net zero CO2emissions earlier than the buildings, industry and transport sectors (Figure 4.1). Strategies can rely on combinations of different options (Figure 4.1, Section 4.5), but doing less in one sector needs to be compensated by further reductions in other sectors if warming is to be limited. ( high confidence )

WGIII SPM C.3 WGIII SPM C.3.1 WGIII SPM 3.2 WGIII SPM C.3.3

(Cross-Section Box.2)

4.1.f 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 America90, Asia and the Arctic, and will disproportionately affect the most vulnerable populations (high confidence). WGII SPM C.3.5 WGII SPM B.2.4 WGII Global to Regional Atlas Annex A1.15 A1.27 WGII 12.2 WGII 10. Box 10.6 WGII TS D.7.5 WGII CCB6 ES SR1.5 SPM B.5.3 SR 1.5 SPM B.5.7 SRCCL A.5.6

(Figure 3.2; Figure 3.3)

4.2 Benefits of Strengthening Near-Term Action

4.2.a Accelerated implementation of adaptation will improve well-being by reducing losses and damages, especially for vulnerable populations. Deep, rapid and sustained mitigation actions would reduce future adaptation costs and losses and damages, enhance sustainable development co-benefits, avoid locking-in emission sources, and reduce stranded assets and irreversible climate changes. These near-term actions involve higher up-front investments and disruptive changes, which can be moderated by a range of enabling conditions and removal or reduction of barriers to feasibility.(high confidence)

4.2.b Accelerated implementation of adaptation responses will bring benefits to human well-being (high confidence) (Section 4.3). As adaptation options often have long implementation times, long-term planning and accelerated implementation, particularly in this decade, is important to close adaptation gaps, recognising that constraints remain for some regions. The benefits to vulnerable populations would be high (see Section 4.4). ( high confidence) { WGI SPM B.1, WGI SPM B.1.3, WGI SPM B.2.2, WGI SPM B.3; WGII SPM C.1.1, WGII SPM C.1.2, WGII SPM C.2, WGII SPM C.3.1, WGII SPM Figure SPM.4b; SROCC SPM C.3.4, SROCC Figure 3.4, SROCC SPM Figure 5}

4.2.c 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). 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 ). Delayed mitigation action will further increase global warming which will decrease the effectiveness of many adaptation options, including Ecosystem-based Adaptation and many water-related options, as well as increasing mitigation feasibility risks, such as for options based on ecosystems ( high confidence ). Comprehensive, effective, and innovative responses integrating adaptation and mitigation can harness synergies and reduce trade-offs between adaptation and mitigation, as well as in meeting requirements for financing ( very high confidence ) (see Section 4.5, 4.6, 4.8 and 4.9)

WGII SPM B.3 WGII SPM B.4 WGII SPM B.6.2 WGII SPM C.2 WGII SPM C.3 WGII SPM D.1 WGII SPM D.4.3 WGII SPM D.5 WG II TS D.1.4 WG II TS.D.5 WGII TS D.7.5 WGIII SPM B.6.3 WGIII SPM B.6.4 WGIII SPM C.9 WGIII SPM D.2 WGIII SPM E.13 SR1.5 SPM C.2.7 SR1.5 D.1.3 SR1.5 D.5.2

.

4.2.d Mitigation actions will have other sustainable development co-benefits (high confidence). Mitigation will improve air quality and human health in the near-term notably because many air pollutants are co-emitted by GHG emitting sectors and because methane emissions leads to surface ozone formation ( high confidence ) The benefits from air quality improvement include prevention of air pollution-related premature deaths, chronic diseases and damages to ecosystems and crops. 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 ). As methane has a short lifetime but is a potent GHG, strong, rapid and sustained reductions in methane emissions can limit near-term warming and improve air quality by reducing global surface ozone ( high confidence ).

WGI SPM D.1.7 WGI SPM D.2.2 WGI Chapter 6.7 WGI TS Box TS.7 WGI Chapter 6 Box 6.2 WGI Figures 6.3 6.16 6.17 WGII TS.D.8.3 WGII Cross-Chapter Box HEALTH WGII Chapter 5 ES WGII Chapter 7 ES WGII Chapter 7.3.1.2 WGIII Figure SPM.8 WGIII SPM C.2.3 WGIII SPM C.4.2 WGIII TS.4.2

infrastructure, stranded assets, and reduced feasibility and effectiveness of adaptation and mitigation options ( high confidence). The continued installation of unabated fossil fuel91infrastructure will ‘lock- in’ GHG emissions (high confidence). 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 ), with globally discounted value projected to be around USD1–4 trillion from 2015 to 2050 ( medium confidence ). Early actions would limit the size of these stranded assets, whereas delayed actions with continued investments in unabated high-emitting infrastructure and limited development and deployment of low-emitting alternatives prior to 2030 would raise future stranded assets to the higher end of the range – acting as barriers and increase political economy feasibility risks that may jeopardise efforts to limit global warming ( high confidence ).

WGIII SPM B.6.3 WGIII SPM C.4 WGIII Box TS.8

.

4.2.e Scaling-up near-term climate actions (Section 4.1) will mobilise a mix of low-cost and high-cost options. High-cost options, as in energy and infrastructure, are needed to avoid future lock-ins, foster innovation and initiate transformational changes (Figure 4.4). Climate resilient development pathways in support of sustainable development for all are shaped by equity, and social and climate justice (v ery high confidence ). 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 )

WGII SPM C.5 WGII SPM D1 WGIII TS.5.2 WGIII Section 8.3.1 WGIII Section 8.3.4 WGIII Section 8.4.1 WGIII Section 8.6

.

4.2.f Scaling-up climate action may generate disruptive changes in economic structure with distributional consequences and need to reconcile divergent interests, values and worldviews, within and between countries . Deeper fiscal, financial, institutional and regulatory reforms can offset such adverse effects and unlock mitigation potentials. Societal choices and actions implemented in this decade will determine the extent to which medium and long-term development pathways will deliver higher or lower climate resilient development outcomes. ( high confidence )

WGII SPM D.2 WGII SPM D.5 WGII Box TS.8 WGIII SPM D.3 WGIII SPM E.2 WGIII SPM E.3 WGIII SPM E.4 WGIII TS.2 WGIII TS.4.1 WGIII TS.6.4 WGIII Chapter 15.2 WGIII Chapter 15.6

4.2.g Enabling conditions would need to be strengthened in the near-term and barriers reduced or removed to realise opportunities for deep and rapid adaptation and mitigation actions and climate resilient development(high confidence)(Figure 4.2). These enabling conditions are differentiated by national, regional and local circumstances and geographies, according to capabilities, and include: equity and and inclusion in climate action (see Section 4.4), rapid and far-reaching transitions in sectors and system (see Section 4.5), measures to achieve synergies and reduce trade-offs with sustainable development goals (see Section 4.6), governance and policy improvements (see Section 4.7), access to finance, improved international cooperation and technology improvements (see Section 4.8), and integration of near-term actions across sectors, systems and regions (see Section 4.9). { WGII SPM D.2, WGIII SPM E.1, WGIII SPM E.2}

4.2.h Barriers to feasibility would need to be reduced or removed to deploy mitigation and adaptation options at scale. Many limits to feasibility and effectiveness of responses can be overcome by addressing a range of barriers, including economic, technological, institutional, social, environmental and geophysical. 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. Strengthened near-term actions in modelled cost-effective pathways that limit global warming to 2 ° C or lower, reduce the overall risk to the feasibility of the system transitions, compared to modelled pathways with delayed or uncoordinated action. ( high confidence )

WGII SPM C.2 WGII SPM C.3 WGII SPM C.5 WGIII SPM E.1 WGIII SPM E.1.3

.

4.2.i91In 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 CO2from power plants, or 50–80% of fugitive

4.2.j Figure 4.2: 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 knowledges 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 hence shape 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.

WGI SPM B.1 WGII SPM B.1-B.5 WGII SPM C.2-5 WGII SPM D.1-5 WGII Figure SPM.3 WGII Figure SPM.4 WGII Figure SPM.5 WGII TS.D.5 WGII Chapter 3.1 WGII Chapter 3.2 WGII Chapter 3.4 WGII Chapter 4.2 WGII Figure 4.4 WGII Chapter 4.5 WGII Chapter 4.6 WGII Chapter 4.9 WGIII SPM A WGIII SPM B1 WGIII SPM B.3 WGIII SPM B.6 WGIII SPM C.4 WGIII SPM D1-3 WGIII SPM E.1 WGIII SPM E.2 WGIII SPM E.4 WGIII SPM E.5 WGIII FigureTS.1 TS.7 Box TS. 3 Box TS.8 Cross-Working Group Box 1 WGIII Cross-Chapter Box 5 in Chapter 4 SR1.5 SPM D1-6 SRCCL SPM D.3

provide benefits ( high confidence). This encompasses three main directions: (a) economy-wide mainstreaming packages supporting options to improved sustainable low-emission economic recovery, development and job creation programs (Sections 4.4, 4.5, 4.6, 4.8, 4.9) (b) safety nets and social protection in the transition (Section 4.4, 4.7); and (c) broadened access to finance, technology and capacity-building and coordinated support to low-emission infrastructure (‘leap-frog’ potential), especially in developing regions, and under debt stress ( high confidence ). (Section 4.8)

WGII SPM C.2 WGII SPM C.4.1 WGII SPM D.1.3 WGII SPM D.2 WGII SPM D.3.2 WGII SPM E.2.2 WGII SPM E.4 WGII SPM TS.2 WGII SPM TS.5.2 WGII TS.6.4 WGII TS.15 WGII TS Box TS.3 WGIII SPM B.4.2 WGIII SPM C.5.4 WGIII SPM C.6.2 WGIII SPM C.12.2 WGIII SPM D.3.4 WGIII SPM E.4.2 WGIII SPM E.4.5 WGIII SPM E.5.2 WGIII SPM E.5.3 WGIII TS.1 WGIII Box TS.15 WGIII Chapter15.2 WGIII Cross-Chapter Box 1 on COVID in Chapter 1

4.3 Near-Term Risks

4.3.a Many changes in the climate system, including extreme events, will become larger in the near term with increasing global warming (high confidence). Multiple climatic and non-climatic risks will interact, resulting in increased compounding and cascading impacts becoming more difficult to manage (high confidence). Losses and damages will increase with increasing global warming (very high confidence), while strongly concentrated among the poorest vulnerable populations (high confidence). Continuing with current unsustainable development patterns would increase exposure and vulnerability of ecosystems and people to climate hazards (high confidence).

4.3.b Global warming will continue to increase in the near term (2021–2040) mainly due to increased cumulative CO2emissions in nearly all considered scenarios and pathways. 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). In the near-term, natural variability92will modulate human-caused changes, either attenuating or amplifying projected changes, especially at regional scales, with little effect on centennial global warming. Those modulations are important to consider in adaptation planning. Global surface temperature in any single year can vary above or below the long-term human-induced trend, due to natural variability. By 2030, global surface temperature in any individual year could exceed 1.5oC relative to 1850–1900 with a probability between 40% and 60%, across the five scenarios assessed in WGI (medium 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. If a large explosive volcanic eruption were to occur in the near-term93, it would temporarily and partially mask human-caused climate change by reducing global surface temperature and precipitation, especially over land, for one to three years ( medium confidence ).

WGI SPM B.1.3 WGI SPM B.1.4 WGI SPM C.1 WGI SPM C.2 WGI Cross-Section Box TS.1 WGI Cross-Chapter Box 4.1 WGII SPM B.3 WGII SPM B.3.1 WGIII Box SPM.1 Figure 1

.

4.3.c The level of risk for humans and ecosystems will depend on near-term trends in vulnerability, exposure, level of socio-economic development and adaptation (high confidence). In the near-term, many climate-associated risks to natural and human systems depend more strongly on changes in these systems’ vulnerability and exposure than on differences in climate hazards between emissions scenarios ( high confidence ). Future exposure to climatic hazards is increasing globally due to socio-economic development trends including growing inequality, and when urbanisation or migration increase exposure ( high confidence ). Urbanisation increases hot extremes ( very high confidence ) and precipitation runoff intensity ( high confidence ). Increasing urbanisation in low-lying and coastal zones will be a major driver of increasing exposure to extreme riverflow events and sea level rise hazards, increasing risks ( high confidence ) (Figure 4.3). Vulnerability will also rise rapidly in low-lying Small Island Developing States and atolls in the context of sea level rise ( high confidence ) (see Figure 3.4 and Figure 4.3). Human vulnerability will concentrate in informal settlements and rapidly growing smaller settlements; and vulnerability in rural areas will be heightened by reduced habitability and

4.3.d92See Annex I: Glossary. The main internal variability phenomena include El Niño–Southern Oscillation, Pacific Decadal Variability and Atlantic Multi-decadal Variability through their regional influence

WGI SPM footnote 37

. The internal variability of global surface temperature in any single year is estimated to be about ±0.25°C (5–95% range, high confidence) WGI SPM footnote 29

.93Based on 2500-year reconstructions, eruptions with a radiative forcing more negative than -1 Wm-2, related to the radiative effect of interdependent ( high confidence ). Vulnerability to climate change for ecosystems will be strongly influenced by past, present, and future patterns of human development, including from unsustainable consumption and production, increasing demographic pressures, and persistent unsustainable use and management of land, ocean, and water ( high confidence ). Several near-term risks can be moderated with adaptation ( high confidence ). (see Section 4.5 and 3.2)

WGI SPM C.2.6 WGII SPM B.2 WGII SPM B.2.3 WGII SPM B.2.5 WGII SPM B.3 WGII SPM B.3.2 WGII TS.C.5.2

4.3.e

Principal hazards and associated risks expected in the near-term (at 1.5°C global warming) are:

4.3.f

● Increased intensity and frequency of hot extremes and dangerous heat-humidity conditions, with increased human mortality, morbidity, and labour productivity loss ( high confidence )

WGI SPM B.2.2 WGI TS Figure TS.6 WGII SPM B.1.4 WGII SPM B.4.4 WGII SPM Figure SPM.2

.

