Final Government Distribution Chapter 4 IPCC WGIII AR6
1
2 Table of Contents
3 Chapter 4: Mitigation and development pathways in the near- to mid-term ................................. 4-1
4 Executive summary.......................................................................................................................... 4-3
5 4.1 Introduction ............................................................................................................................... 4-7
6 4.2 Accelerating mitigation actions across scales ............................................................................ 4-9
7 4.2.1 Mitigation targets and measures in nationally determined contributions..................... 4-9
8 4.2.2 Aggregate effects of NDCs and other mitigation efforts relative to long-term mitigation
9 pathways 4-11
10 Cross-Chapter Box 4 Comparison of NDCs and current policies with the 2030 GHG emissions
11 from long-term temperature pathways ....................................................................................... 4-22
12 4.2.3 Mitigation efforts in subnational and non-state action plans and policies ................. 4-25
13 4.2.4 Mid-century low-emission strategies at the national level ......................................... 4-32
14 4.2.5 What is to be done to accelerate mitigation? ............................................................. 4-39
15 4.2.6 Implications of accelerated mitigation for national development objectives ............. 4-51
16 4.2.7 Obstacles to accelerated mitigation and how overcoming them amounts to shifts in
17 development pathways ............................................................................................................... 4-58
18 4.3 Shifting Development pathways .............................................................................................. 4-61
19 4.3.1 Framing of development pathways ............................................................................ 4-61
20 4.3.2 Implications of development pathways for mitigation and mitigative capacity ........ 4-65
21 4.3.3 Examples of shifts in development pathways and of supporting policies.................. 4-72
22 Cross-Chapter Box 5 Shifting development paths to increase sustainability and broaden mitigation
23 options 4-74
24 4.4 How to shift development pathways and accelerate the pace and scale of mitigation ............ 4-79
25 4.4.1 Approaches, enabling conditions and examples ........................................................ 4-79
26 4.4.2 Adaptation, development pathways and mitigation ................................................... 4-92
27 4.4.3 Risks and uncertainties............................................................................................... 4-97
28 4.5 Equity, including just transitions ............................................................................................. 4-99
29 4.6 Knowledge gaps .................................................................................................................... 4-104
30 Frequently asked questions .......................................................................................................... 4-105
31 References .................................................................................................................................... 4-107
32
33
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1 Executive summary
2 This chapter focuses on accelerating mitigation and on shifting development pathways to increased
3 sustainability, based on literature particularly at national scale. While previous WGIII assessments have
4 discussed mitigation pathways, focus on development pathways is more recent. The timeframe is the
5 near-term (now up to 2030) to mid-term (2030 to 2050), complementing Chapter 3 on the long-term
6 (from 2050 onward).
7 An emissions gap persists, exacerbated by an implementation gap, despite mitigation efforts
8 including those in near-universal nationally determined contributions (NDCs). The “emissions
9 gap” is understood as the difference between the emissions with NDCs in 2030, and mitigation
10 pathways consistent with the temperature goals. In general, the term “implementation gap” refers to the
11 difference between goals on paper and how they are achieved in practice. In this report, the term refers
12 to the gap between mitigation pledges contained in national determined contributions, and the expected
13 outcome of existing policies. There is considerable literature on country-level mitigation pathways,
14 including but not limited to NDCs. Country distribution of this literature is very unequal (robust
15 evidence, high agreement). Current policies lead to median global GHG emissions of 57 GtCO2-eq with
16 a full range of 52-60 by 2030. NDCs with unconditional and conditional elements1 lead to 53 (50-57)
17 and 50 (47-55) GtCO2-eq, respectively (medium evidence, medium agreement) (Table 4.3). This leaves
18 estimated emissions gaps in 2030 between projected outcomes of unconditional elements of NDCs and
19 emissions in scenarios that limit warming to 1.5°C with no or limited overshoot of 20-26 GtCO2-eq,
20 and 10-17 GtCO2-eq for scenarios that likely limit warming to 2°C with immediate action. When
21 conditional elements of NDCs are included, these gaps narrow to 16-24 GtCO2-eq and 7-14 GtCO2-eq,
22 respectively. {Cross-Chapter Box 4, Figure 1}
23 Studies evaluating up to 105 updated NDCs submitted by October 2021 indicate that emissions in
24 conditional NDCs have been reduced by 4.5 (2.7-6.3) GtCO2-eq, but only closes the emission gaps
25 by about one-third to 2°C and about 20% to 1.5°C compared to the original NDCs submitted in
26 2015/16 (medium evidence, medium agreement). The magnitude of these emission gaps calls into
27 question whether current development pathways and efforts to accelerate mitigation are adequate to
28 achieve the Paris mitigation objectives. In addition, an implementation gap exists between the projected
29 emissions of ‘current policies’ and the projected emissions resulting from the implementation of the
30 unconditional and conditional elements of NDCs, and is estimated to be around 4 and 7 GtCO2-eq in
31 2030, respectively (medium evidence, medium agreement), with many countries requiring additional
32 policies and associated climate action to meet their autonomously determined mitigation targets as
33 specified under the first NDCs (limited evidence). There is, furthermore, a potential difference between
34 mitigation targets set in NDCs ex ante and what is achieved ex post. A limited number of studies assess
35 the implementation gaps of conditional NDCs in terms of finance, technology and capacity building
36 support. The disruptions triggered by the COVID-19 epidemic increase uncertainty over range of
37 projections relative to pre-COVID-19 literature. As indicated by a growing number of studies at the
38 national and global level, how large near- to mid-term emissions implications of the COVID-19
39 pandemic are, to a large degree depends on how stimulus or recovery packages are designed. {4.2,
40 4.2.2.5, Cross-Chapter Box 4}
41 Given the gaps, there is a need to explore accelerated mitigation (relative to NDCs and current
42 policies). There is increasing understanding of the technical content of accelerated mitigation pathways,
43 differentiated by national circumstances, with considerable though uneven literature at country-level
44 (medium evidence, high agreement). Transformative technological and institutional changes for the
FOOTNOTE1 See section 4.2.1 for description of ‘unconditional’ and ‘conditional’ elements of NDCs.
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1 near-term include demand reductions through efficiency and reduced activity, rapid decarbonisation of
2 the electricity sector and low-carbon electrification of buildings, industry and transport (robust
3 evidence, medium agreement). A focus on energy use and supply is essential, but not sufficient on its
4 own – the land sector and food systems deserve attention. The literature does not adequately include
5 demand-side options and systems analysis, and captures the impact from non-CO2 GHGs with medium
6 confidence . Countries and regions will have different starting points for transition pathways. Some
7 factors include climate conditions resulting in different heating and cooling needs, endowments with
8 different energy resources, patterns of spatial development, and political and economic conditions.
9 {4.2.5}
10 Accelerated mitigation alone may run into obstacles. If such obstacles are rooted in underlying
11 structural features of society, then transforming such structures helps remove obstacles, which amounts
12 to shifting development pathways. Various actors have developed an increasing number of mitigation
13 strategies up to 2050 (mid-term). A growing number of such strategies aim at net zero GHG or CO2
14 emissions, but it is not yet possible to draw global implications due to the limited size of sample
15 (medium evidence; low agreement). Non-state actors are also engaging in a wide range of mitigation
16 initiatives. When adding up emission reduction potentials, sub-national and non-state international
17 cooperative initiatives could reduce up to about 20 GtCO2-eq in 2030 (limited evidence, medium
18 agreement). Yet perceived or real conflicts between mitigation and other Sustainable Development
19 Goals (SDGs) can impede such action. If undertaken without precaution, accelerated mitigation is found
20 to have significant implications for development objectives and macroeconomic costs at country level.
21 For example, most country-level mitigation modelling studies in which GDP is an endogenous variable
22 report negative impacts of mitigation on GDP in 2030 and 2050, relative to the reference. In all reviewed
23 studies, however, GDP continues to grow even with mitigation (robust evidence, high agreement). The
24 literature finds that employment effect of mitigation policies tends to be limited on aggregate, but can
25 be significant at sectoral level (limited evidence, medium agreement). Detailed design of mitigation
26 policies is critical for distributional impacts and avoiding lock-in (robust evidence, high agreement),
27 though further research is needed in that direction. {4.2.3, 4.2.4, 4.2.6}
28 Shifting development pathways towards sustainability offers ways to (i) broaden the range of
29 levers and enablers that a society can use to provide enabling conditions and accelerate
30 mitigation; and (ii) increase the chances of advancing at the same time towards mitigation and
31 towards other development goals. The way countries develop determines their capacity to accelerate
32 mitigation and achieve other sustainable development objectives simultaneously (medium-robust
33 evidence, medium agreement). Yet meeting ambitious mitigation and development goals cannot be
34 achieved through incremental change, hence the focus on shifting development pathways (robust
35 evidence, medium agreement). Though development pathways result from the actions of a wide range
36 of actors, it is possible to shift development pathways through policies and enhancing enabling
37 conditions (limited evidence, medium agreement). For example, policies such as those listed in Table
38 4.12 are typically associated with broader objectives than greenhouse gas mitigation. They are generally
39 conceived and implemented in the pursuit of overall societal development objectives, such as job
40 creation, macro-economic stability, economic growth, and public health and welfare. In some countries,
41 such policies are framed as part of a just transition. However, they can have major influence on
42 mitigative capacity, and hence can be seen as tools to broaden mitigation options, as illustrated by the
43 Illustrative Mitigation Pathway “Shifting Pathways” (medium evidence, medium agreement). There are
44 practical options to shift development pathways in ways that advance mitigation and other sustainable
45 development objectives, supporting political feasibility, increase resources to meet multiple goals, and
46 reduce emissions (limited evidence, high agreement). Concrete examples assessed in this chapter
47 include high employment and low emissions structural change, fiscal reforms for mitigation and social
48 contract, combining housing policies to deliver both housing and transport mitigation, and change
49 economic, social and spatial patterns of development of the agriculture sector provide the basis for
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1 sustained reductions in emissions from deforestation. These examples differ by context. Examples in
2 other chapters include transformations in energy, urban, building, industrial, transport, and land-based
3 systems, changes in behaviour and social practices, as well as transformational changes across whole
4 economies and societies. Coordinated policy mixes would need to coordinate multiple actors—
5 individuals, groups and collectives, corporate actors, institutions and infrastructure actors—to deepen
6 decarbonisation and shift pathways towards sustainability. Shifts in one country may spill over to other
7 countries. Shifting development pathways can jointly support mitigation and adaptation. Some studies
8 explore the risks of high complexity and potential delay attached to shifting development pathways.
9 {4.3, 4.3.1, 4.3.2, 4.4.2, 4.4.3, 4.4.1.7-4.4.1.10, Figure 4.7, Cross-Chapter Box 5, 5.8, Box 6.2, 8.2,
10 8.3.1, 8.4, 9.8.1, 9.8.2, 10.4.1, Cross-Chapter Box 5, Cross-Chapter Box 7, Cross-Chapter Box 12}
11 The literature identifies a broad set of enabling conditions that can both foster shifting
12 development pathways and accelerated mitigation, along five categories. (medium evidence, high
13 agreement). Policy integration is a necessary component of shifting development pathways, addressing
14 multiple objectives. To this aim, mobilising a range of policies is preferable to single policy instruments
15 (robust evidence, high agreement). Governance for climate mitigation and shifting development
16 pathways is enhanced when tailored to national and local contexts. Improved institutions and
17 governance enable ambitious climate action and help bridge implementation gaps (medium evidence,
18 high agreement). Given that strengthening institutions may be a long term endeavour, it needs attention
19 in the near-term. Accelerated mitigation and shifting development pathways necessitates both re-
20 directing existing financial flows from high- to low-emissions technologies and systems and to provide
21 additional resources to overcome current financial barriers. (robust evidence, high agreement).
22 Opportunities exist in the near-term to close the finance gap. At the national level, public finance for
23 actions promoting the SDG agenda helps broaden the scope of mitigation (medium evidence, medium
24 agreement). Changes in behaviour and lifestyles are important to move beyond mitigation as
25 incremental change, and when supporting shifts to more sustainable development pathways will
26 broadening the scope of mitigation (medium evidence, medium agreement). The direction of innovation
27 matters (robust evidence, high agreement) . The necessary transformational changes are likely to be
28 more acceptable if rooted in the development aspirations of the economy and society within which they
29 take place. {4.4.1, 4.4.1.2, 4.4.1.3, 4.4.1.4, 4.4.1.5, 4.4.1.6, Figure 4.8, 15.2.2}
30 Equity can be an important enabler of deeper ambition for accelerated mitigation, dealing with
31 the distribution of costs and benefits and how these are shared as per social contracts, national policy
32 and international agreements. Transition pathways have distributional consequences such as large
33 changes in employment and economic structure (robust evidence, high agreement). In that regard, the
34 just transition concept has become an international focal point tying together social movements, trade
35 unions, and other key stakeholders to ensure equity is better accounted for in low-carbon transitions .
36 Effectiveness of cooperative action and the perception of fairness of such arrangements are closely
37 related, in that pathways that prioritise equity and allow broad stakeholders participation can enable
38 broader consensus for the transformational change implied by deeper mitigation efforts (robust
39 evidence, medium agreement). Hence, equity is a concept that is instrumentally important. {4.5, Figure
40 4.9}
41 In sum, this Chapter suggests that the immediate tasks are to broaden and deepen mitigation in
42 the near-term if the global community is to deliver emission reductions at the scale required to keep
43 temperature well below 2°C and pursue efforts at 1.5°C. Deepening mitigation means more rapid
44 decarbonisation. Shifting development pathways to increased sustainability (SDPS) broadens the scope
45 of mitigation. Putting the enabling conditions above in place supports both. Depending on context, some
46 enabling conditions such as shifting behaviour may take time to establish, underscoring the importance
47 of early action. Other enabling conditions, such as improved access to financing, can be put in place in
48 a relatively short time frame, and can yield results rapidly.
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1 Accelerating mitigation: The literature points to well-understood policy measures and technologies
2 for accelerating mitigation, though the balance depends on country specificities: 1) decarbonising
3 electricity supply to produce net zero CO2, including renewable energy, 2) radically more efficient use
4 of energy than today; 3) electrification of end-uses including transport; 4) dramatically lower use of
5 fossil fuels than today; 5) converting other uses to low- or zero-carbon fuels (e.g., hydrogen, bioenergy,
6 ammonia) in hard-to-decarbonise sectors; 6) promote bioenergy, demand reduction, dietary changes,
7 and policies, incentives, and rules for mitigation in the land sector; 7) setting and meeting ambitious
8 targets to reduce methane and other short-lived climate forcers. Charting just transitions to net zero may
9 provide a vision, which policy measures can help achieve. Though there is increasing experience with
10 pricing carbon directly or indirectly, decision-makers might consider a broader toolbox of enablers and
11 levers that is available in domains that have not traditionally been climate policy. {4.5, Annex II Part
12 IV Section 11}
13 Broadening opportunities by focusing on development pathways and considering how to shift them:
14 Some of the policy measures may yield rapid results, whereas other, larger transformations may take
15 longer. If we are to overcome obstacles, a near-term priority is to put in place the enabling conditions
16 to shifting development pathways to increased sustainability. Learning from the examples above,
17 focusing on SDPS also provides a broader set of tools to accelerating mitigation and achieve other
18 sustainable development goals. Consider climate whenever you make choices about development, and
19 vice versa. {4.4.1}
20
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1 4.1 Introduction
2 The recent IPCC Report on Global Warming of 1.5C (SR15) made clear that the next three decades
3 are critical if we are to achieve the long-term mitigation goal of the Paris Agreement (IPCC 2018a).
4 The present Chapter assesses the literature on mitigation and development pathways over that
5 timeframe, in the near- (up to 2030) and mid-term (up to 2050).
6 It considers three questions: (1) Where are we heading now? That is, what is the current state of affairs
7 with respect to climate mitigation and how did we get here? (2) Where do we want to go? I.e., what
8 state of affairs would meet the objectives of the Paris Agreement and achieving the Sustainable
9 Development Goals (SDGs)? and (3) How do we bring about this shift? I.e., what interventions are at
10 societies’ disposal to bring about the necessary change in an equitable manner?
11 Where are we heading now? Despite the drop in emissions due to the COVID-19 crisis, the gap
12 between projected emissions based on Nationally Determined Contributions (NDCs) in 2030 and
13 emissions pathways compatible with the long term temperature goal set in the Paris Agreement remains
14 large (4.2.2). In addition to this persistent emissions gap, we face an implementation gap, as current
15 policies are insufficient to achieve mitigation targets in NDCs, and sufficient international support is
16 not yet available to developing countries who have requested and quantified support needs. Continuing
17 along a development pathway characterized by the same underlying drivers, structural obstacles and
18 insufficient enabling conditions that led to high emissions will not address the problem (robust
19 evidence, high agreement).
20 The analysis of the gap is conducted together with Chapter 3 (see Cross-Chapter Box 4). Chapter 3 is
21 working backward, assessing mitigation in the long-term (beyond 2050 up to 2100) to draw the near-
22 and mid-term implications of long-term temperature and mitigations goals. Chapter 4, on the other hand,
23 works forward from current and planned mitigation (including NDCs) (4.2.1, 4.2.2) and from current
24 development paths to assess the implications for near- and mid-term Greenhouse Gases (GHG)
25 emissions and development goals. Some countries, regions, cities, communities and non-state actors are
26 taking leadership in implementing more ambitious action (4.2.3). This chapter also assesses national
27 low emission development strategies (4.2.4).
28 Where do we want to go? Technical alternatives and policy options exist to bridge the emissions and
29 implementation gaps, and the literature illustrates these with a wide range of accelerated techno-
30 economic pathways that deepen decarbonisation closer to the pace and scale required (4.2.5), and
31 examines their impacts on other development objectives (4.2.6). In practice, however, scaling up at the
32 broader, deeper, and faster level required to meet climate goals while advancing other development
33 objectives regularly faces prohibitive obstacles (4.2.7). Mitigation policies grafted on to existing
34 development pathways are unlikely to achieve rapid and deep emission reductions.
35 Secondly, even if carefully designed, climate policies to accelerate mitigation may have adverse
36 consequences for other development objectives. As a complement to mitigation action, taking action to
37 shift development pathways towards sustainability broadens the range of mitigation options, while
38 increasing the possibility to meet other development priorities at the same time (medium evidence, high
39 agreement).
40 Development pathways and shifting them to increased sustainability are introduced in Chapter 1, and
41 constitute a thread throughout the report (see glossary entry on development pathways). The WGII
42 Report highlights the related concept of climate resilient development pathways (Chapter 18). Cross-
43 Chapter Box 5 on shifting sustainable pathway towards sustainability elaborates on the concept. The
44 influence of development pathways on emissions and mitigative capacity is discussed in Chapter 2.
45 Chapter 3 assesses modelling of shifts in development pathways, illustrated by the illustrative mitigation
46 pathway called “shifting pathways”. The importance of behavioural change as societies make decisions
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1 that intentionally shift their future development pathway is emphasized in Chapter 5. The systems
2 Chapters (6-12) take sectoral perspectives, while pathways that are sustainable are the specific focus of
3 Chapter 17.
4 How can one shift development pathway and accelerate mitigation? The literature does not provide
5 a complete handbook for shifting development pathways and accelerating mitigation. The literature
6 does, however, shed light on some of the underlying dynamics. Shifting development pathways can be
7 necessitated by the existence of pervasive obstacles that prove prohibitive to reaching mitigation and
8 other development objectives (4.2.7). Deliberate measures taken to facilitate the shifting of
9 development pathways and accelerated mitigation involve putting in place key enabling conditions that
10 help overcome those obstacles (see Figure 4.6)—improving governance and institutional capacity,
11 fostering behavioural change and technological innovation, designing and implementing adequate
12 policy, and finance. Just transitions, while they will differ by context, are critical to identifying and
13 avoiding or addressing inequitable distributive consequences (robust evidence, high agreement).
14 Enabling conditions necessary to accelerate mitigation and shift development pathways are discussed
15 in depth in Chapters 5, 13, 14, 15 and 16. In addition, Chapters 13 and 14 detail the policy instruments
16 that could help shift development pathways and accelerate the scale and pace of mitigation, while
17 Chapter 4 describes those in broad strategies terms. Chapter 13 adds more texture on institutional and
18 governance machinery; policy choice, design and implementation; as well as policy formulation
19 processes, actors and structure across scales.
20 Since development pathways and mitigation options depend to large extent on national objectives and
21 circumstances, this chapter is primarily concerned with literature at national level (or in the case of the
22 European Union, at regional level), while Chapter 3 is primarily concerned with literature at global
23 scale. The national scale selected in this Chapter requires attention as national mitigation pathways
24 cannot be linked directly to global mitigation goals (see Box 4.2). This chapter is also concerned mostly
25 with economy-wide development and mitigation pathways, as distinct from detailed sectoral work that
26 is assessed in the systems chapters 6 to 12. The present chapter also assesses literature on non-state
27 action.
28 Chapter 4 draws on five major strands of literature: (1) an emerging literature on development
29 pathways—conceptual, empirical, and model-based, including at the national and sub-national scales;
30 (2) a rapidly expanding, model-based, literature on mitigation pathways in the near- and mid-term
31 (Lepault and Lecocq 2021); (3) studies of NDCs and mid-century strategies; (4) a broader literature on
32 transformation and shifts in development pathways, including from non-climate literatures; and (5) a
33 significant literature on equity, including just transitions. This is supported by a database of country-
34 level mitigation scenarios at country level assembled for the preparation of this Chapter (Annex III,
35 Table I.10 and I.11).
36 The Chapter builds on past IPCC reports. In AR5, all mitigation pathways were assessed in a single
37 chapter (Clarke et al. 2014), which focused mostly on the long-term. SR1.5 included a chapter on
38 mitigation pathways compatible with the temperature goal in the Paris Agreement (Rogelj et al. 2018a),
39 mostly at the global level. It also considered strengthening mitigation (de Coninck et al. 2018) in the
40 context of poverty, inequality and sustainable development (Roy et al. 2018). Development pathways
41 have also been explored, albeit less frequently, in past IPCC reports starting with the Special Report on
42 Emissions Scenarios (Nakicenovic et al. 2000). Some early framing of development pathways was
43 included in the Third Assessment Report (William R. Moomaw et al. 2001), further developed in the
44 Fourth Assessment Report (Sathaye et al. 2007). An extended discussion of climate change and equity
45 was conducted in AR5 (Fleurbaey et al. 2014).
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1 Chapter 4 examines mitigation within the broader context of development pathways, and examines how
2 shifting development pathways can have a major impact on mitigative capacity and broadening
3 mitigation options. It is organized as follows.
4 Section 4.2 demonstrates that collective mitigation actions fall short of pathways that keep in reach the
5 Paris temperature goals in the long-term. Section 4.3 introduces development pathways (given its
6 relative novelty in IPCC assessments), considers the implications of mitigation for development and
7 vice versa, and articulates an approach on both accelerating mitigation and shifting development
8 pathways.
9 Section 4.4 discusses how to shift development pathway and accelerate the scale and pace of mitigation,
10 what levers are available to policy makers, and how policies may intersect with adaptation goals. It
11 points out that development pathways also drive adaptation and adaptative capacity, and discusses
12 various risks associated with shifting development pathways and accelerated mitigation strategies.
13 Finally, equity and just transitions are recurring themes in the Chapter, specifically in relation to
14 accelerating mitigation and shifting development pathways toward sustainability. In section 4.2.2.7,
15 equity is discussed in the context of Parties’ assertions regarding the fairness of their NDCs, alongside
16 reflections from academic scholarship on the ethical underpinnings of these assertions and of various
17 quantitative analyses of equitable effort-sharing. Section 4.2.6 discusses certain distributional
18 implications of domestic mitigation efforts, such as shifts in employment. Sections 4.2.7 and 4.3 note
19 the relevance of potential distributional impacts as an obstacle to climate action, as well as the
20 inequitable distribution of decision-making authority. Finally, section 4.5 recognizes the structural
21 relationship between equity and climate, explores just transitions as an international focal point tying
22 together social movements, trade unions, and other stakeholders, and thus an instrumental role in
23 establishing consensus.
24
25 4.2 Accelerating mitigation actions across scales
26 4.2.1 Mitigation targets and measures in nationally determined contributions
27 A central instrument of the Paris Agreement is the NDCs, submitted by each country, and reflecting
28 national efforts to reduce GHG emissions and build resilience to the impacts of climate change. Every
29 five years, collective progress will be compared against long-term goals of the Paris Agreement.
30 Considering the outcome of a global stocktake, countries will prepare subsequent NDCs, showing
31 progression in their ambition and enhancing international cooperation (UNFCCC 2015a).
32 Prior to COP21, in 2015, most countries submitted their INDCs (Intended Nationally Determined
33 Contributions), which included mitigation targets for 2025 or 2030. INDCs become first NDCs on
34 ratification and/or after national governments’ revision, and by 11 October 2021, the official NDC
35 registry contained 194 first NDCs with 105 new and updated NDCs from 132 Parties to the Paris
36 Agreement, covering 53% of the total global emissions in 2019 of 52.4 GtCO2-eq without LULUCF,
37 and 13 second NDCs. Most of the Parties that submitted new or updated NDCs have demonstrated
38 increased ambition in addressing climate change. Moreover, though some countries like China have not
39 submitted their updated NDCs yet, they have already announced their updated NDC goals somewhere.
40 Countries will take the first stock in 2023 based on their progression towards achieving the objectives
41 of Paris Agreement (UNFCCC 2015a, 2018a; SB Chairs 2021) (14.3.2.5).
42 Submitted NDCs vary in content, scope and background assumptions. First NDCs contain mitigation
43 targets, and in many cases also provisions about adaptation. The mitigation targets range from economy-
44 wide absolute emission reduction targets to strategies, plans and actions for low-emission development.
45 Baseline years vary from 1990 to 2015 and in almost all NDCs the targeted time frame is 2030, with a
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1 few specified periods of until 2025, 2035, 2040 or 2050. Around 43% of the mitigation targets in first
2 NDCs are expressed in terms of deviation below business-as-usual by a specified target year, either for
3 the whole economy or for specific sectors, while around 35% include fixed-level targets (either
4 reductions or limitations compared to base years), and another 22% refer to intensity targets (in terms
5 of GHG, CO2 or energy) or policies and measures, with an increasing number of Parties moving to
6 absolute emission reduction targets in their new or updated NDCs (UNFCCC 2016a, 2021). Some
7 developing countries’ NDCs include unconditional elements, while others include conditional ones, the
8 latter with higher ambition if finance, technology and capacity building support from developed
9 countries is provided (UNFCCC 2016a).2 In some NDCs, the additional mitigation is quantified, in
10 others not (Figure 14.2).
11 Most first NDCs cover all specific sectors, including LULUCF, and communicate specific targets for
12 individual sub-sectors to support their overall mitigation targets. Concrete actions and priority areas are
13 more detailed in the energy sector, with increased share of renewable energies and energy efficiency
14 being highlighted in the majority of NDCs. Given the uncertainty behind LULUCF emission and
15 removal accounting (Grassi et al. 2017; Jian et al. 2019), several countries state that their accounting
16 framework will only be defined in later NDCs. The GHG included and the global warming potentials
17 (GWPs) used to aggregate emissions also vary across NDCs. Most countries only refer to carbon
18 dioxide, methane and nitrous oxide emissions aggregated based on IPCC AR2 or AR4 metrics, while
19 few NDCs also include fluorinated gases and use IPCC AR5 GWPs. The shares of Parties that indicate
20 possible use of at least one type of voluntary cooperation and set qualitative limits on their use have
21 both nearly doubled in new or updated NDCs.
22 There is considerable literature on country-level mitigation pathways, including but not limited to
23 NDCs. Country distribution of this literature is very unequal (robust evidence, high agreement). In
24 particular, there is a growing literature on (I)NDCs, with a wide scope which includes estimate of
25 emissions levels of NDCs (see section 4.2.2.2); alignment with sustainable development goals (Caetano
26 et al. 2020; Campagnolo and Davide 2019; Fuso Nerini et al. 2019; Antwi-Agyei et al. 2018); ambition
27 (Höhne et al. 2018; Vogt-Schilb and Hallegatte 2017; Hermwille et al. 2019); energy development
28 (Scott et al. 2018); and the legality of downgrading NDCs (Rajamani and Brunnée 2017). Other studies
29 note that many NDCs contain single-year mitigation targets, and suggest that a multi-year trajectory is
30 important for more rigorous monitoring (Elliott et al. 2017; Dagnet et al. 2017).
31 The literature also points out that beyond the ‘headline numbers’, information in (I)NDCs is difficult to
32 analyse (Pauw et al. 2018). Information for ‘clarity, transparency and understanding’ is to be
33 communicated with NDCs, although initial guidance was not specific (UNFCCC 2014). While the
34 adoption of the Paris rule-book provided some greater specificity (UNFCCC 2018b,c), the information
35 included in the NDCs remains uneven. Many NDCs omit important mitigation sectors and do not
36 adequately provide details on costs and financing of implementation (Pauw et al. 2018). Countries are
37 also invited to explain how their NDCs are fair and ambitious, though the way this has been done so far
38 has been criticised as insufficiently rigorous (Winkler et al. 2018).
FOOTNOTE2 “Unconditional” NDCs refer to abatement efforts pledged without any conditions (this terminology is used by
the literature, not by the Paris Agreement). They are based mainly on domestic abatement actions, although countries can use
international cooperation to meet their targets. (2) “Conditional” NDCs require international cooperation, for example bilateral
agreements under article 6, financing or monetary and/or technological transfers (14.3.2).
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1 4.2.2 Aggregate effects of NDCs and other mitigation efforts relative to long-term
2 mitigation pathways
3 4.2.2.1 Introduction
4 Near-term mitigation targets submitted as part of NDCs to the UNFCCC, as well as currently
5 implemented policies, provide a basis for assessing potential emissions levels up to 2030 at the national,
6 regional and global level. The following sections present an evaluation of the methods used for
7 assessing projected emissions under NDCs and current policies (4.2.2.2), and the results of these
8 assessments at global, regional and national level assessing a broad available literature based on first
9 NDC submissions from 2015/16 and pre-COVID economic projections (4.2.2.3). The impacts of the
10 COVID-19 pandemic and related government responses on emissions projections are then discussed in
11 4.2.2.4 and the implications of updated NDCs submitted in 2020/21 on emissions follow in 4.2.2.5.
12 Section 0 presents an assessment of the so-called “implementation gap” between what currently
13 implemented policies are expected to deliver and what the ambitions laid out under the full
14 implementation of the NDCs are projected to achieve. Finally, a comparison of ambitions across
15 different countries or regions (4.2.2.7) is presented and the uncertainties of projected emissions
16 associated with NDCs and current policies are estimated, including a discussion of measures to reduce
17 uncertainties in the specification of NDCs (4.2.2.8).
18 The literature reviewed in this section includes globally comprehensive assessments of NDCs and
19 current policies, both peer-reviewed and non-peer-reviewed (but not unpublished model results) as well
20 as synthesis reports by the UNFCCC Secretariat, government reports and national studies.
21 The aggregate effects of NDCs provide information on where emissions might be in 2025/2030,
22 working forward from their recent levels. Chapter 3 of this report works backwards from temperature
23 goals, defining a range of long-term global pathways consistent with 1.5°C, 2°C and higher temperature
24 levels. By considering the two together, it is possible to assess whether NDCs are collectively consistent
25 with 1.5°C, 2°C and other temperature pathways (Cross-Chapter Box 4, p.4-22).
26 4.2.2.2 Methods to project emissions under NDCs and current policies
27 A variety of different methods are used to assess emissions implications of NDCs and current policies
28 over the time horizon to 2025 or 2030. Some of these projections were explicitly submitted as part of
29 an official communication to UNFCCC (e.g., Biennial Report, Biennial Update Reports or National
30 Communications) while the majority is from independent studies.
31 Methods that are used in independent studies (but that can also underlie the official communications)
32 can broadly be separated into two groups,
33 (i) system modelling studies which analyse policies and targets in a comprehensive modelling
34 framework such an integrated assessment, energy systems or integrated land-use model to
35 project emissions (or other indicators) of mitigation targets in NDCs and current policies,
36 either at the national or global scale (noting some differences in the systems), and
37 (ii) hybrid approaches that typically start out with emissions pathways as assessed by other
38 published studies (e.g., the IEA World Energy Outlook, national emissions pathways such
39 as those specified in some NDCs) and use these directly or apply additional modifications
40 to them.
41 System modelling studies are conducted at global, regional and national scales. Global models provide
42 an overview, are necessary for assessment of global phenomena (e.g., temperature change), can
43 integrate climate models and trade effects. National models typically include more details on sectors,
44 technology, behaviour and intersectoral linkages, but often use simplifying assumptions for
45 international trade (e.g., the Armington elasticity approach). Critically, they can also better reflect local
46 socio-economic and political conditions and their evolution (i.e., national development pathways). A
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1 variety of modelling paradigms are found, including optimisation and simulation models, myopic and
2 with foresight, monolithic and modular (see Annex III: Scenarios and modelling methods).
3 Among the hybrid approaches, three broader categories can be distinguished, (i) direct use of official
4 emission projection as part of submitted NDC or other communication to UNFCCC, (ii) historical trend
5 extrapolation of emissions based on inventory data, possibly disaggregated by sector and emission
6 species, and (iii) use of Reference/Business-As-Usual pathways from an independent published study
7 (e.g., IEA WEO). In all cases, the reductions are then estimated on top of the resulting emission
8 trajectory. Note that globally comprehensive studies may vary the approach used depending on the
9 country.
10 Beyond the method applied, studies also differ in a number of dimensions, including (i) their spatial
11 resolution and coverage, (ii) their sectoral resolution and coverage, (iii) the GHGs that are included in
12 the assessment, the GWPs (or other metrics) to aggregate them, the emissions inventory (official vs.
13 independent inventory data) and related accounting approaches used as a starting point for the
14 projections, (iv) the set of scenarios analysed (Reference/Business-As-Usual, Current Policies, NDCs,
15 etc.), and (v) the degree to which individual policies and their impact on emissions are explicitly
16 represented (Table 4.1).
17 First, the studies are relevant to different spatial levels, ranging from macro-scale regions with globally
18 comprehensive coverage to national level (4.2.2.3) and subnational and company level in a few cases
19 (4.2.3). It is important to recognise that globally comprehensive studies typically resolve a limited
20 number of countries individually, in particular those that contribute a high share to global emissions,
21 but have poor resolution of remaining countries or regions, which are assessed in aggregate terms.
22 Conversely, studies with high resolution of a particular country tend to treat interactions with the global
23 scale in a limited way. The recent literature includes attempts to provide a composite global picture
24 from detailed national studies (Bataille et al. 2016a; Deep Decarbonization Pathways Project 2015;
25 Roelfsema et al. 2020).
26 A second dimension in which the studies are different is their comprehensiveness of covering different
27 emitting sectors. Some studies focus on the contribution of a single sector, for example the Agriculture,
28 Forestry and Other Land Use (AFOLU) sector (Fyson and Jeffery 2019; Grassi et al. 2017) or the energy
29 system (including both energy supply and demand sectors), to emission reductions as specified in the
30 NDC. Such studies give an indication of the importance of a given sector to achieving the NDC target
31 of a country and can be used as a benchmark to compare to comprehensive studies, but adding sectoral
32 contributions up represents a methodological challenge.
33 Third, GHG coverage is different across studies. Some focus on CO2 only, while others take into
34 account the full suite of Kyoto gases (CO2, CH4, N2O, HFCs, PFCs and SF6, see glossary). For the latter,
35 different metrics for aggregating GHGs to a CO2-equivalent metric are being used, typically GWP 100
36 from different IPCC assessments (Table 4.1)
37 Fourth, studies typically cover a set of scenarios, though how these scenarios are defined varies widely.
38 The literature reporting IAM results often includes Nationally Determined Contribution (NDC), which
39 are officially communicated, and Current Policies (CP) as interpreted by modellers. Studies based on
40 national modelling, by contrast, tend to define scenarios reflecting very different national contexts. In
41 both cases, modellers typically include so-called No Policy Baseline scenarios (alternatively referred to
42 as Reference or Business-as-Usual scenarios) which do not necessarily reflect currently implemented
43 policies and thus are not assessed as reference pathways (see section 4.2.6.1). There are also various
44 approaches to considering more ambitious action compared to the CP or NDC projections that are
45 covered in addition.
46 Fifth, studies differ in the way they represent policies (current or envisioned in NDCs), depending on
47 their internal structure. For example, a subsidy to energy efficiency in buildings may be explicitly
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1 modelled (e.g., in a sectoral model that represents household decisions relative to building insulation),
2 represented by a proxy (e.g., by an exogenous decrease in the discount rate households use to make
3 choices), or captured by its estimated outcome (e.g., by an exogenous decrease in the household demand
4 for energy, say in an energy system model or in a compact CGE). Detailed representations (such as the
5 former example) do not necessarily yield more accurate results than compact ones (the latter example),
6 but the set of assumptions that are necessary to represent the same policy will be very different.
7 Finally, policy coverage strongly varies across studies with some just implementing high level targets
8 specified in policy documents and NDCs while others represent the policies with the largest impact on
9 emissions and some looking at very detailed measures and policies at subnational level. In addition, in
10 countries with rapidly evolving policy environments, slightly different cut-off dates for the policies
11 considered in an emission projection can make a significant difference for the results (Dubash et al.
12 2018).
13 The challenges described above are dealt with in the assessment of quantitative results in Section 4.2.2.3
14 by (i) comparing national studies with country-level results from global studies to understand systematic
15 biases, (ii) comparing economy-wide emissions (incl. AFOLU) as well as energy-related emissions,
16 (iii) using different emission metrics including CO2 and Kyoto GHG emissions where the latter have
17 been harmonized to using AR6 GWP100 metrics, and (iv) tracking cut-off dates of implemented
18 policies and NDCs used in different references (Table S4.1). The most notable differences in
19 quantitative emission estimates related to current policies and NDCs relate to the COVID-19 pandemic
20 and its implications and to the updated NDCs mostly submitted since early 2020 which are separately
21 dealt with in Sections 4.2.2.4 and 4.2.2.5, respectively.
22 In addition to assessing the emissions outcomes of NDCs, some studies report development indicators,
23 by which they mean a wide diversity of socio-economic indicators (Altieri et al. 2016; Jiang et al. 2013;
24 Benavides et al. 2015; Chai and Xu 2014; Delgado et al. 2014; La Rovere et al. 2014a; Paladugula et
25 al. 2018; Parikh et al. 2018; Zevallos et al. 2014; Zou et al. 2016; Yang et al. 2021; Bataille et al. 2016a),
26 share of low-carbon energy (Bertram et al. 2015; Riahi et al. 2015), renewable energy deployment
27 (Roelfsema et al. 2018), production of fossil fuels (SEI et al. 2020) or investments into low-carbon
28 mitigation measures (McCollum et al. 2018) to track progress towards long-term temperature goals.
29 4.2.2.3 Projected emissions under NDCs and current policies by 2025/2030
30 The emissions projections presented in this section relate to the first NDCs, as communicated in 2015
31 and 2016, and on which an extensive literature exists. New and updated NDCs, mostly submitted since
32 the beginning of 2020, are dealt with in Section 4.2.2.5. Similarly, the implications of COVID-19 and
33 the related government responses on emissions projections is specifically dealt with in Section 4.2.2.4.
34 Table 4.1 presents the evidence base for the assessment of projected emissions of original NDCs and
35 current policies until 2030. It covers 31 countries and regions responsible for about 82% of global GHG
36 emission (excluding FOLU CO2 emissions) and draws quantitative estimates from more than 40 studies
37 (see Table S4.1 in the Supplementary Material to Chapter 4). The table allows comparing emission
38 projections from national and globally comprehensive studies as well as official communications by
39 countries to the UNFCCC at the national/regional level. The global aggregates presented in Table 4.1
40 derive from globally comprehensive studies only and are not the result of aggregating country
41 projections up to the global level. As different studies report different emission indicators, the table
42 includes four different indicators: CO2 and GHG emissions, in- or excluding AFOLU emissions. Where
43 possible, multiple indicators are included per study.
