Editing IPCC:AR6/WGIII/Chapter-1 (section)

== 1.4 Drivers and Constraints of Climate Mitigation and System Transitions/Transformation ==

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This section provides a brief assessment of key factors and dynamics that drive, shape and/or limit climate mitigation in (i) '''economic factors''' : which include sectors and services, trade and leakage, finance and investment, and technological innovation; (ii) '''socio-political issues''' : which include political economy, social innovation, and equity and fairness; and (iii) '''institutional factors''' , which comprise policy, legal frameworks and international cooperation.

The AR5 introduced six ‘enabling conditions’ for shifting development pathways which are presented in [[IPCC:Wg3:Chapter:Chapter-4|Chapter 4]] of this report and some of which overlap with the drivers reviewed here. However, the terminology of drivers and constraints have been chosen here to reflect the fact that each of these factors can serve as an enabling condition or a constraint to ambitious climate action depending on the context and how they are deployed. Often one sees the factors exerting both push and pull forces at the same time in the same and across different scales. For example, finance and investments can serve as a barrier or an enabler to climate action ( [[#Battiston--2021|Battiston et al. 2021]] ). Similarly, political economy factors can align in favour of ambitious climate action or act in ways that inhibit strong cooperation and low-carbon transition. The other key insight from the assessment of the system drivers and constraints undertaken below is that none of the factors or conditions by themselves is more or less important than the others. In addition to being deeply intertwined all the factors matter in different measures with each exacting more or less force depending on the prevailing social, economic, cultural and political context. Often achieving accelerated mitigation would require effort to bring several of the factors in alignment in and across multiple levels of political or governance scales.

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=== 1.4.1 Services, Sectors and Urbanisation ===

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Human activities drive emissions primarily through the demand for a wide range of services such as food, shelter, heating/cooling, goods, travel, communication, and entertainment. This demand is fulfilled by various activities often grouped into sectors such as agriculture, industry and commerce. The literature uses a wide range of sectoral definitions to organise data and analysis (Chapter 2). Energy sectors are typically organised into primary energy producers, energy transformation processes (such as power generation and fuel refining), and major energy users such as buildings, industry and transport (Chapters 2 and 5). Other research (Chapter 8) organises data around interacting urban and rural human activities. Land-based activities can be organised into agriculture, forestry and other land-use (AFOLU), or land use, land-use change and forestry (LULUCF) (Chapter 7). Each set of sectoral definitions and analysis offers its own insights.

Sectoral perspectives help to identify and understand the drivers of emissions, opportunities for emissions mitigation, and interactions with resources, other goals and other sectors, including the co-evolution of systems across scales ( [[#Kyle--2016|Kyle et al. 2016]] ; [[#Moss--2016|Moss et al. 2016]] ; [[#Mori--2017|Mori et al. 2017]] ; IPBES 2019). Interactions between sectors and agents pursuing multiple goals is a major theme pervading this assessment.

The ‘nexus’ between energy, water, and land – all key contributors to human well-being – also helps to provide, regulate and support ecosystem and cultural services ( [[#Bazilian--2011|Bazilian et al. 2011]] ; [[#Ringler--2013|Ringler et al. 2013]] ; [[#Smajgl--2016|Smajgl et al. 2016]] ; [[#Albrecht--2018|Albrecht et al. 2018]] ; [[#Brouwer--2018|Brouwer et al. 2018]] ; [[#D’Odorico--2018|D’Odorico et al. 2018]] ; [[#Van%20Vuuren--2019|Van Vuuren et al. 2019]] ), with important implications for cities in managing new systems of transformation ( [[#Thornbush--2013|Thornbush et al. 2013]] ; [[#Wolfram--2016|Wolfram et al. 2016]] ) (Chapter 8). Other important nexuses shaping our planet’s future ( [[#Fajardy--2018|Fajardy et al. 2018]] ) include agriculture, forestry, land use and ecosystem services ( [[#Chazdon--2008|Chazdon 2008]] ; [[#Settele--2016|Settele et al. 2016]] ; [[#Torralba--2016|Torralba et al. 2016]] ; [[#Nesshöver--2017|Nesshöver et al. 2017]] ; [[#Keesstra--2018|Keesstra et al. 2018]] ).

Historically, energy-related GHG emissions were considered a by-product of the increasing scale of human activity, driven by population size, economic activity and technology. That simple notion has evolved greatly over time to become much more complex and diverse, with increasing focus on the provision of energy services ( [[#Cullen--2010|Cullen and Allwood 2010]] ; [[#Bardi--2019|Bardi et al. 2019]] ; [[#Brockway--2019|Brockway et al. 2019]] ; [[#Garrett--2020|Garrett et al. 2020]] ). The demand for agricultural products has historically driven conversion of natural lands (land-use change). AFOLU along with food processing accounts for 21–37% of total net anthropogenic GHG emissions (SRCCL SPM A3). [[#footnote-004|5]]

Continued growth in population and income are expected to continue driving up demand for goods and services (Chapters 2, 3 and 5), with an important role for urbanisation which is proceeding at an unprecedented speed and scale. In the last decade, the urban population grew by 70 million people each year, or about 1.3 million people per week, with urban area expanding by about 102 km 2 per day (Chapter 8). Urban areas account for most (45–87%) of the global carbon footprint (8.1) and the strong and positive correlation between urbanisation and incomes means higher consumption from urban lifestyles will continue driving direct and indirect GHG emissions. Cities provide a conduit to many of the services such as transportation, housing, water, food, medical care and recreation, and other services and urban carbon emissions are driven not only by population and income but also by the form and structure of urban areas (Sections 8.1 and 8.3–8.6). This creates opportunities for decarbonisation through urban planning and purposeful ‘experimentation’ ( [[#Newman--2017|Newman et al. 2017]] ) (Chapter 8).

Human needs and wants evolve over time making the transition toward climate and sustainable development goals either more or less difficult. For example, changes in the composition of goods consumed, such as shifting diets toward a more vegetarian balance, can reduce land-use emissions without compromising the quality of life ( [[#Stehfest--2009|Stehfest et al. 2009]] ; [[#Gough--2017|Gough 2017]] ; [[#van%20Vuuren--2018|van Vuuren et al. 2018]] ; [[#van%20den%20Berg--2019|van den Berg et al. 2019]] ; [[#Hargreaves--2021|Hargreaves et al. 2021]] ; SRCCL SPM B2.3).

Human behaviour and choices, including joint achievement of wider social goals, will play an important part in enabling or hindering climate mitigation and sustainable development ( [[#Shi--2016|Shi et al. 2016]] ), for example, shifting passenger transportation preferences in ways that combine climate, health and sustainable development goals ( [[#Romanello--2021|Romanello et al. 2021]] ).

