Enhancing Climate Change Mitigation through Agriculture

1. Potential for mitigation policies in agriculture: Summary insights

Abstract

The global ambition to reduce greenhouse gas (GHG) emissions in agriculture is currently weak, and the lack of progress will stifle efforts to meet the goals of the Paris Agreement to limit global warming to 1.5°C, or well below 2°C. Although there are policy implementation barriers, policy solutions exist. These include selecting policy options that can navigate trade-offs in economic impacts between different interest groups, and those that can address the practical challenges and transaction costs related to measurement, reporting, and verification of GHG emission reductions.

The need to reduce agricultural emissions

Agriculture continues to contribute substantially to climate change by directly emitting non-carbon dioxide (non-CO₂) emissions, including methane (CH₄) and nitrous oxide (N₂O), from crop and livestock production, and by affecting net CO₂ emissions from agricultural soils, forestry and other land use. Average annual emissions from agriculture amounted to 6.2 ± 1.4 GtCO₂eq of GHG emissions, between 2007 and 2016, representing approximately 12% of global anthropogenic GHGs. There were a further 4.9 ± 2.5 GtCO₂eq of average annual emissions from land use change caused by agriculture during this period, contributing a further 9% to global emissions (IPCC, 2019[1]).

Developing countries are, in general, the largest and fastest growing source. Between 1990 and 2014, they were responsible for the 15% increase in global non-CO₂ emissions from agriculture (Blandford and Hassapoyannes, 2018[2]), while OECD countries as a whole experienced a slight reduction in non-CO₂ emissions over this period. Production efficiency improvements have helped contribute to this reduction by lowering the emission intensity of agricultural output (McLeod et al., 2015[3]). However, the rate of decline in intensity appears to be slowing down. Net CO₂ emissions from forestry and other land use1 have fallen in both developed and developing countries due to progress on deforestation rates and increased afforestation in several regions of the world (Blandford and Hassapoyannes, 2018[2]; Smith et al., 2014[4]).

A recent Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5ºC confirms there is an important role for land use sectors in stabilising global temperatures (IPCC, 2018). Four broad options could be implemented in the agriculture sector to mitigate GHG emissions. The first two encompass supply-side measures and the latter two cover demand-side measures:

• Introduce farm practices that reduce agricultural non-carbon dioxide (non-CO₂) emissions; including methane (CH₄) and nitrous oxide (N₂O).

• Introduce practices to remove CO₂ from the atmosphere and accumulate as carbon in vegetation and soils, or that reduce emissions from the degradation and removal of these carbon stocks

• Introduce measures that encourage consumers to shift to healthier, lower emission diets.

• Introduce measures that reduce product losses along food supply chains and food waste by consumers.

This chapter is primarily concerned with the mitigation potential from measures and policies to reduce agricultural non-CO₂ emissions and net CO₂ emissions from grassland and cropland soils. Reductions in net CO₂ emissions from avoided deforestation and afforestation are reported under forestry and other land use in the IPCC Guidelines for National Greenhouse Gas Inventories (IPPC, 2008[5]). While these do not count as reductions in agricultural emissions, agriculture is a driver of deforestation and there are opportunity costs associated with the use of land for forestry instead of agricultural production. Given these interactions, some policies that affect land use change are also included in the overview of mitigation policies implemented by countries.

OECD research presented in Chapter 5 shows that biofuels derived from food and feed are expected to play a minor role only in climate change mitigation, in particular because the supply of ethanol and biodiesel is constrained by the availability of feedstock and rising agricultural production costs. Consideration of the effects of land use change would most likely decrease this minor potential. Yet according to the IPCC Fifth Assessment report, bioenergy could play an important role in mitigating emissions, although “the scientific debate about the overall climate impact related to land use competition effects of specific bioenergy pathways remains unresolved” (Smith et al., 2014[4]).

Technical and economic potential for supply-side mitigation in agriculture

The mitigation potential of supply-side options in the agriculture sector can be decomposed into four components: technical, economic, market, and socially/politically constrained potential (Figure 1.1). The technical potential is defined as the maximum mitigation possible in the sector with the full implementation of all available supply-side mitigation options, ignoring all barriers to adoption. The economic potential takes the costs and benefits associated with different mitigation measures into account, indicating what can be achieved for a given carbon price. Institutional capacity constraints, political and social barriers related to the distributional impacts of policy options can also erode the potential of supply-side mitigation measures. Finally, these barriers along with practical implementation challenges, particularly those related to measurement reporting and verification (MRV) of emission reductions, combine to markedly lower the “market” potential for mitigation. That is, the collection of mitigation measures that farmers find worthy of adopting, given the existing incentives and constraints they face. This section is mainly concerned with the technical and economic potential to mitigate agricultural GHG emissions.

With full deployment of available emission reduction and carbon sequestration opportunities, the global technical mitigation potential of the agricultural sector in 2030 is estimated to be 5 500-6 000 MtCO₂eq yr¹, with a 95% confidence interval around this mean value of 300-11 400 MtCO₂eq yr¹ (Smith, 2012). This demonstrates that it is technically feasible for agriculture to become close to carbon neutral, relying on supply-side mitigation measures alone, although this depends on optimistic assumptions about the potential of soil carbon sequestration (SCS).

