Editing IPCC:AR6/WGIII/Chapter-5 (section)

== 5.1 Introduction ==

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The ''Sixth Assessment Report'' of the IPCC (AR6), for the first time, features a chapter on demand, services, and social aspects of mitigation. It builds on the AR4 and AR5, which linked behaviour and lifestyle change to mitigating climate change ( [[#IPCC--2007|IPCC 2007]] ; [[#Roy--2009|Roy and Pal 2009]] ; [[#IPCC--2014a|IPCC 2014a]] ), the Global Energy Assessment ( [[#Roy--2012|Roy et al. 2012]] ), and the AR5, which identified sectoral demand-side mitigation options across chapters ( [[#IPCC--2014a|IPCC 2014a]] ; [[#IPCC--2014b|IPCC 2014b]] ; [[#Creutzig--2016b|Creutzig et al. 2016b]] ). The literature on the nature, scale, implementation and implications of demand-side solutions, and associated changes in lifestyles, social norms, and well-being, has been growing rapidly ( [[#Creutzig--2021a|Creutzig et al. 2021a]] ) (Box 5.2). Demand-side solutions support near-term climate change mitigation ( [[#Méjean--2019|Méjean et al. 2019]] ; [[#Wachsmuth--2019|Wachsmuth and Duscha 2019]] ) and include consumers’ technology choices, behaviours, lifestyle changes, coupled with production-consumption infrastructures and systems, service provision strategies, and associated socio-technical transitions. This chapter’s assessment of the social sciences (also see [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-5 Chapter 5] Supplementary Material I) reveals that social dynamics at different levels offer diverse entry points for acting on and mitigating climate change ( [[#Jorgenson--2018|Jorgenson et al. 2018]] ).

Three entry points are relevant for this chapter. First, well-designed demand for services scenarios are consistent with adequate levels of well-being for everyone ( [[#Rao--2012|Rao and Baer 2012]] ; [[#Grubler--2018|Grubler et al. 2018]] ; [[#Mastrucci--2020|Mastrucci et al. 2020]] ; [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ), with high and/or improved quality of life ( [[#Max-Neef--1995|Max-Neef 1995]] ), improved levels of happiness ( [[#Easterlin--2010|Easterlin et al. 2010]] ) and sustainable human development ( [[#Arrow--2013|Arrow et al. 2013]] ; [[#Dasgupta--2017|Dasgupta and Dasgupta 2017]] ).

Second, demand-side solutions support staying within planetary boundaries ( [[#Haberl--2014|Haberl et al. 2014]] ; [[#Matson--2016|Matson et al. 2016]] ; [[#Hillebrand--2018|Hillebrand et al. 2018]] ; [[#Andersen--2020|Andersen and Quinn 2020]] ; [[#UNDESA--2020|UNDESA 2020]] ; [[#Hickel--2021|Hickel et al. 2021]] ; [[#Keyßer--2021|Keyßer and Lenzen 2021]] ). Demand side solutions entail fewer environmental risks than many supply-side technologies ( [[#Von%20Stechow--2016|Von Stechow et al. 2016]] ). Additionally they make carbon dioxide removal technologies, such as bioenergy with carbon capture and storage (BECCS) less relevant ( [[#Van%20Vuuren--2018|Van Vuuren et al. 2018]] ) but modelling studies ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#Hickel--2021|Hickel et al. 2021]] ; [[#Keyßer--2021|Keyßer and Lenzen 2021]] ) still require ecosystem-based carbon dioxide removal. In the IPCC’s Special Report on Global Warming of 1.5°C (SR1.5) ( [[#IPCC--2018|IPCC 2018]] ), four stylised scenarios have explored possible pathways towards stabilising global warming at 1.5°C ( [[#IPCC--2014a|IPCC 2014a]] , Figure SPM.3a) (Figure 5.1) One of these scenarios, LED-19, investigates the scope of demand-side solutions (Figure 5.1). The comparison of scenarios reveals that such low energy demand pathways eliminate the need for technologies with high uncertainty, such as BECCS. Third, interrogating demand for services from the well-being perspective also opens new avenues for assessing mitigation potentials ( [[#Brand-Correa--2017|Brand-Correa and Steinberger 2017]] ; [[#Mastrucci--2017|Mastrucci and Rao 2017]] ; [[#Rao--2018a|Rao and Min 2018a]] ; [[#Mastrucci--2019|Mastrucci and Rao 2019]] ; [[#Baltruszewicz--2021|Baltruszewicz et al. 2021]] ). Arguably, demand-side interventions often operate institutionally or in terms of restoring natural functioning and have so far been politically sidelined but COVID-19 revealed interesting perspectives (Box 5.2). Such demand-side solutions also support near-term goals towards climate change mitigation and reduce the need for politically challenging high global carbon prices ( [[#Méjean--2019|Méjean et al. 2019]] ) (Box 5.11). The well-being focus emphasises equity and universal need satisfaction, compatible with progress towards meeting the Sustainable Development Goals (SDGs) ( [[#Lamb--2017|Lamb and Steinberger 2017]] ).