44 Globally comprehensive studies.
45 The UNFCCC Secretariat has assessed the aggregate effect of NDCs multiple times. The first report
46 considered the intended NDCs in relation to 2°C (UNFCCC 2015b), whereas the second considered
47 NDCs also in relation to 1.5°C (UNFCCC 2016b). New submissions and updates of NDCs in 2020/21
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1 are assessed in Section 4.2.2.5. A number of globally comprehensive studies (den Elzen et al. 2016;
2 Luderer et al. 2016; Rogelj et al. 2016, 2017; Vandyck et al. 2016; Rose et al. 2017; Baumstark et al.
3 2021) which estimate aggregate emissions outcomes of NDCs and current policies have previously been
4 assessed in Cross-Chapter-Box 11 of IPCC SR1.5.
5 According to the assessment in this report, studies projecting emissions of current policies based on
6 pre-COVID assumptions lead to median global GHG emissions of 60 GtCO2-eq with a full range of 54-
7 68 by 2030 and original unconditional and conditional NDCs submitted in 2015/16 to 57 (49-63) and
8 54 (50-60) GtCO2-eq, respectively (robust evidence, medium agreement) (Table 4.1). Globally
9 comprehensive and national-level studies project emissions of current policies and NDCs to 2025 and
10 2030 and, in general, are in good agreement about projected emissions at the country level.
11 These estimates are close to the ones provided by the IPCC SR1.5, Cross-Chapter-Box 11, and the
12 UNEP emissions gap report (UNEP 2020a)3.
13 National studies
14 A large body of literature on national and regional emissions projections, including official
15 communications of as part of the NDC submissions and independent studies exist. A subset of this
16 literature provides quantitative estimates for the 2030 timeframe. As highlighted in Section 4.2.1, the
17 number of independent studies varies considerably across countries with an emphasis on the largest
18 emitting countries. This is reflected in Table 4.1 (see also Table S4.1). Despite smaller differences
19 between globally comprehensive and national studies for a few countries, there is generally good
20 agreement between the different types of studies, providing evidence that these quantitative estimates
21 are fairly robust.
22 Sectoral studies
23 Sectoral studies are essential to understand the contributions of concrete measures of NDCs and current
24 policies. For example, approximately 98% of NDCs include the energy sector in their mitigation
25 contributions, of which nearly 50% include a specific target for the share of renewables, and about 5%
26 aim at increasing nuclear energy production (Stephan et al. 2016). Transport is covered explicitly in
27 75% of NDCs, although specific targets for the sector exist in only 21% of NDCs (PPMC and SLoCaT
28 2016). Measures or targets for buildings are referred to explicitly in 27% of NDCs (GIZ 2017). 36% of
29 NDCs include targets or actions that are specific to the agriculture sector (FAO 2016). LULUCF
30 (mitigation) is included in 80 % of all submitted NDCs, while 59 % include adaptation and 29 % refer
31 to REDD+.
32 Greater sectoral expertise and involvement will be critical to accomplishing development and climate
33 goals due to enhanced availability of information and expertise on specific sectoral options, greater ease
34 of aligning the NDCs with sectoral strategies, and greater awareness among sector-level decision-
35 makers and stakeholders (NDC Partnership 2017; Fekete et al. 2015). Sector-specific studies are
36 assessed in the sectoral Chapters (6-11) of this report.
FOOTNOTE3 Note that the statistical metrics reported are slightly different across the reports. For example, IPCC
SR1.5 reported the 25th to 75th range while the UNEP emissions gap report uses median and 10th to 90th percentile
ranges. In addition, this report applies 100-year GWPs from AR6 to aggregate across different GHG emission
species, whereas 100-year GWPs from AR4 were applied in IPCC SR1.5 and UNEP 2020. The application of
AR6 GWPs on average leads to increase of estimates by about 1.3% and ranges are wider due to the difference in
statistical error metrics.
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37 Table 4.1 Assessment of projected 2030 emissions of current policies based on pre-COVID assumptions and original NDCs submitted in 2015/16 for 28 individual
38 countries/regions and the world. The table compares projected emissions from globally comprehensive studies, national studies and, when available, official
39 communications to UNFCCC using different emission sources (fossil fuels, AFOLU sector) and different emission metrics (CO 2, Kyoto GHGs). The comparison
40 allows identifying potential biases across the ranges and median estimates projected by the different sets of studies.
Current Policies 2030 emissions NDC 2030 emissions (conditional/unconditional)
Kyoto GHGse
[GtCO2-eq]
GHG # CO 2 only [GtCO 2 ] median (min - CO2 only [GtCO2] Kyoto GHGse [GtCO2-eq]
f f
share estimat median (min - max) max) median (min - max)f median (min - max)f
Regiona [%]b Typec esd incl. AFOLUg fossil fuels incl. AFOLUg incl. AFOLUg fossil fuels incl. AFOLUg
World 100 global 93 43 (38 - 51) 37 (33 - 45) 60 (54 - 68) 40 (35 - 45)/37 (35 - 39) 32 (26 - 39)/31 (27 - 37) 54 (50 - 60)/57 (49 - 63)
CHN 27 global 76 12 (9.7 - 15) 11 (8.4 - 14) 15 (12 - 18) - /11 (9.8 - 13) - /8.8 (6.9 - 13) - /14 (13 - 16)
national 13 12 (12 - 12) 11 (9.2 - 13) 15 (13 - 15) - /12 (11 - 12) - /11 (10 - 11) - /15 (13 - 16)
USAh 12 global 71 4.9 (4.4 - 6.6) 4.6 (3.5 - 6.5) 5.9 (4.9 - 6.6) - /3.8 (3.3 - 4.1) - /3.9 (3.1 - 5.3) - /4.6 (4 - 5.1)
national 5 4.1 4.5 (4.1 - 4.9) 5.9 (5.2 - 6.7) - /3.4 - /3.5 - /4.3
EUi 8.1 global 24 2.7 (2.1 - 3.5) 2.6 (2.1 - 3.3) 3.4 (2.6 - 4.7) - /2.6 (2.1 - 2.8) - /2.4 (2.1 - 2.7) - /3.2 (2.6 - 3.7)
national 3 3.1 2.6 - /2.5
official 3 3.2 (2.8 - 3.7)
IND 7.1 global 79 3.7 (3 - 4.5) 3.2 (2.5 - 4.5) 4.7 (4.1 - 6.4) 3.3 (3.1 - 4.4)/4 3.3 (2.4 - 5.6)/3.8 (2.9 - 5 (4.2 - 6.4)/5.8 (4.9 - 6.1)
5.6)
national 9 3.4 (3.3 - 4) 3.4 (2.9 - 3.9) 5.5 (5 - 5.7) 3.4 (3.2 - 3.6)/3.2 3.4 (3.2 - 3.5)/2.9 5.1/4.9
RUS 4.5 global 66 1.7 (0.84 - 2) 1.6 (1.5 - 2) 2.3 (1.6 - 3.3) - /1.7 (0.85 - 1.9) - /1.6 (1.2 - 1.9) - /2.6 (1.9 - 3.1)
national 6 1.5 (1.5 - 1.5) 2.6 - /1.5 (1.5 - 1.5) - /2.5
official 2 2.1 - /2.7
BRA 2.5 global 69 1.1 (0.79 - 1.7) 0.5 (0.28 - 1.1) 1.8 (1.4 - 2.7) - /0.94 (0.52 - 1.5) - /0.38 (0.097 - 0.86) - /1.3 (1.2 - 2.5)
national 4 0.59 0.47 1.8 - /0.51 - /0.47 - /1.2
official 1 - /1.2
JPN 2.4 global 66 1.2 (0.94 - 1.3) 1.1 (0.67 - 1.3) 1.2 (0.95 - 1.3) - /1 (0.9 - 1.2) - /0.83 (0.65 - 1.2) - /1 (0.95 - 1.2)
national 16 1.1 (1.1 - 1.6) 1.1 (1.1 - 1.5) 1.3 (1.2 - 1.7) - /0.93 (0.91 - 1.2) - /0.93 (0.87 - 1.1) - /1 (1 - 1.3)
official 1 - /1
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IDN 2.2 global 25 1.1 (0.79 - 2) 0.62 (0.51 - 0.89) 1.7 (1.4 - 2.4) 0.93 (0.76 - 1.4)/0.99 0.53 (0.45 - 0.66)/0.68 1.8 (1.3 - 2.1)/2.1 (1.5 - 2.2)
(0.6 - 0.77)
official 2 1.9 (1.8 - 1.9)/2.2
CAN 1.5 global 67 0.58 (0.4 - 0.8) 0.43 (0.38 - 0.72) 0.68 (0.51 - 1) - /0.43 (0.34 - 0.67) - /0.43 (0.31 - 0.64) - /0.53 (0.49 - 0.82)
national 2 0.54 0.71 - /0.41 - /0.54
official 2 0.67
MEX 1.5 global 31 0.61 (0.54 - 1.3) 0.48 (0.3 - 0.56) 0.82 (0.72 - 1.7) 0.54 (0.48 - 1)/0.46 0.43 (0.27 - 0.54)/0.33 0.65 (0.62 - 1.4)/0.73 (0.63 -
(0.26 - 0.42) 0.79)
official 2 0.62/0.76
SAU 1.5 global 6 0.7 (0.57 - 0.82) 0.61 (0.48 - 0.74) 1 (0.7 - 1.1) 0.7 (0.58 - 0.82)/ - 0.62 (0.49 - 0.74)/ - 0.83 (0.7 - 0.96)/ -
KOR 1.4 global 64 0.69 (0.55 - 0.76) 0.67 (0.42 - 0.91) 0.72 (0.68 - 0.81) - /0.57 (0.5 - 0.65) - /0.4 (0.26 - 0.61) - /0.57 (0.5 - 0.69)
national 4 0.78 (0.75 - 0.81) 0.73 (0.7 - 0.76) 0.86 (0.83 - 0.89) - /0.62 (0.51 - 0.72) - /0.58 (0.49 - 0.67) - /0.68 (0.56 - 0.8)
official 1
AUS 1.1 global 16 0.42 (0.34 - 0.49) 0.34 (0.28 - 0.46) 0.54 (0.46 - 0.69) - /0.36 (0.28 - 0.43) - /0.3 (0.24 - 0.41) - /0.44 (0.39 - 0.52)
national 3 0.55
official 2 0.52 (0.51 - 0.52)
TUR 1.1 global 18 0.44 (0.44 - 0.49) 0.4 (0.34 - 0.43) 0.6 (0.51 - 0.83) - /0.44 (0.44 - 0.49) - /0.4 (0.27 - 0.43) - /0.94 (0.55 - 1)
official 1 - /0.93
ZAF 1.1 global 26 0.49 (0.35 - 0.62) 0.36 (0.23 - 0.56) 0.64 (0.45 - 0.85) - /0.4 (0.27 - 0.55) - /0.35 (0.21 - 0.44) 0.41/0.58 (0.39 - 0.65)
official 1 - /0.52 (0.41 - 0.64)
VNM 0.92 global 2 0.61/0.77
national 4 0.36 0.28 0.32 (0.28 - 0.36)/0.36 0.26 (0.24 - 0.28)/0.28
GBR 0.86 global 4 0.37 0.33 (0.3 - 0.37) - /0.37 - /0.33 (0.3 - 0.37)
FRA 0.85 global 4 0.22 0.32 (0.24 - 0.4) - /0.22 - /0.32 (0.24 - 0.4)
THA 0.84 global 5 0.41 (0.41 - 0.41) 0.44/0.47
national 3 0.43 0.4 0.58 0.35/0.36 0.32/0.34 0.43/0.46
ARG 0.76 global 22 0.33 (0.17 - 0.52) 0.2 (0.15 - 0.35) 0.51 (0.33 - 0.75) 0.25 (0.17 - 0.46)/0.25 0.21 (0.18 - 0.23)/0.15 0.39 (0.32 - 0.69)/0.51 (0.33 -
(0.14 - 0.16) 0.52)
national 2 0.42 (0.41 - 0.43) - /0.19
official 2 0.4/0.52
KAZ 0.71 global 3 0.45 0.28/0.32
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UKR 0.52 global 2 0.42 (0.42 - 0.42) - /0.54
PHL 0.48 global 3 0.24 0.082/ -
COL 0.4 global 5 0.23 (0.23 - 0.23) 0.26 (0.26 - 0.26)/0.29 (0.29 -
0.29)
ETH 0.31 global 5 0.022 0.23 (0.19 - 0.27) - /0.023 0.16 (0.15 - 0.16)/ -
MAR 0.21 global 5 0.11 (0.087 - 0.13) 0.13 (0.1 - 0.15)/0.13 (0.1 -
0.15)
KEN 0.18 global 5 0.022 0.13 (0.11 - 0.14) - /0.023 0.11 (0.11 - 0.11)/ -
SWE 0.13 global 4 -0.012 0.03 (0.029 - - /-0.012 - /0.03 (0.028 - 0.032)
0.031)
PRT 0.12 global 2 0.045 0.036 - /0.045 - /0.036
national 1 - /0.023
CHE 0.094 global 1 - /0.026
national 1 0.027 0.025
MDG 0.065 global 1 0.033/ -
national 3 0.071 0.0059 0.07 (0.068 - 0.071)/ - 0.0043 (0.0026 - 0.0059)/
-
41 Notes: a Countries are abbreviated by their ISO 3166-1 alpha-3 letter codes. EU denotes the European Union. b 2018 Share of global Kyoto GHG emissions, excluding FOLU
42 emissions, based on 2019 GHG emissions from Chapter 2 (Minx et al. 2021; Crippa et al. 2021). c Type distinguishes between independent globally comprehensive studies
43 (that also provide information at the country/region level), independent national studies and official communications via Biennial Reports, Biennial Update Reports or National
44 Communications. d Different estimates from one study (e.g., data from multiple models or minimum and maximum estimates) are counted individually, if available. e GHG
45 emissions expressed in CO2-eq emission using AR6 100-year GWPs (see Section 2.2.2 for a discussion of implications for historical emissions). GHG emissions from scenario
46 data is recalculated from individual emission species using AR6 100-year GWPs. GHG emissions from studies that do provide aggregate GHG emissions using other GWPs
47 are rescaled using 2019 GHG emissions from Chapter 2 (Minx et al. 2021; Crippa et al. 2021). f If more than one value is available, a median is provided and the full range of
48 estimates (in parenthesis). To avoid a bias due to multiple estimates provided by the same model, only one estimate per model, typically the most recent update, is included in
49 the median estimate. In the full range, multiple estimates from the same model might be included, in case these reflect specific sensitivity analyses of the “central estimate”
50 (e.g., (Baumstark et al. 2021; Rogelj et al. 2017)). g Note that AFOLU emissions from national GHG inventories and global/national land use models are generally different
51 due to different approaches to estimate the anthropogenic CO 2 sink (Grassi et al. 2018, 2021)(7.2.3 and Cross-Chapter Box 6). h The estimates for the USA are based on the
52 first NDC submitted prior to the withdrawal from the Paris Agreement, but not including the updated NDC submitted following its re-entry. i The EU estimates are based on
53 the 28 member states up until 31 January 2020, i.e. including the UK.
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1 4.2.2.4 Estimated impact of COVID-19 and governmental responses on emissions projections
2 The impacts of COVID-19 and national governments’ economic recovery measures on current (see
3 2.2.2) and projected emissions of individual countries and globally under current policies scenarios until
4 2030 may be significant, although estimates are highly uncertain and vary across the few available
5 studies. The analyses published to date (October 2021) are based on limited information about how
6 COVID-19 has affected the economy and hence GHG emissions across countries so far in 2020, and
7 also based on assumptions about COVID-19’s longer term impact. Moreover, the comparison of pre-
8 and post-COVID-19 projections captures the impact of COVID-19 as well as other factors such as the
9 consideration of recently adopted policies not related to COVID-19, as well as methodological changes.
10 Across different studies (Kikstra et al. 2021; IEA 2020; Dafnomilis et al. 2021; Pollitt et al. 2021; UNEP
11 2020a; Climate Action Tracker 2020; Keramidas et al. 2021; Dafnomilis et al. 2020), the impact of the
12 general slowdown of the economy due to the COVID-19 pandemic and its associated policy responses
13 would lead to a reduced estimate of global GHG emissions in 2030 of about 1 to 5 GtCO2eq, equivalent
14 to 1.5 to 8.5 per cent, compared to the pre-COVID-19 estimates (see Table S4.2 for details). Nascimento
15 et al. (2021) analyse the impacts of COVID-19 on current policy emission projections for 26 countries
16 and regions and find a large range of emission reduction—between -1% and -21%—across these.
17 As indicated by a growing number of studies at the national and global level, how large near- to mid-
18 term emissions implications of the COVID-19 pandemic are to a large degree depends on how stimulus
19 or recovery packages are designed (Wang et al. 2020; Gillingham et al. 2020; Forster et al. 2020; Malliet
20 et al. 2020; Le Quéré et al. 2020; Obergassel et al. 2021; IEA 2020; UNEP 2020a; Pollitt et al. 2021).
21 Four studies (Climate Action Tracker 2021; den Elzen et al. 2021; JRC 2021; Riahi et al. 2021) provide
22 an update of the current policies assessment presented in Section 4.2.2.3 by taking into account the
23 effects of COVID-19 as well as potential updates of policies. The resulting GHG emissions in 2030 are
24 estimated to be 57 GtCO2-eq with a full range of 52 to 60 GtCO2-eq (Table 4.2). This is a reduction of
25 about 3 GtCO2-eq or 5% compared to the pre-COVID estimates from Section 4.2.2.3.
26
27 Table 4.2 Projected global GHG emissions of current policies by 2030.
Kyoto GHGsa [GtCO2-eq]
References
median (min - max)b
Climate Action Tracker 54 (52-56) (Climate Action Tracker 2021)
PBL 58 (den Elzen et al. 2021; Nascimento et al. 2021)
JRC GECO 57 (JRC 2021)
ENGAGEc 57 (52-60) (Riahi et al. 2021)
Totald 57 (52-60)
28 Notes: a GHG emissions expressed in CO2-eq emission using AR6 100-year GWPs. GHG emissions from studies
29 that provide aggregate GHG emissions using other GWPs are rescaled using 2019 GHG emissions from Chapter
30 2 (Minx et al. 2021; Crippa et al. 2021). b If a range is available from a study, a median is provided in addition to
31 the range. c Range includes estimates from four models GEM-E3, MESSAGEix-GLOBIOM, POLES, REMIND-
32 MAgPIE based on sensitivity analysis. d To avoid a bias due to multiple estimates provided by the same model,
33 only one estimate per model, typically the most recent update, is included in the median estimate for the total.
34 4.2.2.5 Estimated impact of new and updated NDCs on emissions projections
35 The number of studies estimating the emissions implications of new and updated NDCs and announced
36 mitigation pledges that can be used for the quantitative assessment is limited to four (Table 4.3) (Climate
37 Action Tracker 2021; den Elzen et al. 2021; Meinshausen et al. 2021; JRC 2021). One other study
38 includes a limited number of NDC updates (Riahi et al. 2021) and another (UNFCCC 2021) excludes
39 LULUCF emissions. They are therefore not directly comparable to the other two. In addition, the UNEP
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1 Emissions Gap Report 2021 (UNEP 2021) in itself is assessment of almost the same studies included
2 here. The evidence base for the updated NDC assessment is thus considerably smaller compared to that
3 of the assessment of emissions implications of original NDCs presented in Section 4.2.2.3. However, it
4 is worthwhile to note that the earlier versions of the studies summarized in Table 4.2 and Table 4.3 are
5 broadly representative for the emissions range implied by the pre-COVID-19 current policies and
6 original NDCs of the full set of studies shown in Table 4.1, therefore building confidence in estimates.
7 An additional challenge lies in the fact that these studies do not all apply the same cut-off date for NDC
8 updates, potentially leading to larger systematic deviations in the resulting emission estimates. Another
9 complication is the fact that publicly announced mitigation pledges on global 2030 emissions that have
10 not been officially submitted to the UNFCCC NDC registry yet, have been included in several of the
11 studies to anticipate their impact on emission levels (see notes to Table 4.3). In addition to the updates
12 of NDC targets, most of the new studies also include impacts of COVID-19 on future emission levels
13 (as discussed in 4.2.2.4) which may have led to considerable downward revisions of emission trends
14 unrelated to NDCs. Table 4.3 presents the emission estimates of the four studies that form the basis of
15 the quantitative assessment presented here and three other studies to compare with.
16
17 Table 4.3 Projected global GHG emissions of new and updated NDCs by 2030.
Cut-off Kyoto GHGsa [GtCO2-eq] References
date historical median (min - max)b 2030
2015 2019 Unconditional Conditional
Study NDCs NDCs
Climate Action (Climate Action Tracker
Trackerc 5/2021 51 52 50 47 2021)
(den Elzen et al. 2021;
PBLd 9/2021 52 54 53 (51-55) 52 (49-53) Nascimento et al. 2021)
JRC – GECOe 10/2021 51 48 (JRC 2021)
Meinshausen et al.f 10/2021 54 56 55 (54-57) 53 (52-55) (Meinshausen et al. 2021)
Totalg 53 (50-57) 50 (47-55)
Other studies for comparison
UNEP EGRh 9/2021 53 (50-55) 50 (47-53) (UNEP 2017a)
UNFCCC (UNFCCC 2021)
Secretariati 7/2021 57 (55-58) 54 (52-56)
ENGAGEj 3/2021 51 (49-53) (Riahi et al. 2021)
18 a
Notes: GHG emissions expressed in CO2-eq emission using AR6 100-year GWPs. GHG emissions from studies
19 that provide aggregate GHG emissions using other GWPs are rescaled using 2019 GHG emissions from Chapter
20 2 (Minx et al. 2021; Crippa et al. 2021). Note that due to slightly different system boundaries across historical
21 emission datasets as well as data uncertainties (see Chapter 2, SM2.2 for details) relative change compared to
22 historical emissions should be calculated vis-à-vis the historical emissions data used by a particular study. b If a
23 range is available from a study, a median is provided in addition to the range. c announced mitigation pledges on
24 global 2030 emissions of China and Japan included. d announced mitigation pledges of China, Japan, Republic of
25 Korea included. e announced mitigation pledge of Korea not included. f announced mitigation pledges of China
26 and Republic of Korea not included, emissions from international aviation and shipping not included. g Ranges
27 across four studies are calculated using the median and the full range including the minimum and maximum of
28 studies if available. h UNEP EGR 2021 estimate listed for comparison, but since largely relying on the same
29 studies not included in range estimate. i NDCs submitted until 30 July included, announcements not included,
30 excluding LULUCF emissions. j NDC updates of Brazil, EU and announcement of China included as a sensitivity
31 analysis compared to original NDCs.
32 Comparing the emission levels implied by the new and updated NDCs as shown in Table 4.3 with those
33 estimated by the original NDCs from the same studies (as included in Table 4.1), a downward revision
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1 of 3.8 (3.0-5.3) GtCO2-eq of the central unconditional NDC estimates and of 4.5 (2.7-6.3) GtCO2-eq of
2 the central conditional NDC estimate emerges (medium evidence, medium agreement). The emissions
3 gaps between temperature limits and new and updated NDCs are assessed in Cross-Chapter Box 4
4 below. New and updated unconditional NDC reduce the median gap with 2°C emissions pathways in
5 2030 by slightly more than 20%, from a median gap of 17 GtCO2-eq (9-23) to 13 (10-17). New and
6 updated conditional NDC reduce the median gap with 2°C emissions pathways in 2030 by about one
7 third, from 14 GtCO2-eq (10-20) to 10 (7-14). New and updated unconditional NDC reduce the median
8 gap with 1.5°C emissions pathways in 2030 by about 15%, from a median gap of 27 GtCO2-eq (19-32)
9 to 23 GtCO2-eq (20-26). New and updated conditional NDC reduce the median gap with 1.5°C
10 emissions pathways in 2030 by about 20%, from a median gap of 24 GtCO2-eq (20-29) to 19 GtCO2-
11 eq (16-24). Box 4.1 discusses the adaptation gap.
12 Globally, the implementation gap between projected emissions of current policies and the unconditional
13 and conditional new and updated NDCs is estimated to be around 4 and 7 GtCO2eq in 2030, respectively
14 (Table 4.2 and 4.3) (medium evidence, medium agreement), with many countries requiring additional
15 policies and associated climate action to meet their mitigation targets as specified under the NDCs
16 (limited evidence) (see 4.2.2.6 for more details). It should be noted that the implementation gap varies
17 considerably across countries, with some having policies in place estimated to be sufficient to achieve
18 the emission targets their NDCs, some where additional policies may be required to be sufficient, as
19 well as differences between the policies in place and action on the ground.
20 4.2.2.6 Tracking progress in implementing and achieving NDCs
21 Under the Enhanced Transparency Framework, countries will transition from reporting biennial reports
22 (BRs) and biennial update reports (BURs) to reporting biennial transparency reports (BTRs) starting,
23 at the latest, by December 2024. Each Party will be required to report information necessary to track
24 progress made in implementing and achieving its NDC under the Paris Agreement (UNFCCC 2018b).
25 Thus, no official data exists yet on tracking progress of individual NDCs.
26 Meanwhile, there is some literature at global and national level that aims at assessing whether countries
27 are on track or progressing towards implementing their NDCs and to which degree the NDCs
28 collectively are sufficient to reach the temperature targets of the Paris agreement (Quéré et al. 2018;
29 Höhne et al. 2018; Roelfsema et al. 2020; Rogelj et al. 2016; den Elzen et al. 2019; Höhne et al. 2020).
30 Most of these studies focus on major emitters such as G20 countries and with the aim to inform countries
31 to strengthen their ambition regularly, e.g., through progress of NDCs and as part of the global stocktake
32 (Höhne et al. 2018; Peters et al. 2017). However, a limited number of studies assess the implementation
33 gaps of conditional NDCs in terms of finance, technology and capacity building support. Some authors
34 conclude that finance needed to fulfil conditional NDCs exceeds available resources or the current long-
35 term goal for finance (USD100 billion yr-1) (Pauw et al. 2019); others assess financial resources needed
36 for forest-related activities (Kissinger et al. 2019) (15.4.2). The literature suggests that consistent and
37 harmonised approach to track progress of countries towards their NDCs would be helpful (den Elzen et
38 al. 2019; Höhne et al. 2018; Peters et al. 2017), and negotiations on a common tabular format are
39 expected to conclude during COP26 in November 2021.
40 With an implementation gap in 2030 of 4 to 7 GtCO2-eq (4.2.2.5), many countries will need to
41 implement additional policies to meet their self-determined mitigation targets as specified under the
42 NDCs. Studies that assess the level of projected emissions under current policies indicate that new
43 policies (that have been implemented since the first assessment of the NDCs in 2015 and are thus
44 covered in more recent projections) have reduced projections, by about 2 GtCO2-eq since the adoption
45 of the Paris Agreement in 2015 to 2019 (Climate Action Tracker 2019; UNEP 2020a; den Elzen et al.
46 2019).
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1 4.2.2.7 Literature on fairness and ambition of NDCs
2 Most countries provided information on how they consider their NDCs to be fair and ambitious in the
3 NDCs submitted to UNFCCC and many of these NDCs refer to specific national circumstances such as
4 social, economic and geographical factors when outlining why they are fair and ambitious. Further,
5 several Parties provided information on specific criteria for evaluating fairness and ambition, including
6 criteria relating to: responsibility and capability; share of emissions; development and/or technological
7 capacity; mitigation potential; cost of mitigation actions; the degree of progression or stretching beyond
8 the current level of effort; and the link to objectives and global goals (UNFCCC 2016a).
9 According to its Article 2.2, the Paris Agreement will be implemented to reflect equity and the principle
10 of common but differentiated responsibilities and respective capabilities, in the light of different
11 national circumstances, the latter clause being new, added to the UNFCCC principle (Rajamani 2017;
12 Voigt and Ferreira 2016). Possible different interpretations of equity principles lead to different
13 assessment frameworks (Lahn 2018; Lahn and Sundqvist 2017).
14 Various assessment frameworks have been proposed to analyse fair share ranges for NDCs. The
15 literature on equity frameworks including quantification of national emissions allocation is assessed in
16 section 4.5 (see 13.4.2, 14.3.2 and 14.5.3). Recent literature has assessed equity, analysing how fairness
17 is expressed in NDCs in a bottom-up manner (Cunliffe et al. 2019; Mbeva and Pauw 2016; Winkler et
18 al. 2018). Some studies compare NDC ambition level with different effort sharing regimes and which
19 principles are applied to various countries and regions (Robiou du Pont and Meinshausen 2018; Robiou
20 Du Pont et al. 2017; Holz et al. 2018; Peters et al. 2015; Pan et al. 2017; van den Berg et al. 2019).
21 Others propose multi-dimensional evaluation schemes for NDCs that combine a range of indicators,
22 including the NDC targets, cost-effectiveness compared to global models, recent trends and policy
23 implementation into consideration (Aldy et al. 2017; Höhne et al. 2018). Yet other literature evaluates
24 NDC ambition against factors such as technological progress of energy efficiency and low-carbon
25 technologies (Jiang et al. 2017; Wakiyama and Kuramochi 2017; Kuramochi et al. 2017), synergies
26 with adaptation plans (Fridahl and Johansson 2017), the obligations to deploy carbon dioxide removal
27 technologies like BECCS in the future implied by their near-term emission reductions where they are
28 not reflected on in the first NDCs (Fyson et al. 2020; Pozo et al. 2020; Peters and Geden 2017; Mace et
29 al. 2021). Others identify possible risks of unfairness when applying GWP* as emissions metric at
30 national scale (Rogelj and Schleussner 2019). A recent study on national fair shares draws on principles
31 of international environmental law, excludes approaches based on cost and grandfathering, thus
32 narrowing the range of national fair shares previously assessed, and apply this to the quantification of
33 national fair share emissions targets (Rajamani et al. 2021).
34 4.2.2.8 Uncertainty in estimates
35 There are many factors that influence the global aggregated effects of NDCs. There is limited literature
36 on systematically analysing the impact of uncertainties on the NDC projections with some exception
37 (Benveniste et al. 2018; Rogelj et al. 2017). The UNEP Gap Report (UNEP 2017a) discusses
38 uncertainties of NDC estimates in some detail. The main factors include variations in overall socio-
39 economic development; uncertainties in GHG inventories; conditionality; targets with ranges or for
40 single years; accounting of biomass; and different GHG aggregation metrics (e.g., GWP values from
41 different IPCC assessments). In addition, when mitigation effort in NDCs is described as measures that
42 do only indirectly translate into emission reductions, assumptions necessary for the translation come
43 into play (Doelle 2019). For a more elaborate discussion of uncertainties in NDCs see Section 14.3.2.
44 Some studies assume successful implementation of all of the NDCs’ proposed measures, sometimes
45 including varying assumptions to account for some of the NDC features which are subject to assumed
46 conditions related to finance and technology transfer. Countries “shall pursue domestic mitigation
47 measures” under Article 4.2 of the Paris Agreement (UNFCCC 2015c), but they are not legally bound
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1 to the result of reducing emissions (Winkler 2017a). Some authors consider this to be a lack of a strong
2 guarantee that mitigation targets in NDCs will be implemented (Nemet et al. 2017). Others point to
3 growing extent of national legislation to provide a legal basis for action (Iacobuta et al. 2018) (13.2).
4 These factors together with incomplete information in NDCs mean there is uncertainty about the
5 estimates of anticipated 2030 emission levels.
6 The aggregation of targets results in large uncertainty (Benveniste et al. 2018; Rogelj et al. 2017). In
7 particular, clarity on the contributions from the land use sector to NDCs is needed “to prevent high
8 LULUCF uncertainties from undermining the strength and clarity of mitigation in other sectors” (Fyson
9 and Jeffery 2019). Methodological differences in the accounting of the LULUCF anthropogenic CO2
10 sink between scientific studies and national GHG inventories (as submitted to UNFCCC) further
11 complicate the comparison and aggregation of emissions of NDC implementation (Grassi et al. 2018,
12 2021) (Section 7.2.3 and Cross-Chapter Box 6). This uncertainty could be reduced with clearer
13 guidelines for compiling future NDCs, in particular when it comes to mitigation efforts not expressed
14 as absolute economy-wide targets (Doelle 2019), and explicit specification of technical details,
15 including energy accounting methods, harmonised emission inventories (Rogelj et al. 2017) and finally,
16 increased transparency and comparability (Pauw et al. 2018).
17
18 START CCB 4 HERE
19 Cross-Chapter Box 4 Comparison of NDCs and current policies with the 2030
20 GHG emissions from long-term temperature pathways
21 Authors: Edward Byers (Ireland/Austria), Michel den Elzen (the Netherlands), Céline Guivarch
22 (France), Volker Krey (Germany/Austria), Elmar Kriegler (Germany), Franck Lecocq (France),
23 Keywan Riahi (Austria), Harald Winkler (Republic of South Africa)
24 Introduction
25 The Paris Agreement (PA) sets a long-term goal of holding the increase of global average temperature
26 to ‘well below 2°C above pre-industrial levels’ and pursuing efforts to limit the temperature increase to
27 1.5°C above pre-industrial levels. This is underpinned by the ‘aim to reach global peaking of greenhouse
28 gas emissions as soon as possible’ and ‘achieve a balance between anthropogenic emissions by sources
29 and removals by sinks of GHG in the second half of this century’ (UNFCCC 2015d). The PA adopts a
30 bottom-up approach in which countries determine their contribution to reach the PA’s long-term goal.
31 These national targets, plans and measures are called ‘nationally determined contributions’ or NDCs.
32 The NDCs are a central instrument of the PA to achieve its long-term goal. It thus combines a global
33 goal with a country-driven (bottom-up) instrument to a hybrid climate policy architecture to strengthen
34 the global response to climate change. All signatory countries committed to communicating nationally
35 determined contributions including mitigation targets, every five years. While the NDCs mostly state
36 targets, countries are also obliged to pursue domestic mitigation measures to achieve the objectives.
37 The literature examines the emissions outcome of the range of policies implemented to reach these
38 targets.
39
40
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1
2 Cross-Chapter Box 4, Figure 1 Aggregate GHG emission outcomes of NDCs and long-term mitigation
3 pathways consistent with global temperature limits. Shown are emission ranges that would emerge when
4 assuming the full implementation of current unconditional and conditional NDCs (grey bars, median and
5 full range) and global pathways from the AR6 scenario database that can be grouped into four types:
6 pathways with near-term emissions developments in line with (1) current policies and extended with
7 comparable ambition levels beyond 2030; (2) pathways holding warming below 2°C (66% chance) with
8 near term emissions developments reflecting ambition levels in current NDCs until 2030; and mitigation
9 pathways undertaking immediate action after 2020 towards (3) holding warming below 2°C (66%
10 chance) and (4) limiting warming to 1.5°C by 2100 (>50% chance) with no or limited (<0.1°C) overshoot,
11 respectively. The upper panel shows the emission pathways until 2050 (median and 25 th-75th percentiles)
12 with their emissions ranges in 2030 and 2050 broken out in full (median and 5 th-95th percentiles). The
13 lower panel shows the ranges (25th -75th percentiles) for the four types of emissions pathways over the 21st
14 century.
15 Notes: GHG emissions are expressed in CO2-equivalent based on 100-year GWPs from AR6. Projected emissions
16 for the current policies and NDCs scenarios from Section 4.2.2 (Tables 4.2/3) show median and full range. The
17 studies on current policies include post-COVID effects up until 2021(Table 4.2). Note that NDC estimates include
18 updates submitted up until October 2021 as well as pledge announcements (Table 4.3). Historical emissions are
19 from the RCMIP historical compiled dataset comprising various sources and methods, as described in (Nicholls
20 et al. 2020).
21 Emissions gap
22 A comparison between the projected emission outcomes of current policies, the NDCs (which include
23 unconditional and conditional elements, see Section 4.2.1) and mitigation pathways acting immediately,
24 i.e. from 2020 onwards, on reaching different temperature goals in the long-term (see Section 3.3.3)
25 allows identifying different ‘emission gaps’ in 2030 (Figure 1). First, the implementation gap between
26 ‘current policies’ and unconditional and conditional NDCs is estimated to be around 4 and 7 GtCO2eq
27 in 2030, respectively (Section 4.2.2 and Tables 4.2 and 4.3). Second, the comparison of unconditional
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1 (conditional) NDCs and long-term mitigation pathways likely limit warming to 2 °C or lower; giving
2 rise to a 2030 median emissions gap of 20-26 GtCO2eq (16-24 GtCO2eq) for limiting end-of-century
3 warming to 1.5°C (50% chance) with no or limited overshoot and 10-17 GtCO2eq (7-14 GtCO2eq) for
4 limiting warming to 2°C (66% chance)4. GHG emissions of NDCs are broadly consistent with 2030
5 emission levels of cost-effective long-term pathways staying below 2.5°C.
6 Other ‘gap indicators’
7 Beyond the quantification of different GHG emissions gaps, there is an emerging literature that
8 identifies gaps between current policies, NDCs and long-term temperature in terms of other indicators,
9 including for example the deployment of low-carbon energy sources, energy efficiency improvements,
10 fossil fuel production levels or investments into mitigation measures (Roelfsema et al. 2020; McCollum
11 et al. 2018; SEI et al. 2020).
12 A 2030 gap in the contribution of low-carbon energy sources to the energy mix in 2030 between current
13 policies and cost-effective long-term temperature pathways is calculated to be around 7%-points (2°C)
14 and 13%-points (1.5°C) by Roelfsema et al. (Roelfsema et al. 2020). The same authors estimate an
15 energy intensity improvement gap 10% and 18% for 2030 between current policies pathways and 2°C
16 and 1.5°C pathways, respectively. SEI et al. (2020) estimates the ‘fossil fuel production gap’, i.e. the
17 level of countries’ planned fossil fuel production expressed in their carbon content to be 120% and 50%
18 higher compared to the fossil fuel production consistent with 1.5°C and 2°C pathways, respectively, as
19 assessed in IPCC SR1.5 (Rogelj et al. 2018a). The methodology used for this estimation is very similar
20 to how emissions gaps are derived (SEI et al. 2019). The gap of global annual average investments in
21 low-carbon energy and energy efficiency in 2030 between following current policy on the one hand and
22 achieving the NDCs, the 2°C and 1.5°C targets on the other hand, is estimated to be approximately USD
23 130, 320, or 480 billion per year (McCollum et al. 2018).
24 It is important to note that such comparisons are less straight forward as the link between long-term
25 temperature goals and these indicators is less pronounced compared to the emission levels themselves;
26 they are therefore associated with greater uncertainty compared to the emissions gap.
27 END CCB 4 HERE
28
29 START BOX 4.1 HERE
30 Box 4.1 Adaptation Gap and NDCs
31 NDCs have been an important driver of national adaptation planning, with cascading effects on sectors
32 and sub-national action, especially in developing countries. Yet, only 40 developing countries have
33 quantifiable adaptation targets in their current NDCs; 49 countries include quantifiable targets in their
34 national legislation (UNEP 2018a).
35 Working Group II contribution to this Assessment finds that the overall extent of adaptation-related
36 responses in human systems is low (high confidence) and that there is limited evidence on the extent to
37 which adaptation-related responses in human systems are reducing climate risk (O’Neill et al. 2020).
38 Thus there is an adaptation gap (UNEP 2018a), and bridging that gap requires enablers including
39 institutional capacity, planning and investment (UNEP 2016). Estimates of adaptation costs vary greatly
40 across studies. Recent studies based on climate change under RCP8.5 report adaptation costs for
FOOTNOTE 4 The emission gap ranges provided here is calculated as the difference between minimum and
maximum emissions estimates of NDCs and the median of the 1.5 and 2°C pathways.