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=== 1.4.2 Trade, Consumption and Leakage ===

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Emissions associated with international trade account for 20–33 % of global emissions, as calculated using multi-regional input-output analysis ( [[#Wiedmann--2018|Wiedmann and Lenzen 2018]] ). Whether international trade drives an increase or decrease in global GHG emissions depends on the emissions intensity of traded products as well as the influence of trade on relocation of production, with studies reaching diverse conclusions about the net effect of trade openness on CO 2 emissions ( [[IPCC:Wg3:Chapter:Chapter-2#2.4|Section 2.4]] .5). Tariff reduction of low-carbon technologies could facilitate effective mitigation ( [[#de%20Melo--2014|de Melo and Vijil 2014]] ; [[#Ertugrul--2016|Ertugrul et al. 2016]] ; [[#Islam--2016|Islam et al. 2016]] ; [[#WTO--2016|WTO 2016]] ).

The magnitude of carbon leakage (see Glossary) caused by unilateral mitigation in a fragmented climate policy world depends on trade and substitution patterns of fossil fuels and the design of policies ( [[#IPCC--2014a|IPCC 2014a]] , Box 5.4), but its potential significance in trade-exposed energy-intensive sectors ( [[#Bauer--2013|Bauer et al. 2013]] ; [[#Carbone--2017|Carbone and Rivers 2017]] ; [[#Naegele--2019|Naegele and Zaklan 2019]] ) can make it an important constraint on policy. See [[#13.6.6.1|Section 13.6.6.1]] in [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] for channels and evidence. [[#Akimoto--2018|Akimoto et al. (2018)]] argue that differences in marginal abatement costs of NDCs could cause carbon leakage in energy-intensive, trade-exposed sectors, and could weaken effective global mitigation.

Policy responses to cope with carbon leakage include border carbon adjustment (BCAs) and differentiated carbon taxes ( [[#Liu--2020|Liu et al. 2020]] ). Some BCA options focusing on levelling the cost of carbon paid by consumers on products could be designed in line with the WTO ( [[#Ismer--2016|Ismer et al. 2016]] ), while others may not be ( [[#Mehling--2019|Mehling et al. 2019]] ). All proposals could involve difficulty of tracing and verifying the carbon content of inputs ( [[#Onder--2012|Onder 2012]] ; [[#Denis-Ryan--2016|Denis-Ryan et al. 2016]] ). An international consensus and certification practice on the carbon content would help to overcome WTO compatibility ( [[#Holzer--2014|Holzer 2014]] ). See [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] and [[#Mehling--2019|Mehling et al. (2019)]] on the context of trade law and the PA.

Official inventories report territorial emissions, which do not consider the impacts embodied in imports of goods. Global supply chains undoubtedly lead to a growth in trade volumes ( [[#Federico--2017|Federico and Tena-Junguito 2017]] ), alternative methods have been suggested to account for emissions associated with international trade, such as shared responsibility ( [[#Lenzen--2007|Lenzen et al. 2007]] ), technology-adjusted consumption-based accounting ( [[#Kander--2015|Kander et al. 2015]] ), value-added-based responsibility ( [[#Piñero--2019|Piñero et al. 2019]] ) and exergy-based responsibility based on thermodynamics ( [[#Khajehpour--2019|Khajehpour et al. 2019]] ). Consumption-based emissions (i.e., attribution of emissions related to domestic consumption and imports to final destination) are not officially reported in global emissions datasets but data has improved ( [[#Tukker--2013|Tukker and Dietzenbacher 2013]] ; [[#Afionis--2017|Afionis et al. 2017]] ). This analysis has been used extensively for consumption-based accounting of emissions, and other environmental impacts ( [[#Wiedmann--2018|Wiedmann and Lenzen 2018]] ; [[#Malik--2019|Malik et al. 2019]] ) ( [[IPCC:Wg3:Chapter:Chapter-2#2.3|Section 2.3]] ).

Increasing international trade has resulted in a general shifting of fossil fuel-driven emissions-intensive production from developed to developing countries ( [[#Arto--2014|Arto and Dietzenbacher 2014]] ; [[#Malik--2016|Malik and Lan 2016]] ), and between developing countries ( [[#Zhang--2019|Zhang et al. 2019]] ). High-income developed countries thus tend to be net importers of emissions, whereas low/middle-income developing countries net exporters ( [[#Peters--2011|Peters et al. 2011]] ) (Figure 1.2c, d). This trend is shifting, with a growth in trade between non-OECD countries ( [[#Meng--2018|Meng et al. 2018]] ; [[#Zhang--2019|Zhang et al. 2019]] ), and a decline in emissions intensity of traded goods ( [[#Wood--2020b|Wood et al. 2020b]] ).

The Paris Agreement primarily deals with national commitments relating to domestic emissions and removals, hence emissions from international aviation and shipping are not covered. Aviation and shipping accounted for approximately 2.7% of greenhouse gas emissions in 2019 (before COVID-19); see [[#10.5.2|Section 10.5.2]] for discussion. In addition to CO 2 emissions, aircraft-produced contrail cirrus clouds, and emissions of black carbon and short-lived aerosols (e.g., sulphates) from shipping are especially harmful for the Arctic ( [[#10.8|Section 10.8]] and Box 10.6).

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=== 1.4.3 Technology ===

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The rapid developments in technology over the past decade enhance potential for transformative changes, in particular to help deliver climate goals simultaneously with other SDGs.

The fall in renewable energy costs alongside rapid growth in capacity (Figure 1.3; see also Figures 6.8 and 6.11 in Chapter 6) has been accompanied by varied progress in many other technology areas such as electric vehicles, fuel cells for both stationary and mobile applications ( [[#Dodds--2019|Dodds 2019]] ), thermal energy (Chapter 6), and battery and other storage technologies ( [[#Freeman--2017|Freeman et al. 2017]] ) (Chapters 6, 9 and 12; Figure TS.7). Nuclear contributions may be enhanced by new generations of reactors (e.g., Generation III) and small modular reactors ( [[#Knapp--2018|Knapp and Pevec 2018]] ) (Chapter 6).

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[[File:cda759d1f20fb59f7745037adefe6c14 IPCC_AR6_WGIII_Figure_1_3.png]]

'''Figure 1.3 | Cost reductions and adoption in solar photovoltaic and wind energy.''' Fossil fuel Levelised Cost of Electricity (LCOE) is indicated by blue shading at USD50–177 MWh –1 ( [[#IRENA--2020b|IRENA 2020b]] ). Source: data from IRENA (2021a,b).

