Editing IPCC:AR6/WGIII/TS (section)

== TS.7 Mitigation in the Context of Sustainable Development ==

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Accelerating climate mitigation ''in the context of sustainable development'' involves not only expediting the pace of change but also addressing the underlying drivers of vulnerability and emissions. Addressing these drivers can enable diverse communities, sectors, stakeholders, regions and cultures to participate in just, equitable and inclusive processes that improve the health and well-being of people and the planet. Looking at climate change from a justice perspective also means placing the emphasis on: (i) the protection of vulnerable populations from the impacts of climate change, (ii) mitigating the effects of low-carbon transformations, and (iii) ensuring an equitable decarbonised world ( ''high confidence'' ). {17.1}

'''The SDG framework''' [[#footnote-000|33]] '''can serve as a template to evaluate the long-term implications of mitigation on sustainable development and vice versa (''' '''''high confidence''''' '''). Understanding the co-benefits and trade-offs associated with mitigation is key to understanding how societies prioritise among the various sectoral policy options (''' '''''medium confidence''''' ''').''' Areas with anticipated trade-offs include food and biodiversity, energy affordability/access, and mineral-resource extraction. Areas with anticipated co-benefits include health, especially regarding air pollution, clean energy access and water availability. The possible implementation of the different sectoral mitigation options therefore depends on how societies prioritise mitigation versus other products and services: not least, how societies prioritise food, material well-being, nature conservation and biodiversity protection, as well as considerations such as their future dependence on CDR. Figure TS.29 summarises the assessment of where key synergies and trade-offs exist between mitigation options and the SDGs. (Figures TS.29 and TS.31, Table TS.7) {12.3, 12.4, 12.5, 12.6.1, Figures 3.39 and 17.1}

'''The beneficial and adverse impacts of deploying climate-change mitigation and adaptation responses are highly context-specific and scale-dependent. There are synergies and trade-offs between adaptation and mitigation as well as synergies and trade-offs with sustainable development (''' '''''high confidence''''' ''').''' Strong links also exist between sustainable development, vulnerability and climate risks, as limited economic, social and institutional resources often result in low adaptive capacities and high vulnerability, especially in developing countries. Resource limitations in these countries can similarly weaken the capacity for climate mitigation and adaptation. The move towards climate-resilient societies requires transformational or deep systemic change. This has important implications for countries’ sustainable development pathways ( ''medium evidence'' , ''high agreement'' ) ''.'' (Box TS.3, Figure TS.29) {4.5, Figure 4.9, 17.3.3}

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'''Figure TS.29 |''' '''Mitigation options have synergies with many Sustainable Development Goals (SDGs), but there are trade-offs associated with some options especially when implemented at scale.''' The synergies and trade-offs vary widely and depend on the context. Figure presents a summary of the chapter-level qualitative assessment of the synergies and trade-offs for selected mitigation options. Overlaps may exist in the mitigation options assessed and presented by sector and system, and interlinkages with the SDGs might differ depending on the application of that option by sector. Interactions of mitigation options with the SDGs are context-specific and dependent on the scale of implementation. For some mitigation options, these scaling and context-specific issues imply that there are both synergies and trade-offs in relation to specific SDGs. The SDGs are displayed as coloured squares. They indicate whether a synergy, trade-off, or both synergies and trade-offs exist between the SDG and the mitigation option. Confidence levels are indicated through the solidity of the squares. A solid square indicates high confidence, a partially filled square indicates medium confidence, and an outlined square indicates low confidence. The final column in the figure provides a line of sight to the chapters that provide details on context-specificity and scale of implementation. {6.3, 6.4, 6.7, 7.3, 7.4, 7.5, 7.6, 8.2, 8.4, 8.6, 9.4, 9.5, 9.8, Table 9.5, 10.3, 10.4, 10.5, 10.6, 10.8, 11.5, Table 10.3, 17.3, Figure 17.1, Supplementary Material Table 17.SM.1, Annex II.IV.12}