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1 developing countries of up to 400 (300 in RCP2.6) billion USD2005 in 2030 (New et al. 2020). Of the
2 NDCs submitted in 2015, fifty countries estimated adaptation costs of USD 39 billion annually. Both
3 public and private finance for adaptation is increasing, but remains insufficient and constitutes a small
4 fraction (4-8%) of total climate finance which is mostly aimed at mitigation. The pledge of developed
5 countries of mobilising finance for developing countries to address adaptation needs globally as part of
6 the Paris Agreement are insufficient. By 2030 the adaptation needs are expected to be 3 to 6 times larger
7 than what is pledged, further increasing towards 2050 (UNEP 2016; New et al. 2020).
8 END BOX 4.1 HERE
9
10
11 4.2.3 Mitigation efforts in subnational and non-state action plans and policies
12 The decision adopting the Paris Agreement stresses the importance of “stronger and more ambitious
13 climate action” by non-government and subnational stakeholders, “including civil society, the private
14 sector, financial institutions, cities and other subnational authorities, local communities and indigenous
15 peoples” (UNFCCC 2015e). The Marrakech Partnership for Global Action, launched in the 2016
16 UNFCCC Conference of Parties by two “high-level champions,” further formalized the contributions
17 of non-government and subnational actors taking action through seven thematic areas (e.g., energy,
18 human settlements, industry, land-use, etc.) and one cross-cutting area (resilience). Since then, non-
19 state actors, e.g., companies and civil society, and subnational actors, e.g. cities and regions, have
20 emerged to undertake a range of largely voluntary carbon mitigation actions (Hsu et al. 2019, 2018)
21 both as individual non-state actors (NSA in the following) and through national and international
22 cooperative initiatives (ICIs) (Hsu et al. 2018). ICIs take a variety of forms, ranging from those that
23 focus solely on non-state actors to those that engage national and even local governments. They can
24 also range in commitment level, from primarily membership-based initiatives that do not require
25 specific actions to those that require members to tackle emissions reductions in specific sectors or aim
26 for transformational change.
27 Quantification of the (potential) impact of these actions is still limited. Almost all studies estimate the
28 potential impact of the implementation of actions by NSA and ICI, but do not factor in that they may
29 not reach their targets. The main reason for this is that there is very limited data currently available from
30 individual actors (e.g., annual GHG inventory reports) and initiatives to assess their progress towards
31 their targets. A few studies have attempted to assess progress of initiatives by looking into the
32 initiatives’ production of relevant outputs (Chan et al. 2018). Quantification does not yet cover all
33 commitments and only a selected number of ICIs are analysed in the existing literature. Most of these
34 studies exclude commitments that are not (self-)identified as related to climate change mitigation, those
35 that are not connected to international networks, or those that are communicating in languages other
36 than English.
37 Non state action could make significant contributions to achieving the Paris climate goals (limited
38 evidence, high agreement). However, efforts to measure the extent to which non-state and subnational
39 actors go beyond national policy are still nascent (Kuramochi et al. 2020; Hsu et al. 2019) and we do
40 not fully understand the extent to which ambitious action by non-state actors is additional to what
41 national governments intend to do. Subnational and non-state climate action may also have benefits in
42 reinforcing, implementing, or piloting national policy, in place of or in addition to achieving additional
43 emissions reductions (Broekhoff et al. 2015; Heidrich et al. 2016; Hsu et al. 2017).
44 Quantification of commitments by individual NSAs are limited to date. Attempts to quantify aggregate
45 effects in 2030 of commitments by individual non-state and subnational actors are reported by
46 (Kuramochi et al. 2020; Hsu et al. 2019). (Kuramochi et al. 2020) estimate potential mitigation by more
47 than 1,600 companies, around 6,000 cities and many regions (cities assessed have a collective
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1 population of 579 million, and regions 514 million). Individual commitments by these subnational
2 regions, cities and companies could reduce GHG emissions in 2030 by 1.2 to 2.0 GtCO2-eq yr-1
3 compared to current national policies scenario projections, reducing projected emissions by 3.8%–5.5%
4 in 2030, if commitments are fully implemented and do not lead to weaker mitigation actions by others
5 (Figure 4.1 left). In several countries, NSA commitments could potentially help meet or exceed national
6 mitigation targets.
7 Quantification of potential emission reductions from international cooperative initiatives have been
8 assessed in several studies, and recently synthesised (Hsu et al. 2020; Lui et al. 2021), with some
9 initiatives reporting high potential. In Table 4.4 and Figure 4.1, we report estimates of the emissions
10 reductions from 19 distinct sub-national and non-state initiatives to mitigate climate change. The table
11 shows wide ranges of potential mitigation based on current, target or potential membership, as well as
12 a wide diversity of actors and membership assumptions. Current membership reflects the number of
13 non-state or subnational actors that are presently committed to a particular initiative; while targeted or
14 potential membership represents a membership goal (e.g., increasing from 100 to 200 members) that an
15 initiative may seek to achieve (Kuramochi et al. 2020). When adding up emission reduction potentials,
16 sub-national and non-state international cooperative initiatives could reduce up to about 20 Gt of CO2-
17 eq in 2030 (limited evidence, medium agreement). Chapter 8 also presents data on the savings potential
18 of cities and it suggests that these could reach 2.3 GtCO2-eq annually by 2030 and 4.2 GtCO2-eq
19 annually for 2050.
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20 Table 4.4 Emissions reduction potential for sub-national and non-state international cooperative initiatives by 2030
Sector Leading Name Scale Target(s) 2030 emissions Membership
Actor reduction potential assumptions
compared to no
policy, current
policies or NDC
baseline (GtCO2-eq
yr-1)
Min Max
Energy Intergover United for Global Members to adopt policies for energy- 0.6 1.25 Current
efficiency nmental Efficiency (U4E) (focus on efficient appliances and equipment membership
(UNEP) developing
countries)
Energy Intergover Super-efficient Global Members to adopt current policy best 0.5 1.7 (excl. Current
efficiency nmental Equipment and practices for energy efficiency product China) membership
Appliance standards
Deployment
(SEAD) Initiative
Buildings Business Architecture 2030 Global New buildings and major renovations 0.2 0.2 Current
(focus on shall be designed to meet an energy membership
North consumption performance standard of
America) 70% below the regional (or country)
average/median for that building type and
to go carbon- neutral in 2030
Transport Business Collaborative Global Two key objectives: 1) 2% annual fuel 0.3 0.6 Current
(aviation Climate Action efficiency improvement through 2050, 2) membership
sector) Across the Air Stabilise net carbon emissions from 2020
Transport World
(CAATW)
Transport Business Lean and Green Europe Member companies to reduce CO2 0.02 0.02 Current
emissions from logistics and freight membership
activity by at least 25% over a five-year
period
Transport Hybrid Global Fuel Global Halve the fuel consumption of the LDV 0.5 1.0 Current
Economy Initiative fleet in 2050 compared to 2005 membership
(GFEI)
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Transport Business Below50 LCTPi 1) Global Replace 10% of global transportation 0.5 0.5 Scaled-up
fossil fuel use with low-carbon transport global potential
fuels by 2030
Renewable Business European Europe Supply 20% of electricity from solar 0.2 0.5 Current
energy Technology & Photovoltaic PV technologies by 2030 membership
Innovation Platform
Photovoltaic (ETIP
PV)
Renewable Intergover Africa Renewable Africa Produce 300 GW of electricity for Africa 0.3 0.8 Current
energy nmental Energy Initiative by 2030 from clean, affordable and membership
(African (AREI) appropriate forms of energy
Union)
Renewable Hybrid Global Geothermal Global Achieve a five-fold growth in the 0.2 0.5 Targeted
energy Alliance (GGA) installed capacity for geothermal power capacity
generation and a more than two-fold
growth in geothermal heating by 2030
Renewable Business REscale LCTPi 1) Global Support deployment of 1.5 TW of 5 5 Scaled-up
energy additional renewable energy capacity by global potential
2025 in line with the IEA’s 2°C scenario
Renewable Business RE100 initiative Global 2,000 companies commit to source 100% 1.9 4 Targeted
energy of their electricity from renewable membership
sources by 2030
Forestry Hybrid Bonn Challenge / Global End forest loss by 2030 in member 3.8 8.8 Scaled-up
Governors’ Climate countries and restore 150 million hectares global potential
and Forests Task of deforested and degraded lands by 2020
Force (GCFTF) / and an additional 200 million hectares by
New York 2030
Declaration on
Forests (NYDF)
Non-CO2 Governme Climate & Clean Global Members to implement policies that will 1.4 3.8 Current
emissions nt Air Coalition deliver substantial short-lived climate membership
(CCAC) forcers (SLCP) reductions in the near- to
medium-term (i.e., by 2030) for HFCs
and methane
Non-CO2 Intergover Zero Routine Global Eliminate routine flaring no later than 0.4 0.4 Current
emissions nmental Flaring 2030 membership
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(World
Bank)
Multisecto Cities and Under2 Coalition Global Local governments (220 members) aim 4.6 5 Current
ral regions to limit their GHG emissions by 80 to membership
95% below 1990 levels by 2050
Multisecto Cities and Global Covenant of Global Member cities have a variety of targets 1.4 1.4 Current
ral regions Mayors for Climate (+9,000 members) membership
& Energy (GCoM)
Multisecto Cities and C40 Cities Climate Global 94 member cities have a variety of 1.5 3 Current
ral regions Leadership Group targets, aiming for 1.5°C compatibility by membership
(C40) 2050. The network carries two explicit
goals: 1) to have every C40 city develop
a climate action plan before the end of
2020 (Deadline 2020), which is “deliver
action consistent with the objectives of
the Paris Agreement” and 2) to have
cities achieve emissions neutrality by
2050
Agricultur Business Climate Smart Global Reducing agricultural and land-use 3.7 3.7 Scaled-up
e Agriculture (CSA) change emissions from agriculture by at global potential
LCTPi 1) least 50% by 2030 and 65% by 2050. 24
companies and 15 partners
Multisecto Business Science Based Global By 2030, 2,000 companies have adopted 2.7 2.7 Targeted
ral Targets initiative a science- based target in line with a 2°C membership
(SBTi) temperature goal
21 Source: (Hsu et al. 2020)
22 Note 1 As of December 2020 most of the Low Carbon Technology Partnerships (LCTPi) initiatives are defunct, except the Climate Smart Agriculture programme
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1
2 Figure 4.1 Emissions reduction potential for non-state and sub-national actors by 2030
3 Source: Data in left panel from Hsu et al. (2020), right panel from Lui et al. (2020).
4
5 Non-state action may be broader than assessed in the literature so far, though subject to uncertainty.
6 The examples in Table 4.4 and Figure 4.1 do not include initiatives that target the emissions from
7 religious organisations, colleges and universities, civic and cultural groups, and, to some extent,
8 households, and in this sense may underestimate sub-national potential for mitigating emissions, rather
9 than overestimate it. That said, the estimates are contingent on assumptions that subnational and non-
10 state actors achieve commitments—both with respect to mitigation and in some cases membership—
11 and that these actions are not accounted for in nor lead to weakening of national actions.
12 Care is to be taken not to depict these efforts as additional to action within national NDCs, unless this
13 is clearly established (Broekhoff et al. 2015). There are potential overlaps between individual NSA and
14 ICI, and across ICIs. Kuramochi et al. (2020) propose partial and conservative partial effect methods to
15 avoid double counting when comparing ambition, a matter that merits further attention. As the diversity
16 of actions increased, the potential to count the same reductions multiple times increases.
17 Equally important to note here is that none of the studies reviewed in Figure 4.1 quantified the potential
18 impact of financial sector actions, e.g., divestment from emission intensive activities (see Section 15.3
19 for a more detailed discussion of how financial actors and instruments are addressing climate change).
20 Moreover, only a limited number of studies on the impact of actions by diverse actors go beyond 2050
21 (see Table 4.4), which may reflect analysts’ recognition of the increasing uncertainties of longer time
22 horizons. Accurate accounting methods can help to avoiding counting finance multiple times, and
23 methods across mitigation and finance would consider counting carbon market flows and the tons
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1 reduced. As Table 4.4 and Figure 4.1 indicate, activities by businesses have potential to significantly
2 contribute to global mitigation efforts. For example, the SBTi (Science-Based Targets Initiative)
3 encourages companies to pledge to reduce their emissions at rates which according to SBTI would be
4 compatible with global pathways to well below 2°C or 1.5°C, with various methodologies being
5 proposed (Andersen et al. 2021; Faria and Labutong 2019). Readers may note, however, that the link
6 between emissions by individual actors and long-term temperature goals cannot be inferred without
7 additional assumptions (see Box 4.2). In the energy sector, some voluntary initiatives are also emerging
8 to stop methane emissions associated with oil and gas supply chains. The Oil and Gas Methane
9 Partnership (OGMP) is a voluntary initiative lead by the Climate and Clean Air Coalition, which has
10 recently published a comprehensive framework for methane detection, measurement and reporting
11 (UNEP 2020b).
12 Initiatives made up of cities and subnational regions have an especially large potential to reduce
13 emissions, due to their inclusion of many actors, across a range of different geographic regions, with
14 ambitious emissions reduction targets, and these actors’ coverage of a large share of emissions
15 (Kuramochi et al. 2020). Hsu et al. (2019) find largest potential in that area. Several subnational regions
16 like California and Scotland have set zero emission targets (Höhne et al. 2019), supported by short- and
17 medium-term interim goals (Scottish Government 2020; State of California 2018). Sharing of effort
18 across global and sub-global scales has not been quantified, though one study suggests that non-state
19 actors have increasingly adopted more diverse framings, including vulnerability, human rights and
20 transformational framings of justice (Shawoo and McDermott 2020). Initiatives focused on forestry
21 have high emissions reduction potential due to the current high deforestation rates, and due to the
22 ambitious targets of many of these forestry initiatives, such as the New York Declaration on Forests’
23 goal to end deforestation by 2030 (Höhne et al. 2019; Lui et al. 2021), although the Initiative
24 acknowledges that insufficient progress has to-date been made towards this goal (NYDF Assessment
25 Partners 2020). On the other hand, uncertainties in global forest carbon emissions (and therefore
26 potential reductions) are high and despite a multitude of initiatives in the sector, actually measured
27 deforestation rates have not declined since the initiative was announced in 2014 (7.2, 7.3.1). Moreover,
28 not all initiatives are transparent about how they plan to reach their goals and may also rely on offsets.
29 Initiatives focused on non-CO2 emissions, and particularly on methane, can achieve sizable reductions,
30 in the order of multiple GtCO2-eq yr-1 (see Table 4.4). The Global Cement and Concrete Association
31 (formerly the Cement Sustainability Initiative), has contributed to the development of consistent energy
32 and emissions reporting from member companies. The CSI also suggested possible approaches to
33 balance GHG mitigation and the issues of competitiveness and leakage (Cook and Ponssard 2011). The
34 member companies of the GCCA (CSI) have become better prepared for future legislation on managing
35 GHG emissions and developed management competence to respond to climate change compared to
36 non-member companies in the cement sector (Busch et al. 2008; Global Cement and Concrete
37 Association 2020). Accordingly, the cement industry has developed some roadmaps to reach net zero
38 GHG around 2050 (Sanjuán et al. 2020).
39 It is also important to note that individual NSA and ICI that commit to GHG mitigation activities are
40 often scarce in many crucial and ‘hard-to-abate’ sectors, such as iron and steel, cement and freight
41 transport (see Chapters 10 and 11). Subnational and non-state action efforts could help these sectors
42 meet an urgent need to accelerate the commercialisation and uptake of technical options to achieve low
43 zero emissions (Bataille 2020).
44
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1 4.2.4 Mid-century low-emission strategies at the national level
2 An increasing amount of literature describes mitigation pathways for the mid-term (up to 2050). We
3 assess literature reflecting on the UNFCCC process (4.2.4.1), other official plans and strategies (4.2.4.2)
4 and academic literature on mid-century low-emission pathways at the national level (4.2.4.3). After the
5 Paris Agreement and the IPCC SR1.5 Report, the number of academic papers analysing domestic
6 emission pathways compatible with the 1.5°C limit has been increasing. Governments have developed
7 an increasing number of mitigation strategies up to 2050. Several among these strategies aim at net zero
8 CO2 or net zero GHG, but it is not yet possible to draw global implications due to the limited size of
9 sample (limited evidence, limited agreement).
10
11 START BOX 4.2 HERE
12
13 Box 4.2 Direct links between an individual actor’s mitigation efforts in the near-term and global
14 temperature goals in the long-term cannot be inferred; making direct links requires clear
15 distinctions of spatial and temporal scales (Robertson 2021; Rogelj et al. 2021) and explicit
16 treatment of ethical judgements made (Holz et al. 2018; Klinsky et al. 2017a; Rajamani et al. 2021;
17 Klinsky and Winkler 2018).
18
19 The literature frequently refers to national mitigation pathways up to 2030 or 2050 using long-term
20 temperature limits in the Paris Agreement (i.e., “2°C” or “1.5°C scenario”). Without additional
21 information, such denomination is incorrect. Working Group I reaffirmed “with high confidence the
22 AR5 finding that there is a near-linear relationship between cumulative anthropogenic CO2 emissions
23 and the global warming they cause” (WGI SPM AR6). It is not the function of any single country’s
24 mitigation efforts, nor any individual actor’s. Emission pathways of individual countries or sectors in
25 the near- to mid-term can only be linked to a long-term temperature with additional assumptions
26 specifying (i) the GHG emissions and removals of other countries up the mid-term; and (ii) the GHG
27 emissions and removals of all countries beyond the near- and mid-term. For example, a national
28 mitigation pathway can be labelled “2°C compatible” if it derives from a global mitigation pathway
29 consistent with 2°C via an explicit effort sharing scheme across countries (see 4.2.2.6 and 4.5).
30
31 END BOX 4.2 HERE
32
33
34 4.2.4.1 GHG Mitigation target under UNFCCC and Paris Agreement
35 The Paris Agreement requests that Parties should strive to formulate and communicate long-term low
36 GHG development strategies by 2020. (Note that by “long-term”, the UNFCCC means 2050, which is
37 the end point of the “mid-term” horizon range in the present report.) As of August 25, 2021, 31 countries
38 and the European Union had submitted low-emissions development strategies (LEDS) (Table 4.5).
39 By 2018, most long-term strategies targeted 80% emissions reduction in 2050 relative to a reference
40 (1990, 2000 or 2005). After IPCC SR1.5 was published, the number of the countries aiming at net zero
41 CO2 or GHG emissions has been increasing.5
FOOTNOTE5 Specifying gases aids clarity, see Cross-Chapter Boxes 2 and 3. Some countries refer to net zero
GHG emissions as ‘climate neutrality’ or ‘carbon neutrality’; the more precise terms are used where supported by
the information assessed in this report.
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1
2 Table 4.5 Countries having submitted long-term low GHG emission development strategy
3 (as of August 25, 2021)
Country Date submitted GHG reduction target
USA Nov. 16, 2016 80% reduction of GHG in 2050 compared to 2005 level
Mexico Nov. 16, 2016 50% reduction of GHG in 2050 compared to 2000 level
Canada Nov. 17, 2016 80% reduction of GHG in 2050 compared to 2005 level
Germany Nov. 17, 2016 Greenhouse gas neutrality by 2050
Rev. Apr. 26, 2017 (Old target: 80-95% reduction of GHG in 2050 compared to
1990 level)
Rev. May 4, 2017
France Dec. 28, 2016 Achieving net zero GHG emissions by 2050
Rev. Apr. 18, 2017 (Old target: 75% reduction of GHG in 2050 compared to 1990
level)
Rev. Feb. 8, 2021
Benin Dec. 12, 2016 Resilient to climate change and low carbon intensity by 2025
Czech Republic Jan. 15, 2018 80% reduction of GHG in 2050 compared to 1990 level
UK April 17, 2018 80% reduction of GHG in 2050 compared to 1990 level
Ukraine July 30, 2018 66-69% reduction of GHG in 2050 compared to 1990 level
Republic of the Sept. 25, 2018 Net zero greenhouse gas emissions by 2050
Marshall Islands
Fiji Feb. 25, 2019 Net zero carbon by 2050 as central goal, and net negative
emissions in 2041 under a Very High Ambition scenario
Japan June 26, 2019 80% reduction of GHG in 2050, and decarbonized society as
early as possible in the 2nd half of 21st century
Portugal Sept. 20, 2019 Carbon neutrality by 2050
Costa Rica Dec. 12, 2019 Decarbonized economy with net zero emissions by 2050
European Union March 6, 2020 Net zero GHG emissions by 2050
Slovakia March 30, 2020 Climate neutrality by 2050, with decarbonisation targets
implying reduction of at least 90% compared to 1990 (not
taking into account removals)
Singapore March 31, 2020 Halving emissions from its peak to 33 MtCO2-e by 2050, with
a view to achieving net zero emissions as soon as viable in the
second half of the century.
South Africa Sep. 23, 2020 Net zero carbon economy by 2050
Finland Oct.5, 2020 Carbon neutrality by 2035; 87.5-90% reduction of GHG in
2050 to 1990 level (excluding land use sector)
Norway Nov. 25, 2020 Being a low-emission society by 2050
Latvia Dec. 9, 2020 Climate neutrality by 2050 (non-reducible GHG emissions are
compensated by removals in the LULUCF sector)
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Spain Dec. 10, 2020 Climate neutrality by 2050
Belgium Dec. 10, 2020 Carbon neutrality by 2050 (Walloon Region);Full climate
neutrality (Flemish Region), and the European target of carbon
neutrality by 2050 (Brussels-Capital Region)
Austria Dec. 11, 2020 climate-neutral by no later than 2050
Netherlands Dec. 11, 2020 Reduction of GHG emissions by 95% by 2050 compared to
1990 level.
Sweden Dec. 11, 2020 Zero net emissions of GHG into the atmosphere latest by 2045
Denmark Dec. 30, 2020 Climate neutrality by 2050
Republic of Korea Dec. 30, 2020 Carbon neutrality by 2050
Switzerland Jan. 28, 2021 2050 net zero GHG
Guatemala July 6, 2021 59% reduction of projected emissions by 2050
Indonesia July 22, 2021 540 MtCO2-e by 2050, and with further exploring opportunity
to rapidly progress towards net zero emission in 2060 or sooner
Slovenia Aug. 23, 2021 Net zero emissions or climate neutrality by 2050
1
2 4.2.4.2 Other national emission pathways to mid-century
3 At the 2019 Climate Action Summit, 77 countries indicated their aim to reach net zero CO2 emissions
4 by 2050, more the number of countries having submitted LEDS to the UNFCCC. Table 4.6 lists the
5 countries that have a national net zero by 2050 target in laws, strategies or other documents (The Energy
6 and Climate Intelligence Unit 2019). Bhutan and Suriname already have achieved net negative
7 emissions. France second “low-carbon national strategy” adopted in 2020 has an objective of GHG
8 neutrality by 2050. Net zero is also the basis of the recent revision of the official notional price of carbon
9 for public investment in France (Quinet et al. 2019). The Committee on Climate Change of the UK
10 analyses sectoral options and concludes that delivering net zero GHG by 2050 is technically feasible
11 but highly challenging (Committee on Climate Change 2019). For Germany, three steps to climate
12 neutrality by 2050 are introduced: First, a 65% reduction of emissions by 2030; second, a complete
13 switch to climate- neutral technologies, leading to a 95% cut in emissions, all relative to 1990 levels by
14 2050; and third balancing of residual emissions through carbon capture and storage (Görz et al. 2020).
15 In addition to the countries in Table 4.6, EU reported the net zero GHG emission pathways by 2050
16 under Green Deal (European Commission 2019). China and South Korea, have made announcements
17 of carbon neutrality by 2060 and net zero GHG emission by 2050, respectively (UN 2020a,b). In the
18 case of Japan, the new target to net zero GHG emission by 2050 was announced in 2020 (UN 2020c).
19 As of August 25, 2021, a total 121 countries participate in the ‘Climate Ambition Alliance: Net Zero
20 2050, together with businesses, cities and regions.
21
22 Table 4.6 Countries with a national net zero CO2 or GHG target by 2050 (as of August 25, 2021)
Country Target year Target status Source
Suriname Achieved Suriname INDC
Bhutan Achieved Royal Government of Bhutan National Environment Commission
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Germany 2045 In Law KSG
Sweden 2045 In Law Climate Policy Framework
European Union 2050 In Law European Climate Law
Japan 2050 In Law Japan enshrines PM Suga's 2050 carbon neutrality promise into law
United Kingdom 2050 In Law The Climate Change Act
France 2050 In Law Energy and Climate Law
Canada 2050 In Law Canadian Net Zero Emissions Accountability Act
Spain 2050 In Law New Law
Denmark 2050 In Law The Climate Act
New Zealand 2050 In Law Zero Carbon Act
Hungary 2050 In Law Climate Ambition Alliance: Net Zero 2050
Luxembourg 2050 In Law Climate Ambition Alliance: Net Zero 2050
South Korea 2050 Proposed Legislation Speeches and Statements by the President
Climate Action and Low Carbon Development (Amendment) Bill
Ireland 2050 Proposed Legislation
2021
Chile 2050 Proposed Legislation Chile charts path to greener future
Fiji 2050 Proposed Legislation Draft Climate Law
1 Note: In addition to the above list, the numbers of “In Policy Document” and “Target Under discussion” as Target status are 37 countries and
2 79 countries, respectively.
3
4 4.2.4.3 Mid-century low emission strategies at the national level in the academic literature
5 Since the 2000s, an increasing number of studies have quantified the emission pathways to mid-century
6 by using national scale models. In the early stages, the national emission pathways were mainly assessed
7 in the developed countries such as Germany, UK, France, the Netherlands, Japan, Canada, and USA.
8 For example, the Enquete Commission in Germany identified robust and sustainable 80% emission
9 reduction pathways (Deutscher Bundestag 2002). In Japan, 2050 Japan Low-Carbon Society scenario
10 team (2008) assessed the 70% reduction scenarios in Japan, and summarized the necessary measures to
11 “Dozen Actions towards Low-Carbon Societies.”
12 Among developing countries, China, India, South Africa assessed their national emission pathways. For
13 example, detailed analysis was undertaken to analyse pathways to China’s goal for carbon neutrality
14 (EFC 2020). In South Africa, a Scenario Building Team (2007) quantified the Long Term Mitigation
15 Scenarios for South Africa.
16 Prior to COP21, most of the literature on mid-century mitigation pathways at the national level was
17 dedicated to pathways compatible with a 2°C limit (see Box 4.2 for a discussion on the relationship
18 between national mitigation pathways and global, long-term targets). After COP21 and the IPCC SR15,
19 literature increasingly explored just transition to net zero emissions around 2050. This literature reflects
20 on low-emissions development strategies (cognate with SDPS, see 4.3.1) and policies to get to net zero
21 CO2 or GHG emissions (Waisman et al. 2021)(Cross-Chapter Box 5).
22 Figure 4.2 provides a snapshot of this literature. For a selected set of countries, it shows the mid-century
23 emission pathways at national scale that have been registered in the IIASA national mitigation scenario
24 database built for the purpose of this Report (Annex III.3.3). Overall, the database contains scenarios
25 for 50 countries. Total GHG emission are the most comprehensive information to assess the pathways
26 on climate mitigation actions, but energy-related CO2 emissions are the most widely populated data in
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1 the scenarios. As a result, Figure 4.2 shows energy-related CO2 emission trajectories. Scenarios for EU
2 countries show reduction trends even in the reference scenario, whereas developing countries and non-
3 European developed countries such as Japan and USA show emissions increase in the reference. In
4 most countries plotted on Figure 4.2, studies have found that reaching net zero energy related CO2
5 emissions by 2050 is feasible, although the number of such pathways is limited.
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1
2 Figure 4.2 Energy related CO2 emission pathways to mid-century from existing studies
3 Source of the historical data: Greenhouse Gas Inventory Data of UNFCCC
4 (https://di.unfccc.int/detailed_data_by_party)
5 The literature underlines the differences induced by the shift from “2°C scenarios” (typically assumed
6 to imply mitigation in 2050 around 80% relative to 1990) to “1.5°C scenarios” (typically assumed to
7 imply net zero CO2 or GHG emissions in 2050) (Box 4.2). For Japan, Oshiro et al. (2018) shows the
8 difference between the implications of a 2°C scenario (80% reduction of CO2 in 2050) and a 1.5 °C
9 scenario (net zero CO2 emission in 2050), suggesting that for a net zero CO2 emission scenario, BECCS
10 is a key technology. Their sectoral analysis aims in 2050 at negative CO2 emissions in the energy sector,
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1 and near-zero emissions in the buildings and transport sectors, requiring energy efficiency improvement
2 and electrification. To do so, drastic mitigation is introduced immediately, and, as a result, the
3 mitigation target of Japan’s current NDC is considered not sufficient to achieve a 1.5°C scenario. Jiang
4 et al. (2018) also show the possibility of net negative emissions in the power sector in China by 2050,
5 indicating that biomass energy with CCS must be adopted on a large scale by 2040. Samadi et al. (2018)
6 indicate the widespread use of electricity-derived synthetic fuels in end-use sectors as well as
7 behavioural change for the 1.5 degree scenario in Germany.
8 In addition to those analyses, Vishwanathan et al. (2018b), Chunark and Limmeechokchai (2018) and
9 Pradhan et al. (2018b) build national scenarios in India, Thailand and Nepal, respectively, compatible
10 with a global 1.5°C. Unlike the studies mentioned in the previous paragraph, they translate the 1.5°C
11 goal by introducing in their model a carbon price trajectory estimated by global models as sufficient to
12 achieve the 1.5°C target. Because of the high economic growth and increase of GHG emissions in the
13 reference case, CO2 emissions in 2050 do not reach zero. Finally, the literature also underlines that to
14 achieve a 1.5°C target, mitigation measures relative to non-CO2 emissions become important, especially
15 in developing countries where the share of non-CO2 emissions is relatively high. (La Rovere et al. 2018)
16 treat mitigation actions in AFOLU sector.
17 Chapter 3 reported on multi-model analyses, comparison of results using different models, of global
18 emissions in the long term. At the national scale, multi-model analyses are still limited, though such
19 analyses are growing as shown in Table 4.7. By comparing the results among different models and
20 different scenarios in a country, the uncertainties on the emission pathways including the mitigation
21 measures to achieve a given emission target can be assessed.
22
23 Table 4.7 Examples of research projects on country-level mitigation pathways in the near- to medium-
24 term under the multi-national analyses
Project name Features
16 countries participated and estimated the deep decarbonisation pathways
DDPP (Deep Decarbonisation
from the viewpoint of each country’s perspective using their own models
Pathways Project)
(Waisman et al. 2019).
COMMIT (Climate Policy
assessment and Mitigation This research project assessed the country contributions to the target of the
Modelling to Integrate national and Paris Agreement (COMMIT 2019).
global Transition pathways)
The mitigation potential and socio-economic implications in Brazil, Chile,
Colombia and Peru were assessed (La Rovere et al. 2018; Benavides et al.
2015; Zevallos et al. 2014; Delgado et al. 2014). The experiences of the
MAPS (Mitigation Action Plans MAPS programme suggests that co-production of knowledge by researchers
and Scenarios) and stakeholders strengthens the impact of research findings, and in depth
studies of stakeholder engagement provide lessons (Boulle et al. 2015; Kane
and Boulle 2018; Raubenheimer et al. 2015), which can assist building
capacity for long-term planning in other contexts (Calfucoy et al. 2019).
CD-LINKS (Linking Climate and The complex interplay between climate action and development at both the
Development Policies – global scale and some national perspectives were explored. The climate
Leveraging International Networks policies for G20 countries up to 2015 and some levels of the carbon budget
and Knowledge Sharing) are assessed for short-term and long-term, respectively (Rogelj et al. 2017).
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Total 21 APEC countries assessed 2 degree scenario which follows the
APEC Energy Demand and Supply carbon emissions reduction pathway included in the IEA Energy
Outlook Technology Perspectives (IEA 2017) by using the common framework
(APERC 2019).
The low carbon emission scenarios for several countries and cities in Asia
were assessed by using the same framework (Matsuoka et al. 2013). The
Low-Carbon Asia Research Project mitigation activities were summarised into 10 actions toward Low Carbon
Asia to show a guideline to plan and implement the strategies for an LCS in
Asia (Low-Carbon Asia Research Project 2012).
This is an inter-model comparison exercise that focused on energy and
CLIMACAP–LAMP
climate change mitigation in Latin America (Clarke et al. 2016).
DDPP-LAC (Latin American Deep 6 countries in Latin America analysed the activities in AFOLU (agriculture,
Decarbonisation Pathways project) forestry and land use) commonly (Bataille et al. 2020).
This is an international research project which covers 5 countries and 1
region in order to build capacity and knowledge on low-emissions
MILES (Modelling and Informing
development strategies both at a national and global level, by investigating
Low-Emission Strategies)
the concrete implications of INDCs for the low-carbon transformation by
and beyond 2030 (Spencer et al. 2015).
1
2 Another type of multi-model analysis is international, i.e., different countries join the same project and
3 use their own national models to assess a pre-agreed joint mitigation scenario. By comparing the results
4 of various national models, such projects help highlight specific features of each country. More robust
5 mitigation measures can be proposed if different types of models participate. These activities can also
6 contribute to capacity building in developing countries.
7
8 4.2.5 What is to be done to accelerate mitigation?
9 4.2.5.1 Overview of accelerated mitigation pathways
10 The literature reports an increasing number of accelerated mitigation pathways that are beyond NDCs
11 in different regions and countries. There is increasing understanding of the technical content of such
12 pathways, though the literature remains limited on some dimensions, such as demand-side options,
13 systems analysis, or mitigation of AFOLU non-CO2 GHGs. The present section describes insights from
14 this literature.
15 Overall, the literature shows that pathways considered consistent with likely below 2˚C or 1.5˚C (see
16 Box 4.2)—including inter alia 80% reduction of GHG emissions in 2050 relative to 1990 or 100%
17 renewable electricity scenarios—are technically feasible (Esteban et al. 2018; Esteban and Portugal-
18 Pereira 2014; Lund and Mathiesen 2009; Young and Brans 2017; Mathiesen et al. 2011; Hansen et al.
19 2019; Child et al. 2019). They entail increased end-use energy efficiency, significant increases in low-
20 carbon energy, electrification, other new and transformative technologies in demand sectors, adoption
21 of carbon capture and sequestration (CCS) to reduce gross emissions, and contribution to net negative
22 emissions through carbon dioxide removal (CDR) and carbon sinks. For these pathways to be realized,
23 the literature assumes higher carbon prices, combined in policy packages with a range of other policy
24 measures.
25 The most recent literature also reflects on accelerated mitigation pathways aiming at reaching net zero
26 CO2 emissions or net zero GHG emissions by 2050 (4.2.4, Table 4.6) (see glossary entries on net zero
27 CO2 emissions and net zero GHG emissions). Specific policies, measures and technologies are needed
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1 to reach such targets. These include, broadly, decarbonising electricity supply, including through low
2 carbon energy, radically more efficient use of energy than today; electrification of end-uses (including
3 transport / electric vehicles); dramatically lower use of fossil fuels than today; converting other uses to
4 low- or zero-carbon fuels (e.g., hydrogen, bioenergy, ammonia) in hard-to-decarbonise sectors; and
5 setting ambitious targets to reduce methane and other short-lived climate forcers (SLCFs).
6 Accelerated mitigation pathways differ by countries, depending inter alia on sources of emissions,
7 mitigation opportunities and economic context. In China, India, Japan and other Southeast Asian
8 countries, more aggressive action related to climate change is also motivated by regional concerns over
9 health and air quality related to air pollutants and SLCFs (Ashina et al. 2012; Aggarwal 2017; Dhar et
10 al. 2018; Xunzhang et al. 2017; Khanna et al. 2019; China National Renewable Energy Centre 2019;
11 Energy Transitions Commission and Rocky Mountain Institute 2019; Oshiro et al. 2018; Jiang et al.
12 2018; Kuramochi et al. 2017). Studies of accelerated mitigation pathways in North America tend to
13 focus on power sector and imported fuel decarbonisation in the US , and on electrification and demand-
14 side reductions in Canada (Hammond et al. 2020; Vaillancourt et al. 2017; Jayadev et al. 2020; Hodson
15 et al. 2018; Victor et al. 2018; Bahn and Vaillancourt 2020). In Latin America, many pathways
16 emphasise supply-side mitigation measures, finding that replacing thermal power generation and
17 developing bioenergy (where resources are available) utilisation offers the greatest mitigation
18 opportunities (Nogueira de Oliveira et al. 2016; Lap et al. 2020; Herreras Martínez et al. 2015; Arango-
19 Aramburo et al. 2019; Delgado et al. 2020). The European Union-28’s recently announced 2050 climate
20 neutrality goal is explored by pathways that emphasise complete substitution of fossil fuels with
21 electricity generated by low-carbon sources, particularly renewables; demand reductions through
22 efficiency and conservation, and novel fuels and end-use technologies (Capros et al. 2019; Zappa et al.
23 2019; Louis et al. 2020; Duscha et al. 2019; Prognos Öko-Institut Wuppertal-Institut 2020). The limited
24 literature so far on Africa’s future pathways suggest those could be shaped by increasing energy access
25 and mitigating the air pollution and health effects of relying on traditional biomass use, as well as
26 cleaner expansion of power supply alongside end-use efficiency improvements (Hamilton and Kelly
27 2017; Oyewo et al. 2020, 2019; Wright et al. 2019; Ven et al. 2019; Forouli et al. 2020).
28 Though they differ across countries, accelerated mitigation pathways share common characteristics as
29 follows. First, energy efficiency, conservation, and reducing energy use in all energy demand sectors
30 (buildings, transport, and industry) are included in nearly all literature that addresses future demand
31 growth (Jiang et al. 2016; Saveyn et al. 2012; Hanaoka and Masui 2018; Thepkhun et al. 2013; Chilvers
32 et al. 2017; Chiodi et al. 2013; Schmid and Knopf 2012; Oshiro et al. 2017a; Shahiduzzaman and Layton
33 2017; Fragkos et al. 2017; Elizondo et al. 2017; Ouedraogo 2017; Lee et al. 2018; Schiffer 2015;
34 Deetman et al. 2013; Zhou et al. 2019; McNeil et al. 2016; Lefèvre et al. 2018; Sugiyama et al. 2019;
35 Kato and Kurosawa 2019; Jacobson et al. 2019, 2017; Dioha and Kumar 2020; Dioha et al. 2019; Nieves
36 et al. 2019; Jiang et al. 2013; Altieri et al. 2016; Oshiro et al. 2018; Ashina et al. 2012; Vaillancourt et
37 al. 2017; Khanna et al. 2019; Victor et al. 2018; Duscha et al. 2019; Hodson et al. 2018; Capros et al.
38 2019; Nogueira de Oliveira et al. 2016; Kuramochi et al. 2017)
39 Similarly, electrification of industrial processes (up to 50% for EU and China) and transport (e.g., 30-
40 60% for trucks in Canada), buildings, and district heating and cooling are commonplace (Ashina et al.
41 2012; Chiodi et al. 2013; Deetman et al. 2013; Fragkos et al. 2017; Massetti 2012; Mittal et al. 2018;
42 Oshiro et al. 2017b; Oshiro et al. 2018; Saveyn et al. 2012; Vaillancourt et al. 2017; Zhou et al. 2019;
43 Xunzhang et al. 2017; Hammond et al. 2020; Jiang et al. 2018; Capros et al. 2019).
44 Third, lower emissions sources of energy, such as nuclear, renewables, and some biofuels, are seen as
45 necessary in all pathways. However, the extent of deployment depends on resource availability. Some
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1 countries have set targets of up to 100% renewable electricity, while others such as Brazil rely on
2 increasing biomass up to 40-45% of total or industry energy consumption by 2050.