Large-scale hydrogen developments could provide a complementary energy channel with long-term storage. Like electricity, hydrogen (H 2 ) is an energy vector with multiple potential applications, including in industrial processes such as steel and non-metallic materials production (Chapter 11), for long-range transportation (Chapter 10), and low-temperature heating in buildings (Chapter 9). Emissions depend on how it is produced, and deploying H 2 delivery infrastructure economically is a challenge when the future scale of hydrogen demand is so uncertain (Chapter 6). H 2 from natural gas with CO 2 capture and storage (CCS) may help to kick-start the H 2 economy ( [[#Sunny--2020|Sunny et al. 2020]] ).

CO 2 -based fuels and feedstocks such as synthetic methane, methanol, diesel, jet fuel and other hydrocarbons, potentially from carbon capture and utilisation (CCU), represent drop-in solutions with limited new infrastructure needs ( [[#Artz--2018|Artz et al. 2018]] ; [[#Bobeck--2019|Bobeck et al. 2019]] ; [[#Yugo--2019|Yugo and Soler 2019]] ) (Chapter 10). Deployment and development of CCS technologies (with large-scale storage of captured CO 2 ) have been much slower than projected in previous assessments ( [[#IEA--2019b|IEA 2019b]] ; [[#Page--2019|Page et al. 2019]] ) (Chapter 11).

Potential constraints on new energy technologies may include their material requirements, notably rare earth materials for electronics or lithium for batteries ( [[#Wanger--2011|Wanger 2011]] ; [[#Flexer--2018|Flexer et al. 2018]] ), stressing the importance of recycling ( [[#IPCC--2011b|IPCC 2011b]] ; [[#Rosendahl--2019|Rosendahl and Rubiano 2019]] ). Innovation is enabling greater recycling and reuse of energy-intensive materials ( [[#Shemi--2018|Shemi et al. 2018]] ), and introducing radically new and more environmentally friendly materials, however, still not all materials can be recycled ( [[#Allwood--2014|Allwood 2014]] ).

Bysequestering carbon in biomass and soils, soil carbon management, and other terrestrial strategies could offset hard-to-reduce emissions in other sectors. However, large-scale bioenergy deployment could increase risks of desertification, land degradation, and food insecurity ( [[#IPCC--2019a|IPCC 2019a]] ), and higher water withdrawals ( [[#Hasegawa--2018|Hasegawa et al. 2018]] ; [[#Fuhrman--2020|Fuhrman et al. 2020]] ), though this may be at least partially offset by innovation in agriculture, diet shifts and plant-based proteins contributing to meeting demand for food, feed, fibre and bioenergy (or bioenergy with carbon capture and storage (BECCS) with CCS) ( [[#Havlik--2014|Havlik et al. 2014]] ; [[#Popp--2017|Popp et al. 2017]] ; [[#Köberle--2020|Köberle et al. 2020]] ) (Chapters 5 and 7).

A broad class of more speculative technologies propose to counteract effects of climate change by removing CO 2 from the atmosphere (CDR), or by directly modifying the Earth’s energy balance at a large scale (solar radiation modification or SRM). CDR technologies include ocean iron fertilisation, enhanced weathering and ocean alkalinisation (Council 2015a), along with direct air carbon capture and storage (DACCS). They could potentially draw down atmospheric CO 2 much faster than the Earth’s natural carbon cycle, and reduce reliance on biomass-based removal ( [[#Köberle--2019|Köberle 2019]] ; [[#Realmonte--2019|Realmonte et al. 2019]] ), but some present novel risks to the environment and DACCS is currently more expensive than most other forms of mitigation ( [[#Fuss--2018|Fuss et al. 2018]] ) (Cross-Chapter Box 8 in Chapter 12). Solar radiation modification (SRM) could potentially cool the planet rapidly at low estimated direct costs by reflecting incoming sunlight (Council 2015b), but entails uncertain side effects and thorny international equity and governance challenges ( [[#Netra--2018|Netra et al. 2018]] ; [[#Florin--2020|Florin et al. 2020]] ; [[#National%20Academies%20of%20Sciences--2021|National Academies of Sciences 2021]] ) (Chapter 14). Understanding the climate response to SRM remains subject to large uncertainties (AR6 WGI). Some literature uses the term ‘geoengineering’ for both CDR or SRM when applied at a planetary scale ( [[#Shepherd--2009|Shepherd 2009]] ; [[#GESAMP--2019|GESAMP 2019]] ). In this report, CDR and SRM are discussed separately, reflecting their very different geophysical characteristics.

Large improvements in information storage, processing, and communication technologies, including artificial intelligence, will affect emissions. They can enhance energy-efficient control, reduce transaction costs for energy production and distribution, improve demand-side management (DSM) ( [[#Raza--2015|Raza and Khosravi 2015]] ), and reduce the need for physical transport ( [[#Smidfelt%20Rosqvist--2016|Smidfelt Rosqvist and Winslott Hiselius 2016]] ) (Chapters 5, 6 and 9–11). However, data centres and related IT systems (including blockchain), are electricity-intensive and will raise demand for energy ( [[#Avgerinou--2017|Avgerinou et al. 2017]] ) – cryptocurrencies may be a major global source of CO 2 if the electricity production is not decarbonised ( [[#Mora--2018|Mora et al. 2018]] ) – and there is also a concern that Information technologies can compound and exacerbate current inequalities (Chapters 5, 16 and Cross-Chapter Box 11 in Chapter 16). IT may affect broader patterns of work and leisure ( [[#Boppart--2020|Boppart and Krusell 2020]] ), and the emissions intensity of how people spend their leisure time will become more important (Chapters 5 and 9). Because higher efficiency tends to reduces costs, it often involves some ‘rebound’ offsetting at least some of the emission savings ( [[#Sudbury--2016|Sudbury and Hutchinson 2016]] ; [[#Belkhir--2018|Belkhir and Elmeligi 2018]] ; [[#Cohen--2019|Cohen and Cavoli 2019]] ).

Technology can enable both emissions reductions and/or increased emissions (Chapter 16). Governments play an important role in most major innovations, in both ‘technology-push’ ( [[#Mazzucato--2013|Mazzucato 2013]] ) and induced by ‘demand-pull’ ( [[#Grubb--2021a|Grubb et al. 2021a]] ), so policy is important in determining its pace, direction and utilisation (Roberts and Geels 2019a) (Sections 1.7.1 and 1.7.3). Overall, the challenge will be to enhance the synergies and minimise the trade-offs and rebounds, including taking account of ethical and distributional dimensions ( [[#Gonella--2019|Gonella et al. 2019]] ).