As shown in Figure 1.1, there are several barriers to the uptake of mitigation measures which will reduce its overall technical potential. The economic potential of these measures is reflected by their potential at a given carbon price, taking into account their costs and benefits. The most recent Assessment Report of the IPPC report, based on results from several studies (Rose et al., 2012[6]; McKinsey & Company, 2009[7]; Golub et al., 2009[8]; Smith, P., et al., 2008[9]), found that emission reductions for agriculture of 0.03-2.6 GtCO₂eq are possible at USD 50 tCO₂eq^-1, and 0.2-4.6 GtCO₂eq at USD 100 tCO₂eq^-1 in 2030 (Smith et al., 2014[4]). This wide range reflects the different coverage of mitigation sources and methodologies used. For example, the higher figures in these ranges include SCS measures.

A recent partial equilibrium assessment by Frank et al. (2018[10]) calculated non-CO₂ mitigation potential in 2030 of 1 GtCO₂eq at USD 25 tCO₂eq^-1, and 2.6 GtCO₂eq in 2050 at USD 100/tCO₂eq. Recent assessments presented Chapters 2 and 4 have found comparable economic mitigation potential. As shown in Chapter 2, global non-CO₂ emission reductions of 0.84 GtCO₂eq in 2030 at USD 40 tCO₂eq^-1 and 2.7 GtCO₂eq at USD 100 tCO₂eq^-1 found using the MAGNET computable general equilibrium (CGE) model. The increase in carbon stocks from changes in land use (from agriculture to forestry) substantially raised the economic potential, from 0.84 to 1.4 GtCO₂eq in 2030 and from 2.7 to 4.4 GtCO₂eq in 2050. In the global2 assessment made using AGLINK-COSIMO (Chapter 4), non-CO₂ emission reductions of 0.85 GtCO₂eq in 2030 at USD 60 tCO₂eq^-1 were calculated.

The global potential for SCS is estimated to be large but highly uncertain. Smith (2016[11]) reports the mean global potential for SCS in agricultural soils as 1.5 Gt CO₂ yr^-1 and 2.6 GtCO₂ yr¹, at carbon prices of USD 20/tCO₂eq and USD 100/tCO₂eq, respectively. In addition, the mitigation potential from increasing carbon stocks in vegetation is substantial. For example, Golub et al. (2012[12]) found that a policy package that combined a tax on agricultural emissions and a subsidy to sequester carbon in forest biomass at USD 27/tCO₂eq could mitigate 5.3 GtCO₂eq yr^-1 of emissions. Most of this potential was attributed to the sequestration of carbon in forest biomass, particularly from avoided deforestation and the conversion of forest to agricultural land (i.e. from changes in the extensive margin between forestry and agriculture).

Figure 1.1. Supply-side mitigation potential in the context of barriers to implementation and policy ambition

Source: Adapted from (Smith et al., 2014[4]).

Two requirements are necessary for policy measures to achieve any given level of mitigation at minimum economic cost. The first is that market-based policy instruments that achieve a common price for GHG emissions (such as an emissions tax or emissions trading scheme) be used. The second is that coverage of the market-based policy includes the largest possible share of global emissions from all regions and sectors. Given the large heterogeneity in marginal abatement costs amongst agents, sectors and regions, these two policy requirements will ensure that the lowest cost mitigation measures are adopted. The least cost characteristic of market-based policies stems from the flexibility with which they provide agents to select mitigation measures and technologies that provide them with the lowest net costs (or highest net benefits) for a given carbon price (Baumol and Oates, 1988[13]). Given this flexibility, it is possible it will not be economical to reduce at current or expected carbon market prices mitigation from some agricultural emission sources. According to some studies, mitigation measures that rely on the addition of lipids or nitrates in animal diets to lower CH₄ emissions from enteric fermentation fall into this category (Van Middelaar et al., 2014[14]; Henderson et al., 2015[15]).

The economic mitigation potentials described above are in many respects upper-bound estimates because they ignore several important constraints. These include political constraints related to sensitivities about food security, distributional impact on producers, and emissions leakages which can affect the type and strength of coverage of the policy measures implemented (Wreford, Ignaciuk and Gruère, 2017[16]). In addition, transaction costs, particularly those associated with overcoming complexities for MRV, can be problematic for some sources of mitigation, thereby reducing their cost effectiveness and hindering implementation. Given these constraints, achieving the necessary global uptake of mitigation policies in the agricultural sector to deliver the economic potentials outlined above, is likely to be an enormous political and technical challenge. Policy responses and solutions to address these barriers are elaborated below.

The mitigation potential of demand-side waste reduction measures

Recent research has highlighted the large potential for GHG emission reductions by replacing red meat and milk with less emission-intensive food products in human diets. Smith et al. (2014[4]) report that the potential from such dietary changes and reduced losses in the food supply chain is uncertain, but could mitigate a substantial 0.76-8.55 GtCO₂eq yr^-1 in 2050. Herrero et al. (2016[17]) report a similar mitigation potential of 0.7-7.3 GtCO₂eq yr^-1 in 2050 from a moderation in demand for livestock production, with the potential depending on the size of the moderation and the assumptions on the use of “spared land”.

