Editing IPCC:AR6/SRCCL/Chapter-7 (section)

=== 7.4.4 Policies responding to greenhouse gas (GHG) fluxes ===

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==== 7.4.4.1 GHG fluxes and climate change mitigation ====

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Pathways reflecting current nationally stated mitigation ambitions as submitted under the Paris Agreement would not limit global warming to 1.5°C with no or limited overshoot, but instead result in a global warming of about 3°C by 2100 with warming continuing afterward (IPCC 2018d). Reversing warming after an overshoot of 0.2°C or higher during this century would require deployment of CDR at rates and volumes that might not be achievable given considerable implementation challenges (IPCC 2018d). This gap (Höhne et al. 2017 <sup>[[#fn:r531|531]]</sup> ; Rogelj et al. 2016 <sup>[[#fn:r532|532]]</sup> ) creates a significant risk of global warming impacting on land degradation, desertification, and food security (IPCC 2018d <sup>[[#fn:r533|533]]</sup> ) (Section 7.2). Action can be taken by 2030 adopting already known cost-effective technology (United Nations Environment Programme 2017 <sup>[[#fn:r534|534]]</sup> ), improving the finance, capacity building, and technology transfer mechanisms of the United Nations Framework Convention on Climate Change (UNFCCC), improving food security (listed by 73 nations in their nationally determined contributions (NDCs)) and nutritional security (listed by 25 nations) (Richards et al. 2015 <sup>[[#fn:r535|535]]</sup> ). UNFCCC Decision 1. CP21 reaffirmed the UNFCCC target that ‘developed country parties provide USD 100 billion annually by 2020 for climate action in developing countries’ (Rajamani 2011 <sup>[[#fn:r536|536]]</sup> ) and a new collective quantified goal above this floor is to be set, taking into account the needs and priorities of developing countries (Fridahl and Linnér 2016 <sup>[[#fn:r537|537]]</sup> ).

Mitigation policy instruments to address this shortfall include financing mechanisms, carbon pricing, cap and trade or emissions trading, and technology transfer. While climate change is a global commons problem containing free-riding issues cost-effective international policies that ensure that countries get the most environmental benefit out of mitigation investments promote an international climate policy regime (Nordhaus 1999 <sup>[[#fn:r538|538]]</sup> ; Aldy and Stavins 2012 <sup>[[#fn:r539|539]]</sup> ). Carbon pricing instruments may provide an entry point for inclusion of appropriate agricultural carbon instruments. Models of cost-efficient distribution of mitigation across regions and sectors typically employ a global uniform carbon price, but such treatment in the agricultural sector may impact on food security (Section 7.4.4.4).

One policy initiative to advance climate mitigation policy coherence in this section is the phase out of subsidies for fossil fuel production (see also Section 7.4.8). The G20 agreed in 2009, and the G7 agreed in 2016, to phase out these subsidies by 2025. Subsidies include lower tax rates or exemptions and rebates of taxes on fuels used by particular consumers (diesel fuel used by farming, fishing, etc.), types of fuel, or how fuels are used. The OECD estimates the overall value of these subsides to be 160–200 billion USD annually between 2010 and 2014 (OECD 2015 <sup>[[#fn:r540|540]]</sup> ). The phase-out of fossil fuel subsidies has important economic, environmental and social benefits. Coady et al. (2017) <sup>[[#fn:r541|541]]</sup> estimate the economic and environmental benefits of reforming fossil fuel subsidies could be valued worldwide at 4.9 trillion USD in 2013, and 5.3 trillion USD in 2015. Eliminating subsidies could have reduced emissions by 21%, raised 4% of global GDP as revenue (in 2013), and improved social welfare (Coady et al. 2017 <sup>[[#fn:r542|542]]</sup> ).

Legal instruments addressing perceived deficiencies in climate change mitigation include human rights and liability. Developments in attribution science are improving the ability to detect human influence on extreme weather. Marjanac et al. (2017) <sup>[[#fn:r543|543]]</sup> argue that this broadens the legal duty of government, business and others to manage foreseeable harms, and may lead to more climate change litigation (Marjanac et al. 2017) <sup>[[#fn:r544|544]]</sup> . Peel and Osofsky (2017) <sup>[[#fn:r545|545]]</sup> argue that courts are becoming increasingly receptive to employ human rights claims in climate change lawsuits (Peel and Osofsky 2017 <sup>[[#fn:r546|546]]</sup> ); citizen suits in domestic courts are not a universal phenomenon and, even if unsuccessful, Estrin (2016) <sup>[[#fn:r547|547]]</sup> concludes they are important in underlining the high level of public concern.