4.3.g

● Increasing frequency of marine heatwaves will increase risks of biodiversity loss in the oceans, including from mass mortality events ( high confidence )

WGI SPM B.2.3 WGII SPM B.1.2 WGII SPM Figure SPM.2 SROCC SPM B.5.1

4.3.h

● Near-term risks for biodiversity loss are moderate to high in forest ecosystems ( medium confidence ) and kelp and seagrass ecosystems ( high to very high confidence ) and are high to very high in Arctic sea-ice and terrestrial ecosystems ( high confidence ) and warm-water coral reefs ( very high confidence )

WGII SPM B.3.1

.

4.3.i

● More intense and frequent extreme rainfall and associated flooding in many regions including coastal and other low-lying cities ( medium to high confidence ), and increased proportion of and peak wind speeds of intense tropical cyclones ( high confidence )

WGI SPM B.2.4 WGI SPM C.2.2 WGI SPM C.2.6 WGI Chapter 11.7

.

4.3.j

● High risks from dryland water scarcity, wildfire damage, and permafrost degradation ( medium confidence )

SRCCL SPM A.5.3.

.

4.3.k

● Continued sea level rise and increased frequency and magnitude of extreme sea level events encroaching on coastal human settlements and damaging coastal infrastructure ( high confidence) , committing low-lying coastal ecosystems to submergence and loss ( medium confidence ), expanding land salinization ( very high confidence ), with cascading to risks to livelihoods, health, well-being, cultural values, food and water security ( high confidence ) (Figure 3.4, 4.3).

WGI SPM C.2.5 WGI SPM C.2.6 WGII SPM B.3.1 WGII SPM B.5.2 SRCCL SPM A.5.6 SROCC SPM B.3.4 SROCC SPM 3.6 SROCC SPM B.9.1

.

●

Climate change will significantly increase ill health and premature deaths from the near- to long-term ( high confidence ). Further warming will increase climate-sensitive food-borne, water-borne, and vector-borne disease risks ( high confidence ), and mental health challenges including anxiety and stress ( very high confidence ).

WGII SPM B.4.4

4.3.l

● 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).

WGII TS C.4.2

4.3.m

● The projected increase in frequency and intensity of heavy precipitation (high confidence) will increase rain-generated local flooding (medium confidence).

WGI Figure SPM.6 WGI SPM B.2.2 WGII TS C.4.5

4.3.n Multiple climate change risks will increasingly compound and cascade in the near term (high confidence). Many regions are projected to experience an increase in the probability of compound events with higher global warming ( high confidence ) including concurrent heatwaves and drought. 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 ) (Figure 4.3). 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 ). Concurrent and cascading risks from climate change to food systems, human settlements, infrastructure and health will make these risks more severe and more difficult to manage, including when interacting with non-climatic risk drivers such as competition for land between urban expansion and food production, and pandemics ( 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 ). Increasing transboundary risks are projected supply-chains, markets, and natural resource flows ( high confidence ) and may interact with impacts from other crises such as pandemics. Risks also arise from some responses 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, such as afforestation of naturally unforested land or poorly implemented bioenergy compounding climate-related risks to biodiversity, food and water security, and livelihoods ( high confidence ). (see Section 3.4.1 and 4.5)

WGI SPM.2.7 WGII SPM B.2.1 WGII SPM B.5 WGII SPM B.5.1 WGII SPM B.5.2 WGII SPM B.5.3 WGII SPM B.5.4 WGII Cross-Chapter Box COVID in Chapter 7 WGIII SPM C.11.2 SRCCL SPM A.5 SRCCL SPM A.6.5

(Figure 4.3)

4.3.o With every increment of global warming losses and damages will increase (very high confidence), become increasingly difficult to avoid and be strongly concentrated among the poorest vulnerable populations (high confidence). Adaptation does not prevent all losses and damages, even with effective adaptation and before reaching soft and hard limits. Losses and damages will be unequally distributed across systems, regions and sectors and are not comprehensively addressed by current financial, governance and institutional arrangements, particularly in vulnerable developing countries. (high confidence). WGII SPM B.4 WGII SPM C.3 WGII SPM C.3.5

4.4 Equity and Inclusion in Climate Change Action

4.4.a Actions that prioritise equity, climate justice, social justice and inclusion lead to more sustainable outcomes, co-benefits, reduce trade-offs, support transformative change and advance climate resilient development. Adaptation responses are immediately needed to reduce rising climate risks, especially for the most vulnerable. Equity, inclusion and just transitions are key to progress on adaptation and deeper societal ambitions for accelerated mitigation. (high confidence)

4.4.b Adaptation and mitigation actions, across scales, sectors and regions, that prioritise equity, climate justice, rights-based approaches, social justice and inclusivity, lead to more sustainable outcomes, reduce trade-offs, support transformative change and advance climate resilient development (high confidence). 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.(SDGs), particularly education, hunger, poverty, gender and energy access ( high confidence ). Mitigation efforts embedded within the wider development context can increase the pace, depth and breadth of emission reductions ( medium confidence ). Equity, inclusion and just transitions at all scales enable deeper societal ambitions for accelerated mitigation, and climate action more broadly ( high confidence ). The complexity in risk of rising food prices, reduced household incomes, and health and climate-related malnutrition (particularly maternal malnutrition and child undernutrition) and mortality increases with little or low levels of adaptation ( high confidence ).

WGII SPM B.5.1 WGII SPM C.2.9 WGII SPM D.2.1 WGII TS Box TS.4 WGIII SPM D.3 WGIII SPM D.3.3 WGIII SPM WGIII SPM E.3 SR1.5 SPM D.4.5

(Figure 4.3c)

4.4.c Regions and people with considerable development constraints have high vulnerability to climatic hazards. Adaptation outcomes for the most vulnerable within and across countries and regions are enhanced through approaches focusing on equity, inclusivity, and rights-based approaches, including 3.3 to 3.6 billion people living in contexts that are highly vulnerable to climate change (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 ). Several risks can be moderated with adaptation (h igh confidence ) . The largest adaptation gaps exist among lower income population groups ( high confidence ) and adaptation progress is unevenly distributed with observed adaptation gaps ( 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 ). Vulnerability is exacerbated by inequity and marginalisation linked to gender, ethnicity, low income or combinations thereof, especially for many Indigenous Peoples and local communities ( high confidence ).

WGII SPM B.2 WGII SPM B.2.4 WGII SPM B.3.2 WGII SPM B.3.3 WGII SPM C.1 WGII SPM C.1.2 WGII SPM C.2.9

local knowledge, and scientific knowledge can help address adaptation gaps and avoid maladaptation ( high confidence) . Such actions with flexible pathways may encourage low-regret and timely actions ( very high confidence ). Integrating climate adaptation into social protection programmes, including cash transfers and public works programmes, would increase resilience to climate change, especially when supported by basic services and infrastructure ( high confidence ).

WGII SPM C.2.3 WGII SPM C.4.3 WGII SPM C.4.4 WGII SPM C.2.9 WGII WPM D.3

4.4.d Equity, inclusion, just transitions, broad and meaningful participation of all relevant actors in decision making at all scales enable deeper societal ambitions for accelerated mitigation, and climate action more broadly, and build social trust, support transformative changes and an equitable sharing of benefits and burdens (high confidence). 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, including shifting of income and employment during the transition from high to low emissions activities ( high confidence ). While some jobs may be lost, low-emissions development can also open up opportunities to enhance skills and create jobs ( high confidence ). Broadening equitable access to finance, technologies and governance that facilitate mitigation, and consideration of climate justice can help equitable sharing of benefits and burdens, especially for vulnerable countries and communities.

WGIII SPM D.3 WGIII SPM D.3.2 WGIII SPM D.3.3 WGIII SPM D.3.4 WGIII TS Box TS.4

4.4.e Development priorities among countries also reflect different starting points and contexts, and enabling conditions for shifting development pathways towards increased sustainability will therefore differ, giving rise to different needs (high confidence) . Implementing just transition principles through collective and participatory decision-making processes is an effective way of integrating equity principles into policies at all scales depending on national circumstances, while in several countries just transition commissions, task forces and national policies have been established ( medium confidence ).

WGIII SPM D.3.1 WGIII SPM D.3.3

4.4.f Many economic and regulatory instruments have been effective in reducing emissions and practical experience has informed instrument design to improve them while addressing distributional goals and social acceptance (high confidence). The design of behavioural interventions, including the way that choices are presented to consumers work synergistically with price signals, making the combination more effective ( medium confidence ). 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 ). There are options on design of instruments such as taxes, subsidies, prices, and consumption-based approaches, complemented by regulatory instruments to reduce high-emissions consumption while improving equity and societal well-being ( high confidence ). Behaviour and lifestyle changes to help end-users adopt low-GHG-intensive options can be supported by policies, infrastructure and technology with multiple co-benefits for societal well-being ( high confidence ). Broadening equitable access to domestic and international finance, technologies and capacity can also act as a catalyst for accelerating mitigation and shifting development pathways in low-income contexts ( high confidence ). Eradicating extreme poverty, energy poverty, and providing decent living standards 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 ). 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 ( high confidence ). 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 )

WGII D.2.1 WGIII SPM B.3.3 WGIII SPM.C.8.5 WGIII SPM C.10.2 WGIII SPM C.10.4 WGIII SPM D.3.4 WGIII SPM E.4.2 WGIII TS.5.1 WGIII Chapter 5.4 WGIII Chapter 5.8 WGIII Chapter 15.2

4.4.g 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)

4.4.h Rapid and far-reaching transitions across all sectors and systems are necessary to achieve deep emissions reductions and secure a liveable and sustainable future for all (high confidence). System transitions94consistent with pathways that limit warming to 1.5°C (>50%) with no or limited overshoot are more rapid and pronounced in the near-term than in those that limit warming to 2°C (>67%) ( high confidence ). Such a systemic change is unprecedented in terms of scale, but not necessarily in terms of speed ( medium confidence ). The system transitions make possible the transformative adaptation required for high levels of human health and well-being, economic and social resilience, ecosystem health, and planetary health.

WGII SPM A WGII SPM Figure SPM.1 WGIII SPM C.3 SR1.5 SPM C.2 SR1.5 SPM C.2.1 SR1.5 SPM C.2 SR1.5 SPM C.5

4.4.i Feasible, effective and low-cost options for mitigation and adaptation are already available (high confidence) (Figure 4.4). Mitigation options costing USD100 per tCO2-eq or less could reduce global GHG emissions by at least half the 2019 level by 2030 (options costing less than USD20 tCO2-eq–1are estimated to make up more than half of this potential) ( high confidence ) (Figure 4.4). The availability, feasibility95and potential of mitigation or effectiveness of adaptation options in the near-term differ across systems and regions ( very high confidence ).

WGII SPM C.2 WGIII SPM C.12 WGIII SPM E.1.1 SR1.5 SPM B.6

4.4.j 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 encompasses changes in infrastructure use, end-use technology adoption, and socio-cultural and behavioural change. ( high confidence ) (Figure 4.4)

WGIII SPM C.10

4.4.l

4.5.1 Energy Systems

4.5.1.a Rapid and deep reductions in GHG emissions require major energy system transitions (high confidence). Adaptation options can help reduce climate-related risks to the energy system (very high confidence). Net zero CO2energy systems entail: a substantial reduction in overall fossil fuel use, minimal use of unabated fossil fuels96, and use of Carbon Capture and Storage in the remaining fossil fuel systems;

4.5.1.b96In 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 CO2from power plants, or 50–80% of fugitive less amenable to electrification; energy conservation and efficiency; and greater integration across the energy system ( high confidence ). Large contributions to emissions reductions can come from options costing less than USD20 tCO2-eq–1, including solar and wind energy, energy efficiency improvements, and CH4(methane) emissions reductions (from coal mining, oil and gas, and waste) ( medium confidence ).97Many of these response options are technically viable and are supported by the public ( high confidence ). Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than transitioning to low emission systems ( high confidence )

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.