'''Many of the potential trade-offs between mitigation and other sustainable development outcomes depend on policy design and can be compensated or avoided with additional policies and investments, or through policies that integrate mitigation with other SDGs (''' '''''high confidence''''' ''').''' Targeted SDG policies and investments, for example, in the areas of healthy nutrition, sustainable consumption and production, and international collaboration, can support climate change mitigation policies and resolve or alleviate trade-offs ''.'' Trade-offs can also be addressed by complementary policies and investments, as well as through the design of cross-sectoral policies integrating mitigation with the SDGs, and in particular: good health and well-being (SDG 3), zero hunger and nutrition (SDG 2), responsible consumption and production (SDG 12), reduced inequalities (SDG 10), and life on land (SDG 15). (Figures TS.29 and TS.30) {3.7}

'''''Decent living standards''''' ''', which encompasses many SDG dimensions, are achievable at lower energy use than previously thought (''' '''''high confidence''''' ''').''' Mitigation strategies that focus on lowering demand for energy and land-based resources exhibit reduced trade-offs and negative consequences for sustainable development relative to pathways involving either high emissions and climate impacts or pathways with high consumption and emissions that are ultimately compensated by large quantities of BECCS. Figure TS.30 illustrates how, in the case of pathways limiting warming to 1.5°C (&gt;67%), sustainable development policies can lead to overall benefits compared to mitigation policies alone. (Figures TS.22 and TS.30) {3.7, 5.2}

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'''Figure''' '''TS.30 |''' '''Impacts on SDGs of mitigation limiting warming to 1.5°C (&gt;50%) with narrow mitigation policies vs broader sustainable development policies.''' '''Left:''' benefits of mitigation from avoided impacts. '''Middle:''' sustainability co-benefits and trade-offs of narrow mitigation policies (averaged over multiple models). '''Right:''' sustainability co-benefits and trade-offs of mitigation policies integrating Sustainable Development Goals. Scale: 0% means no change compared to 3°C (left) or current policies (middle and right). Green values correspond to proportional improvements, red values to proportional worsening. Note: only the left panel considers climate impacts on sustainable development; the middle and right panels do not. ‘Res’ C&amp;P’ stands for Responsible Consumption and Production (SDG 12). {Figure 3.39}

'''The timing of mitigation actions and their effectiveness will have significant consequences for broader sustainable development outcomes in the longer term (''' '''''high confidence''''' ''').''' Ambitious mitigation can be considered a precondition for achieving the SDGs. {3.7}

'''Adopting coordinated cross-sectoral approaches to climate mitigation can target synergies and minimise trade-offs, both between sectors and between sustainable development objectives (''' '''''high confidence''''' ''').''' This requires integrated planning using multiple-objective-multiple-impact policy frameworks. Strong inter-dependencies and cross-sectoral linkages create both opportunities for synergies and need to address trade-offs related to mitigation options and technologies. This can only be done if coordinated sectoral approaches to climate change mitigation policies are adopted that mainstream these interactions and ensure local people are involved in the development of new products, as well as production and consumption practices. For instance, there can be many synergies in urban areas between mitigation policies and the SDGs but capturing these depends on the overall planning of urban structures and on local integrated policies such as combining affordable housing and spatial planning with walkable urban areas, green electrification and clean renewable energy ( ''medium confidence'' ) ''.'' Integrated planning and cross-sectoral alignment of climate change policies are also particularly evident in developing countries’ NDCs under the Paris Agreement, where key priority sectors such as agriculture and energy are closely aligned with the proposed mitigation and adaptation actions and the SDGs ''.'' {12.6.2, Supplementary Material Table 17.SM.1, 17.3.3}