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==== 7.4.4.2 Mitigation instruments ====

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Similar instruments for mitigation could be applied to the land sector as in other sectors, including: market-based measures such as taxes and cap and trade systems; standards and regulations; subsidies and tax credits; information instruments and management tools; R&amp;D investment; and voluntary compliance programmes. However, few regions have implemented agricultural mitigation instruments Cooper et al. 2013 <sup>[[#fn:r548|548]]</sup> ). Existing regimes focus on subsidies, grants and incentives, and voluntary offset programmes.

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==== 7.4.4.3 Market-based instruments ====

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Although carbon pricing is recognised to be an important cost- effective instrument in a portfolio of climate policies ( ''high evidence, high agreement'' ) (Aldy et al. 2010 <sup>[[#fn:r549|549]]</sup> ), as yet, no country is exposing their agricultural sector emissions to carbon pricing in any comprehensive way. A carbon tax, fuel tax, and carbon markets (cap and trade system or Emissions Trading System (ETS), or baseline and credit schemes, and voluntary markets) are predominant policy instruments that implement carbon pricing. The advantage of carbon pricing is environmental effectiveness at relatively low cost ( ''high evidence, high agreement'' ) (Baranzini et al. 2017 <sup>[[#fn:r550|550]]</sup> ; Fawcett et al. 2014 <sup>[[#fn:r551|551]]</sup> ). Furthermore, carbon pricing could be used to raise revenue to reinvest in public spending, either to help certain sectors transition to lower carbon systems, or to invest in public spending unrelated to climate change. Both of these options may make climate policies more attractive and enhance overall welfare (Siegmeier et al. 2018 <sup>[[#fn:r552|552]]</sup> ), but there is, as yet, no evidence of the effectiveness of emissions pricing in agriculture (Grosjean et al. 2018 <sup>[[#fn:r553|553]]</sup> ). There is, however, a clear need for progress in this area as, without effective carbon pricing, the mitigation potential identified in chapters 5 and 6 of this report will not be realised ( ''high evidence, high agreement'' ) (Boyce 2018 <sup>[[#fn:r554|554]]</sup> ).

The price may be set at the social cost of carbon (the incremental impact of emitting an additional tonne of CO <sub>2</sub> , or the benefit of slightly reducing emissions), but estimates of the SCC vary widely and are contested ( ''high evidence, high agreement'' ) (Pezzey 2019 <sup>[[#fn:r555|555]]</sup> ). An alternative to the SCC includes a pathways approach that sets an emissions target and estimates the carbon prices required to achieve this at the lowest possible cost (Pezzey 2019 <sup>[[#fn:r556|556]]</sup> ). Theoretically, higher costs throughout the entire economy result in reduction of carbon intensity, as consumers and producers adjust their decisions in relation to prices corrected to reflect the climate externality (Baranzini et al. 2017 <sup>[[#fn:r557|557]]</sup> ).

Both carbon taxes and cap and trade systems can reduce emissions, but cap and trade systems are generally more cost effective ( ''medium evidence, high agreement'' ) (Haites 2018a <sup>[[#fn:r558|558]]</sup> ). In both cases, the design of the system is critical to its effectiveness at reducing emissions ( ''high evidence, high agreement'' ) (Bruvoll and Larsen 2004 <sup>[[#fn:r559|559]]</sup> ; (Lin and Li 2011 <sup>[[#fn:r560|560]]</sup> ). The trading system allows the achievement of emission reductions in the most cost-effective manner possible and results in a market and price on emissions that create incentives for the reduction of carbon pollution. The way allowances are allocated in a cap and trade system is critical to its effectiveness and equity. Free allocations can be provided to trade-exposed sectors, such as agriculture, either through historic or output-based allocations, the choice of which has important implications (Quirion 2009 <sup>[[#fn:r561|561]]</sup> ). Output-based allocations may be most suitable for agriculture, also minimising leakage risk (see below in this section) (Grosjean et al. 2018 <sup>[[#fn:r562|562]]</sup> ; Quirion 2009 <sup>[[#fn:r563|563]]</sup> ). There is ''medium evidence'' and ''high agreement'' that properly designed, a cap and trade system can be a powerful policy instrument (Wagner 2013 <sup>[[#fn:r564|564]]</sup> ) and may collect more rents than a variable carbon tax (Siegmeier et al. 2018 <sup>[[#fn:r565|565]]</sup> ; Schmalensee and Stavins 2017 <sup>[[#fn:r566|566]]</sup> ).

