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

== 5.6 Governance and Policy ==

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=== 5.6.1 Governing Mitigation: Participation and Social Trust ===

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In demand-side mitigation, governance is key to drive the multidimensional changes needed to meet service needs within a society that provide people with a decent living while increasingly reducing resource and energy input levels ( [[#Rojas-Rueda--2012|Rojas-Rueda et al. 2012]] ; [[#Batchelor--2018|Batchelor et al. 2018]] ; [[#OECD--2019a|OECD 2019a]] ). Impartial governance, understood as equal treatment of everyone by the rule of law, creates social trust and is thus a key enabler of inclusive and participatory demand-side climate policies ( [[#Rothstein--2011|Rothstein 2011]] ). Inclusive and broad-based participation itself also leads to greater social trust and thus is also a key enabler of demand-side climate mitigation ( [[#5.2|Section 5.2]] ). Higher social trust and inclusive participatory processes also reduce inequality, restrain opportunistic behaviour and enhance cooperation ( [[#Drews--2016|Drews and van den Bergh 2016]] ; [[#Gür--2020|Gür 2020]] ) ( [[#5.2|Section 5.2]] ). Altogether, broad-based participatory processes are central to the successful implementation of climate policies ( [[#Rothstein--2008|Rothstein and Teorell 2008]] ; [[#Klenert--2018|Klenert et al. 2018]] ) ( ''high evidence, medium agreement'' ). A culture of cooperation feeds back to increase social trust and enables action that reduce GHG emissions ( [[#Carattini--2015|Carattini et al. 2015]] ; [[#Jo--2021|Jo and Carattini 2021]] ), and requires including explicit consideration of the informal sector (Box 5.10). More equitable societies also have the institutional flexibility to allow for mitigation to advance faster, given their readiness to adopt locally-appropriate mitigation policies; they also suffer less from policy lock-in ( [[#Tanner--2009|Tanner et al. 2009]] ; [[#Lorenz--2013|Lorenz 2013]] ; [[#Chu--2015|Chu 2015]] ; [[#Cloutier--2015|Cloutier et al. 2015]] ; [[#Martin--2016|Martin 2016]] ; [[#Seto--2016|Seto et al. 2016]] ; [[#Vandeweerdt--2016|Vandeweerdt et al. 2016]] ; [[#Turnheim--2018|Turnheim et al. 2018]] ).

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=== Box 5.10 | The Informal Sector and Climate Mitigation ===

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The informal economy represents a large and growing portion of socio-economic activities ( [[#Charmes--2016|Charmes 2016]] ; [[#Muchie--2016|Muchie et al. 2016]] ; [[#Mbaye--2018|Mbaye and Gueye 2018]] ), including much of the work done by women worldwide. It accounts for an estimated 61% of global employment in the world; 90% in developing countries, 67% in emerging countries, and 18% in developed countries ( [[#Berik--2018|Berik 2018]] ), representing roughly 30% of GDP across a range of countries ( [[#Durán%20Heras--2012|Durán Heras 2012]] ; [[#Narayan--2017|Narayan 2017]] ). Due to its importance, policies which support informal-sector climate mitigation activities may be extremely efficient ( [[#Garland--2015|Garland 2015]] ). For example, environmental and energy taxes may have negative gross costs when the informal sector dominates economic activity since these taxes indirectly tax the informal sector; informal production may substitute for energy-intensive goods, with strong welfare-enhancing effects ( [[#Bento--2018a|Bento et al. 2018a]] ). The informal sector can assemble social and financial capital, create jobs, and build low-carbon local economies ( [[#Ruzek--2015|Ruzek 2015]] ). Constraints on small and informal-sector firms’ ability to build climate resilience include financial and data barriers, limited access to information technology, and policy exclusion ( [[#Kraemer-Mbula--2016|Kraemer-Mbula and Wunsch-Vincent 2016]] ; [[#Crick--2018a|Crick et al. 2018a]] ; [[#Crick--2018b|Crick et al. 2018b]] ).

Informal-sector innovation is often underrated. It gives marginalised people access to welfare-enhancing innovations, building on alternative knowledge and socially-embedded reciprocal exchange ( [[#Jaffe--2019|Jaffe and Koster 2019]] ; [[#Sheikh--2019|Sheikh 2019]] ; [[#Sheikh--2020|Sheikh and Bhaduri 2020]] ). Large improvements in low-emission, locally-appropriate service provision are possible by facilitating informal-sector service providers’

Box 5.10

access to low-energy technologies (while taking care not to additionally burden the unpaid and marginalised), through such means as education, participatory governance, government policies to assist the informal sector, social services, health care, credit provision, and removing harmful policies and regulatory silos. The importance of the informal economy, especially in low-income countries, opens many possibilities for new approaches to decent living standards service provision along with climate resilience ( [[#Rynikiewicz--2006|Rynikiewicz and Chetaille 2006]] ; [[#Backstränd--2010|Backstränd et al. 2010]] ; [[#Porio--2011|Porio 2011]] ; [[#Kriegler--2014|Kriegler et al. 2014]] ; [[#Taylor--2014|Taylor and Peter 2014]] ; [[#Brown--2016|Brown and McGranahan 2016]] ; [[#Chu--2016|Chu 2016]] ; Satterthwaite et al. 2018; [[#Boran--2019|Boran 2019]] ; [[#Hugo--2019|Hugo and du Plessis 2019]] ; [[#Schröder--2019|Schröder et al. 2019]] ; [[#Javaid--2020|Javaid et al. 2020]] ).