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[[File:ef7980fb5d46ca39552990f514ac17f8 IPCC_AR6_WGIII_Figure_5_1.png]]

'''Figure 5.1 | Low Energy Demand Scenario needs no BECCS and needs less decarbonisation effort.''' Dependence of the size of the mitigation effort to reach a 1.5°C climate target (cumulative GtCO 2 emission reduction 2020–2100 by option) as a function of the level of energy demand (average global final energy demand 2020–2100 in EJ yr –1 ) in baseline and corresponding 1.5°C scenarios (1.9 W m –2 radiative forcing change) based on the IPCC Special Report on Global Warming of 1.5°C (data obtained from the Scenario Explorer database, LED baseline emission data obtained from authors). In this figure an example of remaining carbon budget of 400 Gt has been taken from [[#Rogelj--2019|Rogelj et al. (2019)]] for illustrative purposes. 400 Gt is also the number given in Table SPM.2 ( [[#IPCC--2021|IPCC 2021]] , p. 29) for a probability of 67% to limit global warming to 1.5°C.

The requisites for well-being include collective and social interactions as well as consumption-based material inputs. Moreover, rather than material inputs ''per se'' , people need and demand services for dignified survival, sustenance, mobility, communication, comfort and material well-being ( [[#Nakićenović--1996b|Nakićenović et al. 1996b]] ; [[#Johansson--2012|Johansson et al. 2012]] ; [[#Creutzig--2018|Creutzig et al. 2018]] ). These services may be provided in many different context-specific ways using physical resources (biomass, energy, materials, etc.) and available technologies (e.g., cooking tools, appliances). Here we understand demand as demand for services (often requiring material input), with particular focus on services that are required for well-being (such as lighting, accessibility, shelter, etc.), and that are shaped by culturally and geographically differentiated social aspects, choice architectures and the built environment (infrastructures).

