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1    Table of Contents
3    Chapter 1 Introduction and Framing .................................................................................................... 1-1
4       Executive Summary ......................................................................................................................... 1-4
5       1.1       Introduction .......................................................................................................................... 1-6
6       1.2       Previous Assessments .......................................................................................................... 1-7
7          1.2.1         Key findings from Previous Assessment Reports ........................................................ 1-7
8          1.2.2         Developments in Climate Science, Impacts and Risk .................................................. 1-9
9       1.3       The Multilateral Context, Emission Trends and Key Developments................................. 1-10
10         1.3.1         The 2015 Agreements ................................................................................................ 1-10
11         1.3.2         Global and regional emissions ................................................................................... 1-13
12         1.3.3         Some Other Key Trends and Developments .............................................................. 1-17
13         Cross-chapter Box 1: The COVID-19 crisis: lessons, risks and opportunities for mitigation ... 1-17
14      1.4       Drivers and Constraints of Climate Mitigation and System Transitions/Transformation.. 1-22
15         1.4.1         Services, sectors and urbanisation.............................................................................. 1-22
16         1.4.2         Trade, consumption and leakage ................................................................................ 1-23
17         1.4.3         Technology ................................................................................................................ 1-24
18         1.4.4         Finance and investment .............................................................................................. 1-26
19         1.4.5         Political economy....................................................................................................... 1-28
20         1.4.6         Equity and fairness ..................................................................................................... 1-29
21         1.4.7         Social innovation and behaviour change.................................................................... 1-29
22         1.4.8         Policy impacts ............................................................................................................ 1-30
23         1.4.9         Legal framework and institutions............................................................................... 1-31
24         1.4.10        International cooperation ........................................................................................... 1-32
25      1.5       Emissions Scenarios and Illustrative Mitigation Pathways (IMPs) ................................... 1-34
26      1.6       Achieving mitigation in the context of sustainable development ...................................... 1-38
27         1.6.1         The Climate Change and Development Connection .................................................. 1-38
28         1.6.2         Concepts and frameworks for integrating climate mitigation and development: ...... 1-39
29         1.6.3         Climate Mitigation, Equity and the Sustainable Development Goals (SDGs)........... 1-41
30      1.7       Four Analytic Frameworks for understanding mitigation response strategies ................... 1-44
31         1.7.1         Aggregated approaches: economic efficiency and global dynamics of mitigation .... 1-44
32         1.7.2         Ethical approaches ..................................................................................................... 1-47
33         1.7.3         Transition and transformation processes .................................................................... 1-49
34         1.7.4         Approaches from psychology and politics of changing course.................................. 1-52
35      1.8       Feasibility and multi-dimensional assessment of mitigation ............................................. 1-55
36         1.8.1         Building on the SR1.5 assessment framework: feasibility and enabling conditions.. 1-55

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1         1.8.2          Illustrations of multi-dimensional assessment: lock-in, policies and Just Transition 1-57
2      1.9        Governing climate change ................................................................................................. 1-59
3      1.10       Conclusions ........................................................................................................................ 1-61
4      1.11       Knowledge gaps ................................................................................................................. 1-62
5      1.12       Roadmap to the Report ...................................................................................................... 1-63
6      Frequently Asked Questions (FAQs) ............................................................................................. 1-64
7      References ...................................................................................................................................... 1-66



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1    Executive Summary
 2   Global greenhouse gas (GHG) emissions continued to rise to 2019: the aggregate reductions
 3   implied by current Nationally Determined Contributions (NDCs) to 2030 would still make it
 4   impossible to limit warming to 1.5°C with no or limited overshoot, and would only be compatible
 5   with likely limiting warming below 2°C if followed by much steeper decline, hence limiting
 6   warming to either level implies accelerated mitigation actions at all scales (robust evidence, high
 7   agreement). Since the IPCC’s Fifth Assessment Report (AR5), important changes that have emerged
 8   include the specific objectives established in the Paris Agreement of 2015 (for temperature, adaptation
 9   and finance), rising climate impacts, and higher levels of societal awareness and support for climate
10   action. The growth of global GHG emissions has slowed over the past decade, and delivering the
11   updated NDCs to 2030 would turn this into decline, but the implied global emissions by 2030 exceed
12   pathways consistent with 1.5°C by a large margin, and are near the upper end of the range of modelled
13   pathways which keep temperatures likely below 2°C. Continuing investments in carbon-intensive
14   activities at scale will heighten the multitude of risks associated with climate change and impede societal
15   and industrial transformation towards low carbon development. Meeting the long-term temperature
16   objective in the Paris Agreement therefore implies a rapid turn to an accelerating decline of GHG
17   emissions towards ‘net zero’, which is implausible without urgent and ambitious action at all scales.
18   The unprecedented COVID-19 pandemic has had far-reaching impacts on the global economic and
19   social system, and recovery will present both challenges and opportunities for climate mitigation. {1.2,
20   1.3, 1.5, 1.6, Chapters 3 and 4}.
21   While there are some trade-offs, effective and equitable climate policies are largely compatible
22   with the broader goal of sustainable development and efforts to eradicate poverty as enshrined in
23   the 17 Sustainable Development Goals (SDGs) (robust evidence, high agreement). Climate mitigation
24   is one of many goals that societies pursue in the context of sustainable development, as evidenced by
25   the wide range of the SDGs. Climate mitigation has synergies and/or trade-offs with many other SDGs.
26   There has been a strong relationship between development and GHG emissions, as historically both per
27   capita and absolute emissions have risen with industrialisation. However, recent evidence shows
28   countries can grow their economies while reducing emissions. Countries have different priorities in
29   achieving the SDGs and reducing emissions as informed by their respective national conditions and
30   capabilities. Given the differences in GHG emissions contributions, degree of vulnerabilities and
31   impacts, as well as capacities within and between nations, equity and justice are important
32   considerations for effective climate policy and for securing national and international support for deep
33   decarbonisation. Achieving sustainable global development and eradicating poverty as enshrined in the
34   17 SDGS would involve effective and equitable climate policies at all levels from local to global scale.
35   Failure to address questions of equity and justice over time can undermine social cohesion and stability.
36   International co-operation can enhance efforts to achieve ambitious global climate mitigation in the
37   context of sustainable development. {1.4, 1.6, Chapters 2, 3, 4, 5, 13 and 17}.
38   The transition to a low carbon economy depends on a wide range of closely intertwined drivers
39   and constraints, including policies and technologies where notable advances over the past decade
40   have opened up new and large-scale opportunities for deep decarbonisation, and for alternative
41   development pathways which could deliver multiple social and developmental goals (robust
42   evidence, medium agreement). Drivers for and constraints against low carbon societal transition
43   comprise economic and technological factors (the means by which services such as food, heating and
44   shelter are provided and for whom, the emissions intensity of traded products, finance, and investment),
45   socio-political issues (political economy, equity and fairness, social innovation and behaviour change),
46   and institutional factors (legal framework and institutions, and the quality of international cooperation).
47   In addition to being deeply intertwined all the factors matter to varying degrees, depending on prevailing

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1    social, economic, cultural and political context. They often exert both push and pull forces at the same
2    time, within and across different scales. The development and deployment of innovative technologies
3    and systems at scale are important for achieving deep decarbonisation. In recent years, the cost of
4    several low carbon technologies has declined sharply, alongside rapid deployment. Over twenty
5    countries have also sustained emission reductions, and many more have accelerated energy efficiency
6    and/or land-use improvements. Overall, however the global contribution is so far modest, at a few
7    billion tonnes (tCO2e) of avoided emissions annually. {1.3, 1.4, Chapters 2, 4,13,14}.
 8   Accelerating mitigation to prevent dangerous anthropogenic interference within the climate
 9   system will require the integration of broadened assessment frameworks and tools that combine
10   multiple perspectives, applied in a context of multi-level governance (robust evidence, medium
11   agreement). Analysing a challenge on the scale of fully decarbonising our economies entails integration
12   of multiple analytic frameworks. Approaches to risk assessment and resilience, established across IPCC
13   Working Groups, are complemented by frameworks for probing the challenges in implementing
14   mitigation. Aggregate Frameworks include cost-effectiveness analysis towards given objectives, and
15   cost-benefit analysis, both of which have been developing to take fuller account of advances in
16   understanding risks and innovation, the dynamics of emitting systems and of climate impacts, and
17   welfare economic theory including growing consensus on long-term discounting. Ethical frameworks
18   consider the fairness of processes and outcomes which can help ameliorate distributional impacts across
19   income groups, countries and generations. Transition and transformation frameworks explain and
20   evaluate the dynamics of transitions to low-carbon systems arising from interactions amongst levels,
21   with inevitable resistance from established socio-technical structures. Psychological, behavioural and
22   political frameworks outline the constraints (and opportunities) arising from human psychology and the
23   power of incumbent interests. A comprehensive understanding of climate mitigation must combine
24   these multiple frameworks. Together with established risk frameworks, collectively these help to
25   explain potential synergies and trade-offs in mitigation, imply a need for a wide portfolio of policies
26   attuned to different actors and levels of decision-making, and underpin ‘just transition’ strategies in
27   diverse contexts. {1.2.2, 1.7, 1.8}.
28   The speed, direction and depth of any transition will be determined by choices in the,
29   environmental, technological, economic, socio-cultural and institutional realms (robust evidence,
30   high agreement). Transitions in specific systems can be gradual or rapid and disruptive. The pace of a
31   transition can be impeded by ‘lock-in’ generated by existing physical capital, institutions, and social
32   norms. The interaction between power, politics and economy is central in explaining why broad
33   commitments do not always translate to urgent action. At the same time, attention to and support for
34   climate policies and low carbon societal transition has generally increased, as the impacts have become
35   more salient. Both public and private financing and financial structures strongly affect the scale and
36   balance of high and low carbon investments. COVID-19 has strained public finances, and integrating
37   climate finance into ongoing recovery strategies, nationally and internationally, can accelerate the
38   diffusion of low carbon technologies and also help poorer countries to minimise future stranded assets.
39   Societal & behavioural norms, regulations and institutions are essential conditions to accelerate low
40   carbon transitions in multiple sectors, whilst addressing distributional concerns endemic to any major
41   transition. {1.3.3, Cross-Chapter Box 1 in this chapter, 1.4, 1.8, Chapters 2-4 and 15}.
42   Achieving the global transition to a low-carbon, climate-resilient and sustainable world requires
43   purposeful and increasingly coordinated planning and decisions at many scales of governance
44   including local, subnational, national and global levels (robust evidence, high agreement).
45   Accelerating mitigation globally would imply strengthening policies adopted to date, expanding the
46   effort across options, sectors, and countries, and broadening responses to include more diverse actors
47   and societal processes at multiple – including international – levels. Effective governance of climate
48   change entails strong action across multiple jurisdictions and decision-making levels, including regular

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1    evaluation and learning. Choices that cause climate change as well as the processes for making and
2    implementing relevant decisions involve a range of non-nation state actors such as cities, businesses,
3    and civil society organisations. At global, national and subnational levels, climate change actions are
4    interwoven with and embedded in the context of much broader social, economic and political goals.
5    Therefore, the governance required to address climate change has to navigate power, political,
6    economic, and social dynamics at all levels of decision making. Effective climate-governing
7    institutions, and openness to experimentation on a variety of institutional arrangements, policies and
8    programmes can play a vital role in engaging stakeholders and building momentum for effective climate
9    action. {1.4, 1.9, Chapters 8, 15, 17}.

11   1.1 Introduction
12   This Report (WGIII) aims to assess new literature on climate mitigation including implications for
13   global sustainable development. In this Sixth Assessment Cycle the IPCC has also published three
14   Special Reports1 all of which emphasise the rising threat of climate change and the implications for
15   more ambitious mitigation efforts at all scales. At the same time, the Paris Agreement (PA) and the UN
16   2030 Agenda for Sustainable Development with its 17 Sustainable Development Goals (SDGs), both
17   adopted in 2015, set out a globally agreed agenda within which climate mitigation efforts must be
18   located. Along with a better understanding of the physical science basis of climate change (AR6 WGI),
19   and vulnerabilities, impacts, and adaptation (AR6 WGII), the landscape of climate mitigation has
20   evolved substantially since Fifth Assessment Report (AR5).
21   Since AR5, (IPCC 2014a) climate mitigation policies around the world have grown in both number
22   and shape (Chapter 13). However, while the average rate of annual increase of CO2 emissions has
23   declined (Section 1.3.2) GHG emissions globally continued to rise, underlining the urgency of the
24   mitigation challenge (Chapters 2, 3). Over twenty countries have cut absolute emissions alongside
25   sustained economic growth, but the scale of mitigation action across countries remains varied and
26   generally much slower than the pace required to meet the goals of the Paris Agreement (Section 1.3.2
27   in this chapter and Section 2.7.2 in Chapter 2). Per-capita GHG emissions between countries even at
28   similar stages of economic development (based on GDP per capita) vary by a factor of three (Figure
29   1.6) and by more than two on consumption basis (Section 2.3 in Chapter 2).
30   The Special Report on 1.5oC underlined that humanity is now living with the “unifying lens of the
31   Anthropocene” (SR 1.5 IPCC 2018a, 52 & 53), that requires a sharpened focus on the impact of human
32   activity on the climate system and the planet more broadly given ‘planetary boundaries’ (Steffen et al.
33   2015) including interdependencies of climate change and biodiversity (Dasgupta 2021). Recent
34   literature assessed by WGs I and II of this AR6 underlines the urgency of climate action as cumulative
35   CO2 emissions, along with other greenhouses gases, drives the temperature change. Across AR6, global
36   temperature changes are defined relative to the period 1850-1900, as in SR1.5 and collaboration with
37   WGI enabled the use of AR6-calibrated emulators to assure consistency across the three Working
38   Groups. The remaining ‘carbon budgets’ (see Annex I) associated with 1.5°C and 2°C temperature
39   targets equate to about one (for 1.5°C) to three (for 2°C) decades of current emissions, as from 2020,
40   but with significant variation depending on multiple factors including other gases (Figure 2.7 in Chapter

     FOOTNOTE1 These are the ‘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’ (hereafter SR1.5, 2018) (IPCC
     2018b); the ‘Special Report on Climate Change and Land’ (SRCCL) (IPCC 2019c); and the ‘Special Report on
     the Ocean and Cryosphere in a Changing Climate’ (SROCC) (IPCC 2019b).

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1    2; Cross-Working Group Box 1 in Chapter 3). For an outline of the WGIII approach to mitigation
2    scenarios, emission pathways implied by the Paris goals, and timing of peak and ‘net zero’ (Annex I
3    and FAQ 1.3), see Section 1.5, and Chapter 3.
4    Strong differences remain in responsibilities for, and capabilities to, take climate action within and
5    between countries. These differences, as well as differences in the impact of climate change, point to
6    the role of collective action in achieving urgent and ambitious global climate mitigation in the context
7    of sustainable development, with attention to issues of equity and fairness as highlighted in several
8    chapters of the report (Chapters 4, 5, 14, 15, 17).
 9   Innovation and industrial development of key technologies in several relevant sectors have transformed
10   prospects for mitigation at much lower cost than previously assessed (Chapters 2 and 6–12). Large
11   reductions in the cost of widely-available renewable energy technologies, along with energy efficient
12   technologies and behavioural changes (Chapters 5 and 9–11), can enable societies to provide services
13   with much lower emissions. However, there are still significant differences in the ability to access and
14   utilise low carbon technologies across the world (Chapter 4, 15, 16). New actors, including cities,
15   businesses, and numerous non-state transnational alliances have emerged as important players in the
16   global effort to tackle climate change (Chapters 13–16).
17   Along with continued development of concepts, models and technologies, there have been numerous
18   insights from both the successes and failures of mitigation action that can inform future policy design
19   and climate action. However, to date, policies and investments are still clearly inadequate to put the
20   world in line with the PA’s aims (Chapters 13, 15).
21   The greater the inertia in emission trends and carbon-intensive investments, the more that CO2 will
22   continue to accumulate (Hilaire et al. 2019; IPCC 2019a). Overall, the literature points to the need for
23   a more dynamic consideration of intertwined challenges concerning the transformation of key GHG
24   emitting systems: to minimise the trade-offs, and maximise the synergies, of delivering deep
25   decarbonisation whilst enhancing sustainable development.
26   This Chapter introduces readers to the AR6 WGIII Report and provides an overview of progress and
27   challenges, in three parts. Part A, introduces the climate mitigation challenge, provides key findings
28   and developments since previous assessment, and reviews the main drivers for, and constraints against
29   accelerated climate action. Part B provides an assessment of the key frameworks for understanding the
30   climate mitigation challenge covering broad approaches like sustainable development and more specific
31   economic, political and ethical framings. Part C briefly highlights the role of governance for steering
32   and coordinating efforts to accelerate globally effective and equitable climate mitigation, notes the gaps
33   in knowledge that have been identified in the process of assessment and provides a road map to the rest
34   of the Report.

36   1.2    Previous Assessments
37   1.2.1 Key findings from Previous Assessment Reports
38   Successive WGIII IPCC Assessments have emphasised the importance of climate mitigation along with
39   the need to consider broader societal goals especially sustainable development. Key insights from AR5
40   and the subsequent three Special Reports (IPCC 2019b, 2018b, 2019c) are summarised below.
41   AR5 projected that in baseline scenarios (i.e. based on prevailing trends without explicit additional
42   mitigation efforts), Agriculture, Forestry and Other Land Uses (AFOLU) would be the only sector
43   where emissions could fall by 2100, with some CO2 removal (IPCC 2014b, p. 17). Direct CO2 emissions
44   from energy were projected to double or even triple by 2050 (IPCC 2014b, p. 20) due to global

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1    population and economic growth, resulting in global mean surface temperature increases in 2100 from
2    3.7°C to 4.8°C compared to pre-industrial levels. AR5 noted that mitigation effort and the costs
3    associated with ambitious mitigation differ significantly across countries, and in ‘globally cost-
4    effective’ scenarios, the biggest reductions (relative to projections) occur in the countries with the
5    highest future emissions in the baseline scenarios (IPCC 2014b, p. 17). Since most physical capital (e.g.
6    power plants, buildings, transport infrastructure) involved in GHG emissions is long-lived, the timing
7    of the shift in investments and strategies will be crucial (IPCC 2014b, p. 18).
 8   A key message from recent Special Reports is the urgency to mitigate GHG emissions in order to avoid
 9   rapid and potentially irreversible changes in natural and human systems (IPCC 2019b, 2018b, 2019a).
10   Successive IPCC reports have drawn upon increasing sophistication of modelling tools to project
11   emissions in the absence of ambitious decarbonisation action, as well as the emission pathways that
12   meet long term temperature targets. The SR1.5 examined pathways limiting warming to 1.5°C,
13   compared to historical baseline of 1850-1900, finding that “in pathways with no or limited overshoot
14   of 1.5°C, global net anthropogenic CO2 emissions decline by about 45% from 2010 levels by 2030,
15   reaching net zero around 2050” (2045–2055 interquartile range); with ‘overshoot’ referring to higher
16   temperatures, then brought down by 2100 through ‘net negative’ emissions. It found this would require
17   rapid and far-reaching transitions in energy, land, urban and infrastructure (including transport and
18   buildings), and industrial systems (high confidence) (IPCC 2018b).
19   SR1.5 found that the Nationally Determined Contributions (NDCs) as declared under the Paris
20   Agreement (PA) would not limit warming to 1.5 C; despite significant updates to NDCs in 2020/21,
21   this remains the case though delivery of these more ambition NDCs would somewhat enhance the
22   prospects for staying below 2°C (Section 1.3.3).
23   AR5 WGIII and the Special Reports analysed economic costs associated with climate action. The
24   estimates vary widely depending on the assumptions made as to how ordered the transition is,
25   temperature target, technology availability, the metric or model used, among others (Chapter 6).
26   Modelled direct mitigation costs of pathways to 1.5°C, with no/limited overshoot, span a wide range,
27   but were typically 3-4 times higher than in pathways to 2°C (high confidence), before taking account
28   of benefits, including significant reduction in loss of life and livelihoods, and avoided climate impacts
29   (IPCC 2018b).
30   Successive IPCC Reports highlight a strong connection between climate mitigation and sustainable
31   development. Climate mitigation and adaptation goals have synergies and trade-offs with efforts to
32   achieve sustainable development, including poverty eradication. A comprehensive assessment of
33   climate policy therefore involves going beyond a narrow focus on specific mitigation and adaptation
34   options to incorporate climate issues into the design of comprehensive strategies for equitable
35   sustainable development. At the same time, some climate mitigation policies can run counter to
36   sustainable development and eradicating poverty, which highlights the need to consider trade-offs
37   alongside benefits. Examples include synergies between climate policy and improved air quality,
38   reducing premature deaths and morbidity (IPCC 2014b Fig SPM.6; AR6 WG1 sections 6.6.3 and 6.7.3),
39   but there would be trade-offs if policy raises net energy bills, with distributional implications. The
40   Special Report on Climate Change and Land (SRCCL) also emphasises important synergies and trade-
41   offs, bringing new light on the link between healthy and sustainable food consumption and emissions
42   caused by the agricultural sector. Land-related responses that contribute to climate change adaptation
43   and mitigation can also combat desertification and land degradation and enhance food security (IPCC
44   2019a).
45   Previous ARs have detailed the contribution of various sectors and activities to global GHG emissions.
46   When indirect emissions (mainly from electricity, heat and other energy conversions) are included, the
47   four main consumption (end-use) drivers are industry, AFOLU, buildings and transport (Chapter 2,

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1    Figure 2.14), though the magnitude of these emissions can vary widely between countries. These –
2    together with the energy and urban systems which feed and shape end-use sectors – define the sectoral
3    chapters in this AR6 WGIII report.
4    Estimates of emissions associated with production and transport of internationally traded goods were
5    first presented in AR5 WGIII, which estimated the ‘embodied emission transfers’ from upper-middle-
6    income countries to industrialised countries through trade at about 10 percent of CO2 emissions in each
7    of these groups (IPCC 2014a Fig TS.5). The literature on this and discussion on their accounting has
8    grown substantially since then (Chapters 2 & 8).
 9   The atmosphere is a shared global resource and an integral part of the “global commons”. In the
10   depletion/restoration of this resource, myriad actors at various scales are involved, for instance,
11   individuals, communities, firms and states. Inter alia, international cooperation to tackle ozone
12   depletion and acid rain offer useful examples. AR5 noted that greater cooperation would ensue if
13   policies are perceived as fair and equitable by all countries along the spectrum of economic
14   development–implying a need for equitable sharing of the effort. A key takeaway from AR5 is that
15   climate policy involves value judgement and ethics. (IPCC 2014a Box TS.1 “People and countries have
16   rights and owe duties towards each other. These are matters of justice, equity, or fairness. They fall
17   within the subject matter of moral and political philosophy, jurisprudence, and economics.” p. 37).
18   International cooperation and collective action on climate change alongside local, national, regional and
19   global policies will be crucial to solve the problem, and this report notes cooperative approaches beyond
20   simple ‘global commons’ framings (Chapters 13, 14).
21   AR5 (all Working Group Reports) also underlined that climate policy inherently involves risk and
22   uncertainty (in nature, economy, society and individuals). To help evaluate responses, there exists a rich
23   suite of analytical tools, for example, cost-benefit analysis, cost-effectiveness analysis, multi-criteria
24   analysis, expected utility theory and catastrophe and risk models. All have pros and cons, and have been
25   further developed in subsequent literature and AR6 (next section).
26   Recent Assessments (IPCC 2014a, 2018b) began to consider the role of individual behavioural choices
27   and cultural norms in driving energy and food patterns. Notably, SR1.5 (Section 4.4.3 in Chapter 4)
28   outlined emerging evidence on the potential for changes in behaviour, lifestyle and culture to contribute
29   to decarbonisation (and lower the cost); for the first time, AR6 devotes a whole chapter (Chapter 5) to
30   consider these and other underlying drivers of energy demand, food choices and social aspects.
31   1.2.2 Developments in Climate Science, Impacts and Risk
32   The assessment of the Physical Science Basis (IPCC WGI AR6) documents sustained and widespread
33   changes in the atmosphere, cryosphere, biosphere and ocean, providing unequivocal evidence of a world
34   that has warmed, associated with rising atmospheric CO2 concentrations reaching levels not experienced
35   in at least the last 2 million years. Aside from temperature, other clearly discernible, human-induced
36   changes beyond natural variations include declines in Arctic Sea ice and glaciers, thawing of
37   permafrost, and a strengthening of the global water cycle (WG1 SPM A.2, B.3 and B.4). Oceanic
38   changes include rising sea level, acidification, deoxygenation, and changing salinity (WG1 SPM B.3).
39   Over land, in recent decades, both frequency and severity have increased for hot extremes but decreased
40   for cold extremes; intensification of heavy precipitation is observed in parallel with a decrease in
41   available water in dry seasons, along with an increased occurrence of weather conditions that promote
42   wildfires.
43   In defining the objective of international climate negotiations as being to ‘prevent dangerous
44   anthropogenic interference’ (Article 2 UNFCCC 1992), the UNFCCC underlines the centrality of risk
45   framing in considering the threats of climate change and potential response measures. Against the
46   background of ‘unequivocal’ (AR4) evidence of human-induced climate change, and the growing

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1    experience of direct impacts, the IPCC has sought to systematise a robust approach to risk and risk
2    management.
 3   In AR6 the IPCC employs a common risk framing across all three working groups and provides
 4   guidance for more consistent and transparent usage (AR6 WGI Cross-Chapter Box 3 in Chapter 1; AR6
 5   WGII 1.4.1; IPCC risk guidance). AR6 defines risk as “the potential for adverse consequences for
 6   human or ecological systems, recognising the diversity of values and objectives associated with such
 7   systems” (Annex I), encompassing risks from both potential impacts of climate change and human
 8   responses to it (Reisinger et al. 2020). The risk framing includes steps for identifying, evaluating, and
 9   prioritising current and future risks; for understanding the interactions among different sources of risk;
10   for distributing effort and equitable sharing of risks; for monitoring and adjusting actions over time
11   while continuing to assess changing circumstances; and for communications among analysts, decision-
12   makers, and the public.
13   Climate change risk assessments face challenges including a tendency to mis-characterise risks and pay
14   insufficient attention to the potential for surprises (Weitzman 2011; Aven and Renn 2015; Stoerk et al.
15   2018). Concepts of resilience and vulnerability provide overlapping, alternative entry points to
16   understanding and addressing the societal challenges caused and exacerbated by climate change (AR6,
17   WGII, Chapter 1.2.1).
18   AR6 WGII devotes a full chapter (17) to ‘Decision-Making Options for Managing Risk’, detailing the
19   analytic approaches and drawing upon the Cynefin classification of Known, Knowable, Complex and
20   Chaotic systems (17.3.1). With deep uncertainty, risk management often aims to identify specific
21   combinations of response actions and enabling institutions that increase the potential for favourable
22   outcomes despite irreducible uncertainties (AR6 WGII Chapter 17 Cross-Chapter Box DEEP; also
23   (Marchau et al. 2019; Doukas and Nikas 2020).
24   Literature trying to quantify the cost of climate damages has continued to develop. Different
25   methodologies systematically affect outcomes, with recent estimates based on empirical approaches –
26   econometric measurements based on actual impacts – ‘categorically higher than estimates from other
27   approaches’ (Cross-Working Group Box ECONOMIC in WGII Chapter 16, Section 16.6.2). This, along
28   with other developments strengthen foundations for calculating a ‘social cost of carbon’. This informs
29   a common metric for comparing different risks and estimating benefits compared to the costs of GHG
30   reductions and other risk-reducing options (Section 1.7.1); emissions mitigation itself also involves
31   multiple uncertainties, which alongside risks can also involve potential opportunities (Section 1.7.3).
32   Simultaneously, the literature increasingly emphasises the importance of multi-objective risk
33   assessment and management (e.g., representative key risks in WGII Chapter 16), which may or may
34   not correlate with any single estimate of economic value (AR6 WGII 1.4.1; IPCC risk guidance). Given
35   the deep uncertainties and risks, the goals established (notably in the Paris Agreement and SDGs) reflect
36   negotiated outcomes informed by the scientific assessment of risks.