3 Fourth, CCS and CDR are part of many of the national studies reviewed (Ashina et al. 2012; Chilvers
4 et al. 2017; Jiang et al. 2013; Kuramochi et al. 2018; Herreras Martínez et al. 2015; Massetti 2012;
5 Mittal et al. 2018; Oshiro et al. 2018; Xunzhang et al. 2017; Roberts et al. 2018b; Solano Rodriguez et
6 al. 2017; Thepkhun et al. 2013; Vishwanathan et al. 2018b; Kato and Kurosawa 2019; van der Zwaan
7 et al. 2016). CCS helps reduce gross emissions but does not remove CO2 from the atmosphere, unless
8 combined with bioenergy (BECCS). CO2 removal from sources with no identified mitigation measures
9 is considered necessary to help achieve economy-wide net negative emissions (Deetman et al. 2013;
10 Massetti 2012; Solano Rodriguez et al. 2017).
11 Each option is assessed in more detail in the following sections.
12 4.2.5.2 Accelerated decarbonisation of electricity through renewable energy
13 Power generation could decarbonise much faster with scaled up deployment of renewable energy and
14 storage. Both technologies are mature, available, and fast decreasing in costs, more than for many other
15 mitigation options. Models continuously underestimate the speed at which renewables and storage
16 expand. Higher penetration of renewable energy in the power sector is a common theme in scenarios.
17 Some studies provide cost optimal electricity mix under emission constraints, while others explicitly
18 explore a 100% renewables or 100% emission free electricity sector (Box 4.3).
19 Figure 4.3 shows an increasing share of renewable electricity in most countries historically, with further
20 increases projected in many decarbonisation pathways. Targets for very high shares of renewable
21 electricity generation—up to 100%—are shown for a number of countries, with the global share
22 projected to range from 60% to 70% for 1.5°C with no overshoot (C0) to below 2°C (C4) scenarios.
23 Countries and States that have set 100% renewables targets include Scotland for 2020 (Scottish
24 Government 2021), Austria (2030), Denmark (2035) and California (2045) (Figure 4.3).
25 While 100% renewable electricity generation by 2050 is found to be feasible, it is not without issues.
26 For example, (Jacobson et al. 2017, 2019) find it feasible for 143 countries with only a 9% average
27 increase in economic costs (considering all social costs) if annual electricity demand can be reduced by
28 57%. Others state that challenges exist with speed of expansion, ensuring sufficient supply at all times
29 or higher costs compared to other alternatives (Clack et al. 2017). In-depth discussion of net zero
30 electricity systems can be found in section 6.6.
31
32 START BOX 4.3 HERE
33
34 Box 4.3. Examples of high-renewable accelerated mitigation pathways
35 Many accelerated mitigation pathways include high shares of renewable energy, with national
36 variations. In Europe, some argue that the EU 2050 net zero GHG emissions goal can be met with 100%
37 renewable power generation, including use of renewable electricity to produce hydrogen, biofuels
38 (including imports), and synthetic hydrocarbons, but will require significant increases in transmission
39 capacity (Duscha et al. 2019; Zappa et al. 2019). Capros et al. (2019) explore a 1.5°C compatible
40 pathway that includes 85% renewable generation, with battery, pumped hydro, and chemical storage
41 for variable renewables. High-renewable scenarios also exist for individual Member States. In France,
42 for example, Krakowski et al. (2016) propose a 100% renewable power generation scenario that relies
43 primarily on wind (62%), solar PV (26%) and oceans (12%). To reach this aim, integration into the
44 European grid is of vital importance (Brown et al. 2018). While debated, incremental costs could be
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1 limited regardless of specific assumptions of future costs of individual technologies (Shirizadeh et al.
2 2020). In Germany, similarly, 100% renewable electricity systems are found feasible by numerous
3 studies (Oei et al. 2020; Thomas Klaus et al. 2020; Wuppertal-Institut 2021; Hansen et al. 2019).
4 In South Africa, it is found that long-term mitigation goals could be achieved with accelerated adoption
5 of solar PV and wind generation, if the electricity sector decarbonises by phasing-out coal entirely by
6 2050, even if CCS is not feasible before 2025 (Altieri et al. 2015; Beck et al. 2013). Abundant solar PV
7 and wind potential, coupled with land availability suggest that more than 75% of power generation
8 could ultimately originate from solar PV and wind (Oyewo et al. 2019; Wright et al. 2019).
9 For the US, share of renewables in power generation in 2050 in accelerated mitigation scenarios vary
10 widely, 40% in (Hodson et al. 2018; Jayadev et al. 2020), more than half renewable and nuclear in
11 (Victor et al. 2018) to 100% in (Jacobson et al. 2017, 2019).
12 Under cost optimisation scenarios for Brazil, electricity generation, which is currently dominated by
13 hydropower, could reach 100% by adding biomass (Köberle et al. 2020). Other studies find that
14 renewable energy, including biomass, could account for more than 30% of total electricity generation
15 (Portugal-Pereira et al. 2016; Nogueira de Oliveira et al. 2016).
16 In Colombia, where hydropower resources are abundant and potential also exist for solar and wind, a
17 deep decarbonisation pathway would require 57% renewable power generation by 2050 (Arango-
18 Aramburo et al. 2019) while others find 80% would be possible (Delgado et al. 2020).
19 In Asia, Japan sees could have up to 50% variable renewable electricity supply to reduce CO2 emissions
20 by 80% by 2050 in some of its deep mitigation scenarios (Shiraki et al. 2021; Ju et al. 2021; Silva
21 Herran and Fujimori 2021; Kato and Kurosawa 2019; Sugiyama et al. 2019). One view of China’s 1.5°C
22 pathway includes 59% renewable power generation by 2050 (Jiang et al. 2018). One view of India’s
23 1.5°C pathway also includes 52% renewable power generation, and would require storage needs for
24 35% of generation (Parikh et al. 2018).
25 END BOX 4.3 HERE
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1
2 Figure 4.3 Historical and projected levels and targets for the share of renewables in electricity generation
3 Sources: IEA energy balances for past trends, IPCC AR6 scenario dataset including national model and regional versions in global models (10th to 90th percentile of 1.5 with
4 no overshoot (C0) to below 2°C (C4) scenarios), national / regional sources
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1 4.2.5.3 Bioenergy plays significant role in resource abundant countries in Latin America and parts
2 of Europe
3 Bioenergy could account for up to 40% of Brazil’s total final energy consumption, and a 60% share of
4 fuel for light-duty vehicles by 2030 (Lefèvre et al. 2018), and is considered most cost-effective in
5 transport and industrial applications (Lap et al. 2020). BECCS in the power sector is also considered
6 cost-effective option for supply-side mitigation (Herreras Martínez et al. 2015; Lucena et al. 2016;
7 Borba et al. 2012).
8 Bioenergy also plays a prominent role in some EU countries’ deep decarbonisation strategies. Domestic
9 biomass alone can help Germany meet its 95% CO2 reduction by 2050 goal, and biomass and CCS
10 together are needed to reduce CO2 by 80% by 2050 in the Netherlands (Mikova et al. 2019). Studies
11 suggest that mitigation efforts in France include biofuels and significant increases in biomass use,
12 including up to 45% of industry energy by 2050 for its net GHG neutrality goal (Doumax-Tagliavini
13 and Sarasa 2018; Capros et al. 2019). Increased imports may be needed to meet significant increases in
14 EU’s bioenergy use, which could affect energy security and the sustainability of bioenergy production
15 outside of the EU (Mandley et al. 2020; Daioglou et al. 2020).
16 While BECCS is needed in multiple accelerated mitigation pathways, large-scale land-based biological
17 CDR may not prove as effective as expected, and its large-scale deployment may result in ecological
18 and social impacts, suggesting it may not be a viable carbon removal strategy in the next 10-20 years
19 (Vaughan and Gough 2016; Boysen et al. 2017; Dooley and Kartha 2018). The effectiveness of BECCS
20 could depend on local contexts, choice of biomass, fate of initial aboveground biomass and fossil-fuel
21 emissions offsets—carbon removed through BECCS could be offset by losses due to land-use change
22 (Harper et al. 2018; Butnar et al. 2020; Calvin et al. 2021). Large-scale BECCS may push planetary
23 boundaries for freshwater use, exacerbate land-system change, significantly alter biosphere integrity
24 and biogeochemical flows (Heck et al. 2018; Stenzel et al. 2021; Fuhrman et al. 2020; Ai et al. 2021).
25 See 7.4 and 12.5 for further discussions.
26 4.2.5.4 CCS may be needed to mitigate emissions from the remaining fossil fuels that cannot be
27 decarbonised, but the economic feasibility of deployment is not yet clear
28 CCS is present in many accelerated mitigation scenarios in the literature. In Brazil, (Nogueira de
29 Oliveira et al. 2016) consider BECCS and CCS in hydrogen generation more feasible than CCS in
30 thermal power plants, with costs ranging from USD70-100/tCO2. Overall, (van der Zwaan et al. 2016)
31 estimate that 33-50% of total electricity generation in Latin America could be ultimately covered by
32 CCS. In Japan, CCS and increased bioenergy adoption plus waste-to-energy and hydrogen-reforming
33 from fossil fuel are all considered necessary in the power sector in existing studies, with potential up to
34 200 MtCO2 per year (Ashina et al. 2012; Oshiro et al. 2017a; Kato and Kurosawa 2019; Sugiyama et
35 al. 2021). In parts of the EU, after 2030, CCS could become profitable with rising CO2 prices (Schiffer
36 2015). CDR is seen as necessary in some net GHG neutrality pathways (Capros et al. 2019) but evidence
37 on cost-effectiveness is scarce and uncertain (European Commission 2013). For France and Sweden,
38 (Millot et al. 2020) include CCS and BECCS to meet net zero GHG emissions by 2050. For Italy,
39 (Massetti 2012) propose a zero-emission electricity scenario with a combination of renewable and coal,
40 natural gas, and BECCS.
41 In China, an analysis concluded that CCS is necessary for remaining coal and natural gas generation
42 out to 2050 (Jiang et al. 2018; Energy Transitions Commission and Rocky Mountain Institute 2019).
43 Seven to 10 CCS projects with installed capacity of 15 GW by 2020 and total CCS investment of 105
44 billion RMB (2010 RMB) are projected to be needed by 2050 under a 2°C compatible pathway
45 according to (Jiang et al. 2016, 2013; Lee et al. 2018). Under 1.5°C pathway, an analysis found China
46 would need full CCS coverage of the remaining 12% of power generation from coal and gas power and
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1 250 GW of BECCS (Jiang et al. 2018). Combined with expanded renewable and nuclear development,
2 total estimated investment in this study is 5% of China's total GDP in 2020, 1.3% in 2030, and 0.6% in
3 2050 (Jiang et al. 2016).
4 Views regarding feasibility of CCS can vary greatly for the same country. In the case of India’s
5 electricity sector for instance, some studies indicate that CCS would be necessary (Vishwanathan et al.
6 2018a), while others do not—citing concerns around its feasibility due to limited potential sites and
7 issues related to socio-political acceptance—, and rather point to very ambitious increase in renewable
8 energy, which in turn could pose significant challenges in systematically integrating renewable energy
9 into the current energy systems (Viebahn et al. 2014; Mathur and Shekhar 2020). Some limitations of
10 CCS, including uncertain costs, lifecycle and net emissions, other biophysical resource needs, and social
11 acceptance are acknowledged in existing studies (Sekera and Lichtenberger 2020; Jacobson
12 2019;Viebahn et al. 2014; Mathur and Shekhar 2020)
13 While national mitigation portfolios aiming at net zero emissions or lower will need to include some
14 level of CDR, the choice of methods and the scale and timing of their deployment will depend on the
15 ambition for gross emission reductions, how sustainability and feasibility constraints are managed, and
16 how political preferences and social acceptability evolve (Cross-Chapter Box 8). Furthermore,
17 mitigation deterrence may create further uncertainty, as anticipated future CDR could dilute incentives
18 to reduce emissions now (Grant et al. 2021), and the political economy of net negative emissions has
19 implications for equity (Mohan et al. 2021).
20 4.2.5.5 Nuclear power is considered strategic for some countries, while others plan to reach their
21 mitigation targets without additional nuclear power
22 Nuclear power generation is developed in many countries, though larger-scale national nuclear
23 generation does not tend to associate with significantly lower carbon emissions (Sovacool et al. 2020).
24 Unlike other energy sources such as wind and PV solar, levelized costs of nuclear power has been rising
25 in the last decades (Portugal-Pereira et al. 2018; Gilbert et al. 2017; Grubler 2010). This is mainly due
26 to overrun of overnight construction costs related to delays in project approvals and construction, and
27 more stringent passive safety measures, which increases the complexity of systems. After the
28 Fukushima Dai-Ichi accident in Japan, nuclear programs in several countries have been phased out or
29 cancelled (Carrara 2020; Huenteler et al. 2012; Kharecha and Sato 2019; Hoffman and Durlak 2018).
30 Also the compatibility of conventional PWR and BWR reactors with large proportion of renewable
31 energy in the grid it is yet to be fully understood.
32 Accelerated mitigation scenarios offer contrasting views on the share of nuclear in power generation.
33 In the US, (Victor et al. 2018) build a scenario in which nuclear contributes 23% of CO2 emission
34 reductions needed to reduce GHG emissions by 80% from 2005 levels by 2050. Deep power sector
35 decarbonisation pathways could require a two-folded increase in nuclear capacity according to (Jayadev
36 et al. 2020) for the U.S., and nearly a ten-fold increase for Canada, but may be difficult to implement
37 (Vaillancourt et al. 2017). For China to meet a 1.5°C pathway or achieve carbon neutrality by 2050,
38 nuclear may represent 14%-28% of power generation in 2050 according to (Jiang et al. 2018; China
39 National Renewable Energy Centre 2019; Energy Transitions Commission and Rocky Mountain
40 Institute 2019). For South Korea, (Hong et al. 2014; Hong and Brook 2018) find that increasing nuclear
41 power can help complement renewables in decarbonizing the grid. Similarly, India has put in place a 3-
42 stage nuclear programme which aims to enhance nuclear power capacity from the current level of 6
43 GW to 63 GW by 2032, if fuel supply is ensured (GoI 2015). Nuclear energy is also considered
44 necessary as part of accelerated mitigation pathways in Brazil, although it is not expected to increase
45 significantly by 2050 even under stringent low carbon scenarios (Lucena et al. 2016). France developed
46 its nuclear strategy in response to energy security concerns after the 1970s Oil Crisis, but has committed
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1 to reducing nuclear’s share of power generation to 50% by 2035 (Millot et al. 2020). Conversely, some
2 analysis find deep mitigation pathways, including net zero GHG emissions and 80-90% reduction from
3 2013 levels, feasible without additional nuclear power in EU-28 and Japan respectively, but assuming
4 a combination of bio- and novel fuels and CCS or land-use based carbon sinks (Kato and Kurosawa
5 2019; Duscha et al. 2019).
6 Radically more efficient use of energy than today, including electricity, is a complementary set of
7 measures, explored in the following.
8 4.2.5.6 Efficient cooling, SLCFs and co-benefits
9 In warmer climate regions undergoing economic transitions, improving the energy efficiency of cooling
10 and refrigeration equipment is often important for managing peak electricity demand and can have co-
11 benefits for climate mitigation as well as SLCF reduction, as expected in India, Africa, and Southeast
12 Asia in the future.
13 Air conditioner adoption is rising significantly in low- and middle-income countries as incomes rise
14 and average temperatures increase, including in Southeast Asian countries such as Thailand, Indonesia,
15 Vietnam, and the Philippines, as well as Brazil, Pakistan, Bangladesh, and Nigeria (Biardeau et al.
16 2020). Cooling appliances are expected to increase from 3.6 billion to 9.5 billion by 2050, though up to
17 14 billion could be required to provide adequate cooling for all (Birmingham Energy Institute 2018).
18 Current technology pathways are not sufficient to deliver universal access to cooling or meet the 2030
19 targets under the SDGs, but energy efficiency, including in equipment efficiency like air conditioners,
20 can reduce this demand and help limit additional emissions that would further exacerbate climate
21 change (UNEP and IEA 2020; Dreyfus et al. 2020; Biardeau et al. 2020). Some countries (India, South
22 Africa) have started to recognise the need for more efficient equipment in their mitigation strategies
23 (Paladugula et al. 2018; Altieri et al. 2016; Ouedraogo 2017).
24 One possible synergy between SLCF and climate change mitigation is the simultaneous improvement
25 in energy efficiency in refrigeration and air-conditioning equipment during the hydrofluorocarbon
26 (HFC) phase-down, as recognised in the Kigali Amendment to the Montreal Protocol. The Kigali
27 Amendment and related national and regional regulations are projected to reduce future radiative
28 forcing from HFCs by about half in 2050 compared to a scenario without any HFC controls, and to
29 reduce future global average warming in 2100 from a baseline of 0.3-0.5°C to less than 0.1°C, according
30 to a recent scientific assessment of a wide literature (World Meteorological Organization 2018). If
31 ratified by signatories, the rapid phase-down of HFCs under the Kigali Amendment is possible because
32 of extensive replacement of high-global warming potential (GWP) HFCs with commercially available
33 low-GWP alternatives in refrigeration and air-conditioning equipment. Each country’s choices of
34 alternative refrigerants will likely be determined by energy efficiency, costs, and refrigerant toxicity
35 and flammability. National and regional regulations will be needed to drive technological innovation
36 and development (Polonara et al. 2017).
37 4.2.5.7 Efficient buildings, cooler in summer, warmer in winter, towards net zero energy
38 Most accelerated mitigation pathway scenarios include significant increase in building energy
39 efficiency. Countries in cold regions, in particular, often focus more on building sector GHG emissions
40 mitigation measures such as improving building envelopes and home appliances, and electrifying space
41 heating and water heating.
42 For example, scenarios for Japan project continued electrification of residential and commercial
43 buildings to 65% and 79% respectively by 2050 to reach 70-90% CO2 reduction from 2013 levels (Kato
44 and Kurosawa 2019). Similarly, a mitigation pathway for China compatible with 1.5°C would require
45 58% to 70% electrification of buildings according to (Jiang et al. 2018; Energy Transitions Commission
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1 and Rocky Mountain Institute 2019; China National Renewable Energy Centre 2019). For the EU-28
2 to reach net carbon neutrality, complete substitution of fossil fuels with electricity (up to 65% share),
3 district heating, and direct use of solar and ambient heat are projected to be needed for buildings, along
4 with increased use of solar thermal and heat pumps for heating (Duscha et al. 2019). In the UK and
5 Canada, improved insulation to reduce energy demand and efficient building appliances and heating
6 systems are important building strategies needed to reduce emissions to zero by 2050 (Roberts et al.
7 2018a; Vaillancourt et al. 2017; Chilvers et al. 2017). In Ireland, achieving 80%-95% emissions
8 reduction below 1990 levels by 2050 also requires changes in building energy technology and
9 efficiency, including improving building envelopes, fuel switching for residential buildings, and
10 replacing service-sector coal use with gas and renewables according to (Chiodi et al. 2013). In South
11 Africa, improving industry and building energy efficiency is also considered a key part of mitigation
12 strategies (Ouedraogo 2017; Altieri et al. 2016).
13 In addition, an increasing number of countries have set up Net Zero Energy Building targets (Table 4.8)
14 (Höhne et al. 2020). Twenty seven countries have developed roadmap documents for NZEBs, mostly
15 in developed countries in Europe, North America, and Asia-Pacific, focusing on energy efficiency and
16 improved insulation and design, renewable and smart technologies (Mata et al. 2020). The EU, Japan
17 and the U.S. (the latter for public buildings only) have set targets for shifting new buildings to 100%
18 near-zero energy buildings by 2030, with earlier targets for public buildings. Scotland has a similar
19 target for 2050 (Höhne et al. 2020). Technologies identified as needed for achieving near-zero energy
20 buildings vary by region, but include energy-efficient envelope components, natural ventilation, passive
21 cooling and heating, high performance building systems, air heat recovery, smart and information and
22 communication technologies, and changing future heating and cooling supply fuel mixes towards solar,
23 geothermal, and biomass (Mata et al. 2020). Subnational regions in Spain, U.S., Germany, and Mexico
24 have set local commitments to achieving net zero carbon new buildings by 2050, with California having
25 the most ambitious aspirational target of zero net energy buildings for all new buildings by 2030 (Höhne
26 et al. 2020). The EU is also targeting the retrofitting of 3% of existing public buildings to zero-energy,
27 with emphasis on greater thermal insulation of building envelopes (Mata et al. 2020; Höhne et al. 2020).
28 China’s roadmaps have emphasised insulation of building envelope, heat recovery systems in
29 combination with renewable energy, including solar, shallow geothermal, and air source heat pumps
30 (Mata et al. 2020).
31
32 Table 4.8 Targets by countries, regions, cities and businesses on decarbonising the building sector
Countries Subnational Cities Businesses
Regions
Shift to 100 per cent (near-) zero energy buildings for 3 6 >28 >44
new buildings
Fully decarbonise the building sector 1 6 >28 >44
Phase out fossil fuels (for example, gas) for residential 1 - >3
heating
Increase the rate of zero-energy renovations 1 (public
buildings)
33 Source: (Höhne et al. 2020) (supplementary information). See also https://newclimate.org/ambitiousactions
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1 4.2.5.8 Electrifying transport
2 Electrification of transport in tandem with power sector decarbonisation is expected to be a key strategy
3 for deep CO2 mitigation in many countries. Passenger transport and light duty freight can already be
4 electrified, but electrifying heavy-duty road transport and fuel switching in aviation and shipping are
5 much more difficult and have not been addressed in most of the recent research.
6 In Germany, widespread electrification of private vehicles is expected by 2030 (Schmid and Knopf
7 2012) while for the EU-28, 50% overall transport electrification (excluding feedstock) and 75%
8 electrification of road transport is needed to reach net carbon neutrality according to (Duscha et al.
9 2019). In addition, novel fuels such as hydrogen, synthetic hydrocarbons and sustainable biogenic fuels
10 are needed to decarbonise aviation and water transport to achieve net carbon neutrality (Duscha et al.
11 2019).
12 In India, electrification, hydrogen, and biofuels are key to decarbonising the transport sector (Dhar et
13 al. 2018; Mittal et al. 2018; Vishwanathan et al. 2018b; Mathur and Shekhar 2020). Under a 1.5°C
14 scenario, nearly half of the light-duty passenger vehicle stock needs to be electrified according to
15 (Parikh et al. 2018). In China, a 1.5°C-compatible pathway would requires electrification of 2/5th of
16 transport (Jiang et al. 2018; China National Renewable Energy Centre 2019).
17 Similarly, in Canada, electrification of 59% of light-duty trucks and 23% of heavy-duty trucks are
18 needed as part of overall strategy to reduce CO2 emissions by 80% by 2050. In addition, hydrogen is
19 expected to play a major role by accounting for nearly one-third of light-duty trucks, 68% of heavy-
20 duty trucks, and 33% of rail by 2050 according to Hammond et al. (2020).
21 4.2.5.9 Urban form meets information technology
22 Beyond technological measures, some densely populated countries including Germany, Japan, and
23 India are exploring using information technology/internet-of-things (IOT) to support mode-shifting and
24 reduce mobility demand through broader behaviour and lifestyle changes (Aggarwal 2017; Ashina et
25 al. 2012; Canzler and Wittowsky 2016; Dhar et al. 2018; Vishwanathan et al. 2018b). In Japan,
26 accelerated mitigation pathways consider the use of information technology and IOT to transform
27 human behaviour and transition to a sharing economy (Ashina et al. 2012; Oshiro et al. 2017a, 2018).
28 In Germany, one study points to including electromobility information and communication technologies
29 in the transport sector as key (Canzler and Wittowsky 2016) while another emphasise shifting from
30 road to rail transport, and reduced distances travelled as other possible transport strategies (Schmid and
31 Knopf 2012). India’s transport sector strategies also include use of information technology and the
32 internet, a transition to a sharing economy, and increasing infrastructure investment (Dhar et al. 2018;
33 Vishwanathan et al. 2018b). Behaviour and lifestyle change along with stakeholder integration in
34 decision-making are considered key to implementing new transport policies (Aggarwal 2017; Dhar et
35 al. 2018).
36 4.2.5.10 Industrial energy efficiency
37 Industrial energy efficiency improvements are considered in nearly all countries but for countries where
38 industry is expected to continue to be a key sector, new and emerging technologies that require
39 significant R&D investment, such as hydrogen and CCS, make ambitious targets achievable.
40 In China, for example, non-conventional electrical and renewable technologies, including low-grade
41 renewable heat, biomass use for high-temperature heat in steel and cement sectors, and additional
42 electrification in glass, food and beverage, and paper and pulp industries, are part of scenarios that
43 achieve 60% reduction in national CO2 emission by 2050 (Khanna et al. 2019; Zhou et al. 2019), in
44 addition to increased recycled steel for electric arc furnaces and direct electrolysis or hydrogen-based
45 direct reduction of iron and CCS utilisation in clinker and steel-making (China National Renewable
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1 Energy Centre 2019; Jiang et al. 2018). Similarly, in India, (Vishwanathan and Garg 2020) point to the
2 need for renewable energy and CCS to decarbonize the industrial sector. In EU-28, net CO2 neutrality
3 can only be reached with 92% reduction in industrial emissions relative to 1990, through electrification,
4 efficiency improvement and new technologies such as hydrogen-based direct reduction of steel, low
5 carbon cement, recycling (Duscha et al. 2019). Both China and EU see 50% of industry electrification
6 by 2050 as needed to meet 1.5°C and net carbon neutrality pathways (Jiang et al. 2018; Capros et al.
7 2019).
8 Aggressive adoption of technology solutions for power sector decarbonisation coupled with end-use
9 efficiency improvements and low-carbon electrification of buildings, industry and transport provides a
10 pathway for accelerated mitigation in many key countries, but will still be insufficient to meet zero
11 emission/1.5°C goals for all countries. Although not included in a majority of the studies related to
12 pathways and national modelling analysis, energy demand reduction through deeper efficiency and
13 other measures such as lifestyle changes and system solutions that go beyond components, as well as
14 the co-benefits of the reduction of short-lived pollutants, needs to be evaluated for inclusion in future
15 zero emission/1.5°C pathways.
16 4.2.5.11 Lowering demand, downscaling economies
17 Studies have identified socio-technological pathways to help achieve net zero CO2 and GHG targets at
18 national scale, that in aggregate are crucial to keeping global temperature below agreed limits. However,
19 most of the literature focuses on supply-side options, including carbon dioxide removal mechanisms
20 (BECCS, afforestation, and others) that are not fully commercialised (Cross-Chapter Box 8). Costs to
21 research, deploy, and scale up these technologies are often high. Recent studies have addressed lowering
22 demand through energy conversion efficiency improvements, but few studies have considered demand
23 reduction through efficiency (Grubler et al. 2018) and the related supply implications and mitigation
24 measures.
25 Five main drivers of long-term energy demand reduction that can meet the 1.5˚C target include quality
26 of life, urbanisation, novel energy services, diversification of end-user roles, and information innovation
27 (Grubler et al. 2018). A low-energy-demand scenario requires fundamental societal and institutional
28 transformation from current patterns of consumption, including: decentralised services and increased
29 granularity (small-scale, low-cost technologies to provide decentralised services), increased use value
30 from services (multi-use vs. single use), sharing economies, digitalisation, and rapid transformation
31 driven by end-user demand. This approach to transformation differs from the status quo and current
32 climate change policies in emphasising energy end-use and services first, with downstream effects
33 driving intermediate and upstream structural change.
34 Radical low carbon innovation involves systemic, cultural, and policy changes and acceptance of
35 uncertainty in the beginning stages. However, the current dominant analytical perspectives are grounded
36 in neoclassical economics and social psychology, and focus primarily on marginal changes rather than
37 radical transformations (Geels et al. 2018). Some literature is beginning to focus on mitigation through
38 behaviour and lifestyle changes, but specific policy measures for supporting such changes and their
39 contribution to emission reductions remain unclear (see also Section 4.4.2 and Chapter 5).
40 4.2.5.12 Ambitious targets to reduce short-lived climate forcers, including methane
41 Recent research shows that temperature increases are likely to exceed 1.5°C during the 2030s and 2°C
42 by mid-century unless both CO2 and short-lived climate forcers (SLCFs) are reduced (Shindell et al.
43 2017; Rogelj et al. 2018a). Because of their short lifetimes (days to a decade and a half), SLCFs can
44 provide fast mitigation, potentially avoiding warming of up to 0.6 ºC at 2050 and up to 1.2 ºC at 2100
45 (Ramanathan and Xu 2010; Xu and Ramanathan 2017). In Asia especially, co-benefits of drastic CO2
46 and air pollution mitigation measures reduce emissions of methane, black carbon, sulphur dioxide,
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1 nitrogen oxide, and fine particulate matter by approximately 23%, 63%, 73%, 27%, and 65%
2 respectively in 2050 as compared to 2010 levels. Including the co-benefits of reduction of climate
3 forcing adds significantly to the benefits reducing air pollutants (Hanaoka and Masui 2018).
4 To achieve net zero GHG emissions implies consideration of targets for non-CO2 gases. While methane
5 emissions have grown less rapidly than CO2 and F-gases since 1990 (Chapter 2), the literature urges
6 action to bring methane back to a pathway more in line with the Paris goals (Nisbet et al. 2020).
7 Measures to reduce methane emissions from anthropogenic sources are considered intractable – where
8 they sustain livelihoods – but also becoming more feasible, as studies report the options for mitigation
9 in agriculture without undermining food security (Wollenberg et al. 2016; Frank et al. 2017; Nisbet et
10 al. 2020). The choice of emission metrics has implications for SLCF (Cain et al. 2019)(Cross-Chapter
11 Box 2). Ambitious reductions of methane are complementary to, rather than substitutes for, reductions
12 in CO2 (Nisbet et al. 2020).
13 Rapid SLCF reductions, specifically of methane, black carbon, and tropospheric ozone have immediate
14 co-benefits including meeting sustainable development goals for reducing health burdens of household
15 air pollution and reversing health- and crop-damaging tropospheric ozone (Jacobson 2002, 2010). SLCF
16 mitigation measures can have regional impacts, including avoiding premature deaths in Asia and Africa
17 and warming in central and Northern Asia, southern Africa, and the Mediterranean (Shindell et al.
18 2012). Reducing outdoor air pollution could avoid 2.4 million premature deaths and 52 million tonnes
19 of crop losses for four major staples (Haines et al. 2017). Existing research emphasises climate and
20 agriculture benefits of methane mitigation measures with relatively small human health benefits
21 (Shindell et al. 2012). Research also predicts that black carbon mitigation could substantially benefit
22 global climate and human health, but there is more uncertainty about these outcomes than about some
23 other predictions (Shindell et al. 2012). Other benefits to SLCF reduction include reducing warming in
24 the critical near-term, which will slow amplifying feedbacks, reduce the risk of non-linear changes, and
25 reduce long-term cumulative climate impacts—like sea-level rise—and mitigation costs (Hu et al. 2017;
26 UNEP and WMO 2011; Rogelj et al. 2018a; Xu and Ramanathan 2017; Shindell et al. 2012).
27 4.2.5.13 System analysis solutions are only beginning to be recognised in current literature on
28 accelerated mitigation pathways, and rarely included in existing national policies or
29 strategies
30 Most models and studies fail to address system impacts of widespread new technology deployment, for
31 example: 1) material and resources needed for hydrogen production or additional emissions and energy
32 required to transport hydrogen; or 2) materials, resources, grid integration, and generation capacity
33 expansion limits of a largely decarbonised power sector and electrified transport sector. These impacts
34 could limit regional and national scale-ups.
35 Systemic solutions are also not being sufficiently discussed, such as low-carbon materials; light-
36 weighting of buildings, transport, and industrial equipment; promoting circular economy, recyclability
37 and reusability, and addressing the food-energy-water nexus. These solutions reduce demand in
38 multiple sectors, improve overall supply chain efficiency, and require cross-sector policies. Using fewer
39 building materials could reduce the need for cement, steel, and other materials and thus the need for
40 production and freight transport. Concrete can also be produced from low carbon cement, or designed
41 to absorb CO2 from the atmosphere. Few regions have developed comprehensive policies or strategies
42 for a circular economy, with the exception of the EU and China, and policies in the EU have only
43 emerged within the last decade. While China’s circular economy policies emphasises industrial
44 production, water, pollution and scaling-up in response to rapid economic growth and industrialisation,
45 EU’s strategy is focused more narrowly on waste and resources and overall resource efficiency to
46 increase economic competitiveness (McDowall et al. 2017).
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1 Increased bioenergy consumption is considered in many 1.5˚C and 2˚C scenarios. System thinking is
2 needed to evaluate bioenergy’s viability because increased demand could affect land and water
3 availability, food prices, and trade (Sharmina et al. 2016). To adequately address the energy-water-food
4 nexus, policies and models must consider interconnections, synergies, and trade-offs among and within
5 sectors, which is currently not the norm (see 12.4).
6 A systems approach is also needed to support technological innovation. This includes recognising
7 unintended consequences of political support mechanisms for technology adoption and restructuring
8 current incentives to realise multi-sector benefits. It also entails assimilating knowledge from multiple
9 sources as a basis for policy and decision-making (Hoolohan et al. 2019).
10 Current literature does not explicitly consider systematic, physical drivers of inertia, such as capital and
11 infrastructure needed to support accelerated mitigation (Pfeiffer et al. 2018). This makes it difficult to
12 understand what is needed to successfully shift from current limited mitigation actions to significant
13 transformations needed to rapidly achieve deep mitigation.
14
15 4.2.6 Implications of accelerated mitigation for national development objectives
16 4.2.6.1 Introduction
17 This section examines how accelerated mitigation may impact the realisation of development objectives
18 in the near- and mid-term. It focuses on three objectives discussed in the literature, sustaining economic
19 growth (4.2.6.2), providing employment (4.2.6.3), and alleviating poverty and ensuring equity (4.2.6.4).
20 It complements similar review performed at global level in section 3.6. For a comprehensive survey of
21 research on the impact of mitigation in other areas (including air quality, health, and biodiversity), see
22 Karlsson et al. (2020).
23 4.2.6.2 Mitigation and economic growth in the near- and mid-term
24 A significant part of the literature assesses the impacts of mitigation on GDP, consistent with
25 policymakers’ interest in this variable. It must be noted upfront that computable equilibrium models,
26 on which our assessments are mostly based, capture the impact of mitigation on GDP and other core
27 economic variables while typically overlooking other effects that may matter (like improvements in air
28 quality). Second, even though GDP (or better, GDP per capita) is not an indicator of welfare (Fleurbaey
29 and Blanchet 2013), changes in GDP per capita across countries and over time are highly correlated
30 with changes in welfare indicators in the areas of poverty, health, and education (Gable et al. 2015).
31 The mechanisms linking mitigation to GDP outlined below would remain valid even with alternative
32 indicators of well-being (5.2.1). Third, another stream of literature criticises the pursuit of economic
33 growth as a goal, instead advocating a range of alternatives and suggesting modelling of post-growth
34 approaches to achieve rapid mitigation while improving social outcomes (Hickel et al. 2021). In the
35 language of the present chapter, these alternatives constitute alternative development pathways.
36 Most country-level mitigation modelling studies in which GDP is an endogenous variable report
37 negative impacts of mitigation on GDP in 2030 and 2050, relative to the reference (robust evidence,
38 high agreement), for example (Nong et al. 2017) for Australia, (Chen et al. 2013) for Brazil, (Mu et al.
39 2018a; Cui et al. 2019; Zhao et al. 2018; Li et al. 2017; Dong et al. 2018; Dai et al. 2016) for China,
40 (Álvarez-Espinosa et al. 2018) for Colombia, (Fragkos et al. 2017) for the EU, (Mittal et al. 2018) for
41 India, (Fujimori et al. 2019) for Japan, (Veysey et al. 2014) for Mexico, (Pereira et al. 2016) for
42 Portugal, (Alton et al. 2014; van Heerden et al. 2016) for South Africa, (Chunark et al. 2017) for
43 Thailand, (Acar and Yeldan 2016) for Turkey, (Roberts et al. 2018b) for the UK, (Chen and Hafstead
44 2019; Zhang et al. 2017) for the USA, (Nong 2018) for Vietnam) (Figure 4.4). The downward
45 relationship between mitigation effort and emissions is strong in studies up to 2030, much weaker for
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1 studies looking farther ahead. In all reviewed studies, however, GDP continues to grow even with
2 mitigation. It may be noted that none of the studies assessed above integrates the benefits of mitigation
3 in terms of reduced impacts of climate change or lower adaptation costs. This is not surprising since
4 these studies are at national or regional scale and do not extend beyond 2050, whereas the benefits
5 depend on global emissions and primarily occur after 2050. Discussion on reduced impacts is provided
6 in section 3.6.2 and Cross-Working Group Box 1.
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1
2 Figure 4.4 GDP against emissions in country-level modelling studies, in variations relative to reference
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1 Two major mechanisms interplay to explain the impact of mitigation on GDP. First, the carbon
2 constraint imposes reduced use of a production factor (fossil energy), thus reducing GDP. In the
3 simulations, the mechanism at work is that firms and households reduce their use of GHG-intensive
4 goods and services in response to higher prices due to reduced fossil energy use. Second, additional
5 investment required for mitigation partially crowds out productive investment elsewhere (Fujimori et
6 al. 2019), except in Keynesian models in which increased public investment actually boosts GDP
7 (Pollitt et al. 2015; Bulavskaya and Reynès 2018; Landa Rivera et al. 2016). Magnitude and duration
8 of GDP loss depend on the stringency of the carbon constraint, the degree of substitutability with less-
9 GHG-intensive goods and services, assumptions about costs of low-carbon technologies and their
10 evolution over time (e.g., (Duan et al. 2018; van Meijl et al. 2018; Cui et al. 2019) and decisions by
11 trading partners, which influence competitiveness impacts for firms (Alton et al. 2014; Fragkos et al.
12 2017) (high evidence, high agreement).
13 In the near-term, presence of long-lived emissions intensive capital stock, and rigidities in the labour
14 market (Devarajan et al. 2011) and other areas may increase impacts of mitigation on GDP. In the mid-
15 term, on the other hand, physical and human capital, technology, institutions, skills or location of
16 households and activities are more flexible. The development of renewable energy may help create
17 more employment and demands for new skills, particularly in the high-skill labour market (Hartley et
18 al. 2019). In addition, cumulative mechanisms such as induced technical change or learning by doing
19 on low-emissions technologies and process may reduce the impacts of mitigation on GDP.
20
21 Table 4.9 Examples of country-level modelling studies finding positive short-term outcome of mitigation
22 on GDP relative to baseline
Reference Country/region Explanation for positive outcome of mitigation on GDP
(Antimiani et al. 2016) European Union GDP increases relative to reference only in the scenario
with global cooperation on mitigation
(Willenbockel et al. 2017) Kenya The mitigation scenario introduces cheaper (geothermal)
power generation units than in BAU (in which thermal
increases). Electricity prices actually decrease.
(Siagian et al. 2017) Indonesia Coal sector with low productivity is forced into BAU.
Mitigation redirects investment towards sectors with higher
productivity.
(Blazquez et al. 2017) Saudi Arabia Renewable energy penetration assumed to free oil that
would have been sold at publicly subsidised price on the
domestic market to be sold internationally at market price
(Wei et al. 2019) China Analyse impacts of feed-in tariffs to renewables, find
positive short-run impacts on GDP; public spending boost
activity in the RE sector. New capital being built at faster
rate than in reference increases activity more than activity
decreases due to lower public spending elsewhere.
(Gupta et al. 2019) India Savings adjust to investment and fixed unemployment is
considered target of public policy, thereby limiting impact
of mitigation on GDP relative to other economic variables
(consumption, terms of trade).
(Huang et al. 2019) China Power generation plan in the baseline is assumed not cost
minimising
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1 Country-level studies find that the negative impacts of mitigation on GDP can be reduced if pre-existing
2 economic or institutional obstacles are removed in complement to the imposition of the carbon
3 constraint (robust evidence, high agreement). For example, if the carbon constraint takes the form of a
4 carbon tax or of permits that are auctioned, the way the proceeds from the tax (or the revenues from the
5 sales of permits) are used is critical for the overall macroeconomic impacts (Chen et al. 2013). (For a
6 detailed discussion of different carbon pricing instruments, including the auctioning of permits, see
7 Section 13.6.3).
8 Figure 4.5 shows that depending on the choice of how to implement a carbon constraint, the same level
9 of carbon constraint can yield very different outcomes for GDP. The potential for mitigating GDP
10 implications of mitigation through fiscal reform is discussed in 4.4.1.8.