Focusing on demand for services broadens the climate solution space beyond technological switches confined to the supply side, to include solutions that maintain or improve well-being related to nutrition, shelter and mobility while (sometimes radically) reducing energy and material input levels ( [[#Creutzig--2018|Creutzig et al. 2018]] ; [[#Cervantes%20Barron--2020|Cervantes Barron 2020]] ; [[#Baltruszewicz--2021|Baltruszewicz et al. 2021]] ; [[#Kikstra--2021b|Kikstra et al. 2021b]] ). This also recognises that mitigation policies are politically, economically and socially more feasible, as well as more effective, when there is a two-way alignment between climate action and well-being ( [[#OECD--2019a|OECD 2019a]] ). There is ''medium evidence'' and ''high agreement'' that well-designed demand for services scenarios are consistent with adequate levels of well-being for everyone ( [[#Rao--2012|Rao and Baer 2012]] ; [[#Grubler--2018|Grubler et al. 2018]] ; [[#Rao--2019b|Rao et al. 2019b]] ; [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ; [[#Kikstra--2021b|Kikstra et al. 2021b]] ), with high and/or improved quality of life ( [[#Max-Neef--1995|Max-Neef 1995]] ; [[#Vogel--2021|Vogel et al. 2021]] ) and improved levels of happiness ( [[#Easterlin--2010|Easterlin et al. 2010]] ) and sustainable human development ( [[#Gadrey--2006|Gadrey and Jany-Catrice 2006]] ; [[#Arrow--2013|Arrow et al. 2013]] ; [[#Dasgupta--2017|Dasgupta and Dasgupta 2017]] ). While demand for services is high as development levels increase, and related emissions are growing in many countries ( [[#Yumashev--2020|Yumashev et al. 2020]] ; [[#Bamisile--2021|Bamisile et al. 2021]] ), there is also evidence that provisioning systems delink services provided from emissions ( [[#Conte%20Grand--2016|Conte Grand 2016]] ; Patra et al. 2017; [[#Kavitha--2020|Kavitha et al. 2020]] ). Various mitigation strategies, often classified into Avoid-Shift-Improve (ASI) options, effectively reduce primary energy demand and/or material input ( [[#Haas--2015|Haas et al. 2015]] ; [[#Haberl--2017|Haberl et al. 2017]] ; [[#Samadi--2017|Samadi et al. 2017]] ; [[#Hausknost--2018|Hausknost et al. 2018]] ; [[#Haberl--2019|Haberl et al. 2019]] ; [[#Van%20den%20Berg--2019|Van den Berg et al. 2019]] ; [[#Ivanova--2020|Ivanova et al. 2020]] ). Users’ participation in decisions about how services are provided, not just their technological feasibility, is an important determinant of their effectiveness and sustainability ( [[#Whittle--2019|Whittle et al. 2019]] ; [[#Vanegas%20Cantarero--2020|Vanegas Cantarero 2020]] ).

Sector-specific mitigation approaches (Chapters 6–11) emphasise the potential of mitigation via improvements in energy- and materials-efficient manufacturing ( [[#Gutowski--2013|Gutowski et al. 2013]] ; [[#Gramkow--2019|Gramkow and Anger-Kraavi 2019]] ; [[#Olatunji--2019|Olatunji et al. 2019]] ; [[#Wang--2019|Wang et al. 2019]] ), new product design ( [[#Fischedick--2014|Fischedick et al. 2014]] ), energy-efficient buildings ( [[#Lucon--2014|Lucon et al. 2014]] ), shifts in diet ( [[#Bajželj--2014|Bajželj et al. 2014]] ; [[#Smith--2014|Smith et al. 2014]] ), transport infrastructure design ( [[#Sims--2014|Sims et al. 2014]] ), and compact urban forms ( [[#Seto--2014|Seto et al. 2014]] ). In this chapter, service-related mitigation strategies are categorised as ‘Avoid’, ‘Shift’, or ‘Improve’ options to show how mitigation potentials, and social groups who can deliver them, are much broader than usually considered in traditional sector-specific presentations. ASI originally arose from the need to assess the staging and combinations of inter-related mitigation options in the provision of transportation services ( [[#Hidalgo--2013|Hidalgo and Huizenga 2013]] ). In the context of transportation services, ASI seeks to mitigate emissions through ''avoiding'' as much transport service demand as possible (e.g., through telework to eliminate commutes, mixed-use urban zoning to shorten commute distances), ''shifting'' remaining demand to more efficient modes (e.g., bus rapid transit replacing passenger vehicles), and ''improving'' the carbon intensity of modes utilised (e.g., electric buses powered by renewables) ( [[#Creutzig--2016a|Creutzig et al. 2016a]] ). This chapter summarises ASI options and potentials across sectors and generalises the definitions. ‘Avoid’ refers to all mitigation options that reduce unnecessary (in the sense of being not required to deliver the desired service output) energy consumption by redesigning service provisioning systems; ‘Shift’ refers to the switch to already existing competitive efficient technologies and service provisioning systems; and ‘Improve’ refers to improvements in efficiency in existing technologies. The Avoid-Shift-Improve framing operates in three domains: Socio-cultural, where social norms, culture, and individual choices play an important role – a category especially, but not only, relevant for ‘Avoid’ options; Infrastructure, which provides the cost and benefit landscape for realising options and is particularly relevant for ‘Shift’ options; and Technologies, especially important for the ‘Improve’ options.