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=== 1.4.4 Finance and Investment ===

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Finance is both an enabler and a constraint on mitigation, and since AR5, attention to the financial sector’s role in mitigation has grown. This is partly in the context of the Paris Agreement finance articles and the Green Climate Fund, the pledge to mobilise USD100 billion yr –1 by 2020, and the Addis Abbaba Action Agenda ( [[#1.3.1|Section 1.3.1]] ). However, there is a persistent but uncertain gap in mitigation finance ( [[#Cui--2018|Cui and Huang 2018]] ) (Table 15.15.1), even though tracked climate finance overwhelmingly goes toward mitigation compared to adaptation ( [[#UNEP--2020|UNEP 2020]] ) ( [[#15.3|Section 15.3]] ; Working Group II). Green bond issuance has increased recently in parallel with efforts to reform the international financial system by supporting development of local capital markets ( [[#15.6.4|Section 15.6.4]] ).

Climate finance is a multi-actor, multi-objective domain that includes central banks, commercial banks, asset managers, underwriters, development banks, and corporate planners. Climate change presents both risks and opportunities for the financial sector. The risks include physical risks related to the impacts of climate change itself; transition risks related to the exposure to policy, technology and behavioural changes in line with a low-carbon transition; and liability risks from litigation for climate-related damages (Box 15.2). These could potentially lead to stranded assets (the loss of economic value of existing assets before the end of their useful lifetimes ( [[#Bos--2019|Bos and Gupta 2019]] ) (Sections 6.7 and 15.6.3). Such risks continue to be underestimated by financial institutions ( [[#15.6.1|Section 15.6.1]] ). The continuing expansion of fossil fuel infrastructure and insufficient transparency on how these are valued raises concerns that systemic risk may be accumulating in the financial sector in relation to a potential low-carbon transition that may already be under way ( [[#Battiston--2017|Battiston et al. 2017]] ) ( [[#15.6.3|Section 15.6.3]] ). The Financial Stability Board’s Taskforce on Climate-related Financial Disclosures’ (TCFD) recommendations on transparency aim to ensure that investors and companies consider climate change risks in their strategies and capital allocation ( [[#TCFD--2018|TCFD 2018]] ). This is helping ‘investors to reassess core assumptions’ and may lead to ‘significant’ capital reallocation ( [[#Fink--2020|Fink 2020]] ). However, metrics and indicators of assets risk exposure are inadequate ( [[#Monasterolo--2017|Monasterolo 2017]] ; [[#Campiglio--2018|Campiglio et al. 2018]] ) and transparency alone is insufficient to drive the required asset reallocation in the absence of clear regulatory frameworks ( [[#Ameli--2020|Ameli et al. 2020]] ; [[#Chenet--2021|Chenet et al. 2021]] ). A coalition of central banks have formed the Network for Greening the Financial Sector, to support and advance the transformation of the financial system ( [[#Allen--2020|Allen et al. 2020]] ; [[#NGFS--2020|NGFS 2020]] ), with some of them conducting climate-related institutional stress tests.

Governments cannot single-handedly fund the transition ( [[#15.6.7|Section 15.6.7]] ), least of all in low-income developing countries with large sovereign debt and poor access to global financial markets. Long-term sources of private capital are required to close the financing gap across sectors and geographies ( [[#15.6.7|Section 15.6.7]] ). Future investment needs are greatest in emerging and developing economies ( [[#15.5.2|Section 15.5.2]] ) which already face higher costs of capital, hindering capacity to finance a transition ( [[#Buhr--2018|Buhr et al. 2018]] ; [[#Ameli--2020|Ameli et al. 2020]] ). Requisite North–South financial flows are impeded by both geographic and technological risk premiums ( [[#Iyer--2015|Iyer et al. 2015]] ), and the COVID-19 pandemic has further compromised the ability of developing and emerging economies to finance development activities or attract additional climate finance from developed countries ( [[#15.6.3|Section 15.6.3]] , and Cross-Chapter Box 1 in this chapter). Climate-related investments in developing countries also suffer from structural barriers such as sovereign risk and exchange rate volatility ( [[#Farooquee--2016|Farooquee and Shrimali 2016]] ; [[#Guzman--2018|Guzman et al. 2018]] ) which affect not only climate-related investment but investment in general (Yamahaki et al. 2020) including in needed infrastructure development ( [[#Gray--2003|Gray and Irwin 2003]] ). A Green Climate Fund (GCF) report notes the paradox that USD14 trillion of negative-yielding debt in OECD countries might be expected to flow to much larger low-carbon, climate-resilient investment opportunities in developing countries, but ‘this is not happening’ ( [[#Hourcade--2021b|Hourcade et al. 2021b]] ).

There is often a disconnect between stated national climate ambition and finance flows, and overseas direct investment (ODI) from donor countries may be at odds with national climate pledges such as NDCs. One report found funds supported by foreign state-owned enterprises into 56 recipient countries in Asia and Africa in 2014–2017 went mostly to fossil fuel-based projects not strongly aligned with low-carbon priorities of recipient countries’ NDCs ( [[#Zhou--2018|Zhou et al. 2018]] ). Similarly, [[#Steffen--2019|Steffen and Schmidt (2019)]] found that even within multilateral development banks, ‘public- and private-sector branches differ considerably’, with public-sector lending used mainly in non-renewable and hydropower projects. Political leadership is therefore essential to steer financial flows to support low-carbon transition ( [[#15.6|Section 15.6]] ). [[#Voituriez--2019|Voituriez et al. (2019)]] identify significant mitigation potential if financing countries simply applied their own environmental standards to their overseas investments.

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=== 1.4.5 Political Economy ===

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The politics of interest (most especially economic interest) of key actors at sub-national, national and global levels can be important determinants of climate (in)action ( [[#O’Hara--2009|O’Hara 2009]] ; [[#Lo--2010|Lo 2010]] ; [[#Tanner--2011|Tanner and Allouche 2011]] ; [[#Sovacool--2015|Sovacool et al. 2015]] ; [[#Lohmann--2017|Lohmann 2017]] ; [[#Clapp--2018|Clapp et al. 2018]] ; [[#Newell--2018|Newell and Taylor 2018]] ; [[#Lohmann--2019|Lohmann 2019]] ). Political economy approaches can be crudely divided into ‘economic approaches to politics’, and those used by other social scientists ( [[#Paterson--2018|Paterson and P‐Laberge 2018]] ). The former shows how electoral concerns lead to weak treaties ( [[#Battaglini--2016|Battaglini and Harstad 2016]] ) and when policy negotiations cause status-quo biases and the use of inefficient policy instruments ( [[#Austen-Smith--2019|Austen-Smith et al. 2019]] ) or delays and excessive harmonisation ( [[#Harstad--2007|Harstad 2007]] ). The latter emphasises the central role of structures of power and production, and a commitment to economic growth and capital accumulation in relation to climate action, given the historically central role of fossil fuels to economic development and the deep embedding of fossil energy in daily life ( [[#Newell--2010|Newell and Paterson 2010]] ; [[#Huber--2012|Huber 2012]] ; [[#Di%20Muzio--2015|Di Muzio 2015]] ; [[#Malm--2015|Malm 2015]] ).