11 More generally, mitigation costs can be reduced by proper policy design if the economy initially is not
12 on the efficiency frontier (Grubb 2014), defined as the set of configurations within which the quality of
13 the environment and economic activity cannot be simultaneously improved given current technologies
14 – such improvements in policy design may include reductions in distortionary taxes. Most of the studies
15 which find that GDP increases with mitigation in the near-term precisely assume that the economy is
16 initially not on the frontier. Making the economy more efficient—i.e., lifting the constraints that
17 maintain the economy in an interior position—creates opportunities to simultaneously improve
18 economic activity and reduce emissions. Table 4.9 describes the underlying assumptions in a selection
19 of studies.
20
21
22 Figure 4.5 Illustrative ranges of variations in GDP relative to reference in 2030 associated with
23 introduction of carbon constraint, depending on modality of policy implementation
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1 Based on (Alton et al. 2014; Devarajan et al. 2011; Fernandez and Daigneault 2018; Glomsrød et al. 2016; Nong
2 2018; Asakawa et al. 2021). Stringency of carbon constraint is not comparable across the studies.
3 Finally, marginal costs of mitigation are not always reported in studies of national mitigation pathways.
4 Comparing numbers across countries is not straightforward due to exchange rate fluctuations, differing
5 assumptions by modellers in individual country studies, etc. The database of national mitigation
6 pathways assembled for this Report—which covers only a fraction of available national mitigation
7 studies in the literature—shows that marginal costs of mitigation are positive, with a median value of
8 101 USD2010/tCO2 in 2030, 244 in 2040 and 733 in 2050 for median mitigation efforts of 21%, 46%
9 and 76% relative to business-as-usual respectively. Marginal costs increase over time along accelerated
10 mitigation pathways, as constraints become tighter, with a non-linearity as mitigation reaches 80% of
11 reference emissions or more. Dispersion across and within countries is high, even in the near-term but
12 increases notably in the mid-term (medium evidence, medium agreement).
13 4.2.6.3 Mitigation and employment in the short- and medium-term
14 Numerous studies have analysed the potential impact of carbon pricing on labour markets. Chateau et
15 al. (2018) and OECD (2017a) find that the implementation of green policies globally (defined broadly
16 as policies that internalise environmental externalities through taxes and other tools, shifting
17 profitability from polluting to green sectors) need not harm total employment, and that the broad skill
18 composition (low-, high- and medium-skilled jobs) of emerging and contracting sectors is very similar,
19 with the largest shares of job creation and destruction at the lowest skill level. To smoothen the labour
20 market transition, they conclude that it may be important to reduce labour taxes, to compensate
21 vulnerable households, and to provide education and training programs, the latter making it easier for
22 labour to move to new jobs. Consistent with this, other studies that simulate the impact of scenarios
23 with more or less ambitious mitigation policies (including 100% reliance on renewable energy by 2050)
24 find relatively small (positive or negative) impacts on aggregate global employment that are more
25 positive if labour taxes are reduced but encompass substantial losses for sectors and regions that today
26 are heavily dependent on fossil fuels (Arndt et al. 2013; Huang et al. 2019; Vandyck et al. 2016;
27 Jacobson et al. 2019). Among worker categories, low-skilled workers tend to suffer wage losses as they
28 are more likely to have to reallocate, something that can come at a cost in the form of a wage cut
29 (assuming that workers who relocate are initially less productive than those who already work in the
30 sector). The results for alternative carbon revenue recycling schemes point to trade-offs: a reduction in
31 labour taxes often leads to the most positive employment outcomes while lump-sum (uniform per-
32 capita) transfers to households irrespective of income yield a more egalitarian outcome.
33 The results from country-level studies using CGE models tend be similar to those at global level.
34 Aggregate employment impacts are small and may be positive especially if labour taxes are cut, see
35 e.g., (Telaye et al. 2019) for Ethiopia, (Kolsuz and Yeldan 2017) for Turkey, (Fragkos et al. 2017) for
36 the EU, (Mu et al. 2018b) for China. On the other hand, sectoral reallocations away from fossil-
37 dependent sectors may be substantial, see e.g., (Alton et al. 2014) for South Africa or (Huang et al.
38 2019) for China. Targeting of investment to labour-intensive green sectors may generate the strongest
39 employment gains, see, e.g., (Perrier and Quirion 2018) for France, (van Meijl et al. 2018) for the
40 Netherlands, (Patrizio et al. 2018) for the USA. Changes in skill requirements between emerging and
41 declining sectors appear to be quite similar, involving smaller transitions than during the IT revolution
42 (Bowen et al. 2018).
43 In sum, the literature suggests that the employment impact of mitigation policies tends to be limited on
44 aggregate, but can be significant at the sectoral level (medium evidence, medium agreement) and that
45 cutting labour taxes may limit adverse effects on employment (limited evidence, medium agreement).
46 Labour market impacts, including job losses in certain sectors, can be mitigated by equipping workers
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1 for job changes via education and training, and by reducing labour taxes to boost overall labour demand
2 (Stiglitz et al. 2017) (4.5).
3 Like most of the literature on climate change, the above studies do not address gender aspects. These
4 may be significant since the employment shares for men and women vary across sectors and countries.
5 4.2.6.4 Mitigation and equity in the near- and mid-term
6 Climate mitigation may exacerbate socio-economic pressures on poorer households (Jakob et al. 2014).
7 First, the price increase in energy-intensive goods and services—including food (Hasegawa et al.
8 2018)—associated with mitigation may affect poorer households disproportionally (Bento 2013), and
9 increase the number of energy-poor (Berry 2019). Second, the mitigation may disproportionally affect
10 low-skilled workers (see previous section). Distributional issues have been identified not only with
11 explicit price measures (carbon tax, emission permits system, subsidy removal), but also with subsidies
12 for renewables (Borenstein and Davis 2016), and efficiency and emissions standards (Davis and Knittel
13 2019; Bruegge et al. 2019; Levinson 2019; Fullerton and Muehlegger 2019).
14 Distributional implications, however, are context specific, depending on consumption patterns (initially
15 and ease of adjusting them in response to price changes) and asset ownership (see for example analysis
16 of energy prices in Indonesia by Renner et al. (2019)). In an analysis of the distributional impact of
17 carbon pricing based on household expenditure data for 87 low- and middle-income countries, Dorband
18 et al. (2019) find that, in countries with a per-capita income of up to USD15,000 per capita (PPP
19 adjusted), carbon pricing has a progressive impact on income distribution and that there may be an
20 inversely U-shaped relationship between energy expenditure shares and per-capita income, rendering
21 carbon pricing regressive in high-income countries, i.e., in countries where the capacity to pursue
22 compensatory policies tends to be relatively strong.
23 The literature finds that the detailed design of mitigation policies is critical for their distributional
24 impacts (robust evidence, high agreement). For example, Vogt-Schilb et al. (2019) suggest to turn to
25 cash transfer programs, established as some of the most efficient tools for poverty reduction in
26 developing countries. In an analysis of Latin America and the Caribbean, they find that allocation of 30
27 percent of carbon revenues would suffice to compensate poor and vulnerable households on average,
28 leaving the rest for other uses. This policy tool is not only available in countries with relatively high
29 per-capita incomes: in Sub-Saharan Africa, where per-capita incomes are relatively low, cash transfer
30 programs have been implemented in almost all countries ((Beegle et al. 2018), p. 57), and are found
31 central to the success of energy subsidy reforms (Rentschler and Bazilian 2017). In the same vein,
32 Böhringer et al. (2021) finds that recycling of revenues from emissions pricing in equal amounts to
33 every household appeals as an attractive strategy to mitigate regressive effects and thereby make
34 stringent climate policy more acceptable on societal fairness grounds. However, distributional gains
35 from such recycling may come at the opportunity cost of not reaping efficiency gains from reductions
36 in the taxes that are most distortionary (Goulder et al. 2019).
37 Distributional concerns related to climate mitigation are also prevalent in developed countries, as
38 demonstrated, for instance, by France’s recent yellow-vest movement, which was ignited by an increase
39 in carbon taxes. It exemplifies the fact that, when analysing the distributional effects of carbon pricing,
40 it is not sufficient to consider vertical redistribution (i.e., redistribution between households at different
41 incomes levels but also horizontal redistribution (i.e., redistribution between households at similar
42 incomes which is due to differences in terms of spending shares and elasticities for fuel consumption).
43 Compared to vertical redistribution, it is more difficult to devise policies that effectively address
44 horizontal redistribution (Douenne 2020; Cronin et al. 2019; Pizer and Sexton 2019). However, it has
45 been shown ex post that transfer schemes considering income levels and location could have protected
46 or even improved the purchasing power of the bottom half of the population (Bureau et al. 2019).
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1 Investments in public transportation may reduce horizontal redistribution if it makes it easier for
2 households to reduce fossil fuel consumption when prices increase (cf. Section 4.4.1.5 and 4.4.1.9).
3 Similarly, in relation to energy use in housing, policies that encourage investments that raise energy
4 efficiency for low-income households may complement or be an alternative to taxes and subsidies as a
5 means of simultaneously mitigating and reducing fuel poverty (Charlier et al. 2019). From a different
6 angle, public acceptance of the French increase in the carbon tax could also have been enhanced via a
7 public information campaign could have raised public acceptance of the carbon tax increase (Douenne
8 and Fabre 2020). (See section 4.4.1.8 for a discussion of this and other factors that influence public
9 support for carbon taxation.).
10
11 4.2.7 Obstacles to accelerated mitigation and how overcoming them amounts to shifts
12 in development pathways
13 As outlined in Sections 4.2.3, 4.2.4, 4.2.5 and 4.2.6 there is improved understanding since AR5 of what
14 accelerated mitigation would entail in the coming decades. A major finding is that accelerated
15 mitigation pathways in the near- to mid-term appear technically and economically feasible in most
16 contexts. Chapter 4, however, cannot stop here. Section 4.2.2 has documented an important policy gap
17 for current climate pledges, and Cross-Chapter Box 4 shows an even larger ambition gap between
18 current pledges and what would be needed in the near- term to be on pathways consistent with below
19 2°C, let alone 1.5°C. In other words, while the implementation of mitigation policies to achieve updated
20 NDC almost doubles the mitigation efforts, and notwithstanding the widespread availability of the
21 necessary technologies, this doubling of effort merely narrows the gap to pathways consistent with 2°C
22 by at most 20%.
23 Obstacles to the implementation of accelerated mitigation pathways can be grouped in four main
24 categories (Table 4.10). The first set of arguments can be understood through the lens of cost-benefit
25 analysis of decision-makers, as they revolve around the following question: Are costs too high relative
26 to benefits? More precisely, are the opportunity costs—in economics terms, what is being forfeited by
27 allocating scarce resources to mitigation—justified by the benefits for the decision-maker (whether
28 individual, firm, or nation)? This first set of obstacles is particularly relevant because accelerated
29 mitigation pathways imply significant effort in the short-run, while benefits in terms of limited warming
30 accrue later and almost wholly to other actors. However, as discussed in 3.6 and 4.2.6, mitigation costs
31 for a given mitigation target are not carved in stone. They strongly depend on numerous factors,
32 including the way mitigation policies have been designed, selected, and implemented, the processes
33 through which markets have been shaped by market actors and institutions, and nature of socially- and
34 culturally-determined influences on consumer preferences. Hence, mitigation choices that might be
35 expressed straightforwardly as techno-economic decisions are, at a deeper level, strongly conditioned
36 by underlying structures of society.
37
38 Table 4.10 Objections to accelerated mitigation and where they are assessed in the WG3 report
Category Main dimensions Location in WGIII report
where objection is assessed
and solutions are discussed
Costs of mitigation Marginal, sectoral or macroeconomic costs of 3.6, 4.2.6, 12.2, Chapter 15,
mitigation too high; Scarce resources could/should be Chapter 17
used for other development priorities; Mitigation
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benefits are not worth the costs (or even non-existent);
Lack of financing
Distributional Risk of job losses; Diminished competitiveness; 4.5, Chapter 5, Chapter 13,
implications Inappropriate impact on poor/vulnerable people; Chapter 14
negative impact on vested interests
Lack of technology Lack of suitable technologies; Lack of technology 4.2.5, Chapter 16
transfer; unfavourable socio-political environment
Unsuitable “structures” Inertia of installed capital stock; Inertia of socio- 3.5, Chapter 5, Chapter 13
technical systems; Inertia to behaviour change;
Unsuitable institutions
1
2 A second set of likely obstacles in the short-term to accelerated mitigation revolves around undesirable
3 distributional consequences, within and across countries. As discussed in 4.2.6.3, the distributional
4 implications of climate policies depend strongly on their design, the way they are implemented, and on
5 the context into which they are inserted. Distributional implications of climate policies have both ethics
6 and equity dimensions, to determine what is desirable/acceptable by a given society in a given context,
7 notably the relative power of different winners and losers to have their interests taken into account, or
8 not, in the relevant decision-making processes. Like costs, distributional implications of accelerated
9 mitigation are rooted in the underlying socio-political-institutional structures of a society.
10 A third set of obstacles are about technology availability and adoption. Lack of access even to existing
11 cost-effective mitigation technologies remains an important issue, particularly for many developing
12 countries, and even in the short-term. Though it relates most directly to techno-economic costs,
13 technology availability raises broader issues related to the sociotechnical systems within which
14 innovation and adoption are embedded, and issues of technology availability are inherently issues of
15 systemic failure (16.3). The underlying legal, economic and social structures of the economy are central
16 to the different stages of socio-transition processes (Cross-Chapter Box 12).
17 The last set of obstacles revolves around the unsuitability of existing structures to accelerated
18 mitigation. We include here all forms of established structures, material (e.g., physical capital) or not
19 (institutions, social norms, patterns of individual behaviour), that are potentially long-lived and limit
20 the implementation of accelerated mitigation pathways. Typically, such structures exist for reasons
21 other than climate change and climate mitigation, including the distribution of power among various
22 actors. Modifying them in the name of accelerated climate mitigation thus requires to deal with other
23 non-climate issues as well. For example, resolving the landlord-tenant dilemma, an institutional barrier
24 to the deployment of energy efficiency in building, opens fundamental questions on private property in
25 buildings.
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1
2 Figure 4.6 Obstacles to mitigation (top panel) and measures to remove these obstacles and enable shift in
3 development pathways (lower panel)
4
5 A common thread in the discussion above is that the obstacles to accelerated mitigation are to a large
6 degree rooted in the underlying structural features of societies. As a result, transforming those
7 underlying structures can help to remove those obstacles, and thus facilitate the acceleration of
8 mitigation. This remark is all the more important that accelerated mitigation pathways, while very
9 different across countries, all share three characteristics: speed of implementation, breadth of action
10 across all sectors of the economy, and depth of emission reduction achieving more ambitious targets.
11 Transforming those underlying structures amounts to shifting a society’s development pathway (Figure
12 4.6). In the following Sections 3 and 4, we argue that it is thus necessary to recast accelerated mitigation
13 in the broader context of shifting development pathways, and that doing so opens up additional
14 opportunities to (i) overcome the obstacles outlined above, and also (ii) combine climate mitigation
15 with other development objectives.
16
17
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1 4.3 Shifting Development pathways
2 4.3.1 Framing of development pathways
3 4.3.1.1 What are development pathways?
4 The term development pathway is defined in various ways in the literature, and these definitions
5 invariably refer to the evolution over time of a society’s defining features. A society’s development
6 pathway can be described, analysed, and explained from a variety of perspectives, capturing a range of
7 possible features, trends, processes, and mechanisms. It can be examined in terms of specific
8 quantitative indicators, such as population, urbanisation level, life expectancy, literacy rate, GDP,
9 carbon dioxide emission rate, average surface temperature, etc. Alternately, it can be described with
10 reference to trends and shifts in broad socio-political or cultural features, such as democratisation,
11 liberalisation, colonisation, globalisation, consumerism, etc. Or, it can be described in a way that
12 highlights and details a particular domain of interest; for example, as an “economic pathway”,
13 “technological pathway”, “demographic pathway”, or others. Any such focused description of a
14 pathway is more limited, by definition, than the general and encompassing notion of a development
15 pathway.
16 Development pathways represent societal evolution over time, and can be assessed retrospectively and
17 interpreted in a historical light, or explored prospectively by anticipating and assessing alternative future
18 pathways. Development pathways, and prospective development pathways in particular, can reflect
19 societal objectives, as in “low-emission development pathways”, “climate-resilient development
20 pathways”, “sustainable development pathways”, “inclusive development pathway”, and as such can
21 embed normative assumptions or preferences, or can reflect potential dystopian futures to be avoided.
22 A national development plan (4.3.2) is a representation of a possible development pathway for a given
23 society reflecting its objectives, as refracted through its development planning process.
24 One approach for exploring shifts in future development pathways is through scenarios. Some examples
25 of scenario exercises in the literature are provided in Table 4.11.
26
27 Table 4.11 Prospective development pathways at global, national and local scale
Scale Process and publication Description of development pathways
Global IPCC Special Report on Emission Four different narrative storylines describing relationships
Scenarios (Nakicenovic et al. between driving forces and the evolution of emission
2000) scenarios over the 21st century.
Global Shared Socioeconomic Pathways Five narratives describing alternative socio-economic
developments, including sustainable development, regional
(Riahi et al. 2017; O’Neill et al.
rivalry, inequality, fossil-fuelled development, and middle-
2017)
of-the-road development, using alternative long-term
projections of demographics, human development, economy
and lifestyle, policies and institutions, technology, and
environment and natural resources.
Global (Rao et al. 2019) Alternative development pathways that explore several
drivers of rising or falling inequality.
Global Futures of Work Eight possible visions of the future of work in the year 2030,
based on different combinations of three core variables: the
(World Economic Forum 2018)
rate of technological change and its impact on business
models, the evolution of learning among the current and
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future workforce, and the magnitude of labour mobility
across geographies—all of which are likely to strongly
influence the nature of work in the future.
National Mt Fleur Scenarios Four socio-political scenarios intended to explore possible
futures of a newly post-apartheid South Africa, which
(Galer 2004)
included three dark prophecies and one bright vision which
reportedly influenced the new leadership.
National Mitigation Action Plans and Mitigation and development-focused scenarios for Brazil,
Scenarios (MAPS) (Winkler et al. Chile, Peru, and Colombia, entailing linked sectoral and
2017; Raubenheimer et al. 2015) economy modelling including socio-economic implications,
combined with intensive stakeholder engagement.
National Deep Decarbonisation Pathways Mitigation-focused scenarios for sixteen countries from each
(Bataille et al. 2016a; Waisman et country’s perspective, carried out by local institutes using
al. 2019) national models. The common method is a tool for decision-
makers in each context to debate differing concrete visions
for deep decarbonisation, seek consensus on near-term policy
packages, with aim to contribute to long-term global
decarbonisation.
Local New Lenses on Future Cities Six city archetypes used to create scenarios to help
understand how cities could evolve through more sustainable
(Shell Global 2014)
urbanisation processes and become more efficient, while
coping with major development challenges in the past.
1
2 Different narratives of development pathways can have distinct and even competing focuses such as
3 economic growth, shifts in industrial structure, technological determinism, and can embody alternative
4 framings of development itself (from growth to well-being, see Chapter 5), and of sustainable
5 development in particular (see 1.6 and 17.1). Scenario exercises are structured undertakings to explore
6 alternative future development pathways, often drawing on stakeholder input and accepting the deep
7 and irreducible uncertainty inherent in societal development into the future (Kahane 2019; Schweizer
8 and Kriegler 2012; Raskin and Swart 2020). The results of scenario explorations, including modelling
9 exercises, thus help clarify the characteristics of a particular future pathway, in light of a particular set
10 of assumptions and choice of indicators for assessment. Processes of developing scenarios can inform
11 choices by decision makers of various kinds.
12 Scenarios are useful to clarify societal objectives, understand constraints, and explore future shifts.
13 Scenario exercises are effective when they enable multi-dimensional assessment, and accommodate
14 divergent normative viewpoints (Kowarsch et al. 2017). Such processes might take into account
15 participants’ explicit and implicit priorities, values, disciplinary backgrounds, and world views. The
16 process of defining and describing a society’s development pathway contributes to the ongoing process
17 of understanding, explaining and defining the historical and contemporary meaning and significance of
18 a society. The imagination of facilitated stakeholder process combined with the rigour of modelling
19 helps improve understanding of constraints, trade-offs, and choices. “Scenario analysis offers a
20 structured approach for illuminating the vast range of possibilities. A scenario is a story, told in words
21 and numbers, describing the way events might unfold. If constructed with rigor and imagination,
22 scenarios help us to explore where we might be headed, but more, offering guidance on how to act now
23 to direct the flow of events toward a desirable future” (Raskin et al. 2002). Scenario processes are
24 valuable for the quantitative and qualitative insights they can provide, and also for the role they can
25 play in providing a forum and process by which diverse institutions and even antagonistic stakeholders
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1 can come together, build trust, improve understanding, and ultimately converge in their objectives
2 (Kane and Boulle 2018; Dubash 2021).
3 4.3.1.2 Shifting development pathways
4 Development pathways evolve as the result of the countless decisions and actions at all levels of societal
5 structure, as well due to the emergent dynamics within and between institutions, cultural norms, socio-
6 technological systems, and the biogeophysical environment. Society can choose to make decisions and
7 take actions with the shared intention of influencing the future development pathway toward specific
8 agreed objectives.
9 The SDGs provide a lens on diverse national and local development objectives. Humankind currently
10 faces multiple sustainability challenges that together present global society with the challenge of
11 assessing, deliberating, and attempting to bring about a viable, positive future development pathway.
12 Ecological sustainability challenges include reducing GHG emissions, protecting the ozone, controlling
13 pollutants such as aerosols and persistent organics, managing nitrogen and phosphorous cycles, etc.
14 (Steffen et al. 2015), which are necessary to address the rising risks to biodiversity and ecosystem
15 services on which humanity depends (IPBES 2019a). Socioeconomic sustainability challenges include
16 conflict, persistent poverty and deprivation, various forms of pervasive and systemic discrimination and
17 deprivation, and socially corrosive inequality. The global adoption of the SDGs and their underlying
18 indicators (United Nations 2018) reflect a negotiated prioritisation of these common challenges.
19 Figure 4.7 illustrates the process of shifting development pathways. The lines illustrate different
20 possible development pathways through time, some of which (shown here toward the top of the figure)
21 remove obstacles to the adoption and effective implementation of sustainable development policies,
22 and thus give access to a rich policy toolbox for accelerating mitigation and achieving SDGs. Other
23 development pathways (shown here toward the bottom of the figure) do not overcome, or even reinforce
24 the obstacles to adopting and effectively implementing sustainable development policies, and thus leave
25 decision-makers with more limited policy toolbox (4.2.7; Figure 4.6). A richer tool box enables faster,
26 deeper and broader mitigation.
27 The development pathways branch and branch again, signifying how a diversity of decision-makers
28 (policy makers, organizations, investors, voters, consumers, etc.) are continuously making choices that
29 influence which of many potential development pathways society follows. Some of these choices fall
30 clearly within the domain of mitigation policy. For example, what level carbon price, if any, should be
31 imposed? Should fossil fuel subsidies be removed? Most decisions, of course, fall outside the direct
32 domain of mitigation policy. Shifting development pathways toward sustainability involves this broader
33 realm of choices beyond mitigation policy per se, and requires identifying those choices that are
34 important determinants of the existing obstacles to accelerating mitigation and meeting other SDGs.
35 Addressing these choices coherently shifts the development pathway away from a continuation of
36 existing trends,
37
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1
2 Figure 4.7 Shifting development pathways to increased sustainability: Choices by a wide range of actors
3 at key decision points on development pathways can reduce barriers and provide more tools to accelerate
4 mitigation and achieve other Sustainable Development Goals
5 4.3.1.3 Expanding the range of policies and other mitigative options
6 Shifting development pathways aims to influence the ultimate drivers of emissions (and development
7 generally), such as the systemic and cultural determinants of consumption patterns, the political systems
8 and power structures that govern decision making, the institutions and incentives that guide and
9 constrain socio-technical innovation, and the norms and information platforms that shape knowledge
10 and discourse, and culture, values and needs (Raskin et al. 2002). These ultimate drivers determine the
11 mitigative capacity of a society.
12 Decision-makers might usefully consider a broader palette of policies and measures as part of an overall
13 strategy to meet climate goals and other sustainable development goals (see 4.3.2; Table 4.12). This is
14 consistent with the fact that mitigation is increasingly understood to be inseparable from broader
15 developmental goals, which can be facilitated by policy coherence and integration with broader
16 objectives and policies sectorally and societally. This is supported by other observations that mitigation
17 measures based on conventional climate policy instruments, such as emissions taxes or permits, price
18 incentives such as feed-in tariffs for low-carbon electricity generation, and fuel economy standards, and
19 building codes, which aim to influence the proximate drivers of emissions alone will not achieve the
20 long-term goals of the Paris Agreement (IPCC 2018a; Rogelj et al. 2016; UNEP 2018; Méjean et al.
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1 2015). An approach of shifting development pathways to increased sustainability (SDPS) broadens the
2 scope for mitigation.
3 4.3.1.4 An approach of SDPS helps manage trade-offs between mitigation and other SDGs.
4 Beyond removing structural obstacles to accelerated mitigation, broadening the approach to policies
5 that facilitate shifts in development pathways also helps manage the potential tradeoffs between
6 mitigation and other development objectives discussed in section 4.2.7.
7 Systematic studies of the 17 SDGs have found the interactions among them to be manifold and complex
8 (Pradhan et al. 2017; Nilsson et al. 2016; Weitz et al. 2018; Fuso Nerini et al. 2019). Addressing them
9 calls for interventions affecting fundamental, interconnected, structural features of global society
10 (International Panel on Social Progress 2018; TWI2050 - The World in 2050 2018), such as to our
11 physical infrastructure (e.g., energy, water, industrial, urban infrastructure) (Thacker et al. 2019;
12 Adshead et al. 2019; Waage et al. 2015; Mansell et al. 2019; Chester 2019), our societal institutions
13 (e.g., educational, public health, economic, innovation, and political institutions) (Sachs et al. 2019;
14 Ostrom 2010; Kläy et al. 2015; Messner 2015), and behavioural and cultural tendencies (e.g.,
15 consumption patterns, conventional biases, discriminatory interpersonal and intergroup dynamics, and
16 inequitable power structures) (Esquivel 2016; Sachs et al. 2019). These observations imply that attempt
17 to address each SDG in isolation, or as independent technical challenges, would be insufficient, as
18 would incremental, marginal changes. In contrast, effectively addressing the SDGs is likely to mean
19 significant disruption of long-standing trends and transformative progress to shift development
20 pathways to meet all the SDGs, including climate action, beyond incremental changes targeted at
21 addressing mitigation objectives in isolation. In other words, mitigation conceived as incremental
22 change is not enough. Transformational change has implications for equity in its multiple dimensions
23 (Leach et al. 2018; Klinsky et al. 2017a; Steffen and Stafford Smith 2013) including just transitions
24 (4.5).
25 Working Group II examines climate resilient development pathways – continuous processes that imply
26 deep societal changes and/or transformation, so as to strengthen sustainable development, efforts to
27 eradicate poverty and reduce inequalities while promoting fair and cross-scalar capacities for adaptation
28 to global warming and reduction of GHG emissions in the atmosphere. Transformative action in the
29 context of CRD specifically concerns leveraging change in the five dimensions of development (people,
30 prosperity, partnership, peace, planet) (WGII chapter 18).
31 Section 4.3.2 provides more details on the way development pathways influence emissions and
32 mitigative capacity. Section 4.3.3 provides examples of shifts in development pathways, as well as of
33 policies that might facilitate those. Cross-Chapter Box 5 details the links between SDPS and
34 sustainability.
35 4.3.2 Implications of development pathways for mitigation and mitigative capacity
36 4.3.2.1 Countries have different development priorities
37 At the global level, the SDGs adopted by all the United Nations Member States in 2015 are delineated
38 with a view to end poverty, protect the planet and ensure that all people enjoy peace and prosperity by
39 2030. The 17 SDGs are integrated and imply that development must balance social, economic and
40 environmental sustainability.
41 While all countries share the totality of the SDGs, development priorities differ across countries and
42 over time. These priorities are strongly linked to local contexts, and depend on which dimensions of
43 improvements in the well-being of people are considered the most urgent.
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1 Development priorities are reflected in the decisions that actors within societies make, such as policy
2 choices by governments and parliaments at all levels, votes over competing policy platforms by citizens,
3 or selection of issues that non-state actors push for. Multiple objectives range from poverty eradication
4 to providing energy access, addressing concerns of inequality, providing education, improving health,
5 cleaning air and water, improving connectivity, sustaining growth and providing jobs, among others.
6 For example, eradicating poverty and reducing inequality is a key development priority across many
7 countries, such as Brazil (Grottera et al. 2017), Indonesia (Irfany and Klasen 2017), India (GoI, 2015),
8 South Africa (Winkler 2018) and other low- and middle-income countries (Dorband et al. 2019).
9 Reducing inequality relates not only to income, but also to other dimensions such as in access to energy
10 services (Tait 2017), gender, education, racial and ethnic profiles (Andrijevic et al. 2020), and thereby
11 assumes relevance in both developing and developed countries. The development priorities of many
12 poor countries and communities with low capacities to adapt, has been focused more on reducing
13 poverty, providing basic infrastructure, education and improving health, rather than on mitigation
14 (Chimhowu et al. 2019).
15 4.3.2.2 The nature of national development plans is changing
16 Governments are increasingly resorting to the development of national plans to build institutions,
17 resources, and risk/shock management capabilities to guide national development. The number of
18 countries with a national development plan has more than doubled, from about 62 in 2006 (World Bank
19 2007) to 134 plans published between 2012 and 2018 (Chimhowu et al. 2019). The comeback of
20 planning may be linked to increased consideration given to sustainability, which is by construction
21 forward-looking and far ranging, and therefore requires state and civil society to prepare and implement
22 plans at all levels of governance. Governments are increasingly engaging in the development and
23 formulation of national plans in an organised, conscious and continual attempt to select the best
24 available alternatives to achieve specific goals.
25 A systematic assessment of 107 national development plans and 10 country case studies provides useful
26 insights regarding the type and content of the plans (Chimhowu et al. 2019). development plans are
27 increasingly focusing on mobilising action across multiple actors and multiple dimensions to enhance
28 resilience and improve the ability to undertake stronger mitigation actions. Various initiatives such as
29 the World Summit for Children in 1990; the Heavily Indebted Poor Country initiative that started
30 offering debt relief in exchange for commitments by beneficiary states to invest in health, education,
31 nutrition and poverty reduction in 1996; and push towards Comprehensive Development Frameworks
32 seem to have catalysed the development of national actions plans across countries to estimate, measure
33 and track investments and progress towards SDGs.
34 The most recent development plans also tend to differ from the earlier ones in terms of their approach.
35 Complexity science has over the years argued for new forms of planning based on contingency,
36 behaviour change, adaptation and constant learning (Colander and Kupers 2016; Ramalingam, 2013),
37 and new plans have increasingly focused on increasing resilience of individuals, organisations and
38 systems (Hummelbrunner and Jones, 2013). Finally, alongside short-term (typically 5 year) plans with
39 operational purpose, countries have also expressed visions of their development pathways over longer
40 time horizons, via, e.g., Voluntary National Reviews submitted in the context of the UN High Level
41 Political Forum on Sustainable Development.
42 National development plans are also increasingly more holistic in their approach, linking closely with
43 SDGs and incorporating climate action in their agendas. For instance, the Low Carbon Development
44 Initiative (LCDI), launched in 2017 by the Government of Indonesia, seeks to identify the development
45 policies that can help Indonesia achieve multiple (social, economic, and environmental) goals
46 simultaneously along with preserving and improving the country’s natural resources (Bappenas 2019).
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1 Likewise, Nepal’s Fifteenth five-year plan recognises the need for climate mitigation and adaptation
2 and corresponding access to international finance and technologies. The plan suggests mobilization of
3 foreign aid in the climate change domain in line with Nepal’s priorities and its inclusion in the country’s
4 climate-friendly development programs as the key opportunities in this regard (Nepal 2020).
5 China’s development plans have evolved over time from being largely growth oriented, and geared
6 largely towards the objectives of addressing poverty, improving health, education and public well-being
7 to also including modernisation of agriculture, industry and infrastructure, new forms of urbanisation
8 and a clear intent of focusing on innovation and new drivers of development (Central Compilation &
9 Translation Press 2016). China’s 14th Five Year Plan not only seeks to promote high quality
10 development in all aspects and focus on strengthening the economy in the global industrial chain, but
11 also includes a vision of an ‘ecological civilisation’, which had been developed (CPC-CC 2015) and
12 analysed earlier (He 2016; Xiao and Zhao 2017). It seeks to enhance China’s climate pledge to peak
13 CO2 emissions by 2030 and achieve carbon neutrality by 2060 through more vigorous policies and
14 measures. Development plans tie in multiple development priorities that evolve and broaden over time
15 as societies develop, as exemplified inter alia by the history of development plans in India (Box 4.4).
16
17 START BOX 4.4 HERE
18
19 Box 4.4 India’s national development plan
20 India’s initial national development plans focused on improving the living standards of its people,
21 increasing national income and food self-sufficiency. Accordingly, there was a thrust towards
22 enhancing productivity of the agricultural and industrial sectors. While the main focus was on
23 maintaining high economic growth and industrial productivity, poverty eradication, employment and
24 inclusive growth remained important priorities. The National Action Plan on Climate Change with 8
25 Missions focusing on mitigation as well as adaptation was launched in 2008 integrating climate change
26 considerations in planning and decision making (MoEF 2008). The 12th Five Year Plan (2012-17) also
27 brought in a focus on sustainability and mentioned the need for faster, sustainable and inclusive growth.
28 The National Institution for Transforming India (NITI Aayog) was set up in 2017 replacing the erstwhile
29 Planning Commission, with a renewed focus towards bringing innovation, technology, enterprise and
30 efficient management together at the core of policy formulation and implementation. However, while
31 India has moved away from its Five-Year Plans, decision making is more dynamic, with a number of
32 sector specific initiatives and targets focused on integrating sustainability dimensions through a series
33 of policies and measures supporting resource efficiency, improved energy access, infrastructure
34 development, low carbon options and building resilient communities, among other objectives
35 (MoEFCCC 2021; MoEFCC 2018; GoI 2015). India’s overall development pathway currently has a
36 strong focus on achieving robust and inclusive growth to ensure balanced development across all
37 regions and states and across sectors. There is a thrust on embracing new technologies while fostering
38 innovation and upskilling, modernisation of agriculture, improving regional and inter-personal equity,
39 bridging the gap between public and private sector performance, by focusing on efficient delivery of
40 public services, rooting out corruption and black economy, formalising the economy and expanding the
41 tax base, improving the ease of doing business, nursing the stressed commercial banking sector back to
42 a healthy state, and stopping leakages through direct benefit transfers, among other measures
43 (Government of India 2018; MoEFCCC 2021; GoI 2015).
44
45 END BOX 4.4 HERE
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1
2 4.3.2.3 Development pathways shape emissions and capacities to mitigate
3 Analysis in the mitigation literature often frames mitigation policy as having development co-benefits,
4 the main objective being climate stabilisation. This misses the point that development drives emissions,
5 and not vice versa, and it is the overall development approach and policies that determine mitigation
6 pathways (Munasinghe 2007). A large body of literature supports the fact that development pathways
7 have direct and, just as importantly, indirect implications for GHG emissions (Nakicenovic et al. 2000;
8 Winkler 2017b), through multiple channels, such as the nature of economic activity, spatial patterns of
9 development, degree of inequality, and population growth.
10 Economic structure: Chapter 2 notes that overall, affluence (GDP per capita), economic growth and
11 population growth have remained the main upward drivers of CO2 emissions from fossil-fuel
12 combustion in the past decade, with energy efficiency the main countervailing force (2.4) (Wang and
13 Feng 2017; Lin and Liu 2015). A major component of the development pathway of a country is precisely
14 the nature of the economic activities on which the country relies (e.g., agriculture and mining, heavy
15 industry, services, high-tech products, etc.) as well as the way it articulates its economy with the rest of
16 the World (e.g., export-led growth vs. import substitution strategies). Hence, the development pathway
17 ultimately drives the underlying structure of the economy, and to a large degree the relationship between
18 activity and GHG emissions.
19 At country level, however, the picture is more nuanced. Both India and China show signs of relative
20 decoupling between GDP and emissions because of structural change (Chen et al. 2018a). Sumabat et
21 al. (2016) indicate that economic growth had a negative impact on CO2 emissions in Philippines. Baek
22 and Gweisah (2013) find that CO2 emissions tend to drop monotonously as incomes increased. Lantz
23 and Feng (2006) also indicate that per capita GDP is not related to CO2 emissions in Canada. Other
24 studies point to an emerging consensus that the relationship between CO2 emissions and economic
25 indicators depends on the level of development of countries (Nguyen and Kakinaka 2019; Sharma
26 2011). While some literature indicates that absolute decoupling of economic growth and GHG
27 emissions has occurred in some countries (Le Quéré et al. 2019), a larger systematic review found
28 limited evidence of this (Haberl et al. 2020).
29 Looking ahead, choices about the nature of economic activities are expected to have significant
30 implications for emissions. For example, a development pathway that focuses on enhancing economic
31 growth based on manufacturing is likely to lead to very different challenges for mitigation compared to
32 one that focuses on services-led growth. (Quéré et al. 2018) find that choices about whether or not to
33 export offshore oil in Brazil will have significant implications for the country’s GHG emissions.
34 Similarly, in China, transforming industrial structure towards tertiary sectors (Kwok et al. 2018) and
35 restructuring exports towards higher value-added products (Wu et al. 2019) are expected to have
36 significant implications for GHG emissions.
37 Spatial patterns of development: Chapter 2 notes that rapid urbanisation in developing and transition
38 countries leads to increased CO2 emissions, the substantial migration of rural populations to urban areas
39 in these countries being the main factor leading to increased levels of income and expenditure of new
40 urban dwellers which in turn leads to increased personal carbon footprints and overall emissions (2.4).
41 Urbanisation, and more broadly spatial patterns of development, are in turned driven to a large part by
42 development choices, such as, inter alia, spatial provision of infrastructure and services, choices
43 regarding the agriculture and forestry sector, land-use policies, support to regional/local development,
44 among others (World Bank, 2009). For example, Dorin (2017) points out that if agriculture sectors in
45 Africa and India follow the same development path that developed countries have followed in the past,
46 namely increased labour productivity through enlargement and robotisation of farms, then
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1 unprecedented emigrations of rural workers towards cities or foreign countries will ensue, with large-
2 scale social, economic and environmental consequences. Looking ahead, a development pathway that
3 encourages concentrated influx of people to large urban centres will lead to very different energy and
4 infrastructure consumption patterns than a pathway that prioritises the development of smaller, self-
5 contained towns and cities.
6 Degree of inequality: Chapter 2 notes that while eradicating extreme poverty and providing universal
7 access to modern energy services to poor populations across the globe has negligible implications for
8 emissions growth, existing studies on the role of poverty and inequality as drivers of GHG emissions
9 provide limited evidence that under certain contexts greater inequality can lead to a deterioration in
10 environmental quality and may be associated with higher GHG emissions (2.4). In fact, factors affecting
11 household consumption based emissions include household size, age, education attainment,
12 employment status, urban vs rural location and housing stock (Druckman and Jackson 2015). There is
13 evidence to indicate that at the household level, the increase in emissions from additional consumption
14 of the lower income households could be larger than the reduction in emissions from the drop in
15 consumption from the high income households (Sager 2019). Accordingly, as countries seek to fulfil
16 the objective of reducing inequality, there are possibilities of higher increase in emissions (Sager 2019).