38   1.3    The Multilateral Context, Emission Trends and Key Developments

39   Since AR5, there have been notable multilateral efforts which help determine the context for current
40   and future climate action. This section summarises key features of this evolving context.

41   1.3.1 The 2015 Agreements
42   In 2015 the world concluded four major agreements that are very relevant to climate action. These
43   include: the Paris Agreement under the 1992 United Nations Framework Convention on Climate

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1    Change (UNFCCC), the UN agreements on Disaster Risk Reduction (Sendai) and Finance for
2    Development (Addis Ababa), and the Sustainable Development Goals (SDGs).
3    The Paris Agreement (PA). The Paris Agreement aims to “hold the increase in the global average
4    temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature
5    increase to 1.5°C above pre-industrial levels” (UNFCCC 2015), alongside goals for adaptation (IPCC
6    WGII), and ‘aligning financial flows’ (below) , so as “to strengthen the global response to the threat of
7    climate change, in the context of sustainable development and efforts to eradicate poverty.”
 8   The Paris Agreement is predicated on encouraging progressively ambitious climate action from all
 9   countries on the basis of Nationally Determined Contributions (Rajamani 2016; Clémençon 2016). The
10   NDC approach requires countries to set their own level of ambitions for climate change mitigation but
11   within a collaborative and legally binding process to foster ambition towards the agreed goals (Falkner
12   2016a; Bodansky 2016). The PA entered into force in November 2016 and as of February 2021 it has
13   190 Parties (out of 197 Parties to the UNFCCC).
14   The PA also underlines “the principle of common but differentiated responsibilities and respective
15   capabilities, in the light of different national circumstances” (PA Article 2 para 2), and correspondingly
16   that “developed country Parties should continue taking the lead by undertaking economy-wide absolute
17   emission reductions”. It states that developing country Parties should continue enhancing their
18   mitigation efforts, and are encouraged to move over time towards economy-wide emission reduction or
19   limitation targets in the light of different national circumstances.
20   The Paris Agreement’s mitigation goal implies “to achieve a balance between anthropogenic emissions
21   by sources and removals by sinks of greenhouse gases in the second half of this century” (PA Article 4
22   para 1). The Paris Agreement provides for 5-yearly stocktakes in which Parties have to take collective
23   stock on progress towards achieving its purposes and its long-term goal in the light of equity and
24   available best science (PA Article 14). The first global stocktake is scheduled for 2023. (PA Article 14
25   para 3).
26   The Paris Agreement aims to make ‘finance flows consistent with a pathway towards low greenhouse
27   gas emissions and climate-resilient development’ (PA Article 2.1C). In keeping with the acknowledged
28   context of global sustainable development and poverty eradication, and the corresponding aims of
29   aligning finance and agreed differentiating principles as indicated above, “…the developed country
30   parties are to assist developing country parties with financial resources” (PA Article 9). The Green
31   Climate Fund (GCF), an operating entity of the UNFCCC Financial Mechanism to finance mitigation
32   and adaptation efforts in developing countries (GCF 2020), was given an important role in serving the
33   Agreement and supporting PA goals.. The GCF gathered pledges worth USD 10.3 billion, from
34   developed and developing countries, regions, and one city (Paris) (Antimiani et al. 2017; Bowman and
35   Minas 2019). Financing has since increased but remains short of the goal to mobilise USD100 billion
36   by 2020 (Chapter 15).
37   Initiatives contributing to the Paris Agreement goals include the Non-State Actor Zone for Climate
38   Action (NAZCA or now renamed as Global Climate Action) portal, launched at COP20 (December
39   2014) in Lima, Peru, to support city-based actions for mitigating climate change (Mead 2015) and
40   Marrakech Partnership for Global Climate Action which is a UNFCCC-backed series of events intended
41   to facilitate collaboration between governments and the cities, regions, businesses and investors that
42   must act on climate change.
43   Details of the Paris Agreement, evaluation of the Kyoto Protocol, and other key multilateral
44   developments since AR5 relevant to climate mitigation including the CORSIA aviation agreement
45   adopted under ICAO, the IMO shipping strategy, and the Kigali Amendment to the Montreal Protocol
46   on HFCs, are discussed in Chapter 14.

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 1   SDGs. In September 2015, the UN endorsed a universal agenda – ‘Transforming our World: the 2030
 2   Agenda for Sustainable Development’. The agenda adopted 17 non-legally-binding SDGs and 169
 3   targets to support people, peace, prosperity, partnerships and the planet. While climate change is
 4   explicitly listed as SDG13, the pursuit of the implementation of the UNFCCC is relevant for a number
 5   of other goals including SDG 7 (clean energy for all), 9 (sustainable industry), and 11 (sustainable
 6   cities), 12 (responsible consumption and production) as well as those relating to life below water (14)
 7   and on land (15) (Biermann et al. 2017). Mitigation actions could have multiple synergies and trade-
 8   offs across the SDGs (Chapter 17; Pradhan et al. 2017) and their net effects depend on the pace and
 9   magnitude of changes, the specific mitigation choices and the management of the transition. This
10   suggests that mitigation must be pursued in the broader context of sustainable development as explained
11   in Section 1.6
12   Finance. The Paris Agreement’s finance goal (above) reflects a broadened focus, beyond the costs of
13   climate adaptation and mitigation, to recognising that a structural shift towards low carbon climate-
14   resilient development pathways requires large scale investments that engage the wider financial system
15   (15.1 and 15.2.4). The SR1.5C report estimated that 1.5oC pathways would require increased investment
16   of 0.5-1% of global GDP between now and 2050, which is up to 2.5% of global savings / investment
17   over the period. For low- and middle-income countries, SDG-compatible infrastructure investments in
18   the most relevant sectors are estimated to be around 4-5% of their GDP, and ‘infrastructure investment
19   paths compatible with full decarbonisation in the second half of the century need not cost more than
20   more-polluting alternatives’ (Rozenberg and Fay 2019).
21   The parallel 2015 UN Addis Ababa Conference on Finance for Development, and its resulting Action
22   Agenda, aims to ‘address the challenge of financing … to end poverty and hunger, and to achieve
23   sustainable development in its three dimensions through promoting inclusive economic growth,
24   protecting the environment, and promoting social inclusion.’ The Conference recognises the significant
25   potential of regional co-operation and provides a forum for discussing the solutions to common
26   challenges faced by developing countries (15.6.4).
27   Alongside this, private and blended climate finance is increasing but is still short of projected
28   requirements consistent with Paris Agreement goals ( The financing gap is particularly acute
29   for adaptation projects, especially in vulnerable developing countries. From a macro-regulatory
30   perspective, there is growing recognition that substantial financial value may be at risk from changing
31   regulation and technology in a low-carbon transition, with potential implications for global financial
32   stability (15.6.3). To date, the most significant governance development is the Financial Stability
33   Board’s Task Force on Climate-related Financial Disclosure (TCFD) and its recommendations that
34   investors and companies consider climate change risks in their strategies and capital allocation, so
35   investors can make informed decisions (TCFD 2018), welcomed by over 500 financial institutions and
36   companies as signatories, albeit with patchy implementation (1.4. 4; 15.6.3).
37   Talanoa Dialogue and Just Transition. As mandated at Paris COP21 and launched at COP23, the
38   ‘Talanoa Dialogue’ (UNFCCC 2018a) emphasised holistic approaches across multiple economic
39   sectors for climate change mitigation. At COP24 also, the Just Transition Silesia Declaration, focusing
40   on the need to consider social aspects in designing policies for climate change mitigation was signed
41   by 56 heads of state (UNFCCC 2018b). This underlined the importance of aiming for a ‘just transition’
42   in terms of reducing emissions, at the same time preserving livelihoods and managing economic risks
43   for countries and communities that rely heavily on emissions-intensive technologies for domestic
44   growth (Markkanen and Anger-Kraavi 2019), and for maintaining ecosystem integrity through nature-
45   based solutions.

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1    1.3.2 Global and regional emissions
 2   Global GHG emissions have continued to rise since AR5, though the average rate of emissions growth
 3   slowed, from 2.4% (from 2000-2010) to 1.3% for 2010-2019 (Figure 1.1). After a period of
 4   exceptionally rapid growth from 2000 as charted in AR5, global fossil-fuel- and industry-related (FFI)
 5   CO2 emissions almost plateaued between 2014 and 2016 (while the global economy continued to
 6   expand (World Bank 2020), but increased again over 2017-19, the average annual growth rate for all
 7   GHGs since 2014 being around 0.8%% yr-1 (IPCC/EDGAR emissions database). Important driving
 8   factors include population and GDP growth, as illustrated in panels (b) and (c) respectively. The pause
 9   in emissions growth reflected interplay of strong energy efficiency improvements and low-carbon
10   technology deployment, but these did not expand fast enough to offset the continued pressures for
11   overall growth at global level (UNEP 2018a; IEA 2019a). However, since 2013/14, the decline in global
12   emissions intensity (GHG/GDP) has accelerated somewhat, and global emissions growth has averaged
13   slightly slower than population growth (Figure 1.1d), which if sustained would imply a peak of global
14   CO2 (GHG) emissions per-capita, at about 5tCO2/person (/7tCO2e/person) respectively.

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2                                     Figure 1.1: Global emission trends since 2000 by groups of gases: absolute, per-capita, and intensity
3   Note: Shows CO2 from fossil fuel combustion and industrial processes (FFI); CO 2 from Agriculture, Forestry and Other Land use (AFOLU); methane (CH4); nitrous oxide
4   (N2O); fluorinated gases (F-gases). Gases reported in Gt CO2eq converted based on AR6 global warming potentials with 100-year time horizon (GWP-100).

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1    Due to its much shorter lifetime, methane has disproportionate impact on near-term temperature, and is
2    estimated to account for almost a third of the warming observed to date (AR6 WG1 SPM; WG-III Chapter
3    2, Figure 2.4). Methane reductions could be particularly important in relation to near- and medium-term
4    temperatures, including through counteracting the impact of reducing short-lived aerosol pollutants which
5    have an average cooling effect.2

 6   The land-use component of CO2 emissions has different drivers and particularly large uncertainties (Chapter
 7   2, Figures 2.2, 2.5), hence is shown separately. Also, compared to AR5, new evidence showed that the
 8   AFOLU CO2 estimates by the global models assessed in this report are not necessarily comparable with
 9   national GHG inventories, due to different approaches to estimate the 'anthropogenic' CO2 sink. Possible
10   ways to reconcile these discrepancies are discussed in Chapter 7.

11   Regional trends have varied. Emissions from most countries continued to grow, but in absolute terms, 32
12   countries reduced energy-and-industry-CO2 emissions for at least a decade, and 24 reduced overall GHG
13   (CO2-eq) emissions over the same period, but only half of them by more than 10% over the period in each
14   case (Chapter 2).3 In total, developed country emissions barely changed from 2010, whilst those from the
15   rest of the world grew.

16   Figure 1.2 shows the distribution of regional CO2 (GHG emissions) (a) per capita and (b) per GDP based
17   on purchasing power parity (GDPppp) of different country groupings in 2019. Plotted against population and
18   GDP respectively, the area of each block is proportional to the region’s emissions. Compared to the
19   equivalent presentations in 2004 (AR4, SPM.3) and 2010 (AR5, Figure 1.8), East Asia now forms
20   substantially the biggest group, whilst at about 8(/10tCO2eq) per person, its emissions per-capita remain
21   about half that of north America. In contrast, a third of the world’s population, in southern Asia and Africa,
22   emit on average under 2 (2.5tCO2eq) per person, little more than in the previous Assessments. Particularly
23   for these regions there continue to be substantial differences in the GDP, life expectancy and other measures
24   of wellbeing (see Figure 1.6).

     FOOTNOTE2 Indeed, cooling effects of anthropogenic aerosols (organic carbon, black carbon, sulphates, nitrates),
     which are also important components of local air pollution (Myhre et al. 2013; WGI SPM D1.7) may in global average
     be of similar magnitude to warming from methane at present. Mitigation which reduces such aerosol masking could
     thereby increase global temperatures, and reducing methane emissions would offset this much more rapidly than
     reducing CO2 because of its relatively short lifetime, with the combined effects which could counterbalance each other
     (WGI SPM D1.7). Methane is thus particularly important in determining whether or when 1.5C is reached for

     FOOTNOTE 3 With some exclusions for countries which were very small or undergoing economic collapse: Energy-
     and Industry-CO2 emissions in 2018 were below 2010 levels in 32 developed countries, but only in 24 when including
     other GHGs. Reductions were by less than 10% in half these countries. Data from Chapter 2: see (2.2.3) and Figure
     2.11 for panel of countries that have sustained territorial emission reductions longer than 10 years, as analysed in
     Lamb et al. (2021), and decomposition analysis of national trends in Xia et al. (2021). The previously rising trend of
     ‘outsourced/embodied emissions’ associated with goods imported into developed countries peaked in 2006, but
     detailed data on this are only available EEI-CO2, to 2018 (Section 2.3 in Chapter 2). See Chapter 3 for reduction rates
     associated with 1.5 and 2°C.

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1    Emissions per unit GDP are much less diverse than per-capita, and have also converged significantly.
2    Poorer countries tend to show higher energy/ emissions per unit GDP partly because of higher reliance on
3    basic industries, and this remains the case, though in general their energy/GDP has declined faster.

4    Many developed country regions are net importers of energy-intensive goods, and emissions are affected
5    by the accounting of such ‘embodied emissions’. Panels (c) and (d) show results (only available for CO2,
6    to 2018) on the basis of consumption-footprints which include emissions embodied in traded goods. This
7    makes modest changes to the relative position of different regions (for further discussion see Chapter 2).

 9      Figure 1.1: Distribution of regional GHG emissions for 10 broad global regions according to territorial
10       accounting (panels a & b, GHG emissions) and consumption-based accounting (panels c & d, CO2-FFI
11                                                  emissions only).
12   GHG emissions are categorised into: Fossil fuel and industry (CO 2-FFI), Land use, land use change, forestry
13     (CO2-LULUCF) and other greenhouse gases (methane, nitrous oxide, Fgas - converted to 100-year global
14      warming potentials). Per-capita GHGs for territorial (panel a) and CO2-FFI emissions vs population for
15      consumption-based accounting (panel c). Panels b & d: GHG emissions per unit GDPppp vs GDPppp,
16      weighted with purchasing power parity for territorial accounting (panel b), CO2-FFI emissions per unit
17   GDPppp for consumption-based accounting (panel d). The area of the rectangles refers to the total emissions
18    for each regional category, with the height capturing per-capita emissions (panels a and c) or emissions per
19     unit GDPppp (panels b and d), and the width proportional to the population of the regions and GDPppp.
20      Emissions from international aviation and shipping (2.4% of the total GHG emissions) are not included.

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1    While extreme poverty has fallen in more than half of the world’s economies in recent years, nearly one-
2    fifth of countries faced poverty rates above 30% in 2015 (below USD1.90 a day), reflecting large income
3    inequality (Laborde Debucquet and Martin 2017; Rozenberg and Fay 2019). Diffenbaugh and Burke (2019)
4    find that global warming already has increased global economic inequality, even if between-country
5    inequalities have decreased over recent decade. The distributional implications between regional groups
6    of different in the ‘shared socioeconomic pathways (SSPs)’ diverge according to the scenario (Frame et al.
7    2019).

 8   An important recent development has been commitments by many countries, now covering a large majority
 9   of global emissions, to reach net zero CO2 or greenhouse gas emissions (Chapter 3).4 Furthermore, globally,
10   net zero targets (whether CO2 or GHG) have been adopted by about 823 cities and 101 regions (Chapter 8).

11   1.3.3 Some Other Key Trends and Developments
12   The COVID-19 pandemic profoundly impacted economy and human society, globally and within
13   countries. As detailed in Cross-Chapter Box 1, some of its impacts will be long lasting, permanent even,
14   and there are also lessons relevant to climate change. The direct impact on emissions projected for rest of
15   this decade are modest, but the necessity for economic recovery packages creates a central role for
16   government-led investment, and may change the economic fundamentals involved for some years to come.
17   The COVID-19 aftermath consequently also changes the economic context for mitigation (Sections 15.2
18   and 15.4 in Chapter 15). Many traditional forms of economic analysis (expressed as general equilibrium)
19   assume that available economic resources are fully employed, with limited scope for beneficial economic
20   ‘multiplier effects’ of government-led investment. After COVID-19 however, no country is in this state.
21   Very low interest rates amplify opportunities for large-scale investments which could bring ‘economic
22   multiplier’ benefits, especially if they help to build the industries and infrastructures for further clean
23   growth (Hepburn et al. 2020). However, the capability to mobilise low interest finance vary markedly across
24   countries and large public debts - including bringing some developing countries close to default - undermine
25   both the political appetite and feasibility of large-scale clean investments. In practice the current orientation
26   of COVID-19 recovery packages is very varied, pointing to a very mixed picture about whether or not
27   countries are exploiting this opportunity (Cross-Chapter Box 1).
30        Cross-chapter Box 1 The COVID-19 crisis: lessons, risks and opportunities for mitigation
31   Authors: Diana Ürge-Vorsatz (Hungary), Lilia Caiado Couto (Brazil), Felix Creutzig (Germany), Dipak
32   Dasgupta (India), Michael Grubb (United Kingdom), Kirsten Halsnaes (Denmark), Siir Kilkis (Turkey),
33   Alexandre Koberle (Brazil), Silvia Kreibiehl (Germany), Jan Minx (Germany), Peter Newman (Australia),
34   Chukwumerije Okereke (Nigeria/ United Kingdom)
35   The COVID-19 pandemic triggered the deepest global economic contraction as well as CO2 emission
36   reductions since the Second World War (Section in Chapter 2; AR6 WGI Box 6.1 in Chapter 6) (Le
37   Quéré et al. 2020b;). While emissions and most economies are expected to rebound in 2021-2022 (IEA
38   2021), some impacts of the pandemic (eg. aspects of economy, finance and transport-related emission

     FOOTNOTE4 Continually updated information on net-zero commitments is available at

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1    drivers) may last far longer. COVID-19 pushed more than 100 million people back into extreme poverty,
2    and reversed progress towards some other SDGs including health, life expectancy and child literacy (UN
3    DESA 2021). Health impacts and the consequences of deep economy-wide shocks may last many years
4    even without significant future recurrence (Section 15.6.3 in Chapter 15). These changes, as well as the
5    pandemic response actions, bring both important risks as well as opportunities for accelerating mitigation
6    (Chapters 1, 5, 10 and 15).
 7   Lessons. Important lessons can be drawn from the pandemic to climate change including the value of
 8   forward-looking risk management, the role of scientific assessment, preparatory action and international
 9   process and institutions (1.3, Chapter 5). There had been long-standing warnings of pandemic risks, and
10   precursors – with both pandemic and climate risks being identified by social scientists as ‘uncomfortable
11   knowledge’, or ‘unknown knowns’ which tend to be marginalised in practical policy (Rayner 2012;
12   Sarewitz 2020). This echoes long-standing climate literature on potential ‘high impact’ events, including
13   those perceived as low probability (Dietz 2011; Weitzman 2011). The costs of preparatory action, mainly
14   in those countries that had suffered from earlier pandemics were negligible in comparison, suggesting the
15   importance not just of knowledge but its effective communication and embodiment in society (Chapter 5).
16   (Klenert et al. 2020) offer five early lessons for climate policy, concerning: the cost of delay; the bias in
17   human judgement; the inequality of impacts; the need for multiple forms of international cooperation; and
18   finally, ‘transparency in value judgements at the science-policy interface’.
19   Emissions and behavioural changes. Overall, global CO2 FFI emissions declined by about 5.8% (5.1% to
20   6.3%) from 2019 to 2020, or about 2.2 (1.8-2.4) GtCO2 in total (Section 2.2.2 in Chapter 2). Analysis from
21   previous economic crises suggest significant rebound in emissions without policy-induced structural shifts
22   (; Figure 2.5) (Jaeger et al. 2020). Initial projections suggest the COVID aftermath may reduce
23   emissions by 4-5% over 2025 - 2030 (Shan and 2020; Reilly et al. 2021), below a ‘no-pandemic’
24   baseline The long-term impacts on behaviour, technology and associated emissions remain to be seen, but
25   may be particularly significant in transport - lockdowns reduced mobility-related emissions, alongside two
26   major growth areas: electronic communications replacing many work and personal travel requirements
27   (Section in Chapter 4 and Chapter 10); and, revitalised local active transport and e-micromobility
28   (Earley and Newman 2021). Temporary ‘clear skies’ may also have raised awareness of the potential
29   environment and health co-benefits of reduced fossil fuel use particularly in urban areas (Section 8.7 in
30   Chapter 8), with evidence also indicating that air pollution itself amplified vulnerability to COVID-19 (Wu
31   et al. 2020; Gudka et al. 2020). The significant impacts on passenger aviation are projected to extend not
32   just through behavioural changes, but also fleet changes from retiring older planes, and reduced new orders
33   indicating expectations of reduced demand and associated GHG emissions until 2030 (Section 5.1.2 in
34   Chapter 5 and Section 10.5 in Chapter 10; AR6 WGI Box 6.1 in Chapter 6). However, air cargo has
35   recovered more rapidly (IATA 2020), possibly enhanced by online ordering.
36   Fiscal, growth and inequality impacts. Aspects of the global and regional economic crises from COVID-
37   19 may prevail much longer than the crisis itself, potentially compromising mitigation. Most countries have
38   undertaken unprecedented levels of short-term public expenditures. The IMF projects sovereign debt to
39   GDP to have increased by 20% in advanced economies and 10% in emerging economies by the end of 2021
40   (IMF 2020). This is likely to slow economic growth, and may squeeze financial resources for mitigation
41   and relevant investments for many years to come (15.2.3, 15.6.3). COVID-19 further lowered interest rates
42   which should facilitate low carbon investment, but pandemic responses have increased sovereign debt
43   across countries in all income bands (IMF 2021), and particularly in some developing economies and
44   regions has caused debt distress (Bulow et al. 2021) widening the gap in developing countries’ access to