‘Avoid’, ‘Shift’, and ‘Improve’ choices will be made by individuals and households, instigated by salient and respected role models and novel social norms, but will require support by adequate infrastructures designed by urban planners and building and transport professionals, corresponding investments, and a political culture supportive of mitigation action. This is particularly true for many ‘Avoid’ and ‘Shift’ decisions that are difficult because they encounter psychological barriers of breaking routines, habits and imagining new lifestyles and the social costs of not conforming to society ( [[#Kaiser--2006|Kaiser 2006]] ). Simpler ‘Improve’ decisions like energy efficiency investments, on the other hand, can be triggered and sustained by traditional policy instruments, complemented by behavioural nudges.

A key concern about climate change mitigation policies is that they may reduce quality of life. Based on growing literature, in this chapter we adopt the concept of decent living standards (DLS, explained further in relation to other individual and collective well-being measures and concepts in the Social Science Primer, [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-5 Chapter 5] Supplementary Material I) as a universal set of service requirements essential for achieving basic human well-being. DLS includes the dimensions of nutrition, shelter, living condition, clothing, health care, education, and mobility ( [[#Frye--2018|Frye et al. 2018]] ; [[#Rao--2018b|Rao and Min 2018b]] ). DLS provides a fair, direct way to understand the basic low-carbon energy needs of society and specifies the underlying minimum material and energy requirements. This chapter also comprehensively assesses related well-being metrics that result from demand-side action, observing overall positive effects ( [[#5.3|Section 5.3]] ). Similarly, ambitious low-emissions demand-side scenarios suggest that well-being could be maintained or improved while reducing global final energy demand, and some current literature estimates that it is possible to meet decent living standards for all within the 2°C warming window ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#Burke--2020|Burke 2020]] ; [[#Keyßer--2021|Keyßer and Lenzen 2021]] ) ( [[#5.4|Section 5.4]] ). A key concern here is how to blend new technologies with social change to integrate Improving ways of living, Shifting modalities and Avoiding certain kinds of emissions altogether ( [[#5.6|Section 5.6]] ).

Social practice theory emphasises that material stocks and social relations are key in forming and maintaining habits ( [[#Reckwitz--2002|Reckwitz 2002]] ; [[#Haberl--2021|Haberl et al. 2021]] ). This chapter reflects these insights by assessing the role of infrastructures and social norms in GHG emission-intensive or low-carbon lifestyles ( [[#5.4|Section 5.4]] ).

A core operational principle for sustainable development is equitable access to services to provide well-being for all, while minimising resource inputs and environmental and social externalities/trade-offs, underpinning the Sustainable Development Goals ( [[#Princen--2003|Princen 2003]] ; [[#Lamb--2017|Lamb and Steinberger 2017]] ; [[#Dasgupta--2017|Dasgupta and Dasgupta 2017]] ). Sustainable development is not possible without changes in consumption patterns within the widely recognised constraints of planetary boundaries, resource availability, and the need to provide decent living standards for all ( [[#Langhelle--2000|Langhelle 2000]] ; [[#Toth--2016|Toth and Szigeti 2016]] ; [[#O’Neill--2018|O’Neill et al. 2018]] ). Inversely, reduced poverty and higher social equity offer opportunities for delinking demand for services from emissions, for example via more long-term decision-making after having escaped poverty traps and by reduced demand for non-well-being-enhancing status consumption ( [[#Nabi--2020|Nabi et al. 2020]] ; [[#Ortega-Ruiz--2020|Ortega-Ruiz et al. 2020]] ; [[#Parker--2020|Parker and Bhatti 2020]] ; [[#Teame--2020|Teame and Habte 2020]] ) ( [[#5.3|Section 5.3]] ).