Public information and understanding of the CO 2 -eq emissions implied by consumption patterns can unleash great creativity for meeting service needs fairly and with lower emissions ( [[#Darier--1999|Darier and Schüle 1999]] ; [[#Sterman--2002|Sterman and Sweeney 2002]] ; [[#Lorenzoni--2007|Lorenzoni et al. 2007]] ; [[#Billett--2010|Billett 2010]] ; [[#Marres--2011|Marres 2011]] ; [[#Zapico%20Lamela--2011|Zapico Lamela et al. 2011]] ; [[#Polonsky--2012|Polonsky et al. 2012]] ; [[#Williams--2019|Williams et al. 2019]] ). Community-based mapping, social learning, green infrastructure development, and participatory governance facilitate such information-sharing ( [[#Tauhid--2018|Tauhid and Zawani 2018]] ; [[#Mazeka--2019|Mazeka et al. 2019]] ; [[#Sharifi--2020|Sharifi 2020]] ), strengthening mitigation policies ( [[#Loiter--1999|Loiter and Norberg-Bohm 1999]] ; [[#Stokes--2017|Stokes and Warshaw 2017]] ; Zhou et al. 2019).

Since informal settlements are usually dense, upgrading them supports low-carbon development pathways which leapfrog less-efficient housing, transport and other service provision, using locally-appropriate innovations (Satterthwaite et al. 2018). Examples of informal-sector mitigation include digital banking in Africa; mobility in India using collective transport; food production, meal provision, and reduction of food waste in Latin America (e.g., soup kitchens in Brazil, community kitchens in Lima, Peru); informal materials recycling, space heating and cooling, and illumination ( [[#Hordijk--2000|Hordijk 2000]] ; [[#Baldez--2003|Baldez 2003]] ; [[#Maumbe--2006|Maumbe 2006]] ; [[#Gutberlet--2008|Gutberlet 2008]] ; [[#Chaturvedi--2011|Chaturvedi and Gidwani 2011]] ; [[#Nandy--2015|Nandy et al. 2015]] ; [[#Rouse--2016|Rouse and Verhoef 2016]] ; [[#Ackah--2017|Ackah 2017]] ).

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<span id="policies-to-strengthen-avoid-shift-improve"></span>

=== 5.6.2 Policies to Strengthen Avoid-Shift-Improve ===

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There is high untapped potential of demand-side mitigation options if considered holistically within the domains of Avoid-Shift-Improve (Sections 5.3 and 5.4, Tables 5.1, 5.2, and 5.3a,b). Within the demand-side mitigation options opportunity space, policies currently focus more on efficiency and ‘Improve’ options and relatively less on ‘Shift’ and ‘Avoid’ options ( [[#Dubois--2019|Dubois et al. 2019]] ; [[#Moberg--2019|Moberg et al. 2019]] ). Current demand-side policies are fragmented, piecemeal and too weak to drive demand-side transitions commensurate with 1.5°C or 2°C climate goals ( [[#Wilson--2012|Wilson et al. 2012]] ; [[#Fawcett--2019|Fawcett et al. 2019]] ; [[#Mundaca--2019|Mundaca et al. 2019]] ; [[#Moberg--2019|Moberg et al. 2019]] ) ( ''high evidence, high'' ''agreement'' ). However, increasingly policy mix in a number of countries has seen a rise in prohibitions on fossil fuel use as a way to weaken lock-ins, for example, on fossil fuel heating in favour of low-carbon alternatives ( [[#Rosenbloom--2020|Rosenbloom et al. 2020]] ). Policies that are aimed at behaviour and lifestyle changes carry a perception of political risks for policymakers, which may explain why policy instruments focus more on information provision and adoption of incentives than on regulation and investment ( [[#Rosenow--2017|Rosenow et al. 2017]] ; [[#Moberg--2019|Moberg et al. 2019]] ). Acceleration of demand-side transitions would thus require both a broadening of demand-side options and the creation of comprehensive and targeted policy mixes ( [[#Kern--2017|Kern et al. 2017]] ; [[#Rosenow--2017|Rosenow et al. 2017]] ; [[#IPCC--2018|IPCC 2018]] ) that strengthen the five drivers of decision and action identified in [[#5.4|Section 5.4]] , Table 5.4 and in Tables 5.5–5.7 ( ''high evidence, high agreement'' ). Demand-side transitions in developing and emerging economies would also require stronger administrative capacity as well as technical and financial support ( [[#UN-Habitat--2013|UN-Habitat 2013]] ; [[#Creutzig--2016b|Creutzig et al. 2016b]] ).

