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

== 2.8 Climate and Non-Climate Policies and Measures and their Impacts on Emissions ==

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=== 2.8.1 Introduction ===

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The key to achieving climate change mitigation targets includes crafting environmentally effective, economically efficient and socially equitable policies. For the purposes of this section, policies are defined broadly as actions to guide decisions to reach explicit goals and, accordingly, climate (mitigation) policies are the ones whose primary objective is to reduce GHG emissions. They include a range of domains from economic and institutional to research and development (R&amp;D) and social policies, and are implemented by various instruments (e.g., market-based and regulatory in the economic domain) and measures (e.g., legal provisions and governance arrangements in the institutional domain) (Chapter 13, and see ‘mitigation policies’ in Glossary). Yet GHG emissions are also affected by policies enacted in various social, economic and environmental areas to pursue primarily non-climatic objectives. This section presents succinct assessments of the outcomes and effectiveness of a few selected policy instruments applied in the last two decades that target climate protection (Sections 2.8.2 and 2.8.3) and GHG emissions impacts of selected other policies primarily aimed at improvements in environmental quality and natural resource management ( [[#2.8.4|Section 2.8.4]] ). [[#footnote-002|12]]

It is rather difficult, though not impossible, to discern the genuine impacts of climate and non-climate policies on GHG emissions. Most current and past policies target only a small part of global emissions in a limited geographical area and/or from a small number of economic sectors. However, in addition to the targeted region or sector, policies and measures tend to affect GHG emissions in other parts of the world. Emissions leakage is the key channel by which such phenomena and complex interactions occur. [[#footnote-001|13]] Uncertainties in impacts, synergies, and trade-offs between policies and measures also complicate the evaluation of emissions impacts. These make it challenging to identify the impacts of any specific policy or measure on emissions of any specific region or sector. Rigorous statistical analyses are necessary for building strong empirical evidence, but the experience with climate-related policy experiments to date is limited.

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=== 2.8.2 Comprehensive Multinational Assessments ===

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Comprehensive multinational evaluations with wider regional and sectoral coverage enable the assessment of emissions impacts without distortions from emissions leakage. Among the wide range of climate policy instruments, pricing carbon – such as a carbon tax or an emissions trading system – has been one of the most widely used and effective options to reduce GHG emissions ( ''robust evidence'' , ''high agreement'' ). In a comparison of 142 countries with and without carbon pricing, countries with a carbon price show annual CO 2 emission growth rates of 2 percentage points lower than countries without such policies ( [[#Best--2020|Best et al. 2020]] ). A more comprehensive evaluation of carbon prices shows that countries with a lower carbon pricing gap (a higher carbon price) tend to be more carbon-efficient, that is, they have a lower carbon intensity of GDP (OECD 2018). [[#footnote-000|14]] An empirical analysis of the effects of environmental regulation and innovation on the carbon emissions of OECD countries during the period 1999–2014 indicates that a 1% increase in environmentally friendly patents reduced carbon emissions by 0.017%, and a 1% increase in environmental tax revenue per capita reduced carbon emissions by 0.03% ( [[#Hashmi--2019|Hashmi and Alam 2019]] ).

Domestic and international climate legislation have also contributed to the reduction of GHG emissions. An empirical analysis of legislative activity in 133 countries over the period 1999–2016 based on panel data indicates that each new law reduced annual CO 2 emissions per unit of GDP by 0.78% nationally in the first three years, and by 1.79% beyond three years. Additionally, climate laws as of 2016 were associated with an annual reduction in global CO 2 emissions of 5.9 GtCO 2 and 38 GtCO 2 cumulatively since 1999 ( [[#Eskander--2020|Eskander and Fankhauser 2020]] ). It is notable that 36 countries that accepted legally binding targets under the Kyoto Protocol all complied ( [[#Shishlov--2016|Shishlov et al. 2016]] ). It is impossible to disentangle precisely the contribution of individual mitigation policies, but it is clear that the participating countries, especially those in the OECD, did make substantial policy efforts with material impact ( [[#Grubb--2016|Grubb 2016]] ). An ex-post evaluation shows a significant impact of the Protocol on emissions reductions ( [[#Maamoun--2019|Maamoun 2019]] ).