4.5.1.c

Climate change and related extreme events will affect future energy systems, including hydropower production, bioenergy yields, thermal power plant efficiencies, and demands for heating and cooling ( high confidence ). The most feasible energy system adaptation options support infrastructure resilience, reliable power systems and efficient water use for existing and new energy generation systems ( very 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 ). Energy generation diversification (e.g., wind, solar, small-scale hydroelectric) and demand side management (e.g., storage and energy efficiency improvements) can increase energy reliability and reduce vulnerabilities to climate change, especially in rural populations ( 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 medium- to long-term, with mitigation co-benefits ( very high confidence ).

WGII SPM B.5.3 WGII SPM C.2.10 WGIII TS.5.1

4.4.m

4.5.2 Industry

4.5.2.a There are several options to reduce industrial emissions that differ by type of industry; many industries are disrupted by climate change, especially from extreme events (high confidence). 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 ( high confidence ). Light industry and manufacturing can be largely decarbonized through available abatement technologies (e.g., material efficiency, circularity), electrification (e.g., electrothermal heating, heat pumps), and switching to low- and zero-GHG emitting fuels (e.g., hydrogen, ammonia, and bio-based and other synthetic fuels) ( high confidence ), while deep reduction of cement process emissions will rely on cementitious material substitution and the availability of Carbon Capture and Storage (CCS) until new chemistries are mastered ( high confidence ). 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 Utilisation (CCU), direct air CO2capture, as well as CCS ( high confidence ). Action to reduce industry sector emissions may change the location of GHG-intensive industries and the organisation of value chains, with distributional effects on employment and economic structure ( medium confidence ).

WGII TS.B.9.1 WGII Chapter 16.5.2 WGIII SPM C.5 WGIII SPM C.5.2 WGIII SPM C.5.3 WGIII TS.5.5

4.5.2.b

Many industrial and service sectors are negatively affected by climate change through supply and operational disruptions, especially from extreme events ( high confidence ), and will require adaptation efforts. Water intensive industries (e.g., mining) can undertake measures to reduce water stress, such as water recycling and reuse, using brackish or saline sources, working to improve water use efficiency. However, residual risks will remain, especially at higher levels of warming ( medium confidence ). (Section 3.2)

WGII TS.B.9.1 WGII Chapter 16.5.2 WGII Chapter 4.6.3

4.5.2.c97The mitigation potentials and mitigation costs of individual technologies in a specific context or region may differ greatly from the

4.5.2.d Urban systems are critical for achieving deep emissions reductions and advancing climate resilient development, particularly when this involves integrated planning that incorporates physical, natural and social infrastructure (high confidence). Deep emissions reductions and integrated adaptation actions are advanced by: integrated, inclusive land use planning and decision-making; compact urban form by co-locating jobs and housing; reducing or changing urban energy and material consumption; electrification in combination with low emissions sources; improved water and waste management infrastructure; and enhancing carbon uptake and storage in the urban environment (e.g. bio-based building materials, permeable surfaces and urban green and blue infrastructure). Cities can achieve net-zero emissions if emissions are reduced within and outside of their administrative boundaries through supply chains, creating beneficial cascading effects across other sectors. ( high confidence ).

WGII SPM C.5.6 WGII SPM D.1.3 WGII SPM D.3 WGIII SPM C.6 WGIII SPM C.6.2 WGIII TS 5.4 SR1.5 SPM C.2.4

4.5.2.e

Considering climate change impacts and risks (e.g., through climate services) in the design and planning of urban and rural settlements and infrastructure is critical for resilience and enhancing human well-being. Effective mitigation can be advanced at each of the design, construction, retrofit, use and disposal stages for buildings. Mitigation interventions for buildings include: at the construction phase, low-emission construction materials, highly efficient building envelope and the integration of renewable energy solutions; 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. Sufficiency98measures can limit the demand for energy and materials over the lifecycle of buildings and appliances. ( high confidence )

WGII SPM C.2.5 WGIII SPM C.7.2

.

4.5.2.f

Transport-related GHG emissions can be reduced by demand-side options and low-GHG emissions technologies. Changes in urban form, reallocation of street space for cycling and walking, digitalisation (e.g., teleworking) and programs that encourage changes in consumer behaviour (e.g. transport, pricing) can reduce demand for transport services and support the shift to more energy efficient transport modes ( high confidence ). Electric vehicles powered by low-emissions electricity offer the largest decarbonisation potential for land-based transport, on a life cycle basis (high confidence ). Costs of electrified vehicles are decreasing and their adoption is accelerating, but they require continued investments in supporting infrastructure to increase scale of deployment ( high 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 ). Advances in battery technologies could facilitate the electrification of heavy-duty trucks and compliment conventional electric rail systems ( medium 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 CO2emissions from shipping, aviation, and heavy-duty land transport but require production process improvements and cost reductions ( medium 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 )

WGII SPM B.2.5 WGIII SPM C.6.2 WGIII SPM C.8 WGIII SPM C.8.1 WGIII SPM C.8.2 WGIII SPM C.10.2 WGIII SPM C.10.3 WGIII SPM C.10.4

.

4.5.2.g

Green/natural and blue infrastructure such as urban forestry, green roofs, ponds and lakes, and river restoration can mitigate climate change through carbon uptake and storage, avoided emissions, and reduced energy use while reducing risk from extreme events such as heatwaves, heavy precipitation and droughts, and advancing co-benefits for health, wellbeing and livelihoods ( medium confidence ). Urban greening can provide local cooling ( very high confidence ). Combining green/natural and grey/physical infrastructure adaptation responses has potential to reduce adaptation costs and contribute to flood control, sanitation, water resources management, landslide prevention and coastal protection ( medium confidence ). Globally, more financing is directed at grey/physical infrastructure than green/natural infrastructure and social infrastructure ( medium confidence ), and there is limited evidence of investment in informal settlements ( medium to high confidence ). The greatest gains in well-being in urban areas can be achieved by prioritising finance to reduce climate risk

4.5.2.h98A set of measures and daily practices that avoid demand for energy, materials, land and water while delivering human well-being confidence

).

WGII SPM C.2.5 WGII SPM C.2.6 WGII SPM C.2.7 WGII SPM D.3.2 WGII TS.E.1.4 WGII Cross-Chapter Box FEAS WGIII SPM C.6 WGIII SPM C.6.2 WGIII SPM D.1.3 WGIII SPM D.2.1

4.5.2.i

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. 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 )

WGII SPM C.2.8

4.4.n

4.5.4 Land, Ocean, Food, and Water

4.5.4.a There is substantial mitigation and adaptation potential from options in agriculture, forestry and other land use, and in the oceans, that could be upscaled in the near term across most regions (high confidence) (Figure 4.5). 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 required integrated approaches to meet multiple objectives including food security. Demand-side measures (shifting to sustainable healthy diets and reducing food loss/waste) and sustainable agricultural intensification can reduce ecosystem conversion and CH4and N2O emissions, and free up land for reforestation and ecosystem restoration. Sustainably sourced agriculture 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. The effectiveness of ecosystem-based adaptation and most water-related adaptation options declines with increasing warming (see 3.2). ( high confidence ).

WGII SPM C.2.1 WGII SPM C.2.2 WGII SPM C.2.5 WGIII SPM C.9.1 SRCCL SPM B.1.1 SRCCL SPM B.5.4 SRCCL SPM D.1 SROCC SPM C

4.5.4.b

Some options, such as conservation of high-carbon ecosystems (e.g., peatlands, wetlands, rangelands, mangroves and forests), have immediate impacts while others, such as restoration of high-carbon ecosystems, reclamation of degraded soils or afforestation, take decades to deliver measurable results ( high confidence ). Many sustainable land management technologies and practices are financially profitable in three to ten years ( medium confidence ).

SRCCL SPM B.1.2 SRCCL SPM D.2.2

4.5.4.c Maintaining the resilience of biodiversity and ecosystem services at a global scale depends on effective and equitable conservation of approximately 30–50% of Earth’s land, freshwater and ocean areas, including currently near-natural ecosystems (high confidence) . The services and options provided by terrestrial, freshwater, coastal and ocean 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 ).

WGII SPM C.2.4 WGII SPM D.4 SROCC SPM C.2

4.5.4.d

Large-scale land conversion for bioenergy, biochar, or afforestation can increase risks to biodiversity, water and food security. In contrast, restoring natural forests and drained peatlands, and improving sustainability of managed forests enhances the resilience of carbon stocks and sinks and reduces ecosystem vulnerability to climate change. 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 adaptation across forests and other ecosystems. ( high confidence ).

WGII SPM B.5.4 WGII SPM C.2.3 WGII SPM C.2.4 WGIII SPM D.2.3 SRCCL B.7.3 SRCCL SPM C.4.3 SRCCL TS.7

4.5.4.e

Natural rivers, wetlands and upstream forests reduce flood risk in most circumstances ( high 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 ). For inland flooding, combinations of non-structural measures like early warning systems and structural measures like levees have reduced loss of lives ( medium confidence ), but hard defences against flooding or sea level rise can also be maladaptive ( high confidence ).

WGII SPM C.2.1 WGII SPM C.4.1 WGII SPM C.4.2 WGII SPM C.2.5

4.5.4.f

Protection and restoration of coastal ‘blue carbon’ ecosystems (e.g., mangroves, tidal marshes and seagrass meadows) could reduce emissions and/or increase carbon uptake and storage ( medium confidence ). Coastal wetlands protect against coastal erosion and flooding ( very high confidence ). 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 ). Ecosystem-based management in fisheries and aquaculture supports food security, biodiversity, human health and well-being ( high confidence ).

WGII SPM C.2.2 WGII SPM C.2 SROCC SPM C2.3 SROCC SPM C.2.4

4.4.o

4.5.5 Health and Nutrition

4.5.5.a Human health will benefit from integrated mitigation and adaptation options that mainstream health into food, infrastructure, social protection, and water policies (very high confidence) . Balanced and sustainable healthy diets99and reduced food loss and waste present important opportunities for adaptation and mitigation while generating significant co-benefits in terms of biodiversity and human health ( high confidence ). 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 food waste, reduce healthcare costs, contribute to lower GHG emissions and enhance adaptive capacity ( high confidence ). Improved access to clean energy sources and technologies, and shifts to active mobility (e.g., walking and cycling) and public transport can deliver socioeconomic, air quality and health benefits, especially for women and children ( high confidence ).

WGII SPM C.2.2 WGII SPM C.2.11 WGII Cross-Chapter Box HEALTH WGIII SPM C.2.2 WGIII SPM C.4.2 WGIII SPM C.9.1 WGIII SPM C.10.4 WGIII SPM D.1.3 WGIII SPM Figure SPM6 WGIII SPM Figure SPM.8 SRCCL SPM B.6.2 SRCCL SPM B.6.3 SRCCL B.4.6 SRCCL SPM C.2.4

4.5.5.b Effective adaptation options exist to help protect human health and wellbeing (high confidence). Health Action Plans that include early warning and response systems are effective for extreme heat ( high confidence ). Effective 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 and access to mental health care, and monitoring of psychosocial impacts from extreme weather events ( high confidence ). A key pathway to climate resilience in the health sector is universal access to healthcare ( high confidence )

WGII SPM C.2.11 WGII Chapter 7.4.6

4.4.p

4.5.6 Society, Livelihoods, and Economies

4.5.6.a Enhancing knowledge on risks and available adaptation options promotes societal responses, and behaviour and lifestyle changes supported by policies, infrastructure and technology can help reduce global GHG emissions (high confidence) . Climate literacy and information provided through climate services and community approaches, including those that are informed by Indigenous Knowledge and local knowledge, can accelerate behavioural changes and planning ( high confidence ). Educational and information programmes, using the arts, participatory modelling and citizen science can facilitate awareness, heighten risk perception, and influence behaviours ( high confidence ). The way choices are presented can enable adoption of low GHG intensive socio-cultural options, such as shifts to balanced, sustainable healthy diets, reduced food waste, and active mobility ( high confidence ). Judicious labelling, framing, and communication of social norms can increase the effect of mandates, subsidies, or taxes ( medium confidence )

WGII SPM C.5.3 WGII TS.D.10.1 WGIII SPM C.10 WGIII SPM C.10.2 WGIII SPM C.10.3 WGIII SPM E.2.2 WGIII Figure SPM.6 WGIII TS.6.1 5.4 SR1.5 SPM D.5.6 SROCC SPM C.4

.

4.5.6.b99Balanced diets refer to diets that feature plant-based foods, such as those based on coarse grains, legumes, fruits and vegetables, nuts services and risk spreading and sharing approaches, have broad applicability across sectors and provide greater risk reduction benefits when combined ( high confidence) . Climate services that are demand-driven and inclusive of different users and providers can improve agricultural practices, inform better water use and efficiency, and enable resilient infrastructure planning ( high confidence ). Policy mixes that include weather and health insurance, social protection and adaptive 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 ( high confidence )

.

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 ( high confidence ). Social safety nets can build adaptive capacities, reduce socioeconomic vulnerability, and reduce risk linked to hazards ( robust evidence, medium agreement ).

WGII SPM C.2.9 WGII SPM C.2.13 WGII Cross-Chapter Box FEASIB in Chapter 18 SRCCL SPM C.1.4 SRCCL SPM D.1.2

.