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1    capital (Hourcade et al. 2021b) (Section 15.6.3 in Chapter 15). After decades of global progress in reducing
2    poverty, COVID-19 has pushed hundreds of millions of people below poverty thresholds and raises the
3    spectre of intersecting health and climate crises that are devastating for the most vulnerable (5.1.2 Box 5.1).
4    Like those of climate change, pandemic impacts fall heavily on disadvantaged groups, exacerbate the
5    uneven distribution of future benefits, amplify existing inequities, and introduce new ones. Increased
6    poverty also hinders efforts towards sustainable low-carbon transitions (1.6).
 7   Impacts on profitability and investment. COVID-19-induced demand reduction in electricity
 8   disproportionally affected coal power plants, whilst transport reduction most affected oil (IEA 2020a). This
 9   accelerated pre-existing decline in the relative profitability of most fossil fuel industries (Ameli et al. 2021)
10   Renewables were the only energy sector to increase output (IEA 2020a). Within the context of a wider
11   overall reduction in energy investment this prompted a substantial relative shift towards low carbon
12   investment particularly by the private sector (IEA 2020b; Rosembloom and Markard 2020; 15.2.1, 15.3.1,
13   15.6.1).
14   Post-pandemic recovery pathways provide an opportunity to attract finance into accelerated and
15   transformative low-carbon public investment (15.2, 15.6.3). In most countries, COVID-19 has increased
16   unemployment and/or state-supported employment. There is a profound difference between short-term
17   ‘bail-outs’ to stem unemployment, and the orientation of new public investment. The public debt is mirrored
18   by large pools of private capital. During deep crises like that of the COVID-19, economic multipliers of
19   stimulus packages can be high (Hepburn et al., 2020), so much so that fiscal injections can then generate
20   multipliers from 1.5 to 2.5, weakening the alleged crowding-out effect of public stimulus (Auerbach and
21   Gorodnichenko 2012; Blanchard and Leigh 2013; Section 15.2.3 in Chapter 15).
22   Recovery packages are motivated by assessments that investing in can boost the macroeconomic
23   effectiveness (‘multipliers’) of public spending, crowd-in and revive private investment (Hepburn et al.
24   2020). There are clear reasons why a low-carbon response can create more enduring jobs, better aligned to
25   future growth sectors: by also crowding-in and reviving private investment (e.g. from capital markets and
26   institutional investors, including the growing profile of Environment and Social Governance (ESG) and
27   green bond markets (15.6)), this can boost the effectiveness of public spending (IMF 2020). Stern and
28   Valero (Stern and Valero 2021) argue that investment in low-carbon innovation and its diffusion,
29   complemented by investments in sustainable infrastructure, are key to shape environmentally sustainable
30   and inclusive growth in the aftermath of the COVID-19 pandemic crisis. This would be the case both for
31   high-income economies on the global innovation frontier, and to promote sustainable development in
32   poorer economies.
33   A study with a global general equilibrium model (Liu et al. 2021)finds that because the COVID-19
34   economic aftermath combines negative impacts on employment and consumption, a shift from employment
35   and consumption taxes to carbon or other resource- related taxes would enhance GDP by 1.7% in 2021
36   relative to ‘no policy’, in addition to reducing CO2 and other pollutants. A post-Keynesian model of wider
37   ‘green recovery’ policies (Pollitt et al. 2021) finds a short-run benefit of around 3.5% GDP (compared to
38   ‘no policy’), and even c. 1% above a recovery boosted by cuts in consumption taxes, the latter benefit
39   sustained through 2030 - outperforming an equivalent conventional stimulus package while reducing global
40   CO2 emissions by 12%.
41   Orientation of recovery packages. The large public spending on supporting or stimulating economies,
42   exceeding USD12tn by October 2020, dwarfs clean energy investment needs and hence could either help
43   to solve the combined crises, or result in high-carbon lock-in (Andrijevic et al. 2020). The short-term ‘bail-

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1    outs’ to date do not foster climate resilient long-term investments and have not been much linked to climate
2    action, (Sections 15.2.3 and 15.6.3 in Chapter 15): in the G20 counties, 40% of energy-related support
3    spending went to the fossil fuel industry compared to 37% on low-carbon energy (EPT 2020). Recovery
4    packages are also at risk of being ‘colourless’ (Hepburn et al., 2020) though some countries and regions
5    have prioritised green stimulus expenditures for example as part of ‘Green New Deal’ (Rochedo et al. 2021;
6    Section 13.9.6 in Chapter 13 and Section 15.6.3 in Chapter 15).
 7   Integrating analyses. The response to COVID-19 also reflects the relevance of combining multiple
 8   analytic frameworks spanning economic efficiency, ethics and equity, transformation dynamics, and
 9   psychological and political analyses (Section 1.7). As with climate impacts, not only has the global burden
10   of disease been distributed unevenly, but capabilities to prevent and treat disease were asymmetrical and
11   those in greatest vulnerability often had the least access to human, physical, and financial resources (Ruger
12   and Horton 2020). ‘Green’ versus ‘brown’ recovery has corresponding distributional consequences
13   between these and ‘green’ producers, suggesting need for differentiated policies with international
14   coordination (Le Billon et al. 2021). This illustrates the role of ‘just transition’ approaches to global
15   responses including the value of integrated, multi-level governance (Section 1.7 in this Chapter, Section
16   4.5 in Chapter 4 and Section 17.1 in Chapter 17).
17   Crises and opportunities: the wider context for mitigation and transformation. The impacts of
18   COVID-19 have been devastating in many ways, in many countries, and may distract political and financial
19   capacity away from efforts to mitigate climate change. Yet, studies of previous post-shock periods suggest
20   that waves of innovation that are ready to emerge can be accelerated by crises, which may prompt new
21   behaviours, weaken incumbent (‘meso-level’) systems, and prompt rapid reforms (Section 1.6.5; Roberts
22   and Geels 2019a). Lessons from the collective effort to 'flatten the curve’ during the pandemic, illustrating
23   aspects of science-society interactions for public health in many countries, may carry over to climate
24   mitigation, and open new opportunities (Section 5.1.2 in Chapter 5). COVID-19 appears to have accelerated
25   the emergence of renewable power, electromobility and digitalisation (Newman 2020; Sectiopn 5.1.2 in
26   Chapter 5, Section 6.3 in Chapter 6, Section 10.2 in Chapter 10). Institutional change is often very slow but
27   major economic dislocation can create significant opportunities for new ways of financing and enabling
28   ‘leapfrogging’ investment to happen (Section 10.8 in Chapter 10). Given the unambiguous risks of climate
29   change, and consequent stranded asset risks from new fossil fuel investments (Box 6.11), the most robust
30   recoveries are likely to be those which emerge on lower carbon and resilient pathways (Obergassel et al.
31   2020). Noting the critical global post-COVID-19 challenge as the double-impact of heightened credit risk
32   in developing countries, along with indebtedness in developed countries, (Hourcade et al. 2021a) estimate
33   that a ‘multilateral’ sovereign guarantee structure to underwrite low carbon investments could leverage
34   projects up to 15 times its value, contributing to shifting development pathways consistent with the SDGs
35   and Paris goals.
36   COVID- 19 can thus be taken as a reminder of the urgency of addressing climate change, a warning of the
37   risk of future stranded assets (Rempel and Gupta 2021; and Chapter 17), but also an opportunity for a
38   cleaner recovery.
41   In addition to developments in climate science, emissions, the international agreements in 2015, and the
42   recent impact of COVID-19, a few other key developments have strong implications for climate mitigation.

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1    Cheaper Renewable Energy Technologies: Most striking, the cost of solar PV has fallen by a factor of 5-
2    10 in the decade since the IPCC Special Report on Renewable Energy (IPCC 2011a) and other data inputting
3    to the AR5 assessments, The SR1.5 reported major cost reductions, the IEA (2020) World Energy Outlook
4    described PV as now ‘the cheapest electricity in history’ for projects that ‘tap low cost finance and high
5    quality resources.’ Costs and deployment both vary widely between different countries (chapter 6, 9, 12)
6    but costs are still projected to continue falling (Vartiainen et al. 2020). Rapid technological developments
7    have occurred in many other low-carbon technologies including batteries and electric vehicles (see 1.4.3),
8    IT and related control systems, with progress also where electrification is not possible (Chapters 2, 6, 11)
 9   Civil society pressures for stronger action. Civic engagement increased leading up to the Paris Agreement
10   (Bäckstrand and Lövbrand 2019) and after. Youth movements in several countries show young people’s
11   awareness about climate change, evidenced by the school strikes for the climate (Hagedorn et al. 2019;
12   Buettner 2020; Walker 2020; Thackeray et al. 2020). Senior figures across many religions (Francis 2015;
13   IFEES 2015) stressed the duty of humanity to protect future generations and the natural world, and warned
14   about the inequities of climate change. Growing awareness of local environmental problems such as air
15   pollution in Asia and Africa (Karlsson et al. 2020), and the threat to indigenous people rights and existence
16   has also fuelled climate activism (Etchart 2017). Grass-root movements (Cheon and Urpelainen 2018;
17   Fisher et al. 2019), build political pressure for accelerating climate change mitigation, as does increasing
18   climate litigation (Setzer and Vanhala 2019; Chapters 13 and 14).
19   Climate policies also encounter resistance. However there are multiple sources of resistance to climate
20   action in practice. Corporations and trade associations often lobby against measures they deem detrimental
21   (Section 1.4.6). The emblematic ‘yellow vest’ movement in France was triggered by higher fuel cost as a
22   result of CO2 tax hike (Lianos 2019; Driscoll 2021), though it had broader aspect of income inequality and
23   other social issues. There is often mismatch between concerns on climate change and people’s willingness
24   to pay for mitigation. For example, whilst most Americans believe climate change is happening, 68% said
25   in a survey they would oppose climate policies that added just USD10/month to electricity bills (EPIC et
26   al. 2019), and worry about energy costs can eclipse those about climate change elsewhere (Poortinga et al.
27   2018; Chapter 13).
28   Global trends contrary to multilateral cooperation. State-centred politics and geopolitical/geo-economic
29   tensions seem to have become more prominent across many countries and issues (WEF 2019). In some
30   cases, multilateral cooperation could be threatened by trends such as rising populism, nationalism,
31   authoritarianism and growing protectionism (Abrahamsen et al. 2019), making it more difficult to tackle
32   global challenges including protecting the environment (Schreurs 2016; Parker et al. 2017; WEF 2019).
33   Transnational alliances. Partly countering this trend, cities, businesses, a wide range of other non-state
34   actors also have emerged with important international networks to foster mitigation. City-based examples
35   include the Cities Alliance in addressing climate change, Carbon Neutral Cities Alliance, the Covenant of
36   Mayors (chapter 8); there are numerous other alliances and networks such as those in finance (chapter 15),
37   technology (chapter 16), amongst many others (chapters 13, 14).
38   Finally, under the Paris Agreement process, during 2020/21, many countries strengthened their Nationally
39   Determined Contributions (NDCs). Including updates until October 2021, these would imply global GHG
40   emissions declining by 2030 to between 1-4% below 2019 levels (unconditional NDCs), or 4-10% (for
41   NDCs conditional on international support), See Table 4.3 in Chapter 4 ).This is a significant change but
42   would still not be compatible with 1.5°C pathways, and even if delivered in full, to likely stay below 2°C,
43   emissions would have to fall very rapidly after 2030 (Section 3.2.5).

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1    Thus, developments since AR5 highlight the complexity of the mitigation challenge. There is no far-sighted,
2    globally optimising decision-maker and indeed climate policymaking at all levels is subject to conflicting
3    pressures in multiple ways. The next section overviews the drivers and constraints.

5    1.4 Drivers and Constraints                       of     Climate        Mitigation        and      System
6        Transitions/Transformation
 7   This section provides brief assessment of key factors and dynamics that drive, shape and or limit climate
 8   mitigation in (i) Economic factors: which include sectors and services; trade and leakage; finance and
 9   investment; and technological innovation; (ii) Socio-political issues; which include political economy;
10   social innovation and equity and fairness; and (iii) Institutional factors, which comprise policy, legal
11   frameworks and international co-operation.
12   AR 5 introduced six “enabling conditions” for shifting development pathways which are presented in
13   Chapter 4 of this report and some of which overlap with the drivers reviewed here. However, the
14   terminology of drivers and constraints have been chosen here to reflect the fact that each of these factors
15   can serve as an enabling condition or a constraint to ambitious climate action depending on the context and
16   how they are deployed. Often one sees the factors exerting both push and pull forces at the same time in
17   the same and across different scales. For example, finance and investments can serve as a barrier or an
18   enabler to climate action (Battiston et al. 2021). Similarly, political economy factors can align in favour of
19   ambitious climate action or act in ways that inhibit strong co-operation and low carbon transition. The other
20   key insight from the assessment of the system drivers and constraints undertaken below is that none of the
21   factors or conditions by themselves is more or less important than the others. In addition to being deeply
22   intertwined all the factors matter in different measures with each exacting more or less force depending on
23   prevailing social, economic, cultural and political context. Often achieving accelerated mitigation would
24   require effort to bring several of the factors in alignment in and across multiple levels of political or
25   governance scales.
26   1.4.1 Services, sectors and urbanisation
27   Human activities drive emissions primarily through the demand for a wide range of services such as food,
28   shelter, heating/cooling, goods, travel, communication, and entertainment. This demand is fulfilled by
29   various activities often grouped into sectors such as agriculture, industry and commerce. The literature
30   uses a wide range of sectoral definitions to organize data and analysis (Chapter 2). Energy sectors are
31   typically organised into primary energy producers, energy transformation processes (such as power
32   generation, fuel refining), and major energy users such as buildings, industry, transport (Chapters 2, 5).
33   Other research (Chapter 8) organizes data around interacting urban and rural human activities. Land-based
34   activities can be organized into agriculture, forestry, and other land use (AFOLU), or land use, land use
35   change and forestry (LULUCF) (Chapter 7). Each set of sectoral definitions and analysis offers its own
36   insights.
37   Sectoral perspectives help to identify and understand the drivers of emissions, opportunities for emissions
38   mitigation, and interactions with resources, other goals and other sectors, including the co-evolution of
39   systems across scales (Moss et al. 2016; Kyle et al. 2016; Mori et al. 2017; IPBES 2019). Interactions
40   between sectors and agents pursuing multiple goals is a major theme pervading this assessment.

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1    The ‘nexus’ between energy, water, and land – all key contributors to human well-being – also helps to
2    provide, regulate and support ecosystem and cultural services (Bazilian et al. 2011; Ringler et al. 2013;
3    Smajgl et al. 2016; Albrecht et al. 2018; D’Odorico et al. 2018; Brouwer et al. 2018; Van Vuuren et al.
4    2019), with important implications for cities in managing new systems of transformation (Chapter 8;
5    Thornbush et al. 2013; Wolfram et al. 2016) . Other important nexus’ shaping our planet’s future (Fajardy
6    et al. 2018) include agriculture, forestry, land use and ecosystem services (Chazdon 2008; Keesstra et al.
7    2018; Nesshöver et al. 2017; Torralba et al. 2016; Settele et al. 2016).
 8   Historically, energy-related GHG emissions were considered a by-product of the increasing scale of human
 9   activity, driven by population size, economic activity and technology. That simple notion has evolved
10   greatly over time to become much more complex and diverse, with increasing focus on the provision of
11   energy services (Garrett et al. 2020; Bardi et al. 2019; Cullen and Allwood 2010; Brockway et al. 2019))
12   The demand for agricultural products has historically driven conversion of natural lands (land use change).
13   AFOLU along with food processing account for 21-37% of total net anthropogenic GHG emissions
14   (SRCCL SPM A3).5
15   Continued growth in population and income are expected to continue driving up demand for goods and
16   services (Chapters 2, 3 & 5), with an important role for urbanisation which is proceeding at an
17   unprecedented speed and scale. In the last decade, the urban population grew by 70 million people each
18   year, or about 1.3 million people per week, with urban area expanding by about 102 km2 per day (Chapter
19   8). Urban areas account for most (45-87%) of the global carbon footprint (8.1) and the strong and positive
20   correlation between urbanisation and incomes means higher consumption from urban lifestyles will
21   continue driving direct and indirect GHG emissions. Cities provide conduit to many of the services such as
22   transportation, housing, water, food, medical care, recreation and other services and urban carbon emissions
23   are driven not only by population and income but also by form and structure of urban areas (8.1, 8.3, 8.4,
24   8.5, 8.6). This creates opportunities for decarbonization through urban planning and purposeful
25   “experimentation” (Newman et al. 2017 Chapter 8).
26   Human needs and wants evolve over time making the transition toward climate and sustainable
27   development goals either more or less difficult. For example, changes in the composition of goods
28   consumed, such as, shifting diets toward a more vegetarian balance, can reduce land-use emissions without
29   compromising the quality of life (Stehfest et al. 2009; van Vuuren et al. 2018; van den Berg et al. 2019;
30   Hargreaves et al. 2021; Gough 2017; SRCCL SPM B2.3).
31   Human behavior and choices, including joint achievement of wider social goals, will play an important part
32   in enabling or hindering climate mitigation and sustainable development (Shi et al. 2016), for example
33   shifting passenger transportation preferences in ways that combine climate, health and sustainable
34   development goals (Romanello et al. 2021).
35   1.4.2 Trade, consumption and leakage
36   Emissions associated with international trade account for 20-33 % of global emissions, as calculated using
37   multi-regional input-output analysis (Wiedmann and Lenzen 2018). Whether international trade drives
38   increase or decrease in global GHG emissions depends on emissions intensity of traded products as well as
39   the influence of trade on relocation of production, with studies reaching diverse conclusions about the net
40   effect of trade openness on CO2 emissions (Section 2.4.5). Tariff reduction of low carbon technologies

     FOOTNOTE5 AFOLU accounted for about 13% of CO2, 44% of CH4 and 82% of N2O global anthropogenic GHG
     emissions in 2007-2016 (SRCCL SPM A3).

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1    could facilitate effective mitigation (de Melo and Vijil 2014; WTO 2016; Ertugrul et al. 2016; Islam et al.
2    2016).
3    The magnitude of carbon leakage (Annex I) caused by unilateral mitigation in a fragmented climate policy
4    world depends on trade and substitution patterns of fossil fuels and the design of policies (see Box 5.4.
5    AR5), but its potential significance in trade-exposed energy-intensive sectors (Naegele and Zaklan 2019;
6    Carbone and Rivers 2017; Bauer et al. 2013) can make it an important constraint on policy. See Section
7 in Chapter 13 for channels and evidence. Akimoto et al. (2018) argue that differences in marginal
8    abatement cost of NDCs could cause carbon leakage in energy-intensive, trade-exposed sectors, and could
9    weaken effective global mitigation.
10   Policy responses to cope with carbon leakage include border carbon adjustment (BCAs) and differentiated
11   carbon taxes (Liu et al. 2020). Some BCA options focusing on levelling the cost of carbon paid by
12   consumers on products could be designed in line with WTO (Ismer et al. 2016) while others may not be
13   (Mehling et al. 2019). All proposals could involve difficulty of tracing and verifying the carbon content of
14   inputs (Onder 2012; Denis-Ryan et al. 2016). An international consensus and certification practice on the
15   carbon content would help to overcome WTO compatibility (Holzer 2014). See chapter 13, and (Mehling
16   et al. 2019) on context of trade law and the PA.
17   Official inventories report territorial emissions, which do not consider the impacts embodied in imports of
18   goods. Global supply chains undoubtedly lead to a growth in trade volumes (Federico and Tena-Junguito
19   2017), alternative methods have been suggested to account for emissions associated with international trade,
20   such as shared responsibility (Lenzen et al. 2007), technology adjusted consumption based accounting
21   (Kander et al. 2015), value added-based responsibility (Piñero et al. 2019) and exergy-based responsibility
22   based on thermodynamics (Khajehpour et al. 2019). Consumption-based emissions (i.e. attribution of
23   emissions related to domestic consumption and imports to final destination) are not officially reported in
24   global emissions datasets but data has improved (Afionis et al. 2017; Tukker and Dietzenbacher 2013). This
25   analysis have been used extensively for consumption-based accounting of emissions, and other
26   environmental impacts (Malik et al. 2019; Wiedmann and Lenzen 2018). chapter 2.3).
27   Increasing international trade has resulted in a general shifting of fossil-fuel driven emissions-intensive
28   production from developed to developing countries (Arto and Dietzenbacher 2014; Malik and Lan 2016),
29   and between developing countries (Zhang et al. 2019). High-income developed countries thus tend to be
30   net importers of emissions, whereas low/middle income developing countries net-exporters (Peters et al.
31   2011; Figure 1.2c, d).This trend is shifting, with a growth in trade between non-OECD countries (Meng et
32   al. 2018; Zhang et al. 2019), and a decline in emissions intensity of traded goods (Wood et al. 2020b).
33   The Paris Agreement primarily deals with national commitments relating to domestic emissions and
34   removals, hence emissions from international aviation and shipping are not covered. Aviation and shipping
35   accounted for approximately 2.7% of greenhouse gas emissions in 2019 (before COVID-19); see Chapter
36   10.5.2 for discussion. In addition to CO2 emissions, aircraft-produced contrail cirrus clouds and emissions
37   of black carbon and short-lived aerosols (e.g. sulphates) from shipping are especially harmful for the Arctic
38   (10.8, Box 10.6).
39   1.4.3 Technology
40   The rapid developments in technology over the past decade enhance potential for transformative changes,
41   in particular to help deliver climate goals simultaneously with other SDGs.

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1    The fall in renewable energy costs alongside rapid growth in capacity (Figure 1.3; Figure X in Chapter 2)
2    has been accompanied by varied progress in many other technology areas such electric vehicles, fuel cells
3    for both stationary and mobile applications (Dodds 2019), thermal energy (chapter 6) and battery and other
4    storage technologies (Chapters 6, 9, 12; Freeman et al. 2017). Nuclear contributions may be enhanced by
5    new generations of reactors, e.g., Generation III, and small modular reactors (Knapp and Pevec 2018; see
6    also Chapter 6).

 9                     Figure 1.2: Cost reductions and adoption in solar PV and wind energy
10    Source: (IRENA 2020a,b), with fossil fuel LCOE indicated as shaded blue at USD 50-177/MWh (IRENA 2020b)
11   Large-scale hydrogen developments could provide a complementary energy channel with long-term
12   storage. Like electricity, hydrogen (H2) is an energy vector with multiple potential applications, including
13   in industrial processes such as steel and non-metallic materials production (Chapter 11), for long-range
14   transportation (Chapter 10), and low-temperature heating in buildings (Chapter 9). Emissions depend on
15   how it is produced, and deploying H2 delivery infrastructure economically is a challenge when the future
16   scale of hydrogen demand is so uncertain (Chapter 6). H2 from natural gas with CO2 capture and storage
17   (CCS) may help to kick-start the H2 economy (Sunny et al. 2020).
18   CO2-based fuels and feedstocks such as synthetic methane, methanol, diesel, jet fuel and other
19   hydrocarbons, potentially from carbon capture and utilisation (CCU), represent drop-in solutions with
20   limited new infrastructure needs (Artz et al. 2018; Bobeck et al. 2019; Yugo and Soler 2019); Chapter 10.
21   Deployment and development of CCS technologies (with large-scale storage of captured CO2) have been
22   much slower than projected in previous Assessments (Page et al. 2019; IEA 2019b; see also Chapter 11).
23   Potential constraints on new energy technologies may include their material requirements, notably rare
24   earth materials for electronics or lithium for batteries (Wanger 2011; Flexer et al. 2018), stressing the
25   importance of recycling (Rosendahl and Rubiano 2019; IPCC 2011b). Innovation is enabling greater
26   recycling and re-use of energy-intensive materials (Shemi et al. 2018) and introducing radically new and
27   more environmentally friendly materials, however, still not all materials can be recycled (Allwood 2014).
28   By sequestering carbon in biomass and soils, soil carbon management, and other terrestrial strategies could
29   offset hard-to-reduce emissions in other sectors. However, large-scale bioenergy deployment could increase
30   risks of desertification, land degradation, and food insecurity (IPCC 2019a), and higher water withdrawals
31   (Hasegawa et al. 2018; Fuhrman et al. 2020), though this may be at least partially offset by innovation in
32   agriculture, diet shifts and plant-based proteins contributing to meeting demand for food, feed, fibre and,
33   bioenergy (or BECCS with CCS) (Chapters 5, 7; Köberle et al. 2020; Havlik et al. 2014; Popp et al. 2017).