Systematic categorisation of demand-side policy options in different sectors and services through the Avoid-Shift-Improve framework enables identification of major entry points and possible associated social struggles to overcome for the policy instruments/interventions as discussed below.

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==== 5.6.2.1 ‘Avoid’ Policies ====

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There is ''high evidence'' and ''high'' ''agreement'' that ‘Avoid’ policies that affect lifestyle changes offer opportunities for cost-effective reductions in energy use and emissions, but would need to overcome political sensitivities around government efforts to shape and modify individual-level behaviour ( [[#Rosenow--2017|Rosenow et al. 2017]] ; [[#Grubb--2020|Grubb et al. 2020]] ) (Table 5.5). These policies include ways to help avoid travel growth through integrated city planning or building retrofits to help avoid demand for transport, heating or cooling ( [[#Bakker--2014|Bakker et al. 2014]] ; [[#Lucon--2014|Lucon et al. 2014]] ; [[#de%20Feijter--2019|de Feijter et al. 2019]] ), which interact with existing infrastructure. Dense pedestrianised cities and towns and medium-density transit corridors are better placed to implement policies for car reductions than ‘sprawled’ cities characterised by low-density, auto-dependent and separated land uses ( [[#Seto--2014|Seto et al. 2014]] ; [[#Newman--2015|Newman and Kenworthy 2015]] ; [[#Newman--2017|Newman et al. 2017]] ; [[#Bakker--2014|Bakker et al. 2014]] ).

Cities face pressing priorities like poverty reduction, meeting basic services and building human and institutional capacity. These are met with highly accessible walkable and cyclable cities, connected with public transit corridors, enabling equal accessibility for all citizens, and enabling a high level of service provisioning ( [[#UN-Habitat--2013|UN-Habitat 2013]] ; Creutziget al. 2016b). Infrastructure development costs less than for car dependent cities. However, it requires a mindset shift for urban and transport planners ( ''medium evidence, high agreement'' ).

Policies that support the avoidance of higher-emission lifestyles and improve well-being are facilitated by the introduction of smart technologies, infrastructures and practices ( [[#Amini--2019|Amini et al. 2019]] ). They include regulations and measures for investment in high-quality ICT infrastructure and regulations to restrict number plates, as well as company policy around flexible working conditions ( [[#Lachapelle--2018|Lachapelle et al. 2018]] ; [[#Shabanpour--2018|Shabanpour et al. 2018]] ). Working-from-home arrangements may advantage certain segments of society such as male, older, higher-educated and highly-paid employees, potentially exacerbating existing inequalities in the labour market ( [[#Lambert--2020|Lambert et al. 2020]] ; [[#Bonacini--2021|Bonacini et al. 2021]] ). In the absence of distributive or other equity-based measures, the potential gains in terms of emissions reduction may therefore be counteracted by the cost of increasing inequality. This potential growth in inequality is likely to be more severe in poorer countries that will additionally suffer from a lack of international funding for achieving the SDGs ( ''high evidence, medium agreement'' ) ( [[#Barbier--2020|Barbier and Burgess 2020]] ; [[#UN--2020|UN 2020]] ).

'''Table 5.5 | Examples of policies to enable ‘Avoid’ options.'''

{| class="wikitable"
|-
| '''Mitigation option'''

| '''Perceived struggles to overcome'''

| '''Policy to overcome struggles (Incentives)'''

|-
| '''Reduce passenger km'''

| – Existing paradigms and planning practices and car dependency ( [[#Rosenow--2017|Rosenow et al. 2017]] ; [[#Grubb--2020|Grubb et al. 2020]] )

– Financial and capacity barrier in many developing countries

– Status dimension of private cars

| – Integrated city planning to avoid travel growth, car reduction, building retrofits to avoid heating or cooling demand ( [[#Bakker--2014|Bakker et al. 2014]] ; [[#Lucon--2014|Lucon et al. 2014]] ; [[#de%20Feijter--2019|de Feijter et al. 2019]] )

– Public-private partnership to overcome financial barrier ( [[#Roy--2018b|Roy et al. 2018b]] ) (Box 5.8)

– Taxation of status consumption; reframing of low-carbon transport as high status ( [[#Hoor--2020|Hoor 2020]] ; [[#Ramakrishnan--2021|Ramakrishnan and Creutzig 2021]] )

|-
| '''Reduce/Avoid food waste'''

| Little visible political and social momentum to prevent food waste in the Global North

| Strengthen national nutrition guidelines for health safety; improve education/awareness on food waste; policies to eliminate ambiguous food labelling include well-defined and clear date labelling systems for food ( [[#Wilson--2017|Wilson et al. 2017]] ); policies to support R&amp;D to improve packaging to extend shelf life ( [[#Thyberg--2016|Thyberg and Tonjes 2016]] ); charging according to how much food households throw away

|-
| '''Reduce size of dwellings'''