Throughout this chapter we discuss how people can realise various opportunities to reduce GHG emission-intensive consumption (Sections 5.2 and 5.3), and act in various roles ( [[#5.4|Section 5.4]] ), within an enabling environment created by policy instruments and infrastructure that build on social dynamics ( [[#5.6|Section 5.6]] ).

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=== Box 5.1 | Bibliometric Foundation of Demand-side Climate Change Mitigation ===

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A bibliometric overview of the literature found 99,065 academic peer-reviewed papers identified with 34 distinct search queries addressing relevant content of this chapter ( [[#Creutzig--2021a|Creutzig et al. 2021a]] ). The literature is growing rapidly (15% yr –1 ) and the literature body assessed in the AR6 period (2014–2020) is twice as large as all literature published before.

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[[File:9e074fcb0dda11fd83af4f575ed77e6d IPCC_AR6_WGIII_Box_5_1_Figure_1.png]]

'''Box 5.1, Figure 1 | Map of the literature on demand, services and socialaspects of climate change mitigation.''' Dots show document positions obtained by reducing the 60-dimensional topic scores to two dimensions aiming to preserve similarity in overall topic score. The two axes therefore have no direct interpretation but represent a reduced version of similarities between documents across 60 topics. Documents are coloured by query category. Topic labels of the 24 most relevant topics are placed in the centre of each of the large clusters of documents associated with each topic. % value in caption indicates the proportion of studies in each ‘relevance’ bracket. Source: reused with permission from Creutzig et al. ( 2021a).

A large part of the literature is highly repetitive and/or includes no concepts or little quantitative or qualitative data of relevance to this chapter. For example, a systematic review on economic growth and decoupling identified more than 11,500 papers treating this topic, but only 834 of those, that is, 7%, included relevant data ( [[#Wiedenhofer--2020|Wiedenhofer et al. 2020]] ). In another systematic review, assessing quantitative estimates of consumption-based solutions ( [[#Ivanova--2020|Ivanova et al. 2020]] ), only 0.8% of papers were considered after consistency criteria were enforced. Altogether, we relied on systematic reviews wherever possible. Other important papers were not captured by systematic reviews but are included in this chapter through expert judgement. Based on topical modelling and relevance coding of resulting topics, the full literature body can be mapped into two dimensions, where spatial relationships indicate topical distance (Box 5.1, Figure 1). The interpretation of topics demonstrates that the literature organises in four clusters of high relevance for demand-side solutions (housing, mobility, food, and policy), whereas other clusters (nature, energy supply) are relatively less relevant.

[[#5.2|Section 5.2]] provides evidence on the links among mitigation and well-being, services, equity, trust, and governance. [[#5.3|Section 5.3]] quantifies the demand-side opportunity space for mitigation, relying on the Avoid-Shift-Improve framework. [[#5.4|Section 5.4]] assesses the relevant contribution of different parts of society to climate change mitigation. [[#5.5|Section 5.5]] evaluates the overall dynamics of social transition processes while [[#5.6|Section 5.6]] summarises insights on governance and policy packages for demand-side mitigation and well-being. A Social Science Primer ( [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-5 Chapter 5] Supplementary Material I) defines and discusses key terms and social science concepts used in the context of climate change mitigation.