17 Since reducing inequality, as noted above, is globally one of the main development priorities, a large
18 body of literature focuses on the compatibility of climate change mitigation and reduction in economic
19 inequality (Berthe and Elie 2015; Grunewald et al. 2017; Hao et al. 2016; Wiedenhofer et al. 2017;
20 Auffhammer and Wolfram 2014; Baek and Gweisah 2013). However, the use of narrow approaches or
21 simple methods of studying the relationships of income inequality and emissions by looking at
22 correlations, may miss important linkages. For example, the influence of inequality on social values
23 such as status and civic mindedness and non-political interests that shape environmental policy can
24 influence overall consumption and its environmental impacts (Berthe and Elie 2015). Moreover,
25 inequalities may also be reflected in gender, education, racial and ethnic profiles and could accordingly
26 be associated with the level of emissions and mitigation prospects (Andrijevic et al. 2020).
27 The Illustrative Mitigation Pathways (IMP) developed for this Report (Box 3.1 and section 3.2.5)
28 provide another example of how development pathways influence mitigative capacity. Precisely,
29 IMP1.5-SP (Shifting Pathways) and 1.5-Ren (Renewables) lead to the same long-term temperature, but
30 differ in underlying socio-economic conditions. The former is based on Shared Socio-economic
31 Pathway (SSP) 1 (sustainable development), whereas the latter is based on SSP 2 (middle of the road).
32 Comparing 1.5-Ren to 1.5-SP can thus be interpreted as a numerical translation of trying the reach the
33 same long-term temperature goal without and with shifting development pathways towards
34 sustainability. Data shows that the global price of carbon necessary to remain on target is 40%-50%
35 lower in the latter relative to the former, thus indicating that mitigation is cheaper with a shift in
36 development pathway towards sustainability. Other cost indicators (e.g. consumption loss or GDP loss)
37 tell the same story. Since both IMPs were computed using the same underlying model, the comparison
38 is even more robust.
39 In sum, development pathways can lead to different emission levels and different capacities and
40 opportunities to mitigate (medium evidence, high agreement). Thus, focusing on shifting development
41 pathways can lead to larger systemic sustainability benefits.
42 4.3.2.4 Integrating mitigation considerations requires non-marginal shifts in development
43 pathways
44 Concerns about mitigation are already being introduced in national development plans, as there is
45 evidence that development strategies and pathways can be carefully designed so as to align towards
46 multiple priorities and achieve greater synergistic benefits. For example, India’s solar programme is a
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1 key element in its NDC that can in the long run, not only provide energy security and contribute to
2 mitigation, but can simultaneously contribute to economic growth, improved energy access and
3 additional employment opportunities, if appropriate policies and measures are carefully planned and
4 implemented. However, the environmental implications of the transition need to be carefully examined
5 with regard to the socio-economic implications in light of the potential of other alternatives like green
6 hydrogen, nuclear or CCUS. Similarly, South Africa National Development Plan (2011) also integrates
7 transition to low-carbon as part of the country development objectives (Box 4.5).
8
9 START BOX 4.5 HERE
10
11 Box 4.5 South Africa’s National Development Plan
12 South Africa adopted its first National Development Plan (NDP) in 2011 (NPC 2011), the same year in
13 which the country adopted climate policy (RSA 2011) and hosted COP17 in Durban. Chapter 5 of the
14 NDP addresses environmental sustainability in the context of development planning, and specifically
15 “an equitable transition to a low-carbon economy” (NPC 2011). The chapter refers explicitly to the need
16 for a just transition, protecting the poor from impacts and any transitional costs from emissions-
17 intensive to low-carbon. The plan proposes several mitigation measures, including a carbon budgeting
18 approach, reference to Treasury’s carbon tax, use of various low carbon options while maintaining
19 energy security, and the integrated resource plan for electricity. The NDP refers to coal in several
20 chapters, in some places suggesting additional investment (including new rail lines to transport coal and
21 coal to liquids), in others decommissioning coal-fired power “Procuring at least 20 000MW of
22 renewable electricity by 2030, importing electricity from the region, decommissioning 11 000MW of
23 ageing coal-fired power stations and stepping up investments in energy-efficiency” (NPC 2011: p.46).
24 Reference to environmental sustainability is not limited to chapter 5 – the introductory vision statement
25 includes acknowledgement “that each and every one of us is intimately and inextricably of this earth
26 with its beauty and life-giving sources; that our lives on earth are both enriched and complicated by
27 what we have contributed to its condition” (NPC 2011: p. 21); and the overview of the plan includes a
28 section on climate change, addressing both mitigation and adaptation.
29 END BOX 4.5 HERE
30
31 Looking ahead, given that different development pathways can lead to different levels of GHG
32 emissions and to different capacities and opportunities to mitigate, there is increasing research on how
33 to make development pathways more sustainable. Literature is also focusing on the need for a “new
34 normal” as a system capable of achieving higher quality growth while addressing multiple development
35 objectives by focusing on “innovative development pathways”.
36 Literature suggests that if development pathways are to be changed to address the climate change
37 problem, choices that would need to be made about development pathways would not be marginal
38 (Stern and Professor 2009), and would require a new social contract to address a complex set of inter-
39 linkages across sectors, classes and the whole economy (Winkler 2017b). Shifting development
40 pathways necessitates planning in a holistic manner, rather than thinking about discrete and isolated
41 activities and actions to undertake mitigation. Further, the necessary transformational changes can be
42 positive if they are rooted in the development aspirations of the economy and society in which they take
43 place (Dubash 2012; Jones et al. 2013), but they can also lead to carbon colonialism if the
44 transformations are imposed by Northern donors or perceived as such.
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1 Accordingly, influencing a societies’ development pathways draws upon a broader range of policies
2 and other efforts than narrowly influencing mitigation pathways, to be able to achieve the multiple
3 objectives of reducing poverty, inequality and GHG emissions. The implications for employment,
4 education, mobility, housing and many other development aspects must be integrated and new ways of
5 looking at development pathways which are low carbon must be considered (Bataille et al. 2016b;
6 Waisman et al. 2019). For instance, job creation and education are important elements that could play
7 a key role in reducing inequality and poverty in countries like South Africa and India (Rao and Min
8 2018; Winkler et al. 2015) while these also open up broader opportunities for mitigation.
9 4.3.2.5 New tools are needed to pave and assess development pathways
10 Relative to the literature on mitigation pathways described in 4.2.5 and in 4.3.3, the literature on
11 development pathways is limited. The climate research community has developed the Shared Socio-
12 economic pathways (SSPs) that link several socio-economic drivers including equity in relation to
13 welfare, resources, institutions, governance and climate mitigation policies in order to reflect many of
14 the key development directions (O’Neill et al. 2014). In most modelling exercises however,
15 development remains treated as an exogenous input. In addition, models may capture only some
16 dimensions of development that are relevant for mitigation options, thereby not capturing distributional
17 aspects and not allowing consistency checks with broader developmental goals (Valadkhani et al. 2016).
18 Quantitative tools for assessing mitigation pathways could be more helpful if they could provide
19 information on a broader range of development indicators, and could model substantively different
20 alternative development paths, thereby providing information on which levers might shift development
21 in a more sustainable direction.
22 Doing so requires new ways of thinking with interdisciplinary research and use of alternative
23 frameworks and methods suited to deeper understanding of change agents, determinants of change and
24 adaptive management among other issues (Winkler 2018). This includes, inter alia, being able to
25 examine enabling conditions for shifting development pathways (see 4.4.1); re-evaluating the neo-
26 classical assumptions within most models, both on the functioning of markets and on the behaviour of
27 agents, to better address obstacles on the demand side, obstacles on the supply side and market
28 distortions (Ekholm et al. 2013; Staub-Kaminski et al. 2014; Grubb et al. 2015) improving
29 representation of issues related with uncertainty, innovation, inertia and irreversibility within the larger
30 development contexts, including energy access and security ; improving the representation of social and
31 human capital, and of social, technological and governance innovations (Pedde et al. 2019).
32 Tools have been developed in that direction, for example in the Mitigation Action Plans and Scenarios
33 (MAPS) community (La Rovere et al. 2014b), but need to be further mainstreamed in the analysis.
34 Back-casting is often a preferred modelling approach for assessment aiming to align national
35 development goals with global climate goals like CO2 stabilisation. Back-casting is a normative
36 approach where modellers construct desirable futures and specify upfront targets and then find out
37 possible pathways to attain these targets (IPCC et al. 2001). Use of approaches like back-casting are
38 useful not only in incorporating the long term national development objectives in the models, but also
39 evaluating conflicts and synergies more effectively (van der Voorn et al. 2020). In back casting, the
40 long-term national development objectives remain the key benchmarks guiding the model dynamics
41 and the global climate goal is interfaced to realise the co-benefits. The models then delineate the
42 roadmap of national actions such that the national goals are achieved with a comprehensive
43 understanding of the full costs and benefits of low carbon development (often including the costs of
44 adaptation and impacts from residual climate change). Back-casting modelling exercises show that
45 aligning development and climate actions could result in much lower ‘social cost of carbon’ (Shukla et
46 al. 2008). Back-casting does not aim to produce blueprints. Rather, it indicates the relative feasibility
47 and the social, environmental, and political implications of different development and climate futures
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1 on the assumption of a clear relationship between goal setting and policy planning (Dreborg 1996).
2 Accordingly, back-casting exercises are well suited for preparing local specific roadmaps like for cities
3 (Gomi et al. 2011, 2010).
4
5 4.3.3 Examples of shifts in development pathways and of supporting policies
6 As noted in 4.3.1, policy approaches that include a broader range of instruments and initiatives would
7 impact more fundamentally on the actors, institutions and structures of societies and the dynamics
8 among them, aiming to alter the underlying drivers of emissions, opening up a wider range of mitigation
9 opportunities and potential in the process of achieving societal development goals. While the evolution
10 of these drivers is subject to varied influences and complex interactions, there are policy measures by
11 which decision-makers might influence them. Table 4.12 provides some examples of policy measures
12 that can affect key drivers (shown in the row headings).
13
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1 Table 4.12 Examples of policies that can help shift development pathways
Drivers Examples of policy measures
Behaviour • Progressive taxation
• Ecological tax reform
• Regulation of advertisement
• Investment in public transit
• Eco-labelling
Governance and • Campaign finance laws
institutions
• Regulatory transparency
• Commitment to multi-lateral environmental governance
• Public investment in education and R&D
• Public-service information initiatives
• Public sector commitment to science-based decision-making
• Anti-corruption policies
Innovation • Investment in public education
• Public sector R&D support
• Fiscal incentives for private investments in public goods
• International technology development and transfer initiatives
Finance and • International investment treaties support common objectives
investment
• Litigation and Liability regulations
• Reform of subsidies and other incentives not aligned with
• Insurance sector and pension regulation
• Green quantitative easing
• Risk disclosure
2
3 Policies such as those listed in Table 4.12 are typically associated with broader objectives than GHG
4 mitigation. They are generally conceived and implemented in the pursuit of overall societal
5 development objectives, such as job creation, macro-economic stability, economic growth, and public
6 health and welfare. However, they can have major influence on mitigative capacity, and hence can be
7 seen as necessary tools if mitigation options are to be significantly broadened and accelerated (medium
8 evidence, medium agreement). The example of the UK shows how accelerated mitigation through
9 dietary changes require a wide set of efforts to shift underlying drivers of behaviour. In this case,
10 multiple forces have interacted to lead to reduced meat consumption, including health attitudes, animal
11 welfare concerns, and an increasing focus on climate and other environmental impacts of livestock
12 production, along with corporate investment in market opportunities, and technological developments
13 in meat alternatives (Box 5.5).
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1 Other historic cases that are unrelated to recent mitigation efforts might be more appropriate examples
2 of major socio-technical shifts that were largely driven by intentional, coherent intentional policy
3 initiatives across numerous domains to meet multiple objectives. The modernization of agriculture in
4 various national contexts fits such a mold. In the US, for example, major government investments in
5 agricultural innovation through the creation of agricultural universities and support for research
6 provided advances in the technological basis for modernization. A network of agricultural extension
7 services accelerated the popularization and uptake of modern methods. Infrastructure investments in
8 irrigation and drainage made production more viable, and investment in roadways and rail for transport
9 supported market formation. Agricultural development banks made credit available, and government
10 subsidies improved the profitability for farmers and agricultural corporations. Public campaigns were
11 launched to modify food habits (Ferleger 2000).
12 Further examples of SDPS across many different systems and sectors are elaborated across this report.
13 Concrete examples assessed in this Chapter include high employment and low emissions structural
14 change, fiscal reforms for mitigation and social contract, combining housing policies to deliver both
15 housing and transport mitigation, and change economic, social and spatial patterns of development of
16 the agriculture sector provide the basis for sustained reductions in emissions from deforestation (4.4.1.7-
17 4.4.1.10). These examples differ by context. Examples in other chapters include transformations in
18 energy, urban, building, industrial, transport, and land-based systems, changes in behaviour and social
19 practices, as well as transformational changes across whole economies and societies (Cross Chapter
20 Box 5, 5.8, Box 6.2, 8.2, 8.3.1, 8.4, 9.8.1, 9.8.2, 10.4.1, Cross-Chapter Box 12}. These examples and
21 others can be understood in the context of an explanation of the concept of SDPS, and how to shifting
22 development pathways (Cross-Chapter Box 5).
23
24 START CCB 5 HERE
25 Cross-Chapter Box 5 Shifting development pathways to increase sustainability
26 and broaden mitigation options
27 Authors: Franck Lecocq (France), Harald Winkler (Republic of South Africa), Mustafa Babiker
28 (Sudan/Saudi Arabia), Brett Cohen (Republic of South Africa), Heleen de Coninck (the Netherlands),
29 Dipak Dasgupta (India), Navroz K. Dubash (India), María Josefina Figueroa Meza
30 (Denmark/Venezuela), Michael Grubb (United Kingdom), Kirsten Halsnaes (Denmark), Şiir Kilkis
31 (Turkey), William Lamb (Germany), Sebastian Mirasgedis (Greece), Sudarmanto Budi Nugroho
32 (Indonesia), Chukwumerije Okereke (Nigeria/United Kingdom), Minal Pathak (India), Joyashree Roy
33 (India/Thailand), Ambuj Sagar (India/the United States of America), Yamina Saheb (France/Algeria),
34 Priyadarshi Shukla (India), Jim Skea (United Kingdom), Youba Sokona (Mali), Julia Steinberger
35 (United Kingdom/Switzerland), Mariama Williams (Jamaica/the United States of America)
36
37 1. What do we mean by development pathways?
38 In the present report, development pathways refer to patterns of development resulting from multiple
39 decisions and choices made by many actors in the national and global contexts. Each society whether
40 in the Global North or the Global South follows its own pattern of development (Figure 1.6).
41 Development pathways can also be described at smaller scales (e.g., for regions or cities). By extension,
42 the concept can also be applied to sectors and systems (e.g., the development pathway of the agricultural
43 sector or of industrial systems).
44
45 2. Why do development pathways matter in a report about mitigation?
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1 2a. Past development pathways determine both today’s GHG emissions and the set of opportunities
2 to reduce emissions
3
4 Development pathways drive GHG emissions for a large part (2.4, 2.5 and 2.6). For example, different
5 social choices and policy packages with regard to land use and associated rents will result in human
6 settlements with different spatial patterns, different types of housing markets and cultures, and different
7 degrees of inclusiveness, and thus different demand for transport services and associated GHG
8 emissions (8.3.1, 10.2.1).
9
10 There is compelling evidence to show that continuing along existing development pathways is unlikely
11 to achieve rapid and deep emission reductions (robust evidence, medium agreement). For example,
12 investments in long-lived infrastructure, including energy supply systems, could lock-in high emissions
13 pathways and risk making deep decarbonisation and sustainable policies more difficult and expensive.
14 Development pathways also determine the set of tools available to mitigate climate change (Figure 4.7).
15 For example, the capacity of households to move closer to their workplace, in response to, e.g., a price
16 signal on carbon and thus on gasoline, depends on rents, which themselves depend on the spatial
17 patterns of development of human settlements (8.3.1). Said differently, mitigation costs depend on past
18 development choices. Similarly, development pathways determine the enablers and levers available for
19 adaptation (WGII, Chapter 18) and for achieving other SDGs.
20
21 In the absence of shifts in development pathways, conventional mitigation policy instruments (e.g.,
22 carbon tax, emission quotas, technological norms, etc.) may not be able to limit emissions to a degree
23 sufficient for deep decarbonisation or only at very high economic and social costs.
24
25 Policies to shift development pathways, on the contrary, make mitigation policies more effective. For
26 example, policies that prioritise non-car transit, or limit rents close to work places would make it easier
27 for households to relocate in response to a price signal on transport, and thus makes the same degree of
28 mitigation achievable at lower economic and social cost.
29
30 2b. Shifting development pathways broadens the scope for synergies between development objectives
31 and mitigation
32 Second, societies pursue a variety of development objectives, of which protecting the Earth’s climate
33 is part. The SDGs provide a global mapping of these goals. Absent climate mitigation, our collective
34 ability to achieve the SDGs in 2030 and to sustain them beyond 2030 is likely to be compromised, even
35 if adaptation measures are put in place (WGII).
36
37 There are many instances in which reducing GHG emissions and moving towards the achievement of
38 other development objectives can go hand in hand, in the near-, mid- and long-term (3.7, 6.7.7, 7.6.5,
39 8.2, 9.8, 10.1.1, 11.5.3, 17.3) (Figures 3.40, 12.1). For example, transitions from coal-based power to
40 lower-emissions electricity generation technologies and from Internal Combustion Engine to lower-
41 carbon transport has large mitigation potential and direct benefits for health through reduction in local
42 air pollution (Box 6.2, 10.4.1). Energy efficiency in buildings and energy poverty alleviation through
43 improved access to clean fuels also delivers significant health benefits (9.8.1 and 9.8.2).
44
45 Careful design of mitigation policies is critical to achieving these synergies (13.8). Integrated policies
46 can support the creation of synergies between climate change goals and other SDGs. For example, when
47 measures promoting walkable urban areas are combined with electrification and clean renewable
48 energy, there are several co-benefits to be attained (5.2, Figure SPM.8). These include reduced pressures
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1 on agricultural land from reduced urban growth, health co-benefits from cleaner air and benefits from
2 enhanced mobility (8.2; 8.4; 4.4.1.9).
3
4 Policy design can also manage trade-offs, for example through policy measures as part of just transitions
5 (17.4). However, even with good policy design, decisions about mitigation actions, and the timing and
6 scale thereof, may entail trade-offs with the achievement of other national development objectives in
7 the near-, mid- and long-term. In the near-term, for example, regulations may ban vehicles from city
8 centres to reduce congestion and local air pollution, but reduce mobility and choice. Increasing green
9 spaces within cities without caps on housing prices may involve trade-offs with affordable housing and
10 push low income residents outside the city (8.2.2). In the mid- and long-term, large-scale deployment
11 of biomass energy raises concerns about food security and biodiversity conservation (3.7.1, 3.7.5, 7.4.4,
12 9.8.1, 12.5.2, 12.5.3). Conflicts between mitigation and other development objectives can act as an
13 impediment to climate action (13.8). Climate change is the result of decades of unsustainable energy
14 production, land-use, production and consumption patterns, as well as governance arrangements and
15 political economic institutions that lock in resource-intensive development patterns (robust evidence,
16 high agreement). Reframing development objectives and shifting development pathways towards
17 sustainability can help transform these patterns and practices, allowing space for transitions
18 transforming unsustainable systems (medium evidence, high agreement) (Chapter 17 Executive
19 Summary).
20
21 Prioritising is one way to manage trade-offs, addressing some national development objectives earlier
22 than others. Another way is to adopt policy packages aimed at shifting development pathways towards
23 sustainability as they expand the range of tools available to simultaneously achieve multiple
24 development objectives, including mitigation. In the city example of section 2a, a carbon tax alone
25 would run counter to other development objectives if it made suburban households locked into high
26 emissions transport modes poorer or if it restricted mobility choices, in particular for low- and middle-
27 income households. Policy packages combining affordable housing and provision of safe low-carbon
28 mobility could both facilitate equitable access to housing (a major development objective in many
29 countries) and make it easier to mitigate by shifting the urban development pathway.
30
31 Similarly, a fundamental shift in the service provision that helps reduce energy demand (Chapter 5),
32 driven by targeted policies, investment and enabling socio-cultural and behavioural change, would
33 reduce pressure on supply side mitigation need, hence limiting pressure on water and food and the
34 achievement of associated SDGs. Some studies assume Western European lifestyle as a reference for
35 the global North and an improvement in the living standard for the Global South to reduce energy
36 demand and emissions (e.g., (Grubler et al. 2018)), while others explore a transformative change in the
37 global North to achieve a decent living standard for all (Millward-Hopkins et al. 2020; Bertram et al.
38 2018) (3.7.8). For example, in the UK, interaction between multiple behavioural, socio-cultural, and
39 corporate drivers including NGO campaigns, social movements and product innovations resulted in an
40 observed decline in meat consumption (5.4, 5.6.4).
41
42 3. What does shifting development pathways towards sustainability entail?
43 Shifting development pathways towards sustainability implies making transformative changes that
44 disrupt existing developmental trends. Such choices would not be marginal (Stern and Professor 2009),
45 but include technology adoption, infrastructure availability and use, and socio-behavioural factors
46 (Chapter 5).
47
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1 These include creating new infrastructure, sustainable supply chains, institutional capacities for
2 evidence-based and integrated decision-making, financial alignment towards low-carbon socially
3 responsible investments, just transitions and shifts in behaviour and norms to support shifts away from
4 fossil-fuel consumption (Green and Denniss 2018). Adopting multi-level governance modes, tackling
5 corruption where it inhibits shifts to sustainability, and improving social and political trust are also key
6 for aligning and supporting long-term environmentally just policies and processes.
7
8 Shifting development pathways entails fundamental changes in energy, urban, building, industrial,
9 transport, and land-based systems. It also requires changes in behaviour and social practices.
10 Overcoming inertia and locked-in practices may face considerable opposition (5.4.5) (Geels et al. 2017).
11 The durability of carbon intensive transport modes and electricity generating infrastructures increase
12 the risk of lock-in to high emissions pathways, as these comprise not just consumer practices, but sunk
13 costs in infrastructure, supporting institutions and rules (Seto et al. 2016; Mattioli et al. 2020). Shifting
14 investments towards low-GHG solutions requires a combination of conducive public policies, attractive
15 investment opportunities, as well as the availability of financing to enable such a transition (15.3).
16
17 4. How to shift development pathways?
18 Shifting development paths is complex. If history is any guide, practices that can easily supplant existing
19 systems and are clearly profitable move fastest (Griliches 1957). Changes that involve ‘dissimilar,
20 unfamiliar and more complex science-based components’ take more time, acceptance and legitimation
21 and involve complex social learning (Conley and Udry 2010), even when they promise large gains
22 (Pezzoni et al. 2019).
23
24 Yet despite the complexities of the interactions that result in patterns of development, history also shows
25 that societies can influence the direction of development pathways based on choices made by decision-
26 makers, citizens, the private sector and social stakeholders. For example, fundamentally different
27 responses to the first oil shock shifted then-comparable economies on to different energy sector
28 development and economic pathways in the 1970s and 80s (Sathaye et al. 2009). More recent examples
29 have shown evidence of voluntary transitions for e.g., advanced lighting in Sweden, improved cook-
30 stoves in China, liquefied petroleum gas stoves in Indonesia or ethanol vehicles in Brazil (Sovacool
31 2016).
32
33 There is no one-size-fits-all recipe for shifting development pathways. However, the following insights
34 can be drawn from past experience and scenarios of possible future development pathways (4.4.1). For
35 example, policies making inner-urban neighbourhoods more accessible and affordable reduce transport
36 costs for low- and middle-income households, and also reduce transport emissions (4.4.1.9). Shifts in
37 development pathways result from both sustained political interventions and bottom-up changes in
38 public opinion. No single sector or policy action is enough to achieve this. Coordinated policy mixes
39 would need to coordinate multiple actors – i.e., individuals, groups and collectives, corporate actors,
40 institutions and infrastructure actors – to deepen decarbonisation and shift pathways towards
41 sustainability (Pettifor 2020). One example was the LPG Subsidy ("Zero Kero") Program in Indonesia
42 which harnessed creative policy design to shift to cleaner energy by overcoming existing private
43 interests. The objective of decreasing fiscal expenditures on domestic kerosene subsidies by replacing
44 it with LPG was achieved by harnessing distribution networks of existing providers supported by
45 government subsidized provision of equipment and subsidized pricing (Cross-Chapter Box 9).
46
47 Shifts in one country may spill over to other countries. Collective action by individuals as part of formal
48 social movements or informal lifestyle changes underpins system change (5.2.3, 5.4.1, 5.4.5.3, 13.5).
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1 Sectoral transitions that aspire to shift development pathways often have multiple objectives, and deploy
2 a diverse mix or package of policies and institutional measures (Figure 13.6). Context specific
3 governance conditions can significantly enable or disable sectoral transitions, and play a determinative
4 role in whether a sectoral transition leads to a shift in development pathway. For example, if
5 implemented policies to tackle fuel poverty target the most socially vulnerable households, this can help
6 address barriers poor households face in undertaking building retrofits. In the EU-28, it has been shown
7 that accelerated energy efficiency policies coupled with strong social policies targeting the most
8 vulnerable households, can help reduce the energy demand in residential sector, and deliver additional
9 co-benefits of avoided premature deaths and reduced health impacts (9.8.2).
10
11 Literature suggests that through equitable resource distribution, high levels of human development can
12 be provided at moderate energy and carbon levels by changing consumption patterns and redirecting
13 systems in the direction of more sustainable resource use, suggesting that a special effort can be made
14 in the near term for those on higher incomes who account for a disproportionate fraction of global
15 emissions (Millward-Hopkins et al. 2020; Hickel et al. 2021) (5.2.2, Figure 5.14).
16
17 The necessary transformational changes are likely to be more acceptable if rooted in the development
18 aspirations of the economy and society within which they take place (Jones et al. 2013; Dubash 2012)
19 and may enable a new social contract to address a complex set of inter-linkages across sectors, classes
20 and the whole economy (Fleurbaey et al. 2018).
21
22 Taking advantage of windows of opportunity and disruptions to mindsets and socio-technical systems
23 could advance deeper transformations. These might include the globally declining costs of renewables
24 (Fig.1.7, 2.2.5, Box 16.2), emerging social norms for climate mitigation (Green and Denniss 2018), or
25 the COVID-19 pandemic, all of which might be harnessed to centre political action on protecting human
26 and planetary health (Büchs et al. 2020), but if not handled carefully could also risk to undermine the
27 support for transformation.
28
29 5. How can shifts in development pathways be implemented by actors in different contexts?
30 Shifting development pathways to increased sustainability is a shared aspiration. Yet since countries
31 differ in starting points (e.g., social, economic, cultural, political) and history, they have different urgent
32 needs in terms of facilitating the economic, social, and environmental dimensions of sustainable
33 development and, therefore, give different priorities (4.3.2, 17.4). The appropriate set of policies to shift
34 development pathways thus depends on national circumstances and capacities.
35
36 In some developed countries and communities, affluence leads to high levels of consumption and
37 emissions across sectors (Wiedmann et al. 2020; Mazur and Rosa 1974). For some countries, reducing
38 consumption can reduce emissions without compromising on wellbeing. However, some developing
39 countries still face the challenge of escaping “middle-income traps” (Agénor and Canuto 2015), as
40 labour-saving technological change and globalisation have limited options to develop via the
41 manufacturing sector (Altenburg and Rodrik 2017). In least developed countries, infrastructure,
42 industry, and public services are still being established, posing both a challenge to financial support to
43 deploy technologies, and large opportunities to support accelerating low-to-zero carbon options
44 (especially in terms of efficient and sufficient provision, (Millward-Hopkins et al. 2020)). Availability
45 of capital, or lack thereof, is a critical discriminant across countries and requires international
46 cooperation (15.2.2).
47
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1 Shifting development pathways towards sustainability needs to be supported by global partnerships to
2 strengthen suitable capacity, technological innovation (16.6), and financial flows (14.4.1, 15.2.4). The
3 international community can play a particularly key role by helping ensure the necessary broad
4 participation in climate-mitigation efforts, including by countries at different development levels,
5 through sustained support for policies and partnerships that support shifting development pathways
6 towards sustainability while promoting equity and being mindful of different transition capacities
7 (4.3.2, 16.5, 16.6, 14.4, 17.4).
8
9 END CCB 5 HERE
10
11 In sum, development pathways unfold over time in response to complex dynamics among various
12 drivers and diverse actors with varying interests and motivations (high agreement, robust evidence).
13 The way countries develop determines the nature and degree of the obstacles to accelerating mitigation
14 and achieving other sustainable development objectives (medium-robust evidence, medium agreement).
15 Meeting ambitious mitigation and development goals cannot be achieved through incremental change
16 (robust evidence, medium agreement). Shifting development pathways thus involves designing and
17 implementing policies where possible to intentionally enhance enabling conditions and reduce obstacles
18 to desired outcomes (medium evidence, medium agreement).
19 Section 4.4 elaborates mechanisms through which societies can develop and implement policies to
20 substantially shift development pathways toward securing shared societal objectives. Such policies
21 entail overcoming obstacles (see 4.2.7) by means of favourable enabling conditions: governance and
22 institutions, behaviour, innovation, policy and finance. These enabling conditions are amenable to
23 intentional change – to greater or lesser degrees and over longer or shorter time scales – based on a
24 range of possible measures and processes (see section 4.4).
25
26 4.4 How to shift development pathways and accelerate the pace and scale
27 of mitigation
28 4.4.1 Approaches, enabling conditions and examples
29 4.4.1.1 Framing the problem
30 What have we learned so far? As highlighted above, despite 30 years of UNFCCC and growing
31 contributions by non-state actors, the emissions gap keeps growing (4.2.2 and 4.2.3). Mitigation
32 conceived as incremental change is not enough. Meeting ambitious mitigation goals entails rapid, non-
33 marginal changes in production and consumption patterns (4.2.4 and 4.2.5). Taking another approach,
34 we have seen in section 4.3 that shifting development pathways broadens the scope for mitigation (4.3.1,
35 4.3.2) and offers more opportunities than mitigation alone to combine mitigation with the realisation of
36 other SDGs (4.3.1, Cross-Chapter Box 5).
37 A practical way forward is to combine shifting development pathways and accelerating mitigation
38 (medium evidence, high agreement). This means introducing multi-objective policy packages and
39 sequences with climate and development components that both target mitigation directly and create the
40 conditions for shifts in development pathways that will help accelerate further mitigation down the line,
41 and meet other development objectives. Since development pathways result from a myriad of decisions
42 from multiple actors (4.3.1), coordination across countries and with non-state actors is essential.
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1 The literature does not provide a handbook on how to accomplish the above. However, analysis of past
2 experience as well as understanding of how societies function yield insights that the present section
3 aims at presenting. Human history has seen multiple transformation of economies due to path-breaking
4 innovations (Michaelowa et al. 2018), like the transformation of the energy system from traditional
5 biomass to fossil fuels or from steam to electricity (Fouquet 2010, 2016a; Sovacool 2016). Fouquet
6 (2016b) and Smil (2016) argue that even the most rapid global transformations have taken several
7 decades. Enabling transformational change implies to create now the conditions that lead to that
8 transformation (Díaz et al. 2019). The starting point is that there is no single factor determining such a
9 transformation. Rather a range of enabling conditions can combine in a co-evolutionary process.
10 Amongst the conditions that have been cited in the literature are higher levels of innovation, multilevel
11 governance, transformative policy regimes or profound behavioural transformation (IPCC 2018a; Geels
12 et al. 2018; Kriegler et al. 2018; Rockström et al. 2017). It might be possible to put in place some of the
13 above conditions rapidly, while others may take longer, thereby requiring an early start.
14 The present chapter uses the set of enabling conditions identified in the IPCC SR1.5 report, namely
15 policy, governance and institutional capacity, finance, behaviour and lifestyles and innovation and
16 technology (de Coninck et al. 2018). As Figure 4.8 illustrates, public policies are required to foster both
17 accelerating mitigation and shifting development pathways. They are also vital to guide and provide the
18 other enabling conditions (cf. Table 4.12). Improved governance and enhanced institutional capacity
19 facilitate the adoption of policies that accelerate mitigation and shift development pathways, with the
20 potential to achieve multiple mitigation and development objectives. Finance is required both to
21 accelerate mitigation and to shift development pathways. Chapter 15 argues that near-term actions to
22 shift the financial system over the next decade (2021-2030) are critically important and feasible, and
23 that the immediate post-COVID recovery opens up opportunities to scale up financing from billions to
24 trillions (15.6.7) (Mawdsley 2018). As discussed in section 4.2.5, accelerated mitigation pathways
25 encompass both rapid deployment of new technologies such as CCS or electric vehicles, as well as
26 changes in consumption patterns: rapid deployment of mitigation technology and behaviour change are
27 thus two enabling conditions to accelerated mitigation. Dynamics of deployment of technologies are
28 relatively well known, pointing to specific, short-term action to accelerate innovation and deployment
29 (Cross-Chapter Box 12), whereas dynamics of collective behaviour change is less well understood.
30 Arguably, the latter also facilitates shifting development pathways.
31
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1 Figure 4.8 Enabling conditions for accelerating mitigation and shifting development pathways towards
2 sustainability
3 Individual enabling conditions are discussed at length in Chapter 5 (behaviour change), 13 (policies,
4 governance and institutional capacity), 15 (Finance) and 16 (Innovation). The purpose of the discussion
5 below is to draw operational implications from these chapters for action, taking into account the focus
6 of the present Chapter on action at the national level in the near- and mid-term, and its special emphasis
7 on shifting development pathways in addition to accelerated mitigation.
8 The rest of the section is organised as follows. Policy packages that combine climate and development
9 policies are first discussed (4.4.1.2). The next sections are dedicated to the conditions that facilitate
10 shifts in development pathways and accelerated mitigation: governance and institutions (4.4.1.3),
11 financial resources (4.4.1.4), behaviour change (4.4.1.5) and innovation (4.4.1.6). Four examples of
12 how climate and development policies can be combined to shift pathways and accelerate mitigation are
13 then presented (4.4.1.7, 4.4.1.8, 4.4.1.9 and 4.4.1.10). Section 4.4.2 focuses specifically on how shifts
14 in development pathways can deliver both mitigation and adaptation. Finally, 4.4.3 discusses risks and
15 uncertainties associated with combining shifting development pathways and accelerating mitigation.
16 4.4.1.2 Policy packages that include climate and development policies
17 Although many transformations in the past have been driven by the emergence and diffusion of an
18 innovative technology, policy intervention was frequent, especially in the more rapid ones (Grubb et al.
19 2021; Michaelowa et al. 2018). Likewise, it is not expected that spontaneous behaviour change or
20 market evolution alone yield the type of transformations outlined in the accelerated mitigation pathways
21 described in 4.2.5, or in the shifts in development pathways described in 4.3.3. On the contrary, stringent
22 temperature targets imply bold policies in the short term (Rockström et al. 2017; Kriegler et al. 2018)
23 to enforce effective existing policy instruments and regulations, as well as to reform or remove harmful
24 existing policies and subsidies (Díaz et al. 2019).
25 Policy integration, addressing multiple objectives, is an essential component of shifting development
26 pathways and accelerating mitigation (robust evidence, high agreement). A shift in development
27 pathways that fosters accelerated mitigation may best be achieved through integrated actions that
28 comprise policies in support of the broader SDG agenda, based on country-specific priorities (4.3.2,
29 13.8, 13.9). These may include for example, fiscal policies, or integrating industrial (Nilsson et al. 2021)
30 and energy policies (Fragkos et al. 2021) with climate policies. Similarly, sectoral transitions that aspire
31 to shifting development pathways towards sustainability often have multiple objectives, and deploy a
32 diverse mix or package of policies and institutional measures (Cross-Chapter Box 5).
33 Because low-carbon transitions are political processes, analyses are needed of policy as well as for
34 policy (13.6). Political scientists have developed a number of theoretical models that both explain
35 policy-making processes and provide useful insights for influencing those processes. Case studies of
36 successes and failures in sustainable development and mitigation offer equally important insights. Both
37 theoretical and empirical analysis reinforce the argument that single policy instruments are not
38 sufficient (robust evidence, high agreement). Policymakers might rather mobilise a range of policies,
39 such as financial instruments (taxes, subsidies, grants, loans), regulatory instruments (standards, laws,
40 performance targets) and processual instruments (demonstration projects, network management, public
41 debates, consultations, foresight exercises, roadmaps) (Voß et al. 2007). Policies can be designed to
42 focus on limiting or phasing out high-carbon technology. The appropriate mix is likely to vary between
43 countries and domains, depending on political cultures and stakeholder configurations (Rogge and
44 Reichardt 2016), but is likely to include a combination of: a) standards, nudges and information to
45 encourage low-carbon technology adoption and behavioural change; b) economic incentives to reward
46 low carbon investments; c) supply-side policy instruments including for fossil fuel production (to
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1 complement demand-side climate policies) and d) innovation support and strategic investment to
2 encourage systemic change (Grubb 2014). These approaches can be mutually reinforcing. For example,
3 carbon pricing can incentivise low carbon innovation, while targeted support for emerging niche
4 technologies can make them more competitive encourage their diffusion and ultimately facilitate a
5 higher level of carbon pricing. Similarly, the success of feed-in tariffs in Germany only worked as well
6 as it did because it formed part of a broader policy mix including “supply-push” mechanisms such as
7 subsidies for research and “systemic measures” such as collaborative research projects and systems of
8 knowledge exchange (Rogge et al. 2015).
9 4.4.1.3 Governance and institutional capacity
10 Governance for climate mitigation and shifting development pathways is enhanced when tailored to
11 national and local contexts. Improved institutions and governance enable ambitious climate action and
12 help bridge implementation gaps (medium evidence, high agreement). Improving institutions involve a
13 broad range of stakeholders and multiple regional and temporal scales. It necessitates a credible and
14 trusted process for reconciling perspectives and balancing potential side-effects, managing winners and
15 losers and adopting compensatory measures to ensure an inclusive and just transition (Newell and
16 Mulvaney 2013; Miller and Richter 2014; Diffenbaugh and Burke 2019; Gambhir et al. 2018),
17 managing the risk of inequitable or non-representative power dynamics and avoiding regulatory capture
18 by special interests (Helsinki Design Lab 2014; Kahane 2019; Boulle et al. 2015).
19 Long experience of political management of change demonstrates that managing such risks is not easy,
20 and requires sufficiently strong and competent institutions (Stiglitz 1998). For example, shift away
21 from fossil fuel-based energy economy could significantly disrupt the status quo, leading to a stranding
22 of financial and capital assets and shifting of political-economic power. Ensuring the decision-making
23 process is not unduly influenced by actors with much to lose is key to managing a transformation.
24 Effective governance, as noted in Chapter 13, requires establishing strategic direction, coordination of
25 policy responses, and mediation among divergent interests. Among varieties of climate governance,
26 which institutions emerge is path-dependent, based on the interplay of national political institutions,
27 international drivers, and bureaucratic structures (Dubash 2021). Focused national climate institutions
28 to address these challenges are more likely to emerge, persist and be effective when they are consistent
29 with a framing of climate change that has broad national political support (medium evidence, medium
30 agreement) (4.5, 13.2, 13.5).
31 Innovative governance approaches can help meet these challenges (Clark et al. 2018; Díaz et al. 2019).
32 Enabling multilevel governance—i.e., better alignment across governance scales—and coordination of
33 international organisations and national governments can help accelerate a transition to sustainable
34 development and deep decarbonisation (Tait and Euston-Brown 2017; Michaelowa and Michaelowa
35 2017; Ringel 2017; Revi 2017; Cheshmehzangi 2016; IPCC 2018a). Participatory and inclusive
36 governance—partnerships between state and non-state actors—, and concerted effort across different
37 stakeholders are crucial in supporting acceleration (Roberts 2016; Hering et al. 2014; Figueres et al.