OECD research presented in Chapter 4 has shown that a dietary shift away from ruminant products (a 10% reduction in red meat and milk consumption, offset by a commensurate increase in the consumption of pig and poultry products) could lower emissions by 0.9 GtCO₂eq yr^-1 in 2030. This is substantial, but it is at the lower range of estimates from the literature for this type of measure because of the modest size of the assumed dietary shift and because its scope was limited to changes in non-CO₂ emissions. Large emission reductions of between 0.4 and 0.8 GtCO₂eq yr^-1 were found to be possible if food waste was eliminated by 2030.

Despite the significant potential from these demand-side mitigation approaches, specific policy mechanisms to incentivise dietary adjustments and waste reduction have not been identified. Their policy potential is therefore unknown and likely to be much smaller than the upper range of estimates in the literature. In addition to identifying plausible policy options to reduce food waste, their potential to cause farm income to decrease and impose costs on consumers are typically ignored, and yet their inclusion has the potential to increase food prices and exacerbate farm income losses (Chapter 4).

Policy progress in mitigating GHG emissions originating from agricultural activities

185 states and the European Union have ratified the Paris Agreement and have outlined their commitments to mitigate GHG emissions in their Nationally Determined Contributions (NDCs), submitted under the Agreement. One hundred and three of these NDCs mention agriculture as a contributing sector but, with the exception of a few developing countries, they do not commit to specific targets for that sector. Moreover, progress in implementing concrete mitigation policy incentives and regulations lags behind other sectors, such as energy and transport, including in countries that have implemented or are scheduled to implement national level carbon pricing instruments for GHG emissions (World Bank and Ecofys, 2018[18]; Sense Partners, 2018[19]).

A snapshot of the main mitigation policies and targets to date can be seen in the timeline displayed in Figure 1.2. This non-exhaustive list was selected on the basis of two steps. First, a review of NDCs was conducted, and some countries with ambitious emission reduction targets specific to agriculture were selected. Second, a review of countries was carried out to identify mitigation policies with explicit incentives that either establish a price on emissions or make substantial funds available for investment in mitigation measures in agriculture. For consistency, the figure includes agricultural emission reductions and reduction targets, and excludes emission reductions from forestry and other land use. European Union–wide targets pertinent to agriculture are presented in Figure 1.2, whereas agriculture-specific targets set by some individual Member States, which can contribute to the broader targets, are described below.

Reflecting concerns about imposing costs on producers, emission leakages and MRV challenges, concrete mitigation outcomes have mainly been delivered by a small number of voluntary policies on the basis of paying farmers to mitigate emissions by adopting management improvements that are considered to be more than “business as usual”. These include Australia’s Emissions Reduction Fund (ERF) and offset schemes within regulated emission reduction systems, such as the Alberta Emission Offset System (AEOS), and the California Air Resources Board (ARB) Compliance Offset Program (CARB, 2019[20]). The ERF is notable for its relatively large government budget and the scale of its emission reductions, the overwhelming share of which have come from vegetation projects that enhance or protect carbon stocks,3 mostly on farmland (Regulator, 2019[21])(Clean Energy Regulator, 2019). The AEOS offsets are purchased using private funds, with the majority from increased soil carbon sequestration as a result of reduced and zero tillage. These AEOS offsets also include new uses of the Anaerobic Decomposition of Agricultural Materials protocol and the Reducing Emissions from Fed Cattle protocols (AEOR, 2019[22]). The ARB Compliance Offset Program is narrower in scope, including only protocols for measures to reduce methane from livestock manure and rice production. Policy action to address emissions in California has been substantially augmented with the Senate Bill No. 1383 on Climate Short-Lived Pollutants (2016), which sets the target of cutting dairy and livestock manure methane by 40% by 2030 from 2013 levels (equal to a reduction of about 12 MtCO₂eq yr^-1 in 2030) (Lee and Sumner, 2018[23]).

Figure 1.2. A snapshot of mitigation policy progress in the agriculture sector

Note: Includes a selection of mitigation policies, realised reductions, and national mitigation targets. Within the European Union, several countries have set specific targets and budgets for agriculture to contribute to Effort Sharing goals. An attempt was made to place the policies/targets at midpoint of their timeframes.

Sources: : (a) AEOR, 2019; (b) Gebara and Thuault, 2013; (c) CARB, 2019; (d) European Commission, 2019; (e) Clean Energy Regulator, 2019; (f) UNFCCC, 2019; (g) Meat & Livestock Australia, 2017; (h) CARB, 2017; (i) Bundesamt für Landwirtschaft, 2019.

In countries and jurisdictions where carbon pricing policies have been implemented, they have exempted non-CO₂ emissions from agriculture, including in the EU Emissions Trading System (EU ETS), the New Zealand Emissions Trading Scheme (NZ ETS), the carbon pricing component of Canada’s recently introduced Pan-Canadian Framework (PCF) policy, and the California Air Resources Board (CARB) Cap-and-Trade Program.

In its 2015 NDC submission under the Paris Agreement, Brazil pledged to strengthen its Low Carbon Emission Agriculture (ABC) program, including actions to restore an additional 15 million hectares of degraded pastureland UNFCCC (2019). This along with other mitigation measures that were initially set in its National Appropriate Mitigation Action (NAMA) submitted to the UNFCCC in 2010 are mostly incentivised by a substantial line of credit as part of its ABC program. However, the level of progress in meeting the mitigation goals from agriculture in its NAMA are unclear. Brazil’s major mitigation ambition comes from its efforts to curb deforestation. Although these do not count as reductions in agricultural emissions, agriculture is a driver of deforestation.