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=== Box 5.2 | COVID-19, Service Provisioning and Climate Change Mitigation ===

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There is now ''high evidence'' and ''high agreement'' that the COVID-19 pandemic has increased the political feasibility of large-scale government actions to support the services for provision of public goods, including climate change policies. Many behavioural changes due to COVID-19 reinforce sufficiency and emphasis on solidarity, economies built around care, livelihood protection, collective action, and basic service provision, linked to reduced emissions.

COVID-19 led to direct and indirect health, economic, and confinement-induced hardships and suffering, mostly for the poor, and reset habits and everyday behaviours of the well-off too, enabling a reflection on the basic needs for a good life. Although COVID-19 and climate change pose different kinds of threats and therefore elicit different policies, there are several lessons from COVID-19 for advancing climate change mitigation ( [[#Klenert--2020|Klenert et al. 2020]] ; [[#Manzanedo--2020|Manzanedo and Manning 2020]] ; [[#Stark--2020|Stark 2020]] ). Both crises are global in scale, requiring holistic societal response; governments can act rapidly, and delay in action is costly ( [[#Bouman--2020a|Bouman et al. 2020a]] ; [[#Klenert--2020|Klenert et al. 2020]] ). The pandemic highlighted the role of individuals in collective action and many people felt morally compelled and responsible to act for others ( [[#Budd--2020|Budd and Ison, 2020]] ). COVID-19 also taught the effectiveness of rapid collective action (physical distancing, wearing masks, etc.) as contributions to the public good. The messaging about social distancing, wearing masks and handwashing during the pandemic called attention to the importance of effective public information (e.g., also about reducing personal carbon footprints), recognising that rapid pro-social responses are driven by personal and socio-cultural norms ( [[#Bouman--2020a|Bouman et al. 2020a]] ; [[#Sovacool--2020a|Sovacool et al. 2020a]] ). In contrast, low trust in public authorities impairs the effectiveness of policies and polarises society ( [[#Bavel--2020|Bavel et al. 2020]] ; [[#Hornsey--2020|Hornsey 2020]] ).

During the shutdown, emissions declined relatively most in aviation, and absolutely most in car transport ( [[#Le%20Quéré--2020|Le Quéré et al. 2020]] , Sarkis et al. 2020), and there were disproportionally strong reductions in GHG emissions from coal ( [[#Bertram--2021|Bertram et al. 2021]] ) (Chapter 2). At their peak, CO 2 emissions in individual countries decreased by 17% on average ( [[#Le%20Quéré--2020|Le Quéré et al. 2020]] ). Global energy demand was projected to drop by 5% in 2020, energy-related CO 2 emissions by 7%, and energy investment by 18% ( [[#IEA--2020a|IEA 2020a]] ). COVID-19 shock and recovery scenarios project final energy demand reductions of 1–36 EJ yr −1 by 2025 and cumulative CO 2 emission reductions of 14–45 GtCO 2 by 2030 ( [[#Kikstra--2021a|Kikstra et al. 2021a]] ). Plastics use and waste generation increased during the pandemic ( [[#Klemeš--2020|Klemeš et al. 2020]] ; [[#Prata--2020|Prata et al. 2020]] ). Responses to COVID-19 had important connections with energy demand and GHG emissions due to quarantine and travel restrictions ( [[#Sovacool--2020a|Sovacool et al. 2020a]] ). Reductions in mobility and economic activity reduced energy use in sectors such as industry and transport, but increased energy use in the residential sector ( [[#Diffenbaugh--2020|Diffenbaugh et al. 2020]] ). COVID-19 induced behavioural changes that may translate into new habits, some beneficial and some harmful for climate change mitigation. New digitally-enabled service accessibility patterns (videoconferencing, telecommuting) played an important role in sustaining various service needs while avoiding demand for individual mobility. However, public transit lost customers to cars, personalised two wheelers, walking and cycling, while suburban and rural living gained popularity, possibly with long-term consequences. Reduced air travel, pressures for more localised