In the land sector, carbon markets are challenging to implement. Although several countries and regions have an ETS in place (for example, the EU, Switzerland, the Republic of Korea, Quebec in Canada, California in the USA (Narassimhan et al. 2018 <sup>[[#fn:r567|567]]</sup> )), none have included non-CO <sub>2</sub> (methane and nitrous oxide) emissions from agriculture. New Zealand is the only country currently considering ways to incorporate agriculture into its ETS (see Case study: Including agriculture in the New Zealand Emissions Trading Scheme).

Three main reasons explain the lack of implementation to date:

# The large number of heterogeneous buyers and sellers, combined with the difficulties of monitoring, reporting and verification (MRV) of emissions from biological systems introduce potentially high levels of complexity (and transaction costs). Effective policies therefore depend on advanced MRV systems which are lacking in many (particularly developing) countries (Wilkes et al. 2017) <sup>[[#fn:r568|568]]</sup> . This is discussed in more detail in the case study on the New Zealand Emissions Trading Scheme.
# Adverse distributional consequences (Grosjean et al. 2018 <sup>[[#fn:r569|569]]</sup> ) ( ''medium evidence, high agreement'' ). Distributional issues depend, in part, on the extent that policy costs can be passed on to consumers, and there is ''medium evidence'' and ''medium agreement'' that social equity can be increased through a combination of non-market and market-based instruments (Haites 2018b <sup>[[#fn:r570|570]]</sup> ).
# Regulation, market-based or otherwise, adopted in only one jurisdiction and not elsewhere may result in ‘leakage’ or reduced effectiveness – where production relocates to weaker regulated regions, potentially reducing the overall environmental benefit. Although modelling studies indicate the possibility of leakage following unilateral agricultural mitigation policy implementation (e.g., Fellmann et al. 2018), there is no empirical evidence from the agricultural sector yet available. Analysis from other sectors shows an overestimation of the extent of carbon leakage in modelling studies conducted before policy implementation compared to evidence after the policy was implemented (Branger and Quirion 2014 <sup>[[#fn:r571|571]]</sup> ). Options to avoid leakage include: border adjustments (emissions in non-regulated imports are taxed at the border, and payments made on products exported to non-regulated countries are rebated); differential pricing for trade-exposed products; and output-based allocation (which effectively works as a subsidy for trade-exposed products). Modelling shows that border adjustments are the most effective at reducing leakage, but may exacerbate regional inequality (Böhringer et al. 2012 <sup>[[#fn:r572|572]]</sup> ) and through their trade-distorting nature may contravene World Trade Organization rules. The opportunity for leakage would be significantly reduced, ideally through multi- lateral commitments (Fellmann et al. 2018 <sup>[[#fn:r573|573]]</sup> ) ( ''medium evidence, high agreement'' ) but could also be reduced through regional or bi-lateral commitments within trade agreements.

'''Case study | Including agriculture in the New Zealand Emissions Trading Scheme (ETS)'''