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 1   A broad class of more speculative technologies propose to counteract effects of climate change by removing
 2   CO2 from the atmosphere (CDR), or directly modify the Earth’s energy balance at a large scale (SRM).
 3   CDR technologies include ocean iron fertilisation, enhanced weathering and ocean alkalinisation (Council
 4   2015a), along with Direct Air Capture with Carbon Storage (DACCS). They could potentially draw down
 5   atmospheric CO2 much faster than the Earth’s natural carbon cycle, and reduce reliance on biomass-based
 6   removal (Realmonte et al. 2019; Köberle 2019), but some present novel risks to the environment and
 7   DACCS is currently more expensive than most other forms of mitigation (Fuss et al. 2018; Cross-chapter
 8   box 8 in Chapter 12). Solar radiation modification (SRM) could potentially cool the planet rapidly at low
 9   estimated direct costs by reflecting incoming sunlight (Council 2015b), but entails uncertain side effects
10   and thorny international equity and governance challenges (Netra et al. 2018; Florin et al. 2020; National
11   Academies of Sciences 2021) (Chapter 14). Understanding the climate response to SRM remains subject
12   to large uncertainties (AR6 WG1). Some literature uses the term “geoengineering” for both CDR or SRM
13   when applied at a planetary scale (Shepherd 2009; GESAMP 2019). In this report, CDR and SRM are
14   discussed separately reflecting their very different geophysical characteristics.
15   Large improvements in information storage, processing, and communication technologies, including
16   artificial intelligence, will affect emissions. They can enhance energy-efficient control, reduce transaction
17   cost for energy production and distribution, improve demand-side management (Raza and Khosravi 2015),
18   and reduce the need for physical transport (Smidfelt Rosqvist and Winslott Hiselius 2016; see Chapters 5,
19   6, 9-11). However, data centres and related IT systems (including blockchain), are electricity-intensive and
20   will raise demand for energy (Avgerinou et al. 2017) - cryptocurrencies may be a major global source of
21   CO2 if the electricity production is not decarbonised (Mora et al. 2018) – and there is also a concern that
22   information technologies can compound and exacerbate current inequalities (Chapter 16; Box 2). IT may
23   affect broader patterns of work and leisure (Boppart and Krusell 2020), and the emissions intensity of how
24   people spend their leisure time will become more important (see Chapters 5, 9). Because higher efficiency
25   tends to reduces costs, it often involves some ‘rebound’ offsetting at least some of the emission savings
26   (Belkhir and Elmeligi 2018; Sudbury and Hutchinson 2016; Cohen and Cavoli 2019).
27   Technology can enable both emissions reductions and/or increased emissions (Chapter 16). Governments
28   play an important role in most major innovations, in both ‘technology-push’ (Mazzucato 2013) and induced
29   by ‘demand-pull’ (Grubb et al. 2021a), so policy is important in determining its pace, direction, and
30   utilisation (Roberts and Geels 2019a; Sections 1.7.1, 1.7.3). Overall, the challenge will be to enhance the
31   synergies and minimise the trade-offs and rebounds, including taking account of ethical and distributional
32   dimensions (Gonella et al. 2019).
33   1.4.4 Finance and investment
34   Finance is both an enabler and constraint on mitigation, and since AR5, attention to the financial sector’s
35   role in mitigation has grown. This is partly in the context of the Paris Agreement finance articles and Green
36   Climate Fund, the pledge to mobilise USD100bn/yr by 2020, and the Addis Abbaba Action Agenda
37   (Section 1.3.1). However there is a persistent but uncertain gap in mitigation finance (Cui and Huang
38   2018); (Table 15.15.1), even though tracked climate finance overwhelmingly goes toward mitigation
39   compared to adaptation (UNEP 2020; 15.3; Working Group II). Green bond issuance has increased recently
40   in parallel with efforts to reform the international financial system by supporting development of local
41   capital markets (15.6.4).
42   Climate finance is a multi-actor, multi-objective domain that includes central banks, commercial banks,
43   asset managers, underwriters, development banks, and corporate planners. Climate change presents both

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 1   risks and opportunities for the financial sector. The risks include physical risks related to the impacts of
 2   climate change itself; transition risks related to the exposure to policy, technology and behavioural changes
 3   in line with a low-carbon transition; and liability risks from litigation for climate-related damages (Box
 4   15.2). These could potentially lead to stranded assets (the loss of economic value of existing assets before
 5   the end of their useful lifetimes (Bos and Gupta 2019; Section 6.7 in Chapter 6, Section 15.6.3 in Chapter
 6   15). Such risks continue to be underestimated by financial institutions (Section 15.6.1 in Chapter 15). The
 7   continuing expansion of fossil fuel infrastructure and insufficient transparency on how these are valued
 8   raises concerns that systemic risk may be accumulating in the financial sector in relation to a potential low-
 9   carbon transition that may already be under way (Battiston et al. 2017; Section 15.6.3 in Chapter 15). The
10   Financial Stability Board’s TCFD recommendations on transparency aim to ensure that investors and
11   companies consider climate change risks in their strategies and capital allocation (TCFD 2018). This is
12   helping "investors to reassess core assumptions” and may lead to “significant” capital reallocation (Fink
13   2020). However, metrics and indicators of assets risk exposure are inadequate (Campiglio et al. 2018;
14   Monasterolo 2017) and transparency alone is insufficient to drive the required asset reallocation in the
15   absence of clear regulatory frameworks (Chenet et al. 2021; Ameli et al. 2020). A coalition of Central Banks
16   have formed the Network for Greening the Financial Sector, to support and advance the transformation of
17   the financial system (Allen et al. 2020; NGFS 2020), with some of them conducting Climate-related
18   institutional stress tests
19   Governments cannot singlehandedly fund the transition (Section 15.6.7 in Chapter 15), least of all in low-
20   income developing countries with large sovereign debt and poor access to global financial markets. Long-
21   term sources of private capital are required to close the financing gap across sectors and geographies
22   (Section 15.6.7 in Chapter 15). Future investment needs are greatest in emerging and developing economies
23   (Section 15.5.2 In Chapter 15) which already face higher cost of capital, hindering capacity to finance a
24   transition (Buhr et al. 2018; Ameli et al. 2020). Requisite North-South financial flows are impeded by both
25   geographic and technological risk premiums (Iyer et al. 2015), and the Covid-19 pandemic has further
26   compromised the ability of developing and emerging economies to finance development activities or attract
27   additional climate finance from developed countries (Cross-Chapter Box 1 in this chapter; Section 15.6.3
28   in Chapter 15). Climate-related investments in developing countries also suffer from structural barriers
29   such as sovereign risk and exchange rate volatility (Farooquee and Shrimali 2016; Guzman et al. 2018)
30   which affect not only climate-related investment but investment in general (Yamahaki et al. 2020) including
31   in needed infrastructure development (Gray and Irwin 2003). A GCF report notes the paradox that USD14
32   trillion of negative-yielding debt in OECD countries might be expected to flow to much larger low-carbon,
33   climate-resilient investment opportunities in developing countries, but “this is not happening” (Hourcade
34   et al. 2021b).
35   There is often a disconnect between stated national climate ambition and finance flows, and overseas direct
36   investment (ODI) from donor countries may be at odds with national climate pledges such as NDCs. One
37   report found funds supported by foreign State-Owned Enterprises into 56 recipient countries in Asia and
38   Africa in 2014-2017 went mostly to fossil fuel-based projects not strongly aligned with low-carbon
39   priorities of recipient countries’ NDCs (Zhou et al. 2018). Similarly, Steffen and Schmidt (2019) found that
40   even within Multilateral Development Banks, ‘public- and private-sector branches differ considerably’,
41   with public-sector lending used mainly in non-renewable and hydropower projects. Political leadership is
42   therefore essential to steer financial flows to support low carbon transition (15.6). Voituriez er al. (2019)
43   identify significant mitigation potential if financing countries simply applied their own environmental
44   standards to their overseas investments.

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1    1.4.5 Political economy
 2   The politics of interest (most especially economic interest) of key actors at subnational, national and global
 3   level can be important determinants of climate (in)action (O’Hara 2009; Lo 2010; Tanner and Allouche
 4   2011; Sovacool et al. 2015; Clapp et al. 2018; Lohmann 2017; Newell and Taylor 2018; Lohmann 2019).
 5   Political economy approaches can be crudely divided into “economic approaches to politics”, and those
 6   used by other social scientists (Paterson and P‐Laberge 2018). The former shows how electoral concerns
 7   lead to weak treaties (Battaglini and Harstad 2016) and when policy negotiations cause status-quo biases
 8   and the use of inefficient policy instruments (Austen-Smith et al. 2019) or delays and excessive
 9   harmonization (Harstad 2007). The latter emphasises the central role of structures of power, production,
10   and a commitment to economic growth and capital accumulation in relation to climate action, given the
11   historically central role of fossil fuels to economic development and the deep embedding of fossil energy
12   in daily life (Malm 2015; Huber 2012; Di Muzio 2015; Newell and Paterson 2010).
13   The economic centrality of fossil fuels raises obvious questions regarding the possibility of decarbonisation.
14   Economically, this is well understood as a problem of decoupling. But the constraint is also political, in
15   terms of the power of incumbent fossil fuel interests to block initiatives towards decarbonisation (Newell
16   and Paterson 2010; Geels 2014; Jones and Levy 2009). The effects of climate policy are key considerations
17   in deciding the level of policy ambition and direction and strategies of states (Alam et al. 2013; Ibikunle
18   and Okereke 2014; Lo 2010), regions (Goldthau and Sitter 2015); and business actors (Wittneben et al.
19   2012) and there is a widespread cultural assumption that continued fossil fuel use is central to this (Strambo
20   and Espinosa 2020). Decarbonisation strategies are often centred around projects to develop new sources
21   of economic activity: carbon markets creating new commodities to trade profit from (Newell and Paterson
22   2010); the investment generated in new urban infrastructure (Whitehead 2013); innovations in a range of
23   new energy technologies (Fankhauser et al. 2013; Lachapelle et al. 2017; Meckling and Nahm 2018).
24   One factor limiting the ambition of climate policy has been the ability of incumbent industries to shape
25   government action on climate change (Newell and Paterson 1998; Breetz et al. 2018; Jones and Levy 2009;
26   Geels 2014). Incumbent industries are often more concentrated than those benefiting from climate policy
27   and lobby more effectively to prevent losses than those who would gain (Meng and Rode 2019). Drawing
28   upon wider networks (Brulle 2014), campaigns by oil and coal companies against climate action in the US
29   and Australia are perhaps the most well-known and largely successful of these (Brulle et al. 2020; Stokes
30   2020; Mildenberger 2020; Pearse 2017) although similar dynamics have been demonstrated for example in
31   Brazil and South Africa (Hochstetler 2020), Canada (Harrison 2018), Norway , or Germany (Fitzgerald et
32   al. 2019). In other contexts, resistance by incumbent companies is more subtle but nevertheless has
33   weakened policy design on emissions trading systems (Rosembloom and Markard 2020), and limited the
34   development of alternative fuelled automobiles (Wells and Nieuwenhuis 2012; Levy and Egan 2003).
35   The interaction of politics, power and economics is central in explaining why countries with higher per-
36   capita emissions, which logically have more opportunities to reduce emissions, in practice often take the
37   opposite stance, and conversely, why some low-emitting countries may find it easier to pursue climate
38   action because they have fewer vested interests in high-carbon economies. These dynamics can arise from
39   the vested interest of State-owned Enterprises (Polman 2015; Wright and Nyberg 2017; Wittneben et al.
40   2012), the alignment and coalitions of countries in climate negotiations (Gupta 2016; Okereke and Coventry
41   2016), and the patterns of opposition to or support for climate policy among citizens (Swilling et al. 2016;
42   Ransan-Cooper et al. 2018; Turhan et al. 2019; Baker 2015; Heffron and McCauley 2018).

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1    1.4.6 Equity and fairness
 2   Equity and fairness can serve as both driver and barrier to climate mitigation at different scales of
 3   governance. Literature regularly highlights equity and justice issues as critical components in local politics
 4   and international diplomacy regarding all SDG, such as goals for no poverty, zero hunger, gender equality,
 5   affordable clean energy, reducing inequality, but also for climate action (Goal 13) (Marmot and Bell 2018;
 6   Spijkers 2018). Equity issues help explain why it has proved hard to reach more substantive global
 7   agreements, as it is hard to agree on a level of greenhouse gas mitigation (or emissions) and how to distribute
 8   mitigation efforts among countries (Kverndokk 2018) for several reasons. First, an optimal trade-off
 9   between mitigation costs and damage costs of climate change depends on ethical considerations, and
10   simulations from integrated assessment models using different ethical parameters producing different
11   optimal mitigation paths, see (IPCC 2018b and Section in Chapter 3). Second, treaties that are
12   considered unfair may be hard to implement (Liu et al. 2017; Klinsky et al. 2017). Lessons from
13   experimental economics show that people may not accept a distribution that is considered unfair, even if
14   there is a cost of not accepting (Gampfer 2014). As equity issues are important for reaching deep
15   decarbonisation, the transition towards a sustainable development (Okereke 2018; Evans and Phelan 2016;
16   Heffron and McCauley 2018) depends on taking equity seriously in climate policies and international
17   negotiations (Martinez et al. 2019; Okereke and Coventry 2016; Klinsky et al. 2017).
18   Climate change and climate policies affect countries and people differently Low-income countries tend to
19   be more dependent on primary industries (agriculture, fisheries, etc.) than richer countries, and their
20   infrastructure may be less robust to tackle more severe weather conditions. Within a country, the burdens
21   may not be equally distributed either, due to policy measures implemented and from differences in
22   vulnerability and adaptive capacity following from e.g. income and wealth distribution, race and gender.
23   For instance, unequal social structures can result in women being more vulnerable to the effects of climate
24   change compared to men, especially in poor countries (Jost et al. 2016; Rao et al. 2019; Arora-Jonsson
25   2011). Costs of mitigation also differ across countries. Studies show there are large disparities of economic
26   impacts of NDCs across regions, and also between relatively similar countries when it comes to the level
27   of development, due to large differences in marginal abatement cost for the emission reduction goal of
28   NDCs (Akimoto et al. 2018; Fujimori et al. 2016; Edmonds et al. 2019; Hof et al. 2017). Equalizing the
29   burdens from climate policies may give more support for mitigation policies (Maestre-Andrés et al. 2019).
30   Taking equity into account in designing an international climate agreement is complicated as there is no
31   single universally accepted equity criterion, and countries may strategically choose a criterion that favours
32   them (Lange et al. 2007, 2010). Still, several studies analyse the consequences of different social
33   preferences in designing climate agreements, such as for instance inequality aversion, sovereignty and
34   altruism (Anthoff et al. 2010; Kverndokk et al. 2014).
35   International transfers from rich to poor countries to support mitigation and adaptation activities may help
36   equalizing burdens, as agreed upon in the UNFCCC (1992; Chapters 14 and 15) such that they may be
37   motivated by strategic as well as equity reasons (Kverndokk 2018; see also 1.4.4).
38   1.4.7 Social innovation and behaviour change
39   Social and psychological factors affect both perceptions and behaviour (Whitmarsh et al. 2021; Weber
40   2015). Religion, values, culture, gender, identity, social status and habits strongly influence individual
41   behaviours and choices and therefore, sustainable consumption (Section in this chapter and Section
42   5.2 in Chapter 5). Identities can provide powerful attachments to consumption activities and objects that
43   inhibit shifts away from them (Stoll-Kleemann and Schmidt 2017; Ruby et al. 2020; Brekke et al. 2003;

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1    Bénabou and Tirole 2011). Consumption is a habit-driven and social practice rather than simply a set of
2    individual decisions, making shifts in consumption harder to pursue (Evans et al. 2012; Shove and Spurling
3    2013; Kurz et al. 2015; Warde 2017; Verplanken and Whitmarsh 2021). Finally, shifts towards low-carbon
4    behaviour are also inhibited by social-psychological and political dynamics that cause individuals to ignore
5    the connections from daily consumption practices to climate change impacts (Norgaard 2011; Brulle and
6    Norgaard 2019).
 7   As a notable example, plant-based alternatives to meat could reduce emissions from diets (Willett et al.
 8   2019; Eshel et al. 2019) however, diets are deeply entrenched in cultures and identities and hard to change
 9   (Fresco 2015; Mylan 2018). Changing diets also raises cross-cultural ethical issues, in addition to meat’s
10   role in providing nutrition (Plumwood 2004). Henceforth, some behaviours that are harder to change will
11   only be transformed by the transition itself: triggered by policies, the transition will bring about
12   technologies that, in turn, will entrench new sustainable behaviours.
13   Behaviour can be influenced through a number of mechanisms besides economic policy and regulation,
14   such as information campaigns, advertising and ‘nudging’. Innovations and infrastructure also impact
15   behaviour, as with bicycle lanes to reduce road traffic. Wider social innovations also have indirect impacts.
16   Education is increasing across the world, and higher education will have impacts on fertility, consumption
17   and the attitude towards the environment (Osili and Long 2008; McCrary and Royer 2011; Hamilton 2011).
18   Reducing poverty and improvements in health and reproductive choice will also have implications for
19   fertility, energy use and consumption globally. Finally, social capital and the ability to work collectively
20   may have large consequences for mitigation and the ability to adapt to climate change (Adger 2009; Section
21   4.3.5 in IPCC 2014a).
22   1.4.8 Policy impacts
23   Transformation to different systems will hinge on conscious policy to change the direction in which energy,
24   land-use, agriculture and other key sectors develop (Bataille et al. 2016; Chapters 13, 16). Policy plays a
25   central role in in land-related systems (Chapter 7), urban development (Chapter 8), improving energy
26   efficiency in buildings (Chapter 9) and transport / mobility (Chapter 10), and decarbonising industrial
27   systems (Chapter 11).
28   Policy has been and will be central not only because greenhouse gas emissions are almost universally under-
29   priced in market economies (Stern and Stiglitz 2017; World Bank 2019), and because of inadequate
30   economic incentives to innovation (Jaffe et al. 2005) but also due to various delay mechanisms (Karlsson
31   and Gilek 2020) and multiple sources of path-dependence and lock-in to existing systems (Section 1.8.2),
32   including “Infrastructure developments and long-lived products that lock societies into GHG-intensive
33   emissions pathways may be difficult or very costly to change, reinforcing the importance of early action
34   for ambitious mitigation (robust evidence, high agreement).” (AR5 p.18).
35   Many hundreds of policies have been introduced explicitly to mitigate GHG emissions, improve energy
36   efficiency or land use, or to foster low carbon industries and innovation, with demonstrable impact. The
37   role of policy to date has been most evident in energy efficiency (Sections 5.4 and 5.6 in Chapter 5) and
38   electricity (Chapter 6). The IPCC Special Report on Renewable Energy already found that “Government
39   policies play a crucial role in accelerating the deployment of RE technologies”, (IPCC 2011a, p. 24). Policy
40   packages since then have driven rapid expansion in renewables capacity and cost reductions (eg. through
41   the German Energiewende), and emission reductions from electricity (most dramatically with the halving
42   of CO2 emissions from UK power sector, driven by multiple policy instruments and regulatory changes),
43   as detailed in Chapter 6 (Section 6.7.5).

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1    Chapter 13 charts the international evolution of policies and many of the lessons drawn. Attributing the
2    overall impact on emissions is complex, but an emerging literature of several hundred papers indicates
3    impacts on multiple drivers of emissions. Collectively, policies are likely to have curtailed global emissions
4    growth by several GtCO2e annually already by the mid-2010s (see Cross-Chapter Box 10 in Chapter 14).
5    This suggests initial evidence that policy has driven some decoupling (e.g. Figure 1.1d) and started to ‘bend
6    the curve’ of global emissions, but more specific attribution to observed trends is not as yet possible.6
 7   However, some policies (e.g. subsidies to fossil fuel production or consumption), increase emissions; whilst
 8   others (e.g. investment protection) may constrain efforts at mitigation. Also, wider economic and
 9   developmental policies have important direct and indirect impacts on emissions. Policy is thus both a driver
10   and a constraint on mitigation.
11   Synergies and trade-offs arise partly because of the nexus of GHG emissions with other adverse impacts
12   (e.g. local air pollution) and critical resources (e.g. water and food) (Conway et al. 2015; Andrews-Speed
13   and Dalin 2017), which also imply interacting policy domains.
14   The literature shows increasing emphasis on policy packages, including those spanning the different levels
15   of niche/behaviour; existing regimes governing markets and public actors; and strategic and landscape
16   levels (Section 1.7.3). Chapters 13, 16, and 17 appraise policies for transformation in the context of
17   sustainable development, indicating the importance of policy as a driver at multiple levels and across many
18   actors, with potential for benefits as well as costs at many levels.
19   National-level legislation may be particularly important to the credibility and long-term stability of policy
20   to reduce the risks, and hence cost, of finance (Chapters 13, 15) and for encouraging private sector
21   innovation at scale (Chapter 16), for example if it offers greater stability and mid-term predictability for
22   carbon prices; Nash and Steurer (2019) find that seven national Climate Change Acts in European countries
23   all act as ‘living policy processes, though to varying extents’.
24   The importance of policy at multiple levels does not lessen the importance of international policy, for
25   reasons including long-term stability, equity, and scope, but examples of effective implementation policy
26   at international levels remain fewer and governance weaker (Chapter 14).
27   1.4.9 Legal framework and institutions
28   Institutions are rules and norms held in common by social actors that guide, constrain and shape human
29   interaction (IPCC 2018b). Institutions can be formal, such as laws and policies, or informal, such as norms
30   and conventions. Institutions can both facilitate or constrain climate policy-making and implementation in
31   multiple ways. Institutions set the economic incentives for action or inaction on climate change at national,
32   regional and individual levels (Dorsch and Flachsland 2017; Sullivan 2017).

     FOOTNOTE 6 Linking estimated policy impacts to trends is complex, and as yet very tentative. An important factor
     is that many mitigation policies involve investments in low carbon or energy efficient technology, the savings from
     which persist. As a purely illustrative example: the annual increase in global emissions during 2000-2010 averaged
     around 1GtCO2e yr-1, but with large fluctuations. If policies by 2010 reduced the annual increase in that year by
     100MtCO2e (0.1GtC02e) below what it would otherwise have been, this is hard to discern. But if these savings sustain,
     and in each subsequent year, policies cut another 100MtCO2e off the annual increase compared to the previous year,
     global emissions after a decade would be around 5GtCO2e yr-1 below what they would have been without any such
     policies, and on average close to stabilising. However each step would be difficult to discern in the noise of annual

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1    Institutions entrench specific political decision-making processes, often empowering some interests over
2    others, including powerful interest groups who have vested interest in maintaining the current high carbon
3    economic structures (Engau et al. 2017; Okereke and Russel 2010; Wilhite 2016); see also 1.4.6 and Chapter
4    13 on the sub national and national governance challenges including coordination, mediating politics and
5    strategy setting.
 6   Some suggest that societal transformation towards low a carbon future requires new politics that involves
 7   thinking in intergenerational time horizons, as well as new forms of partnerships between private and public
 8   actors (Westman and Broto 2018), and associated institutions and social innovations to increase
 9   involvement of non-state actors in climate governance (Fuhr et al. 2018). However literature is divided as
10   to how much democratisation of climate politics, with greater emphasis on equity and community
11   participation, would advance societal transformation in the face of climate change (Stehr 2005), or may
12   actually hinder radical climate action in some circumstances (Povitkina 2018).
13   Since 2016, the number of climate litigation cases has increased rapidly. UN Environment’s “Global
14   Climate Litigation Report: 2020 Status Review” (UNEP 2020) noted that between March 2017 and 1 July
15   2020, the number of cases nearly doubled with at least 1,550 climate cases filed in 8 countries. Several
16   important cases such as Urgenda Foundation v. The State of the Netherlands (“Urgenda”) and Juliana et al
17   v. United States (“Juliana”) have had ripple effects, inspiring other similar cases (Lin and Kysar 2020).
18   Numerous international climate governance initiatives engage national and subnational governments,
19   NGOs and private corporations, constituting a “regime complex” (Keohane and Victor 2011; Raustiala and
20   Victor 2004). They may have longer-run and second-order effects if commitments are more precise and
21   binding (Kahler 2017). However, without targets, incentives, defined baseline or monitoring, reporting, and
22   verification, they are not likely to fill the “mitigation gap” (Michaelowa and Michaelowa 2017).
23   1.4.10 International cooperation
24   Tackling climate change is often mentioned as an important reason for strong international co-operation in
25   the 21st century (Bodansky et al. 2017; Cramton et al. 2017b; Keohane and Victor 2016; Falkner 2016).
26   Mitigation costs are borne by countries taking action, while the benefits of reduced climate change are not
27   limited to them, being in economic terms “global and non-excludable”. Hence anthropogenic climate
28   change is typically seen as a global commons problem (Wapner and Elver 2017; Falkner 2016). Moreover,
29   the belief that mitigation will raise energy cost and may adversely affect competitiveness creates incentives
30   for free riding, where states avoid taking their fair share of action (Barrett 2005; Keohane and Victor 2016).
31   International cooperation has the potential to address these challenges through collective action (Tulkens,
32   2019) and international institutions offer opportunity for actors to engage in meaningful communication,
33   and exchange of ideas about potential solutions (Cole 2015). International cooperation is also vital for the
34   creation and diffusion of norms and the framework for stabilising expectations among actors (Pettenger
35   2016).
36   Some key roles of the UNFCCC have been detailed by its former heads (Kinley et al. 2021). In addition to
37   specific agreements (most recently the PA) it has enhanced transparency through reporting and data, and
38   generated or reinforced several important norms for global climate action including the principles of equity,
39   common but differentiated responsibility and respective capabilities, and the precautionary principles for
40   maintaining global cooperation among states with unevenly distributed emissions sources, climate impacts,
41   and varying mitigation cost across countries (Keohane and Victor, 2016). In addition to formal negotiations,
42   the annual Conference of Parties have increased awareness, and motivated more ambitious actions,
43   sometimes through for example the formation of ‘coalitions of the willing’. It provides a structure for