| Size of dwellings getting larger in many countries

| Compact city design, taxing residential properties with high per capita area, progressive taxation of high status consumption ( [[#Ramakrishnan--2021|Ramakrishnan and Creutzig 2021]] )

|-
| '''Reduce/Avoid heating, cooling and lighting in dwellings'''

| Change in individual behaviour in dress codes and working times

| Temperature set point as norm; building energy codes that set building standards; bioclimatic and/or zero emissions buildings; cities and buildings that incorporate features like daylighting and increased building depth, height, and compactness ( [[#Steemers--2003|Steemers 2003]] ; [[#Creutzig--2016a|Creutzig et al. 2016a]] )

|-
| '''Sharing economy for more service per product'''

| Lack of inclusivity and involvement of users in design. Digital divide, unequal access and unequal digital literacy ( [[#Pouri--2018|Pouri and Hilty 2018]] ). Political or power relations among actors involved in the sharing economy ( [[#Curtis--2019|Curtis and Lehner 2019]] )

| Lower prices for public parking, and subsidies towards the purchase of electric vehicles for providers of electric vehicle sharing services ( [[#Jung--2018|Jung and Koo 2018]] )

|}

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==== 5.6.2.2 ‘Shift’ Policies ====

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As indicated in Table 5.6, ‘Shift’ policies have various forms such as the demand for low-carbon materials for buildings and infrastructure in manufacturing and services and shift from meat-based protein, mainly beef, to plant-based diets of other protein sources ( ''high evidence, high agreement'' ) ( [[#Springmann--2016|Springmann et al. 2016]] a; [[#Ritchie--2018|Ritchie et al. 2018]] ; [[#Willett--2019|Willett et al. 2019]] ). Governments also play a direct role beyond nudging citizens with information about health and well-being.While the effectiveness of these policies on behaviour change overall may be limited ( [[#Pearson-Stuttard--2017|Pearson-Stuttard et al. 2017]] ; [[#Shangguan--2019|Shangguan et al. 2019]] ), there is some room for policy to influence actors upstream, such as industry and supermarkets, which may give rise to longer-term, structural change.

'''Table 5.6 | Examples of policies to enable ‘Shift’ options.'''

{| class="wikitable"
|-
| '''Mitigation option'''

| '''Perceived struggles to overcome'''

| '''Policy to overcome struggles''' '''(Incentives)'''

|-
| '''More walking, less car use, train rather air travel'''

| Adequate infrastructure may be absent, speed a part of modern life

| – Congestion charges ( [[#Pearson-Stuttard--2017|Pearson-Stuttard et al. 2017]] ; [[#Shangguan--2019|Shangguan et al. 2019]] ); deliberate urban design including cycling lanes, shared micromobility, and extensive cycling infrastructure; synchronised/integrated transport system and timetable

– Fair street space allocation ( [[#Creutzig--2020|Creutzig et al. 2020]] )

|-
| '''Multifamily housing'''

| Zonings that favour single family homes have been dominant in planning ( [[#Hagen--2016|Hagen 2016]] )

| Taxation, relaxation of single-family zoning policies and land use regulation ( [[#Geffner--2017|Geffner 2017]] )

|-
| '''Shifting from meat to other protein'''

| Minimal meat required for protein intake, especially in developing countries for population suffering from malnutrition and when plant-based protein is lacking ( [[#Garnett--2011|Garnett 2011]] ; [[#Sunguya--2014|Sunguya et al. 2014]] ; [[#Behrens--2017|Behrens et al. 2017]] ; [[#Godfray--2018|Godfray et al. 2018]] ); dominance of market-based instruments limits governments’ role to nudging citizens with information about health and well-being, and point-of-purchase labelling ( [[#Pearson-Stuttard--2017|Pearson-Stuttard et al. 2017]] ; [[#Shangguan--2019|Shangguan et al. 2019]] )

| – Tax on meat/beef in wealthier countries and/or households ( [[#Edjabou--2013|Edjabou and Smed 2013]] ; [[#Säll--2015|Säll and Gren 2015]] )

– Nationally recommended diets ( [[#Garnett--2011|Garnett 2011]] ; [[#Sunguya--2014|Sunguya et al. 2014]] ; [[#Behrens--2017|Behrens et al. 2017]] ; [[#Godfray--2018|Godfray et al. 2018]] )

|-
| '''Material-efficient product design, packaging'''

| Resistance by architects and builders who might perceive risks with lean designs. Cultural and social norms. Policy measures not keeping up with changes on the ground such as increased consumption of packaging

| Embodied carbon standards for buildings ( [[#IEA--2019c|IEA 2019c]] )

|-
| '''Architectural design with shading and ventilation'''

| Lack of education, awareness and capacity for new thinking, local air pollution

| Incentives for increased urban density and incentives to encourage architectural forms with lower surface-to-volume ratios and increased shading support ( [[#Creutzig--2016a|Creutzig et al. 2016a]] )