New Zealand has a high proportion of agricultural emissions at 49% (Ministry of the Environment 2018) – the next-highest developed country agricultural emitter is Ireland at around 32% (EPA 2018 <sup>[[#fn:r1656|1656]]</sup> ) – and is considering incorporating agricultural non-CO <sub>2</sub> gases into the existing national ETS. In the original design of the ETS in 2008, agriculture was intended to be included from 2013, but successive governments deferred the inclusion (Kerr and Sweet 2008 <sup>[[#fn:r1657|1657]]</sup> ) due to concerns about competitiveness, lack of mitigation options and the level of opposition from those potentially affected (Cooper and Rosin 2014 <sup>[[#fn:r1658|1658]]</sup> ). Now though, as the country’s agricultural emissions are 12% above 1990 levels, and the country’s total gross emissions have increased 19.6% above 1990 levels (New Zealand Ministry for the Environment 2018 <sup>[[#fn:r1659|1659]]</sup> ), there is a recognition that, without any targeted policy for agriculture, only 52% of the country’s emissions face any substantive incentive to mitigate (Narassimhan et al. 2018 <sup>[[#fn:r1660|1660]]</sup> ). Including agriculture in the ETS is one option to provide incentives for emissions reductions in that sector. Other options are discussed in Section 7.4.4. Although some producer groups raise concern that including agriculture will place New Zealand producers at a disadvantage compared with their international competitors who do not face similar mechanisms (New Zealand Productivity Commission 2018 <sup>[[#fn:r1661|1661]]</sup> ), there is generally greater acceptance of the need for climate policies for agriculture.

The inclusion of non-CO <sub>2</sub> emissions from agriculture within an ETS is potentially complex, however, due to the large number of buyers and sellers if obligations are placed at farm level, and different choices of how to estimate emissions from biological systems in cost- effective ways. New Zealand is currently investigating practical and equitable approaches to include agriculture through advice being provided by the Interim Climate Change Committee (ICCC 2018 <sup>[[#fn:r1662|1662]]</sup> ). Main questions centre around the point of obligation for buying and selling credits, where trade-offs have to be made between providing incentives for behaviour change at farm level and the cost and complexity of administering the scheme (Agriculture Technical Advisory Group 2009 <sup>[[#fn:r1663|1663]]</sup> ; Kerr and Sweet 2008 <sup>[[#fn:r1664|1664]]</sup> ). The two potential points of obligation are at the processor level or at the individual farm level. Setting the point of obligation at the processor level means that farmers would face limited incentive to change their management practices, unless the processors themselves rewarded farmers for lowered emissions. Setting it at the individual farm level would provide a direct incentive for farmers to adopt mitigation practices, however, the reality of having thousands of individual points of obligation would be administratively complex and could result in high transaction costs (Beca Ltd 2018 <sup>[[#fn:r1665|1665]]</sup> ).

Monitoring, reporting and verification (MRV) of agricultural emissions presents another challenge, especially if emissions have to be estimated at farm level. Again, trade-offs have to be made between accuracy and detail of estimation method and the complexity, cost and audit of verification (Agriculture Technical Advisory Group 2009 <sup>[[#fn:r1666|1666]]</sup> ).

The ICCC is also exploring alternatives to an ETS to provide efficient abatement incentives (ICCC 2018 <sup>[[#fn:r1667|1667]]</sup> ).

Some discussion in New Zealand also focuses on a differential treatment of methane compared to nitrous oxide. Methane is a short- lived gas with a perturbation lifetime of 12 years in the atmosphere; nitrous oxide on the other hand is a long-lived gas and remains in the atmosphere for 114 years (Allen et al. 2016 <sup>[[#fn:r1668|1668]]</sup> ). Long-lived gases have a cumulative and essentially irreversible effect on the climate (IPCC 2014b <sup>[[#fn:r1669|1669]]</sup> ) so their emissions need to reduce to net-zero in order to avoid climate change. Short-lived gases, however, could potentially be reduced to a certain level and then stabilised, and would not contribute further to warming, leading to suggestions of treating these two gases separately in the ETS or alternative policy instruments, possibly setting different budgets and targets for each (New Zealand Productivity Commission 2018 <sup>[[#fn:r1670|1670]]</sup> ). Reisinger et al. (2013) <sup>[[#fn:r1671|1671]]</sup> demonstrate that different metrics can have important implications globally and potentially at national and regional scales on the costs and levels of abatement.

While the details are still being agreed on in New Zealand, almost 80% of nationally determined contributions committed to action on mitigation in agriculture (FAO 2016 <sup>[[#fn:r1672|1672]]</sup> ), so countries will be looking for successful examples.