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1    measuring and monitoring action towards a global goal (Milkoreit and Haapala 2019). International
2    cooperation (including the UNFCCC) can also promote technology development and transfer and capacity
3    building; mobilise finance for mitigation and adaptation, and help address concerns on climate justice (Chan
4    et al. 2018; Okereke and Coventry 2016; see Chapters 14-16).
 5   A common criticism of international institutions is their limited (if any) powers to enforce compliance
 6   (Zahar 2017). As a global legal institution, the PA has little enforcement mechanism (Sindico 2015), but
 7   enforcement is not a necessary condition for an instrument to be legally binding (Bodansky 2016; Rajamani
 8   2016). In reality implementation of specific commitments tends to be high once countries have ratified and
 9   a Treaty or an Agreement is in force (Bodansky 2016; Rajamani 2016). Often, the problem is not so much
10   of 'power to enforce compliance or sanction non-compliance', but the level of ambition (Chapter 14).
11   However, whilst in most respects a driver, international cooperation has also been characterised as
12   ‘organised hypocrisy’ where proclamations are not matched with corresponding action (Egnell 2010).
13   Various reasons for inadequate progress after 30 years of climate negotiations, have been identified
14   (Stoddard et al. 2021). International cooperation can also seem to be a barrier to ambitious action when
15   negotiation is trapped in ‘relative-gains’ calculus, seek to game the regime or gain leverage over one
16   another (Purdon 2017), or where states lower ambition to the ‘least common dominator’ to accommodate
17   participation of the least ambitious states (Falkner 2016). Geden (2016) and Dubash (2020) offer more
18   nuanced assessments.
19   International collaboration works best if an agreement can be made self-reinforcing with incentives for
20   mutual gains and joint action (Keohane and Victor 2016; Barrett 2016), but the structure of the climate
21   challenge makes this hard to achieve. The evidence from the Montreal Protocol on ozone depleting
22   substances and from the Kyoto Protocol on GHGs, is that legally binding targets have been effective in that
23   participating Parties complied with them (Albrecht and Parker 2019; Shishlov et al. 2016), and (for Kyoto)
24   these account for most of the countries that have sustained emission reductions for at least the past 10-15
25   years (Section 1.3.2; Section 2.2 in Chapter 2). However, such binding commitments may deter
26   participation if there are no clear incentives to sustain participation and especially if other growing emitters
27   are omitted by design, as with the Kyoto Protocol. Consequently the US refused to ratify (and Canada
28   withdrew), particularly on the grounds that developing countries had no targets; with participation in
29   Kyoto’s second period commitments declining further, the net result was limited global progress in
30   emissions under Kyoto (Scavenius and Rayner 2018; Bodansky 2016; Okereke and Coventry 2016) despite
31   full legal compliance in both commitment periods (chapter 14).
32   The negotiation of the Paris Agreement was thus done in the context of serious questions about how best
33   to structure international climate cooperation to achieve better results. This new agreement is designed to
34   side-step the fractious bargaining which characterised international climate cooperation (Marcu 2017). It
35   contains a mix of hard, soft and non-obligations, the boundaries between which are blurred, but each of
36   which plays a distinct and valuable role (Rajamani 2016). The provisions of the PA could encourage flexible
37   responses to changing conditions, but limit assurances of ambitious national commitments and their
38   fulfilment (Pickering et al. 2018). The extent to which this new arrangement will drive ambitious climate
39   policy in the long run remains to be seen (Chapter 14).
40   Whilst the PA abandoned common accounting systems and timeframes, outside the UNFCCC many other
41   platforms and metrics for comparing mitigation efforts have emerged (Aldy 2015). Countries may assess
42   others’ efforts in determining their actions through multiple platforms including Climate Change
43   Cooperation Index (C3-I), Climate Change Performance Index (CCPI) ‘Climate Laws, Institutions and

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1    Measures Index’ (CLIMI) (Bernauer and Böhmelt 2013) and Energy Transition Index (Singh et al. 2019).
2    International cooperative initiatives between and among non-state (e.g., business, investors, civil society)
3    and subnational (e.g., city, state) actors have also been emerging, taking the forms of public-private
4    partnerships, private sector governance initiatives, NGO transnational initiatives, and subnational
5    transnational initiatives (Bulkeley and Schroeder 2012; Hsu et al. 2018). Literature is mostly positive about
6    the role of these transnational initiatives in facilitating climate action across scales although criticism and
7    caution about their accountability and effectiveness remain (Chan et al. 2016; Roger et al. 2017; Widerberg
8    and Pattberg 2017; Michaelowa and Michaelowa 2017; Chapter 14).

10   1.5 Emissions Scenarios and Illustrative Mitigation Pathways (IMPs)
11   Scenarios are a powerful tool for exploring an uncertain future world against the background of alternative
12   choices and development. Scenarios can be constructed using both narrative and quantitative methods.
13   When these two methods are combined they provide complementary information and insights. Quantitative
14   and narrative models are frequently used to represent scenarios to explore choices and challenges. The
15   IPCC has a long history of assessing scenarios (Nakicenovic et al. 2000; van Vuuren et al. 2011, 2014; see
16   also section 1.6 of AR6 WGI for a history of scenarios within the IPCC). This WGIII assessment employs
17   a wide range of qualitative and quantitative scenarios including quantitative scenarios developed through a
18   wide and heterogeneous set of tools ranging from spreadsheets to complex computational models (Annex
19   III provides further discussion and examples of computational models).
20   The concept of an illustrative pathway (IP) was introduced in IPCC Special Report on 1.5 (IPCC 2018b)
21   to highlight a subset of the quantitative scenarios, drawn from a larger pool of published literature, with
22   specific characteristics that would help represent some of the key findings emerging from the assessment
23   in terms of different strategies, ambitions and options available to achieve the Paris goals.
24   Integrated Assessment Models (IAMs) are the primary tools for quantitatively evaluating the technological
25   and macro-economic implications of decarbonisation, particularly for global long-term pathways. They
26   broadly divide into ‘stylized aggregate benefit-cost models’, and more complex, ‘detailed process’ IAMs
27   (Weyant 2017), often mirroring the benefit-cost and cost-effective approaches outlined in 1.7.1, with more
28   detailed classification in eg. Nikas et al. (2019). IAMs embody a number of structural and socio-
29   demographic assumptions and include multiple modelling approaches, ranging from economic optimising
30   behaviour to simulation (See Annex III). Detailed process models can include energy system models used
31   to analyse decarbonisation and ‘net zero’ scenarios by international agencies (eg. IEA 2020a).
32   Calculating cost-effective trajectories towards given goals typically involves detailed process IAMs. Often
33   these calculate the dynamic portfolio of technologies consistent with a given climate target. Some track
34   records of technology forecasting in IAMs are outlined in Chapters 2.5.4, and Box 16.1. Climate targets
35   may be imposed in models in a variety of ways that include, but are not limited to, constraints on emissions
36   or cumulated emissions (carbon budgets), and the pricing of emissions. The time-path of mitigation costs
37   calculated through these models may be translated into ‘shadow prices’ that (like the social-cost-of-carbon)
38   offer a benchmark to assess the cost-effectiveness of investments, as used by some governments and
39   companies (1.8.2).
40   Scenarios in the IPCC and AR6. For AR6, WG III received submissions of more than 2500 model-based
41   scenarios published in the scientific literature. Such scenarios, which explore different possible evolutions
42   of future energy and land use (with or without climate policy) and associated emissions, are made available

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1    through an interactive AR6 scenario database. The main characteristics of pathways in relation to ‘net zero’
2    emissions and remaining ‘carbon budgets’ are summarised in Box 3.5 in Chapter 3. The warming
3    contribution of CO2 is very closely related to cumulative CO2 emissions, but the remaining ‘carbon budget’
4    for a given warming depends strongly inter alia on emissions of other GHGs; for targets below 2°C this
5    may affect the corresponding ‘carbon budget’ by c. +/- 220GtCO2, compared to central estimates of around
6    500GtCO2 (for 1.5°C) and 1350GtCO2 (for 2°C) (AR6 WGI, Table SPM.2; Cross-Working Group Box 1
7    in Chapter 3).
 8   Pathways and ‘net zero’. The date at which the world needs aggregate emissions to reach net zero for Paris-
 9   consistent temperature goals depends both on progress in reducing non-CO2 GHG emissions and near-term
10   progress in reducing CO2 emissions. Faster progress in the near term extends the date at which net zero
11   must be reached, while conversely, slower near-term progress brings the date even closer to the present.
12   Some of the modelled 1.5°C pathways with limited overshoot cut global CO2 emissions in half until 2030,
13   which allows for a more gradual decline thereafter, reaching net zero CO2 after 2050; also, net zero GHGs
14   occurs later, with remaining emissions of some non-CO2 GHGs compensated by ‘net negative’ CO2 (see
15   Annex I and FAQ 1.3, and Cross-Chapter Box 3 in Chapter 3).
16   Drawing from the scenarios database, five Illustrative Mitigation Pathways’ (IMPs) were defined for this
17   report (Figure 3.5 in Chapter 3 and Table 1.1). These are introduced here, with a more complete description
18   and discussion provided in Section 3.2.5 of Chapter 3. These IMPs were chosen to illustrate key themes
19   with respect to mitigation strategies across the entire WG III assessment. The IMPs embody both a storyline,
20   which describes in narrative form the key socio-economic characteristics of that scenario, and a quantitative
21   illustration providing numerical values that are internally consistent and comparable across chapters of this
22   report. Quantitative IMPs can be associated directly with specific human activities and provide a
23   quantitative point of reference that links activities in different parts of socioeconomic systems. Some parts
24   of the report draw on these quantitative scenarios, whilst others use only the narratives. No assessment of
25   the likelihood of each IMP has been made (as they reflect both human choice and deep uncertainty).


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1      Figure 1.3 Illustrative Mitigation Pathways (IMPs) used in AR6 – illustration of key features and levels of
2                                                     ambition
 4   The IMPs are organized around two dimensions: the level of ambition consistent with meeting Paris goals
 5   and the scenario features (Figure 1.4). The IMPs explore different pathways potentially consistent with
 6   meeting the long-term temperature goals of the Paris Agreement. As detailed in Section 3.2.5 of Chapter 3
 7   and Chapter 4, a pathway of Gradual Strengthening of current policies (IMP-GS) to 2030, if followed by
 8   very fast reductions, may stay below 2C. The IMP-NEG pathway, with somewhat deeper emission
 9   cutbacks to 2030, might enable 1.5C to be reached but only after significant overshoot, through the
10   subsequent extensive use of CDR in the energy and the industry sectors to achieve net negative global
11   emissions, as discussed in Chapters 3, 12, 7, 6, and 10.
12   Three other IMPs illustrate different features of technology scenarios with more short term rapid emission
13   reductions, which could deliver outcomes compatible with the temperature range in the Paris agreement
14   without large overshoot. Based on the assessment in Section 5.3.3 of Chapter 5, one key mitigation strategy
15   would be to rely on the opportunities for reducing demand (IMP-LD). Chapter 6 and the Chapter 7-11 show
16   how energy systems based on accelerated deep renewable energy penetration and electrification can also
17   provide a pathway to deep mitigation (IMP-REN). Chapter 4, 17 and 3 provide insights how shifting
18   development pathways can lead to deep emission reductions and achieve sustainable development goals
19   (IMP-SP).
20   These pathways can be implemented with different levels of ambition, that can be measured through the
21   classes (C) of temperature levels from the scenarios database, see Chapter 3 (Table 3.2). In the IMP
22   framework, Section 3.2.5 in Chapter 3 presents and explores quantitative scenarios that can limit warming
23   to 1.5 °C (with a probability of 50% or greater, i.e., C1 for the illustrated quantification of LD, SP and REN,
24   and C2 for NEG scenario), along with others GS pathway which keeps warming below 2 oC with a
25   probability of 67% or greater (C3). In addition to these primary IMPs, the full scenario database contains
26   sensitivity cases that explore alternative warming levels.
27   In addition to the IMPs two additional scenarios were selected, which illustrate the consequences of current
28   policies and pledges. Current Policies (CurPol) explores the consequences of continuing along the path of
29   implemented climate policies in 2020 and only a gradual strengthening after that, drawing on numerous
30   such scenarios in the literature. Moderate Action (ModAct) explores the impact of implementing NDCs to
31   2030, but without further strengthening; both results in global mean temperature above 2oC. They provide
32   benchmarks against which to compare the IMPs.
33   Table 1.1 summarises the main storyline elements of the reference scenarios and each IMP.

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                                                 Table 1.1 Illustrative Mitigation Pathways used in AR6

            Scenarios            Full Name       Main Policy Characteristics

            CurPol               Current         Implementation of current climate policies (mostly as reported in NDCs), neglecting stated
                                 Policies        subsequent goals and objectives (e.g. for 2030); only gradual strengthening after 2030; Grey
                                                 Covid recovery.

            ModAct               Moderate        Implementation of current policies and achievement of 2030 NDCs, with further strengthening
                                 Action          post-2030. Similarly to the situation implied by the diversity of NDCs (both policies and pledge),
                                                 a fragmented policy landscape remains; mixed Covid recovery.

                           GS    Gradual         Until 2030, primarily current NDCs are implemented; after that a strong, universal regime leads
                                 Strengthening   to coordinated and rapid decarbonisation actions.

                           Neg   Net Negative    Successful international climate policy regime reduces emissions below ModAct or GS to 2030,
                                 Emissions       but with a focus on the long-term temperature goal, negative emissions kick in at growing scales
                                                 thereafter, so that mitigation in all sectors also includes a growing and ultimately large reliance
                                                 on negative emissions, with large ‘net global negative’ after 2050 to meet 1.5C after significant

                           Ren   Renewables      Successful international climate policy regime with immediate action particularly policies and

                   1.5/<                         incentives (including international finance) favouring renewable energy; Less emphasis on
                     2                           negative-emission technologies. Rapid deployment and innovation of renewables and systems;
                                                 electrification of all end-use.

                           LD    Low Demand      Successful international climate policy regime with immediate action on the demand side; policies
                                                 and financial incentives favouring reduced demand that in turn leads to early emission reductions;
                                                 this reduces the decarbonisation effort on the supply side.

                           SP    Shifting        Successful international climate policy regime with a focus on additional SDG policies aiming,
                                 Pathways        for example, at poverty reduction and broader environmental protection. Major transformations
                                                 shift development towards sustainability and reduced inequality, including deep GHG emissions

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1    What the IMPs do and don’t do. The IMPs are, as their name implies, a set of scenarios meant to
2    illustrate some important themes that run through the entire WGIII assessment. They illustrate that the
3    climate outcomes that the individuals and society will face in the century ahead depend on individual
4    and societal choices In addition, they illustrate that there are multiple ways to successful achievement
5    of Paris long-term temperature goals.
 6   IMPs are not intended to be comprehensive. They are not intended to illustrate all possible themes in
 7   this report. They do not, for example attempt to illustrate the range of alternative socioeconomic
 8   pathways against which efforts to implement Paris goals may be set, or to reflect variations in potential
 9   regional development pathways. They do not explore issues around income distribution or
10   environmental justice, but assume implicitly that where and how action occurs can be separated from
11   who pays, in ways to adequately address such issues. They are essentially pathways of technological
12   evolution and demand shifts reflecting broad global trends in social choice. The IMPs do not directly
13   assess issues of realization linked to the “drivers and constraints” summarized in our previous section,
14   and the quantifications use, for the most part, models that are grounded mainly in the Aggregate
15   Economics Frameworks (section 7.1). As such they reflect primarily the geophysical, economic and
16   technological Dimensions of Assessment, but can be assessed in relation to the full set of Feasibility
17   criteria (section 1.8.1).
18   Together the IMPs provide illustrations of potential future developments that can be shaped by human
19   choices, including: Where are current policies and pledges leading? What is needed to reach specific
20   temperature goals under varying assumptions? What are the consequences of different strategies to meet
21   climate targets (i.e. demand-side strategy, a renewable energy strategy or a strategy with a role for net
22   negative emissions)? What are the consequences of delay? What are the implications for other SDGs of
23   various climate mitigation pathways?

25   1.6 Achieving mitigation in the context of sustainable development
26   This chapter now sets out approaches to understanding the mitigation challenge, working from its broad
27   location in the context of wider aspirations for sustainable development, then identifying specific
28   analytic approaches, before summarising the corresponding main dimensions used for assessment of
29   options and pathways in much of the report.
30   1.6.1 The Climate Change and Development Connection
31   Climate change mitigation is one of many goals that societies pursue in the context of sustainable
32   development, as evidenced by the wide range of the Sustainable Development Goals (SDGs). Climate
33   change and sustainable development as well as development more broadly, are interwoven along
34   multiple and complex lines of relationship (Fankhauser 2016; Gomez-Echeverri 2018a; Okereke and
35   Massaquoi 2017; Okereke et al. 2009), as highlighted in several previous IPCC reports (IPCC 2007,
36   2019a, 2018b, 2011a, 2014a). With its significant negative impact on natural systems, food security and
37   infrastructure, loss of lives and territories, species extinction, conflict health, among several other risks,
38   climate change poses a serious threat to development and wellbeing in both rich and poor countries
39   (IPCC 2019b, 2018b, 2007, 2011a, 2014a). Without serious efforts at mitigation and adaptation, climate
40   change could push millions further into poverty and limit the opportunities for economic development
41   (Chapter 4 and 17). It follows that ambitious climate mitigation is necessary to secure a safe climate
42   within which development and wellbeing can be pursued and sustained.
43   At the same time, rapid and largescale economic development (which has in the past driven climate
44   change through land use change and dependence on fossil fuels), is widely seen as needed to improve
45   global wellbeing and lift millions especially in low- and middle-income countries out of poverty
46   (Baarsch et al. 2020; Lu et al. 2019; Mugambiwa and Tirivangasi 2017; Chen et al. 2017; See Figure
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1    1.6). This strand of literature emphasises the importance of economic growth including for tackling
2    climate change itself, pointing to the relationship between economic development and climate resilience
3    as well as the role of industry-powered technologies such as electric vehicles in reducing GHG levels
4    and promoting wellbeing (Heinrichs et al. 2014; Kasztelan 2017). Yet, others argue that the character
5    of social and economic development produced by the nature of capitalist society (Pelling and Manuel-
6    Navarrete 2011; Koch 2012; Malm 2016) is ultimately unsustainable.
 7   There are at least two major implications of the very close link between climate change and
 8   development as outlined above. The first is that the choice of development paths made by countries and
 9   regions have significant consequences for GHG emissions and efforts to combat climate change (see
10   Chapters 2, 3, 4, 5, and 14). The second is that climate mitigation at local, national and global level
11   cannot be effectively achieved by a narrow focus on ‘climate-specific’ sectors, actors and policies; but
12   rather through a much broader attention to the mix of development choices and the resulting
13   development paths and trajectories (see Chapter 4, 6, 10; O’Neill et al. 2014).
14   As a key staple of IPCC reports and global climate policy landscape (Gidden et al. 2019; Quilcaille et
15   al. 2019; van Vuuren et al. 2017; IPCC 2014b, 2007; see also Chapter 2), integrated assessment models
16   and global scenarios (such as the “Shared Socio-Economic Pathways” – SSPs) highlight the interaction
17   between development paths, climate change and emission stabilisation (see Section 3.6 in Chapter 3).
18   The close links are also recognised in the PA (section 1.3.1).
19   The impact of climate change in limiting wellbeing is most acutely felt by the world’s poorest people,
20   communities, and nations, who have the smallest carbon footprint, constrained capacity to respond and
21   limited voice in important decision-making circles (Okereke and Ehresman 2015; Tosam and Mbih
22   2015; Mugambiwa and Tirivangasi 2017). The wide variation in the contribution to, and impact of
23   climate change within and across countries makes equity, inequality, justice, and poverty eradication,
24   inescapable aspects of the relationship between sustainable development and climate change (Reckien
25   et al. 2017; Okereke and Coventry 2016; Bos and Gupta 2019; Klinsky et al. 2017; Baarsch et al. 2020;
26   Kayal et al. 2019; Diffenbaugh and Burke 2019). This underpins the conclusion as commonly expressed
27   that climate action needs to be pursued in the context of sustainable development, equity and poverty
28   eradication (Burton et al. 2001; Smit et al. 2001; Klinsky and Winkler 2014; Tschakert and Olsson
29   2005; IPCC 2014a, 2018b).
30   1.6.2 Concepts and frameworks for integrating climate mitigation and development:
31   At one level, sustainable development can be seen as a meta framework for integrating climate action
32   with other global sustainability goals (Antal and Van Den Bergh 2016; Casadio Tarabusi and Guarini
33   2013). Fundamentally, the concept of sustainable development underscores the interlinkages and
34   interdependence of human and natural systems and the need to balance economic, social, and
35   environmental (including climate pollution) aspects in development planning and processes (Nunan
36   2017; Gomez-Echeverri 2018b; Zhenmin and Espinosa 2019).
37   Despite the appeal of the concept, tensions remain over the interpretation and practical application, with
38   acute disagreements regarding what the balancing entails in real life, how to measure wellbeing, which
39   goals to set, and the means through which such goals might be pursued (Michelsen et al. 2016; Shang
40   et al. 2019; Okereke and Massaquoi 2017; UNEP 2018b; Arrow et al. 2011; Dasgupta et al. 2015;
41   Sugiawan et al. 2019; Haberl et al. 2019).
42   Moreover, countries differ enormously in their respective situation regarding their development path –
43   a condition which affects their capability, goals, priorities and approach to the pursuit of sustainability
44   (Ramos-Mejía et al. 2018; Okereke et al. 2019; Shi et al. 2016). Most of the literature recognises that
45   despite its limitations, sustainable development with its emphasis on integrating social, economic and
46   environmental goals, provides a more comprehensive approach to the pursuit of planetary health and

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1    human wellbeing. Sustainable development is then not a static objective but a dynamic framework for
2    measuring human progress (Costanza et al. 2016; Fotis and Polemis 2018), relevant for all countries
3    even if different groups of nations experience the challenge of sustainability in different ways.
 4   Much like sustainable development, concepts like low-carbon development (Mulugetta and Urban
 5   2010; Yuan et al. 2011; Wang et al. 2017; Tian et al. 2019), climate-compatible development (CCD)
 6   (Mitchell and Maxwell 2010; Tompkins et al. 2013; Stringer et al. 2014; Bickersteth et al. 2017) and
 7   more recently climate-resilient development (CRD) (Fankhauser and McDermott 2015; Henly-Shepard
 8   et al. 2018) (see IPCC SR 1.5 2018b) have all emerged as ideas, tools and frameworks, intended to
 9   bring together the goals of climate mitigation and the SDGs, as well as development more broadly.
10   Figure 1.5 suggests that the prospects for realizing a climate-resilient and equitable world is enhanced
11   by a process of transformation and development trajectories that seek to limit global warming while
12   also achieving the SDGS. The SDGs represent medium-term goals, and long-term sustainability
13   requires continued effort to keep the world along a climate resilient development path. A key feature of
14   development or transformation pathways that achieve a climate resilient world is that they maximise
15   the synergies and minimise the trade-offs between climate mitigation and other sustainable development
16   goals (Dagnachew et al. 2018; Fuso Nerini et al. 2018; Thornton and Comberti 2017; Wüstemann et al.
17   2017; Mainali et al. 2018; Klausbruckner et al. 2016). Crucially, the nature of trade-offs and timing of
18   related decisions will vary across countries depending on circumstances including the level of
19   development, capability and access to resources (see Cross-chapter Box 5, Shifting Development Paths
20   to increase Sustainability, in Chapter 4).

