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

=== 5.2.1 Metrics of Well-being and their Relationship to Greenhouse Gas Emissions ===

<div id="h2-6-siblings" class="h2-siblings"></div>

There is ''high evidence'' and ''high agreement'' in the literature that human well-being and related metrics provide a societal perspective which is inclusive, compatible with sustainable development, and generates multiple ways to mitigate emissions. Development targeted to basic needs and well-being for all entails less carbon intensity than GDP-focused growth ( [[#Rao--2014|Rao et al. 2014]] ; [[#Lamb--2015|Lamb and Rao 2015]] ).

Current socioeconomic systems are based on high-carbon economic growth and resource use ( [[#Steffen--2018b|Steffen et al. 2018b]] ). Several systematic reviews confirm that economic growth is tightly coupled with increasing CO 2 emissions ( [[#Ayres--2005|Ayres and Warr 2005]] ; [[#Tiba--2017|Tiba and Omri 2017]] ; [[#Mardani--2019|Mardani et al. 2019]] ; [[#Wiedenhofer--2020|Wiedenhofer et al. 2020]] ) although the level of emissions depends on inequality ( [[#Baležentis--2020|Baležentis et al. 2020]] ; [[#Liu--2020b|Liu et al. 2020b]] ), and on geographic and infrastructural constraints that force consumers to use fossil fuels ( [[#Pottier--2021|Pottier et al. 2021]] ). Different patterns emerge in the causality of the energy–growth nexus: (i) energy consumption causes economic growth; (ii) growth causes energy consumption; (iii) bidirectional causality; and (iv) no significant causality ( [[#Ozturk--2010|Ozturk 2010]] ). In a systematic review, [[#Mardani--2019|Mardani et al. (2019)]] found that in most cases, energy use and economic growth have a bidirectional causal effect, indicating that as economic growth increases, further CO 2 emissions are stimulated at higher levels; in turn, measures designed to lower GHG emissions may reduce economic growth. However, energy substitution and efficiency gains may offer opportunities to break the bidirectional dependency ( [[#Komiyama--2014|Komiyama 2014]] ; [[#Brockway--2017|Brockway et al. 2017]] ; [[#Shuai--2019|Shuai et al. 2019]] ). Worldwide trends reveal that at best only relative decoupling (resource use grows at a slower pace than GDP) was the norm during the twentieth century ( [[#Jackson--2009|Jackson 2009]] ; [[#Krausmann--2009|Krausmann et al. 2009]] ; [[#Ward--2016|Ward et al. 2016]] ; [[#Jackson--2016|Jackson 2016]] ), while absolute decoupling (when material use declines as GDP grows) is rare, observed only during recessions or periods of low or no economic growth ( [[#Heun--2019|Heun and Brockway 2019]] ; [[#Hickel--2019|Hickel and Kallis 2019]] ; [[#Vadén--2020|Vadén et al. 2020]] ; [[#Wiedenhofer--2020|Wiedenhofer et al. 2020]] ). Recent trends in OECD countries demonstrate the potential for absolute decoupling of economic growth not only from territorial but also from consumption-based emissions ( [[#Le%20Quéré--2019|Le Quéré et al. 2019]] ), albeit at scales insufficient for mitigation pathways ( [[#Vadén--2020|Vadén et al. 2020]] ) (Chapter 2).