Australia’s Emissions Reduction Fund, and the preceding Carbon Farming Initiative, are examples of baseline-and-credit schemes, which creates credits for activities that generate emissions below a baseline – effectively a subsidy (Freebairn 2016 <sup>[[#fn:r1673|1673]]</sup> ). It is a voluntary scheme, and has the potential to create real and additional emission reductions through projects reducing emissions and sequestering carbon (Verschuuren 2017 <sup>[[#fn:r1674|1674]]</sup> ) ( ''low evidence, low agreement'' ). Key success factors in the design of such an instrument are policy-certainty for at least 10 to 20years, regulation that focuses on projects and not uniform rules, automated systems for all phases of the projects, and a wider focus of the carbon farming initiative on adaptation, food security, sustainable farm business, and creating jobs (Verschuuren 2017 <sup>[[#fn:r1675|1675]]</sup> ). A recent review highlighted the issue of permanence and reversal, and recommended that projects detail how they will maintain carbon in their projects, and deal with the risk of fire.

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==== 7.4.4.4 Technology transfer and land-use sectors ====

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Technology transfer has been part of the UNFCCC process since its inception and is a key element of international climate mitigation and adaptation efforts under the Paris Agreement. The IPCC definition of ‘technology transfer’ includes transfer of knowledge and technological cooperation (see Glossary) and can include modifications to suit local conditions and/or integration with indigenous technologies (Metz et al. 2000 <sup>[[#fn:r1676|1676]]</sup> ). This definition suggests greater heterogeneity in the applications for climate mitigation and adaptation, especially in land-use sectors where indigenous knowledge may be important for long-term climate resilience (Nyong et al. 2007 <sup>[[#fn:r574|574]]</sup> ). For land-use sectors, the typical reliance on trade and patent data for empirical analyses is generally not feasible as the ‘technology’ in question is often related to resource management and is neither patentable nor tradable (Glachant and Dechezleprêtre 2017 <sup>[[#fn:r575|575]]</sup> ) and ill-suited to provide socially beneficially innovation for poorer farmers in developing countries (Lybbert and Sumner 2012 <sup>[[#fn:r576|576]]</sup> ; Baker et al. 2017 <sup>[[#fn:r577|577]]</sup> ).

Technology transfer has contributed to emissions reductions ( ''medium confidence'' ). A detailed study for nearly 4000 Clean Development Mechanism (CDM) projects showed that 39% of projects had a stated and actual technology transfer component, accounting for 59% of emissions reductions; however, the more land-intensive projects (e.g., afforestation, bioenergy) showed lower percentages (Murphy et al. 2015 <sup>[[#fn:r578|578]]</sup> ). Bioenergy projects that rely on agricultural residues offer substantially more development benefits than those based on industrial residues from forests (Lee and Lazarus 2013 <sup>[[#fn:r579|579]]</sup> ). Energy projects tended to have a greater degree of technology transfer under the CDM compared to non-energy projects (Gandenberger et al. 2016 <sup>[[#fn:r580|580]]</sup> ). However, longer-term cooperation and collaborative R&amp;D approaches to technology transfer will be more important in land-use sectors (compared to energy or industry) due to the time needed for improved resource management and interaction between researchers, practitioners and policymakers. These approaches offer longer-term technology transfer that is more difficult to measure compared to specific cooperation projects; empirical research on the effects of R&amp;D collaboration could help to avoid the ‘one-policy-fits- all’ approach (Ockwell et al. 2015 <sup>[[#fn:r581|581]]</sup> ).

There is increasing recognition of the role of technology transfer in climate adaptation, but in the land-use sector there are inherent adoption challenges specific to adaptation, due to uncertainties arising from changing climatic conditions, agricultural prices, and suitability under future conditions (Biagini et al. 2014 <sup>[[#fn:r582|582]]</sup> ). Engaging the private sector is important, as adoption of new technologies can only be replicated with significant private sector involvement (Biagini and Miller 2013 <sup>[[#fn:r583|583]]</sup> ).