23   Figure 1.4: A climate-resilient and equitable world requires limiting global warming while achieving the
24                                                    SDGS.
25                                              Source: IPCC 2018b
27   Other concepts such as “Doughnut Economics” (Raworth 2018), ecological modernisation, and
28   mainstreaming are also used to convey ideals of development pathways that take sustainability, climate
29   mitigation, and environmental limits seriously (Dale et al. 2015a). Mainstreaming focuses on
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 1   incorporating climate change into national development activities, such as the building of infrastructure
 2   (Wamsler and Pauleit 2016; Runhaar et al. 2018). The ‘green economy’ and green growth – growth
 3   without undermining ecological systems, partly by gaining economic value from cleaner technologies
 4   and systems and is inclusive and equitable in its outcomes - has gained popularity in both developed
 5   and developing countries as an approach for harnessing economic growth to address environmental
 6   issues (Bina 2013; Georgeson et al. 2017; Capasso et al. 2019; Song et al. 2020; Hao et al. 2021). Critics
 7   however argue that green economy ultimately emphasises economic growth to the detriment of other
 8   important aspects of human welfare such as social justice (Adelman 2015; Death 2014; Kamuti 2015),
 9   and challenge the central idea that it is possible to decouple economic activity and growth (measured
10   as GDP increment) from increasing use of biophysical resources (raw materials, energy) (Jackson and
11   Victor 2019; Parrique et al. 2019; Hickel and Kallis 2020; Haberl et al. 2020; Vadén et al. 2020).
12   Literature on degrowth, post growth, and post development questions the sustainability and imperative
13   of more growth especially in already industrialised countries and argues that prosperity and the ‘Good
14   Life’ are not immutably tied to economic growth (Escobar 2015; Asara et al. 2015; Kallis 2019;
15   Latouche 2018; see also Section 5.2.1 in Chapter 5). The concept of ‘just transition’ also stresses the
16   need to integrate justice concerns so as to not impose hardship on already marginalised populations
17   within and between countries (Goddard and Farrelly 2018; Smith, Jackie and Patterson 2018;
18   McCauley and Heffron 2018; Evans and Phelan 2016; Heffron and McCauley 2018; see section 1.7.2).
19   The key insight is that pursuing climate goals in the context of sustainable development requires holistic
20   thinking including on how to measure well-being, serious consideration of the notion of ecological
21   limits, at least some level of decoupling and certainly choices and decision-making approaches that
22   exploit and maximise the synergy and minimises the trade-off between climate mitigation and other
23   sustainable development goals. It also requires consideration of equity and justice within and between
24   countries. However, ideas of a synergistic relationship between development and climate mitigation
25   can sometimes offer limited practical guidelines for reconciling the tensions that are often present in
26   practical policy making (Dale et al. 2015b; Ferguson et al. 2014; Kasztelan 2017; Kotzé 2018).
27   1.6.3 Climate Mitigation, Equity and the Sustainable Development Goals (SDGs)
28   Climate action can be conceptualised as both a stand-alone and cross-cutting issue in the 2030 SDGs
29   (Makomere and Liti Mbeva 2018), given that several of the other goals such as ending poverty (Goal
30   1), zero hunger (Goal 2), good health and wellbeing (Goal 3), affordable and clean energy (Goal 7)
31   among many others are related to climate change (see Figure 3.39 in Chapter 3).
32   In addition to galvanising global collective action, the SDGs provide concrete themes, targets and
33   indicators for measuring human progress to sustainability (Kanie and Biermann 2017). The SDGs also
34   provide a basis for exploring the synergies and trade-offs between sustainable development and climate
35   change mitigation (Makomere and Liti Mbeva 2018; Mainali et al. 2018; Fuso Nerini et al. 2018;
36   Pradhan et al. 2017). Progress to date (Sachs et al. 2016) shows fulfilling SDGs is a challenge for all
37   groups of countries – developed and developing – even though the challenge differs between countries
38   and regions (Pradhan et al. 2017).
39   Historically, the industrialisation associated with economic development has involved a strong
40   relationship with GHG emissions (see Section 5.2.1 in Chapter 5). Figure 1.6 shows per capita GHG
41   emissions on the vertical axis and Historical Index of Human Development (HIHD) levels (Prados de
42   la Escosura 2015) on the horizontal axis.7 The grey line shows historic global average GHG emissions

     FOOTNOTE7 The Historical Index of Human Development (HIHD) emulates the widely used Human
     Development Index (HDI) as they both summarise in indexes, key human development dimensions consisting of
     a healthy life, knowledge and a decent standard of living. HDI is based on: life expectancy, expected years of

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1    per capita and levels of human development over time, from 1870 to 2014. The current position of
2    different regions are shown by bubbles, with sizes representing total GHG emissions. Figure 1.6 also
3    shows the estimated position of the SDGs zone for the year 2030, and a “sustainable development
4    corridor” as countries reach towards higher HDI and lower emissions. To fulfil the SDGs, including
5    SDG 13 climate action, the historic relationship needs to change.
 6   The top of the SDG zone is situated around the global per capita GHG emissions level of 5 tonnes
 7   CO2eq required for the world to be path towards fulfilling the Paris Agreement.8 The horizontal position
 8   of the SDG zone is estimated based on the HIHD levels (Prados de la Escosura 2015) of countries that
 9   have been shown to either have achieved, or have some challenges, when it comes to SDG 3, SDG 4
10   and SDG 8 (Sachs et al. 2016); as these SDGs are related to the constituent parts of the HIHD. Beyond
11   2030, the sustainable development corridor allows for increasing levels of human development while
12   lowering per capita GHG emissions.
13   Figure 1.6 shows that at present, regions with HIHD levels of around 0.5 all have emissions at or above
14   about 5tCO2eq per-capita (even more so on a consumption footprint basis, see Figure 1.1c,d), but there
15   are wide variations within this. Indeed, there are regions with HIHD levels above 0.8 which have GHG
16   per-capita emissions lower than several with HIHD levels of around 0.5. The mitigation challenge
17   involves countries at many different stages of development seeking paths towards higher welfare with
18   low emissions.
19   From Figure 1.6, there are two distinct dimensions to sustainable development pathways for fulfilling
20   the SDGs. In terms of per-capita GHG emissions (the vertical), some regions have such low levels that
21   they could increase and still be below the global average required in 2030 for the world to be on path
22   to fulfil the Paris Agreement. Meanwhile other regions with high per capita GHG emissions would
23   require a rapid transformation in technologies and practices. It is against this background that Dubash
24   (2019) emphasises placing the need for urgent action on climate change in the context of domestic
25   political priorities and the institutions within which national frameworks are crystallised.
26   Concerns over equity in the context of growing global inequality and very tight remaining global carbon
27   budgets have motivated an emphasis on equitable access to sustainable development (Peters et al. 2015;
28   Kartha et al. 2018b; Matthews et al. 2019; van den Berg et al. 2019). This literature emphasises the
29   need for less developed countries to have sufficient room for development while addressing climate
30   change (Pan et al. 2014; Winkler et al. 2013; Gajevic Sayegh 2017; Warlenius 2018; Robinson and
31   Shine 2018). Meanwhile, many countries reliant on fossil fuels, related technologies and economic
32   activities are eager to ensure tax revenues are maintained, workers and industries have income and
33   justice is embedded in the economic transformations required to limit GHG emissions (Cronin et al.
34   2021).

     schooling of children, the mean years of schooling of the adult population, and GNI per capita adjusted for
     purchasing power; the HIHD is based on: life expectancy at birth, adult literacy rates, educational enrolment rates,
     and GDP per capita, and is used in Figure 1.6 because it is available for a longer time series (Prados de la Escosura
     FOOTNOTE8 Based on global population projections of between 8 and 8.5 billion people in 2030, and GHG
     emissions levels from the C1, C2 and C3 categories of scenarios in Table 3.2 and Box 3.7 in Chapter 3.
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 2                    Figure 1.5: Sustainable development pathways towards fulfilling the SDGs.
 3   The graph shows global average per capita GHG emissions (vertical axis) and relative "Historic Index of
 4   Human Development" (HIHD) levels (horizonal) have increased globally since the industrial revolution
 5   (grey line). The bubbles on the graph show regional per capita GHG emissions and human development
 6     levels in the year 2015, illustrating large disparities. Pathways towards fulfilling the Paris Agreement
 7   (and SDG 13) involve global average per capita GHG emissions below about 5 tCO2e by 2030. Likewise,
 8    to fulfil SDGs 3, 4 and 8, HIHD levels (see footnote 7) need to be at least 0.5 or greater. This suggests a
 9     ‘sustainable development zone’ for year 2030 (in green); the in-figure text also suggests a sustainable
10   development corridor, where countries limit per capita GHG emissions while improving levels of human
11    development over time. The emphasis of pathways into the sustainable development zone differ (green
12       arrows) but in each case transformations are needed in how human development is attained while
13                                              limiting GHG emissions.

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1    Correlation between CO2 emission intensity, or absolute emission and gross domestic product growth,
2    is not rigid, unambiguous and deterministic (Ojekunle et al. 2015), but the extent to which SDGs and
3    economic growth expectations can be fulfilled while decoupling GHG emissions remains a concern
4    (Hickel and Kallis 2020; Haberl et al. 2020). Below some thresholds of absolute poverty, more
5    consumption is necessary for development to lead to well-being (see Section in Chapter 5),
6    which may not be the case at higher levels of consumption (Steinberger et al. 2020; Lamb and
7    Steinberger 2017; Section 1.7.2).
 8   In conclusion, achieving climate stabilisation in the context of sustainable development and efforts to
 9   eradicate poverty requires collective action and exploiting synergies between climate action and
10   sustainable development, while minimising the impact of trade-offs (Najam 2005; Makomere and Liti
11   Mbeva 2018; Okereke and Massaquoi 2017; Dooley et al. 2021). It also requires a focus on equity
12   considerations to avoid climate induced harm, as well as unfairness that can result from urgent actions
13   to cut emissions (Kartha et al. 2018a; Robiou du Pont et al. 2017; Pan et al. 2014). This is ever more
14   important as the diminishing carbon budget has intensified debates on which countries should have the
15   greatest claim to the ‘remaining space’ for emissions (Raupach et al. 2014) or production (McGlade
16   and Ekins 2015),amplified by persistent concerns over the insufficiency of support for means of
17   implementation, to support ambitious mitigation efforts (Pickering et al. 2015; Weikmans and Roberts
18   2019).

20   1.7    Four Analytic Frameworks for understanding mitigation response
21         strategies
22   Climate change is unprecedented in its scope (sectors, actors and countries), depth (major
23   transformations) and timescales (over generations). As such, it creates unique challenges for analysis.
24   It has been called “the greatest market failure in history” (Stern 2007); the Perfect Moral Storm
25   (Gardiner 2006) and a “super wicked problem” (Lazarus 2009; Levin et al. 2012) - one which appears
26   difficult to solve through the traditional tools and assumptions of social organisation and analysis.
27   To complement the extensive literature on risks and decision-making under uncertainty reviewed in
28   AR6-WGII (notably, Chapter 19), this section summarises insights and developments in key analytic
29   frameworks and tools particularly relevant to understanding specific mitigation strategies, policies and
30   other actions, including explaining the observed if limited progress to date. Organised partly as reflected
31   in the quotes above, these include aggregated (principally, economic) frameworks to evaluate system-
32   level choices; ethical perspectives on values and equity including stages of development and
33   distributional concerns; and transition frameworks which focus on the processes and actors involved in
34   major technological and social transitions. These need to be complemented by a fourth set of approaches
35   which shine more light on psychological/behavioural and political factors. All these frameworks are
36   relevant, and together they point to the multiple perspectives and actions required if the positive drivers
37   of emission reduction summarised in section 4 are to outweigh the barriers and overcome the
38   constraints.
39   1.7.1 Aggregated approaches: economic efficiency and global dynamics of mitigation
40   Some of the most established and influential approaches to understand aggregate causes and
41   consequences of climate change and mitigation across societies, draw upon economic theories and
42   modelling to generate global emission pathways in the absence of climate policies (a reference) and to
43   study alternative mitigation pathways (described in detail in Section 3.2.5 in Chapter 3). The underlying
44   economic concepts aggregate wealth or other measures of welfare based on utilitarian ethical
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1    foundations, and in most applications, a number of additional assumptions detailed in AR5 (Chapters 2
2    and 3).
3   Cost-benefit and cost-effectiveness analysis
 4   Such global aggregate economic studies coalesce around two main questions. One, as pioneered by
 5   Nordhaus (1992; 2008) attempts to monetize overall climate damages and mitigation costs so as to
 6   strike a ‘cost-benefit optimum’ pathway. More detailed and empirically-grounded ‘cost-effectiveness
 7   analysis’ explores pathways that would minimise mitigation costs (IPCC 2014a section 2.5; Ekholm
 8   2014; Weyant 2017) for given targets (e.g. as agreed in international negotiations, see Section 3.2 in
 9   Chapter 3). Both approaches recognise that resources are limited, and climate change competes with
10   other priorities in government policymaking, and are generally examined with some form of Integrated
11   Assessment Model (IAMs: see 1.5, and Appendix C). Depending on the regional disaggregation of the
12   modelling tools used and on the scope of the analyses, these studies may or may not address
13   distributional aspects within and across nations associated with climate policies (Bauer et al. 2020).
14   For at least 10-15 years after the first computed global cost-benefit estimate (Nordhaus 1992), the
15   dominant conclusions from these different approaches seemed to yield very different recommendations,
16   with cost-benefit studies suggesting lenient mitigation compared to the climate targets typically
17   recommended from scientific risk assessments (Weyant 2017). Over the past 10-15 years, literature has
18   made important strides towards reconciling these two approaches, both in the analytic methods and the
19   conclusions arising.
20   Damages and risks Incorporating impacts which may be extremely severe but are uncertain (known as
21   “fat tails” (Weitzman 2009, 2011), strengthens the economic case for ambitious action to avoid risks of
22   extreme climate impacts (Ackerman et al. 2010; Dietz and Stern 2015; Fankhauser et al. 2013). The
23   salience of risks has also been amplified by improved understanding of climate ‘tipping points’
24   (Lontzek et al. 2015; Lenton et al. 2019); valuations should reflect that cutting emissions reduces not
25   only average expected damages, but also the risk of catastrophic events (IWG 2021).
26   Discounting. The role of time-discounting, in weighting future climate change impacts against today’s
27   costs of mitigating emissions, has been long recognised (Weitzman 1994, 2001; Nordhaus 2007;
28   Dasgupta 2008; Stern 2007). Its importance is underlined in analytical Integrated Assessment Models
29   (IAMs) (Golosov et al. 2014; van der Ploeg and Rezai 2019; van den Bijgaart et al. 2016); also Annex
30   III. Economic literature suggests applying risk-free, public, and long-term interest rates when evaluating
31   overall climate strategy (Arrow et al. 2013; Groom and Hepburn 2017; Weitzman 2001; Dasgupta
32   2008). Expert elicitations indicate values around 2% (majority) to 3% (Drupp et al. 2018). This is lower
33   than in many of the studies reviewed in earlier IPCC Assessments, and many IAM studies since, and
34   by increasing the weight accorded to the future would increase current ‘optimal effort’. The U.S.
35   Interagency Working Group on the Social Cost of Carbon used 3% as its central value (IAWG 2016;
36   Li and Pizer 2018; Adler et al. 2017). Individual projects may require specific risk adjustments.
37   Distribution of impacts. The economic damages from climate change at the nationally aggregated and
38   subnational level are very diverse (Moore et al. 2017; Ricke et al. 2018; Carleton et al. 2020). A 'global
39   damage function’ necessarily implies aggregating impacts across people and countries with different
40   levels of income, and over generations, a process which obscures the strategic considerations that drive
41   climate policy making (Keohane and Oppenheimer 2016). Economics acknowledges there is no single,
42   objectively-defined such ‘social welfare function’ (IPCC 1995, 2014a). This applies also to distribution
43   of responses; both underline the relevance of equity (next section) and global negotiations to determine
44   national and collective objectives.

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1    Obvious limitations arise from these multiple difficulties in assessing an objective, globally-acceptable
2    single estimate of climate change damages (e.g. Pindyck 2013; Arrow et al. 2013; Auffhammer 2018;
3    Stern et al. 2021), with some arguing that agreement on a specific value can never be expected (Rosen
4    and Guenther 2015; Pezzey 2018). A new generation of cost-benefits analysis, based on projections of
5    actual observed damages, result in stronger mitigation efforts as optimal (Glanemann et al. 2020; Hänsel
6    et al. 2020). Overall the combination of improved damage functions with the wider consensus on low
7    discount rates (as well as lower mitigation costs due to innovation) has increasingly yielded ‘optimal’
8    results from benefit-cost studies in line with the range established in the Paris Agreement (see Cross-
9    Working-Group Box 1 in Chapter 3).
10   Hybrid cost-benefit approaches that extend the objective of the optimisation beyond traditional
11   welfare, adding some form of temperature targets as in (Llavador et al. 2015; Held 2019) also represent
12   a step in bridging the gap between the two approaches and result in proposed strategies much more in
13   line with those coming from the cost-effectiveness literature. Approaching from the opposite side, cost-
14   effectiveness studies have looked into incorporating benefits from avoided climate damages, to improve
15   the assessment of net costs (Drouet et al. 2021).
16   Cost-benefit IAMs utilise damage functions to derive a social cost of CO2 emissions’ (SCC - the
17   additional cost to society of a pulse of CO2 emissions). One review considered “the best estimate” of
18   the optimal [near-term] level “still ranges from a few tens to a few hundreds of dollars per ton of carbon
19   (Tol 2018)”, with various recent studies in the hundreds, taking account of risks (Taconet et al. 2019),
20   learning (Ekholm 2018) and distribution (Ricke et al. 2018). In addition to the importance of
21   uncertainty/risk, aggregation, and realistic damage functions as noted, on which some progress has been
22   made, some reviews additionally critique how IAMs represent abatement costs in terms of energy
23   efficiency and innovation (e.g. Rosen and Guenther 2015; Farmer et al. 2015; Keen 2021); see also
24   1.7.3 and 1.7.4. IAMs may better reflect associated ‘rebound’ at system level (Saunders et al. 2021),
25   and inefficient implementation would raise mitigation costs (Homma et al. 2019); conversely, co-
26   benefits – most extensively estimated for air-quality, valued at a few tens of USD/tCO2 across sixteen
27   studies (Karlsson et al. 2020) - complement global with additional local benefits (see alsoTable 1.2).
28   Whereas many of these factors affect primarily cost-benefit evaluation, discounting also determines the
29   cost-effective trajectory: Emmerling et al. (2019) find that, for a remaining budget of 1000GtCO2,
30   reducing the discount rate from 5% to 2% would more than double current efforts, limit ‘overshoot’,
31   greatly reduce a late rush to negative emissions, and improve intergenerational justice by more evenly
32   distributing policy costs across the 21st century.
33   Dynamic efficiency and uncertainty
34   Care is required to clarify what is optimised (Dietz and Venmans 2019). Optimising a path towards a
35   given temperature goal by a fixed date (e.g. 2100) gives time-inconsistent results backloaded to large,
36   last-minute investment in carbon dioxide removal. ‘Cost-effective’ optimisations generate less initial
37   effort than equivalent cost-benefit models (Gollier 2021; Dietz and Venmans 2019) as they do not
38   incorporate benefits of reducing impacts earlier.
39    ‘Efficient pathways’ are affected by inertia and innovation. Inertia implies amplifying action on long-
40   lived investments and infrastructure that could otherwise lock in emissions for many decades (Vogt-
41   Schilb et al. 2018; Baldwin et al. 2020). Chapter 3 (section 3.5) discusses interactions between near,
42   medium and long-term actions in global pathways, particularly vis-à-vis inertia. Also, to the extent that
43   early action induces low carbon innovation, it ‘multiplies’ the optimal effort (for given damage
44   assumptions), because it facilitates subsequent cheaper abatement. For example, a ‘learning-by-doing'

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1    analysis concludes that early deployment of expensive PV was of net global economic benefit, due to
2    induced innovation (Newbery 2018).
3    Research thus increasingly emphasises the need to understand climate transformation in terms of
4    dynamic, rather than static, efficiency (Gillingham and Stock 2018). This means taking account of
5    inertia, learning and various additional sources of ‘path-dependence’. Including induced innovation in
6    stylised IAMs can radically change the outlook (Acemoglu et al. 2012, 2016), albeit with limitations
7    (Pottier et al. 2014); many more detailed-process IAMs now do include endogenous technical change
8    (as reviewed in Yang et al. (2018) and Grubb et al. (2021b); also Annex III).
 9   These dynamic and uncertainty effects typically justify greater up-front effort (Kalkuhl et al. 2012;
10   Bertram et al. 2015), including accelerated international diffusion (Schultes et al. 2018), and strengthen
11   optimal initial effort in cost-benefit models (Grubb et al. 2021b; Baldwin et al. 2020). Approaches to
12   risk premia common in finance would similarly amplify the initial mitigation effort, declining as
13   uncertainties reduce (Daniel et al. 2019).
14   Disequilibrium, complex systems and evolutionary approaches
15   Other approaches to aggregate evaluation draw on various branches of intrinsically non-equilibrium
16   theories (e.g. Chang 2014). These including long-standing theories from the 1930s (e.g. Schumpeter
17   1934a; Keynes 1936) to understand situations of structurally under-employed resources, potential
18   financial instabilities (Minsky 1986), and related economic approaches which emphasise time
19   dimensions (e.g. recent reviews in Legrand and Hagemann 2017; Stern 2018). More recently
20   developing have been formal economic theories of endogenous growth building on eg. Romer (1986),
21   and developments of Schumpeterian creative destruction (Aghion et al. 2021) and evolutionary
22   economic theories which abandon any notion of full or stable resource utilisation even as a reference
23   concept (Nelson and Winter 1982; Freeman and Perez 1988; Carlsson and Stankiewicz 1991; Perez
24   2001; Freeman and Louçã 2001).
25   The latter especially are technically grounded in complex system theories (e.g. Arthur 1989, 1999;
26   Beinhocker 2007; Hidalgo and Hausmann 2009). These take inherently dynamic views of economies
27   as continually evolving systems with continuously unfolding and path-dependent properties, and
28   emphasise uncertainty in contrast to any predictable or default optimality. Such approaches have been
29   variously applied in policy evaluation (Walton 2014; Moore et al. 2018), and specifically for global
30   decarbonisation (e.g. Barker and Crawford-Brown 2014) using global simulation models. Because these
31   have no natural reference ‘least lost’ trajectory, they illustrate varied and divergent pathways and tend
32   to emphasise the diversity of possibilities and relevant policies, particularly linked to innovation and
33   potentially ‘sensitive intervention points’ (Farmer et al. 2019; see also section 1.7.3). They also illustrate
34   that different representations of innovation and financial markets together can explain why estimated
35   impacts of mitigation on GDP can differ very widely (potentially even in sign), between different model
36   types (Chapter 15, Section 15.6.3 and Box 15.7).
37   1.7.2 Ethical approaches
38   Gardiner's (2011) description of climate change as ”The Perfect Moral Storm” identified three
39   ‘tempests’. Its global dimension, in a world of sovereign states which have only fragmentary
40   responsibility and control, makes it ‘difficult to generate the moral consideration and necessary political
41   will’. Its impacts are intergenerational but future generations have no voice in contemporary affairs,
42   the usual mechanism for addressing distributional injustices, amplified by the intrinsic inequity of
43   wealthy big emitters impacting particularly poorer victims. He argues that these are exacerbated by a
44   third, theoretical failure to acknowledge a central need for ‘moral sensitivity, compassion, transnational
45   and transgenerational care, and other forms of ethical concern to rise to the surface’ to help guide
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1    effective climate action. As noted in section 1.4.6, however, equity and ethics are both a driver of and
2    constraint on mitigation.
3   Ethics and values
 4   A large body of literature examines the critical role of values, ethics, attitudes, and behaviours as
 5   foundational frames for understanding and assessing climate action, sustainable development and
 6   societal transformation (IPCC WGIII IPCC 2014a chapter 3). Most of this work is offered as a counter
 7   point or critique to mainstream literature’s focus on safe-guarding of economic growth of nations,
 8   corporations and individuals (Castree 2017; Gunster 2017). These perspectives highlight the dominance
 9   of economic utilitarianism in western philosophical thought as a key driver for unsustainable
10   consumption and global environmental change (Hoeing et al. 2015; Popescu 2016).
11   Entrenching alternative values that promote deep decarbonisation, environmental conservation and
12   protection across all levels of society is then viewed as foundational component of climate resilient and
13   sustainable development and for achieving human rights, and a safe climate world (Jolly et al. 2015;
14   Evensen 2015; Popescu 2016; Tàbara et al. 2019). The UN Human Rights Office of the High
15   Commissioner has highlighted the potentially crucial role of human rights in relation to climate change
16   (UNHCR 2018). While acknowledging the role of policy, technology, and finance, the ‘managerialist’
17   approaches that emphasise ‘technical governance’ and fail to challenge the deeper values that underpin
18   societies may not secure the deep change required to avert dangerous climate change and other
19   environmental challenges (Hartzell-Nichols 2014; Steinberger et al. 2020).
20   Social justice perspectives emphasise the distribution of responsibilities, rights, and mutual obligations
21   between nations in navigating societal transformations (Patterson et al. 2018; Gawel and Kuhlicke 2017;
22   Leach et al. 2018). Current approaches to climate action may fail to match what is required by science
23   because they tend to circumvent constraints on human behaviour, especially constraints on economic
24   interest and activity. Related literature explores governance models that are centred on environmental
25   limits, planetary boundaries and the moral imperative to prioritise the poor in earth systems governance
26   (Carley and Konisky 2020; Kashwan et al. 2020), with emphasis on trust and solidarity as foundations
27   for global co-operation on climate change (Jolly et al. 2015). A key obstacle is that the economic
28   interests of states tend to be stronger than the drivers for urgent climate action (Bain 2017).
29   Short-term interests of stakeholders is acknowledged to impede the reflection and deliberation needed
30   for climate mitigation and adaptation planning (Hackmann 2016; Herrick 2018; Sussman et al. 2016;
31   Schlosberg et al. 2017). Situationally appropriate mitigation and adaptation policies at both national
32   and international level may require more ethical self-reflection (Herrick 2018), including self-
33   transcendent values such as universalism and benevolence, and moderation which are positively related
34   to pro-environmental behaviours (Howell and Allen 2017; Jonsson and Nilsson 2014; Katz-Gerro et al.
35   2015; Braito et al. 2017).
36   Another strong theme in the literature concerns recognition of interdependence including the intimate
37   relationship between humans and the non-human world (Hannis 2016; Gupta and Racherla 2018;
38   Howell and Allen 2017), with such ecological interdependence offered as an organising principle for
39   enduring transformation to sustainability. A key policy implication of this is moving away from valuing
40   nature only in market and monetary terms to strongly incorporating existential and non-material value
41   of nature in natural resource accounting (Neuteleers and Engelen 2015; Himes-Cornell et al. 2018;
42   Shackleton et al. 2017). There has been increasing attention on ways to design climate policy
43   frameworks to help reconcile ecological virtue (with its emphasis on the collective) with and individual
44   freedoms and personal autonomy (Kasperbauer 2016; Nash et al. 2017; Xiang et al. 2019). In such a
45   framework, moderation, fairness, and stewardship are all understood and promoted as directly