Energy demand and demand for GHG-intensive products increased from 2010 until 2020 across all sectors and categories. 2019 witnessed a reduction in energy demand growth rate to below 1% and 2020 an overall decline in energy demand, with repercussions for energy supply disproportionally affecting coal via merit order effects ( [[#Bertram--2021|Bertram et al. 2021]] ) (Cross-Chapter Box 1 in Chapter 1). There was a slight but significant shift from high-carbon beef consumption to medium-carbon intensive poultry consumption. Final energy use in buildings grew from 118 EJ in 2010 to around 128 EJ in 2019 (increased about 8%). The highest increase was observed in non-residential buildings, with a 13% increase against 8% in residential energy demand ( [[#IEA--2019a|IEA 2019a]] ). While electricity accounted for one-third of building energy use in 2019, fossil fuel use also increased at a marginal annual average growth rate of 0.7% since 2010 ( [[#IEA--2020a|IEA 2020a]] ). Energy-related CO 2 emissions from buildings have risen in recent years after flattening between 2013 and 2016. Direct and indirect emissions from electricity and commercial heat used in buildings rose to 10 GtCO 2 in 2019, the highest level ever recorded. Several factors have contributed to this rise, including growing energy demand for heating and cooling with rising air conditioner ownership and extreme weather events. A critical issue remains how comfortable people feel with temperatures they will be exposed to in the future and this depends on physical, psychological and behavioural factors ( [[#Singh--2018|Singh et al. 2018]] ; [[#Jacobs--2019|Jacobs et al. 2019]] ). Literature now shows ''high evidence'' and ''high agreement'' around the observation that policies and infrastructure interventions that lead to change in human preferences are more valuable for climate change mitigation. In economics, welfare evaluations are predominantly based on the preference approach. Preferences are typically assumed to be fixed, so that only changes in relative prices will reduce emissions. However, as decarbonisation is a societal transition, individuals’ preferences do shift and this can contribute to climate change mitigation ( [[#Gough--2015|Gough 2015]] ). Even if preferences are assumed to change in response to policy, it is nevertheless possible to evaluate policy, and demand-side solutions, by approaches to well-being and welfare that are based on deeper concepts of preferences across disciplines ( [[#Roy--2009|Roy and Pal 2009]] ; [[#Fleurbaey--2014|Fleurbaey and Tadenuma 2014]] ; [[#Komiyama--2014|Komiyama 2014]] ; [[#Dietrich--2016|Dietrich and List 2016]] ; [[#Mattauch--2016|Mattauch and Hepburn 2016]] ). In cases of past societal transitions, such as smoking reduction, there is evidence that societies guided the processes of shifting preferences, and values changed along with changing relative prices ( [[#Nyborg--2003|Nyborg and Rege 2003]] ; [[#Stuber--2008|Stuber et al. 2008]] ; [[#Brownell--2009|Brownell and Warner 2009]] ). Further evidence on changing preferences in consumption choices pertinent to decarbonisation includes [[#Grinblatt--2008|Grinblatt et al. (2008)]] and [[#Weinberger--2010|Weinberger and Goetzke (2010)]] for mobility; [[#Erb--2016|Erb et al. (2016)]] , [[#Muller--2017|Muller et al. (2017)]] , and [[#Costa--2019|Costa and Johnson (2019)]] for diets; and [[#Baranzini--2017|Baranzini et al. (2017)]] for solar panel uptake. If individuals’ preferences and values change during a transition to the low-carbon economy, then this overturns conclusions on what count as adequate or even optimal policy responses to climate change mitigation in economics ( [[#Jacobsen--2012|Jacobsen et al. 2012]] ; [[#Schumacher--2015|Schumacher 2015]] ; [[#Dasgupta--2016|Dasgupta et al. 2016]] ; [[#Daube--2016|Daube and Ulph 2016]] ; [[#Ulph--2021|Ulph and Ulph 2021]] ). In particular, if policy instruments, such as awareness campaigns, infrastructure development or education, can change people’s preferences, then policies or infrastructure provision – socially constrained by deliberative decision making – which change both relative prices and preferences, are more valuable for mitigation than previously thought ( [[#Creutzig--2016b|Creutzig et al. 2016b]] ; [[#Mattauch--2016|Mattauch et al. 2016]] ; [[#Mattauch--2018|Mattauch et al. 2018]] ). The provisioning context of human needs is participatory, so transformative mitigation potential arises from social as well as technological change ( [[#Lamb--2017|Lamb and Steinberger 2017]] ). Many dimensions of well-being and ‘basic needs’ are social, not individual, in character ( [[#Schneider--2016|Schneider 2016]] ), so extending well-being and DLS analysis to emissions also involves understanding individual situations in social contexts. This includes building supports for collective strategies to reduce emissions ( [[#Chan--2019|Chan et al. 2019]] ), going beyond individual consumer choice. Climate policies that affect collective behaviour fairly are the most acceptable policies across political ideologies ( [[#Clayton--2018|Clayton 2018]] ); thus collective preferences for mitigation are synergistic with evolving policies and norms in governance contexts that reduce risk, ensure social justice and build trust ( [[#Atkinson--2017|Atkinson et al. 2017]] ; [[#Cramton--2017|Cramton et al. 2017]] ; [[#Milkoreit--2017|Milkoreit 2017]] ; [[#Tvinnereim--2017|Tvinnereim et al. 2017]] ; [[#Smith--2018|Smith and Reid 2018]] ; [[#Carattini--2019|Carattini et al. 2019]] ).