|}

Mobility services is one of the key areas where a combination of market-based and command-and-control measures have been implemented to persuade large numbers of people to get out of their automobiles and take up public transport and cycling alternatives ( [[#Gehl--2011|Gehl et al. 2011]] ). Congestion charges are often complemented by other measures, such as company subsidies for bicycles, to incentivise the shift to public mobility services. Attracting people to public transport requires sufficient spatial coverage of transport with adequate level of provision, and good quality service at affordable fares ( [[#Sims--2014|Sims et al. 2014]] ; [[#Moberg--2019|Moberg et al. 2019]] ) ( ''high evidence, high agreement'' ). Cities such as Bogota, Colombia, Buenos Aires, Argentina, and Santiago, Chile, have seen rapid growth of cycling, resulting in a six-fold increase in cyclists ( [[#Pucher--2017|Pucher and Buehler 2017]] ). Broadly, the history and type of city determines how quickly the transition to public modes of transport can be achieved. For example, cities in developed countries enjoy an advantage in that there is a network of high-quality public transport predating the advent of automobiles, whereas cities in less developed countries are latecomers to large-scale network infrastructure ( [[#UN-Habitat--2013|UN-Habitat 2013]] ; [[#Gota--2019|Gota et al. 2019]] ).

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==== 5.6.2.3 ‘Improve’ Policies ====

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‘Improve’ policies focus on the efficiency and enhancement of technological performance of services (Table 5.7). In mobility services, ‘Improve’ policies aim at improving vehicles, comfort, fuels, transport operations and management technologies; and in buildings, they include policies for improving efficiency of heating systems and retrofitting existing buildings. Efficiency improvements in electric cooking appliances, together with the ongoing decrease in prices of renewable energy technologies, are opening policy opportunities to support households to adopt electrical cooking at mass scale ( ''medium evidence, medium agreement'' ) ( [[#IEA--2017c|IEA 2017c]] ; [[#Puzzolo--2019|Puzzolo et al. 2019]] ). These actions towards cleaner energy for cooking often come with cooking-related reduction of GHG emissions, even though the extent of the reductions is highly dependent on context and technology and fuel pathways ( ''high evidence, high agreement'' ) ( [[#Martínez--2017|Martínez et al. 2017]] ; [[#Mondal--2018|Mondal et al. 2018]] ; [[#Rosenthal--2018|Rosenthal et al. 2018]] ; [[#Serrano-Medrano--2018|Serrano-Medrano et al. 2018]] ; [[#Dagnachew--2019|Dagnachew et al. 2019]] ) (Box 5.6).

Table 5.7 highlights the significant progress made in the uptake of the electrical vehicle (EV) in Europe, driven by a suite of incentives and policies. Increased activity in widening electric vehicle use is also occurring in developing countries. The Indian Government’s proposal to reach the target of a 100% electric vehicle fleet by 2030 has stimulated investment in charging infrastructure that can facilitate diffusion of larger EVs ( [[#Dhar--2017|Dhar et al. 2017]] ). Although the proposal was not converted into a policy, India’s large and growing two-wheeler market has benefitted from the policy attention on EVs, showing a significant potential for increasing the share of electric two- and three-wheelers in the short term ( [[#Ahmad--2019|Ahmad and]] [[#Creutzig--2019|Creutzig 2019]] ). Similar opportunities exist for China, where e-bikes have replaced car trips and are reported to act as intermediate links in multimodal mobility ( [[#Cherry--2016|Cherry et al. 2016]] ).

In recent years, policy interest has arisen to address the energy access challenge in Africa using low-carbon energy technologies to meet energy for poverty reduction and climate action simultaneously ( [[#Rolffs--2015|Rolffs et al. 2015]] ; [[#Fuso%20Nerini--2018|Fuso Nerini et al. 2018]] ; [[#Mulugetta--2019|Mulugetta et al. 2019]] ). This aspiration has been bolstered on the technical front by significant advances in appliance efficiency such as light-emitting diode (LED) technology, complemented by the sharp reduction in the cost of renewable energy technologies, and largely driven by market-stimulating policies and public R&amp;D to mitigate risks ( ''high evidence, high agreement'' ) ( [[#Alstone--2015|Alstone et al. 2015]] ; [[#Zubi--2019|Zubi et al. 2019]] ).

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<span id="policies-in-transition-phases"></span>
=== 5.6.3 Policies in Transition Phases ===