Renewable energy policies, such as Renewable Portfolio Standards and Feed-in-Tariff, have played an essential role in the massive expansion of renewable energy capacities, another key driver of GHG emissions reductions ( ''robust evidence'' , ''high agreement'' ). Drivers of decreasing CO 2 emissions seen in a group of 18 developed economies that decarbonised over the period 2005–2015 are the displacement of fossil fuels by renewable energy and decreases in energy use ( [[#Le%20Quéré--2019|Le Quéré et al. 2019]] ). Renewable energy policies both at the EU and member states level have played an essential role in abating GHG emissions ( [[#ICF%20International--2016|ICF International 2016]] ).

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=== 2.8.3 National, Sectoral, and Cross-sectoral Policies ===

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==== 2.8.3.1 National and Regional Carbon Pricing ====

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Carbon prices – such as carbon taxes and GHG emissions trading schemes (ETSs) – are among the most widely used climate policy instruments across the globe, together with technology support instruments ( [[#IRENA--2018|IRENA 2018]] ). As of May 2020, there were 61 carbon pricing schemes in place or scheduled for implementation, consisting of 31 ETSs and 30 carbon tax regimes, covering 12 GtCO 2 -eq or about 22% of annual global GHG emissions ( [[#World%20Bank--2020|World Bank 2020]] ). The performance of carbon pricing in practice varies by countries and sectors, and depends on the policy environment ( ''robust evidence'' , ''high agreement'' ).

The European Union Emissions Trading Scheme (EU ETS), the longest-standing regional climate policy instrument to date, has reduced emissions, though the estimates of the amount vary by study, by country, and by sector; ranging from 3–28% ( [[#McGuinness--2008|McGuinness and Ellerman 2008]] ; [[#Ellerman--2010|Ellerman et al. 2010]] ; [[#Abrell--2011|Abrell et al. 2011]] ; [[#Anderson--2011|Anderson and Di Maria 2011]] ; [[#Egenhofer--2011|Egenhofer et al. 2011]] ; Petrick and Wagner 2014; [[#Arlinghaus--2015|Arlinghaus 2015]] ; [[#Martin--2016|Martin et al. 2016]] ). The EU ETS avoided emitting about 1.2 GtCO 2 between 2008 and 2016 (3.8%), almost half of what EU governments promised to reduce under their Kyoto Protocol commitments ( [[#Bayer--2020|Bayer and Aklin 2020]] ).

China’s emission trading pilots have resulted in a decline in carbon intensity in the pilot provinces by adjusting the industrial structure ( [[#Zhou--2019|Zhou et al. 2019]] ). The Regional Greenhouse Gas Initiative (RGGI) in the USA has induced leakage in emissions through increases in electricity generation in surrounding non-RGGI areas, but it has led to the reduction of emissions by way of changes in the fuel mix from coal to gas ( [[#Fell--2018|Fell and Maniloff 2018]] ). Actual emissions declined in six of the 10 ETSs for which data is available, although other factors, such as the 2009 recession, have had significant impacts on those emissions as well ( [[#Haites--2018|Haites et al. 2018]] ).

The evidence of environmental effectiveness of carbon taxes in Western European countries is varied depending on country and study ( ''robust evidence'' , ''high agreement'' ). A significant impact is found in Finland but insignificant impacts are found in Denmark and the Netherlands, and there are mixed results for Sweden ( [[#Lin--2011|Lin and Li 2011]] ; [[#Brännlund--2014|Brännlund et al. 2014]] ). Only six of the 17 taxes, where data are available, have reduced actual emissions subject to the tax. Tax rates tend to be too low in many cases and the scale and frequency of the rate changes has not been sufficient to stimulate further emissions reductions ( [[#Haites--2018|Haites et al. 2018]] ).