Because of data limitations, which can make cross-country comparisons difficult, health-based indicators and in particular life expectancy ( [[#Lamb--2014|Lamb et al. 2014]] ) have sometimes been proposed as quick and practical ways to compare local or national situations, climate impacts, and policy effects ( [[#Decancq--2009|Decancq et al. 2009]] ; [[#Sager--2017|Sager 2017]] ; [[#Burstein--2019|Burstein et al. 2019]] ). A number of different well-being metrics are valuable in emphasising the constituents of what is needed for a decent life in different dimensions ( [[#Lamb--2017|Lamb and Steinberger 2017]] ; [[#Porter--2017|Porter et al. 2017]] ; [[#Smith--2018|Smith and Reid 2018]] ). The SDGs overlap in many ways with such indicators, and the data needed to assess progress in meeting the SDGs is also useful for quantifying well-being ( [[#Gough--2017|Gough 2017]] ). For the purposes of this chapter, indicators directly relating GHG emissions to well-being for all are particularly relevant.

Well-being can be categorised either as ‘hedonic’ or ‘eudaimonic’. Hedonic well-being is related to a subjective state of human motivation, balancing pleasure over pain, and has gained influence in psychology assessing ‘subjective well-being’, assuming that the individual is motivated to enhance personal freedom, self-preservation and enhancement ( [[#Sirgy--2012|Sirgy 2012]] ; [[#Brand-Correa--2017|Brand-Correa and Steinberger 2017]] ; [[#Lamb--2017|Lamb and Steinberger 2017]] ; [[#Ganglmair-Wooliscroft--2019|Ganglmair-Wooliscroft and Wooliscroft 2019]] ). Eudaimonic well-being focuses on the individual in the broader context, associating happiness with virtue ( [[#Sirgy--2012|Sirgy 2012]] ), allowing for the creation of social institutions and political systems and considering their ability to enable individuals to flourish. Eudaimonic analysis supports numerous development approaches ( [[#Fanning--2019|Fanning and O’Neill 2019]] ) such as the capabilities ( [[#Sen--1985|Sen 1985]] ), human needs ( [[#Doyal--1991|Doyal and Gough 1991]] ; [[#Max-Neef--1991|Max-Neef et al. 1991]] ) and models of psychosocial well-being ( [[#Ryan--2001|Ryan and Deci 2001]] ). Measures of well-being differ somewhat in developed and developing countries ( [[#Sulemana--2016|Sulemana et al. 2016]] ; [[#Ng--2019|Ng and Diener 2019]] ); for example, food insecurity, associated everywhere with lower subjective well-being, is more strongly associated with poor subjective well-being in more-developed countries ( [[#Frongillo--2019|Frongillo et al. 2019]] ); in wealthier countries, the relationship between living in rural areas is less strongly associated with negative well-being than in less-developed countries ( [[#Requena--2016|Requena 2016]] ); and income inequality is negatively associated with subjective well-being in developed countries, but positively so in less-developed countries ( [[#Ngamaba--2018|Ngamaba et al. 2018]] ). This chapter connects demand-side climate mitigation options to multiple dimensions of well-being, going beyond the single dimensional metric of GDP which is at the core of IAMs. Many demand side-mitigation solutions generate positive and negative impacts on wider dimensions of human well-being which are not always quantifiable ( ''medium evidence, medium agreement'' ) ''.''

<div id="5.2.1.1" class="h3-container"></div>

<span id="services-for-well-being"></span>
==== 5.2.1.1 Services for Well-being ====