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Demand-side policies tend to vary for different transition phases ( ''high evidence, high agreement'' ) ( [[#Roberts--2019|Roberts and Geels 2019]] ; [[#Sandin--2019|Sandin et al. 2019]] ). In the first phase, which is characterised by the emergence or introduction of radical innovations in small niches, policies focus on: (i) supporting R&amp;D and demonstration projects to enable learning and capability developments, (ii) nurturing the building of networks and multi-stakeholder interactions, and (iii) providing future orientation through visions or targets ( [[#Brown--2003|Brown et al. 2003]] ; [[#López-García--2019|López-García et al. 2019]] ; [[#Roesler--2019|Roesler and Hassler 2019]] ). In the second phase, the policy emphasis shifts towards upscaling of experiments, standardisation, cost reduction, and the creation of early market niches ( [[#Borghei--2018|Borghei and Magnusson 2018]] ; [[#Ruggiero--2018|Ruggiero et al. 2018]] ). In the third and later phases, comprehensive policy mixes are used to stimulate mass adoption, infrastructure creation, social acceptance and business investment ( [[#Fichter--2016|Fichter and Clausen 2016]] ; [[#Geels--2018|Geels et al. 2018]] ; [[#Strauch--2020|Strauch 2020]] ). In the fourth phase, transitions can also be stimulated through policies that weaken or phase out existing regimes, such as removing inefficient subsidies (for cheap petrol or fuel oil) that encourage wasteful consumption, increasing taxes on carbon-intensive products and practices (Box 5.11), or substantially tightening regulations and standards ( [[#Kivimaa--2016|Kivimaa and Kern 2016]] ; [[#David--2017|David 2017]] ; [[#Rogge--2017|Rogge and Johnstone 2017]] ).

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<span id="box-5.11-carbon-pricing-and-fairness"></span>
=== Box 5.11 | Carbon Pricing and Fairness ===

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Whether the public supports specific policy instruments for reducing greenhouse gas emissions is determined by cultural and political world views ( [[#Cherry--2017|Cherry et al. 2017]] ; [[#Kotchen--2017|Kotchen et al. 2017]] ; [[#Alberini--2018|Alberini et al. 2018]] ) and national positions in international climate negotiations, with major implications for policy design. For example, policy proposals need to circumvent ‘solution aversion’: that is, individuals are more doubtful about the urgency of climate change mitigation if the proposed policy contradicts their political worldviews ( [[#Campbell--2014|Campbell and Kay 2014]] ). While there are reasons to believe that carbon pricing is the most efficient way to reduce emissions, a recent literature – focusing on populations in Western Europe and North America and carbon taxes – documents that efficiency features alone is not what makes citizens like or dislike carbon pricing schemes ( [[#Kallbekken--2011|Kallbekken et al. 2011]] ; [[#Carattini--2017|Carattini et al. 2017]] ; [[#Klenert--2018|Klenert et al. 2018]] ).

Citizens tend to ignore or doubt the idea that pricing carbon emissions reduces GHG emissions ( [[#Kallbekken--2011|Kallbekken et al. 2011]] ; [[#Douenne--2019|Douenne and Fabre 2019]] ; [[#Maestre-Andrés--2019|Maestre-Andrés et al. 2019]] ). Further, citizens have fairness concerns about carbon pricing ( [[#Büchs--2013|Büchs and Schnepf 2013]] ; [[#Douenne--2019|Douenne and Fabre 2019]] ; [[#Maestre-Andrés--2019|Maestre-Andrés et al. 2019]] ), even if higher carbon prices can be made progressive by suitable use of revenues ( [[#Rausch--2011|Rausch et al. 2011]] ; [[#Williams--2015|Williams et al. 2015]] ; [[#Klenert--2016|Klenert and Mattauch 2016]] ). There are also non-economic properties of policy instruments that matter for public support: Calling a carbon price a ‘CO 2 levy’ alleviates solution aversion ( [[#Kallbekken--2011|Kallbekken et al. 2011]] ; [[#Carattini--2017|Carattini et al. 2017]] ). It may be that the word ‘tax’ evokes a feeling of distrust in government and fears of high costs, low benefits and distributional effects ( [[#Strand--2020|Strand 2020]] ). Trust in politicians is negatively correlated with higher carbon prices ( [[#Hammar--2006|Hammar and Jagers 2006]] ; [[#Rafaty--2018|Rafaty 2018]] ) and political campaigns for a carbon tax can lower public support for them ( [[#Anderson--2019|Anderson et al. 2019]] ). Few developing countries have adopted carbon taxes, probably due to high costs, relatively low benefits, and distributional effects ( [[#Strand--2020|Strand 2020]] ).

To address these realities regarding support for carbon pricing, some studies have examined whether specific uses of the revenue can increase public support for higher carbon prices ( [[#Carattini--2017|Carattini et al. 2017]] ; [[#Beiser-McGrath--2019|Beiser-McGrath and Bernauer 2019]] ). Doubt about the environmental effectiveness of carbon pricing may be alleviated if revenue from carbon pricing is earmarked for specific uses ( [[#Kallbekken--2011|Kallbekken et al. 2011]] ; [[#Carattini--2017|Carattini et al. 2017]] ) and higher carbon prices may then be supported ( [[#Beiser-McGrath--2019|Beiser-McGrath and Bernauer 2019]] ). This is especially the case for using the proceeds on ‘green investment’ in infrastructure or energy efficiency programmes ( [[#Kotchen--2017|Kotchen et al. 2017]] ). Further, returning the revenues to individuals in a salient manner may increase public support and alleviate fairness proposals, given sufficient information ( [[#Carattini--2017|Carattini et al. 2017]] ; [[#Klenert--2018|Klenert et al. 2018]] ). Perceived fairness is one of the strongest predictors of policy support ( [[#Jagers--2010|Jagers et al. 2010]] ; [[#Whittle--2019|Whittle et al. 2019]] ).

