Editing IPCC:AR6/SR15/Chapter-2 (section)

== 2.5.1 Policy Frameworks and Enabling Conditions ==

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Moving from a 2°C to a 1.5°C pathway implies bold integrated policies that enable higher socio-technical transition speeds, larger deployment scales, and the phase-out of existing systems that may lock in emissions for decades ( ''high confidence'' ) (Geels et al., 2017; Kuramochi et al., 2017; Rockström et al., 2017; Vogt-Schilb and Hallegatte, 2017; Kriegler et al., 2018a; Michaelowa et al., 2018) <sup>[[#fn:r485|485]]</sup> . This requires higher levels of transformative policy regimes in the near term, which allow deep decarbonization pathways to emerge and a net zero carbon energy–economy system to emerge in the 2040–2060 period (Rogelj et al., 2015b; Bataille et al., 2016b) <sup>[[#fn:r486|486]]</sup> . This enables accelerated levels of technological deployment and innovation (Geels et al., 2017; IEA, 2017a; Grubler et al., 2018) <sup>[[#fn:r487|487]]</sup> and assumes more profound behavioural, economic and political transformation (Sections 2.3, 2.4 and 4.4). Despite inherent levels of uncertainty attached to modelling studies (e.g., related to climate and carbon cycle response), studies stress the urgency for transformative policy efforts to reduce emissions in the short term (Riahi et al., 2015; Kuramochi et al., 2017; Rogelj et al., 2018) <sup>[[#fn:r488|488]]</sup> .

The available literature indicates that mitigation pathways in line with 1.5°C pathways would require stringent and integrated policy interventions ( ''very high confidence'' ). Higher policy ambition often takes the form of stringent economy-wide emission targets (and resulting peak-and-decline of emissions), larger coverage of NDCs to more gases and sectors (e.g., land-use, international aviation), much lower energy and carbon intensity rates than historically seen, carbon prices much higher than the ones observed in real markets, increased climate finance, global coordinated policy action, and implementation of additional initiatives (e.g., by non-state actors) (Sections 2.3, 2.4 and 2.5.2). The diversity (beyond explicit carbon pricing) and effectiveness of policy portfolios are of prime importance, particularly in the short-term (Mundaca and Markandya, 2016; Kuramochi et al., 2017; OECD, 2017; Kriegler et al., 2018a; Michaelowa et al., 2018) <sup>[[#fn:r489|489]]</sup> . For instance, deep decarbonization pathways in line with a 2˚C target (covering 74% of global energy-system emissions) include a mix of stringent regulation (e.g., building codes, minimum performance standards), carbon pricing mechanisms and R&amp;D (research and development) innovation policies (Bataille et al., 2016a) <sup>[[#fn:r490|490]]</sup> . Explicit carbon pricing, direct regulation and public investment to enable innovation are critical for deep decarbonization pathways (Grubb et al., 2014) <sup>[[#fn:r491|491]]</sup> . Effective planning (including compact city measures) and integrated regulatory frameworks are also key drivers in the IEA-ETP B2DS study for the transport sector (IEA, 2017a) <sup>[[#fn:r492|492]]</sup> . Effective urban planning can reduce GHG emissions from urban transport between 20% and 50% (Creutzig, 2016) <sup>[[#fn:r493|493]]</sup> . Comprehensive policy frameworks would be needed if the decarbonization of the power system is pursued while increasing end-use electrification (including transport) (IEA, 2017a) <sup>[[#fn:r494|494]]</sup> . Technology policies (e.g., feed-in-tariffs), financing instruments, carbon pricing and system integration management driving the rapid adoption of renewable energy technologies are critical for the decarbonization of electricity generation (Bruckner et al., 2014; Luderer et al., 2014; Creutzig et al., 2017; Pietzcker et al., 2017) <sup>[[#fn:r495|495]]</sup> . Likewise, low-carbon and resilient investments are facilitated by a mix of coherent policies, including fiscal and structural reforms (e.g., labour markets), public procurement, carbon pricing, stringent standards, information schemes, technology policies, fossil-fuel subsidy removal, climate risk disclosure, and land-use and transport planning (OECD, 2017) <sup>[[#fn:r496|496]]</sup> . Pathways in which CDR options are restricted emphasize the strengthening of near-term policy mixes (Luderer et al., 2013; Kriegler et al., 2018a) <sup>[[#fn:r497|497]]</sup> . Together with the decarbonization of the supply side, ambitious policies targeting fuel switching and energy efficiency improvements on the demand side play a major role across mitigation pathways (Clarke et al., 2014; Kriegler et al., 2014b; Riahi et al., 2015; Kuramochi et al., 2017; Brown and Li, 2018; Rogelj et al., 2018; Wachsmuth and Duscha, 2018) <sup>[[#fn:r498|498]]</sup> .