A few other countries have pledged ambitious future mitigation targets specific to agriculture (including Ethiopia and Nigeria), although some of these targets are conditional on external support and details about the policy instruments are unknown at present. Despite the current exemption of agriculture from the NZ ETS, New Zealand recently announced the Zero Carbon Amendment Bill4 which targets the reduction of all national GHG emissions5 – with the exception of biogenic methane6 – to net zero by 2050. The Bill sets separate targets to reduce biogenic methane emissions (which come mainly from ruminant livestock) by 10% by 2030, and to between 24% and 47% by 2050, which is below 2017 levels (Ministry for the Environment, 2019). The New Zealand government is currently considering the policies required to reach these methane reduction targets. In the European Union, the EU Effort sharing legislation sets binding targets for non-ETS sectors (transport,7 agriculture, buildings, and waste) of 10% by 2020 and 30% by 2030 (European Commission, 2019a). Member States have flexibility regarding the contribution from non-ETS sectors, with some banking/borrowing and trading allowances, as well as the possibility to offset some emissions with reductions from Land Use, Land-Use Change and Forestry (LULUCF) measures.

The targets set under the EU Effort sharing legislation can vary slightly among Member States; while most do not have agriculture-specific targets, there are exceptions. For example, the Netherlands have proposed an emission reduction target of 3.5 MtCO₂eq yr^-1 by 2030 (~18% of agricultural emissions in 2016), to be achieved through government and industry collaboration and co-funding of mitigation solutions, in their National Climate Agreement (Klimaatakkoord, 2018[24]). Other Member States have established carbon budgets for agriculture. France, for example, has targeted a reduction of GHG emissions of 8% by 2023, 13% by 2028, and 20% by 2033, compared to 2015 levels, in their National Low-Carbon Strategy (Ministère de l’Ecologie, du Développement Durable, 2015[25]). The United Kingdom has also developed carbon budgets with strategic targets for sectors, including a 20% reduction in Agriculture, Forestry and Other Land Use (AFOLU) emissions between 2016 and 2030 (CCC, 2019[26]). Germany has more ambitious reduction goals of 31-34% for agricultural emissions by 2030, compared to 1990 levels, in its Climate Action Plan 2050 (BMUB, 2016[27]). The Climate Change Programme for Finnish Agriculture includes a national reduction goal of 13% for agricultural emissions between 2005 and 2020 (Ministry of Agriculture and Forestry (Finland), 2014[28])). Ireland’s Climate Action Plan sets out a decarbonisation pathway to 2030, which is consistent with the adoption of a net zero emission target by 2050.8 With cumulative CH₄ and N₂O emission reductions of 16.5 to 18.5 Mt CO₂-e between 2021 and 2030, the agricultural sector is expected to deliver 17% of total emission reductions set by this plan. A larger contribution of 26.8 Mt CO₂-e from LULUCF actions, mainly in the forestry sector, is targeted by the Plan over this same period. It is expected that the next CAP, beyond 2020, will be the main driver of emission reductions in agriculture (Ireland, Government of, 2019[29]).

Without direct and strong policy incentives in place to drive GHG mitigation in the agricultural sectors of EU Member States, some of their targets are strategic or aspirational. There are, however, strong regulatory frameworks in place in the European Union for other pollutants, which can have a synergistic impact on mitigating GHG emissions in agriculture, including the Nitrates Directive and the National Emission Ceilings Directive (NEC).

There has been a slow emergence of industry-led initiatives to move ahead with GHG mitigation initiatives in the absence of strong policy action by governments, and in recognition of growing consumer preferences for low-emission products. An example is the Australian red meat and livestock industry's ambitious goal to become carbon neutral by 2030.9 The National Farmers Union of the United Kingdom announced they would try to achieve “net zero” agricultural emissions from UK Agriculture by 2040 through a combination of improvements in efficiency, increased carbon storage, and bioenergy production (NFU, 2019[30]). Emerging public policy frameworks incentivising mitigation in agriculture could create more favourable returns to such industry-led investments and initiatives. There are nevertheless limitations to all voluntary approaches such as these, and in most countries stronger incentives will be needed to underpin large-scale mitigation ambitions that are commensurate with the targets of the Paris Agreement.

The small number of policies that have been implemented to date have generated useful knowledge on the feasibility and costs of certain practices. The viability of measures based on reducing manure methane emissions from confined livestock operations, such as piggeries and dairy farms, is apparent from their level of enrolment in offset schemes, e.g. Australia’s ERF and the California’s Offset Credit Scheme. This is not surprising given that manure methane from intensive systems is the closest of all agricultural GHGs to a point source, which tend to be much easier to manage than diffuse sources that dominate the sector’s profile of GHG emissions. Thus, the MRV challenges raised earlier have played out to some extent in the types of abatement measures that are permitted and that have been enrolled in these schemes. However, manure CH₄ emissions represent only a small share of agriculture’s overall emissions at the global level.