The economic centrality of fossil fuels raises obvious questions regarding the possibility of decarbonisation. Economically, this is well understood as a problem of decoupling. But the constraint is also political, in terms of the power of incumbent fossil fuel interests to block initiatives towards decarbonisation ( [[#Jones--2009|Jones and Levy 2009]] ; [[#Newell--2010|Newell and Paterson 2010]] ; [[#Geels--2014|Geels 2014]] ). The effects of climate policy are key considerations in deciding the level of policy ambition and direction and strategies of states ( [[#Lo--2010|Lo 2010]] ; [[#Alam--2013|Alam et al. 2013]] ; [[#Ibikunle--2014|Ibikunle and Okereke 2014]] ), regions ( [[#Goldthau--2015|Goldthau and Sitter 2015]] ), and business actors ( [[#Wittneben--2012|Wittneben et al. 2012]] ), and there is a widespread cultural assumption that continued fossil fuel use is central to this ( [[#Strambo--2020|Strambo and Espinosa 2020]] ). Decarbonisation strategies are often centred around projects to develop new sources of economic activity: carbon markets creating new commodities ( [[#Newell--2010|Newell and Paterson 2010]] ); investment generated in new urban infrastructure ( [[#Whitehead--2013|Whitehead 2013]] ); and/or innovations in a range of new energy technologies ( [[#Fankhauser--2013|Fankhauser et al. 2013]] ; [[#Lachapelle--2017|Lachapelle et al. 2017]] ; [[#Meckling--2018|Meckling and Nahm 2018]] ).

Onefactor limiting the ambition of climate policy has been the ability of incumbent industries to shape government action on climate change ( [[#Newell--1998|Newell and Paterson 1998]] ; [[#Jones--2009|Jones and Levy 2009]] ; [[#Geels--2014|Geels 2014]] ; [[#Breetz--2018|Breetz et al. 2018]] ). Incumbent industries are often more concentrated than those benefiting from climate policy and lobby more effectively to prevent losses than those who would gain ( [[#Meng--2019|Meng and Rode 2019]] ). Drawing upon wider networks ( [[#Brulle--2014|Brulle 2014]] ), campaigns by oil and coal companies against climate action in the United States of America and Australia are perhaps the most well known and largely successful of these ( [[#Pearse--2017|Pearse 2017]] ; [[#Brulle--2020|Brulle et al. 2020]] ; [[#Mildenberger--2020|Mildenberger 2020]] ; [[#Stokes--2020|Stokes 2020]] ), although similar dynamics have been demonstrated in Brazil and South Africa ( [[#Hochstetler--2020|Hochstetler 2020]] ), Canada ( [[#Harrison--2018|Harrison 2018]] ), and Norway and Germany ( [[#Fitzgerald--2019|Fitzgerald et al. 2019]] ), for example. In other contexts, resistance by incumbent companies is more subtle but nevertheless has weakened policy design on emissions trading systems ( [[#Rosembloom--2020|Rosembloom and Markard 2020]] ), and limited the development of alternative-fuelled automobiles ( [[#Levy--2003|Levy and Egan 2003]] ; [[#Wells--2012|Wells and Nieuwenhuis 2012]] ).

The interaction of politics, power and economics is central in explaining why countries with higher per-capita emissions, which logically have more opportunities to reduce emissions, in practice often take the opposite stance, and conversely, why some low-emitting countries may find it easier to pursue climate action because they have fewer vested interests in high-carbon economies. These dynamics can arise from the vested interest of state-owned enterprises (SOEs) ( [[#Wittneben--2012|Wittneben et al. 2012]] ; [[#Polman--2015|Polman 2015]] ; [[#Wright--2017|Wright and Nyberg 2017]] ), the alignment and coalitions of countries in climate negotiations ( [[#Gupta--2016|Gupta 2016]] ; [[#Okereke--2016|Okereke and Coventry 2016]] ), and the patterns of opposition to or support for climate policy among citizens ( [[#Baker--2015|Baker 2015]] ; [[#Swilling--2016|Swilling et al. 2016]] ; [[#Heffron--2018|Heffron and McCauley 2018]] ; [[#Ransan-Cooper--2018|Ransan-Cooper et al. 2018]] ; [[#Turhan--2019|Turhan et al. 2019]] ).

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=== 1.4.6 Equity and Fairness ===

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Equity and fairness can serve as both drivers and barriers to climate mitigation at different scales of governance. Literature regularly highlights equity and justice issues as critical components in local politics and international diplomacy regarding all SDGs, such as goals for no poverty, zero hunger, gender equality, affordable clean energy, reducing inequality, but also for climate action (SDG 13) ( [[#Marmot--2018|Marmot and Bell 2018]] ; [[#Spijkers--2018|Spijkers 2018]] ). Equity issues help explain why it has proved hard to reach more substantive global agreements, as it is hard to agree on a level of greenhouse gas (GHG) mitigation (or emissions) and how to distribute mitigation efforts among countries ( [[#Kverndokk--2018|Kverndokk 2018]] ) for several reasons. First, an optimal trade-off between mitigation costs and damage costs of climate change depends on ethical considerations, and simulations from integrated assessment models using different ethical parameters producing different optimal mitigation paths ( [[#IPCC--2018b|IPCC 2018b]] ) ( [[IPCC:Wg3:Chapter:Chapter-3#3.6.1|Section 3.6.1]] .2). Second, treaties that are considered unfair may be hard to implement ( [[#Klinsky--2017|Klinsky et al. 2017]] ; [[#Liu--2017|Liu et al. 2017]] ). Lessons from experimental economics show that people may not accept a distribution that is considered unfair, even if there is a cost of not accepting ( [[#Gampfer--2014|Gampfer 2014]] ). As equity issues are important for reaching deep decarbonisation, the transition towards sustainable development ( [[#Evans--2016|Evans and Phelan 2016]] ; [[#Heffron--2018|Heffron and McCauley 2018]] ; [[#Okereke--2018|Okereke 2018]] ) depends on taking equity seriously in climate policies and international negotiations ( [[#Okereke--2016|Okereke and Coventry 2016]] ; [[#Klinsky--2017|Klinsky et al. 2017]] ; [[#Martinez--2019|Martinez et al. 2019]] ).