4.5.6.c Reducing future risks of involuntary migration and displacement due to climate change is possible through cooperative, international efforts to enhance institutional adaptive capacity and sustainable development ( high confidence ). Increasing adaptive capacity minimises risk associated with involuntary migration and immobility and improves the degree of choice under which migration decisions are made, while policy interventions can remove barriers and expand the alternatives for safe, orderly and regular migration that allows vulnerable people to adapt to climate change ( high confidence ).

WGII SPM C.2.12 WGII TS.D.8.6 WGII Cross-Chapter Box MIGRATE in Chapter 7

4.5.6.d Accelerating commitment and follow-through by the private sector is promoted for instance by building business cases for adaptation, accountability and transparency mechanisms, and monitoring and evaluation of adaptation progress (medium confidence) . Integrated pathways for managing climate risks will be most suitable when so-called ‘low-regret’ anticipatory options are established jointly across sectors in a timely manner and are feasible and effective in their local context, and when path dependencies and maladaptations across sectors are avoided ( 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 ).

WGII SPM C.5.1 WGII SPM C.5.2 WGII TS.D.10.4

4.6 Co-Benefits of Adaptation and Mitigation for Sustainable Development Goals

4.6.a Mitigation and adaptation actions have more synergies than trade-offs with Sustainable Development Goals (SDGs). Synergies and trade-offs depend on context and scale of implementation. Potential trade-offs can be compensated or avoided with additional policies, investments and financial partnerships. (high confidence)

4.6.b Many mitigation and adaptation actions have multiple synergies with Sustainable Development Goals (SDGs), but some actions can also have trade-offs. Potential synergies with SDGs exceed potential trade- offs . Synergies and trade-offs are context specific and depend on: means and scale of implementation, intra- and inter-sectoral interactions, cooperation between countries and regions, the sequencing, timing and stringency of actions, governance, and policy design. Eradicating extreme poverty, energy poverty, and providing decent living standards to all, consistent with near-term sustainable development objectives, can be achieved without significant global emissions growth. ( high confidence ) (Figure 4.5)

WGII SPM C.2.3 WGII SPM Figure SPM.4b WGIII SPM B.3.3 WGIII SPM C.9.2 WGIII SPM D.1.2 WGIII SPM D.1.4 WGIII SPM Figure SPM.8

4.6.c Several mitigation and adaptation options can harness near-term synergies and reduce trade-offs to advance sustainable development in energy, urban and land systems (Figure 4.5) (high confidence) . Clean energy supply systems have multiple co-benefits, including improvements in air quality and health. Heat Health Action Plans that include early warning and response systems, approaches that mainstream health into synergies between multiple Sustainable Development Goals and sustainable land use and urban planning with more green spaces, reduced air pollution, and demand-side mitigation including shifts to balanced, sustainable healthy diets. Electrification combined with low-GHG energy, and shifts to public transport can enhance health, employment, and can contribute to energy security and deliver equity. Conservation, protection and restoration of terrestrial, freshwater, coastal and ocean ecosystems, together with targeted management to adapt to unavoidable impacts of climate change can generate multiple additional benefits, such as agricultural productivity, food security, and biodiversity conservation. ( high confidence ).

WGII SPM C.1.1 WGII C.2.4 WGII SPM D.1 WGII SPM Figure SPM.4 WGII Cross-Chapter Box HEALTH in Chapter 17 WGII Cross-Chapter Box FEASIB in Chapter 18 WGIII SPM C.4.2 WGIII SPM D.1.3 WGIII SPM D.2 WGIII SPM Figure SPM.8 SRCCL SPM B.4.6

4.6.d When implementing mitigation and adaptation together, and taking trade-offs into account, multiple co-benefits and synergies for human well-being as well as ecosystem and planetary health can be realised (high confidence) . There is a strong link between sustainable development, vulnerability and climate risks. 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.Land restoration contributes to mitigation and adaptation with synergies via enhanced ecosystem services and with economically positive returns and co-benefits for poverty reduction and improved livelihoods.Trade-offs can be evaluated and minimised by giving emphasis to capacity building, finance, technology transfer, investments; governance, development, context specific gender-based and other social equity considerations with meaningful participation of Indigenous Peoples, local communities and vulnerable populations. ( high confidence ).

WGII SPM C.2.9 WGII SPM C.5.6 WGII SPM D.5.2 WGII Cross-Chapter Box on Gender in Chapter 18 WGIII SPM C.9.2 WGIII SPM D.1.2 WGIII SPM D.1.4 WGIII SPM D.2 SRCCL SPM D.2.2 SRCCL TS.4

4.6.e Context relevant design and implementation requires considering people’s needs, biodiversity, and other sustainable development dimensions (very high 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, or political circumstances, resource endowment, capabilities, international environment, and prior development. n regions with high dependency on fossil fuels for, among other things, revenue and employment generation, mitigating risks for sustainable development requires policies that promote economic and energy sector diversification and considerations of just transitions principles, processes and practices ( high confidence ). For individuals and households in low-lying coastal areas, in Small Islands, and smallholder farmers transitioning from incremental to transformational adaptation can help overcome soft adaptation limits ( high confidence ). Effective governance is needed to limit trade-offs of some mitigation options such as large scale afforestation and bioenergy options due to risks from their deployment for food systems, biodiversity, other ecosystem functions and services, and livelihoods ( high confidence ). Effective governance requires adequate institutional capacity at all levels ( high confidence )

WGII SPM B.5.4 WGII SPM C.3.1 WGII SPM C.3.4 WGIII SPM D.1.3 WGIII SPM E.4.2 SR1.5 SPM C.3.4 SR1.5 SPM C.3.5 SR1.5 SPM Figure SPM.4 SR1.5 SPM D.4.3 SR1.5 SPM D.4.4

4.7 Governance and Policy for Near-Term Climate Change Action

4.7.a Effective climate action requires political commitment, well-aligned multi-level governance and institutional frameworks, laws, policies and strategies. It needs clear goals, adequate finance and financing tools, coordination across multiple policy domains, and inclusive governance processes. Many mitigation and adaptation policy instruments have been deployed successfully, and could support deep emissions reductions and climate resilience if scaled up and applied widely, depending on national circumstances. Adaptation and mitigation action benefits from drawing on diverse knowledge. (high confidence)

4.7.b Effective climate governance enables mitigation and adaptation by providing overall direction based on national circumstances, setting targets and priorities, mainstreaming climate action across policy domains and levels, based on national circumstances and in the context of international cooperation. Effective governance enhances monitoring and evaluation and regulatory certainty, prioritising inclusive, transparent and equitable decision-making, and improves access to finance and technology (high confidence) . These functions can be promoted by climate-relevant laws and plans, which are growing in number across sectors and regions, advancing mitigation outcomes and adaptation benefits ( high confidence ). Climate laws have been growing in number and have helped deliver mitigation and adaptation outcomes ( medium confidence ).

WGII SPM C.5 WGII SPM C.5.1 WGII SPM C5.4 WGII SPM C.5.6 WGIII SPM B.5.2 WGIII SPM E.3.1

4.7.c Effective municipal, national and sub-national climate institutions, such as expert and co-ordinating bodies, enable co-produced, multi-scale decision-processes, build consensus for action among diverse interests, and inform strategy settings (high confidence). This requires adequate institutional capacity at all levels ( high confidence ). 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 based on gender, ethnicity, disability, age, location and income ( high confidence ). Policy support is influenced by Indigenous Peoples, businesses, and actors in civil society, including, youth, labour, media, and local communities, and effectiveness is enhanced by partnerships between many different groups in society ( high confidence ).Climate-related litigation 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

4.7.d

WGII SPM C.5.5, WGII SPM C.5.6, WGII SPM D.3.1; WGIII SPM E3.2, WGIII SPM E.3.3}

4.7.e Effective climate governance is enabled by inclusive decision processes, allocation of appropriate resources, and institutional review, monitoring and evaluation (high confidence). Multi-level, hybrid and cross-sector governance facilitates appropriate consideration for co-benefits and trade-offs, particularly in land sectors where decision processes range from farm level to national scale ( high confidence ). Consideration of climate justice can help to facilitate shifting development pathways towards sustainability.

WGII SPM C.5.5 WGII SPM C.5.6 WGII SPM D.1.1 WGII SPM D.2 WGII SPM D.3.2 SRCCL SPM C.3 SRCCL TS.1

4.7.f Drawing on diverse knowledge and partnerships, including with women, youth, Indigenous Peoples, local communities, and ethnic minorities can facilitate climate resilient development and has allowed locally appropriate and socially acceptable solutions (high confidence) .

WGII SPM D.2 D.2.1

4.7.g Many regulatory and economic instruments have already been deployed successfully. These instruments could support deep emissions reductions if scaled up and applied more widely. Practical experience has informed instrument design and helped to improve predictability, environmental effectiveness, economic efficiency, and equity. ( high confidence )

WGII SPM E.4 WGIII SPM E.4.2

.

4.7.h Scaling up and enhancing the use of regulatory instruments, consistent with national circumstances, can improve mitigation outcomes in sectoral applications (high confidence), and regulatory instruments that include flexibility mechanisms can reduce costs of cutting emissions (medium confidence). WGII SPM C.5.4 WGIII SPM E.4.1

4.7.i

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). Revenue from carbon taxes or emissions trading can be used for equity and distributional goals, for example to support low-income households, among other approaches ( high confidence ). There is no consistent evidence that current emission trading systems have led to significant emissions leakage ( medium confidence ).

WGIII SPM E4.2 WGIII SPM E.4.6

4.7.j Removing fossil fuel subsidies would reduce emissions, improve public revenue and macroeconomic performance, and yield other environmental and sustainable development 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 re-distributing revenue saved, and depend on national circumstances (high confidence). Fossil fuel subsidy removal is projected by various studies to reduce global CO2emissions by 1–4%, and GHG emissions by up to 10% by 2030, varying across regions ( medium confidence ).

WGIII SPM E.4.2

4.7.k National policies to support technology development, and participation in international markets for emission reduction, can bring positive spillover effects for other countries (medium confidence) , although reduced demand for fossil fuels as a result of climate policy could result in costs to exporting countries ( high confidence ). Economy-wide packages can meet short-term economic goals while reducing emissions and shifting development pathways towards sustainability ( medium confidence ). Examples are public spending commitments; pricing reforms; and investment in education and training, R&D and infrastructure ( high confidence ).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( high confidence ) . WGIII SPM E4.4 WGIII SPM 4.5 WGIII SPM 4.6

4.7.l Finance, international cooperation and technology are critical enablers for accelerated climate action. If climate goals are to be achieved, both adaptation and mitigation financing would have 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. Barriers include institutional, regulatory and market access barriers, are reduced and address the needs and opportunities, economic vulnerability and indebtedness in many developing countries. Enhancing international cooperation is possible through multiple channels. Enhancing technology innovation systems is key to accelerate the widespread adoption of technologies and practices. (high confidence)

4.7.m

4.8.1 Finance for Mitigation and Adaptation Actions

4.8.1.a Improved availability and access to finance100will 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 mitigation and shifting development pathways (high confidence) . Climate resilient development is enabled by increased international cooperation including improved access to financial resources, particularly for vulnerable regions, sectors and groups, and inclusive governance and coordinated policies (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 ). {WGII SPM C.1.2, WGII SPM C.3.2, WGII SPM C.5, WGII SPM C.5.4,

WGII SPM

D.2, WGII SPM D.3.2, WGII SPM D.5, WGII SPM D.5.2; WGIII SPM B.4.2,WGIII SPM B.5, WGIII SPM B.5.4, WGIII SPM C.4.2, WGIII SPM C.7.3, WGIII SPM C.8.5, WGIII SPM D.1.2, WGIII SPM D.2.4, WGIII SPM D.3.4, WGIII SPM E.2.3, WGIII SPM E.3.1, WGIII SPM E.5, WGIII SPM E.5.1, WGIII SPM E.5.2, WGIII SPM E.5.3, WGIII SPM E.5.4, WGIII SPM E.6.2}

4.8.1.b Both adaptation and mitigation finance need to increase many-fold, to address rising climate risks and to accelerate investments in emissions reduction (high confidence). Increased finance would address soft limits to adaptation and rising climate risks while also averting some related losses and damages, particularly in vulnerable developing countries ( high confidence ). Enhanced mobilisation of and access to finance, together with building capacity, are essential for implementation of adaptation actions and to reduce adaptation gaps given rising risks and costs, especially for the most 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 ). Adaptation funding predominately comes from public sources, and public mechanisms and finance can leverage private sector finance by addressing real and perceived regulatory, cost and market barriers, for instance 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 ). 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 levels, 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 large need for financial, technical, and human resources for adaptation (high confidence) (Section 2.3.2, 2.3.3, 4.4, Figure 4.6)

WGII SPM C.1.2 WGII SPM C2.11 WGII SPM C.3 WGII SPM C.3.2 WGII SPM C3.5 WGII SPM C.5 WGII SPM C.5.4 WGII SPM D.1 WGII SPM D.1.1 WGII SPM D.1.2 WGII SPM C.5.4 WGIII SPM D.2.4 WGIII SPM E.5 WGIII SPM E.5.1 WGIII Chapter 15.2

4.8.1.c 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 many

4.8.1.d100Finance can originate from diverse sources, singly or in combination: public or private, local, national or international, bilateral or multilateral, and alternative sources (e.g., philanthropic, carbon offsets). It can be in the form of grants, technical assistance, loans climate-related risks and investment opportunities within the financial system, reducing sectoral and regional mismatches between available capital and investment needs, improving the risk-return profiles of climate investments, and developing institutional capacities and local capital markets. Macroeconomic barriers include, amongst others, indebtedness and economic vulnerability of developing regions. ( high confidence ). { WGII SPM C.5.4; WGIII SPM E.4.2, WGIII SPM E.5, WGIII SPM E.5.2, WGIII SPM E.5.3}

4.8.1.e Scaling up financial flows requires clear signalling from governments and the international community. 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. This includes a stronger alignment of public finance, lowering real and perceived regulatory, cost and market barriers, and higher levels of public finance to lower the risks associated with low-emission investments. Up-front risks deter economically sound low carbon projects, and developing local capital markets are an option. Investors, financial intermediaries, central banks and financial regulators can shift the systemic underpricing of climate-related risks. A robust labelling of bonds and transparency is needed to attract savers.( high confidence ).