When considering the pledges and policy outcomes of the land sector as whole, it is not uncommon for higher mitigation ambition and outcomes to be found in the forestry component of AFOLU. In Ireland, for example, the state-funded Afforestation Scheme, which incentivises land owners to convert land from agricultural production to forestry has been instrumental in increasing the country’s forest cover. Since 1990, as a consequence of this scheme, Ireland is expected to remove a net 4.5 Mt CO₂e per year from the atmosphere over the period 2021-30 (DCCAE, 2017[31]) In general, the forestry sector is more widely cited than agriculture as a contributor to emission reduction targets in countries’ NDC commitments (Richards et al., 2016).

In order to evaluate a country’s mitigation efforts in agriculture fairly, it is important to take an economy-wide perspective. The European Union may, for instance, lack strong and direct GHG mitigation policy incentives for agriculture but it has committed to an ambitious economy-wide mitigation goal in its NDC, and has a large-scale carbon pricing policy (EU ETS) which covers 45% of its GHG emissions (European Commission, 2019[32]).

In summary, the progress to-date on GHG mitigation policy in agriculture has been uneven across countries, relying on a combination of voluntary policies including beneficiary-pays approaches, green finance, and modest target setting. This amounts to an aggregate global level of policy ambition that is out of step with the agricultural sector’s potential to address climate change. Richards et al. (2016[33]) calculate that the mitigation potential of countries providing specific targets for agriculture in their NDCs is 15%. However, given that most countries have submitted agriculture-specific targets, it is not possible to gauge the overall impact of NDCs submissions on global agricultural emissions (Richards et al., 2016[33]). Continued lack of progress in agriculture could stifle efforts to limit global warming, with some model scenarios showing that non-CO₂ emissions from agriculture could become the largest sectoral source of global GHG emissions by mid-century if other sectors succeed in their decarbonisation (Gernaat et al., 2015[34]; Wollenberg et al., 2016[35]). Alarmingly, recent research by Nisbet et al. (2019[36]) shows that methane emissions (the second most important anthropogenic GHG), of which agriculture is a major contributor, have risen much faster than expected. This reduces the timeframe needed to achieve net-zero CO₂ emissions to meet the goals of the Paris Agreement. With most national level targets set for 2030, there is still time for countries to develop more concrete policies for the agricultural sector, but recent analysis by the UN (UNEP, 2018[37]) shows that without full implementation of the NDC commitments global temperature will increase by 3^oC by 2100, well in excess of the 1.5^oC and 2^oC targets of the Paris Agreement.

Possible responses to the mitigation policy challenges for agriculture

Managing the trade-offs between mitigation effectiveness and the distributional impacts of mitigation policies

To mitigate GHG emissions from agriculture as cost effectively as possible, global action and a reliance on market-based mitigation policies are required. The barriers mentioned above – political constraints related to sensitivities about food security, distributional impacts on producers, emission leakages, and the challenges related to institutional capacity and the MRV of emission reductions – need to be addressed to enable the widespread implementation of effective mitigation policies in the agricultural sector. In this section, several policy design options are explored.

OECD research presented in the subsequent chapters, shows that the choice of policy used to mobilise mitigation efforts in agriculture can induce profoundly different trade-offs in terms of impact on mitigation, farm income, food consumption, government finances, cost effectiveness, and overall economic welfare. These policy choices can have very different impacts on the competitiveness of producers in different sectors and regions.

The economic potential described above includes the assumption that a carbon pricing policy is applied to all agricultural emissions. Such policies are based on the “beneficiary pays principle” and are very effective at reducing emissions for a given carbon price. In addition to incentivising the uptake of mitigation measures, much of their effectiveness stems from the contraction of output they induce by reducing profits and causing farms to exit the sector. This is particularly the case for farmers producing emission-intensive commodities, which lack affordable solutions to reduce the bulk of their emissions. This is typical of some biological emission sources in agriculture, such as enteric methane from ruminants. Policies base on the beneficiary pays principle are the most economically efficient policy instruments (Baumol and Oates, 1988[13]), and these adjustments are a necessary part of the process to attain efficiency benefits. However, their distributional impacts can pose significant political challenges. Although many of the same concerns could be expressed for producers of emission-intensive commodities in other sectors of the economy, there are unique sensitivities in several regions that are associated with food production and agricultural development which can amplify the political challenge of securing support.

Where these concerns prevail, market-based policies that are based on the “beneficiary pays principle” can pay for emission reductions either via a subsidy or the creation of an offset market. These policies can provide the same marginal abatement incentives as a GHG tax, while they avoid imposing costs on producers and tend to have negligible impacts on food consumption and prices compared to a GHG emission tax. For these reasons, paying farmers to abate emissions is less of a political challenge than making them pay for their emissions. It is, however, a less effective way to reduce agricultural GHG emissions. As shown in Chapter 2, a global-level abatement payment would be half as effective as a GHG tax for a given carbon price. This is the case because abatement payments do not reduce farm profits and, unlike taxes, do not induce farmers to exit the sector. Indeed, if payments overcompensate farmers for their abatement costs, this can encourage new farmers to enter the sector, thereby reducing the effectiveness of the policy (Baumol and Oates, 1988[13]).