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1    contributing to the ‘Good Life’. Such approaches are deemed vital to counteract tendencies to ‘free
2    ride’, and to achieve behavioural changes often associated with tackling climate change (Section 5.2.1
3    in Chapter 5).
4    Some literature suggests that attention to emotions, especially with regards to climate communication,
5    could help societies and individuals act in ways that focus less on monetary gain and more on climate
6    and environmental sustainability (Bryck and Ellis 2016; Chapman et al. 2017; Nabi et al. 2018; Zummo
7    et al. 2020).
8   Equity and representation: international public choice across time and space
 9   Equity perspectives highlight three asymmetries relevant for climate change (Okereke 2017; Okereke
10   and Coventry 2016; 1.4.6). Asymmetry in contribution highlights different contributions to climate
11   change both in historical and current terms, and apply both within and between states as well as between
12   generations (Caney 2016; Heyward and Roser 2016). Asymmetry in impacts highlight the fact that the
13   damages will be borne disproportionately across countries, regions, communities, individuals and
14   gender; moreover, it is often those that have contributed the least that stand to bear the greatest impact
15   of climate change (Shi et al. 2016; IPCC 2014a). Asymmetry in capacity highlights differences of power
16   between groups and nations to participate in climate decision and governance, including capacity to
17   implement mitigation and adaptation measures.
18   If attention is not paid to equity, efforts designed to tackle climate change may end up exacerbating
19   inequities among communities and between countries (Heffron and McCauley 2018). The implication
20   is that to be sustainable in the long run, mitigation involves a central place for consideration of justice,
21   both within and between countries (Chapters 4, 14). Arguments that the injustices following from
22   climate change are symptomatic of a more fundamental structural injustice in social relations, are taken
23   to imply a need to address the deeper inequities within societies (Routledge et al. 2018).
24   Climate change and climate policies affect countries and people differently, with the poor likely to be
25   more affected (1.6.1). Ideas of ‘just transition’ (outlined in 1.8.2.) often have a national focus in the
26   literature, but also imply that mitigation should not increase the asymmetries between rich and poor
27   countries, implying a desire for transitions which seek reduce (or at least avoid adverse) distributional
28   affects. Thus, it comes into play in the timing of zero emissions (chapter 3 and 14). International climate
29   finance in which rich countries finance mitigation and adaptation in poor countries is also essential for
30   reducing the asymmetries between rich and poor countries (1.6.3 and chapter 15).
31   Equity across generations also matters, i.e., the distribution between the present and future generations.
32   One aspect is discounting (1.7.1). Another approach has been to study the burdens on each generation
33   following from the transition to low-carbon economies (IPCC 2014a chapter 3, Cross Working Group
34   Box 3 in Chapter 12). Suggestions include shifting more investments into ‘natural capital’, so that future
35   generations will inherit less physical capital but a better environment, or financing mitigation efforts
36   today using governmental debt redeemed by future generations (Broome 2012; Heijdra et al. 2006; Karp
37   and Rezai 2014; Hoel et al. 2019).
38   1.7.3 Transition and transformation processes
39   This report uses the term transition as the process, and transformation as the overall change or outcome,
40   of large-scale shifts in technological, economic and social systems, called socio-technical systems in
41   the innovation literature. Typically, new technologies, ideas and associated systems initially grow
42   slowly in absolute terms, but may then ‘take-off’ in a phase of exponential growth as they emerge from
43   a position of niche into mainstream diffusion, as indicated by the ‘S-curve’ growth in Figure 1.7 (lower
44   panel). These dynamics arise from interactions between innovation (in technologies, companies and

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1    other organisations), markets, infrastructure and institutions, at multiple levels (Geels et al. 2017;
2    Kramer 2018). Consequently, interdisciplinary perspectives are needed (Turnheim et al. 2015; Geels et
3    al. 2016; Hof et al. 2020). Beyond aggregated economic perspectives on dynamics (, these
4    emphasise the multiple actors and processes involved.

7                         Figure 1.6: Transition dynamics: levels, policies and processes
 8       Note: The lower panel illustrates growth of innovative technologies or practices, which if successful
 9     emerge from niches into an S-shape dynamic of exponential growth. The diffusion stage often involves
10       new infrastructure and reconfiguration of existing market and regulatory structures (known in the
11   literature as the “socio-technical regime”). During the phase of more widespread diffusion; growth levels
12         off to linear, then slows as the industry and market matures. The processes displace incumbent
13       technologies/practices which decline, initially slowly but then at an accelerating pace. Many related
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1     literatures identify three main levels with different characteristics, most generally termed micro, meso
2      and macro. Transitions can be accelerated by policies appropriately targeted, which may be similarly
3     grouped and sequenced (upper panel) in terms of corresponding three pillars of policy (Section 1.7.3);
4        generally all are relevant, but their relative importance differs according to stage of the transition.
 6   Technological Innovation Systems (TIS) frameworks (chapter 16.4) focus on processes and policies of
 7   early innovation and ‘emergence’, which combine experimentation and commercialisation, involving
 8   Strategic Niche Management (Rip and Kemp 1998; Geels and Raven 2006). Literatures on the wider
 9   processes of transition highlight different stages (eg. Cross-Chapter box 12 in Chapter 16) and scales
10   across three main levels, most generally termed micro, meso and macro (Rotmans et al. 2001).
11   The widely-used ‘Multi-Level Perspective’ or MLP (Geels 2002) identifies the meso-level as the
12   established ‘socio-technical (ST) regime’, an set of interrelated sub-systems which define rules and
13   regulatory structures around existing technologies and practices. The micro level is an ecosystem of
14   varied niche alternatives, and overlaying the ST regime is a macro ‘landscape’ level. Transitions often
15   start with niche alternatives (Köhler et al. 2019; Grin et al. 2010), which may break through to wider
16   diffusion (second stage in Figure 1.8), especially if external landscape developments ‘create pressures
17   on the regime that lead to cracks, tensions and windows of opportunity’ (Geels 2010; Rotmans et al.
18   2001); an example is climate change putting sustained pressure on current regimes of energy production
19   and consumption (Kuzemko et al. 2016). There are continual interactions between landscape, regime
20   and niches, with varied implications for Transition Management (Loorbach 2010; Rotmans et al. 2001).
21   In contrast to standard economic metrics of marginal or smooth change (e.g. elasticities), transition
22   theories emphasise interdisciplinary approaches and the non-linear dynamics, social, economic and
23   environmental aspects of transitions to sustainability (Köhler et al. 2018; Cherp et al. 2018). This may
24   explain persistent tendencies to underestimate the exponential pace of change now being observed in
25   renewable electricity (Chapters 2, 6) and emerging in mobility (Chapter 10).
26   Recent decades have seen parallel broadening of economic perspectives and theories. Building also on
27   the New Institutional Economics literatures (Williamson 2000), Grubb et al. (2015) classify these into
28   three ‘domains of economic decision-making’ associated with different branches of economic theory,
29   respectively (1) behavioural and organisational; (2) neoclassical and welfare, and (3) evolutionary and
30   institutional. Like MLP, these are related to different social and temporal scales, as applied also in
31   studying the ‘adaptive finance’ in UK electricity transition (Hall et al. 2017). There are significant
32   differences but these approaches all point to understanding the characteristics of different actors,
33   notably, individuals/local actors; larger corporate organisations (public or private); and (mainly) public
34   authorities, each with different decision-making characteristics.
35   Sustainability may require purposeful actions at the different levels to foster the growth of sustainable
36   technologies and practices, including support for niche alternatives (Grin et al. 2010). The middle level
37   (established ‘socio-technical regime’) tends to resist major change, reforms generally involve pressures
38   from the other two levels. Thus, transitions can be accelerated by policies appropriately targeting
39   relevant actors at the different levels (Köhler et al. 2019), the foundations for “three pillars of policy”
40   (Grubb et al. 2014), which logically evolve in the course of transition (Figure 2.6a). Incumbent
41   industries have to adapt if they are to thrive within the growth of new systems. Policy may need to
42   balance existing socio-technical systems with strategic investment and institutional development of the
43   emerging niches (e.g. the maintenance of energy provision and energy security with the development
44   of renewables), and help manage declining industries (Koasidis et al. 2020).

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 1   There is usually a social dimension to such transitions. Key elements include capacity to transform
 2   (Folke et al. 2010), planning, and interdisciplinarity (Woiwode 2013). The Second World War
 3   demonstrated the extent to which crises can motivate (sometimes positive) change across complex
 4   social and technical systems, including industry, and agriculture which then doubled its productivity
 5   over 15 years (Roberts and Geels 2019b). In practice, climate change may involve a combination of
 6   (reactive) transformational adaptation, and (proactive) societal transformation (Feola 2015), the latter
 7   seen as reorientation (including values and norms) in a sustainable direction (Section 5.4 in Chapter 5),
 8   including eg. ‘democratisation’ in energy systems (Sorman et al. 2020). Business change management
 9   principles could be relevant to support positive social change (Stephan et al. 2016). Overall, effective
10   transitions rest on appropriate enabling conditions, which can also link socio-technical transitions to
11   broader development pathways (Cross-Chapter Box 12 in Chapter 16).
12   Transition theories tend to come from very different disciplines and approaches compared to either
13   economics or other social sciences, with less quantification, notwithstanding evolutionary and complex
14   system models ( However, a few distinct types of quantitative models of ‘socio-technical
15   energy transition’ (Li et al. 2015) have emerged. For policy evaluation, transitions can be viewed as
16   processes in which dynamic efficiency (1.7.2) dominates over static allocative efficiency, with potential
17   ‘positive intervention points’ (Farmer et al. 2019). Given inherent uncertainties, there are obvious risks
18   (e.g. Alic and Sarewitz 2016). All this may make an evaluation framework of risks and opportunities
19   more appropriate than traditional cost-benefit (Mercure et al. 2021), and (drawing on lessons from
20   renewables and electric vehicles), create foundations for sector-based international ‘positive sum
21   cooperation’ in climate mitigation (Sharpe and Lenton 2021).
22   1.7.4 Approaches from psychology and politics of changing course
23   The continued increase in global emissions to 2019, despite three decades of scientific warnings of ever-
24   greater clarity and urgency, motivates growing attention in the literature to the psychological ‘faults of
25   our rationality’ (Bryck and Ellis 2016), and the political nature of climate mitigation.
26   Psychological and behavioural dimensions
27   AR5 emphasised that decision processes often include both deliberate (‘calculate the costs and
28   benefits’) and intuitive thinking, the latter utilising emotion- and rule-based responses that are
29   conditioned by personal past experience, social context, and cultural factors (e.g. Kahneman 2003), and
30   that laypersons tend to judge risks differently than experts - for example, ‘intuitive’ reactions are often
31   characterised by biases to status quo and aversion to perceived risks and ambiguity (Kahneman and
32   Tversky 1979). Many of these features of human reasoning create ‘psychological distance’ from climate
33   change (Spence et al. 2012; Marshall 2014). These can impede adequate personal responses, in addition
34   to the collective nature of the problem, where such problems can take the form of ‘uncomfortable
35   knowledge’, neglected and so becoming ‘Unknown knowns’ (Sarewitz 2020).These decision processes,
36   and the perceptions that shape them, have been studied through different lenses from psychology
37   (Weber 2016) to sociology (Guilbeault et al. 2018), and media studies (Boykoff 2011). Karlsson and
38   Gilek (2020) identify science denialism and ‘decision thresholds’ as key mechanisms of delay.
39   Experimental economics (Allcott 2011) also helps explain why cost-effective energy efficiency
40   measures or other mitigation technologies are not taken up as fast or as widely as the benefits might
41   suggest, including procrastination and inattention, as “we often resist actions with clear long-term
42   benefits if they are unpleasant in the short run.” (Allcott and Mullainathan 2010). Incorporating
43   behavioural and social dynamics in models is required particularly to better represent the demand side
44   (Nikas et al. 2020), eg. Safarzyńska (2018) demonstrates how behavioural factors change responses to
45   carbon pricing relative to other instruments. A key perspective is to eschew ‘either/or’ between
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1    economic and behavioural frameworks, as the greatest effects often involve combining behavioural
2    dimensions (e.g. norms, social influence networks, convenience and quality assurance) with financial
3    incentives and information (Stern et al. 2010). Randomised, controlled field trials can help predict the
4    effects of behavioural interventions (Levitt and List 2009; McRae and Meeks 2016; Gillan 2017).
5    Chapter 5 explores both positive and negative dimensions of behaivour in more depth, including the
6    development of norms and interactions with the wider social context, with emphasis upon the services
7    associated with human wellbeing, rather than the economic activities per se.
8   Socio-political and institutional approaches
 9   Political and institutional dynamics shape climate change responses in important ways, not least because
10   incumbent actors have frequently blocked climate policy (1.4.5). Institutional perspectives probe
11   networks of opposition (Brulle 2019) and emphasise that their ability to block - as well as the ability
12   of others to foster low carbon transitions - are structured by specific institutional forms across countries
13   (Lamb and Minx 2020). National institutions have widely been developed to promote traditionally
14   fossil-fuel based sectors like electricity and transport as key to economic development, contributing to
15   carbon lock-in (Seto et al. 2016) and inertia (Rosenschöld et al. 2014).
16   The influence of interest groups on policy-making varies across countries. Comparative political
17   economy approaches tend to find that countries where interests are closely coordinated by governments
18   (‘coordinated market economies’) have been able to generate transformative change more than those
19   with a more arms-length, even combative relationship between interest groups and governments
20   (‘liberal market economies’) (Lachapelle and Paterson 2013; Meckling 2018; Ćetković and Buzogány
21   2016; Zou et al. 2016). ‘Developmental states’ often have the capacity for strong intervention but any
22   low-carbon interventions may be overwhelmed by other pressures and very rapid economic growth
23   (Wood et al. 2020a).
24   Institutional features affecting climate policy include levels and types of democracy (Povitkina 2018),
25   electoral systems, or levels of institutional centralisation (federal vs unitary states, presidential vs
26   parliamentary systems) (Steurer and Clar 2018; Clulow 2019; Lachapelle and Paterson 2013). Countries
27   that have constructed an overarching architecture of climate governance institutions (e.g. cross-
28   department and multilevel coordination, and semi-autonomous climate agencies), are more able to
29   develop strategic approaches to climate governance needed to foster transformative change (Dubash
30   2021).
31   Access of non-governmental organisations (NGOs) to policy processes enables new ideas to be adopted,
32   but too close an NGO-government relation may stifle innovation and transformative action (Dryzek et
33   al. 2003). NGO campaigns on fracking (Neville et al. 2019) or divestment (Mangat et al. 2018) have
34   raised attention to ideas such as ‘stranded assets’ in policy arenas (Piggot 2018; Newell et al. 2020;
35   Paterson 2021; Green 2018). Attempts to depoliticise climate change may narrow the space for
36   democratic participation and contestation, thus impacting policy responses (Swyngedouw 2010, 2011;
37   Kenis and Lievens 2014). Some institutional innovations have more directly targeted enhanced public
38   deliberation and participation, notably in citizens’ climate assemblies (Howarth et al. 2020) and in the
39   use of legal institutions to litigate against those opposing climate action (Peel and Osofksy 2020). This
40   literature shows that transformative pathways are possible within a variety of institutional settings,
41   although institutional innovation will be necessary everywhere to pursue zero carbon transitions; see
42   also Chapters 4 (Section 4) and 13.
43   Balancing the forces outlined in Section 4.6 in Chapter 4 typically involves building coalitions of actors
44   who benefit economically from climate policy (Levin et al. 2012). Policy stability is critical to enabling
45   long-term investments in decarbonisation (Rietig and Laing 2017; Rosenbloom et al. 2018). Policy

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 1   design can encourage coalitions to form, that sustain momentum by supporting further policy
 2   development to accelerate decarbonisation (Roberts et al. 2018), for example by generating
 3   concentrated benefits to coalition members (Millar et al. 2020; Bernstein and Hoffmann 2018; Meckling
 4   2019), as with renewable feed-in-tariffs (FiTs) in Germany (Michaelowa et al. 2018). Coalitions may
 5   also be sustained by overarching framings, especially to involve actors (e.g. NGOs) for whom the
 6   benefits of climate policy are not narrowly economic. However policy design can also provoke
 7   coalitions to oppose climate policy, as in the FiT programme in Ontario (Stokes 2013; Raymond 2020)
 8   or the yellow vest protests against carbon taxation in France (Berry and Laurent 2019). The ‘just
 9   transitions’ frame can thus also be understood in terms of coalition-building, as well as ethics, as the
10   pursuit of low carbon transitions which spread the economic benefits broadly, through ‘green jobs’, and
11   the redistributive policies embedded in them both nationally and globally (Healy and Barry 2017;
12   Winkler 2020). Appropriate policy design will be different at different stages of the transition process
13   (Meckling et al. 2017; Breetz et al. 2018).
14   Integration. Politics is ultimately the way in which societies make decisions – which in turn, reflect
15   diverse forces and assumed frameworks. Effective policy requires understandings which combine
16   economic efficiency, ethics and equity, the dynamics and processes of large-scale transitions, and the
17   role of psychology and politics. No one framework is adequate to such a broad-ranging goal, nor are
18   single tools. Chapter 13 (Figure 13.6) presents a ‘framing’ table for policy instruments depending on
19   the extent to which they focus on mitigation per se or wider socio-economic development, and whether
20   they aim to shift marginal incentives or drive larger transitions. Holistic analysis needs to bridge
21   modelling, qualitative transition theories illuminated by case studies, and practice-based action research
22   (Geels et al. 2016).
23   These analytic frameworks also point to arenas of potential synergies and trade-offs (when broadly
24   known), and opportunities and risks (when uncertainties are greater), associated with mitigation. This
25   offers theoretical foundations for mitigation strategies which can also generate co-benefits. Climate
26   policy may help to motivate policies with beneficial synergies (such as the consumer cost savings from
27   energy efficiency, better forest management, transitions to cleaner vehicles) and opportunities (such as
28   stimulating innovation), by focusing on options for which the positives outweigh the negatives, or can
29   be made to through smart policy (e.g. Karlsson et al. 2020). More broadly, climate concerns may help
30   to attract international investment, and help overcoming bureaucratic or political obstacles to better
31   policy, to support synergies between mitigation, adaptation, and other SDGs, a foundation for shifting
32   development pathways towards sustainability (Section 1.6.1; Chapter 17)

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1         Table 1.2: Potential for net co-benefits arising from synergies and trade-offs, opportunities and risks
                                            Positives                         Negatives
         Broadly known (e.g.          air Synergies                           Trade-offs
         pollution, distributional)
         Deep uncertainties (e.g. radical Opportunities                       Risks
                                            Select options with maximum Ameliorate    trade-offs (e.g.
                                            synergies, and foster and revenue redistribution), and
                                            exploit opportunities       minimize or allocate risks
                                             ↑     ↑      ↑      ↑        ↑   ↑     ↑      ↑     ↑     ↑       ↑
                                                 Net co-benefits from appropriate mitigation choices

6    1.8       Feasibility and multi-dimensional assessment of mitigation
7    1.8.1 Building on the SR1.5 assessment framework: feasibility and enabling conditions
 8   While previous ARs dealt with the definition of alternative mitigation pathways mostly exploring the
 9   technological potentials, latest research focused on what kind of mitigation pathways are feasible in a
10   broader sense, underlining the multi-dimensional nature of the mitigation challenge. Building on
11   frameworks introduced by Majone (1975) and Gilabert and Lawford-Smith (2012), SR1.5 introduced
12   multi-dimensional approaches to analysing ‘feasibility’ and ‘enabling conditions’, which AR6 develops
13   and applies broadly in relation to six ‘dimensions of feasibility assessment’ (Figure 1.7). Two reflect
14   the physical environment:
15   •     Geophysical, not only the global risks from climate change but also, for technology assessment, the
16         global availability of critical resources;
17   •     Environmental & ecological, including local environmental constraints and co-benefits of different
18         technologies and pathways
19   The other four dimensions correspond broadly to the four Analytic Frameworks outlined in Section 1.7:
20   •     Economic, particularly aggregate economic and financial indicators, and SDGs reflecting different
21         stages and goals of economic development;
22   •     Socio-cultural, including particularly ethical and justice dimensions, and social and cultural norms;
23   •     Technological, including innovation needs and transitional dynamics associated with new and
24         emergent technologies and associated systems; and
25   •     Institutional & political, including political acceptability, legal and administrative feasibility, and
26         the capacity and governance requirements at different levels to deliver sustained mitigation in the
27         wider context of sustainable development.
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1    AR6 emphasises that all pathways involve different challenges and require choices to be made.
2    Continuing ‘business as usual’ is still a choice, which in addition to the obvious geophysical risks,
3    involves not making best use of new technologies, risks of future stranded assets, greater local pollution,
4    and multiple other environmental threats.
5    The dimensions as listed provide a basis for this assessment both in the sectoral chapters (6-11),
6    providing a common framework for cross-sectoral assessment detailed further in chapter 12, and in the
7    evaluation of global pathways (Section 3.2 in Chapter 3). More specific indicators under each of these
8    dimensions offer consistency in assessing the challenges, choices, and enabling requirements facing
9    different aspects of mitigating climate change.

12                          Figure 1.7: Feasibility and related dimensions of assessment
14   Figure 1.7 also illustrates variants on these dimensions appropriate for evaluating domestic and
15   international policies (Chapters 13 and 14). The SR1.5 (Section 4.4 in Chapter 4) also introduced a
16   framework of ‘Enabling Conditions for systemic change’, which as illustrated also has key dimensions
17   in common with those of our feasibility assessment. In AR6 these enabling conditions are applied
18   particularly in the context of shifting developments pathways (Chapter 4.4).
19   Some fundamental criteria may span across several dimensions. Most obviously, issues of ethics and
20   equity are intrinsic to the economic, socio-cultural (values, including intergenerational justice) and
21   institutional (e.g., procedural justice) dimensions. Geopolitical issues could also clearly involve several
22   dimensions, e.g., concerning the politics of international trade, finance and resource distribution
23   (economic dimension); international vs nationalistic identity (socio-cultural); and multilateral
24   governance (institutional).
25   In this report, chapters with a strong demand-side dimension also suggest a simple policy hierarchy,
26   reflecting that avoiding wastage – demands superfluous to human needs and wants – can carry benefits
27   across multiple indicators. Consequently, chapters 5 and 10 organise key actions in a hierarchy of Avoid
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1    (unnecessary demand) – Shift (to less resource-intensive modes) - Improve (technologies for existing
2    modes), with a closely-related policy hierarchy in Chapter 9 (buildings).
3    1.8.2 Illustrations of multi-dimensional assessment: lock-in, policies and ‘just
4          transition’
5    The rest of this section illustrates briefly how such multi-dimensional assessment, utilising the
6    associated analytic frameworks, can shed light on a few key issues which arise across many chapters of
7    this assessment.
 8   ‘Carbon Lock-in’. The continued rise of global emissions reflects in part the strongly path-dependent
 9   nature of socio-economic systems, which implies a historic tendency to ‘carbon lock-in’ (Unruh 2000).
10   An interdisciplinary review (Seto et al. 2016) identifies a dozen main components organised into four
11   types, across the relevant Dimensions of Assessment as summarised in Table 1.3.