The combined evidence suggests that aggressive policies addressing energy efficiency are central in keeping 1.5°C within reach and lowering energy system and mitigation costs ( ''high confidence'' ) (Luderer et al., 2013; Rogelj et al., 2013b, 2015b; Grubler et al., 2018) <sup>[[#fn:r499|499]]</sup> . Demand-side policies that increase energy efficiency or limit energy demand at a higher rate than historically observed are critical enabling factors for reducing mitigation costs in stringent mitigation pathways across the board (Luderer et al., 2013; Rogelj et al., 2013b, 2015b; Clarke et al., 2014; Bertram et al., 2015a; Bataille et al., 2016b) <sup>[[#fn:r500|500]]</sup> . Ambitious sector-specific mitigation policies in industry, transportation and residential sectors are needed in the short run for emissions to peak in 2030 (Méjean et al., 2018) <sup>[[#fn:r501|501]]</sup> . Stringent demand-side policies (e.g., tightened efficiency standards for buildings and appliances) driving the expansion, efficiency and provision of high-quality energy services are essential to meet a 1.5˚C mitigation target while reducing the reliance on CDR (Grubler et al., 2018) <sup>[[#fn:r502|502]]</sup> . A 1.5˚C pathway for the transport sector is possible using a mix of additional and stringent policy actions preventing (or reducing) the need for transport, encouraging shifts towards efficient modes of transport, and improving vehicle-fuel efficiency (Gota et al., 2018) <sup>[[#fn:r503|503]]</sup> . Stringent demand-side policies also reduce the need for CCS (Wachsmuth and Duscha, 2018) <sup>[[#fn:r504|504]]</sup> . Even in the presence of weak near term policy frameworks, increased energy efficiency lowers mitigation costs noticeably compared to pathways with reference energy intensity (Bertram et al., 2015a) <sup>[[#fn:r505|505]]</sup> . Common issues in the literature relate to the rebound effect, the potential overestimation of the effectiveness of energy efficiency policy, and policies to counteract the rebound (Saunders, 2015; van den Bergh, 2017; Grubler et al., 2018) <sup>[[#fn:r506|506]]</sup> (Sections 2.4 and 4.4).

SSP-based modelling studies underline that socio-economic and climate policy assumptions strongly influence mitigation pathway characteristics and the economics of achieving a specific climate target ( ''very high confidence'' ) (Bauer et al., 2017; Guivarch and Rogelj, 2017; Riahi et al., 2017; Rogelj et al., 2018) <sup>[[#fn:r507|507]]</sup> . SSP assumptions related to economic growth and energy intensity are critical determinants of projected CO <sub>2</sub> emissions (Marangoni et al., 2017) <sup>[[#fn:r508|508]]</sup> . A multimodel inter-comparison study found that mitigation challenges in line with a 1.5˚C target vary substantially across SSPs and policy assumptions (Rogelj et al., 2018) <sup>[[#fn:r509|509]]</sup> . Under SSP1-SPA1 (sustainability) and SSP2-SPA2 (middle-of-the-road), the majority of IAMs were capable of producing 1.5˚C pathways. On the contrary, none of the IAMs contained in the SR1.5 database could produce a 1.5°C pathway under SSP3-SPA3 assumptions. Preventing elements include, for instance, climate policy fragmentation, limited control of land-use emissions, heavy reliance on fossil fuels, unsustainable consumption and marked inequalities (Rogelj et al., 2018) <sup>[[#fn:r510|510]]</sup> . Dietary aspects of the SSPs are also critical: climate-friendly diets were contained in ‘sustainability’ (SSP1) and meat-intensive diets in SSP3 and SSP5 (Popp et al., 2017) <sup>[[#fn:r511|511]]</sup> . CDR requirements are reduced under ‘sustainability’ related assumptions (Strefler et al., 2018b) <sup>[[#fn:r512|512]]</sup> . These are major policy-related reasons for why SSP1-SPA1 translates into relatively low mitigation challenges whereas SSP3-SPA3 and SSP5-SPA5 entail futures that pose the highest socio-technical and economic challenges. SSPs/SPAs assumptions indicate that policy-driven pathways that encompass accelerated change away from fossil fuels, large-scale deployment of low-carbon energy supplies, improved energy efficiency and sustainable consumption lifestyles reduce the risks of climate targets becoming unreachable (Clarke et al., 2014; Riahi et al., 2015, 2017; Marangoni et al., 2017; Rogelj et al., 2017, 2018; Strefler et al., 2018b) <sup>[[#fn:r513|513]]</sup> .