'''The feasibility of deploying response options is shaped by barriers and enabling conditions across geophysical, environmental-ecological, technological, economic, socio-cultural, and institutional dimensions (''' '''''high confidence''''' ''').''' Accelerating the deployment of response options depends on reducing or removing barriers across these dimensions, as well on establishing and strengthening enabling conditions. Feasibility is context-dependent, and also depends on the scale and the speed of implementation. For example: the institutional, legal and administrative capacity to support deployment varies across countries; the feasibility of options that involve large-scale land-use changes is highly context-dependent; spatial planning has a higher potential in early stages of urban development; the geophysical potential of geothermal is site-specific; and cultural and local conditions may either inhibit or enable demand-side responses. Figure TS.31 summarises the assessment of barriers and enablers for a broad range of sector-specific, and cross-sectoral response options. (Box TS.15) {6.4, 7.4, 8.5, 9.10, 10.8, 12.3}

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'''Figure TS.31''' '''|''' '''Geophysical, environmental-ecological, technological, economic, socio-cultural and institutional factors can enable or act as barriers to the deployment of response options.''' Chapter-level assessment for selected mitigation options. Overlaps may exist in the mitigation options assessed and presented by sector and system, and feasibility might differ depending on the demarcation of that option in each sector. Chapters 6, 8, 9, 10, and 12 assess mitigation response options across six feasibility dimensions: ''geophysical, environmental-ecological, technological, economic, socio-cultural and institutional'' . AFOLU (Chapter 7) and industry (Chapter 11) are not included because of the heterogeneity of options in these sectors. For each dimension, a set of feasibility indicators was identified. Examples of indicators include impacts on land use, air pollution, economic costs, technology scalability, public acceptance and political acceptance (see Box TS.15, and Annex II.IV.11 for a detailed explanation). An indicator could refer to a barrier or an enabler to implementation, or could refer to both a barrier or an enabler, depending on the context, speed, and scale of implementation. Dark blue bars indicate the extent of enablers to deployment within each dimension. This is shown relative to the maximum number of possible enablers, as indicated by the light blue shading. Dark orange bars indicate the extent of barriers to deployment within each dimension. This is shown relative to the maximum number of possible barriers, as indicated by light orange shading. A light grey dot indicates that there is limited or no evidence to assess the option. A dark grey dot indicates that one of the feasibility indicators within that dimension is not relevant for the deployment of the option. The relevant sections in the underlying chapters include references to the literature on which the assessment is based and indicate whether the feasibility of an option varies depending on context (e.g., region), scale (e.g., small, medium or full scale), speed (e.g., implementation in 2030 versus 2050) and warming level (e.g., 1.5°C versus 2°C). {6.4, 8.5, 9.10, 10.8, 12.3, Annex II.IV.11}

'''Alternative mitigation pathways are also associated with different feasibility challenges (''' '''''high confidence''''' ''').''' These challenges are multi-dimensional, context-dependent, malleable to policy and to technological and societal trends. They can also be reduced by putting in place appropriate enabling conditions. Figure TS.32 highlights the dynamic and transient nature of feasibility risks. These risks are transient and concentrated in the decades before mid-century. Figure TS.32 also illustrates how different feasibility dimensions pose differentiated challenges: for example, institutional feasibility challenges are shown as ''unprecedented'' for a high proportion of scenarios, in line with the qualitative literature, but moving from 2030 to 2050 and 2100 these challenges decrease.

'''The feasibility challenges associated with mitigation pathways are predominantly''' '''''institutional''''' '''and''' '''''economic''''' '''rather than''' '''''technological''''' '''and''' '''''geophysical''''' '''(''' '''''medium confidence''''' ''').''' The rapid pace of technological development and deployment in mitigation scenarios is not incompatible with historical records, but rather, institutional capacity is a key limiting factor for a successful transition. Emerging economies appear to have highest feasibility challenges in the near to mid-term. This suggests a key role of policy and technology as enabling factors. (Figure TS.32) {3.8}