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<span id="policy-sequencing-and-packaging-to-strengthen-enabling-conditions"></span>

=== 5.6.4 Policy Sequencing and Packaging to Strengthen Enabling Conditions ===

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Policy coordination is critical to manage infrastructure interdependence across sectors, and to avoid trade-off effects ( [[#Raven--2007|Raven and Verbong 2007]] ; [[#Hiteva--2019|Hiteva and Watson 2019]] ), specifically requiring the consideration of interactions among supply-side and demand-side measures ( ''high evidence'' , ''high agreement'' ) ( [[#Kivimaa--2014|Kivimaa and Virkamäki 2014]] ; [[#Rogge--2016|Rogge and Reichardt 2016]] ; de Coninck et al. 2018; [[#Edmondson--2019|Edmondson et al. 2019]] ). For example, the amount of electricity required for cooking can overwhelm the grid which can lead to failure, causing end-users to shift back to traditional biomass or fossil fuels ( [[#Ateba--2018|Ateba et al. 2018]] ; [[#Israel-Akinbo--2018|Israel-Akinbo et al. 2018]] ); thus grid stability policies need to be undertaken in conjunction.

Policymakers operate in a politically dynamic national and international environment, and their policies often reflect their contextual situations and constraints with regards to climate-related reforms ( [[#Levin--2012|Levin et al. 2012]] ; [[#Copland--2019|Copland 2019]] ), including differentiation between developed and developing countries ( ''high evidence, high agreement'' ) (Beer and [[#Beer--2014|Beer 2014]] ; [[#Roy--2018c|Roy et al. 2018c]] ) ''.'' Variables such as internal political stability, equity, informality (Box 5.10), macro-economic conditions, public debt, governance of policies, global oil prices, quality of public services, and the maturity of green technologies play important roles in determining policy directions.

Sequencing policies appropriately is a success factor for climate policy regimes ( ''high evidence'' , ''high agreement'' ). In most situations policy measures require a preparatory phase that prepares the ground by lowering the costs of policies, communicating the costs and benefits to citizens, and building coalitions for policies, thus reducing political resistance ( [[#Meckling--2017|Meckling et al. 2017]] ). This policy sequencing aims to incrementally relax or remove barriers over time to enable significant cumulative increases in policy stringency and create coalitions that support future policy development ( [[#Pahle--2018|Pahle et al. 2018]] ). German policies on renewables began with funding for research, design and development (RD&amp;D), then subsidies for demonstration projects during the 1970s and 1980s, and continued to larger-scale projects such as ‘Solar Roofs’ programmes in the 1990s, including scaled-up feed-in tariffs for solar power ( [[#Jacobsson--2006|Jacobsson and Lauber 2006]] ). These policies led to industrial expansion in wind and solar energy systems, giving rise to powerful renewables interest coalitions that defend existing measures and lend political support for further action. Policy sequencing has also been deployed to introduce technology bans and strict performance standards with a view to eliminating emissions as the end goal, and may involve simultaneous support for low-carbon options while deliberately phasing out established technological regimes ( [[#Rogge--2017|Rogge and Johnstone 2017]] ).

As a key contending policy instrument, carbon pricing also requires embedding into policy packages ( ''high evidence'' , ''medium agreement'' ) ''.'' Pricing may be regressive and perceived as additional costs by households and industry, making investments in green infrastructure politically unfeasible, as examples from France and Australia show ( [[#Copland--2019|Copland 2019]] ; [[#Douenne--2020|Douenne and Fabre 2020]] ). Reforms that would push up household energy expenses are often left aside for fear of how citizens, especially the poor, would react or cope with higher bills ( ''high evidence'' , ''medium agreement'' ) ( [[#Martinez--2017|Martinez and Viegas 2017]] ; [[#Tesfamichael--2021|Tesfamichael et al. 2021]] ). This makes it important to precede carbon pricing with investments in renewable energy and low-carbon transport modes ( [[#Biber--2017|Biber et al. 2017]] ; [[#Tvinnereim--2018|Tvinnereim and Mehling 2018]] ), and especially support for developing countries by building up low-carbon energy and mobility infrastructures and technologies, thus reducing resistance to carbon pricing ( [[#Creutzig--2019|Creutzig 2019]] ). Additionally, carbon pricing receives higher acceptance if fairness and distributive considerations are made explicit in revenue distribution (Box 5.11).