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==== 2.8.3.2 Selected Sectoral Climate Policy Instruments ====

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Many governments have implemented sector-specific policies, in addition to nationwide measures, to reduce GHG emissions ( ''high confidence'' ). Examples of sectoral climate policies include carbon taxes on transportation fuels, low-carbon fuel standards, and regulation of coal power generation.

The implementation of a carbon tax and value-added tax on gasoline and diesel in Sweden resulted in significant reductions of CO 2 emissions in the transportation sector ( [[#Shmelev--2018|Shmelev and Speck 2018]] ; [[#Andersson--2019|Andersson 2019]] ). An assessment of a variety of carbon tax schemes across various sectors in the EU shows a negative relationship between CO 2 emissions and a CO 2 tax ( [[#Hájek--2019|Hájek et al. 2019]] ). In British Columbia (Canada), the carbon tax resulted in a decrease in demand for gasoline and a reduction in total GHG emissions (not exclusive to the transportation sector) estimated to be between 5–15% ( [[#Murray--2015|Murray and Rivers 2015]] ; [[#Rivers--2015|Rivers and Schaufele 2015]] ). The Low Carbon Fuel Standard in California has contributed to reducing carbon emissions in the transportation sector by approximately 9.85–13.28% during 1997–2014 ( [[#Huseynov--2018|Huseynov and Palma 2018]] ).

The power sector typically accounts for a large portion of countries’ CO 2 emissions. Market-based regulation and government subsidies in China contributed to improving operational efficiency and reducing emissions ( [[#Zhao--2015|Zhao et al. 2015]] ). In addition, the implementation of ultra-low emission standards has also resulted in a significant reduction in emissions from China’s power plants ( [[#Tang--2019|Tang et al. 2019]] ). Mandatory climate and energy policies, including the California Global Warming Solutions Act, reduced CO 2 emissions by 2.7–25% of the average state-level annual emissions from the power sector over the period 1990–2014 in the USA. Mandatory GHG registry/reporting, electric decoupling and a public benefit fund have been effective in further decreasing power sector emissions in the USA ( [[#Martin--2017|Martin and Saikawa 2017]] ). In the UK electricity sector, a carbon price floor, combined with electricity market reform (competitive auctions for both firm capacity and renewable energy), displaced coal, whose share fell from 46% in 1995 to 7% in 2017, halving CO 2 emissions, while renewables grew from under 4% in 2008 to 22% by 2017 ( [[#Grubb--2018|Grubb and Newbery 2018]] ). See [[IPCC:Wg3:Chapter:Chapter-13|Chapter 13]] for more information.

An alternative approach to a carbon tax is an indirect emissions tax on fuels such as an excise tax, or on vehicles, based on the expected CO 2 intensity of new passenger vehicles. Vehicle purchase taxes can result in a reduction in GHG emissions through reducing the CO 2 emissions intensity of vehicles, while also discouraging new vehicle purchases ( [[#Aydin--2018|Aydin and Esen 2018]] ). For example, a vehicle tax policy in Norway resulted in a reduction of average CO 2 intensity per kilometre of 7.5 gCO 2 km –1 ( [[#Ciccone--2018|Ciccone 2018]] ; [[#Steinsland--2018|Steinsland et al. 2018]] ). Despite such evidence, studies of carbon pricing find that additional policies are often needed to stimulate sufficient emissions reductions in transportation ( ''medium confidence'' ) ( [[#Tvinnereim--2018|Tvinnereim and Mehling 2018]] ).