Box 5.2

food and manufacturing supply chains ( [[#Hobbs--2020|Hobbs 2020]] ; [[#Nandi--2020|Nandi et al. 2020]] ; [[#Quayson--2020|Quayson et al. 2020]] ), and governments’ revealed willingness to make large-scale interventions in the economy also reflect sudden shifts in service provisions and GHG emissions, some likely to be lasting ( [[#Aldaco--2020|Aldaco et al. 2020]] ; Bilal et al. 2020; [[#Boyer--2020|Boyer 2020]] ; [[#Hepburn--2020|Hepburn et al. 2020]] ; [[#Norouzi--2020|Norouzi et al. 2020]] ; [[#Prideaux--2020|Prideaux et al. 2020]] ; [[#Sovacool--2020a|Sovacool et al. 2020a]] ). If changes in some preference behaviours, for example for larger homes and work environments to enable home working and online education, lead to sprawling suburbs or gentrification with linked environmental consequences, this could translate into long-term implications for climate change ( [[#Beaunoyer--2020|Beaunoyer et al. 2020]] ; [[#Diffenbaugh--2020|Diffenbaugh et al. 2020]] ). Recovering from the pandemic by adopting low energy demand practices – embedded in new travel, work, consumption and production behaviour and patterns – could reduce carbon prices for a 1.5°C consistent pathway by 19%, reduce energy supply investments until 2030 by USD1.8 trillion, and lessen pressure on the upscaling of low-carbon energy technologies ( [[#Kikstra--2021a|Kikstra et al. 2021a]] ).

COVID-19 drove hundreds of millions of people below poverty thresholds, reversing decades of poverty reduction accomplishments ( [[#Krieger--2020|Krieger 2020]] ; [[#Mahler--2020|Mahler et al. 2020]] ; [[#Patel--2020|Patel et al. 2020]] ; [[#Sumner--2020|Sumner et al. 2020]] ) and raising the spectre of intersecting health and climate crises that are devastating for the most vulnerable ( [[#Flyvbjerg--2020|Flyvbjerg 2020]] ; [[#Phillips--2020|Phillips et al. 2020]] ). Like those of climate change, pandemic impacts fall heavily on disadvantaged groups, exacerbate the uneven distribution of future benefits, amplify existing inequities, and introduce new ones ( [[#Beaunoyer--2020|Beaunoyer et al. 2020]] ; [[#Devine-Wright--2020|Devine-Wright et al. 2020]] ). Addressing such inequities is a positive step towards the social trust that leads to improved climate policies as well as individual actions. Increased support for care workers and social infrastructures within a solidarity economy is consistent with lower-emission economic transformation ( [[#Shelley--2017|Shelley 2017]] ; [[#Di%20Chiro--2019|Di Chiro 2019]] ; [[#Pichler--2019|Pichler et al. 2019]] ; [[#Smetschka--2019|Smetschka et al. 2019]] ).

Fiscally, the pandemic may have slowed the transition to a sustainable energy world: governments redistributed public funding to combat the disease, adopted austerity and reduced capacity. Of nearly 300 policies implemented to counteract the pandemic, the vast majority are related to rescue, including worker and business compensation, and only 4% of these focus on green policies with potential to reduce GHG emissions in the long term; some rescue policies also assist emissions-intensive business ( [[#Hepburn--2020|Hepburn et al. 2020]] ; [[#Leach--2021|Leach et al. 2021]] ). However, climate investments can double as the basis of the COVID-19 recovery ( [[#Stark--2020|Stark 2020]] ), with policies focused on both economic multipliers and climate impacts, such as clean physical infrastructure, natural capital investment, clean research and development (R&amp;D) and education and training ( [[#Hepburn--2020|Hepburn et al. 2020]] ). This requires attention to investment priorities, including often-underprioritised social investment, given how inequality intersects with, and is a recognised core driver of, environmental damage and climate change ( [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ).

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