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

=== 2.8.4 Emission Impacts of Other Related Policies ===

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Policies other than those intended directly to mitigate GHGs can also influence these emissions. Policies to protect the stratospheric ozone layer is a case in point. Implementing the Montreal Protocol and its amendments, emissions of controlled ozone-depleting substances (ODSs) (those covered by the protocol) declined to a very low level of about 1.4 GtCO 2 -eq yr –1 by 2010, avoiding GHG emissions of an estimated 13.3–16.7 GtCO 2 -eq yr –1 (9.7–12.5 GtCO 2 -eq yr –1 when accounting for the ozone depletion and hydrofluorocarbons (HFCs) offsets) ( [[#Velders--2007|Velders et al. 2007]] ). Yet fluorinated gases (F-gases), the substances introduced to substitute ODSs are also potent GHGs. See [[#2.2|Section 2.2]] for emissions data, and [[IPCC:Wg3:Chapter:Chapter-13|Chapter 13]] on current policies to mitigate HFCs and other F-gases. GHG implications of two other categories of non-climate policies are briefly assessed in this section.

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==== 2.8.4.1 Co-impacts of Air Quality, Sector-specific and Energy Policies on Climate Mitigation ====

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Co-impacts of local or regional air pollution abatement policies for climate mitigation are widely studied in the literature. Cross-border externalities of air pollution have also made these a focus of several international agreements ( [[#Mitchell--2020|Mitchell et al. 2020]] ). Evaluating the effectiveness of such treaties and policies is difficult because deriving causal inferences and accurate attribution requires accounting for several confounding factors, and direct and indirect spillovers ( [[#Isaksen--2020|Isaksen 2020]] ). Nevertheless, several studies assess the effectiveness of such treaties and regulations (De Foy et al. 2016; [[#Li--2017a|Li et al. 2017a]] , 2017b; [[#Morgenstern--2018|Morgenstern 2018]] ; [[#Mardones--2020|Mardones and Cornejo 2020]] ). However, there is little ex-post empirical analysis and a greater focus on ex-ante studies in the literature.

At a local scale, air pollutants are often co-emitted with GHGs in combustion processes. Many air quality policies and regulations focus on local pollution from specific sources that can potentially either substitute or complement global GHG emissions in production and generation processes. Also, policies that reduce certain air pollutants, such as sulphur dioxide (SO 2 ), have a positive radiative forcing effect ( [[#Navarro--2016|Navarro et al. 2016]] ). The evidence on individual air pollution control regulation and policies for GHG emissions is therefore mixed ( ''medium evidence'' , ''medium agreement'' ). Evidence from the USA suggests that increased stringency of local pollution regulation had no statistically detectable co-benefits or costs on GHG emissions ( [[#Brunel--2019|Brunel and Johnson 2019]] ). Evidence from China suggests that the effectiveness of policies addressing local point sources differed from those of non-point sources and the co-benefits for climate are mixed, though policies addressing large industrial point sources have been easier to implement and have had significant impact ( [[#Huang--2016|Huang and Wang 2016]] ; [[#Xu--2016|Xu et al. 2016]] ; [[#van%20der%20A--2017|van der A et al. 2017]] ; [[#Dang--2019|Dang and Liao 2019]] ; [[#Fang--2019|Fang et al. 2019]] ; [[#Yu--2019|Yu et al. 2019]] ). Legislation to reduce emissions of air pollutants in Europe have significantly improved air quality and health but have had an unintended warming effect on the climate ( [[#Turnock--2016|Turnock et al. 2016]] ).

Often, the realisation of potential co-benefits depends on the type of pollutant addressed by the specific policy, and whether complementarities between local pollution and global GHG emissions are considered in policy design ( ''medium evidence'' , ''high agreement'' ) ( [[#Rafaj--2014|Rafaj et al. 2014]] ; [[#Li--2017a|Li et al. 2017a]] ). Effective environmental regulations that also deliver co-benefits for climate mitigation require integrated policies ( [[#Schmale--2014|Schmale et al. 2014]] ; [[#Haines--2017|Haines et al. 2017]] ). Uncoordinated policies can have unintended consequences and even increase emissions ( [[#Holland--2015|Holland et al. 2015]] ). Many studies suggest that policies that target both local and global environmental benefits simultaneously may be more effective ( ''medium evidence'' , ''medium agreement'' ) ( [[#Klemun--2020|Klemun et al. 2020]] ). Furthermore, air pollution policies aimed at inducing structural changes – for example, closure of polluting coal power plants or reducing motorised miles travelled – are more likely to have potential positive spillover effects for climate mitigation, as compared to policies incentivising end-of-pipe controls ( [[#Wang--2021|Wang 2021]] ).

Other policies that typically have potential co-benefits for climate mitigation include those specific to certain sectors and are discussed in Chapters 5–11. Examples of such policies include those that encourage active travel modes, which have been found to have ancillary benefits for local air quality, human health, and GHG emissions ( [[#Fujii--2018|Fujii et al. 2018]] ). Policies to reduce energy use through greater efficiency have also been found to have benefits for air quality and the climate ( ''robust evidence'' , ''medium agreement'' ) ( [[#Tzeiranaki--2019|Tzeiranaki et al. 2019]] ; [[#Bertoldi--2020|Bertoldi and Mosconi 2020]] ). Important air quality and climate co-benefits of renewable or nuclear energy policies have also been found ( ''medium evidence'' , ''medium agreement'' ) ( [[#Lee--2017|Lee et al. 2017]] ; [[#Apergis--2018|Apergis et al. 2018]] ; [[#Sovacool--2021|Sovacool and Monyei 2021]] ).