The effectiveness of a policy package is determined by design decisions as well as the wider governance context that include the political environment, institutions for coordination across scales, bureaucratic traditions, and judicial functioning ( ''high evidence'' , ''high agreement'' ) ( [[#Howlett--2013|Howlett and Rayner 2013]] ; [[#Rogge--2013|Rogge and Reichardt 2013]] ; [[#Rosenow--2016|Rosenow et al. 2016]] ). Policy packages often emerge through interactions between different policy instruments as they operate in either complementary or contradictory ways, resulting from conflicting policy goals ( [[#Cunningham--2013|Cunningham et al. 2013]] ; [[#Givoni--2013|Givoni et al. 2013]] ). An example includes the acceleration in shift from traditional biomass to the adoption of modern cooking fuel for 80 million households in rural India over a very short period of four years (2016–2020), which employed a comprehensive policy package including financial incentives, infrastructural support and strengthening of the supply chain to induce households to shift towards a clean cooking fuel from the use of biomass ( [[#Kumar--2019|Kumar 2019]] ). This was operationalised by creating a LPG supply chain by linking oil and gas companies with distributors to assure availability, and create infrastructure for local storage along with an improvement of the rural road network, especially in the rural context ( [[#Sankhyayan--2019|Sankhyayan and Dasgupta 2019]] ). State governments initiated separate policies to increase the distributorship of LPG in their states ( [[#Kumar--2016|Kumar et al. 2016]] ). Similarly, policy actions for scaling up electric vehicles need to be well designed and coordinated where EV policy, transport policy and climate policy are used together, working on different decision points and different aspects of human behaviour ( [[#Barton--2017|Barton and Schütte 2017]] ). The coordination of the multiple policy actions enables co-evolution of multiple outcomes that involve shifting towards renewable energy production, improving access to charging infrastructure, carbon pricing and other GHG measures ( [[#Wolbertus--2018|Wolbertus et al. 2018]] ).

Design of policy packages should consider not only policies that support low-carbon transitions but also those that challenge existing carbon-intensive regimes, generating not just policy ‘winners’ but also ‘losers’ ( ''high evidence'' , ''high agreement'' ) ( [[#Carley--2020|Carley and Konisky 2020]] ). The winners include low-carbon innovators and entrepreneurs, while the potential losers include incumbents with vested interests in sustaining the status quo ( [[#Mundaca--2018|Mundaca et al. 2018]] ; [[#Monasterolo--2019|Monasterolo and Raberto 2019]] ). Low-carbon policy packages would benefit from looking beyond climate benefits to include non-climate benefits such as health benefits, fuel poverty reductions and environmental co-benefits ( [[#Ürge-Vorsatz--2014|Ürge-Vorsatz et al. 2014]] ; [[#Sovacool--2020b|Sovacool et al. 2020b]] ). The uptake of decentralised energy services using solar PV in rural areas in developing countries is one such example where successful initiatives are linked to the convergence of multiple policies that include import tariffs, research incentives for R&amp;D, job creation programmes, policies to widen health and education services, and strategies for increased safety for women and children ( [[#Kattumuri--2019|Kattumuri and Kruse 2019]] ; [[#Gebreslassie--2020|Gebreslassie 2020]] ).

The energy-efficient lighting transition in Europe represents a good case of the formation of policy coalitions that led to the development of policy packages. As attention to energy efficiency in Europe increased in the 1990s, policymakers attempted to stimulate energy-saving lamp diffusion through voluntary measures. But policies stimulated only limited adoption. Consumers perceived compact fluorescent lamps (CFLs) as giving ‘cold’ light, being unattractively shaped, taking too long to achieve full brightness, unsuitable for many fixtures, and unreliable ( [[#Wall--2009|Wall and Crosbie 2009]] ). Still, innovations by major CFL and LED multinationals continued. Increasing political attention to climate change and criticisms from environmental NGOs (e.g. WWF, Greenpeace) strengthened awareness about the inefficiency of incandescent light bulbs (ILBs), which led to negative socio-cultural framings that associated ILBs with energy waste ( [[#Franceschini--2016|Franceschini and Alkemade 2016]] ). The combined pressures from the lighting industry, NGOs and member states led the European Commission to introduce the 2009 ban of ILBs of more than 80W, progressing to lower-wattage bans in successive years. While the ILB ban initially mainly boosted CFL diffusion, it also stimulated LED uptake. LED prices decreased quickly by more than 85% between 2008 and 2012 ( [[#Sanderson--2014|Sanderson and Simons 2014]] ), because of scale economies, standardisation and commoditisation of LED chip technology, and improved manufacturing techniques. Because of further rapid developments to meet consumer tastes, LEDs came to be seen as the future of domestic lighting ( [[#Franceschini--2018|Franceschini et al. 2018]] ). Acknowledging these changing views, the 2016 and 2018 European bans on directional and non-directional halogen bulbs explicitly intended to further accelerate the LED transition and reduce energy consumption for residential lighting.

In summary, more equitable societies are associated with high levels of social trust and enable actions that reduce GHG emissions. To this end, people play an important role in the delivery of demand-side mitigation options within which efficiency and ‘Improve’ options dominate. Policies that are aimed at behaviour and lifestyle changes come with political risks for policymakers. However, the potential exists for broadening demand-side interventions to include ‘Avoid’ and ‘Shift’ policies. Longer term thinking and implementation that involves careful sequencing of policies as well as designing policy packages that address multiple co-benefits would be critical to manage interactions among supply-side and demand-side options to accelerate mitigation.

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