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'''Figure TS.3''' '''2 |''' '''The feasibility of mitigation scenarios.''' Figure TS.32 shows the proportion of scenarios in the AR6 scenarios database – falling within the warming level classifications C1 and C3 ( '''C1:''' below 1.5°C (&gt;50%), no or limited overshoot; '''C3:''' below 2°C (&gt;67%)) – that exceed threshold values in 2030, 2050 and 2100 for five dimensions of feasibility (Boxes TS.5 and TS.15). The feasibility dimensions shown are: ''geophysical, technological, economic, socio-cultural and institutional'' . The thresholds shown are: (i) ''plausible'' – range of values based on past historical trends or other peer reviewed assessments; (ii) ''best-case scenario'' – range of values assuming major political support or technological breakthrough; (iii) ''unprecedented'' – values going beyond those observed or reported in peer-reviewed assessments. Overlayed are the Illustrative Mitigation Pathways consistent with SSP2 (LD, SP, Ren: C1 category; Neg, GS: C3 category). The positioning of the illustrative pathways is simply indicative of the general trade-offs over time and across the feasibility dimensions, it is not determined mathematically. (Box TS.5) {3.8}

'''Pathways relying on a broad portfolio of mitigation strategies are more robust and resilient (''' '''''high confidence''''' ''').''' Portfolios of technological solutions reduce the feasibility risks associated with the low-carbon transition. (Figures TS.31 and TS.32, Box TS.15) {3.8}

'''Box TS.15 | A Harmonised Approach to Assessing Feasibility'''

The assessment of feasibility in this report aims to identify barriers and enablers to the deployment of mitigation options and pathways. The assessment organises evidence to support policy decisions, and decisions on actions, that would improve the feasibility of mitigation options and pathways by removing relevant barriers and by strengthening enablers of change.

'''The feasibility of mitigation response options'''
Mitigation response options are assessed against six dimensions of feasibility. Each dimension comprises a key set of indicators that can be evaluated by combining various strands of literature. {Annex II.IV.11, Table 6.1}

The assessment – undertaken by the sectoral chapters in this report – evaluates to what extent each indicator (listed in Box TS.15, Table.1) would be an enabler or barrier to implementation using a scoring methodology (described in detail in Annex II.IV.11). When appropriate, it is also indicated whether the feasibility of an option varies across context, scale, time and temperature goal. The resulting scores provide insight into the extent to which each feasibility dimension enables or inhibits the deployment of the relevant option. It also provides insight into the nature of the effort needed to reduce or remove barriers, thereby improving the feasibility of individual options. {Annex II.IV.11}

'''Box TS.15, Table.1 |''' '''Feasibility dimensions and indicators to assess the barriers and enablers of implementing mitigation options.'''

{| class="wikitable"
|-
| Feasibility dimension

| Indicators

|-
| Geophysical feasibility

| Availability of required geophysical resources:

– Physical potential

– Geophysical resource availability

– Land use

|-
| Environmental-ecological feasibility

| Impacts on environment:

– Air pollution

– Toxic waste, ecotoxicity and eutrophication

– Water quantity and quality

– Biodiversity

|-
| Technological feasibility

| Extent to which the technology can be implemented at scale soon:

– Simplicity

– Technology scalability

– Maturity and technology readiness

|-
| Economic feasibility

| Financial costs and economic effects:

– Costs now, in 2030 and in the long term

– Employment effects and economic growth

|-
| Socio-cultural feasibility

| Public engagement and support, and social impacts:

– Public acceptance

– Effects on health and well-being

– Distributional effects

|-
| Institutional feasibility

| Institutional conditions that affect the implementation of the response option:

– Political acceptance

– Institutional capacity and governance, cross-sectoral coordination

– Legal and administrative capacity

|}

'''The feasibility of mitigation scenarios'''
Scenarios provide internally consistent projections of emission-reduction drivers and help contextualise the scale of deployment and interactions of mitigation strategies. Recent research has proposed and operationalised frameworks for the feasibility assessment of mitigation scenarios. In this report the feasibility assessment of scenarios uses an approach that involves developing a set of multi-dimensional metrics capturing the ''timing'' , ''disruptiveness'' and the ''scale'' of the transformative change within five dimensions: ''geophysical, technological, economic, socio-cultural and institutional,'' as illustrated in Box TS.15, Figure 1.