WGII SPM C.5.4 WGIII SPM B.5.4 WGIII SPM E.4 WGIII SPM E.5.4 WGIII Section 15.2 15.6.1 15.6.2 15.6.7

4.8.1.g The largest climate finance gaps and opportunities are in developing countries (high confidence). Accelerated support from developed countries and multilateral institutions is a critical enabler to enhance mitigation and adaptation action and can address inequities in finance, including its costs, terms and conditions, and economic vulnerability to climate change. Scaled-up public grants for mitigation and adaptation funding for vulnerable regions, e.g., 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 and adaptation 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 USD 100 billion-a-year goal of the Paris Agreement; increase the 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 long term through increased flows of financing over this decade can accelerate climate action, including in developing regions facing high debt costs, debt distress and macroeconomic uncertainty. ( high confidence )

WGII SPM C.5.2 WGII SPM C.5.4 WGII SPM C.6.5 WGII SPM D.2 WGII TS.D.10.2 WGIII SPM E.5 WGIII SPM E.5.3 WGIII TS.6.4 WGIII Box TS.1 WGIII Chapter 15.2 WGIII Chapter 15.6

4.7.n

4.8.2 International Cooperation and Coordination

4.8.2.a International cooperation is a critical enabler for achieving ambitious climate change mitigation goals 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 ). While agreed processes and goals, such as those in the UNFCCC, Kyoto Protocol and Paris Agreement, are helping (Section 2.2.1), international financial, technology and capacity building support to developing countries will enable greater implementation and more ambitious actions ( medium confidence ). By integrating equity and climate justice, national and international policies can help to facilitate shifting development pathways towards sustainability, especially by mobilising and enhancing access to finance for vulnerable regions, sectors and communities ( high confidence ). International cooperation and coordination, including combined policy packages, may be particularly important for sustainability transitions in emissions-intensive and highly traded basic materials industries that are exposed to international competition ( high confidence ). The large majority of emission modelling studies assume significant international cooperation to secure financial flows and address inequality and poverty issues in pathways limiting global warming. 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 cooperation ( high confidence ). Delayed global cooperation increases policy costs across regions ( high confidence ).

WGII SPM D.2 WGII SPM D.3.1 WGII SPM D.5.2 WGIII SPM D.3.4 WGIII SPM C5.4 WGIII SPM C.12.2 WGIII SPM E.6 WGIII SPM E.6.1 WGIII E.5.4 WGIII TS.4.2 WGIII TS.6.2 SR1.5 SPM D.6.3 SR1.5 SPM D.7 SR1.5 SPM D.7.3

. resource flows in food, fisheries, energy and water, and potential for conflict) increases the need for climate-informed transboundary management, cooperation, responses and solutions through multi- national or regional governance processes ( high confidence) . Multilateral governance efforts can help reconcile contested interests, world views and values about how to address climate change. International environment and sectoral agreements, and initiatives in some cases, may help to stimulate low GHG investment and reduce emissions (such as ozone depletion, transboundary air pollution and atmospheric emissions of mercury). Improvements to national and international governance structures would further enable the decarbonisation of shipping and aviation through deployment of low-emissions fuels, for example through stricter efficiency and carbon intensity standards. Transnational partnerships can also stimulate policy development, low-emissions technology diffusion, emission reductions and adaptation, 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, though uncertainties remain over their costs, feasibility, and effectiveness. 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. ( medium confidence )

WGII SPM B.5.3 WGII SPM C.5.6 WGII TS.E.5.4 WGII TS.E.5.5 WGIII SPM C.8.4 WGIII SPM E.6.3 WGIII SPM E.6.4 WGIII SPM E.6.4 WGIII TS.5.3

4.7.o

4.8.3 Technology Innovation, Adoption, Diffusion and Transfer

4.8.3.a Enhancing technology innovation systems can provide opportunities to lower emissions growth and create social and environmental co-benefits. Policy packages tailored to national contexts and technological characteristics have been effective in supporting low-emission innovation and technology diffusion. Support for successful low-carbon technological innovation includes public policies such as training and R&D, complemented by regulatory and market-based instruments that create incentives and market opportunities such as appliance performance standards and building codes. ( high confidence )

WGIII SPM B.4 WGIII SPM B.4.4 WGIII SPM E.4.3 WGIII SPM E4.4

.

4.8.3.b International cooperation on innovation systems and 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 and align these with other development objectives (high confidence) . Choice architecture can help end-users adopt technology and low-GHG-intensive options ( 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 building ( medium confiden ce).

WGIII SPM B.4.2 WGIII SPM E.6.2 WGIII SPM C.10.4 WGIII Chapter 16.5

4.8.3.c

International cooperation on innovation works best when tailored to and beneficial for local value chains, when partners collaborate on an equal footing, and when capacity building is an integral part of the effort ( medium confidence ).

WGIII SPM E.4.4 WGIII SPM E.6.2

.

4.8.3.d Technological innovation can have trade-offs that include externalities such as new and greater environmental impacts and social inequalities; rebound effects leading to lower net emission reductions or even emission increases; and overdependence on foreign knowledge and providers (high confidence). Appropriately designed policies and governance have helped address distributional impacts and rebound effects ( high confidence ). For example, digital technologies can promote large increases in energy efficiency through coordination and an economic shift to services ( high confidence ). However, societal digitalization can induce greater consumption of goods and energy and increased electronic waste as well as negatively impacting labour markets and worsening inequalities between and within countries ( medium confidence ). Digitalisation requires appropriate governance and policies in order to enhance mitigation potential ( high confidence ) . Effective policy packages can help to realise synergies, avoid trade-offs and/or reduce rebound effects: these might include a mix of efficiency targets, performance standards, information provision, carbon pricing, finance and technical assistance ( high confidence) . { WGIII SPM B.4.2, WGIII SPM B.4.3, WGIII SPM E.4.4, WGIII TS 6.5, WGIII Cross-Chapter Box 11 on Digitalization in Chapter 16} management, and improved agricultural productivity supports reduced emissions from deforestation and land use change while also improving GHG accounting and standardisation ( medium confidence )

SRCCL SPM C.2.1 SRCCL SPM D.1.2 SRCCL SPM D.1.4 SRCCL Chapter 7.4.4 SRCCL Chapter 7.4.6

.

4.9 Integration of Near-Term Actions Across Sectors and Systems

4.9.a The feasibility, effectiveness and benefits of mitigation and adaptation actions are increased when multi-sectoral solutions are undertaken that cut across systems. When such options are combined with broader sustainable development objectives, they can yield greater benefits for human well-being, social equity and justice, and ecosystem and planetary health.(high confidence)

4.9.b Climate resilient development strategies that treat climate, ecosystems and biodiversity, and human society as parts of an integrated system are the most effective (high confidence). Human and ecosystem vulnerability are interdependent ( high confidence ). Climate resilient development is enabled when decision- making processes and actions are integrated across sectors ( very high confidence ). Synergies with and progress towards the Sustainable Development Goals enhance prospects for climate resilient development. Choices and actions that treat humans and ecosystems as an integrated system build on diverse knowledge about climate risk, equitable, just and inclusive approaches, and ecosystem stewardship.

WGII SPM B.2 WGII Figure SPM.5 WGII SPM D.2 WGII SPM D2.1 WGII SPM 2.2 WGII SPM D4 WGII SPM D4.1 WGII SPM D4.2 WGII SPM D5.2 WGII SPM Figure SPM.5

.

4.9.c Approaches that align goals and actions across sectors provide opportunities for multiple and large- scale benefits and avoided damages in the near-term . Such measures can also achieve greater benefits through cascading effects across sectors (medium confidence). For example, the feasibility of using land for both agriculture and centralised solar production can increase when such options are combined ( high confidence ). Similarly, integrated transport and energy infrastructure planning and operations can together reduce the environmental, social, and economic impacts of decarbonising the transport and energy sectors ( high confidence ).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 (very high confidence ). Integrated design approaches to the construction and retrofit of buildings provide increasing examples of zero energy or zero carbon buildings in several regions. To minimise maladaptation, multi-sectoral, multi-actor and inclusive planning with flexible pathways encourages low-regret and timely actions that keep options open, ensure benefits in multiple sectors and systems and suggest the available solution space for adapting to long-term climate change ( very high confidence ). 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, with frameworks for integrated policy implementation (high confidence) WGII SPM C.2 WGII SPM C.2.1–2.13 WGII SPM C.4.4 WGIII SPM C.6.3 WGIII SPM C.6 WGIII SPM C.7.2 WGIII SPM C.8.5 WGIII SPM D.1.2 WGIII SPM D.1.5 WGIII SPM E.1.2

4.9.d Mitigation and adaptation when implemented together, and combined with broader sustainable development objectives, would yield multiple benefits for human well-being as well as ecosystem and planetary health (high confidence). The range of such positive interactions is significant in the landscape of near-term climate policies across regions, sectors and systems. For example, AFOLU mitigation actions in land-use change and forestry, when sustainably implemented, can provide large-scale GHG emission reductions and removals that simultaneously benefit biodiversity, food security, wood supply and other ecosystem services but cannot fully compensate for delayed mitigation action in other sectors . Adaptation measures in land, ocean and ecosystems similarly can have widespread benefits for food security, nutrition, health and well-being, ecosystems and biodiversity. Equally, urban systems are critical, interconnected sites for climate resilient development; urban policies that implement multiple interventions can yield adaptation or mitigation gains with equity and human well-being. Integrated policy packages can improve the ability to integrate considerations of equity, gender equality and justice. Coordinated cross-sectoral policies and planning can maximise synergies and avoid or reduce trade-offs between mitigation and adaptation. Effective action in all of the above areas will require near-term political commitment and follow-through, social

4.9.e

(3.4, 4.4)

WGII SPM C.1 WG II SPM C.2 WGII SPM C.2 WGII SPM C.5 WGII SPM D.2 WGII SPM D.3.2 WGII SPM D.3.3 WGII SPM Figure SPM.4 WGIII SPM C.6.3 WGIII SPM C.8.2 WGIII SPM C.9 WGIII SPM C.9.1 WGIII SPM C.9.2 WGIII SPM D.2 WGIII SPM D.2.4 WGIII SPM D.3.2 WGIII SPM E.1 WGIII SPM E.2.4 WGIII SPM Figure SPM.8 WGIII TS.7 WGIII TS Figure TS.29: SRCCL ES Section 7.4.8 SRCCL SPM B.6

4.9.f

Back Matter, Footnotes, Figures, Tables, Boxes

Footnotes

Back Matter, Footnotes, Figures, Tables, Boxes

2.1.1.d

increased rapidly over recent decades ( panel (a) ). Global net anthropogenic GHG emissions include CO2from fossil fuel combustion and industrial processes (CO2-FFI) (dark green); net CO2from land use, land-use change and forestry (CO2- LULUCF) (green); CH4; N2O; and fluorinated gases (HFCs, PFCs, SF6, NF3) (light blue). These emissions have led to increases in the atmospheric concentrations of several GHGs including the three major well-mixed GHGs CO2, CH4and N2O ( panel (b) , annual values). To indicate their relative importance each subpanel’s vertical extent for CO2, CH4and N2O is scaled to match the assessed individual direct effect (and, in the case of CH4indirect effect via atmospheric chemistry impacts on tropospheric ozone) of historical emissions on temperature change from 1850 – 1900 to 2010 – 2019. This estimate arises from an assessment of effective radiative forcing and climate sensitivity. The global surface temperature (shown as annual anomalies from a 1850 – 1900 baseline) has increased by around 1.1°C since 1850 – 1900 ( panel (c) ). The vertical bar on the right 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). Prior to that, the next most recent warm period was about 125,000 years ago, when the assessed multi-century temperature range [0.5°C–1.5℃] overlaps the observations of the most recent decade. These past warm periods were caused by slow (multi-millennial) orbital variations. Formal detection and attribution studies synthesise information from climate models and observations and show that the best estimate is that all the warming observed between 1850 – 1900 and 2010 – 2019 is caused by humans ( panel (d) ). The panel shows temperature change attributed to: total human influence; its decomposition into changes in GHG concentrations and other human drivers (aerosols, ozone and land-use change (land-use reflectance)); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges.