Climate change and climate policies affect countries and people differently. Low-income countries tend to be more dependent on primary industries (agriculture and fisheries, etc.) than richer countries, and their infrastructure may be less robust to tackle more severe weather conditions. Within a country, the burdens may not be equally distributed either, due to policy measures implemented and from differences in vulnerability and adaptive capacity following from e.g. income and wealth distribution, race and gender. For instance, unequal social structures can result in women being more vulnerable to the effects of climate change compared to men, especially in poor countries ( [[#Arora-Jonsson--2011|Arora-Jonsson 2011]] ; [[#Jost--2016|Jost et al. 2016]] ; [[#Rao--2019|Rao et al. 2019]] ). Costs of mitigation also differ across countries. Studies show there are large disparities of economic impacts of NDCs across regions, and also between relatively similar countries when it comes to the level of development, due to large differences in marginal abatement costs for the emission-reduction goal of NDCs ( [[#Fujimori--2016|Fujimori et al. 2016]] ; [[#Hof--2017|Hof et al. 2017]] ; [[#Akimoto--2018|Akimoto et al. 2018]] ; Evans &amp; Gabbatiss 2019). Equalising the burdens from climate policies may give more support for mitigation policies ( [[#Maestre-Andrés--2019|Maestre-Andrés et al. 2019]] ).

Taking equity into account in designing an international climate agreement is complicated as there is no single universally accepted equity criterion, and countries may strategically choose a criterion that favours them ( [[#Lange--2007|Lange et al. 2007]] , 2010). Still, several studies analyse the consequences of different social preferences in designing climate agreements, such as, for instance, inequality aversion, sovereignty and altruism (Anthoff et al. 2010; [[#Kverndokk--2014|Kverndokk et al. 2014]] ).

International transfers from rich to poor countries to support mitigation and adaptation activities may help with equalising burdens, as agreed upon in the [[#UNFCCC--1992|UNFCCC (1992)]] (Chapters 14 and 15), such that they may be motivated by strategic as well as equity reasons ( [[#Kverndokk--2018|Kverndokk 2018]] ) ( [[#1.4.4|Section 1.4.4]] ).

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=== 1.4.7 Social Innovation and Behaviour Change ===

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Social and psychological factors affect both perceptions and behaviour ( [[#Weber--2015|Weber 2015]] ; [[#Whitmarsh--2021|Whitmarsh et al. 2021]] ). Religion, values, culture, gender, identity, social status and habits strongly influence individual behaviours and choices, and therefore sustainable consumption (Sections 1.6.3.1 and 5.2). Identities can provide powerful attachments to consumption activities and objects that inhibit shifts away from them ( [[#Brekke--2003|Brekke et al. 2003]] ; [[#Bénabou--2011|Bénabou and Tirole 2011]] ; [[#Stoll-Kleemann--2017|Stoll-Kleemann and Schmidt 2017]] ; [[#Ruby--2020|Ruby et al. 2020]] ). Consumption is a habit-driven and social practice rather than simply a set of individual decisions, making shifts in consumption harder to pursue ( [[#Evans--2012|Evans et al. 2012]] ; [[#Shove--2013|Shove and Spurling 2013]] ; [[#Kurz--2015|Kurz et al. 2015]] ; [[#Warde--2017|Warde 2017]] ; [[#Verplanken--2021|Verplanken and Whitmarsh 2021]] ). Finally, shifts towards low-carbon behaviour are also inhibited by social-psychological and political dynamics that cause individuals to ignore the connections from daily consumption practices to climate change impacts ( [[#Norgaard--2011|Norgaard 2011]] ; [[#Brulle--2019|Brulle and Norgaard 2019]] ).

As a notable example, plant-based alternatives to meat could reduce emissions from diets ( [[#Eshel--2019|Eshel et al. 2019]] ; [[#Willett--2019|Willett et al. 2019]] ). However, diets are deeply entrenched in cultures and identities, and hard to change ( [[#Fresco--2015|Fresco 2015]] ; [[#Mylan--2018|Mylan 2018]] ). Changing diets also raises cross-cultural ethical issues, in addition to meat’s role in providing nutrition ( [[#Plumwood--2004|Plumwood 2004]] ). Henceforth, some behaviours that are harder to change will only be transformed by the transition itself: triggered by policies, the transition will bring about technologies that, in turn, will entrench new sustainable behaviours.

Behaviour can be influenced through a number of mechanisms besides economic policy and regulation, such as information campaigns, advertising and ‘nudging’. Innovations and infrastructure also impact behaviour, as with bicycle lanes to reduce road traffic. Wider social innovations also have indirect impacts. Education is increasing across the world, and higher education will have impacts on fertility, consumption and the attitude towards the environment ( [[#Osili--2008|Osili and Long 2008]] ; [[#Hamilton--2011|Hamilton 2011]] ; [[#McCrary--2011|McCrary and Royer 2011]] ). Reducing poverty and improvements in health and reproductive choice will also have implications for fertility, energy use and consumption globally. Finally, social capital and the ability to work collectively may have large consequences for mitigation and the ability to adapt to climate change ( [[#Adger--2009|Adger 2009]] ; [[#IPCC--2014a|IPCC 2014a]] [[IPCC:Wg3:Chapter:Chapter-4#4.3|Section 4.3]] .5).

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<span id="policy-impacts"></span>
=== 1.4.8 Policy Impacts ===

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Transformation to different systems will hinge on conscious policy to change the direction in which energy, land use, agriculture and other key sectors develop ( [[#Bataille--2016|Bataille et al. 2016]] ) (Chapters 13 and 16). Policy plays a central role in in land-related systems (Chapter 7), urban development (Chapter 8), improving energy efficiency in buildings (Chapter 9) and transport/mobility (Chapter 10), and decarbonising industrial systems (Chapter 11).

Policy has been and will be central not only because GHG emissions are almost universally under-priced in market economies ( [[#Stern--2017|Stern and Stiglitz 2017]] ; [[#World%20Bank--2019|World Bank 2019]] ), and because of inadequate economic incentives to innovation ( [[#Jaffe--2005|Jaffe et al. 2005]] ), but also due to various delay mechanisms ( [[#Karlsson--2020|Karlsson and Gilek 2020]] ) and multiple sources of path-dependence and lock-in to existing systems ( [[#1.8.2|Section 1.8.2]] ), including: ‘Infrastructure developments and long-lived products that lock societies into GHG-intensive emissions pathways may be difficult or very costly to change, reinforcing the importance of early action for ambitious mitigation ( ''robust evidence'' , ''high agreement'' ).’ (AR5 WGIII p.18).