Policies specific to other sectors, such as encouraging green building design, can also reduce GHG emissions ( [[#Eisenstein--2017|Eisenstein et al. 2017]] ). Evidence from several countries also shows that replacing polluting solid biomass cooking with cleaner gas-burning or electric alternatives have strong co-benefits for health, air quality, and climate change ( ''robust evidence'' , ''high agreement'' ) ( [[#Anenberg--2017|Anenberg et al. 2017]] ; [[#Singh--2017|Singh et al. 2017]] ; [[#Tao--2018|Tao et al. 2018]] ).

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==== 2.8.4.2 Climate Impacts of Agricultural, Forestry, Land Use, and AFOLU-related Policies ====

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Policies on agriculture, forestry, and other land use (AFOLU), and AFOLU sector-related policies have had a long history in many developing and developed countries. Co-impacts of these policies on the climate have been only marginally studied, although their impacts might be quite important because the AFOLU sector is responsible for 22% of total GHG emissions ( ''robust evidence'' , ''high agreement'' ). The results of afforestation policies around the world and the contribution to CCS are also important.

Private and governmental policies can have a major impact on the climate. Experience indicates that ‘climate proofing’ a policy is likely to require some stimulus, resources, and expertise from agencies or organisations from outside the country. Stimulus and support for adaptation and mitigation can come from the UN system and from international development institutions ( [[#FAO--2009|FAO 2009]] ). These findings are also valid for small/organic farmers vis-à-vis large-scale agro-industry. For example, small/medium and environmentally concerned farmers in Europe are often asking for more policies and regulations, and see it as necessary from a climate perspective, and also to maintain competitiveness relative to large agro-industrial complexes. Therefore, the need for governmental support for small producers in regulations encompasses all AFOLU sectors.

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===== Forestry case: zero deforestation =====

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Forest is generally defined as land spanning more than 0.5 hectares with trees higher than 5 metres and a canopy cover of more than 10%, or trees able to reach these thresholds in situ ( [[#FAO--1998|FAO 1998]] ). Zero-deforestation (i.e., both gross and net zero deforestation) initiatives generate results at multiple levels ( [[#Meijer--2014|Meijer 2014]] ). Efforts to achieve zero-deforestation (and consequently emissions) are announced by non-governmental organisations (NGOs), companies, governments, and other stakeholder groups. NGOs engage through their campaigning, but also propose tools and approaches for companies ( [[#Leijten--2020|Leijten et al. 2020]] ). The extent to which companies can actually monitor actions conducive to zero-deforestation pledges depends on their position in the supply chain. Beyond the business practices of participating companies, achieving long-term positive societal impacts requires upscaling from supply chains towards landscapes, with engagement of all stakeholders, and in particular small producers. The various success indicators for zero deforestation mirror the multiple levels at which such initiatives develop: progress towards certification, improved traceability, and legality are apparent output measures, whereas direct-area monitoring and site selection approaches target the business practices themselves.

Such efforts have led to the development of the High Carbon Stock (HCS) approach that combines carbon stock values with the protection of HCS areas (including peatlands and riparian zones) and areas important for the livelihoods of local communities ( [[#Rosoman--2017|Rosoman et al. 2017]] ). Long-term positive impacts, however, will need to be assessed with hindsight and focus on national and global statistics. Successful initiatives targeting zero deforestation at jurisdictional level would also need to improve the enforcement of forest laws and regulations ( [[#EII--2015|EII 2015]] ; [[#Meyer--2015|Meyer and Miller 2015]] ).

Large-scale agribusiness, banks, and consumer goods companies dominate supply chain-focused zero-deforestation initiatives, but only the producers, including local communities and smallholders, can change the production circumstances ( [[#TFD--2014|TFD 2014]] ). Producers shoulder much of the burden for meeting environmental requirements of pledges. And local communities and small producers are vulnerable to being cut out when supply chains reorient. The zero-deforestation pledges do not always devise programmes for introducing new sourcing strategies, and governments may have an important contribution to make, particularly in safeguarding the interests of small producers.

Other than in Brazil and Indonesia, beyond individual supply chains, there is still little evidence on positive results of zero-deforestation commitments, as information available for companies to judge their progress is scarce. Moreover, many zero-deforestation pledges set targets to be achieved by 2020 or 2030, and, consequently, many companies have not yet reported publicly on their progress. Similarly, only a few governments have yet shown progress in reducing deforestation, but the New York Declaration on Forests, the Sustainable Development Goals (SDGs) and the Paris Agreement were adopted relatively recently. The effectiveness of private-sector zero-deforestation pledges depends on the extent to which they can be supported by governmental action and foster a cooperative environment with the engagement of all stakeholders. Where the pledges are coordinated with regulation, multi-stakeholder dialogues, and technical and financial support, a true paradigm shift becomes possible. Many governments are still building the capacity to improve overall forest governance, but implementing ambitious international targets is likely to depend on technical and major financial support that has not yet been mobilised.

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