There are other limitations to using a beneficiary-pays policy, least of which is the need to raise funds to finance it and the associated opportunity costs. Where the policy is financed by government, a competitive market-based mechanism such as an auction would be required to deliver cost-effective mitigation outcomes. Unless the payments replace existing distortionary forms of support, they risk reducing the overall economic welfare compared to a GHG tax or emission-trading scheme in countries that have highly supported agricultural sectors. Chapter 2 demonstrates that the economic welfare (or efficiency of economic resource allocation) costs of using additional government funds to pay for a global abatement subsidy would be higher on a per unit of mitigation basis than a comparably priced GHG tax. A potentially more economically efficient option is to redirect existing coupled distortionary forms of farm support for this purpose. The level of funds needed to support a global abatement payment (assuming a carbon price of USD 100 tCO₂eq^-1) represents a small proportion of agricultural producer support currently provided by countries for non-environmental purposes. However, given that the level of support among countries is so variable, some countries could easily fund abatement this way, while others could not, thus limiting the widespread applicability of this option. More analysis is needed to assess the welfare impacts and feasibility of this approach to finance abatement payment policies.

There are alternative market-based policy designs that could draw on the strengths of both the GHG tax and abatement payment policies to achieve a more desirable blend of trade-offs. Hybrid tax-subsidy mechanisms that recycle emission tax revenue back to producers to subsidise the adoption of low emission technologies offer a potential compromise (Pezzey, 2003[38]). These type of instruments have been used with some success in Europe to control nitrous oxide and sulphur dioxide emissions from industrial facilities (Millock and Nauges, 2006[39]). There are a range of ETS designs that also merit further attention, including the provision of free but binding permit allocations to agriculture which could help adjust the balance between mitigation effectiveness and the impact on farm incomes.

Policies to improve agricultural productivity have the potential to substantially mitigate emissions without compromising food security, although some types of productivity improvement can have unintended negative impacts on producers. The assessment presented in Chapter 4 shows that a 10% increase in the total factor productivity of agricultural production by 2030 could reduce annual emissions by 330 MtCO₂eq. However, this could also cause significant reductions in consumer food prices and agricultural incomes. While productivity improvements are often correctly framed as win-win options for the environment and the economy, their potential impact on some producers should be evaluated.

With respect to the substantial mitigation potential that could arise from changing human diets, the taxing of GHG emissions could facilitate a shift away from emission-intensive food products. It is possible to obtain the mitigation benefits of a GHG tax and maintain baseline food consumption levels by combining this policy with a food consumption subsidy (Chapter 2). However, a significant shift in consumer preferences to less emission intensive diets would be required to achieve the large mitigation potential that has been reported for this measure in the literature. Raising awareness about the climate change, health and other environmental impacts associated with ruminant products could help with this transition and is indeed already be happening in some developed countries. However, such approaches are likely to have a gradual impact and make a significant contribution over the long term only.

Another major policy challenge is that the largest populations of ruminant animals are found in developing regions, including in India and sub-Saharan Africa, where reducing the consumption of ruminant-based food products is likely to adversely impact food security and nutrition.

Mitigation policy options for managing the impacts of leakage

The spectre of emission leakages has been a potential deterrent for countries seeking to implement mitigation policies in agriculture. As with the distributional impacts, policy choice matters a lot with regard to managing trade-offs between leakage and mitigation effectiveness. Scenarios restricting a GHG tax on agricultural emissions in OECD countries, assessed in an ex ante global model presented in Chapter 2, showed that more than a third of emission reductions in these countries could be leaked as emission increases in other countries. If the number of countries applying this policy were smaller, the rate of leakage could be even larger. However, results from the ex ante modelling literature may overestimate leakage results due to difficulties in representing some policies that restrict market access and trade flows, including sanitary regulations and other non-trade barriers (Grosjean et al., 2016[40]). There are alternative policy options that can address leakage impacts. For example, the global assessment presented in Chapter 2 shows that an abatement payment to reduce emissions could deliver similar reductions to a GHG tax for a given carbon price without inducing emission leakages. The challenge of funding such a payment, however, would need to be resolved.

It is possible that expanding abatement payments to incentivise carbon sequestration on agricultural land could also cause some emission leakage. While most SCS measures should increase long term agricultural productivity and not create any obvious trade-offs with production, some measures such as protecting and restoring degraded peatlands would displace agricultural production. The displacement of production from policies that subsidise an increase in forest and shrub land biomass on agricultural land is more direct and likely to cause larger rates of leakage (Montserrat and Sohngen, 2009[41]). More research is needed to estimate the mitigation potential of such policies, net of these leakage impacts.

The use of a GHG-based tax levied on emission-intensive consumer products (red meat and dairy products) within OECD countries from domestic and imported sources could also eliminate leakage impacts. However, as with all policies that exclude non-OECD countries, this would have a very small impact on global agricultural emissions (Chapter 2). Furthermore, failure to take into account the emission intensities of products from different sources would reduce the economic efficiency of this policy option.

The importance of policy coherence and policy certainty

The absence of policy coherence can hamper the effectiveness of mitigation policies as the agriculture sector is subject to a wide range of regulations and policies which can have intended and unintended effects on its GHG emissions. For instance, subsidies for emission-intensive inputs such as nitrogen fertilisers and fossil fuels can cause agricultural emissions to increase (OECD, 2015[42]). Policies that affect or promote agricultural production can pose further challenges to reducing GHG emissions, as seen recently in the Irish dairy sector: the abolition of the EU milk quota regime in 2015, combined with Ireland’s comparative advantage in dairy and policies to increase its national milk production have led to an increase in dairy output and emissions (EPA, 2017[43]). However, dairy output has increased by more than emissions since this time, reducing the GHG emission intensity of the sector’s output.