Many hundreds of policies have been introduced explicitly to mitigate GHG emissions, improve energy efficiency or land use, or to foster low-carbon industries and innovation, with demonstrable impact. The role of policy to date has been most evident in energy efficiency (Sections 5.4 and 5.6) and electricity (Chapter 6). The IPCC Special Report on Renewable Energy already found that: ‘Government policies play a crucial role in accelerating the deployment of RE technologies’ ( [[#IPCC--2011a|IPCC 2011a]] , p. 24). Policy packages since then have driven rapid expansion in renewables capacity and cost reductions (e.g., through the German ''Energiewende'' ), and emission reductions from electricity (most dramatically with the halving of CO 2 emissions from the UK power sector, driven by multiple policy instruments and regulatory changes), as detailed in [[IPCC:Wg3:Chapter:Chapter-6|Chapter 6]] ( [[IPCC:Wg3:Chapter:Chapter-6#6.7.5|Section 6.7.5]] ).

[https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] charts the international evolution of policies and many of the lessons drawn. Attributing the overall impact on emissions is complex, but an emerging literature of several hundred papers indicates impacts on multiple drivers of emissions. Collectively, policies are likely to have curtailed global emissions growth by several GtCO 2 -eq annually already by the mid-2010s (Cross-Chapter Box 10 in Chapter 14). This suggests initial evidence that policy has driven some decoupling (Figure 1.1d) and started to ‘bend the curve’ of global emissions, but more specific attribution to observed trends is not as yet possible. [[#footnote-003|6]]

However, some policies (e.g., subsidies to fossil fuel production or consumption) increase emissions, whilst others (e.g., investment protection) may constrain efforts at mitigation. Also, wider economic and developmental policies have important direct and indirect impacts on emissions. Policy is thus both a driver and a constraint on mitigation.

Synergies and trade-offs arise partly because of the nexus of GHG emissions with other adverse impacts (e.g., local air pollution) and critical resources (e.g., water and food) ( [[#Conway--2015|Conway et al. 2015]] ; [[#Andrews-Speed--2017|Andrews-Speed and Dalin 2017]] ), which also imply interacting policy domains.

The literature shows increasing emphasis on policy packages, including those spanning the different levels of niche/behaviour; existing regimes governing markets and public actors; and strategic and landscape levels ( [[#1.7.3|Section 1.7.3]] ). Chapters 13, 16 and 17 appraise policies for transformation in the context of sustainable development, indicating the importance of policy as a driver at multiple levels and across many actors, with potential for benefits as well as costs at many levels.

National-level legislation may be particularly important to the credibility and long-term stability of policy to reduce the risks, and hence cost, of finance (Chapters 13 and 15), and for encouraging private-sector innovation at scale (Chapter 16), for example, if it offers greater stability and mid-term predictability for carbon prices; [[#Nash--2019|Nash and Steurer (2019)]] find that seven national climate change acts in European countries all act as ‘living policy processes, though to varying extents’.

The importance of policy at multiple levels does not lessen the importance of international policy, for reasons including long-term stability, equity, and scope, but examples of effective implementation policy at international levels remain fewer and governance weaker (Chapter 14).

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=== 1.4.9 Legal Framework and Institutions ===

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Institutions are rules and norms held in common by social actors that guide, constrain and shape human interaction ( [[#IPCC--2018b|IPCC 2018b]] ). Institutions can be formal, such as laws and policies, or informal, such as norms and conventions. Institutions can both facilitate or constrain climate policymaking and implementation in multiple ways. Institutions set the economic incentives for action or inaction on climate change at national, regional and individual levels ( [[#Dorsch--2017|Dorsch and Flachsland 2017]] ; [[#Sullivan--2017|Sullivan 2017]] ).

Institutions entrench specific political decision-making processes, often empowering some interests over others, including powerful interest groups who have vested interests in maintaining the current high-carbon economic structures ( [[#Okereke--2010|Okereke and Russel 2010]] ; [[#Wilhite--2016|Wilhite 2016]] ; [[#Engau--2017|Engau et al. 2017]] ); see also [[#1.4.6|Section 1.4.6]] and [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] on the sub-national and national governance challenges including coordination, mediating politics and strategy setting.

Some suggest that societal transformation towards a low-carbon future requires new politics that involves thinking in intergenerational time horizons, as well as new forms of partnerships between private and public actors ( [[#Westman--2018|Westman and Broto 2018]] ), and associated institutions and social innovations to increase involvement of non-state actors in climate governance ( [[#Fuhr--2018|Fuhr et al. 2018]] ). However literature is divided as to how much democratisation of climate politics, with greater emphasis on equity and community participation, would advance societal transformation in the face of climate change ( [[#Stehr--2005|Stehr 2005]] ), or may actually hinder radical climate action in some circumstances ( [[#Povitkina--2018|Povitkina 2018]] ).

Since 2016, the number of climate litigation cases has increased rapidly. The UN Environment Programme’s Global Climate Litigation Report: 2020 Status Review ( [[#UNEP--2020|UNEP 2020]] ) noted that between March 2017 and 1 July 2020, the number of cases nearly doubled with at least 1550 climate cases filed in eight countries. Several important cases such as Urgenda Foundation vs The State of the Netherlands (‘Urgenda’) and Juliana et al. vs United States (‘Juliana’) have had ripple effects, inspiring other similar cases ( [[#Lin--2020|Lin and Kysar 2020]] ).

Numerous international climate governance initiatives engage national and sub-national governments, NGOs and private corporations, constituting a ‘regime complex’ ( [[#Raustiala--2004|Raustiala and Victor 2004]] ; [[#Keohane--2011|Keohane and]] [[#Victor--2011|Victor 2011]] ). They may have longer-run and second-order effects if commitments are more precise and binding ( [[#Kahler--2017|Kahler 2017]] ). However, without targets, incentives, defined baselines or monitoring, reporting, and verification, they are not likely to fill the ‘mitigation gap’ ( [[#Michaelowa--2017|Michaelowa and Michaelowa 2017]] ).

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<span id="international-cooperation"></span>
=== 1.4.10 International Cooperation ===

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Tackling climate change is often mentioned as an important reason for strong international cooperation in the 21st century ( [[#Falkner--2016|Falkner 2016]] ; [[#Keohane--2016|Keohane and Victor 2016]] ; [[#Bodansky--2017|Bodansky et al. 2017]] ; [[#Cramton--2017b|Cramton et al. 2017b]] ). Mitigation costs are borne by countries taking action, while the benefits of reduced climate change are not limited to them, being in economic terms ‘global and non-excludable’. Hence anthropogenic climate change is typically seen as a global commons problem ( [[#Falkner--2016|Falkner 2016]] ; [[#Wapner--2017|Wapner and Elver 2017]] ). Moreover, the belief that mitigation will raise energy costs and may adversely affect competitiveness creates incentives for free riding, where states avoid taking their fair share of action ( [[#Barrett--2005|Barrett 2005]] ; [[#Keohane--2016|Keohane and Victor 2016]] ). International cooperation has the potential to address these challenges through collective action ( [[#Tulkens--2019|Tulkens 2019]] ) and international institutions offer the opportunity for actors to engage in meaningful communication and exchange of ideas about potential solutions ( [[#Cole--2015|Cole 2015]] ). International cooperation is also vital for the creation and diffusion of norms and the framework for stabilising expectations among actors ( [[#Pettenger--2016|Pettenger 2016]] ).