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'''Box TS.15, Figure 1 |''' '''Steps involved in evaluating the feasibility of scenarios.''' {Figure 3.41} Note: in this approach the ''environmental-ecological'' dimension is captured through different scenarios’ categories.

More than 20 indicators were chosen to represent feasibility dimensions that could be related to scenario metrics. Thresholds of feasibility risks of different intensity were obtained through empirical analysis of historical data and assessed literature. Details of indicators, thresholds, and how they were applied is reported in Annex II.IV.11. {3.8}

'''A wide range of factors have been found to enable sustainability transitions, ranging from technological innovations to shifts in markets, and from policies and governance arrangements to shifts in belief systems and market forces (''' '''''high confidence''''' ''').''' Many of these factors have come together in a co-evolutionary process that has unfolded globally, internationally and locally over several decades ( ''low evidence'' , ''high agreement'' ). Those same conditions that may serve to impede the transition (i.e., organisational structure, behaviour, technological lock-in) can also ‘flip’ to enable both the transition and the framing of sustainable development policies to create a stronger basis for policy support ( ''high confidence'' ). It is important to note that strong shocks to these systems, including accelerating climate change impacts, economic crises and political changes, may provide crucial openings for accelerated transitions to sustainable systems. For example, rebuilding more sustainably after an extreme event, or renewed public debate about the drivers of social and economic vulnerability to multiple stressors ( ''medium confidence'' ) ''.'' {17.4}

'''While transition pathways will vary across countries it is anticipated that they will be challenging in many contexts (''' '''''high confidence''''' ''').''' Climate change is the result of decades of unsustainable production and consumption patterns, as well as governance arrangements and political economic institutions that lock-in resource-intensive development patterns ( ''high confidence'' ). Resource shortages, social divisions, inequitable distributions of wealth, poor infrastructure and limited access to advanced technologies and skilled human resources can constrain the options and capacity of developing countries to achieve sustainable and Just Transitions ( ''medium evidence'' , ''high agreement'' ) {17.1.1} . Reframing development objectives and shifting development pathways towards sustainability can help transform these patterns and practices, allowing space to transform unsustainable systems ( ''medium evidence'' , ''high agreement'' ). {1.6, Cross-Chapter Box 5 in Chapter 4, 17.1, 17.3}

'''The landscape of transitions to sustainable development is changing rapidly, with multiple transitions already underway. This creates the room to manage these transitions in ways that prioritise the needs of workers in vulnerable sectors (e.g., land, energy) to secure their jobs and maintain secure and healthy lifestyles (''' '''''medium evidence, high agreement''''' ''').''' {17.3.2}

'''Actions aligning sustainable development, climate mitigation and partnerships can support transitions. Strengthening different stakeholders’ ‘response capacities’ to mitigate and adapt to a changing climate will be critical for a sustainable transition (''' '''''high confidence''''' ''').''' {17.1}

'''Accelerating the transition to sustainability will be enabled by explicit consideration being given to the principles of justice, equality and fairness (''' '''''high confidence''''' ''').''' {5.2, 5.4, 5.6, 13.2, 13.6, 13.8, 13.9,17.4}

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[[#footnote-032-backlink|1]] The three Special Reports are: Global Warming of 1.5°C: an IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty (2018); Climate Change and Land: an IPCC Special Report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems (2019); IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (2019).

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[[#footnote-031-backlink|2]] Each finding is grounded in an evaluation of the underlying evidence, typeset in italics. The validity of a finding is evaluated in terms of the evidence quality – ‘ ''limited'' ’, ‘ ''medium'' ’, ‘ ''robust'' ’ – and the degree of agreement between sources – ‘ ''low'' ’, ‘ ''medium'' ’, ‘ ''high'' ’. A level of confidence is expressed using five qualifiers: ''very low'' , ''low'' , ''medium'' , ''high'' and ''very high'' . Generally, the level of confidence is highest where there is robust evidence from multiple sources and high agreement. For findings with, for example, ‘ ''robust evidence'' , ''medium agreement'' ’, a confidence statement may not always be appropriate. The assessed likelihood of an outcome or a result is described as: ''virtually certain'' (99–100% probability); ''very likely'' (90–100%); ''likely'' (66–100%); ''about as likely as not'' (33–66%); ''unlikely'' (0–33%); ''very unlikely'' (0–10%); ''exceptionally unlikely'' (0–1%). Additional terms may also be used when appropriate, consistent with the IPCC uncertainty guidance: https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf .

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[[#footnote-030-backlink|3]] Current NDCs refer to Nationally Determined Contributions submitted to the UNFCCC, as well as publicly announced but not yet submitted mitigation pledges with sufficient detail on targets, reflected in studies published up to 11 October 2021. Revised NDCs submitted or announced after 11 October 2021 are not included. Intended Nationally Determined Contributions (INDCs) were converted to NDCs as countries ratified the Paris Agreement. Original INDCs and NDCs refer to those submitted to the UNFCCC in 2015 and 2016.

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[[#footnote-029-backlink|4]] Emissions of GHGs are weighed by global warming potentials (GWPs) with a 100-year time horizon (GWP100) from the Sixth Assessment Report. GWP100 is commonly used in wide parts of the literature on climate change mitigation and is required for reporting emissions under the United Nations Framework Convention on Climate Change (UNFCCC). All metrics have limitations and uncertainties. {Cross-Chapter Box 2, Annex II.II.8}

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[[#footnote-028-backlink|5]] In 2019, CO 2 from fossil fuel and industry (FFI) was 38 ± 3.0 Gt; CO 2 from net land use, land-use change and forestry (LULUCF) was 6.6 ± 4.6 Gt.

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[[#footnote-027-backlink|6]] Fluorinated gases, also known as ‘F-gases’, include: hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluouride (SF 6 ) and nitrogen trifluouride (NF 3 ).

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[[#footnote-026-backlink|7]] IEA: International Energy Agency

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[[#footnote-025-backlink|8]] EDGAR: Emissions Database for Global Atmospheric Research

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[[#footnote-024-backlink|9]] Emission metrics also exist for aerosols, but these are not commonly used in climate policy. This assessment focuses on GHG emission metrics only.

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[[#footnote-023-backlink|10]] The CMA is the Conference of the Parties serving as the Meeting of the Parties to the Paris Agreement. See 18/CMA.1 (Annex, para. 37) and 4/CMA.1 (Annex II, para. 1) regarding the use of GHG emission metrics in reporting of emissions and removals and accounting for Parties’ NDCs.

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[[#footnote-022-backlink|11]] Bookkeeping models and dynamic global vegetation models.

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[[#footnote-021-backlink|12]] Decent Living Standards (DLS) – a benchmark of material conditions for human well-being – overlaps with many Sustainable Development Goals (SDGs). Minimum requirements of energy use consistent with enabling well-being for all is between 20 and 50 GJ per capita yr –1 depending on the context. (Figure TS.22) {5.2.2, 5.2.2, Box 5.3}

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[[#footnote-020-backlink|13]] Current NDCs refers to the most recent Nationally Determined Contributions submitted to the UNFCCC as well as those publicly announced (with sufficient detail on targets, but not yet submitted) up to 11 October 2021, and reflected in literature published up to 11 October 2021. Original INDCs and NDCs refer to those submitted to the UNFCCC in 2015 and 2016.

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[[#footnote-019-backlink|14]] See {4.2.1} for descriptions of ‘unconditional’ and ‘conditional’ elements of NDCs.

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[[#footnote-018-backlink|15]] Submitted by 11 October 2021.

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[[#footnote-017-backlink|16]] Reductions greater than 100% in energy supply and AFOLU indicate that these sectors would become carbon sinks.

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[[#footnote-016-backlink|17]] NDCs announced prior to COP26 refer to the most recent Nationally Determined Contributions submitted to the UNFCCC up to the literature cut-off date of this report, 11 October 2021, and revised NDCs announced by China, Japan and the Republic of Korea prior to October 2021 but only submitted thereafter. 25 NDC updates were submitted between 12 October 2021 and the start of COP26.