<div id="h3-1-siblings" class="h3-siblings"></div>

Well-being needs are met through services. Provision of services associated with low energy demand is a key component of current and future efforts to reduce carbon emissions. Services can be provided in various culturally-appropriate ways, with diverse climate implications. There is ''high evidence'' and ''high agreement'' in the literature that many granular service provision systems can make ‘demand’ more flexible, provide new options for mitigation, support access to basic needs, and enhance human well-being. Energy services offer an important lens to analyse the relationship between energy systems and human well-being ( [[#Jackson--2008|Jackson and Papathanasopoulou 2008]] ; [[#Druckman--2010|Druckman and Jackson 2010]] ; [[#Mattioli--2016|Mattioli 2016]] ; [[#Walker--2016|Walker et al. 2016]] ; [[#Fell--2017|Fell 2017]] ; [[#Brand-Correa--2018|Brand-Correa et al. 2018]] ; [[#King--2019|King et al. 2019]] ; [[#Pagliano--2019|Pagliano and Erba 2019]] ; [[#Whiting--2020|Whiting et al. 2020]] ). Direct and indirect services provided by energy, rather than energy itself, deliver well-being benefits ( [[#Kalt--2019|Kalt et al. 2019]] ). For example, illumination and transport are intermediary services in relation to education, health care, meal preparation, sanitation, and so on, which are basic human needs. Sustainable consumption and production revolve around ‘doing more and better with the same’ and thereby increasing well-being from economic activities ‘by reducing resource use, degradation and pollution along the whole lifecycle, while increasing quality of life’ ( [[#UNEP--2010|UNEP 2010]] ). Although energy is required for delivering human development by supporting access to basic needs ( [[#Lamb--2015|Lamb and Rao 2015]] ; [[#Lamb--2017|Lamb and Steinberger 2017]] ), a reduction in primary energy use and/or shift to low-carbon energy, if associated with the maintenance or improvement of services, can not only ensure better environmental quality but also directly enhance well-being ( [[#Roy--2012|Roy et al. 2012]] ). The correlation between human development and emissions is not necessarily coupled in the long term, which implies there is a need to prioritise human well-being and the environment over economic growth ( [[#Steinberger--2020|Steinberger et al. 2020]] ). At the interpersonal and community levels, cultural specificities, infrastructure, norms, and relational behaviours differ (Box 5.3). For example, demand for space heating and cooling depends on building materials and designs, urban planning, vegetation, clothing and social norms as well as geography, incomes, and outside temperatures ( [[#Brand-Correa--2018|Brand-Correa et al. 2018]] ; [[#Campbell--2018|Campbell et al. 2018]] ; [[#Ivanova--2018|Ivanova et al. 2018]] ; [[#IEA--2019b|IEA 2019b]] ; [[#Dreyfus--2020|Dreyfus et al. 2020]] ). In personal mobility, different variable needs satisfiers (e.g., street space allocated to cars, buses or bicycles) can help satisfy human needs, such as accessibility to jobs, health care, and education. Social interactions and normative values play a crucial role in determining energy demand. Hence, demand-side and service-oriented mitigation strategies are most effective if geographically and culturally differentiated ( [[#Niamir--2020a|Niamir et al. 2020a]] ).

Decent living standards (DLS) serves as a socio-economic benchmark as it views human welfare not in relation to consumption but rather in terms of services which together help meet human needs (e.g., nutrition, shelter, health, etc.), recognising that these service needs may be met in many different ways (with different emissions implications) depending on local contexts, cultures, geography, available technologies, social preferences, and other factors. Therefore, one key way of thinking about providing well-being for all with low carbon emissions centres around prioritising ways of providing services for DLS in a low-carbon way (including choices of needs satisfiers, and how these are provided or made accessible). They may be supplied to individuals or groups or communities, both through formal markets and/or informally, for example by collaborative work, in coordinated ways that are locally appropriate, designed and implemented in accordance with overlapping local needs.

The most pressing DLS service shortfalls, as shown in Figure 5.2, lie in the areas of nutrition, mobility, and communication. Gaps in regions such as Africa and the Middle East are accompanied by current levels of service provision in the highly industrialised countries at much higher than DLS levels for the same three service categories. The lowest population quartile by income worldwide faces glaring shortfalls in housing, mobility, and nutrition. Meeting these service needs using low-emissions energy sources is a top priority. Reducing GHG emissions associated with high levels of consumption and material throughput by those far above DLS levels has potential to address both emissions and inequality in energy and emission footprints ( [[#Otto--2019|Otto et al. 2019]] ). This, in turn, has further potential benefits; under the conditions of ‘fair’ income reallocation to public services, this can reduce national carbon footprint by up to 30% while allowing the consumption of those at the bottom to increase ( [[#Millward-Hopkins--2021|Millward-Hopkins and Oswald 2021]] ). The challenge then is to address the upper limits of consumption. When consumption only just supports the satisfaction of basic needs, any decrease causes deficiencies in human-need satisfaction. This is quite unlinke the case of consumption that exceeds the limits of basic needs, in which deprivation causes a subjective discomfort ( [[#Brand-Correa--2020|Brand-Correa et al. 2020]] ). Therefore, to collectively remain within environmental limits, the establishment of minimum and maximum standards of consumption, or sustainable consumption corridors, ( [[#Wiedmann--2020|Wiedmann et al. 2020]] ) has been suggested, depending on the context. In some countries, carbon-intensive ways of satisfying human needs have been locked-in, for example via car-dependent infrastructures ( [[#Jackson--2008|Jackson and Papathanasopoulou 2008]] ; [[#Druckman--2010|Druckman and Jackson 2010]] ; [[#Mattioli--2016|Mattioli 2016]] ; [[#King--2019|King et al. 2019]] ), and both infrastructure reconfiguration and adaptation are required to organise need satisfaction in low-carbon ways (see also [[IPCC:Wg3:Chapter:Chapter-10#10.2|Section 10.2]] ).