Policy assumptions that lead to weak or delayed mitigation action from what would be possible in a fully cooperative world strongly influence the achievability of mitigation targets ( ''high confidence'' ) (Luderer et al., 2013; Rogelj et al., 2013b; OECD, 2017; Holz et al., 2018a; Strefler et al., 2018b) <sup>[[#fn:r514|514]]</sup> . Such regimes also include current NDCs (Fawcett et al., 2015; Aldy et al., 2016; Rogelj et al., 2016a, 2017; Hof et al., 2017; van Soest et al., 2017) <sup>[[#fn:r515|515]]</sup> , which have been reported to make achieving a 2°C pathway unattainable without CDR (Strefler et al., 2018b) <sup>[[#fn:r516|516]]</sup> . Not strengthening NDCs would make it very challenging to keep 1.5°C within reach (see Section 2.3 and Cross-Chapter Box 11 in Chapter 4). One multimodel inter-comparison study (Luderer et al., 2016b, 2018) <sup>[[#fn:r517|517]]</sup> explored the effects on 1.5°C pathways assuming the implementation of current NDCs until 2030 and stringent reductions thereafter. It finds that delays in globally coordinated actions lead to various models reaching no 1.5°C pathways during the 21st century. Transnational emission reduction initiatives (TERIs) outside the UNFCCC have also been assessed and found to overlap (70–80%) with NDCs and be inadequate to bridge the gap between NDCs and a 2°C pathway (Roelfsema et al., 2018) <sup>[[#fn:r518|518]]</sup> . Weak and fragmented short-term policy efforts use up a large share of the long-term carbon budget before 2030–2050 (Bertram et al., 2015a; van Vuuren et al., 2016) <sup>[[#fn:r519|519]]</sup> and increase the need for the full portfolio of mitigation measures, including CDR (Clarke et al., 2014; Riahi et al., 2015; Xu and Ramanathan, 2017) <sup>[[#fn:r520|520]]</sup> . Furthermore, fragmented policy scenarios also exhibit ‘carbon leakage’ via energy and capital markets (Arroyo-Currás et al., 2015; Kriegler et al., 2015b) <sup>[[#fn:r521|521]]</sup> . A lack of integrated policy portfolios can increase the risks of trade-offs between mitigation approaches and sustainable development objectives (see Sections 2.5.3 and 5.4). However, more detailed analysis is needed about realistic (less disruptive) policy trajectories until 2030 that can strengthen near-term mitigation action and meaningfully decrease post-2030 challenges (see Chapter 4, Section 4.4).

Whereas the policy frameworks and enabling conditions identified above pertain to the ‘idealized’ dimension of mitigation pathways, aspects related to 1.5°C mitigation pathways in practice are of prime importance. For example, issues related to second-best stringency levels, international cooperation, public acceptance, distributional consequences, multilevel governance, non-state actions, compliance levels, capacity building, rebound effects, linkages across highly heterogeneous policies, sustained behavioural change, finance and intra- and inter-generational issues need to be considered (see Chapter 4, Section 4.4) (Bataille et al., 2016a; Mundaca and Markandya, 2016; Baranzini et al., 2017; MacDougall et al., 2017; van den Bergh, 2017; Vogt-Schilb and Hallegatte, 2017; Chan et al., 2018; Holz et al., 2018a; Klinsky and Winkler, 2018; Michaelowa et al., 2018; Patterson et al., 2018) <sup>[[#fn:r522|522]]</sup> . Furthermore, policies interact with a wide portfolio of pre-existing policy instruments that address multiple areas (e.g., technology markets, economic growth, poverty alleviation, climate adaptation) and deal with various market failures (e.g., information asymmetries) and behavioural aspects (e.g., heuristics) that prevent or hinder mitigation actions (Kolstad et al., 2014; Mehling and Tvinnereim, 2018) <sup>[[#fn:r523|523]]</sup> . The socio-technical transition literature points to multiple complexities in real-world settings that prevent reaching ‘idealized’ policy conditions but at the same time can still accelerate transformative change through other co-evolutionary processes of technology and society (Geels et al., 2017; Rockström et al., 2017) <sup>[[#fn:r524|524]]</sup> . Such co-processes are complex and go beyond the role of policy (including carbon pricing) and comprise the role of citizens, businesses, stakeholder groups or governments, as well as the interplay of institutional and socio-political dimensions (Michaelowa et al., 2018; Veland et al., 2018) <sup>[[#fn:r525|525]]</sup> . It is argued that large system transformations, similar to those in 1.5°C pathways, require prioritizing an evolutionary and behavioural framework in economic theory rather than an optimization or equilibrium framework as is common in current IAMs (Grubb et al., 2014; Patt, 2017) <sup>[[#fn:r526|526]]</sup> . Accumulated know-how, accelerated innovation and public investment play a key role in (rapid) transitions (see Sections 4.2 and 4.4) (Geels et al., 2017; Michaelowa et al., 2018) <sup>[[#fn:r527|527]]</sup> .

In summary, the emerging literature supports the AR5 on the need for integrated, robust and stringent policy frameworks targeting both the supply and demand-side of energy-economy systems ( ''high confidence'' ). Continuous ex-ante policy assessments provide learning opportunities for both policy makers and stakeholders.

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