WGI SPM A.2.2 WGI Figure SPM.1 WGI Figure SPM.2 WGI TS2.2 WGI 2.1 WGIII Figure SPM.1 WGIII A.III.II.2.5.1

Average annual GHG emissions 12 during 2010–2019 were higher than in any previous decade, but the rate of growth between 2010 and 2019 (1.3% yr-1) was lower than that between 2000 and 2009 (2.1% yr- 1). Historical cumulative net CO2emissions from 1850 to 2019 were 2400 ±240 GtCO2. Of these, more than half (58%) occurred between 1850 and 1989 [1400 ±195 GtCO2], and about 42% between 1990 and 2019 [1000 ±90 GtCO2]. Global net anthropogenic GHG emissions have been estimated to be 59±6.6 GtCO2-eq in 2019, about 12% (6.5 GtCO2-eq) higher than in 2010 and 54% (21 GtCO2-eq) higher than in 1990. By 2019, the largest growth in gross emissions occurred in CO2from fossil fuels and industry (CO2-FFI) followed by CH4, whereas the highest relative growth occurred in fluorinated gases (F-gases), starting from low levels in 1990. ( high confidence )

WGIII SPM B1.1 WGIII SPM B.1.2 WGIII SPM B.1.3 WGIII Figure SPM.1 WGIII Figure SPM.2

12GHG emission metrics are used to express emissions of different GHGs 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. {WGI SPM D.1.8, WGI 7.6; WGIII

Figure 2.2: Regional GHG emissions, and the regional proportion of total cumulative production-based CO2emissions from 1850 to 2019. Panel (a) shows the share of historical cumulative net anthropogenic CO2emissions per region from 1850 to 2019 in GtCO2. This includes CO2-FFI and CO2-LULUCF. Other GHG emissions are not included. CO2-LULUCF emissions are subject to high uncertainties, reflected by a global uncertainty estimate of ±70% (90% in 2019. GHG emissions are categorised into: CO2-FFI; net CO2-LULUCF; and other GHG emissions (CH4, N2O, 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 CO2removals rather than emissions. Panel (c) shows global net anthropogenic GHG emissions by region (in GtCO2-eq yr–1(GWP100-AR6)) for the time period 1990–2019. 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 of WGIII. Panel (d) shows population, GDP per person, emission indicators by region in 2019 for 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.

WGIII Figure SPM.2

Regional contributions to global human-caused GHG emissions continue to differ widely. Historical contributions of CO2emissions 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 (Figure 2.2). Variations in regional and national per capita emissions partly reflect different development stages, but they also vary widely at similar income levels. Average per capita net anthropogenic GHG emissions in 2019 ranged from 2.6 tCO2-eq to 19 tCO2-eq across regions (Figure 2.2). 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 . Around 48% of the global population in 2019 lives in countries emitting on average more than 6 tCO2-eq per capita, 35% of the global population live in countries emitting more than 9 tCO2-eq per capita13(excluding CO2- LULUCF) while 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. ( high confidence )

WGIII SPM B.3 WGIII SPM B3.1 WGIII SPM B.3.2 WGIII SPM B.3.3

Net GHG emissions have increased since 2010 across all major sectors (high confidence). In 2019, approximately 34% (20 GtCO2-eq) of net global GHG emissions came from the energy sector, 24% (14 GtCO2- eq) from industry, 22% (13 GtCO2-eq) from AFOLU, 15% (8.7 GtCO2-eq) from transport and 6% (3.3 GtCO2- eq) from buildings14( high confidence ). 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–1in the transport sector ( high confidence ). About half of total net AFOLU emissions are from CO2LULUCF, predominantly from deforestation (medium confidence ). Land overall constituted a net sink of –6.6 (±4.6) GtCO2yr–1for the period 2010–201915( medium confidence ).

WGIII SPM B.2 WGIII SPM B.2.1 WGIII SPM B.2.2 WGIII TS 5.6.1

Human-caused climate change is a consequence of more than a century of net GHG emissions from energy use, land-use and land use change, lifestyle and patterns of consumption, and production. Emissions reductions in CO2from 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. The 10% of households with the highest per capita emissions contribute 34–45% of global consumption-based household GHG emissions, while the middle 40% contribute 40–53%, and the bottom 50% contribute 13–15%. An increasing share of emissions can be attributed to urban areas (a rise from about 62% to 67 – 72% of the global share between 2015 and 2020). The drivers of urban GHG emissions16are complex and include population size,

13Territorial emissions14GHG emission levels are rounded to two significant digits; as a consequence, small differences in sums due to rounding may occur

WGIII SPM footnote 8

15Comprising a gross sink of -12.5 (±3.2) GtCO2yr-1resulting from responses of all land to both anthropogenic environmental change and natural climate variability, and net anthropogenic CO2- LULUCF emissions +5.9 (±4.1) GtCO2yr-1based on book-keeping models

WGIII SPM Footnote 14

.16This estimate is based on consumption-based accounting, including both direct emissions from within urban areas, and indirect

SPM B.3.4, WGIII SPM D.1.1}

2.1.2.b

Table 2.1: Assessment of observed changes in large-scale indicators of mean climate across climate system components, and their attribution to human influence. The colour coding indicates the assessed confidence in / likelihood18of the observed change and the human contribution as a driver or main driver (specified in that case) where available (see colour key). Otherwise, explanatory text is provided.

WGI Table TS.1

include all CO2and CH4emission categories except for aviation and marine bunker fuels, land-use change, forestry and agriculture

WGIII SPM footnote 15

17‘Main driver’ means responsible for more than 50% of the change

WGI SPM footnote 12

.18Based on scientific understanding, key findings can be formulated as statements of fact or associated with an assessed level of

2.2.2.f

Figure 2.4 : Unit cost reductions and use in some rapidly changing mitigation technologies. The top panel (a) 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. Yellow 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 three 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 (b) 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 over the past decade. The electricity production share reflects different capacity factors; for example, for the same amount of installed capacity, wind produces about twice as examples because they have recently shown rapid changes in costs and adoption, and because consistent data are available. Other mitigation options assessed in the WGIII report are not included as they do not meet these criteria.

WGIII Figure SPM.3

The magnitude of global climate finance flows has increased and financing channels have broadened (high confidence). Annual tracked total financial flows for climate mitigation and adaptation increased by up to 60% between 2013/14 and 2019/20, but average growth has slowed since 2018 ( medium confidence ) and most climate finance stays within national borders ( high confidence ). Markets for green bonds, environmental, social and governance and sustainable finance products have expanded significantly since AR5 ( high confidence ). Investors, central banks, and financial regulators are driving increased awareness of climate risk to support climate policy development and implementation ( high confidence ). Accelerated international financial cooperation is a critical enabler of low-GHG and just transitions ( high confidence ).

WGIII SPM B.5.4 WGIII SPM E.5 WGIII TS.6.3 WGIII TS.6.4

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 ). 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 ). Equity and distributional impacts of 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 ). The mix of policy instruments which reduced costs and stimulated adoption of solar energy, wind energy and lithium-ion batteries includes public R&D, funding for demonstration and pilot projects, and demand pull instruments such as deployment subsidies to attain scale ( high confidence ) (Figure 2.4).

WGIII SPM B.4.1 WGIII SPM B.5.2 WGIII SPM E.4.2 WG III TS.3

Mitigation actions, supported by policies, have contributed to a decrease in global energy and carbon intensity between 2010 and 2019, with a growing number of countries achieving absolute GHG emission reductions for more than a decade (high confidence). While global net GHG emissions have increased since 2010, global energy intensity (total primary energy per unit GDP) decreased by 2% yr–1between 2010 and 2019. Global carbon intensity (CO2-FFI per unit primary energy) also decreased by 0.3% yr–1, mainly due to fuel switching from coal to gas, reduced expansion of coal capacity, and increased use of renewables, and with large regional variations over the same period. 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 ). At least 18 countries have sustained production-based CO2and GHG and consumption-based CO2absolute emission reductions for longer than 10 years since 2005 through energy supply decarbonization, energy efficiency gains, and energy demand reduction, which resulted from both policies and changes in economic structure ( high confidence ). Some countries have reduced production-based GHG emissions by a third or more since peaking, and some have achieved reduction rates of around 4% yr–1for several years consecutively ( 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–1of avoided emissions can be accounted for by aggregating separate estimates for the effects of economic and regulatory instruments ( medium confidence ). Growing numbers of laws and executive orders have impacted global emissions and are estimated to have resulted in 5.9 GtCO2-eq yr–1of avoided emissions in 2016 ( medium confidence ). These reductions have only partly offset global emissions growth ( high confidence )

WGIII SPM B.1 WGIII SPM B.2.4 WGIII SPM B.3.5 WGIII SPM B.5.1 WGIII SPM B.5.3 WGIII 1.3.2 WGIII 2.2.3

2.3.1.f

Table 2.2 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 gross differences in emissions are based on emissions of 52–56 GtCO2-eq yr–1in 2019 as assumed in underlying model studies40. ( medium confidence ) {WGIII Table SPM.1} (Table 3.1, CSB.2) only submitted thereafter. 25 NDC updates were submitted between 12 October 2021 and the start of COP26.

WGIII SPM footnote 24

35Immediate 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 3.1. 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 3.1). {WGIII SPM footnote 26)36In 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.

WGIII SPM footnote 27

37Implementation gaps refer to how far currently enacted policies and actions fall short of reaching the pledges. 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.

WGIII Table 4.2 WGIII SPM footnote 25

38Abatement here refers to human interventions that reduce the amount of GHGs that are released from fossil fuel infrastructure to the atmosphere.

WGIII SPM footnote 34

39WGI provides carbon budgets that are in line with limiting global warming to temperature limits with different likelihoods, such as 50%, 67% or 83%

WGI Table SPM.2

.40The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO2-eq] is within the uncertainty ranges of 2019

2.3.1.g

Figure 2.5 Global GHG emissions of modelled pathways (funnels in Panel a), 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, WGIII 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 probability of 50% or greater after high overshoot (subset of 42 scenarios from C2, WGIII Table SPM.2). – Limit to 2°C (>67%) with immediate action: Pathways that limit warming to 2°C (>67%) with immediate action after 2020 (C3a, WGIII 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, WGIII 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 line. Panel b shows a snapshot of the GHG emission ranges of the modelled pathways in 2030 and projected emissions outcomes from near-term policy assessments in 2030 from WGIII Chapter 4.2 (Tables 4.2 and 4.3; median and full range). GHG emissions are CO2-equivalent using GWP100 from AR6 WGI.

WGIII Figure SPM.4 WGIII 3.5 4.2 Table 4.2 Table 4.3 Cross-Chapter Box 4 in Chapter 4

(Table 3.1, CSB.2)

Cross-Section Box.1: Understanding Net Zero CO2and Net Zero GHG Emissions Limiting human-caused global warming to a specific level requires limiting cumulative CO2emissions, reaching net zero or net negative CO2emissions, along with strong reductions in other GHG emissions (see 3.3.2). Future additional warming will depend on future emissions, with total warming dominated by past and future cumulative CO₂ emissions

WGI SPM D.1.1 WGI Figure SPM.4 SR1.5 SPM A.2.2

.

Reaching net zero CO2emissions is different from reaching net zero GHG emissions. The timing of net zero for a basket of GHGs depends on the emissions metric, such as global warming potential over a 100-year period, chosen to convert non-CO2emissions into CO2-equivalent ( high confidence ). However, for a given emissions pathway, the physical climate response is independent of the metric chosen ( high confidence )

WGI SPM D.1.8 WGIII Box TS.6 WGIII Cross-chapter box 2

.

Achieving global net zero GHG emissions requires all remaining CO2and metric-weighted41non-CO2GHG emissions to be counterbalanced by durably stored CO2removals (high confidence). Some non- CO2emissions, such as CH4and N2O from agriculture, cannot be fully eliminated using existing and anticipated technical measures

WGIII SPM C.2.4 WGIII SPM C.11.4 Cross-Chapter Box 3

.

Global net zero CO2or GHG emissions can be achieved even if some sectors and regions are net emitters, provided that others reach net negative emissions (see Figure 4.1). The potential and cost of achieving net zero or even net negative emissions vary by sector and region. If and when net zero emissions for a given sector or region are reached depends on multiple factors, including the potential to reduce GHG emissions and undertake carbon dioxide removal, the associated costs, and the availability of policy mechanisms to balance emissions and removals between sectors and countries. ( high confidence )

WGIII Box TS.6 WGIII Cross-Chapter Box 3

.

The adoption and implementation of net-zero emission targets by countries and regions also depend on equity and capacity considerations (high confidence). The formulation of net zero pathways by countries will benefit from clarity on scope, plans-of-action, and fairness. Achieving net zero emission targets relies on policies, institutions, and milestones against which to track progress. Least-cost global modelled pathways have been shown to distribute the mitigation effort unevenly, and the incorporation of equity principles could change the country-level timing of net zero ( high confidence ). The Paris Agreement also recognizes that peaking of emissions will occur later in developing countries than developed countries (Article 4.1)

WGIII Box TS.6 WGIII Cross-Chapter Box 3 WGIII 14.3

.