12                        Table 1.3: Carbon lock-in – types and key characteristics
13                                      Source: Adapted from (Seto et al. 2016)

       Lock-in type      Key characteristics

       Economic          - Large investments with long lead-times and sunk costs, made on basis of anticipated use of
                         resources, capital, and equipment to pay back the investment and generate profits
                         - Initial choices account for private but not social costs and benefits

       Socio-cultural,   - Lock-in through social structure (e.g., norms and social processes)
       equity and        - Lock-in through individual decision making (e.g., psychological processes)
       behaviour         - Single, calculated choices become a long string of non-calculated and self-reinforcing habits
                          which are- Interrupting habits is difficult but possible (e.g., family size, thermostat setting) to
                         - Individuals and communities become dependent on fossil-fuel economy, meaning that change
                         may have adverse distributional impacts

       Technology        - Learning-by-doing and scale effects, including cumulative nature of innovation, reinforces
       and               established technologies
       infrastructure    - Interaction of technologies and networks (physical, organisational, financial) on which they
                         - Random, unintentional events including network and learning effect final outcomes (e.g.,
                         Lock-in to the QWERTY keyboard)

       Institutional &   - Powerful economic, social, and political actors seek to reinforce status quo that favours their
       political         interests
                         - Laws and Institutions, including regulatory structures, are designed to stabilise and lock -in
                         also to provide long-term predictability (socio-technical regimes in transition theories)
                         - Beneficial and intended outcomes for some actors
                         - Not random chance but intentional choice (e.g., support for renewable electricity in
                         Germany) can develop political consistencies that reinforce a direction of travel
15   Along with the long lifetime of various physical assets detailed in AR5, AR6 underlines the exceptional
16   degree of path-dependence in urban systems (Chapter 8) and associated buildings (9) and transport (10)
17   sectors, but it is a feature across almost all the major emitting sectors. The (typically -expected)
18   operating lifetimes of existing carbon-emitting assets would involve anticipated emissions (often but
19   inaccurately called ‘committed’ emissions in the literature), substantially exceeding the remaining

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1    carbon budgets associated with 1.5C pathways (Chapter 2.7). Ongoing GHG-intensive investments,
2    including those from basic industrialisation in poorer countries, are adding to this.
3    The fact that investors anticipate a level of fossil fuel use that is not compatible with severe climate
4    constraints creates a clear risk of ‘stranded assets’ facing these investors (Box 6.2), and others who
5    depend on them, which itself raises issues of equity. A multi-dimensional / multi-framework assessment
6    helps to explain why such investments have continued, even in rich countries, and the consequent risks,
7    and the complexity of shifting such investments in all countries. It may also inform approaches that
8    could exploit path-dependence in clean energy systems, if there is sufficient investment in building up
9    the low-GHG industries, infrastructures and networks required.
10   Carbon pricing. Appraisal of policy instruments also requires such multi-dimensional assessment.
11   Stern’s (2007) reference to climate change as “the greatest market failure in history” highlights that
12   damages inflicted by climate change are not properly costed in most economic decision-making.
13   Economic perspectives emphasise the value of removing fossil-fuel subsidies, and pricing emissions to
14   ‘internalise’ in economic decision-making the ‘external’ damages imposed by GHG emissions, and/or
15   to meet agreed goals. Aggregate economic frameworks generally indicate carbon pricing (on principles
16   which extend to other gases) as the most cost-effective way to reduce emissions, notwithstanding
17   various market failures which complicate this logic.9 The High Level Commission on carbon pricing
18   (Stern and Stiglitz 2017) estimated an appropriate range as USD40-80/tCO2 in 2020, rising steadily
19   thereafter. In practice the extent and level of carbon pricing implemented to date is far lower than this
20   or than most economic analyses now recommend (Section 3.6.1 in Chapter 3), and nowhere is carbon
21   pricing the only instrument deployed.
22   A socio-cultural and equity perspective emphasises that the faith in and role of markets varies widely
23   between countries – many energy systems do no in fact operate on a basis of competitive markets – and
24   that because market-based carbon pricing involves large revenues transfers, it must also contend with
25   major distributional effects and political viability (Klenert et al. 2018; Prinn et al. 2017), both domestic
26   (Chapter 13) and international (Chapter14). A major review (Maestre-Andrés et al. 2019) finds
27   persistent distributional concerns (rich incumbents have also been vocal in using arguments about
28   impacts on the poor (Rennkamp 2019), but suggests these may be addressed by combining
29   redistribution of revenues with support for low carbon innovation. Measures could include
30   redistributing the tax revenue to favour of low-income groups or differentiated carbon taxes (Metcalf
31   2009; Klenert and Mattauch 2016; Stiglitz 2019), including ‘dual track’ approaches (van den Bergh et
32   al. 2020). To an extent though, all these depend on levels of trust, and institutional capacity.
33   Technological and transitions perspectives in turn find carbon pricing incentives may only stimulate
34   incremental improvements, but other instruments may be much more effective for driving deeper
35   innovation and transitions (Chapters 14, 15, 16), whilst psychological and behavioural studies
36   emphasise many factors beyond only pricing (Sections 5.4.1 and 5.4.2 in Chapter 5). In practice, a wide
37   range of policy instruments are used (Chapter 13).
38   Finally, in economic theory, negotiations on a common carbon price (or other common policies) may
39   have large benefits (less subject to ‘free riding’) compared to a focus on negotiating national targets
40   (Cramton et al. 2017a). The fact that this has never even been seriously considered (outside some efforts
41   in the EU) may reflect the exceptional sovereignty sensitivities around taxation and cultural differences
42   around the role of markets. However, carbon pricing concepts can be important outside of the traditional

     FOOTNOTE9 Beyond GHG externalities, Stern (2015) lists such market failures as; inadequate R&D; failures in
     risk/capital markets; network effects creating coordination failures; wider information failures; and co-benefits.
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1    market (‘tax or trading’) applications. A ’social cost of carbon’ can be used to evaluate government and
2    regulatory decisions, to compensate for inadequate carbon prices in actual markets, and by companies
3    to reflect the external damage of their emissions and strategic risks of future carbon controls (Zhou and
4    Wen 2020). An agreed ‘social value of mitigation activities’ could form a basic index for underwriting
5    risks in low carbon investments internationally (Hourcade et al. 2021a).
 6   Thus, practical assessment of carbon pricing inherently needs multi-dimensional analysis. The realities
 7   of political economy and lobbying have to date severely limited the implementation of carbon pricing
 8   (Mildenberger 2020), leading some social scientists to ask ‘Can we price carbon?’ (Rabe 2018). Slowly
 9   growing adoption (World Bank 2019) suggests “yes”, but only through complex evolution of efforts: a
10   study of 66 implemented carbon pricing policies show important effects of regional clustering,
11   international processes, and seizing political windows of opportunity (Skovgaard et al. 2019).
12   Just Transitions. Finally, whilst ‘transition’ frameworks may explain potential dynamics that could
13   transform systems, a multi-dimensional/multi-framework assessment underlines the motivation for ‘just
14   transitions’ (see subsection in this chapter and section 4.5 in Chapter 4). This can be defined as
15   a transition from a high-carbon to a low-carbon economy which is considered sufficiently equitable for
16   the affected individuals, workers, communities, sectors, regions and countries (Jasanoff 2018; Newell
17   and Mulvaney 2013). As noted, sufficient equity is not only an ethical issue but an enabler of deeper
18   ambition for accelerated mitigation (Hoegh-Guldberg et al. 2019; Klinsky and Winkler 2018;
19   Urpelainen and Van de Graaf 2018). Perception of fairness influences the effectiveness of cooperative
20   action (Winkler et al. 2018), and this can apply to affected individuals, workers, communities, sectors,
21   regions and countries (Newell and Mulvaney 2013; Jasanoff 2018).
22   A ‘just transitions’ framing can also enable coalitions which integrate low carbon transformations with
23   concerns for climate adaptation (Patterson et al. 2018). All this explains the emergence of ‘just transition
24   Commissions’ in several of the more ambitious developed countries and complex social packages for
25   coal phase-out in Europe (Section 4.5 in Chapter 4; Sovacool et al. 2019; Green and Gambhir 2020), as
26   well as reference to the concept in the PA and its emphasis in the Talanoa dialogue and Silesia
27   declaration (1.2.2).
28   Whilst the broad concepts of ‘just transition’ have roots going back decades, its specific realisation in
29   relation to climate change is of course complex: Section 5 in Chapter 4 identifies at least eight distinct
30   elements proposed in the literature, even before considering the international dimensions.

32   1.9 Governing climate change
33   Previous sections have highlighted the multiple factors that drive and constrain climate action, the
34   complex interconnection between climate mitigation and other societal objectives, and the diversity of
35   analytical frames for interpreting these connections. Despite the complexities, there are signs of
36   progress including increased societal awareness, change in social attitudes, policy commitments by a
37   broad range of actors and sustained emission reductions in some jurisdictions. Nevertheless, emission
38   trends at the global level remains incompatible with the goals agreed in the Paris Agreement.
39   Fundamentally, the challenge of how best to urgently scale up and speed-up the climate mitigation effort
40   at all scales –from local to global – to the pace needed to address the climate challenge is that of
41   governance understood as ‘modes and mechanisms to steer society’ (Jordan et al. 2015). The concept
42   of governance encompasses the ability to plan and create the organisations needed to achieve a desired
43   goal (Güney 2017) and the process of interaction among actors involved in a common problem for
44   making and implementing decisions (Hufty 2012; Kooiman 2003).
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1    Climate change governance has been projected as conscious transformation at unprecedented scale and
2    speed involving a contest of ideas and experimentation across scales of authority and jurisdiction
3    (Hildén et al. 2017; Laakso et al. 2017; Gordon 2018; van der Heijden 2018; Kivimaa et al. 2017). Yet,
4    there remains a sense that achieving the urgent transition to a low carbon, climate resilient and
5    sustainable world requires significant innovation in governance (Hoffmann 2011; Stevenson and
6    Dryzek 2013; Aykut 2016).
 7   Starting from an initial focus on multilateral agreements, climate change governance has long evolved
 8   into a complex polycentric structure that spans from the global to national and sub-national levels, with
 9   “multiple parallel initiatives involving a range of actors at different levels of governance” (Okereke et
10   al. 2009) and relying on both formal and informal networks and policy channels channels (Bulkeley et
11   al. 2014; Jordan et al. 2015). At the international level, implementation of the Paris Agreement and the
12   UNFCCC more broadly is proceeding in parallel with other activities in an increasingly diverse
13   landscape of loosely coordinated institutions, constituting ’regime complex’ (Keohane and Victor
14   2011), and new cooperative efforts demonstrate an evolution in the shifting authority given to actors at
15   different level of governance (Chan et al. 2018).
16   Multi-level governance has been used to highlight the notion that the processes involved in making and
17   implementing decisions on climate change is no longer the exclusive preserve of government actors but
18   rather involve a range of non-nation state actors such as cities, businesses, and civil society
19   organisations (Bäckstrand et al. 2017; Jordan et al. 2018; IPCC 2014a Chapter 13, 13.3.1 and 13.5.2).
20   Increased multi-level participation of subnational actors, along with a diversity of other transnational
21   and non-state actors have helped to facilitate increased awareness, experimentation, innovation,
22   learning and achieving benefits at multiple scales. Multi-level participation in governance systems can
23   help to build coalitions to support climate change mitigation policies (Roberts et al. 2018) and
24   fragmentation has the potential to take cooperative and even synergistic forms (Biermann et al. 2009)
25   However, there is no guarantee that multilevel governance can successfully deal with complex human-
26   ecological systems (Biermann et al. 2017; York et al. 2005; Di Gregorio et al. 2019). Multi-level
27   governance can contribute to an extremely polarised discussion and policy blockage rather than
28   enabling policy innovation (Fisher and Leifeld 2019). Fragmented governance landscape may lead to
29   coordination and legitimacy gaps undermining the regime (Nasiritousi and Bäckstrand 2019).
30   Nevertheless, the realities of the ‘drivers and constraints’ detailed in Section 4 the “glocal” nature of
31   climate change, the divided authority in world politics, diverse preferences of public and private entities
32   across the spectrum, and pervasive suspicions of free riding, implying the challenge as how to
33   incrementally deepen cooperation in a polycentric global system, rather than seeking a single, integrated
34   governance (Keohane and Victor 2016).
35   Crucially, climate governance takes place in the context of embedded power relations, operating at
36   global, national and local context. Effective rules and institutions to govern climate change are more
37   likely to emerge when where power structures and interests favour action. However widespread and
38   enduring co-operation can only be expected to when the benefits outweigh the cost of cooperation and
39   when the interest of key actors are sufficiently aligned (Barrett 1994; Victor 2011; Finus and Rübbelke
40   2008; Tulkens 2019; Mainali et al. 2018). Investigating the distribution and role of hard and soft power
41   resources, capacities and power relations within and across different jurisdictional levels is therefore
42   important to uncover hindrances to effective climate governance (Marquardt 2017). Institutions at
43   international and national levels as also critical as they have the ability to mediate power and interest of
44   actors and sustain cooperation based on equity and fair rules and outcomes. Governance, in fact, helps
45   to align and moderate the interests of actors as well as to shift perceptions, including the negative,
46   burden-sharing narratives that often accompany discussion about climate action especially in
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1    international negotiations. It is also useful for engaging the wider public and international networks in
2    imagining low carbon societies (e.g. Levy and Spicer 2013; Milkoreit 2017; Nikoleris et al. 2017;
3    Wapner and Elver 2017; Bengtsson Sonesson et al. 2019; Fatemi et al. 2020). Experimentation also
4    represents an important source of governance innovation and capability-formation, linked to global
5    knowledge and technology flows, which could reshape emergent socio-technical regimes and so
6    contribute to alternative development pathways (Berkhout et al. 2010; Roberts et al. 2018; Turnheim et
7    al. 2018; Lo and Castán Broto 2019).

9    1.10 Conclusions
10   Global conditions have changed substantially since the IPCCs Fifth Assessment in 2014. The Paris
11   Agreement and the SDGs provided a new international context, but global intergovernmental
12   cooperation has been under intense stress. Growing direct impacts of climate change are unambiguous
13   and movements of protest and activism – in countries and transnational organisations at many levels –
14   have grown. Global emissions growth had slowed but not stopped up to 2018/19, albeit with more
15   diverse national trends. Growing numbers of countries have adopted ‘net zero’ CO2 and/or GHG
16   emission goals and decarbonisation or low carbon growth strategies, but the current NDCs to 2030
17   collectively would barely reduce global emissions below present levels (1.3.3).. An unfolding
18   technology revolution is making significant contributions in some countries, but as yet its global impact
19   is limited. Global climate change can only be tackled within, and if integrated with, the wider context
20   of sustainable development, and related social goals including equity concerns. Countries and their
21   populations have many conflicting priorities. Developing countries in particular have multiple urgent
22   needs associated with earlier stages of sustainable development as reflected in the non-climate SDGs.
23   Developed countries are amongst the most unsustainable in terms of overall consumption, but also face
24   social constraints particularly arising from distributional impacts of climate policies.
25   The assessment of the key drivers for, and barriers against mitigation undertaken in this chapter
26   underscore the complexity and multidimensional nature of climate mitigation. Historically, much of the
27   academic analysis of mitigating climate change, particularly global approaches, has focused on
28   modelling costs and pathways, and discussion about ‘optimal’ policy instruments. Developments since
29   AR5 have continued to highlight the role of a wide range of factors intersecting the political, economic,
30   social and institutional domains. Yet despite such complexities, there are signs of progress emerging
31   from years of policy effort in terms of technology, social attitudes, emission reductions in some
32   countries, with tentative signs of impact on the trajectory of global emissions. The challenge remains
33   how best to urgently scale up and speed-up the climate mitigation effort at all scales –from local to
34   global – to achieve the level of mitigation needed to address the problem as indicated by climate science.
35   A related challenge is how to ensure that mitigation effort and any associated benefits of action are
36   distributed fairly within and between countries and aligned to the overarching objective of global
37   sustainable development. Lastly, globally effective and efficient mitigation will require international
38   co-operation especially in the realms of finance, and technology.
39   Multiple frameworks of analytic assessment, adapted to the realities of climate change mitigation, are
40   therefore required. We identified four main groups. Aggregate economic frameworks – including
41   environmental costs or goals, and with due attention to implied behavioural, distributional and dynamic
42   assumptions - can provide insights about trade-offs, cost-effectiveness and policies for delivering
43   agreed goals. Ethical frameworks are equally essential to inform both international and domestic
44   discourse and decisions, including the relationship with international (and intergenerational)
45   responsibilities, related financial systems, and domestic policy design in all countries. Explicit
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1    frameworks for analysing transition and transformation across multiple sectors need to draw on both
2    socio-technical transition literatures, and those on social transformation. Finally, literatures on
3    psychology, behaviour and political sciences can illuminate obstacles that have impeded progress to
4    date, and suggest ways to overcome them.
 5   No single analytical framework, or single discipline, on its own can offer a comprehensive assessment
 6   of climate change mitigation. Together they point to the relevance of growing literatures and discourses
 7   on ‘just transitions’, and the role of governance at multiple levels. Ultimately all these frameworks are
 8   needed to inform the decisions required to deepen and connect the scattered elements of progress to
 9   date, and hence accelerate progress towards agreed goals and multiple dimensions of climate change
10   mitigation in the context of sustainable development.

12   1.11 Knowledge gaps
13   Despite huge expansion in the literature (Callaghan et al. 2020), knowledge gaps remain. Modeling still
14   struggles to bring together detailed physical and economic climate impacts and mitigation, with limited
15   representation of financial and distributional dynamics. There are few interdisciplinary tools which
16   apply theories of transition and transformation to questions of economic and social impacts,
17   compounded by remaining uncertainties concerning the role of new technological sets, international
18   instruments, policy and political evaluation.
19   One scan of future research needs suggests three priority areas (Roberts et al. 2020); 1. Human welfare
20   focused development (e.g. reducing inequality), 2. How the historic position of states within
21   international power relations conditions their ability to respond to climate change, 3. Transition
22   dynamics and the flexibility of institutions to drive towards low carbon development pathways. There
23   remain gaps in understanding how international dynamics and agreements filter down to affect
24   constituencies and local implementation. Literature on the potential for supply side agreements, in
25   which producers agree to restrict the supply of fossil fuels (e.g. Asheim et al. 2019) is limited but gaining
26   increasing academic attention.
27   Nature is under pressure both at land and at sea as demonstrated by declining biodiversity (IPBES
28   2019). Climate policies could increase the pressure on land and oceans (see IPCC 2019c,b), with
29   insufficient attention to relationships between biodiversity and climate agreements and associated
30   policies. IPBES aims to coordinate with the IPCC more directly, but literature will be required to
31   support these reports.
32   Compounding these gaps is the fact that socially oriented, agriculture-related options, where human and
33   non-human systems intersect most obviously, remain under-researched (e.g. Balasubramanya and Stifel
34   2020). Efforts to engage with policies here, especially framed around ecosystem services, have often
35   neglected their “practical fitness” in favor of focusing on their “institutional fitness”, which needs to be
36   addressed in future research (Stevenson et al. 2021).
37   The relative roles of short-term mitigation policies and long-term investments, including government
38   and financial decision-making tools, remains inadequately explored. Strategic investments may include
39   city planning, public transport, EV charging networks, and CCU/CCS. Understanding how international
40   treaties can increase incentives to make such investments is all the more salient in the aftermath of
41   COVID-19, on which research is necessarily young but rapidly growing. Finally, the economic,
42   institutional and political strategies to close the gap between NDCs, actual implementation, and
43   mitigation goals– informed by the PA and the UNFCCC Global Stocktake – require much further
44   research.
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1    1.12 Roadmap to the Report
2    This Sixth Assessment Report covers Mitigation in five main parts (Figure 1.8), namely: introduction
3    and frameworks; emission trends, scenarios and pathways; sectors; institutional dimensions including
4    national and international policy, financial and technological mitigation drivers; and conclusions.

7                              Figure 1.8: The Structure of AR6 Mitigation Report
 8   Chapters 2-5 cover the big picture trends, drivers and projections at national and global levels. (2)
 9   analyses emission trends and drivers to date. (3) presents long-term global scenarios, including the
10   projected economic and other characteristics of mitigation through to balancing of sources and sinks
11   through the second half this century, and the implications for global temperature change and risks. (4)
12   explores the shorter-term prospects including NDCs, and the possibilities for accelerating mitigation
13   out to 2050 in the context of sustainable development at the national, regional and international scales.

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1    (5), a new chapter for IPCC Assessments, focuses upon the role of services and derived demand for
2    energy and land use, and the social dimensions.
 3   Chapters 6-12 examine sectoral contributions and possibilities for mitigation. (6) summarises
 4   characteristics and trends in the energy sector, specifically supply, including the remarkable changes in
 5   the cost of some key technologies since AR5; (7) examines the roles of AFOLU, drawing upon and
 6   updating the recent Special Report, including the potential tensions between the multiple uses of land;
 7   (8) presents a holistic view of the trends and pressures of urban systems, as both a challenge and an
 8   opportunity for mitigation; Chapters 9 and 10 then examine two sectors which entwine with, but go
 9   well beyond, urban systems: buildings (9) including construction materials and zero carbon buildings;
10   and transport (10), including shipping and aviation and a wider look at mobility as a general service;
11   (11) explores the contribution of industry, including supply chain developments, resource
12   efficiency/circular economy, and the cross-system implications of decarbonisation for industrial
13   systems; finally (12) takes a cross-sectoral perspective and explores cross-cutting issues like the
14   interactions of biomass energy, food and land, and carbon dioxide removal.
15   Four chapters then review thematic issues in implementation and governance of mitigation. (13)
16   explores national and sub-national policies and institutions, bringing together lessons of policies
17   examined in the sectoral chapters, as well as insights from service and demand-side perspectives (5),
18   along with governance approaches and capacity-building, and the role and relationships of sub-national
19   actors. (14) then considers the roles and status of international cooperation, including the UNFCCC
20   agreements and international institutions, sectoral agreements and multiple forms of international
21   partnerships, and the ethics and governance challenges of Solar Radiation Modification. (15) explores
22   investment and finance, including current trends, the investment needs for deep decarbonisation, and
23   the complementary roles of public and private finance. This includes climate-related investment
24   opportunities and risks (e.g. ‘stranded assets’), linkages between finance and investments in adaptation
25   and mitigation; and the impact of COVID-19. A new chapter on innovation (16) looks at technology
26   development, accelerated deployment and global diffusion as systemic issues that hold potential for
27   transformative changes, and the challenges of managing such changes at multiple levels including the
28   role of international cooperation.
29   Finally, (17) considers Accelerating the transition in the context of sustainable development, including
30   practical pathways for joint responses to climate change and sustainable development challenges. This
31   includes major regional perspectives, mitigation-adaptation interlinkages, and enabling conditions
32   including the roles of technology, finance and cooperation for sustainable development.

34   Frequently Asked Questions (FAQs)
35   FAQ 1.1 What is climate change mitigation?
36   Climate change mitigation refers to actions or activities that limit emissions of GHGs from entering the
37   atmosphere and/or reduce their levels in the atmosphere. Mitigation includes reducing the GHGs
38   emitted from energy production and use (eg. that reduces use of fossil fuels) and land use, and methods
39   to mitigate warming eg. by carbon sinks which remove emissions from the atmosphere through land
40   use or other (including artificial) mechanisms (See section 12.3, 14.4.5; see WGI for physical science,
41   and Chapter 7 for AFOLU mitigation).
42   The ultimate goal of mitigation is to preserve a biosphere which can sustain human civilisation and the
43   complex of ecosystem services which surround and support it. This means reducing anthropogenic
44   GHGs emissions towards net zero to limit the warming, with global goals agreed in the Paris
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     Final Government Distribution                       Chapter 1                           IPCC AR6 WGIII

1    Agreement. Effective mitigation strategies require an understanding of mechanisms that underpin
2    release of emissions, and the technical, policy and societal options for influencing these
3    FAQ 1.2 Which Greenhouse Gasses (GHGs) are relevant to which sectors?
4    Anthropogenic GHGs such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and
5    fluorinated gases (e.g. hydrofluorocarbons, perfluorocarbons, Sulphur hexafluoride) are released from
6    various sources. CO2 makes the largest contribution to global GHG emissions; but some have extremely
7    long atmospheric lifetimes extending to tens of thousands of years, such as F gases (Chapter 2).
 8   Different combinations of gases are emitted from different activities. The largest source of CO2 is
 9   combustion of fossil fuels in energy conversion systems like boilers in electric power plants, engines in
10   aircraft and automobiles, and in cooking and heating within homes and businesses (approximately 64%
11   of emissions, Figure SPM.2). Fossil fuels are also a major source of methane (CH4), the second biggest
12   contributor to global warming. While most GHGs come from fossil fuel combustion, about one quarter
13   comes from land-related activities like agriculture (mainly CH4 and N2O) and deforestation (mainly
14   CO2), with additional emissions from industrial processes (mainly CO2, N2O and F-gases), and
15   municipal waste and wastewater (mainly CH4) (2). In addition to these emissions, black carbon – an
16   aerosol that is, for example, emitted during incomplete combustion of fossil fuels – contributes to
17   warming of the Earth’s atmosphere, whilst some other short-lived pollutants temporarily cool the
18   surface (IPCC WG1 Chapter
19   FAQ 1.3 What is the difference between “net zero emissions” and “carbon neutrality”?
20   Annex I states that “carbon neutrality and net zero CO2 emissions are overlapping concepts” which
21   “can be applied at the global or sub-global scales (e.g., regional, national and sub-national)”. At the
22   global scale the terms are equivalent. At sub-global scales, net-zero CO2 typically applies to emissions
23   under direct control or territorial responsibility of the entity reporting them (e.g. a country, district or
24   sector); while carbon neutrality is also applied to firms, commodities and activities (e.g. a service or an
25   event) and generally includes emissions and removals beyond the entity’s direct control or territorial
26   responsibility, termed ‘Scope 3’ or ‘value chain emissions’ (Bhatia et al. 2011).
27   This means the emissions and removals that should be included are wider for ‘neutrality’ than for net-
28   zero goals, but also that offset mechanisms could be employed to help achieve neutrality through
29   abatement beyond what is possible under the direct control of the entity. Rules and environmental
30   integrity criteria are intended to ensure additionality and avoid double counting of offsets consistent
31   with “neutrality” claims (see Annex I definitions of “Carbon neutrality” and “Offset” for detail and a
32   list of criteria).
33   While the term ‘carbon’ neutrality in this report is defined as referring specifically to CO2 neutrality,
34   use of this term in practice can be ambiguous, as some users apply it to neutrality of all GHG emissions.
35   GHG neutrality means an entity’s gross emissions of all GHG must be balanced by the removal of an
36   equivalent amount of CO2 from the atmosphere. This requires the selection of a suitable metric that
37   aggregates emissions from non-CO2 gases, such as the commonly used GWP100 metric (for a
38   discussion of GHG metrics, see AR6 WG1 Box 1.3 and Cross-Chapter Box 2 in Chapter 2 of this
39   report).

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