It is important to send clear and consistent policy signals to the agricultural sector. The presence of high fixed investment costs in some production systems such as dairy can significantly lower the effectiveness of mitigation policies (Chapter 3). In the short run, investment costs are sunk and farms will continue to operate as long as market revenues exceed the variable costs of production rather than make new investments in response to mitigation policy incentives. Fixed investment costs are thus likely to slow the transition to lower-carbon agriculture. The transition will take longer where investments are more recent and where their costs are higher. Thus, there is a need for governments to avoid uncertainty in their long-term GHG mitigation objectives and policies so that farmers can make the appropriate investment decisions.

Policy options for MRV and other challenges related to SCS measures

MRV challenges and mitigation policy solutions for agriculture in general

Barriers related to the measurement reporting and verification (MRV) of emission reductions and institutional and education capacity constraints need to be taken into consideration as they limit the mitigation potential of the agricultural sector. The agricultural sector is comprised of a very large number of heterogeneous producers with mostly diffuse sources of emissions. This presents large MRV-related challenges to implementing mitigation policies in the sector, given that a significant proportion of the transaction costs related to MRV are considered to be fixed costs that are invariant to farm size (Bellassen et al., 2015[44]). However, there is a paucity of transaction cost estimates in the literature and the size of the available cost estimates vary widely, from as little as EUR 0.2-0.7 tCO₂eq^-1 for CDM projects in Latin America to 65-85% of the total costs of credits in an offset scheme in Western Canada (Grosjean et al., 2016[40]). These costs should decrease over time as farmers and agencies learn new procedures and find new ways to minimise the time and resources needed to comply with and administer new policies (Grosjean et al., 2016[40]).

Despite the tendency of MRV challenges and costs to decrease over time, weaknesses in the institutional capacity of many developing countries is a significant constraint for accurate MRV and large-scale policy implementation. Evidence of this is the dominant reliance on IPCC Tier 1 emission factors (IPPC, 2008[5]) to calculate and report national level GHG emissions from agriculture in developing countries. For example, Wilkes et al. (2017[45]) found that 118 of the 140 developing countries they assessed used the Tier 1 approach to calculate enteric CH₄ emissions from ruminant livestock. This simple calculation approach involves multiplying animal numbers default emission factors, which vary by species and region, but not according to feed quality, productivity improvements, and management practices which can lower emission levels. Consequently, it is not possible to reflect emission reductions from mitigation practices other than from the reduction of animal numbers in national GHG inventories, which lowers the recognition governments can gain from implementing mitigation policies in this sector. This occurs despite the fact that over half of developing countries have identified the potential to reduce livestock-related GHG emissions in their communications to the UNFCCC (Wilkes et al., 2017[45]). In contrast, a review of OECD countries’ national GHG inventory reports revealed that 33 of 36 OECD countries use more complex Tier 2 or Tier 3 approaches, which are better able to reflect the impact of changes in management on emission levels (IPPC, 2008[5]). Furthermore, some countries may have institutional frameworks linked to administering other environmental policies that can bring down the transaction costs associated with adopting new MRV protocols for new environmental policies (Coggan, Whittten and Bennett, 2010[46]). This is true of the European Union, where existing regulations – such as the National Emissions Ceilings directive, the Nitrate Directive and MRV tools linked to the CAP – can provide synergies to lower the transactions costs of regulating GHG emissions (Grosjean et al., 2016[40]).

The use of emission proxies, which are easier and cheaper than more direct forms of emission measurement, can lower these MRV-related transaction costs. According to the global assessment presented in Chapter 2, applying a GHG-based tax to ruminant animal numbers and quantity of nitrogen fertiliser would be far less effective than policies that directly taxed emissions10 or that issued payments for emission reductions. Farm-level assessment results also show it is more cost effective to target GHG emissions directly than to rely on simplistic emission proxies, even when transaction costs are accounted for (Chapter 3). A major problem with relying on simplistic emission proxies is that they severely limit the available options for mitigation, which means they require much higher carbon prices and therefore much higher costs to achieve the same mitigation outcomes as policies that target emissions more accurately and directly.

Given that a high share of MRV-related costs are fixed costs that are invariant to farm size (Bellassen et al., 2015[44]), it is possible to reduce some of these costs on a per-farm or per-emission basis with mechanisms to aggregate farms into larger units for MRV purposes.

Policy implementation challenges and solutions specific to SCS

The uncertainty and complexity of measuring some sources of emission reductions, including N₂O emission reductions from soils and SCS, are greater than other sources, introducing stronger trade-offs between MRV accuracy and cost (Grosjean et al., 2016[40]). An inherent MRV challenge for SCS is that the changes in soil carbon are often small relative to the size of the carbon stocks in the soil, and relative to the large area over which these changes occur. In addition, concerns about the permanence of carbon stocks, the finite capacity of soil carbon storage, and difficulties in demonstrating additionality have led to skepticism about the policy potential of SCS measures (MacLeod et al., 2018[47]). However, avoiding CO₂ emissions from the cultivation of soils with high organic matter content and from preventing their degradation through restoration can deliver high rates of mitigation over small areas (Lal, 2004[48]; Smith et al., 2014[4]; Griscom et al., 2017[49]). This may create viable mitigation opportunities despite the challenges.