More information on country-level net zero pledges is provided in S2.3.1, on the timing of global net zero emissions in S3.3.2, and on sectoral aspects of net zero in S4.1.

Many countries have signalled an intention to achieve net-zero GHG or net-zero CO2emissions by around mid-century (Cross-Section Box 1). More than 100 countries have either adopted, announced or are discussing net zero GHG or net zero CO2emissions commitments, covering more than two-thirds of global GHG emissions. A growing number of cities are setting climate targets, including net-zero GHG targets. Many companies and institutions have also announced net zero emissions targets in recent years. The various net zero emission pledges differ across countries in terms of scope and specificity, and limited policies are to date in place to deliver on them.

WGIII SPM C.6.4 WGIII TS.4.1 WGIII Table TS.1 WGIII 13.9 WGIII 14.3 WGIII 14.5

All mitigation strategies face implementation challenges, including technology risks, scaling, and costs (high confidence). Almost all mitigation options also face institutional barriers that need to be addressed to enable their application at scale ( medium confidence ). 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 ). 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 ( medium confidence ). 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 ( medium confidence ).

WGIII SPM C.3.6 WGIII SPM E.1.1 WGIII SPM E.2.1 WGIII SPM E.3.3

The 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 (medium confidence). In many countries, especially those with limited institutional capacity, several adverse side-effects have been observed as a result of diffusion of low-emission technology, e.g., low-value employment, and dependency on foreign knowledge and suppliers ( medium confidence ). 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 ). Persistent and region-specific barriers also continue to hamper the economic and political feasibility of deploying AFOLU mitigation options ( medium confidence ). Barriers to 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 ( high confidence ).

WGIII SPM B.4.2 WGIII SPM C.9.1 WGIII SPM C.9.3

2.3.3.f

Cross-Section Box.2: Scenarios, Global Warming Levels, and Risks

Modelled scenarios and pathways45are 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 socio-economic 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 intra-regional income distribution. IPCC is neutral with regard to the assumptions underlying the scenarios in the

45In 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 emissions and mitigation pathways. The SYR primarily uses scenarios when referring to WGI and modelled emissions and mitigation pathways when referring to WGIII.

SPM.1; WGI Box SPM.1; WGII Box SPM.1; WGIII Box SPM.1}.

Socio-economic Development, Scenarios, and Pathways The five Shared Socio-economic Pathways (SSP1 to SSP5) were designed to span a range of challenges to climate change mitigation and adaptation. For the assessment of climate impacts, risk and adaptation, the SSPs are used for future exposure, vulnerability and challenges to adaptation. Depending on levels of GHG mitigation, modelled emissions scenarios based on the SSPs can be consistent with low or high warming levels47. There are many different mitigation strategies that could be consistent with different levels of global warming in 2100 (see Figure 4.1).

WGI Box SPM.1 WGII Box SPM.1 WGIII Box SPM.1 WGIII Box TS.5 WGIII Annex III SRCCL Box SPM.1 Figure SPM.2

WGI assessed the climate response to five illustrative scenarios based on SSPs48that cover the range of possible future development of anthropogenic drivers of climate change found in the literature. These scenarios combine socio-economic assumptions, levels of climate mitigation, land use and air pollution controls for aerosols and non-CH4ozone precursors. The high and very high GHG emissions scenarios (SSP3-7.0 and SSP5-8.5) have CO2emissions that roughly double from current levels by 2100 and 2050, respectively49. The intermediate GHG emissions scenario (SSP2-4.5) has CO2emissions 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 CO2emissions declining to net zero around 2050 and 2070, respectively, followed by varying levels of net negative CO2emissions. In addition, Representative Concentration Pathways (RCPs)50were used by WGI and WGII to assess regional climate changes, impacts and risks.

WGI Box SPM.1

(Cross-Section Box.2, Figure 1)

In WGIII, a large number of global modelled emissions pathways were assessed, of which 1202 pathways were categorised based on their projected global warming over the 21st century, with categories ranging from pathways that limit warming to 1.5°C with more than 50% likelihood51with no or limited overshoot (C1) to pathways that exceed 4°C (C8). Methods to project global warming associated with the modelled pathways were updated to ensure consistency with the AR6 WGI assessment of the climate system response52.

WGIII Box SPM.1 WGIII Table 3.1

(Table 3.1, Cross-Section Box.2, Figure 1)

Global Warming Levels (GWLs) For many climate and risk variables, the geographical patterns of changes in climatic impact-drivers53and climate impacts for a level of global warming54are common to all scenarios considered and independent of

46Around half of all modelled global emissions pathways assume cost-effective approaches that rely on least-cost mitigation/abatement options globally. The other half look at existing policies and regionally and sectorally differentiated actions. 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 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).

WGIII Box SPM.1

.47High 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 )

SRCCL Box SPM.1 WGIII SPM C.1.4

.48SSP-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.

WGI SPM footnote 22

49Very high emission scenarios have become less likely but cannot be ruled out. Temperature levels > 4C may result from very high emission scenarios, but can also occur from lower emission scenarios if climate sensitivity or carbon cycle feedbacks are higher than the best estimate.50RCP-based scenarios are referred to as RCPy, where ‘y’ refers to the approximate level of radiative forcing (in watts per square metre, or Wm-2) resulting from the scenario in the year 2100.

WGII SPM footnote 21

51Denoted ‘>50%’ in this report.52The climate response to emissions is investigated with climate models, paleoclimatic insights and other lines of evidence. The assessment outcomes are used to categorise thousands of scenarios via simple physically-based climate models (emulators)

WGI TS.1.2.2

.53See Annex I: Glossary54See Annex I: Glossary. Here, global warming is the 20-year average global surface temperature relative to 1850–1900. The assessed time of when a certain global warming level is reached under a particular scenario is defined here as the mid-point of the first 20-year running average period during which the assessed average global surface temperature change exceeds the level of global warming.

SPM.1.4, WGI TS.1.3.2; WGII Box SPM.1} (Figure 3.1, Figure 3.2)

Risks Dynamic interactions between climate-related hazards, exposure and vulnerability of the affected human society, species, or ecosystems result in risks arising from climate change. AR6 assesses key risks across sectors and regions as well as providing an updated assessment of the Reasons for Concern (RFCs) – five globally aggregated categories of risk that evaluate risk accrual with increasing global surface temperature. Risks can also arise from climate change mitigation or adaptation responses when the response does not achieve its intended objective, or when it results in adverse effects for other societal objectives.

WGII SPM A WGII Figure SPM.3 WGII Box TS.1 WGII Figure TS.4 SR1.5 Figure SPM.2 SRCCL Figure SPM.2 SROCC Errata Figure SPM.3

(3.1.2, Cross-Section Box.2, Figure 1; Figure 3.3)

Section 3: Long-Term Climate and Development Futures

* The terminology SSPx-y is used, 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. ** The AR5 scenarios (RCPy), which partly inform the AR6 WGI and WGII assessments, are indexed to a similar set of approximate 2100 radiative forcing levels (in Wm-2). The SSP scenarios cover a broader range of GHG and air pollutant futures than the RCPs. They are similar but not identical, with differences in concentration trajectories for different GHGs. The overall radiative forcing tends to be higher for the SSPs compared to the RCPs with the same label ( medium confidence ).

WGI TS.1.3.1

*** 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.

Cross-Section Box.2, Figure 1: Schematic of the AR6 framework for assessing future greenhouse gas emissions, climate change, risks, impacts and mitigation. Panel ( a ) The integrated framework encompasses socio-economic development and policy, emissions pathways and global surface temperature responses to the five scenarios considered by WGI (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and eight global mean temperature change categorisations (C1–C8) assessed by WGIII, and the WGII risk assessment. The dashed arrow indicates that the influence from impacts/risks to socio-economic changes is not yet considered in the scenarios assessed in the AR6. Emissions include GHGs, aerosols, and ozone precursors. CO2emissions are shown as an example on the left. The assessed global surface temperature changes across the 21st century relative to 1850–1900 for the five GHG emissions scenarios are shown as an example in the centre. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0. Projected temperature outcomes at 2100 relative to 1850–1900 are shown for C1 to C8 categories with median (line) and the combined very likely range across scenarios (bar). On the right, future risks due to increasing warming are represented by an example ‘burning ember’ figure (see 3.1.2 for the definition of RFC1). Panel ( b ) Description and relationship of scenarios considered across AR6 Working Group reports. Panel ( c ) Illustration of risk arising from the interaction of hazard (driven by changes in climatic impact-drivers) with vulnerability, exposure and response to climate change.

WGI TS1.4 Figure 4.11 WGII Figure 1.5 WGII Figure 14.8 WGIII Table SPM.2 Figure 3.11

3.1.1.k

Figure 3.1: Projected changes of annual maximum daily temperature, annual mean total column soil moisture CMIPand annual maximum daily precipitation at global warming levels of 1.5°C, 2°C, 3°C, and 4°C relative to 1850–1900. Simulated ( a ) annual maximum temperature change (°C), ( b ) annual mean total column soil moisture (standard deviation), ( c ) annual maximum daily precipitation change (%). Changes correspond to 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.

WGI Figure SPM.5 WGI Figure TS.5 WGI Figure 11.11 WGI Figure 11.16 WGI Figure 11.19

(CSB.2)

3.1.2.j

65Several SRM approaches have been proposed, including stratospheric aerosol injection, marine cloud brightening, ground-based

Figure 3.2: 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 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 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 1.5°C, 2°C, 3°C and 4°C. Underpinning projections of temperature are from 21 Earth system models and do not consider extreme events impacting ecosystems such as the Arctic. (b) Risk to human health as indicated by the days per year of population exposure to hypothermic 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 WGLs by 2081-2100 under RCP2.6, RCP4.5 and assessments. (c) Impacts on food production: (c1) Changes in maize yield 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) Changes 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

WGII Fig. TS.5 WGII Fig TS.9 WGII Annex I: Global to Regional Atlas Figure AI.15 Figure AI.22 Figure AI.23 Figure AI.29 WGII 7.3.1.2 7.2.4.1 SROCC Figure SPM.3

(3.1.2, Cross-Section Box.2)

3.1.2.k

Figure 3.3: Synthetic risk diagrams of global and sectoral assessments and examples of regional key 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); Right - Global Reasons for Concern, comparing AR6 (thick embers) and AR5 (thin embers) assessments. Diagrams are shown for each RFC, assuming low to no adaptation (i.e., adaptation is fragmented, localised and comprises incremental adjustments to existing practices). However, the transition to a very high risk level has an emphasis on irreversibility and adaptation limits. The horizontal line denotes the present global warming of 1.1°C which is used to separate the observed, past impacts below the line from the future projected risks above it. Lines connect the midpoints of the transition from moderate to high risk across AR5 and AR6. Panel (b) : Risks for land-based systems and ocean/coastal ecosystems. Diagrams shown for each

Global mean sea level change in centimetres, relative to 1900. 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) and indicating the IPCC AR6 baseline period (1995–2014). 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” 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 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 defences, ecosystem restoration or creation of new natural buffers areas, and subsidence management) and planned relocation. Planned relocation refers to managed retreat or resettlement. Forced displacement is not considered in this assessment. 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) : 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 socio-economic pathways (SSP1 and SSP3) excluding the effects of targeted mitigation and adaptation policies. Panel (e) : 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.

WGI Figure SPM.8 WGII SPM B.3.3 WGII Figure SPM.3 WGII SM 16.6 WGII SM 16.7.4 SRCCL Figure SPM.2 SROCC Figure SPM.3d SROCC SPM.5a SROCC 4SM SRCCL 7.3.1 SRCCL 7SM

(CSB.2)

3.2.h

Figure 3.4: Observed and projected global mean sea level change and its impacts, and time scales of coastal risk management. Panel (a) : Global mean sea level change in metres relative to 1900. The historical changes (black) are observed by tide gauges before 1992 and altimeters afterwards. The future changes to 2100 and for 2150 (coloured lines and shading) are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models, and median values and likely ranges are shown for the considered scenarios. Relative to 1995–2014, the likely global mean sea level rise by 2050 is between 0.15–0.23 m in the very low GHG emissions scenario (SSP1-1.9) and 0.20– 0.29 m in the very high GHG emissions scenario (SSP5-8.5); by 2100 between 0.28–0.55 m under SSP1-1.9 and 0.63– 1.01 m under SSP5-8.5; and by 2150 between 0.37–0.86 m under SSP1-1.9 and 0.98–1.88 m under SSP5-8.5 ( medium to 1995–2014) to simulated changes relative to 1995–2014. The future changes to 2300 (bars) are based on literature assessment, representing the 17th–83rd percentile range for SSP1-2.6 (0.3–3.1 m) and SSP5-8.5 (1.7–6.8 m). Red dashed lines: Low-likelihood, high-impact storyline, including ice sheet instability processes. These indicate the potential impact of deeply uncertain processes, and show the 83rd percentile of SSP5-8.5 projections that include low-likelihood, high-impact processes that cannot be ruled out; because of low confidence in projections of these processes, this is not part of a likely range. IPCC AR6 global and regional sea level projections are hosted at https://sealevel.nasa.gov/ipcc-ar6-sea- level-projection-tool. The low-lying coastal zoneis currently home to around 896 million people (nearly 11% of the 2020 global population), projected to reach more than one billion by 2050 across all five SSPs. Panel (b) : Typical time scales for the planning, implementation (dashed bars) and operational lifetime of current coastal risk-management measures (blue bars). Higher rates of sea level rise demand earlier and stronger responses and reduce the lifetime of measures (inset). As the scale and pace of sea level rise accelerates beyond 2050, long-term adjustments may in some locations be beyond the limits of current adaptation options and for some small islands and low-lying coasts could be an existential risk.