38 2017; Leal Filho et al. 2018; Burch et al. 2014; Lee et al. 2018; Clark et al. 2018). So do partnerships
39 through transnational climate governance initiatives, which coordinate nation-states and non-state
40 actors on an international scale (Hsu et al. 2018). Although they are unlikely to close the gap of the
41 insufficient mitigation effort of national governments (Michaelowa and Michaelowa 2017) (4.2.3), they
42 help building confidence in governments concerning climate policy and push for more ambitious
43 national goals (UNEP 2018b).
44 Meeting these challenges also requires enhanced institutional capacity and enhanced institutional
45 mechanisms to strengthen the coordination between multiple actors, improve complementarities and
46 synergies between multiple objectives (Rasul 2016; Ringel 2017; Liu et al. 2018) and pursue climate
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1 action and other development objectives in an integrated and coherent way (Rogelj et al. 2018b; Von
2 Stechow et al. 2016; Fuso Nerini et al. 2019; Roy et al. 2018; McCollum et al. 2018), particularly in
3 developing countries (Adenle et al. 2017; Rosenbloom 2017). Institutional capacities to be strengthened
4 include vertical collaboration and interaction within Nation-States and horizontal collaboration (e.g.,
5 transnational city networks) for the development and implementation of plans, regulations and policies.
6 More specifically capacities include: capacity for knowledge harnessing and integration (from multiple
7 perspectives); for integrated policy design and implementation (Scott 2017); for long-term planning
8 (Lecocq et al. 2021) for monitoring and review process; for coordinating multi-actor processes to create
9 synergies and avoid trade-offs. As a result, institutions that enable and improve human capacities and
10 capabilities are a major driver of transformation. To this extent, promoting education, health care and
11 social safety, also are instrumental to undertake climate change mitigation and cope with environmental
12 problems (Winkler et al. 2007; Sachs et al. 2019). Given that strengthening institutions may be a long
13 term endeavour, it needs attention in the near-term.
14 4.4.1.4 Channelling financial resources
15 Accelerated mitigation and shifting development pathways necessitate both re-directing existing
16 financial flows from high- to low-emissions technologies and systems and providing additional
17 resources (robust evidence, high agreement). An example is changes in investments from fossil fuels to
18 renewable energy, with pressures to disinvest in the former while increasing levels of ‘green finance’
19 (6.7.4, 15.5). While some lower-carbon technologies have become competitive (1.4.3, 2.5), support
20 remains needed for the low-emissions options have higher costs per unit of service provided than high-
21 emission ones. Lack of financial resources is identified as a major barrier to the implementation of
22 accelerated mitigation and of shifts in development pathways. Overcoming this obstacle has two major
23 components. One relates to private capital. The other to public finance.
24 There is substantial amount of research on the redirection of private financial flows towards low-carbon
25 investment and the role of financial regulators and central banks, as detailed in Chapter 15. Financial
26 systems are an indispensable element of a systemic transition (Fankhauser et al. 2016; Naidoo 2020).
27 Policy frameworks can re-direct financial resources towards low-emission assets and services (UNEP
28 2015), mainstreaming climate finance within financial and banking system regulation, and reducing
29 transaction costs for bankable mitigation technology projects (Mundaca et al. 2013; Brunner and Enting
30 2014; Yeo 2019). Shifts in the financial system to finance climate mitigation and other SDGs can be
31 achieved by aligning incentives and investments with multiple objectives (UNEP Inquiry 2016).
32 Different approaches have been explored to improve such alignment (15.6), from national credit
33 policies to directly green mainstream financial regulations (e.g., through modifications in the Basel
34 rules for banks). For all approaches, an essential precondition is to assess and monitor the contribution
35 of financial flows to climate and sustainability goals, with better metrics that clearly link with financial
36 activity (Chenet et al. 2019). Enabling the alignment of investment decision-making with achieving
37 climate and broader sustainability goals includes acknowledgment and disclosure of climate-change
38 related risk and of risks associated with mitigation in financial portfolios. Current disclosures remain
39 far from the scale the markets need to channel investment to sustainable and resilient solutions (UNEP
40 - Finance Initiative 2020; Clark et al. 2018; Task Force on Climate-Related Financial Disclosures 2019;
41 IPCC 2018b). Disclosure, however, is not enough (Ameli et al. 2020). In addition, climate targets can
42 be translated into investment roadmaps and financing needs for financial institutions, both at national
43 and international level. Financing needs are usable for financial institutions, to inform portfolio
44 allocation decisions and financing priorities (Chenet et al. 2019). At the international level, for example,
45 technology roadmaps for key sectors can be translated into investment roadmaps and financing needs,
46 as shown by existing experiences in energy and industrial sectors (Chenet et al. 2019; WBSCD 2018;
47 International Energy Agency 2015)
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1 The transition from traditional public climate finance interventions to the market-based support of
2 climate mitigation (Bodnar et al. 2018) demands innovative forms of financial cooperation and
3 innovative financing mechanisms to help de-risk low-emission investments and support new business
4 models. These financial innovations may involve sub-national actors like cities and regional
5 governments in raising finance to achieve their commitments (Cartwright 2015; CCFLA 2017).
6 Moreover, public-private partnerships have proved to be an important vehicle for financing investments
7 to meet the SDGs, including economic instruments for financing conservation (Sovacool 2013; Díaz et
8 al. 2019).
9 Overall, early action is needed to overcome barriers and to adjust the existing i..ncentive system to align
10 national development strategies with climate and sustainable development goals in the medium-term.
11 Steckel et al. (2017) conclude that climate finance could become a central pillar of sustainable
12 development by reconciling the global goal of cost-efficient mitigation with national policy priorities.
13 Without a more rapid, scaled redeployment of financing, in development trajectories that hinder the
14 realisation of the global goals will be locked in (Zadek and Robins 2016). Investment might be designed
15 to avoid trading off the Paris goals against other SDGs, as well as those that simultaneously reduce
16 poverty, inequality, and emissions (Fuso Nerini et al. 2019).
17 At the national level, it is also essential to create public fiscal space for actions promoting the SDG
18 agenda and thereby broadening the scope of mitigation (medium evidence, medium agreement). To do
19 so, pricing carbon—either through tax payments based on the level of emissions or cap-and-trade
20 systems that limit total allowable emissions—is an efficient means of discouraging carbon emissions
21 throughout an economy (both in consumption and production) while simultaneously encouraging a
22 switch to non-carbon energy sources and generating revenues for prioritised actions (13.6.3). Regarding
23 to levels, the High-Level Commission on Carbon Prices concluded that “carbon-price level consistent
24 with achieving the Paris temperature target is at least USD40–80/tCO2 by 2020 and USD50–100/tCO2
25 by 2030, provided a supportive policy environment is in place” (CPLC 2017; Wall Street Journal 2019).
26 National level models yield median carbon values of carbon values of 733 USD/tCO2 in 2050 along
27 accelerated mitigation pathways (4.2.6), while global models find a median value of 578 USD/tCO2 for
28 pathways that reach net zero CO2 between 2045 and 2055 [interquartile range 405-708] (3.6.1).
29 Carbon pricing, however, is designed to reduce its fiscal base. Fiscal space may therefore also need to
30 stem from other sources, although fiscal reforms are complex endeavours (4.4.1.8). For countries at
31 lower income levels, foreign aid can make an important contribution to the same agenda (Kharas and
32 McArthur 2019).It may also be noted that, according to estimates at the global level, military spending
33 amounted to USD1.748 trillion in 2012 (the last year with data), a figure that corresponded to 2.3
34 percent of GDP, 55 percent of government spending in education, and was 13 times the level of net
35 ODA (World Bank 2020; SIPRI 2020). Given this, moderate reductions in military spending (which
36 may involve conflict resolution and cross-country agreements on arms limitations) could free up
37 considerable resources for the SDG agenda, both in the countries that reduce spending and in the form
38 of ODA. The resolution of conflicts within and between countries before they become violent would
39 also reduce the need for public and private spending repairing human and physical damage. The fact
40 that civil wars are common in the countries that face the severest SDG challenges underscores the
41 importance of this issue (Collier 2007 pp.17-37).
42 4.4.1.5 Changing behaviour and lifestyles
43 Changes in behaviour and lifestyles are important to accelerated mitigation. Most global mitigation
44 pathways in line with likely below 2°C and 1.5°C temperature limits assume substantial behavioural
45 and societal change and low-c arbon lifestyles (Luderer et al. 2018a; de Coninck et al. 2018; IPCC
46 2018a) (See also 3.3, and Table 4.9 and Figure 4.3 in IPCC SR 1.5). Chapter 5 concludes that
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1 behavioural changes within transition pathways offer Gigaton-scale CO2 savings potential at the global
2 level, an often overlooked strategy in traditional mitigation scenarios.
3 Individual motivation and capacity are impacted by different factors that go beyond traditional social,
4 demographic and economic predictors. However, it is unclear to what extent behavioural factors (i.e.,
5 cognitive, motivational and contextual aspects) are taken into account in policy design (Mundaca et al.
6 2019; Dubois et al. 2019). In fact, while economic policies play a significant role in influencing people’s
7 decisions and behaviour, many drivers of human behaviour and values work largely outside the market
8 system (Díaz et al. 2019; Winkler et al. 2015) as actors in society, particularly individuals, do not
9 respond in an economically ‘rational’ manner based on perfect-information cost-benefit analyses
10 (Shiller 2019; Runge 1984). Rather, compelling narratives can drive individuals to adopt new norms
11 and policies. And norms can be more quickly and more robustly shifted by proposing and framing
12 policies designed with awareness of how framings interact with individual cognitive tendencies (van
13 der Linden et al. 2015). Transformative policies are thus much more likely to be successfully adopted
14 and lead to long-term behavioural change if designed in accordance with principles of cognitive
15 psychology (van der Linden et al. 2015), and with the deep understanding of decision-making offered
16 by behavioural science (UNEP 2017b). Similarly, given that present bias—being motivated by costs
17 and benefits that take effect immediately than those delivered later—significantly shapes behaviour,
18 schemes that bring forward distant costs into the present or that upfront incentives have proved to be
19 more effective (Zauberman et al. 2009; van den Broek et al. 2017; Safarzyńska 2018). Overall,
20 transformational strategies that align mitigation with subjective life satisfaction, and build societal
21 support by positive discourses about economic, social, and cultural benefits of low-carbon innovations,
22 promises far more success than targeting mitigation alone (Asensio and Delmas 2016; WBGU 2011;
23 Geels et al. 2017).
24 Climate actions are related to knowledge but even strongly to motivational factors (Hornsey et al. 2016;
25 Bolderdijk et al. 2013; Boomsma and Steg 2014), which explains the gap between awareness and action
26 (Ünal et al. 2018). Social influences, particularly from peers, affect people’s engagement in climate
27 action (Schelly 2014). Role models appear to have a solid basis in people’s everyday preferences
28 (WBGU 2011). Social norms can reinforce individuals’ underlying motivations and be effective in
29 encouraging sustainable consumption patterns, as many examples offered by behavioural science
30 illustrate. Social networks also influence and spread behaviours (Service et al. 2014; Clayton et al. 2015;
31 Farrow et al. 2017; Shah et al. 2019). These social influences can be harnessed by climate policy.
32 Collective action by individuals as part of formal social movements or informal lifestyle movements
33 underpins system change (robust evidence, high agreement) (5.4, 5.5). Organisations are comprised of
34 individuals, but also become actors in their own right. Recent literature has considered the role of
35 coalitions and social movements in energy democracy and energy transitions towards sustainability
36 (Hess 2018). Other scholars have examined the role of women in redistributing power, both in the sense
37 of energy transition and in terms of gender relations (Allen et al. 2019; Routledge et al. 2018).
38 Mitigation and broader sustainable development policies that facilitate active participation by
39 stakeholders can build trust, forge new social contracts, and contribute to a positive cycle building
40 climate governance capacity (5.2.3).
41 However, behavioural change not embedded in structural change will contribute little to climate change
42 mitigation, suggesting that behavioural change is not only a function of individual agency but also
43 depends on other enabling factors, such as the provision of infrastructure and institutions (5.4).
44 Successful shifts towards public transport, for example, involve technologies (buses, trams),
45 infrastructure (light rail, dedicated bus lanes), regulations (operational licenses, performance contracts),
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1 institutions (new organisations, responsibilities, oversight), and high-enough density, which in turns
2 depends on such choices as housing or planning policies (4.4.1.9).
3 4.4.1.6 Fostering Technological Innovation
4 As outlined in section 4.2.5, rapid, large-scale deployment of improved low-carbon technology is a
5 critical component of accelerated mitigation pathways. As part of its key role in technological change,
6 R&D can make a crucial contribution to accelerated mitigation up to 2030 and beyond, among other
7 things by focusing on closing technology gaps that stand in the way of decarbonising today’s high
8 emitting sectors. Such sectors include shipping, trucking, aviation and heavy industries like steel,
9 cement and chemicals. More broadly, it is increasingly clear that digital changes are becoming a key
10 driving force in societal transformation (Tegmark 2017). Digitalisation is not only an “instrument” for
11 resolving sustainability challenges, it is also a fundamental driver of disruptive, multiscalar change
12 (Sachs et al. 2019) that amounts to a shift in development pathway. Information and communication
13 technologies, artificial intelligence, the internet of things, nanotechnologies, biotechnologies, robotics,
14 are not usually categorised as climate technologies, but have a potential impact on GHG emissions
15 (OECD 2017b) (Cross-Chapter Box 11).
16 The direction of innovation matters (robust evidence, high agreement). The research community has
17 called for more “responsible innovation” (Pandza and Ellwood 2013), “open innovation” (Rauter et al.
18 2019), “mission-oriented” innovation (Mazzucato and Semieniuk 2017), “holistic innovation” (Chen et
19 al. 2018b), “next-generation innovation policy” (Kuhlmann and Rip 2018) or “transformative
20 innovation” (Schot and Steinmueller 2018) so that innovation patterns and processes are commensurate
21 to our growing sustainability challenges. There is a growing recognition that new forms of innovation
22 can be harnessed and coupled to climate objectives (Fagerberg et al. 2016; Wang et al. 2018). As such,
23 innovation and sociotechnical change can be channelled to intensify mitigation via “deliberate
24 acceleration” (Roberts et al. 2018a) and “coalition building” (Hess 2018).
25 Innovation goes beyond technology. For example, decarbonisation in sectors with long lived capital
26 stock (such as heavy industry, buildings, transport infrastructure) entail technology, policy and
27 financing innovations (Bataille 2020). Similarly, expanding the deployment of photovoltaics can draw
28 upon policies that support specific technical innovations (e.g., to improve photovoltaics efficiency), or
29 innovations in regulatory and market regimes (e.g., net-metering), to innovations in social organisation
30 (e.g., community-ownership). System innovation is a core focus of the transitions literature (Grin et al.
31 2010; Markard et al. 2012; Geels et al. 2017). Accelerating low carbon transitions not only involves a
32 shift of system elements but also underlying routines and rules, and hence transitions shift the
33 directionality of innovation. They hence concern the development of a new paradigm or regime that is
34 more focused on solving sustainability challenges that cannot be solved within the dominant regime
35 they substitute (Cross-Chapter Box 12).
36 Several studies have pointed at the important possible contributions of grassroots innovators for the
37 start-up of sustainability transitions (Seyfang and Smith 2007; Smith et al. 2016; Seyfang et al. 2014).
38 In particular, a range of studies have shown that users can play a variety of roles in promoting system
39 innovation: shielding, nurturing (including learning, networking and visioning) and empowering the
40 niches in relation to the dominant system and regime (Schot et al. 2016; Randelli and Rocchi 2017;
41 Meelen et al. 2019). More fundamentally, innovation regimes can be led and guided by markets driven
42 by monetizable profits (as much of private sector led technological innovation of patentable intellectual
43 property), or prioritise social returns (e.g., innovation structures such as innovation prizes, public sector
44 innovation, investments in human capital, and socially-beneficial intellectual property regimes). In both
45 cases, public policies can play a key role by providing resources and favourable incentives (IEA 2020).
46 Chapter 16 provides more details on ways to foster innovation.
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1 4.4.1.7 Example: Structural change provides a way to keep jobs and mitigate
2 Developing countries have experienced a period of rapid economic growth in the past two decades.
3 Patterns of growth have differed markedly across regions, with newly emerging East Asian economies
4 building on transition to manufacturing—as China has done in the past—while Latin American
5 countries tend to transition directly from primary sector to services (Rodrik 2016), and African countries
6 tend to rely on productivity improvements in the primary sectors (Diao et al. 2019). Yet many countries
7 still face the challenge of getting out of the “middle-income trap” (Agénor and Canuto 2015), as labour-
8 saving technological change and globalisation have limited options to develop via the manufacturing
9 sector (Altenburg and Rodrik 2017).
10 Looking ahead, several studies have illustrated how structural change towards sustainability could lead
11 to reduced emissions intensity and higher mitigative capacity. In China, for example, the shift away
12 from heavy industry (to light industry and services) has already been identified as the most important
13 force limiting emissions growth (Guan et al. 2018), and as a major factor for future emissions (Kwok
14 et al. 2018).
15 Overall, Altenburg et al. (2017) argue that reallocation of capital and labour from low- to high-
16 productivity sectors—i.e., structural change—remains a necessity, and that it is possible to combine it
17 with reduced environmental footprint (including, but not limited to, mitigation). They argue that this
18 dual challenge calls for structural transformation policies different from those implemented in the past,
19 most importantly through a “systematic steering of investment behaviour in a socially agreed direction”
20 and encompassing policy coordination (limited evidence, medium agreement).
21 In order to permit progress on their SDG agendas, it is essential that countries develop visions of their
22 future decarbonised sectoral production structure, including its ability to generate growth in incomes,
23 employment and foreign exchange earnings. as well as the related spatial distribution of production,
24 employment, and housing. To this extent, governance and institutional capacity matter, such as
25 availability of tools to support long-term planning. A sectoral structure that permits strong growth is
26 essential given strong associations between growth in per-capita incomes and progress on most SDGs
27 (including those related to poverty; health; education; and access to water, sanitation, electricity, and
28 roads; but not income equality), in part due to the fact that higher incomes provide both households and
29 governments with resources that at least in part would be used to promote SDGs (Gable et al. 2015).
30 The future viability of sectors will depend on the extent to which they can remain profitable while
31 relying on lower-carbon energy. The challenge to identify alternative sectors of growth is particularly
32 acute for countries that today depend on oil and natural gas for most of their foreign exchange and
33 government revenues (Mirzoev et al. 2020). Changes in economic structure will also have gender
34 implications since the roles of men and women vary across sectors. For example, in many developing
35 countries, sectors in which women play a relatively important role, including agriculture and unpaid
36 household services like collection of water and fuel wood, may be negatively affected by climate change
37 (Roy 2018). It may thus be important to take complementary actions to address the gender implications
38 of changes in economic structure.
39 Given strong complementarities between policies discussed above, an integrated policy approach is
40 crucial. For example, as suggested, the actions that influence the pace at which GHG emissions can be
41 cut with political support may depend on taxation (including carbon taxes), investments in
42 infrastructure, spending on R&D, changes in income distribution (influenced by transfers), and
43 communication. In this light, it is important to consider the demands that alternative policy packages
44 put on government policy-making efficiency and credibility as well as the roles of other enabling
45 conditions. In fact, plans to undertake major reforms may provide governments with impetus to
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1 accelerate the enhancement of their capacities as part of the preparations (Karapin 2016; Jakob et al
2 2019; Withana & Sirini 2016).
3 4.4.1.8 Example: Embedding carbon finance in broader fiscal reforms offers a way to mitigate and
4 rethink the social contract
5 In many countries, fiscal systems are currently under stress to provide resources for the implementation
6 of development priorities, such as, for example, providing universal health coverage and other social
7 services (Meheus and McIntyre 2017) or sustainably funding pension systems in the context of aging
8 populations (Asher and Bali 2017; Cruz-Martinez 2018). Overall, Baum et al. (2017) argue that low-
9 income countries are likely not to have the fiscal space to undertake the investment entailed in reaching
10 the SDGs. To create additional fiscal space, major options include improving tax recovery, reducing
11 subsidies and levying additional taxes.
12 Mitigation offers an opportunity to create additional fiscal space, and thus to serve the objectives
13 outlined above, by creating a new source of revenue for the government via carbon taxation or emissions
14 permit auctioning and by reducing existing expenditures via reduction in subsidies to fossil-fuel. The
15 1991 tax reform in Sweden is an early example in which environmental taxation (including, but not
16 limited to, fossil fuel taxation) was introduced as part of a package primarily aimed at lowering the
17 marginal tax rates (more than 80% at the time), at reducing other taxes, while keeping most of the
18 welfare state. To do so, the tax base was broadened, including through environmental and carbon
19 taxation (Sterner 2007). Once in place, the carbon tax rate was substantially ramped up over time, and
20 its base broadened (Criqui et al. 2019).
21 The future potential for using carbon taxation as a way to provide space for fiscal reform has been
22 highlighted in the so-called “green fiscal reform” literature (Vogt-Schilb et al. 2019). The potential is
23 large, since only 13 percent of global GHG emissions were covered by carbon pricing schemes in 2019
24 (Watts et al. 2019) and since many countries price carbon negatively by subsidising fossil fuel use, thus
25 generating effects that are the opposite of those that positive carbon prices hope to promote. In 2018,
26 the global subsidy value amounted to $427 billion, i.e., some 10 times the payment for carbon use
27 (Watts et al. 2019). However, the size of the potential for creating fiscal space varies strongly across
28 countries given differences in terms of current carbon prices and fuel subsidies.
29 The limited adoption of and political support for carbon pricing may be explained by the fact that most
30 of the gains occur in the future and depend on actions across the globe, making them seem abstract and
31 unpredictable, whereas the costs in the form of higher carbon prices are immediate (Karapin 2016).
32 Furthermore, the links between carbon pricing and emissions may not be clear to the public who, in
33 addition, may not trust that the government will use budgetary savings according to stated plans. The
34 latter may be due to various factors, including a history of limited government commitment and
35 corruption (Maestre-Andrés et al 2019 ; Withana & Sirini 2016; Chadwick 2017).
36 The literature reports limited systematic evidence based on ex post analysis of the performance of
37 carbon pricing–carbon taxes and greenhouse gas (GHG) emissions trading systems (ETSs) (Haites
38 2018). Performance assessment is complicated by the effect of other policies and exogenous factors.
39 (Haites 2018) suggests that since 2008, other policies have probably contributed more to emission
40 reductions than carbon taxes, and most tax rates are too low to achieve mitigation objectives. Emissions
41 under ETSs have declined, with the exception of four systems without emissions caps (ibid). Every
42 jurisdiction with an ETS and/or carbon tax also has other policies that affect its GHG emissions.
43 To help policymakers overcome obstacles, research has reviewed the international experience from
44 carbon pricing reforms. Elimination of fossil fuel subsidies, equivalent to the elimination of negative
45 carbon prices, have been more successful when they have included complementary and transparent
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1 measures that enjoy popular support, accompanied by a strong communications component that
2 explains the measures and stresses their benefits (Rentschler and Bazilian 2017; Withana & Sirini 2016;
3 Maestre-Andrés et al 2019).
4 Part of the losses (and related calls for compensation or exemptions) due to carbon pricing are related
5 to the fact that it hurts the competitiveness of sectors that face imports from countries with lower carbon
6 prices, leading to “carbon leakage” if carbon-intensive production (and related jobs) migrates from
7 countries with relatively high carbon prices. Research confirms that a border carbon tax (or adjustment),
8 set on the basis of the carbon content of the import, including a downward adjustment on the basis of
9 any carbon payments (taxes or other) already made before entry, could reduce carbon leakage while
10 also raising additional revenue and encouraging carbon pricing in the exporting country (Withana &
11 Sirini 2016; Cosbey et al 2019).
12 The timing of carbon pricing reforms is also important: they are more likely to succeed if they exploit
13 windows of opportunity provided by events that raise awareness of the costs of carbon emissions (like
14 bouts of elevated local air pollution or reports about the role of emissions in causing global warming),
15 as well as momentum from climate actions by other countries and international climate agreements
16 (Karapin 2016; Jakob et al 2019). It is also important to consider the level of international prices of
17 carbon energy: when they are low, consumer resistance would be smaller since prices will remain
18 relatively low, though the tax may become more visible when energy prices increase again. As part of
19 ongoing efforts to accelerate mitigation, such tax hikes may be crucial to avoid a slow-down in the shift
20 to renewable energy sources (Rentschler and Bazilian 2017; Withana & Sirini 2016). In countries that
21 exports carbon energy, carbon taxation may run into additional resistance from producers.
22 There is also considerable literature providing insights on the political and social acceptability of carbon
23 taxes, suggesting for example that political support may be boosted if the revenue is recycled to the tax
24 payers or earmarked for areas with positive environmental effects (e.g., (Bachus et al. 2019) for
25 Belgium, and (Beiser-McGrath and Bernauer 2019) for Germany and the USA), as well as on the
26 difficulties associated with political vagaries (and economic consequences thereof) associated with the
27 introduction of such instruments (Pereira et al. 2016). Similarly, “best practice” have been drawn from
28 past experience on fossil-fuel subsidy reforms (Sovacool 2017; Rentschler and Bazilian 2017). Specific
29 policies, however, depend on societal objectives, endowments, structure of production, employment,
30 and trade, and institutional structure (including the functioning of markets and government capacity)
31 (Kettner et al. 2019). As noted in Section 4.2.6, macroeconomic analysis finds that the overall economic
32 implications of carbon pricing differ markedly depending on the way the proceeds from carbon pricing
33 are used, and thus on the way the fiscal system is reformed, with potential for double dividend if the
34 proceeds from the tax are used to repeal the most distortive taxes in the economy.
35 In the context of this section on development pathways, it is worth emphasising that potential revenues
36 drawn from the climate mitigation component of the fiscal reform varies strongly with the context, and
37 may not be sufficient to address the other objectives pursued. Even if the carbon price is high, the
38 revenue it generates may be moderate as a share of GDP and eventually it will be zero if emissions are
39 eliminated. For example, Jakob et al. (2016) find that the carbon pricing revenues that most countries
40 in Sub-Saharan Africa could expect to generate only would meet a small part of their infrastructure
41 spending needs. In Sweden, the country with the highest carbon tax rate in the world, the tax has not
42 been a significant part of total tax revenues. Moreover, emissions from sectors covered by the tax have
43 shrunk and, as a result, the revenues from the tax, as a share of GDP, have also declined, from a peak
44 of 0.93 percent in 2004, when the rate was USD109 per metric ton of CO2, to 0.48 per cent in 2018,
45 when the rate had reached USD132 (Jonsson et al. 2020; Statistics Sweden 2020). This means that
46 governments that want to avoid a decline in the GDP share for total tax revenues over time would have
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1 to raise the intake from other taxes. However, it is here important to note that domestic tax hikes are
2 likely to involve trade-offs since, at the same time as the spending they fund may provide various
3 benefits, they may also reduce the capacity of households and the private sector to consume and invest,
4 something that may reduce growth over time and reduced resources for spending in support of human
5 development (Lofgren et al. 2013). It is also worth emphasising that restructuring of the fiscal system
6 amount to changes in the social contract of the society (Combet and Hourcade 2017, 2014), and thus
7 represents a major economic and social decision.
8 4.4.1.9 Example: Combining housing policies with carbon taxation can deliver both housing and
9 mitigation in the transport sector
10 The spatial distribution of households and firms across urban and rural areas is a central characteristic
11 of development pathways. Patterns of urbanisation, territorial development, and regional integration
12 have wide-ranging implications for economic, social and environmental objectives (World Bank 2009).
13 Notably, choices regarding spatial forms of development have large-scale implications for demand for
14 transportation and associated GHG emissions.
15 Exclusionary mechanisms such as decreasing accessibility and affordability of inner-urban
16 neighbourhoods is a major cause of suburbanisation of low- to middle-income households (e.g.,
17 (Hochstenbach and Musterd 2018). Suburbanisation, in turn, is associated with higher transportation
18 demand (Bento et al. 2005) and higher carbon footprints for households (Jones and Kammen 2014).
19 Similarly, other studies find a significant positive link between housing prices and energy demand
20 (Lampin et al. 2013).
21 Reducing emissions from transport in cities through traditional climate policy instruments (e.g., through
22 a carbon tax) is more difficult when inner-urban neighbourhoods are less accessible and less affordable,
23 because exclusionary mechanisms act as a countervailing force to the rising transportation costs induced
24 by the climate policy, pushing households outwards rather than inwards. Said differently, the costs of
25 mitigating intra-city transportation emissions are higher when inner-urban housing prices are higher
26 (Lampin et al. 2013).
27 This suggests that policies making inner-urban neighbourhoods more accessible and more affordable
28 can open up broader opportunities for suburban households to relocate in the face of increasing
29 transportation costs. This is particularly important for low- and middle-income households, who spend
30 a greater portion of their income on housing and transportation, and are more likely to be locked into
31 locations that are distant from their jobs. Making inner-urban neighbourhoods more accessible and more
32 affordable has the potential to reduce both the social costs—e.g., households feeling helpless in front
33 of rising fuel prices—and the economic costs of mitigation policies—as a lower price of carbon is likely
34 to achieve the same amount of emission reductions since households have more capacities to adjust.
35 Making inner-cities neighbourhoods more accessible and more affordable is a complex endeavour
36 (Benner and Karner 2016). At the same time, it is already a policy objective in its own right in many
37 countries, independent of the climate mitigation motivation, for a range of social, health and economic
38 reasons. Revenues derived from climate policies could provide additional resources to support such
39 programs, as some climate policy already have provisions to use their revenues towards low-income
40 groups (Karner and Marcantonio 2018). The mitigation benefits of keeping inner-cities more accessible
41 and affordable for low- and middle-income households often remains out of, or is only emerging in the
42 debates surrounding the planning of fast-developing cities in many developing countries (Grant 2015;
43 IADB 2012; Khosla and Bhardwaj 2019). Finally, from a political economy perspective, it is also
44 interesting to note that (Bergquist et al. 2020) find higher support for climate policy packages in the
45 U.S. when affordable housing programs are included.
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1 In addition, investment in infrastructure is critical to the development of decarbonised economic
2 structures that generate growth, employment, and universal access to a wide range of services that are
3 central to the SDG agenda: transportation, water, sanitation, electricity, flood protection, and irrigation.
4 For low- and middle-income countries, annual costs of reaching these goals by 2030 and putting their
5 economies on a path toward decarbonisation may range between 2 and 8 percent of GDP, with the level
6 depending on spending efficiency. Notably, these costs need not exceed those of more polluting
7 alternatives (Rozenberg and Fay 2019). For transportation, this involves a shift toward more public
8 transportation (rail and bus), and decarbonised electricity for vehicles, combined with land-use policies
9 that densify cities and reduce distances between homes and jobs. By influencing the spatial distribution
10 of households and firms and the organisation of transportation, infrastructure has a strong bearing on
11 GHG emissions and the costs of providing services to different populations. Depending on country
12 context, the private sector may play a particularly important role in the financing of infrastructure
13 (World Bank 2009; Klein 2015).
14 Many investments in infrastructure and sectoral capital stocks have long lifetimes. Given this, it may
15 be important to make sure that today’s investments be fully decarbonised at the start or that they later
16 can be converted to zero carbon. Today’s investments in electric vehicles in settings where electricity
17 is produced with fossil fuels is an example of convertible investments—they will be decarbonised once
18 electricity production has switched to renewable energies. For capital stocks that cannot be
19 decarbonised, countries may face costs of decommissioning well before the end of their useful lifetimes,
20 especially when it is needed to respect country commitments to future full decarbonisation.
21 4.4.1.10 Example: Changing economic, social and spatial patterns of development of the agriculture
22 sector provide the basis for sustained reductions in emissions from deforestation
23 A growing literature assesses co-benefits of sectoral policies that lead to decarbonisation and
24 simultaneously promote economic development, improve living standards, reduce inequality, and create
25 job opportunities (Bataille et al. 2018; Pye et al. 2016; Maroun and Schaeffer 2012; Richter et al. 2018;
26 Bataille et al. 2016b; La Rovere et al. 2018; Waisman et al. 2019). While this may be particularly
27 challenging in developing countries, given large populations still lacking basic needs, previous
28 development paths show that finding synergies in development and climate objectives in the AFOLU
29 sector is possible. One example is Brazil, which has arguably shifted its development pathway to reduce
30 emissions and make progress towards several SDGs, though progress is not linear. Over the past two
31 decades, Brazil had made remarkable progress in implementing a sequence of policies across multiple
32 sectors. This policy package simultaneously increased minimum wages of low income families,
33 achieved universal energy access, and raised the quality of life and well-being for the large majority of
34 the population (Da Silveira Bezerra et al. 2017; Grottera et al. 2018, 2017; La Rovere et al. 2018). This
35 led to significant social benefits, reduction of income inequality and poverty eradication (Da Silveira
36 Bezerra et al. 2017; Grottera et al. 2017), reflected in a decrease of the Gini coefficient and a rise in the
37 human development index (La Rovere 2017).
38 Regulatory instruments were used to limit deforestation rates, together with implemented economic
39 instruments that provided benefits to those protecting local ecosystems and enhancing land-based
40 carbon sinks (Soterroni et al. 2019, 2018; Bustamante et al. 2018; Nunes et al. 2017). In parallel, public
41 policies reinforced environmental regulation and command-and-control instruments to limit
42 deforestation rates and implemented market-based mechanisms to provide benefits to those protecting
43 local ecosystems and enhancing land-based carbon sinks (Sunderlin et al. 2014; Hein et al. 2018;
44 Simonet et al. 2019; Nunes et al. 2017). The private sector, aligned with public policies and civil society,
45 implemented the Amazon Soy Moratorium, a voluntary agreement that bans trading of soybeans from
46 cropland associated with cleared Amazon rainforest and blacklists farmers using slave labour. This was
47 achieved without undermining production of soybean commodities (Soterroni et al. 2019). As a result,
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1 between 2005 and 2012, the country halved its GHG emissions and reduced the rate of deforestation by
2 78 per cent (INPE 2019a,b). This example shows that development delivering well-being can be
3 accompanied by significant mitigation. A long-term and strategic vision was important in guiding
4 enabling policies and mechanisms.
5 In more recent years, some of these shifts in Brazil’s development pathways were undone. Political
6 changes have redefined development priorities, with higher priority being given to agricultural
7 development than climate change mitigation. The current administration has reduced the power of
8 environmental agencies and forestry protection laws (including the forest code), while allowing the
9 expansion of cropland to protected Amazon rainforest areas (Ferrante and Fearnside 2019; Rochedo et
10 al. 2018). As a result, in 2020, deforestation exceeded 11,000 km2, and reached the highest rate in the
11 last 12 years (INPE 2020). The literature cautions that, if current policies and trends continue, the
12 Amazon may reach an irreversible tipping point beyond which it will be impossible to remediate lost
13 ecosystems and restore carbon sinks and indigenous people knowledge (Nobre 2019; Lovejoy and
14 Nobre 2018; INPE 2019a). In addition, fossil fuel subsidies and other fiscal support of increased
15 exploitation of oil resources may create carbon lock-ins that further inhibit low-carbon investments
16 (Lefèvre et al. 2018).
17 Brazil’s progress in mitigation depended significantly on reduced deforestation in the past. If
18 deforestation rates keep on rising, mitigation efforts would need to shift to the energy sector. However,
19 according to Rochedo et al. (2018), mitigation costs in the energy sector in Brazil are three times the
20 costs of reducing deforestation and increasing land-based carbon sinks. Further mitigation strategies
21 may depend on CCS in Brazil as elsewhere (Nogueira de Oliveira et al. 2016; Herreras Martínez et al.
22 2015), though the economic feasibility of deployment is not yet clear (4.2.5.4).
23 4.4.2 Adaptation, development pathways and mitigation
24 Mitigation actions are strongly linked to adaptation. These connections come about because mitigation
25 actions can be adaptive (e.g., some agroforestry projects) but also through policy choices (e.g., climate
26 finance is allocated among adaptation or mitigation projects) and even biophysical links (e.g., climate
27 trajectories, themselves determined by mitigation, can influence the viability of adaptation projects).
28 As development pathways shape the levers and enablers available to a society (4.3.1, Figure 4.7), a
29 broader set of enabling conditions also helps with adaptation (medium evidence, high agreement).
30 Previous assessments have consistently recognised this linkage. The Paris Agreement includes
31 mitigation and adaptation as key areas of action, through NDCs and communicating adaptation actions
32 and plans. The Agreement explicitly recognises that mitigation co-benefits resulting from adaptation
33 can count towards NDC targets. The IPCC Fifth Assessment Report (IPCC 2014) emphasised that
34 sustainable development is helpful in going beyond a narrow focus on separate mitigation and
35 adaptation options and their specific co-benefits. The IPCC Special Report on climate change and land
36 addresses GHG emissions from land-based ecosystems with a focus on the vulnerability of land-based
37 systems to climate change. The report identifies the potential of changes to land use and land
38 management practices to mitigate and adapt to climate change, and to generate co-benefits that help
39 meet other SDGs (Jian et al. 2019).
40 A substantial literature detailing trade-offs and synergies between mitigation and adaptation exists and
41 is summarised in the IPCC SR15 including energy system transitions; land and ecosystem transitions
42 (including addressing food system efficiency, sustainable agricultural intensification, ecosystem
43 restoration); urban and infrastructure system transitions (including land use planning, transport systems,
44 and improved infrastructure for delivering and using power); industrial system transitions (including
45 energy efficiency, bio-based and circularity, electrification and hydrogen, and industrial Carbon
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1 Capture, Utilisation and Storage (CCUS); and carbon dioxide removal (including bioenergy with CCS,
2 afforestation and reforestation, soil carbon sequestration, and enhanced weathering.) (IPCC 2018:
3 supplementary information Table 4.SM.5.1). Careful design of policies to shift development pathways
4 towards sustainability can increase synergies and manage trade-offs between mitigation and adaptation
5 (robust evidence, medium agreement).
6 This section examines how development pathways can build greater adaptive and mitigative capacity,
7 and then turns to several examples of mitigation actions with implications for adaptation where there is
8 a notable link to development pathways and policy choices. These examples are in the areas of
9 agriculture, blue carbon and terrestrial ecosystem restoration.
10 4.4.2.1 Development pathways can build greater capacity for both adaptation and mitigation
11 Previous IPCC assessments have reflected on making development more sustainable (Fleurbaey et al.
12 2014; Sathaye et al. 2007; IPCC et al. 2001). Other assessments have highlighted how ecosystem
13 functions can support sustainable development and are critical to meeting the goals of the Paris
14 Agreement (IPBES 2019b). IPCC SR15 found that sustainable development pathways to 1.5 °C broadly
15 support and often enable transformations and that “sustainable development has the potential to
16 significantly reduce systemic vulnerability, enhance adaptive capacity, and promote livelihood security
17 for poor and disadvantaged populations (high confidence)” (IPCC 2018b: 5.3.1). With careful
18 management, shifting development pathways can build greater adaptive and mitigative capacity, as
19 further confirmed in recent literature (Schramski et al. 2018; Harvey et al. 2014; Ebi et al. 2014;
20 Rosenbloom et al. 2018; Antwi-Agyei et al. 2015; Singh 2018; IPBES 2019b). The literature points to
21 the challenge of design of specific policies and shifts in development pathways to achieve both
22 mitigation and adaptation goals.
23 Governance and Institutional capacity
24 Governance and institutional capacity necessary for mitigation actions also enables effective adaptation
25 actions. Implementation of mitigation and adaptation actions can, however, encounter different sets of
26 challenges. Mitigation actions requiring a shift away from established sectors and resources (e.g., fossil
27 fuels) entail governance challenges to overcome vested interests (SEI et al. 2020; Piggot et al. 2020).