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==== 7.4.4.5 International cooperation under the Paris Agreement ====

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New cooperative mechanisms under the Paris Agreement illustrate the shift away from the Kyoto Protocol’s emphasis on obligations of developed country Parties to pursue investments and technology transfer, to a more pragmatic, decentralised and collaborative approach (Savaresi 2016 <sup>[[#fn:r584|584]]</sup> ; Jiang et al. 2017 <sup>[[#fn:r585|585]]</sup> ). These approaches can effectively include any combination of measures or instruments related to adaptation, mitigation, finance, technology transfer and capacity building, which could be of particular interest in land-use sectors where such aspects are more intertwined than in energy or industry sectors. Article 6 sets out several options for international cooperation (Gupta and Dube 2018 <sup>[[#fn:r586|586]]</sup> ).

The close relationship between emission reductions, adaptive capacity, food security and other sustainability and governance objectives in the land sectors means that Article 6 could bring co-benefits that increase its attractiveness and the availability of finance, while also bringing risks that need to be monitored and mitigated against, such as uncertainties in measurements and the risk of non-permanence (Thamo and Pannell 2016 <sup>[[#fn:r587|587]]</sup> ; Olsson et al. 2016 <sup>[[#fn:r588|588]]</sup> ; Schwartz et al. 2017 <sup>[[#fn:r589|589]]</sup> ). There has been progress in accounting for land-based emissions, mainly forestry and agriculture ( ''medium evidence, low agreement'' ), but various challenges remain (Macintosh 2012 <sup>[[#fn:r590|590]]</sup> ; Pistorius et al. 2017 <sup>[[#fn:r591|591]]</sup> ; Krug 2018 <sup>[[#fn:r592|592]]</sup> ).

Like the CDM and other existing carbon trading mechanisms, participation in Article 6.2 and 6.4 of the Paris Agreement requires certain institutional and data management capacities in the land sector to effectively benefit from the cooperation opportunities (Totin et al. 2018 <sup>[[#fn:r593|593]]</sup> ). While the rules for the implementation of the new mechanisms are still under development, lessons from REDD+ (reducing emissions from deforestation and forest degradation) may be useful, which is perceived as more democratic and participative than the CDM (Maraseni and Cadman 2015 <sup>[[#fn:r594|594]]</sup> ). Experience with REDD+ programmes emphasise the necessity to invest in ‘readiness’ programmes that assist countries to engage in strategic planning and build management and data collection systems to develop the capacity and infrastructure to participate in REDD+ (Minang et al. 2014 <sup>[[#fn:r595|595]]</sup> ). The overwhelming majority of countries (93%) cite weak forest sector governance and institutions in their applications for REDD+ readiness funding (Kissinger et al. 2012 <sup>[[#fn:r596|596]]</sup> ). Technology transfer for advanced remote sensing technologies that help to reduce uncertainty in monitoring forests helps to achieve REDD+ ‘readiness’ (Goetz et al. 2015 <sup>[[#fn:r597|597]]</sup> ).

As well as new opportunities for finance and support, the Paris cooperation mechanisms and the associated roles for technology transfer bring new challenges, particularly in reporting, verifying and accounting in land-use sectors. Since developing countries must now achieve, measure and communicate emission reductions, they now have value for both developing and developed countries in achieving their NDCs, but reductions cannot be double-counted (i.e., towards multiple NDCs). All countries have to prepare and communicate NDCs, and many countries have included in their NDCs either economy-wide targets that include the land-use sectors, or specific targets for the land-use sectors. The Katowice climate package clarifies that all Parties have to submit ‘Biennial Transparency Reports’ from 2024 onwards, using common reporting formats, following most recent IPCC Guidelines (use of the 2013 Supplement on Wetlands is encouraged), identifying key categories of emissions, ensuring time-series consistency, and providing completeness and uncertainty assessments as well as quality control (UNFCCC 2018a <sup>[[#fn:r598|598]]</sup> ; Schneider and La Hoz Theuer 2019 <sup>[[#fn:r599|599]]</sup> ). In total, the ambiguity in how countries incorporate land-use sectors into their NDC is estimated to lead to an uncertainty of more than 2 GtCO <sub>2</sub> in 2030 (Fyson and Jeffery 2018 <sup>[[#fn:r600|600]]</sup> ). Uncertainty is lower if the analysis is limited to countries that have provided separate land-use sector targets in their NDCs (Benveniste et al. 2018 <sup>[[#fn:r601|601]]</sup> ).

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