WGI SPM B.5 C.2.5 Figure SPM.8 9.6 WGII SPM B.4.5 B.5.2 C.2.8 D.3.3 TS.D.7 Cross-Chapter Box SLR

(CSB.2)

3.3.1.g

73When adjusted for emissions since previous reports, these RCB estimates are similar to SR1.5 but larger than AR5 values due to methodological improvements.

WGI SPM D.1.3

74Uncertainties for total carbon budgets have not been assessed and could affect the specific calculated fractions.75See footnote 77.76These projected adjustments of carbon sinks to stabilisation or decline of atmospheric CO2concentrations are accounted for in

Figure 3.5: Cumulative past, projected, and committed emissions, and associated global temperature changes. Panel (a) Assessed remaining carbon budgets to limit warming more likely than not to 1.5°C, below 2°C with a 83% and 67% likelihood, compared to cumulative emissions corresponding to constant 2019 emissions until 2030, existing and planned fossil fuel infrastructures (in GtCO2). For remaining carbon budgets, thin lines indicate the uncertainty due to the contribution of non-CO2warming. For lifetime emissions from fossil fuel infrastructure, thin lines indicate the assessed sensitivity range. Panel (b) Relationship between cumulative CO2emissions and the increase in global surface temperature. Historical data (thin black line) shows historical CO2emissions versus observed global surface temperature increase relative to the period 1850–1900. The grey range with its central line shows a corresponding estimate of the human-caused share of historical warming. 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 CO2emissions for the selected scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Projections until 2050 use the cumulative CO2emissions of each respective scenario, and the projected global warming includes the contribution from all anthropogenic forcers.

WGI SPM D.1 WGI Figure SPM.10 WGI Table SPM.2 WGIII SPM B.1 WGIII SPM B.7 WGIII 2.7 SR1.5 SPM C.1.3

Table 3.1: Key characteristics of the modelled global emissions pathways. Summary of projected CO2and GHG emissions, projected net-zero timings and the resulting global warming outcomes. Pathways are categorised (columns), 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 CO2or GHGs.

WGIII Table SPM.2

1 Detailed explanations on the Table are provided in WGIII Box SPM.1 and WGIII Table SPM.2. The relationship between the temperature categories and SSP/RCPs is discussed in Cross-Section Box 2. Values in the table refer to the 50th and [5th–95th] percentile values across the pathways falling within a given category as defined in WGIII Box SPM.1. The three dots (…) sign denotes that the value cannot be given (as the value is after 2100 or, for net zero, net-zero is not reached). Based on the assessment of climate emulators in AR6 WG I (Chapter 7, Box 7.1), two climate emulators were used for the probabilistic assessment 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 in the “likelihood” column, the median warming for every pathway in that category is calculated for each of the two climate model emulators (MAGICC and FaIR). These ranges cover both the uncertainty of the emissions pathways as well as the climate emulators’ uncertainty. All global warming levels are relative to 1850–1900. 2 C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in WGIII Figure SPM.4. 3 Global emission reductions 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 WGIII SPM Section B and WGIII 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 (see WGIII SPM Footnote 49). Negative values (e.g., in C5, C6) represent an increase in emissions. The modelled GHG emissions in 2019 are 55 [53–58] GtCO2-eq, thus within the uncertainty ranges of estimates for 2019 emissions [53-66] GtCO2-eq (see 2.1.1). 4 Emissions milestones are provided for 5-year intervals in order to be consistent with the underlying 5-year time-step data of the modelled pathways. Ranges in square brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile 5-year interval and the upper bound of the 95th percentile 5-year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones over the 21st century. Percentiles reported across all pathways in that category include those that do not reach net zero before 2100. 5 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 WGIII Annex III.II.5. 6 Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO2emissions, ensuring consistency with the WG I assessment of the remaining carbon budget.

WGIII Box 3.4 WGIII SPM Footnote 50

4.1.g

90The southern part of Mexico is included in the climatic 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. {WGII 12.1.1,

Figure 4.1: Sectoral emissions in pathways that limit warming to 1.5 ° C. Panel (a) shows sectoral CO2and non-CO2emissions in global modelled pathways that limit warming to 1.5°C (>50%) with no or limited overshoot. The horizontal lines illustrate halving 2015 emissions (base year of the pathways) (dashed) and reaching net-zero emissions (solid line). The range shows the 5–95th percentile of the emissions across the pathways. The timing strongly differs by sector, with the CO2emissions from the electricity/fossil fuel industries sector and land-use change generally reaching net zero earlier. Non-CO2emissions from agriculture are also substantially reduced compared to pathways without climate policy but do not typically reach zero. Panel (b) Although all pathways include strongly reduced emissions, there are different pathways as indicated by the illustrative mitigation pathways used in IPCC WGIII. The pathways emphasise routes consistent with limiting warming to 1.5°C with a high reliance on net negative emissions (IMP-Neg), high resource efficiency (IMP-LD), a focus on sustainable development (IMP-SP) or renewables (IMP-Ren) and consistent with 2°C

Positive (solid filled bars) and negative emissions (hatched bars) for different illustrative mitigation pathways are compared to GHG emissions from the year 2019. The category “energy supply (including electricity)” includes bioenergy with carbon capture and storage and direct air carbon capture and storage.

WGIII Box TS.5 3.3 3.4 6.6 10.3 11.3

(Cross-Section Box 2)

4.3.p

Figure 4.3: Every region faces more severe or frequent compound and/or cascading climate risks in the near term. Changes in risk result from changes in the degree of the hazard, the population exposed, and the degree of vulnerability of people, assets, or ecosystems. Panel (a) Coastal flooding events affect many of the highly populated regions of the world where large percentages of the population are exposed. The panel shows near-term projected increase of population exposed to 100-year flooding events depicted as the increase from the year 2020 to 2040 (due to sea level rise and migration from coastal areas due to future sea level rise is not considered in the scenario. Panel (b) projected median probability in the year 2040 for extreme water levels resulting from a combination of mean sea level rise, tides and storm surges, which have a historical 1% average annual probability. A peak-over-threshold (99.7%) method was applied to the historical tide gauge observations available in the Global Extreme Sea Level Analysis version 2 database, which is the same information as WGI Figure 9.32, except here the panel uses relative sea level projections under SSP2-4.5 for the year 2040 instead of 2050 The absence of a circle indicates an inability to perform an assessment due to a lack of data, but does not indicate absence of increasing frequencies. Panel (c) Climate hazards can initiate risk cascades that affect multiple sectors and propagate across regions following complex natural and societal connections. This example of a compound heat wave and a drought event striking an agricultural region shows how multiple risks are interconnected and lead to cascading biophysical, economic, and societal impacts even in distant regions, with vulnerable groups such as smallholder farmers, children and pregnant women particularly impacted.

WGI Figure 9.32 WGII SPM B4.3 WGII SPM B1.3 WGII SPM B.5.1 WGII TS Figure TS.9 WGII TS Figure TS.10 (c) WGII Fig 5.2 WGII TS.B.2.3 WGII TS.B.2.3 WGII TS.B.3.3 WGII 9.11.1.2

4.4.k

94System transitions involve a wide portfolio of mitigation and adaptation options that enable deep emissions reductions and transformative adaptation in all sectors. This report has a particular focus on the following system transitions: energy; industry; cities, settlements and infrastructure; land, ocean, food and water; health and nutrition; and society, livelihood and economies

WGII SPM A. WGII SPM Figure SPM.1 WGII SPM Figure SPM.4 SR1.5 SPM C.2

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. Migration, when voluntary, safe and orderly, allows reduction of risks to climatic and non-climatic stressors. 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. Relative potentials and costs will vary by place, context and time and in the longer term compared to 2030. Costs are net lifetime discounted monetary costs of avoided greenhouse gas emissions calculated relative to a reference technology. The potential (horizontal axis) is the quantity of net GHG emission reduction 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 mitigation potentials are assessed independently for each option and are not necessarily 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. The length of the solid bars represents the mitigation potential of an option. 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. The uncertainty in the total potential is typically 25–50%. When interpreting this figure, the following should be taken into account: (1) 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; (2) Different options have different feasibilities beyond the cost aspects, which are not reflected in the figure; and (3) Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included.

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).

WGII SPM Figure SPM 4 WGII Cross-Chapter Box FEASIB in Chapter 18 WGIII SPM C.10 WGIII Chapter 12.2.1 WGIII Chapter 12.2.2 WGIII Figure SPM 6 WGIII SPM Figure SPM 7

4.6.f

Figure 4.5: Potential synergies and trade-offs between the portfolio of climate change mitigation and adaptation options and the Sustainable Development Goals (SDGs). This figure presents a high-level summary of potential synergies and trade-offs assessed in WGII Figure SPM.4b and WGIII Figure SPM.8, based on the qualitative and quantitative assessment of each individual mitigation or option. The SDGs serve as an analytical framework for the assessment of different sustainable development dimensions, which extend beyond the time frame of 2030 SDG targets. Synergies and trade-offs across all individual options within a sector/system are aggregated into sector/system potentials for the whole mitigation or adaptation portfolio.

The length of each bar represents the total number of mitigation or adaptation options under each system/sector. The number of adaptation and mitigation options vary across system/sector, and have been normalised to 100% so that bars are comparable across mitigation, adaptation, system/sector, and SDGs. Positive links shown in WGII Figure SPM 4b and WGIII Figure SPM 8 are counted and aggregated to generate the percentage share of synergies, represented here by the blue proportion within the bars. Negative links shown in WGII Figure SPM 4b and WGIII Figure SPM 8 are counted and aggregated to generate the percentage share of trade-offs and is represented by orange proportion within the bars. ‘Both synergies and trade-offs’ shown in WGII Figure SPM 4b WGIII Figure SPM 8 are counted and aggregated to

‘white’ proportion within the bar indicates limited evidence/ no evidence/ not assessed.

Energy systems comprise all mitigation options listed in WGIII Figure SPM.8 and WGII Figure SPM.4b for adaptation. Urban and infrastructure comprises all mitigation options listed in WGIII Figure SPM.8 under Urban systems, under Buildings and under Transport and adaptation options listed in WGII Figure SPM.4b under Urban and infrastructure systems. Land system comprises mitigation options listed in WGIII Figure SPM.8 under AFOLU and adaptation options listed in WGII Figure SPM.4b under Land and ocean systems: forest-based adaptation, agroforestry, biodiversity management and ecosystem connectivity, improved cropland management, efficient livestock management, water use efficiency and water resource management. Ocean ecosystems comprises adaptation options listed in WGII Figure SPM.4b under Land and ocean systems: coastal defence and hardening, integrated coastal zone management and sustainable aquaculture and fisheries. Society, livelihood and economies comprises adaptation options listed in WGII Figure SPM.4b under Cross-sectoral; Industry comprises all those mitigation options listed in WGIII Figure SPM.8 under Industry.

SDG 13 (Climate Action) is not listed because mitigation/ adaptation is being considered in terms of interaction with SDGs and not vice versa (SPM SR1.5 Figure SPM.4 caption). The bars denote the strength of the connection and do not consider the strength of the impact on the SDGs. The synergies and trade-offs differ depending on the context and the scale of implementation. Scale of implementation particularly matters when there is competition for scarce resources. For the sake of uniformity, we are not reporting the confidence levels because there is knowledge gap in adaptation option wise relation with SDGs and their confidence level which is evident from WGII fig SPM 4b.

WGII Figure SPM.4b WGIII Figure SPM.8

4.8.1.f

Figure 4.6: Breakdown of average mitigation investment flows and investment needs until 2030 (USD billion). Mitigation investment flows and investment needs by sector (energy efficiency, transport, electricity, and agriculture, schemes for countries and areas). The blue bars display data on mitigation investment flows for four years: 2017, 2018, 2019 and 2020 by sector and by type of economy. For the regional breakdown, the annual average mitigation investment flows for 2017

–

2019 are shown. The grey bars show the minimum and maximum level of global annual mitigation investment needs in the assessed scenarios. This has been averaged until 2030. The multiplication factors show the ratio of global average early mitigation investment needs (averaged until 2030) and current yearly mitigation flows (averaged for 2017/18–2020). The lower multiplication factor refers to the lower end of the range of investment needs. The upper multiplication factor refers to the upper range of investment needs. Given the multiple sources and lack of harmonised methodologies, the data can be considered only if indicative of the size and pattern of investment needs.

WGIII Figure TS.25 WGIII Sections 15.3 15.4 15.5 Table 15.2 Table 15.3 Table 15.4