Some key roles of the UNFCCC have been detailed by its former heads ( [[#Kinley--2021|Kinley et al. 2021]] ). In addition to specific agreements (most recently the PA) it has enhanced transparency through reporting and data, and generated or reinforced several important norms for global climate action including the principles of equity, common but differentiated responsibility and respective capabilities, and the precautionary principles for maintaining global cooperation among states with unevenly distributed emissions sources, climate impacts, and varying mitigation costs across countries ( [[#Keohane--2016|Keohane and Victor, 2016]] ). In addition to formal negotiations, the annual Conference of the Parties (COPs) have increased awareness, and motivated more ambitious actions, sometimes through the formation of ‘coalitions of the willing’, for example. It provides a structure for measuring and monitoring action towards a global goal ( [[#Milkoreit--2019|Milkoreit and Haapala 2019]] ). International cooperation (including the UNFCCC) can also promote technology development and transfer and capacity building; mobilise finance for mitigation and adaptation; and help address concerns on climate justice ( [[#Okereke--2016|Okereke and Coventry 2016]] ; [[#Chan--2018|Chan et al. 2018]] ) (Chapters 14–16).

A common criticism of international institutions is their limited (if any) powers to enforce compliance ( [[#Zahar--2017|Zahar 2017]] ). As a global legal institution, the PA has little enforcement mechanism ( [[#Sindico--2015|Sindico 2015]] ), but enforcement is not a necessary condition for an instrument to be legally binding ( [[#Bodansky--2016|Bodansky 2016]] ; [[#Rajamani--2016|Rajamani 2016]] ). In reality implementation of specific commitments tends to be high once countries have ratified and a treaty or an agreement is in force ( [[#Bodansky--2016|Bodansky 2016]] ; [[#Rajamani--2016|Rajamani 2016]] ). Often, the problem is not so much of ‘power to enforce compliance or sanction non-compliance’, but the level of ambition (Chapter 14).

However, whilst in most respects a driver, international cooperation has also been characterised as ‘organised hypocrisy’ where proclamations are not matched with corresponding action ( [[#Egnell--2010|Egnell 2010]] ). Various reasons for inadequate progress after 30 years of climate negotiations, have been identified ( [[#Stoddard--2021|Stoddard et al. 2021]] ). International cooperation can also seem to be a barrier to ambitious action when negotiation is trapped in ‘relative-gains’ calculus, in which countries seek to game the regime or gain leverage over one another ( [[#Purdon--2017|Purdon 2017]] ), or where states lower ambition to the ‘least common dominator’ to accommodate participation of the least ambitious states ( [[#Falkner--2016|Falkner 2016]] ). [[#Geden--2016|Geden (2016)]] and [[#Dubash--2020|Dubash (2020)]] offer more nuanced assessments.

International collaboration works best if an agreement can be made self-reinforcing with incentives for mutual gains and joint action ( [[#Barrett--2016|Barrett 2016]] ; [[#Keohane--2016|Keohane and Victor 2016]] ), but the structure of the climate challenge makes this hard to achieve. The evidence from the Montreal Protocol on ozone-depleting substances and from the Kyoto Protocol on GHGs, is that legally binding targets have been ''effective'' in that participating Parties complied with them ( [[#Shishlov--2016|Shishlov et al. 2016]] ; [[#Albrecht--2019|Albrecht and Parker 2019]] ), and (for Kyoto) these account for most of the countries that have sustained emission reductions for at least the past 10 to 15 years (Sections 1.3.2 and 2.2). However, such binding commitments may deter ''participation'' if there are no clear incentives to sustain participation and especially if other growing emitters are omitted by design, as with the Kyoto Protocol. Consequently the USA refused to ratify (and Canada withdrew), particularly on the grounds that developing countries had no targets; with participation in Kyoto’s second period commitments declining further, the net result was limited global progress in emissions under Kyoto ( [[#Bodansky--2016|Bodansky 2016]] ; [[#Okereke--2016|Okereke and Coventry 2016]] ; [[#Scavenius--2018|Scavenius and Rayner 2018]] ) despite full legal compliance in both commitment periods (Chapter 14).

The negotiation of the Paris Agreement was thus done in the context of serious questions about how best to structure international climate cooperation to achieve better results. This new agreement is designed to sidestep the fractious bargaining which characterised international climate cooperation ( [[#Marcu--2017|Marcu 2017]] ). It contains a mix of hard, soft and non-obligations, the boundaries between which are blurred, but each of which plays a distinct and valuable role ( [[#Rajamani--2016|Rajamani 2016]] ). The provisions of the PA could encourage flexible responses to changing conditions, but limit assurances of ambitious national commitments and their fulfilment ( [[#Pickering--2018|Pickering et al. 2018]] ). The extent to which this new arrangement will drive ambitious climate policy in the long run remains to be seen (Chapter 14).

Whilst the PA abandoned common accounting systems and time frames, outside of the UNFCCC many other platforms and metrics for comparing mitigation efforts have emerged ( [[#Aldy--2015|Aldy 2015]] ). Countries may assess others’ efforts in determining their actions through multiple platforms including the Climate Change Cooperation Index (C3-I), Climate Change Performance Index (CCPI), Climate Laws, Institutions and Measures Index (CLIMI) ( [[#Bernauer--2013|Bernauer and Böhmelt 2013]] ) and Energy Transition Index ( [[#Singh--2019|Singh et al. 2019]] ). International cooperative initiatives between and among non-state (e.g., business, investors and civil society) and sub-national (e.g., city and state) actors have also been emerging, taking the forms of public-private partnerships, private-sector governance initiatives, NGO transnational initiatives, and sub-national transnational initiatives ( [[#Bulkeley--2012|Bulkeley and Schroeder 2012]] ; [[#Hsu--2018|Hsu et al. 2018]] ). Literature is mostly positive about the role of these transnational initiatives in facilitating climate action across scales although criticism and caution about their accountability and effectiveness remain ( [[#Chan--2016|Chan et al. 2016]] ; [[#Michaelowa--2017|Michaelowa and Michaelowa 2017]] ; [[#Roger--2017|Roger et al. 2017]] ; [[#Widerberg--2017|Widerberg and Pattberg 2017]] ) (Chapter 14).

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