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[[#footnote-015-backlink|18]] Numbers in parentheses represent he interquartile range of the scenario samples.

<div id="footnote-014" class="_idFootnote"></div>

[[#footnote-014-backlink|19]] In this assessment the terms ''net zero CO'' 2 emissions and ''carbon neutrality'' have different meanings and are only equivalent at the global scale. At the scale of regions, or sectors, each term applies different system boundaries. This is also the case for the related terms ''net zero GHG'' and ''GHG neutrality'' . {Cross-Chapter Box 3 in Chapter 3}

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[[#footnote-013-backlink|20]] Carbon dioxide capture and utilisation (CCU) refers to a process in which CO 2 is captured and the carbon is then used in a product. The climate effect of CCU depends on the product lifetime, the product it displaces, and the CO 2 source (fossil, biomass or atmosphere). CCU is sometimes referred to as carbon dioxide capture and use, or carbon capture and utilisation.

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[[#footnote-012-backlink|21]] These estimates are based on consumption-based accounting, including both direct emissions from within urban areas, and indirect emissions from outside urban areas related to the production of electricity, goods, and services consumed in cities. Estimates include all CO 2 and CH 4 emission categories except for aviation and marine bunker fuels, land-use change, forestry, and agriculture. {8.1, Annex I: Glossary}

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[[#footnote-011-backlink|22]] These scenarios have been assessed by WGI to correspond to intermediate, high, and very low GHG emissions.

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[[#footnote-010-backlink|23]] These scenarios have been assessed by WGI to correspond to intermediate, high, and very low GHG emissions.

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[[#footnote-009-backlink|24]] These examples are considered to be a subset of ‘nature-based solutions’ or ‘ecosystem-based approaches’.

<div id="footnote-008" class="_idFootnote"></div>

[[#footnote-008-backlink|25]] ‘Active travel’ is travel that requires physical effort, for example journeys made by walking or cycling.

<div id="footnote-007" class="_idFootnote"></div>

[[#footnote-007-backlink|26]] See section TS.5.9.

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[[#footnote-006-backlink|27]] AFOLU is a sector in the ''2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories'' . AFOLU anthropogenic greenhouse gas emissions and removals by sinks reported by governments under the UNFCCC are defined as all those occurring on ‘managed land’. Managed land is land where human interventions and practices have been applied to perform production, ecological or social functions.

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[[#footnote-005-backlink|28]] For example: in the ''2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories'' , CO 2 emissions from biomass used for energy are reported in the AFOLU sector, calculated as an implicit component of carbon stock changes. In the energy sector, CO 2 emissions from biomass combustion for energy are recorded as an information item that is not included in the sectoral total emissions for the that sector.

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[[#footnote-004-backlink|29]] These potentials do not include avoided emissions resulting from bioenergy use associated with BECCS, which depends on energy substitution patterns, conversion efficiencies, and supply chain emissions for both the BECCS and substituted energy systems. Estimates of substitution effects of bioenergy indicate that this additional mitigation would be of the same magnitude as provided through CDR using BECCS. Bio-based products with long service life, for example, construction timber, can also provide mitigation through substitution of steel, concrete, and other products, and through carbon storage in the bio-based product pool. See section TS.5.7 for the CDR potential of BECCS. {7.4, 12.3}

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[[#footnote-003-backlink|30]] As a median value [5–95th percentile range].

<div id="footnote-002" class="_idFootnote"></div>

[[#footnote-002-backlink|31]] Most of climate finance stays within national borders, especially private climate flows (over 90%). The reasons for this range from national policy support, differences in regulatory standards, exchange rate, political and governance risks, to information market failures.

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[[#footnote-001-backlink|32]] Climate finance flows refers to local, national, or transnational financing from public, private, and alternative sources, to support mitigation and adaptation actions addressing climate change.

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[[#footnote-000-backlink|33]] The 17 SDGs are at the heart of the UN 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015.