Electric vehicles (EVs) powered by clean electricity can reduce GHG emissions, and such policies are important for spurring adoption of such vehicles ( [[#Kumar--2020|Kumar and Alok 2020]] ; [[#Thiel--2020|Thiel et al. 2020]] ). The extent to which EV deployment can decrease emissions by replacing internal combustion engine-based vehicles depends on the generation mix of the electric grid ( [[#Abdul-Manan--2015|Abdul-Manan 2015]] ; [[#Nichols--2015|Nichols et al. 2015]] ; Canals [[#Casals--2016|Casals et al. 2016]] ; [[#Hofmann--2016|Hofmann et al. 2016]] ; [[#Choi--2018|Choi et al. 2018]] ; [[#Teixeira--2018|Teixeira and Sodré 2018]] ) although, even with current grids, EVs reduce emissions in almost all cases ( [[#Knobloch--2020|Knobloch et al. 2020]] ). Policy incentives for EV adoption can be an effective mechanism to increase EV sales ( [[#Langbroek--2016|Langbroek et al. 2016]] ) and may include discounts, purchase subsidies, regulations, and government leadership ( ''medium confidence'' ) ( [[#Bakker--2013|Bakker and Jacob Trip 2013]] ; [[#Silvia--2016|Silvia and Krause 2016]] ; [[#Teixeira--2018|Teixeira and Sodré 2018]] ; [[#Qiu--2019|Qiu et al. 2019]] ; [[#Santos--2020|Santos and Davies 2020]] ). The presence of charging infrastructure and publicly available charging increases the adoption rate of EVs ( [[#Vergis--2015|Vergis and Chen 2015]] ; [[#Javid--2019|Javid et al. 2019]] ). A comparison of EV adoption rates across 30 countries shows a positive correlation between charging stations and EV market share ( [[#Sierzchula--2014|Sierzchula et al. 2014]] ). A rollout of 80,000 DC fast chargers across the USA is estimated to have resulted in a 4% reduction in emissions compared to a baseline of no additional fast chargers ( [[#Levinson--2018|Levinson and West 2018]] ). More recently, bans on internal combustion engine vehicles have provided a much more direct approach to stimulating the adoption of EVs and its supporting infrastructure; however, the efficacy of such measures depends on enforcement ( [[#Plötz--2019|Plötz et al. 2019]] ).

Public transit can reduce vehicle travel and lower GHG emissions by reducing the number of trips taken by private vehicles and the length of those trips ( ''medium confidence'' ). Changes to the operation of public transportation systems (such as density of bus stops, distance from stops to households, duration and frequency of trip times, and lowering ridership costs) can result in a mode shift from private car trips to public transit trips ( [[#Cats--2017|Cats et al. 2017]] ; [[#Choi--2018|Choi 2018]] ; [[#Carroll--2019|Carroll et al. 2019]] ). These changes in the public transit system operation and network optimisation have been shown to have reduced GHG emissions in cases such as San Francisco, where the cost optimisation of the transit network was estimated to decrease emissions by a factor of three ( [[#Cheng--2018|Cheng et al. 2018]] ) and Barcelona, where the optimisation of the urban bus system was estimated to reduce GHG emissions by 50% ( [[#Griswold--2017|Griswold et al. 2017]] ). For every 1% increase in investment in transit services and transit-oriented design, there is an estimated 0.16% reduction in private vehicle kilometres travelled per capita ( [[#McIntosh--2014|McIntosh et al. 2014]] ).

Bike- and car-sharing programmes can reduce GHG emissions ( ''medium confidence'' ). Albeit a study of eight cities in the USA with larger bike share systems and higher ridership found that their potential to reduce total emissions is limited to &lt;0.1% of total GHG emissions from the transportation sectors of these cities ( [[#Kou--2020|Kou et al. 2020]] ). The emissions reductions effects of car-sharing programmes depends on the specifics of programmes: the mode shift from public transit to car-sharing services can outweigh the decreases in GHG emissions associated with a reduced number of cars on the road ( [[#Jung--2018|Jung and Koo 2018]] ), whereas car-sharing programmes with EV fleets may reduce GHG emissions ( [[#Luna--2020|Luna et al. 2020]] ).

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=== 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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