28 Mitigation-focused initiatives from non-state actors tend to attain greater completion than adaptation-
29 focused initiatives (NewClimate Institute et al. 2019).
30 Behaviour and lifestyles
31 On the level of individual entities, adaptation is reactive to current or anticipated environmental changes
32 but mitigation is undertaken deliberately. Chapter 5 considers behavioural change, including the
33 reconsideration of values and what is meant by well-being, and reflecting on a range of actors addressing
34 both adaptation and mitigation. Shifting development pathways may be disruptive (Cross Chapter Box
35 5), and there may be limits to propensity to change. Some studies report that climate change deniers
36 and sceptics can be induced to undertake pro-environmental action if those actions are framed in terms
37 of societal welfare, not climate change (Bain et al. 2012; Hornsey et al. 2016). Concrete initiatives to
38 change behaviour and lifestyles include the Transition Town movement, which seeks to implement a
39 just transition—both in relation to adaptation and mitigation—in specific localities (Roy et al. 2018).
40 Finance
41 Finance and investment of mitigation actions must be examined in conjunction with funding of
42 adaptation actions, due to biophysical linkages and policy trade-offs (Box 15.1). Most climate funding
43 supports mitigation efforts, not adaptation efforts (Buchner et al. 2019) (Halimanjaya and Papyrakis
44 2012). Mitigation projects are often more attractive to private capital (Abadie et al. 2013; Buchner et
45 al. 2019). Efforts to integrate adaptation and mitigation in climate change finance are limited (Locatelli
46 et al. 2016; Kongsager et al. 2016) There is a perception that integration of mitigation and adaptation
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1 projects would lead to competition for limited finance available for adaptation (Locatelli et al. 2016).
2 Long-standing debates (Ayers and Huq 2009; Smith et al. 2011) whether development finance counts
3 as adaptation funding remain unresolved. See chapter 15 for more in-depth discussion relating
4 investment in funding mitigation and adaptation actions.
5 Innovation and technologies
6 Systems transitions that address both adaptation and mitigation include the widespread adoption of new
7 and possibly disruptive technologies and practices and enhanced climate-driven innovation (IPCC
8 2018a). See Chapter 16 for an in-depth discussion of innovation and technology transfer. The literature
9 points to trade-offs that developing countries face in investing limited resources in research and
10 development, though finding synergies in relation to agriculture (Adenle et al. 2015). Other studies
11 point to difference in technology transfers for adaptation and mitigation (Biagini et al. 2014).
12 Adaptation projects tend to use existing technologies whereas mitigation climate actions are more likely
13 to rely on novel technologies. Innovations for mitigation are typically technology transfers from
14 developed to less-developed countries (Biagini et al. 2014), however this so-called North-South
15 technology transfer pathway is not exclusive (Biagini et al. 2014), and is increasingly challenged by
16 China’s global role in implementing mitigation actions (Chen 2018; Urban 2018). Indigenous
17 knowledge can be a unique source for techniques for adaptation (Nyong et al. 2007) and may be
18 favoured over externally generated knowledge (Tume et al. 2019).
19 Policy
20 Adaptation-focused pathways might reduce inequality, if adequate support is available and well-
21 distributed (Pelling and Garschagen 2019). Some studies suggest that cities might plan for possible
22 synergies in adaptation and mitigation strategies, currently done independently (Grafakos et al. 2019).
23 The literature suggests that cities might identify both mitigation and adaptation as co-benefits of
24 interventions targeted at developmental goals (Dulal 2017).
25 4.4.2.2 Specific links between mitigation and adaptation
26 Mitigation actions can be adaptive and vice-versa. In particular, many nature-based solutions (NBS) for
27 climate mitigation are adaptive (medium evidence, medium agreement). Multiple NBS are being
28 pursued under current development pathways (see Chapter 7), but shifting to sustainable development
29 pathways may enable a wider set of nature-based mitigation solutions with adaptation benefits. An
30 example of this would be a shift to more sustainable diets through guidelines, carbon taxes, or
31 investment in R&D of animal product substitutes (Figure 13.2) which could reduce pressure on land
32 and allow for implementation of multiple NBS. Many of these solutions are consistent with meeting
33 other societal goals, including biodiversity conservation and other sustainable development goals
34 (Griscom et al. 2017; Tallis et al. 2018; Fargione et al. 2018). However, there can be synergies and
35 trade-offs in meeting a complex set of sustainability goals (e.g., biodiversity, see 7.6.5 and 3.1.5).
36 Development is a key factor leading to land degradation in many parts of the world (IPBES 2019b).
37 Shifting development pathways to sustainability can include restoration and protection of ecosystems,
38 which can enhance capacity for both mitigation and adaptation actions (IPBES 2019b).
39 In this section, we explore mitigation actions related to sustainable agriculture, coastal ecosystems
40 (“blue carbon”), and restoration and protection of some terrestrial ecosystems. These mitigation actions
41 are exemplary of trade-offs and synergies with adaptation, sensitivity to biophysical coupling, and
42 linkages to development pathways. Other specific examples can be found in Chapters 6 to 11.
43 Farming system approaches can benefit mitigation and adaptation
44 Farming system approaches can be a significant contributor to mitigation pathways. These practices
45 (which are not mutually exclusive) include agroecology, conservation agriculture, integrated production
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1 systems and organic farming (Box 7.5). Such methods have potential to sequester significant amounts
2 of soil carbon (7.4.3.1) as well as reduce emissions from on-field practices such as rice cultivation,
3 fertilizer management, and manure management (7.4.3) with total mitigation potential of 3.9±0.2
4 GtCO2-eq yr-1 (Chapter 7). Critically, these approaches may have significant benefits in terms of
5 adaptation and other development goals.
6 Farming system approaches to agricultural mitigation have a wide variety of co-benefits and tradeoffs.
7 Indeed, there are conceptual formulations for these practices in which the co-benefits are more of a
8 focus, such as climate-smart agriculture (CSA) which ties mitigation to adaptation through its three
9 pillars of increased productivity, mitigation, and adaptation (Lipper et al. 2014). The ‘4 per 1000’ goal
10 to increase soil carbon by 0.4% per year (Soussana et al. 2019) is compatible with the three pillars of
11 CSA. Sustainable intensification, a framework which centers around a need for increased agricultural
12 production within environmental constraints also complements CSA (Campbell et al. 2014). The
13 literature reports examples of mitigation co-benefits of adaptation actions, with evidence from various
14 regions (Chapter 7, Thornton and Herrero (2015), Thornton et al. (2018)).
15 Conservation agriculture, promoted for improving agricultural soils and crop diversity (Powlson et al.
16 2016) can help build adaptive capacity (Smith et al. 2017; Pradhan et al. 2018a) and yield mitigation
17 co-benefits through improved fertiliser use or efficient use of machinery and fossil fuels (Cui et al.
18 2018; Harvey et al. 2014; Pradhan et al. 2018a).
19 There is a complex set of barriers to implementation of farming-system approaches for climate
20 mitigation (7.6.4), suggesting a need for deliberate shifts in development pathways to achieve
21 significant progress in this sector. The link between NDCs and mitigation in the land use sector can
22 provide impetus for such policies. For example, there are multiple agricultural mitigation options that
23 southeast Asian countries could use to meet NDCs that would have an important adaptive impact
24 (Amjath-Babu et al. 2019).
25 Some agricultural practices considered sustainable have trade-offs, and their implementation can have
26 negative effects on adaptation or other ecosystem services. Fast-growing tree monocultures or biofuel
27 crops may enhance carbon stocks but reduce downstream water availability and decrease availability of
28 agricultural land (Windham-Myers et al. 2018; Kuwae and Hori 2019). In some dry environments
29 similarly, agroforestry can increase competition with crops and pastures, decreasing productivity, and
30 reduce catchment water yield (Schrobback et al. 2011).
31 Agricultural practices can adapt to climate change while decreasing CO2 emissions on the farm field.
32 However, if such a practice leads to lower yields, interconnections of the global agricultural system can
33 lead to land use change elsewhere and a net increase in GHG emissions (Erb et al. 2016).
34 Implementation of sustainable agriculture can increase or decrease yields depending on context (Pretty
35 et al. 2006).
36 Blue carbon and mitigation co-benefits of adaptation actions
37 The Paris Agreement recognises that mitigation co-benefits resulting from Parties’ adaptation actions
38 and/or economic diversification plans can contribute to mitigation outcomes (UNFCCC 2015: Article
39 4.7). Blue carbon refers to biologically-driven carbon flux or storage in coastal ecosystems such as
40 seagrasses, salt marshes, and mangroves (Wylie et al. 2016; Fennessy et al. 2019; Fourqurean et al.
41 2012; Tokoro et al. 2014) (see Cross-Chapter Box 8 on blue carbon as a storage medium and removal
42 process).
43 Restoring or protecting coastal ecosystems is a mitigation action with synergies with adaptation and
44 development. Such restoration has been described as a ‘no regrets’ mitigation option in the Special
45 Report on the Ocean and Cryosphere in a Changing Climate (Bindoff et al. 2019) and advocated as a
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1 climate solution at national scales (Bindoff et al. 2019; Taillardat et al. 2018; Fargione et al. 2018) and
2 global scales (Howard et al. 2017). On a per-area basis, carbon stocks in coastal ecosystems can be
3 higher than in terrestrial forests (Howard et al. 2017), with below-ground carbon storage up to 1000 tC
4 ha-1 (Crooks et al. 2018; McLeod et al. 2011; Bindoff et al. 2019). Overall, coastal vegetated systems
5 have a mitigation potential of around 0.5% of current global emissions, with an upper limit of less than
6 2% (Bindoff et al. 2019).
7 Restoration or protection of coastal ecosystems is an important adaptation action with multiple benefits,
8 with bounded global mitigation benefits (Gattuso et al. 2018; Bindoff et al. 2019). Such
9 restoration/preservation reduces coastal erosion and protects from storm surges, and otherwise mitigates
10 impacts of sea level rise and extreme weather along the coast line (Siikamäki et al. 2012; Romañach et
11 al. 2018; Alongi 2008). Restoration of tidal flow to coastal wetlands inhibits methane emissions which
12 occur in fresh and brackish water (Kroeger et al. 2017) (7.4.2.8 describes a more inclusive set of
13 ecosystem services provided by coastal wetlands). Coastal habitat restoration projects can also provide
14 significant social benefits in the form of job creation (through tourism and recreation opportunities), as
15 well as ecological benefits through habitat preservation (Edwards et al. 2013; Sutton-Grier et al. 2015;
16 Sutton-Grier and Moore 2016; Kairo et al. 2018; Wylie et al. 2016; Bindoff et al. 2019).
17 Coastal ecosystem-based mitigation can be cost-effective, but interventions should be designed with
18 care. One concern is to assure that actions remain effective at higher levels of climate change (Alongi
19 2015; Bindoff et al. 2019). Also, methane emissions from ecosystems may partially reduce the benefit
20 of the carbon sequestration (Rosentreter et al. 2018) depending on the salinity (Poffenbarger et al. 2011;
21 Kroeger et al. 2017). As the main driver of mangrove forest loss is aquaculture/agriculture (Thomas et
22 al. 2017), there may be entrenched interests opposing restoration and protection actions.
23 Restoration and protection of terrestrial ecosystems
24 Restoration of terrestrial landscapes can be a direct outcome of development pathways, and can be
25 critical to achieving a variety of SDGs (especially 1, 2, 6, 8, 13, 15) (Lapola et al. 2018; Vergara et al.
26 2016) although it also presents risks and can have trade-offs with other SDGs (Cao et al. 2010; Dooley
27 and Kartha 2018). Landscape restoration is nearly always a mitigation action, and can also provide
28 adaptive capacity. While policy in Brazil has tended to focus on the Amazon as a carbon sink, the
29 mitigation co-benefits of ecosystem-based adaptation actions have been highlighted in the literature (Di
30 Gregorio et al. 2016; Locatelli et al. 2011). A study of potential restoration of degraded lands in Latin
31 America (Vergara et al. 2016) indicates that substantial benefits for mitigation, adaptation, and
32 economic development accrue after several years, underscoring a reliance on deliberate development
33 choices. In agricultural contexts, restoration is a development choice that can enhance adaptive and
34 mitigative capacity via impact on farmer livelihoods.
35 Preventing degradation of landscapes can support both mitigation and adaptation (IPCC 2019).
36 Restoration of ecosystems is associated with improved water filtration, ground water recharge and flood
37 control and multiple other ecosystem services (Ouyang et al. 2016).
38 Restoration projects must be designed with care. There can be trade-offs in addition to the synergies
39 noted above (7.6.4.3). Restorations may be unsuccessful if not considered in their socio-economic
40 context (Lengefeld et al. 2020; Iftekhar et al. 2017; Jellinek et al. 2019). Restoration projects for
41 mitigation purposes can be more effective if done with adaptation in mind (Gray et al. 2011) as a
42 changing climate may render some mitigation actions biophysically infeasible (Arneth et al. 2021).
43 Landscape restoration projects intended for CDR may underperform due to future release of stored
44 carbon, or deferral of storage until after irreversible climate change effects (e.g. extinctions) (Dooley
45 and Kartha 2018).
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1 Afforestation plans have received substantial attention as a climate mitigation action, with ongoing
2 unresolved debate on the feasibility and tradeoffs of such plans. Such afforestation programs can fail
3 for biophysical reasons (7.4.2.2, Fleischman et al. 2020) but also lack of consideration of socioeconomic
4 and development contexts (Fleischman et al. 2020).
5 4.4.3 Risks and uncertainties
6 Shifting development pathways and accelerating mitigation are complex endeavours that carry risks.
7 Some of these risks can be easily captured by quantitative models. Others are better understood via
8 qualitative approaches, such as qualitative narrative storylines (told in words) and methods mixing
9 qualitative and quantitative models (Kemp-Benedict 2012; Hanger-Kopp et al. 2019). The following
10 outline key risks and relevant hedging strategies identified in the literature.
11 4.4.3.1 Actions by others not consistent with domestic efforts
12 The international context is a major source of uncertainty for national-level planning, especially for
13 small- or medium-sized open economies, because the outcome of domestic choices may significantly
14 depend on decisions made by other countries and actor, over which national governments have limited
15 or no control (Lachapelle and Paterson 2013). Availability of foreign financial resources in countries
16 with limited domestic savings (Baum et al. 2017) and availability of technology transfers (Glachant and
17 Dechezleprêtre 2017) are some examples. Other external decisions with significant bearing on domestic
18 action include mitigation policies in other countries (Dai et al. 2017), and especially in major trading
19 partners, the lack of which can result in competitive disadvantage for sectors exposed to international
20 competition (Alton et al. 2014). The international prices of the key commodities (notably energy), goods
21 and services are important, notably when shifting development pathway is based on structural change
22 (e.g., Willenbockel et al. (2017) for Ghana and Kenya).
23 Remedies include first devising policy packages that are, to the extent possible, robust to uncertainty
24 regarding external decisions. For example, mitigation in the building sector is considered less
25 problematic for competitiveness since the construction sector is less exposed to international
26 competition. Remedies also include securing international cooperation to reduce the uncertainty that
27 domestic decision-makers face about the international context. Shifting investments towards low-GHG
28 solutions requires a combination of conducive public policies, attractive investment opportunities and
29 financing of transitions (15.6), which can enable shifting development pathways. Cooperation can
30 generate positive spill overs through technology diffusion (13.6.6). Third, cooperation is not limited to
31 governments. As discussed in section 4.2.3, international cooperative initiatives among non-State actors
32 (cities, economic branches, etc.) can also provide know-how, resources and stable cooperative
33 frameworks that reduce uncertainty for individual actors (14.5.5).
34 4.4.3.2 Parts of complex policy packages fail
35 As outlined in the examples in section 4.4.1 above, shifting development pathways and accelerating
36 mitigation are complex endeavours, on which there is limited experience and know-how from the past.
37 An uncertainty is that parts of these policy packages may fail, i.e., under-deliver relative to the amount
38 of mitigation and of transformations initially expected. For example, France has failed to meet its 2015-
39 2018 carbon budget as housing retrofitting programs, in particular, have failed to deliver the expected
40 amount of emission reductions (Haut Conseil pour le Climat 2019). There are two main options to tackle
41 this risk. The first is to build in redundancy. The second is to anticipate that some parts of the policies
42 will inevitably fail, and build-in monitoring and corrective mechanisms in a sequential decision-making
43 process. To this regard, building institutions that can properly monitor, learn from and improve over
44 time is critical (Nair and Howlett 2017).
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1 4.4.3.3 New information becomes available
2 The science on climate change, its impacts and the opportunities to mitigate is continuously being
3 updated. Even though decisions are no longer made “in a sea of uncertainty” (Lave 1991), we know
4 that new information will come over time, that may have significant bearing on the design and
5 objectives of policies to shift development pathways and accelerate mitigation. New information may
6 come from climate sciences (e.g., updated GWP values or available carbon budgets) (Quéré et al. 2018),
7 impact sciences (e.g., re-evaluation of climate impacts associated with given emission pathways) (Ricke
8 et al. 2018) or mitigation sciences (e.g., on availability of given technologies) (Lenzi et al. 2018;
9 Giannousakis et al. 2020).
10 At the same time, economic and social systems are characterised by high degree of inertia, via long-
11 lived capital stock or urban forms (Lecocq and Shalizi 2014), or more broadly mutually reinforcing
12 physical, economic, and social constraints (Seto et al. 2016) that may lead to carbon lock-ins (Erickson
13 et al. 2015). Risks associated with long-lasting fossil-fuel power plants have been the object of particular
14 attention. For example, Pfeiffer et al. (2018) estimate that even if the current pipeline of power plants
15 was cancelled, about 20% of the existing capacity might be stranded to remain compatible with 1.5°C
16 or 2°C pathways—implying that additional capital accumulation would lead to higher sunk costs
17 associated with stranded assets (Luderer et al. 2018b; Johnson et al. 2015; Ansar et al. 2013; Kriegler
18 et al. 2018).
19 In the presence of uncertainty and inertia (or irreversibilities), hedging strategies may be considered,
20 that include selection of risk-hedging strategies and processes to adjust decisions as new information
21 becomes available. The notion of hedging against risks is also prominent in the adaptation literature, as
22 exemplified by the terminology of “climate resilient development” (Fankhauser and McDermott 2016)
23 (WGII, Ch.18). There is also a growing literature on hedging strategies for individual actors (e.g., firms
24 or investors) in the face of the uncertainties associated with mitigation (e.g., policy uncertainty or the
25 associated carbon price uncertainty) (e.g., (Morris et al. 2018) or (Andersson et al. 2016)). On the other
26 hand, there is often limited discussion of uncertainty and of its implication for hedging strategies in the
27 accelerated mitigation pathway literature. Exceptions include (Capros et al. 2019), who elicit “no-
28 regret” and “disruptive” mitigation options for the EU through a detailed sensitivity analysis, and
29 (Watson et al. 2015) who discuss flexible strategies for the U.K. energy sector transition in the face of
30 multiple uncertainties.
31 4.4.3.4 Black swans (e.g., COVID-19 crisis)
32 As the current COVID-19 crisis demonstrates, events happen that can derail the best-laid plans.
33 Unexpected events beyond the range of human experience until then are called ‘black swans’, given the
34 expectation that all swans are white. The only point to note here is that such events may also provide
35 opportunities. In the COVID-19 case, for example, the experience of conducting many activities on-
36 line, which reduces emissions from transport, may leave an imprint on how some of these activities are
37 carried out in the post-COVID-19 world. Similarly, reduced air pollution seen during the pandemics
38 may increase support for mitigation and strengthen the case for climate action. However, the emissions
39 implications of recovery packages depend on choosing policies that support climate action while
40 addressing the socio-economic implications of COVID-19 (Hepburn et al. 2020). Governments may be
41 in a stronger position to do so due to their pivotal role in assuring the survival of many businesses during
42 the pandemics. Given the magnitude of recovery packages and their implications (Pollitt et al. 2021),
43 choosing the direction of recovery packages amounts to choosing a development pathway (Cross-
44 Chapter Box 1).
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1 4.4.3.5 Transformations run into oppositions
2 As noted above, shifting development pathways and accelerating mitigation involve a broad range of
3 stakeholders and decision-makers, at multiple geographical and temporal scales. They require a credible
4 and trusted process for reconciling perspectives and balancing potential side-effects, managing winners
5 and losers and implementing compensatory measures to ensure an inclusive just transition (Newell and
6 Mulvaney 2013; Miller and Richter 2014; Gambhir et al. 2018; Diffenbaugh and Burke 2019). Such
7 processes are designed to manage the risk of inequitable or non-representative power dynamics
8 (Helsinki Design Lab 2014; Kahane 2019; Boulle et al. 2015). More generally, stakeholder processes
9 can be subject to regulatory capture by special interests, or outright opposition from a variety of
10 stakeholders. Information asymmetry between government and business may shape the results of
11 consultative processes. Long experience of political management of change demonstrates that managing
12 such risks is not easy, and requires sufficiently strong and competent institutions (Stiglitz 1998). The
13 next section on Just Transition (4.5) addresses this issue.
14
15
16 4.5 Equity, including just transitions
17 Equity is an ethical and at times economic imperative, but it is also instrumentally an enabler of deeper
18 ambition for accelerated mitigation (Hoegh-Guldberg et al. 2019). The literature supports a range of
19 estimates of the net benefits—globally or nationally—of low-carbon transformation, and it identifies a
20 number of difficulties in drawing definitive quantitative conclusions (e.g., comparisons of costs &
21 benefits among different actors, the existence of non-economic impacts, comparison across time,
22 uncertainty in magnitude, 3.6). One of the most important of these dimensions is the distributional
23 consequences of mitigation, as well as a range of equity considerations arising from the uncertainty in
24 net benefits, as well as from the distribution of costs and benefits among winners and losers (Rendall
25 2019; Caney 2016; Lahn and Bradley 2016; Lenferna 2018a; Kartha et al. 2018b; Robiou Du Pont et
26 al. 2017). Some equity approaches are even just seeking corrective justice including for historical
27 emissions (Adler 2007). For an assessment of literature on fairness in NDCs, see 4.2.2.7.
28 Equity issues are often discussed in the literature via frameworks that are well-founded in the ethical
29 literature and that have a strong bearing on effort-sharing, but have not yet been quantitatively modelled
30 and expressed in the form of an emissions allocation quantified framework. These include, for example,
31 ethical perspectives based in human rights (Johl and Duyck 2012), human capabilities (Klinsky et al.
32 2017b), environmental justice (Mohai et al. 2009; Schlosberg 2009), ecological debt (Srinivasana et al.
33 2008; Warlenius et al. 2015), transitional justice (Klinsky 2017; Klinsky and Brankovic 2018), and
34 planetary boundaries (Häyhä et al. 2016).
35 While there is extensive literature on equity frameworks for national emissions allocations (CSO Equity
36 Review 2018, 2015, 2017; Kemp-Benedict et al. 2018; Pye et al. 2020; Robiou du Pont and
37 Meinshausen 2018; Fyson et al. 2020; Holz et al. 2018; Pozo et al. 2020), such studies have tended to
38 focus on allocation of a global carbon budget among countries based on quantified equity frameworks.
39 The implicit normative choices made in these analysis have limitations (Kartha et al. 2018a). Moreover,
40 there are many ethical parameters that could be introduced to enrich the existing quantitative
41 frameworks, such as progressivity (Holz et al. 2018), consumption-based accounting (Afionis et al.
42 2017), prioritarianism (Adler and Treich 2015), and a right to development (Moellendorf 2020).
43 Introducing these ethical frames into conventional quantification approaches generally implies greater
44 allocations for poorer and lower-emitting populations, suggesting that the approaches that are typically
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1 highlighted in emissions allocation analyses tends to favour wealthier and higher-emitting countries.
2 Broader, more inclusive sharing of costs and burdens is seen as a way to enhance equity in procedures
3 and outcomes.
4 Ultimately, equity consequences depend on how costs and benefits are initially incurred and how they
5 are shared as per social contracts (Combet and Hourcade 2017), national policy, and international
6 agreements. The literature suggests a relationship between the effectiveness of cooperative action and
7 the perception of fairness of such arrangements. Winkler et al. (2018) demonstrate that countries have
8 put forward a wide variety of indicators and approaches for explaining the fairness and ambition of their
9 NDCs, reflecting the broader range of perspectives found in the moral philosophical literature cited
10 above. Mbeva and Pauw (2016) further find that adaptation and financing issues take on greater salience
11 in the national perspectives reflected in the NDCs.
12 Topics of equity and fairness have begun to receive a greater amount of attention within the energy and
13 climate literature, namely through the approaches of gender and race (Pearson et al. 2017; Lennon 2017;
14 Allen et al. 2019), climate justice (Roberts and Parks 2007; Routledge et al. 2018) (Roberts & Parks,
15 2006; Routledge et al. 2018), and energy justice (Sovacool and Dworkin 2014). While such approaches
16 frequently envision justice and equity as an ethical imperative, justice also possesses the instrumental
17 value of enabling deeper and more socially acceptable mitigation efforts (Klinsky and Winkler 2018).
18 A concrete focal point on these issues has been that of “just transition”. Getting broad consensus for the
19 transformational changes entailed in moving from a high- to a low-carbon economy means ‘leaving no
20 one behind’, i.e., ensuring (sufficiently) equitable transition for the relevant affected individuals,
21 workers, communities, sectors, regions and countries (Newell & Mulvaney, 2013; Jasanoff 2018). The
22 concept of a “just transition” owes its origin to the US trade union movement of the 1980s. The earliest
23 version of a just transition was called the “Superfund for Workers” modelled on the 1980 Superfund
24 program that designed federal funds for the clean-up of toxic substances from chemicals, mining and
25 energy production (Stevis and Felli 2015). It was further taken up, for example in the collaboration of
26 the International Trade Union Confederation (ITUC), the International Labour Organization (ILO) and
27 the UN Environmental Programme (UNEP) in promoting “green jobs” as integral elements of a just
28 transition (ILO 2015; Rosemberg 2015). In recent years the concept of a “just transition” has gained
29 increased traction, for example incorporated in the outcome of the Rio+20 Earth Summit and more
30 recently recognised in the preamble of the Paris Agreement, which states “the imperative of a just
31 transition of the workforce and the creation of decent work and quality jobs in accordance with
32 nationally defined development priorities” (UNFCCC 2015c). Some heads of state and government
33 signed a Solidarity and Just Transition Silesia Declaration first introduced at COP24 in Poland (HoSG
34 2018).
35 The literature identifies targeted and proactive measures from governments, agencies, and authorities
36 to ensure that any negative social, environmental or economic impacts of economy-wide transitions are
37 minimised, whilst benefits are maximised for those disproportionally affected (Healy and Barry 2017).
38 While the precise definition varies by source, core elements tend to include: (1) investments in
39 establishing low-emission and labour-intensive technologies and sectors (Mijn Cha et al. 2020); (2)
40 research and early assessment of the social and employment impacts of climate policies (Green and
41 Gambhir 2020; Mogomotsi et al. 2018); (3) social dialogue and democratic consultation of social
42 partners and stakeholders (Smith 2017; Swilling and Annecke 2012); (4) the creation of decent jobs;
43 active labour markets policies; and rights at work (UNFCCC 2016c; ILO 2015); (5) fairness in energy
44 access and use (Carley and Konisky 2020); (6) economic diversification based on low-carbon
45 investments; (7) realistic training/retraining programs that lead to decent work; (8) gender specific
46 politics that promote equitable outcomes (Allwood 2020); (9) the fostering of international cooperation
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1 and coordinated multilateral actions (Lenferna 2018b; Newell and Simms 2020); (10) redressing of past
2 harms and perceived injustices (UNHRC 2020; Setzer and Vanhala 2019); and (11) consideration of
3 inter-generational justice concerns, such as the impacts of policy decisions on future generations
4 (Newell & Mulvaney, 2013).
5 A just transition could therefore entail that the state intervenes more actively in the eradication of
6 poverty, and creates jobs in lower-carbon sectors, in part to compensate for soon-to-be abandoned
7 fossil-fuel-based sectors, and that governments, polluting industries, corporations and those more able
8 to pay higher associated taxes pay for transition costs, provide a welfare safety net and adequate
9 compensation for people, communities, places, and regions that have been impacted by pollution,
10 marginalised or negatively impacted by a transition from a high- to low-carbon economy and society
11 (Muttitt and Kartha 2020; Le Billon and Kristoffersen 2020; Kartha et al. 2018b). Reducing climate
12 impacts is another important dimension of equity, in that the poor who are least responsible for climate
13 change are most vulnerable to its impacts (WGII, Chapter 8). Focusing on financial losses alone
14 however can obscure an important distinction between losses incurred by corporations and states and
15 losses experienced by workers and communities. Processes established in the name of a just transition
16 are also at risk of being co-opted by incumbent interests and powerful/wealthy agents (Green and
17 Gambhir, 2020). Policy interventions associated with good governance, democratic oversight, and legal
18 recourse can help overcome attempted co-optation of just transition, or use of COVID-19 recovery
19 packages for continued carbon lock-in (Hepburn et al. 2020; SEI et al. 2020).
20 The just transition concept has thus become an international focal point tying together social
21 movements, trade unions, and other key stakeholders to ensure equity is better accounted for in low-
22 carbon transitions and to seek to protect workers and communities. It also forms a central pillar of the
23 growing movement for a ‘Green New Deal’—a roadmap for a broad spectrum of policies, programs,
24 and legislation that aims to rapidly decarbonises the economy while significantly reducing economic
25 inequality (Galvin and Healy 2020)(Allam et al. 2021) The US Green New Deal Resolution (Ocasio-
26 Cortez 2019) for example positions structural inequality, poverty mitigation, and a just transition at its
27 centre. The European Green Deal proposed in 2019 (European Commission 2019), including a UDF100
28 billion “Just Transition Mechanism” to mitigate the social effects of transitioning away from jobs in
29 fossil based industries. National level green new deals with strong just transition components have been
30 proposed in South Korea, Australia, Spain, UK, Puerto Rico, Canada, as well as regional proposals
31 across Latin America and the Caribbean (Pollin 2020). .
32
33 START BOX 4.6 HERE
34
Box 4.6 Selected organisations and movements supporting a just transition
Asian Pacific Forum on Women, Law and Kentuckians for the Commonwealth (US)
Development (Asia Pacific) Labor Network for Sustainability (US)
Blue Green Alliance (US) Latrobe Valley Authority (Australia)
Beyond Coal campaign (US) Movement Generation (US)
Central Única dos Trabalhadores (Brazil) NAACP (US)
Climate Action Network (global) National Union of Mineworkers of South
Climate Justice Alliance (US) Africa (South Africa)
Cooperation Jackson (US) Pan African Climate Justice Alliance (Africa)
Dejusticia (Colombia) Post Petroleum Transitions Roundtable (Mesa
Deutscher Gewerkschaftsbund (German Trade de Transición Post Petrolera) (Argentina)
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Union Confederation) (Germany) Powering Past Coal Alliance (global)
DiEM25 (pan-European) Right to the city alliance (US)
European Union Sierra Club (US)
European Trade Union Confederation (EU) Sunrise Movement (US)
Grassroots Global Justice (US) The Leap Manifesto (Canada)
IndustriALL Global Union (global) The Trade Unions for Energy Democracy
Indigenous Environmental Network (US) Initiative (Global)
International Labor Organization (global) Trade Union Confederation of the Americas
International Trade Union Confederation— (TUCA) ITUC’s regional branch
-affiliated Just Transition Centre (Global) Just (Americas)
Transition Alliance (US) Transitions Town Movement (UK)
Just Transition Centre (global) Women’s Environment and Development
Just Transition Fund (US) Organization (Global)
350.org (Global)
1 END BOX 4.6 HERE
2
3
4 A just transition at national, regional and local scales can help to ensure that workers, communities,
5 frontline communities and the energy-poor are not left behind in the transition. Moreover, a just
6 transition necessitates that rapid decarbonisation does not perpetuate asymmetries between richer and
7 poorer states and people (UNHRC 2020). Alliances around a just transition in countries across the world
8 take many forms (Box 4.6).
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1
2 Figure 4.9 Just Transitions around the world, 2020
3 Panel A shows commissions, task forces, dialogues behind a just transition in many countries ((Snell 2018;
4 Government of Canada 2019; Piggot et al. 2019; Harrison 2013; Government of Costa Rica 2019; Ng et al.
5 2016; van Asselt and Moerenhout 2018; European Union 2019, 2020; Galgóczi 2019; Finnish Government
6 2020; Commission on Growth Structural Change and Employment 2019; Ministry of Employment and Labour
7 Relations of Ghana 2018; Popp 2019; Galgóczi 2014; Adeoti et al. 2016; Gass and Echeverria 2017; Ministry of
8 Business Innovation & Employment New Zealand 2019; Mendoza 2014; Szpor, A. and Ziółkowska 2018;
9 Government of Scotland 2020; Bankwatch 2019; NPC (National Planning Commission) 2019; Strambo et al.
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1 2019; Thalmann 2004; White House 2016; Schweitzer, M. and Tonn 2003; International Labor Organization
2 2018; Mijn Cha et al. 2020); Panel B shows the funds related to the Just Transition within the European
3 Union Green Deal, and Panel C shows the European Union’s Platform for Coal Regions in Transition.
4 As Figure 4.9 shows, no fewer than 7 national commissions or task forces on a just transition existed as
5 of 2020 as well as 7 other sets of national policies and a multitude of other actors, networks, and
6 movements. For instance, the German phase-out of coal subsidies involved a savings package for
7 unemployed miners. Subsidy reform packages introduced by Iran, Namibia, the Philippines, Turkey,
8 and the United Kingdom provide similar compensating measures to affected groups (Sovacool 2017).
9 Spain’s just transition plan for coal miners includes early retirement, redundancy packages, silicosis
10 compensation, retraining for green jobs, and priority job placement for former miners.
11
12 4.6 Knowledge gaps
13 This section summarises knowledge gaps that require further research:
14 • Literature on mitigation pathways at the national level remains skewed towards large emitters.
15 Many low-income countries have very few or no studies at all (Lepault and Lecocq 2021) (4.2)
16 (Annex III). Development of new studies and inclusion of associated scenarios in updated
17 mitigation national mitigation pathway database would enhance understanding of mitigation at
18 national level.
19 • Ex ante and ex post analysis of mitigation action and of mitigation plans by non-state actors,
20 and their relationship with mitigation action and plans by governments is limited (4.2.3).
21 • System analysis solutions are only beginning to be recognised in current literature on deep
22 mitigation pathways, and rarely included in existing national policies or strategies (4.2.5).
23 • While the technology elements of accelerated mitigation pathways at national level are
24 generally well documented, studies of the economic and social implications of such pathways
25 remain scarce (4.2.6).
26 • Literature on the implication of development choices for emissions and for capacity to mitigate
27 is limited (4.3.2). In particular, more contributions from the research community working on
28 development issues would be very useful here.
29 • Literature describing shifts in development pathways, and the conditions for such shifts (based
30 on past experience or on models) remains scarce (4.3.1, 4.3.3, 4.4.1). Studying shifts in
31 development pathways requires new ways of thinking with interdisciplinary research and use
32 of alternative frameworks and methods suited for understanding of change agents, determinants
33 of change and adaptive management among other issues (Winkler 2018). Research is not only
34 expected to produce knowledge and boost innovation, but also to help identify transformation
35 pathways and to enlighten public debate and public decision making on related political
36 choices.
37 • Other research gaps concern the open ocean and blue carbon. There is limited knowledge about
38 quantification of the blue carbon stocks. Research is required into what happens if the
39 sequestration capacity of the ocean and marine ecosystems is damaged by climate change to
40 the tipping point until the sink becomes an emitter, and on how to manage blue carbon (4.4.2).
41 • Knowledge is limited on: i) linking equity frameworks on mitigation with adaptation and most
42 importantly with loss and damage, ii) applying ethical parameters to enrich many of the existing
43 quantitative frameworks, to assess fairness and ambition of NDCs; iii) extending equity
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1 frameworks to quantify equitable international support, as the difference between equity-based
2 national emissions scenarios and national domestic emissions scenarios (4.2.2.7, 4.5).
3
4 Frequently asked questions
5 FAQ 4.1 What is to be done over and above countries existing pledges under the Paris Agreement
6 to keep global warming well below 2C?
7 Current pledges and efforts under the PA aimed at keeping global warming below 2°C are not enough,
8 falling short by 14-23 GtCO2-eq (Cross-Chapter Box 4). There is a further shortfall of about 4 to 7
9 GtCO2-eq in 2030 if the conditions are not fulfilled for those Parties that have made their pledges with
10 conditions for support (4.2.2.3). To cover up for these shortfalls will require taking actions across all
11 sectors that can substantially reduce GHG emissions. Examples of such actions include shifting to low-
12 or zero-emission power generation, such as renewables; changing food systems, such as diet changes
13 away from land-intensive animal products; electrifying transport and developing ‘green infrastructure’,
14 such as building green roofs, or improving energy efficiency by smart urban planning, which will
15 change the layout of many cities. Because these different actions are connected, it means all relevant
16 companies, industries and stakeholders would need to be involved to increase the support and chance
17 of successful implementation (4.2.5). The deployment of low-emission technology depends upon
18 economic conditions (e.g., employment generation or capacity to mobilize investment), but also on
19 social/cultural conditions (e.g., awareness and acceptability) and institutional conditions (e.g., political
20 support and understanding), and the provision of relevant enabling conditions (4.4.1). Encouraging
21 stronger and more ambitious climate action by non-government and subnational stakeholders, as well
22 as international cooperative initiatives (ICIs) could make significant contributions to emissions
23 reduction (4.2.3).
24 FAQ 4.2 Option 1: What is to be done in the near-term to accelerate mitigation and shift
25 development pathways?
26 Increasing speed of implementation, breadth of action across all sectors of the economy, and depth of
27 emission reduction faces important obstacles, that are rooted in the underlying structure of societies
28 (4.2.7). Addressing these obstacles amounts to shifting away from existing developmental trends (i.e.,
29 shifting development pathways, Cross-Chapter Box 5). This can be done by strengthening governance
30 and institutional capacity, aligning technology and innovation systems with low-carbon development,
31 facilitating behaviour change and providing adequate finance within the context of multi-objective
32 policy packages and sequences (4.4.1). Shifting development pathways towards sustainability broadens
33 the scope for, and is thus a complement to, accelerated mitigation (4.3).
34 FAQ 4.3 Is it possible to accelerate mitigation in the near-term while there are so many other
35 development priorities? (education, health, employment, etc.)
36 It is possible to accelerate mitigation while addressing other developmental priorities by implementing
37 measures that simultaneously address both climate and development goals. Casting mitigation in the
38 broader context of development pathways provides additional opportunities to articulate both (4.3.1.4).
39 Policies such as progressive taxation, investment in public transport, regulatory transparency,
40 commitment to multi-lateral environmental governance, fiscal incentives for private investments,
41 international technology development and transfer initiatives, and risk disclosure and efforts to improve
42 underlying enabling conditions (improving governance and institutional capacity, fostering behavioural
43 change and technological innovation, and provision of finance) address multiple objectives beyond
44 mitigation, such as job creation, macro-economic stability, economic growth, public health and welfare,
45 providing energy access, providing formal housing, and providing mobility. How we manage our land
46 and agriculture, growing cities, transport needs, our industries, and the way people are trained and
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Final Government Distribution Chapter 4 IPCC AR6 WGIII
1 employed all impact on GHG emissions and the options we have to reduce them. In turn, reducing GHG
2 emissions can also contribute to reducing poverty, preventing hunger, improving health and wellbeing,
3 and providing clean water and clean energy. Implementing right policies and investments can help to
4 address the challenges of how to reduce emissions without constraining development. For example, in
5 land use, widespread planting of a single tree species or crops for bioenergy (organic matter turned into
6 renewable energy) could affect food and water supplies. Therefore, if bioenergy is to be relied upon to
7 offset emissions, the right policies and investments are needed (see also Chapter 17).
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