<div id="_idContainer011" class="Basic-Text-Frame"></div>

[[File:a7c3b34a9e34a6cb0cf7ba886618ef22 IPCC_AR6_WGIII_Figure_5_2.png]]

'''Figure 5.2''' [[#footnote-000|2]] '''| Heterogeneity in access to and availability of services for human well-being within and across countries.''' Panel '''(''' '''a)''' Across-country differences in panel (a) food (meat and other), (b) housing, (c) mobility, (d) communication (mobile phones and high-speed internet access). Variation in service levels across countries within a region is shown as error bars (black). Values proposed as decent standards of living threshold ( [[#Rao--2019b|Rao et al. 2019b]] ) are shown as red dashed lines. Global average values are shown as blue dashed lines. Panel '''(b)''' Within-country differences in service levels as a function of income differences for the Netherlands (bottom and top 10% of incomes) and India (bottom and top 25% of incomes) ( [[#Grubler--2012b|Grubler et al. 2012b]] ) (data update 2016). Panel '''(c)''' Decent living energy (DLE) scenario using global, regional and DLS dimensions for final energy consumption at 149 EJ (15.3 GJ cap –1 yr –1 ) in 2050 ( [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ), requiring advanced technologies in all sectors and radical demand-side changes. Values are shown for five world regions based on the AR6 WGIII Regional breakdown. We use passenger kilometres per day per capita ( km day '''–1''' cap '''–1''' ) as a metric for mobility only as a reference, however, transport and social inclusion research suggest the aim is to maximise accessibility and not travel levels or travelled distance.

There is ''high evidence'' and ''high agreement'' in the literature that vital dimensions of human well-being correlate with consumption, but only up to a threshold. High potential for mitigation lies in using low-carbon energy for new basic needs satisfaction while cutting emissions of those whose basic needs are already met ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#Rao--2018b|Rao and Min 2018b]] ; [[#Rao--2019b|Rao et al. 2019b]] ; [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ;

[[#Keyßer--2021|Keyßer and Lenzen 2021]] ). Decent living standards indicators serve as tools to clarify this socio-economic benchmark and identify well-being for all compatible mitigation potential. Energy services provisioning opens up avenues of efficiency and possibilities for decoupling energy services demand from primary energy supply, while needs satisfaction leads to the analysis of the factors influencing the energy demand associated with the achievement of well-being ( [[#Brand-Correa--2017|Brand-Correa and Steinberger 2017]] ; [[#Tanikawa--2021|Tanikawa et al. 2021]] ). Vital dimensions of well-being correlate with consumption, but only up to a threshold: decent living energy thresholds range from about 13 to 18.4 GJ cap –1 yr – 1 of final energy consumption but the current consumption ranges from under 5 GJ cap –1 yr –1 to over 200 GJ cap –1 yr –1 ( [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ), thus a mitigation strategy that protects minimum levels of essential-goods service delivery for DLS, but critically views consumption beyond the point of diminishing returns of needs satisfaction, is able to sustain well-being while generating emissions reductions ( [[#Goldemberg--1988|Goldemberg et al. 1988]] ; [[#Jackson--1999|Jackson and Marks 1999]] ; [[#Druckman--2010|Druckman and Jackson 2010]] ; [[#Girod--2010|Girod and De Haan 2010]] ; [[#Vita--2019a|Vita et al. 2019a]] ; [[#Baltruszewicz--2021|Baltruszewicz et al. 2021]] ). Such relational dynamics are relevant both within and between countries, due to variances in income levels, lifestyle choice (see also [[#5.4.4|Section 5.4.4]] ), geography, resource assets and local contexts. Provisioning for human needs is recognised as participatory and inter-relational; transformative mitigation potential can be found in social as well as technological change ( [[#Mazur--1974|Mazur and Rosa 1974]] ; [[#Goldemberg--1985|Goldemberg et al. 1985]] ; [[#Lamb--2017|Lamb and Steinberger 2017]] ; [[#O’Neill--2018|O’Neill et al. 2018]] ; [[#Hayward--2019|Hayward and Roy 2019]] ; [[#Vita--2019a|Vita et al. 2019a]] ). More equitable societies which provide DLS for all can devote attention and resources to mitigation ( [[#Richards--2003|Richards 2003]] ; [[#Dubash--2013|Dubash 2013]] ; [[#Rafaty--2018|Rafaty 2018]] ; [[#Oswald--2021|Oswald et al. 2021]] ). For further exploration of these concepts, see [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-5 Chapter 5] Supplementary Material I.

<div id="5.2.2" class="h2-container"></div>

<span id="inequity-in-access-to-basic-energy-use-and-services"></span>