Permanence is problematic because sequestration can easily be reversed at any point in time by poor soil management (Smith, 2012). Policy solutions are available to deal with this issue. One such approach is the creation of buffer pools to manage the risk of impermanence, whereby projects contribute a share of their offsets (based on the risk of reversal) to the pool, which can then be used to replace unforeseen losses of carbon stocks. Buffer pools were a feature of six of the ten carbon-offset protocols reviewed by Richards and Huebner (2014). In addition, accounting systems that record both carbon gains and carbon losses from storage pools are needed. Finally, policies that place greater value on temporary over permanent carbon sequestration are sometimes favoured as they are politically convenient, but are ultimately inefficient (Gramig, 2011[50]).

Conclusions

Progress on GHG mitigation policy in agriculture has been uneven across countries, relying on a combination of voluntary policies including beneficiary-pays approaches, green finance, and modest target setting. Collectively, they imply an aggregate level of ambition that is out of step with the sector’s potential to address climate change. Continued lack of progress will stifle efforts to meet the goals of the Paris Agreement to limit global warming to between 1.5°C and 2°C. The modest assembly of policies and targets are, in some ways, a testament to the policy implementation constraints faced by the sector. However, the evidence reported here demonstrates there are policy design solutions to overcome the most serious of these challenges, and bring the agriculture sector closer to fulfilling its substantial GHG mitigation potential.

Given that the vast majority of agricultural production and emissions is outside the OECD area, any mitigation policy restricted to OECD countries will have a limited impact on global emissions. However, reaching a global scale of uptake in mitigation policies, while managing the distributional impacts on producers and consumers in regions where food security and development objectives predominate, is a significant political challenge. In this context, the choice of policy used to mobilise mitigation is profoundly important as the distributional impacts and effectiveness for a given carbon price vary considerably among the main market-based mitigation policy options.

For example, polluter-pays policies, including the taxation of producer-level GHG emissions, are the most effective options available but they can impose relatively high costs on farmers and create emission leakages. Where these concerns stifle progress on mitigation, beneficiary-pays policies that pay for emission reductions by either a subsidy or the creation of an offset market could be a useful alternative. These policies are less effective however and unless they replace existing distortionary forms of support to agriculture, they risk reducing economic welfare compared to polluter-pays policies. There are alternative hybrid policy designs which could draw on the strengths of both types of market-based policy options and potentially achieve a more politically acceptable blend of trade-offs. A hybrid tax-subsidy mechanism which recycles emission tax revenue back to producers in order to subsidise the adoption of low emission technologies is one example. Free, but binding, allocations of permits in emission trading schemes are another.

There are also policy design solutions to address the practical challenges and transaction costs related to MRV. Simple emission proxies can be used instead of more direct forms of measurement to reduce these costs, but they are less effective and less cost-effective than policies that target emissions more directly, even after considering their transaction cost savings. The use of process-based models, supplemented with measurements, is another approach that can lower MRV costs, especially for SCS measures. However, there are serious questions about the policy feasibility of SCS measures, which is of concern given that they comprise such a large share of agriculture’s global mitigation potential.

Growing attention is being given to the important technical mitigation potential of demand-side mitigation options (including measures that encourage consumers to switch to lower emission diets and reduce food waste). However, the potential of such policies to achieve this is remains untested.

Whatever option is chosen, it is important to send clear and consistent policy signals to the agricultural sector. The presence of high-fixed investment costs in some production systems can significantly lower the effectiveness of mitigation policies, especially in the short run when investment costs are sunk. By avoiding uncertainty in their long-term GHG mitigation objectives and policies, governments allow farmers to make the appropriate investment decisions to facilitate the transition to low carbon agriculture.

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Notes

← 1.  As per Smith et al. (2014[4]), the term “forestry and other land use” here is consistent with the non-agricultural component of the term Agriculture, Forestry and Other Land Use (AFOLU) from the IPCC (2006) Guidelines and is also consistent with the term Land Use, Land-Use Change and Forestry (IPCC, 2003).

← 2.  Carbon tax applied to all global regions except to least developed countries.

← 3.  Between 2015 and 2019, 125.5 MtCO₂e of abatement was achieved with vegetation projects compared to 18.1 MtCO₂e from agricultural projects (Clean Energy Regulator, 2019).

← 4.  New Zealand Climate Change Response (Zero Carbon) Amendment Bill (amendment to the current Climate Change Response Act 2002).

← 5.  Includes carbon dioxide, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulphur hexafluoride, and nitrogen trifluoride.

← 6.  Biogenic methane emissions refer to methane emissions produced by the agriculture and waste sectors.

← 7.  With the exceptions of aviation and international maritime shipping.

← 8.  This is in line with the EU 2050 carbon neutrality objective outlined in the European strategic long-term vision for a climate neutral economy (European Commission, 2018b).

← 9.  https://www.mla.com.au/news-and-events/industry-news/red-meat-industry-can-be-carbon-neutral-by-2030

← 10.  Although emissions are rarely measured directly, some approaches such as those that rely on the accurate monitoring of production inputs, processes and outputs, coupled with detailed process-based models carefully calibrated to local conditions (i.e. IPCC Tier 3 measurement methods) are much closer to direct measurement than are approaches based on monitoring more simplistic emission proxies, such as number of cattle (i.e. IPCC Tier 1 measurement methods).