Agricultural GHG emissions in the EU: an exploratory economic assessment of mitigation policy options

To achieve energy conservation and the reduction of agricultural greenhouse gas (GHG) emissions, the Ministry of Agriculture of the People’s Republic of China in 2015 made Zhejiang Province the first national low-carbon and circular agriculture pilot province. Specialized policies were conducted in Zhejiang Province for reducing agricultural GHG emissions. In this study, we collected the GHG emission sources data of each city in Hubei and Zhejiang Provinces and calculated the estimated agricultural GHG emission of each city from 2011 to 2020 by using the recommended method from the Intergovernmental Panel on Climate Change (IPCC). Following this, we evaluated the impact of the pilot policies on the agricultural GHG emission in the treatment province, Zhejiang, by implementing the difference-in-differences (DID) analysis. The empirical results showed that after considering variables such as income level, rural employment, and average power of agricultural machinery, the agricultural GHG emissions in Zhejiang Province decreased significantly after 2015, compared with Hubei Province, driven by the low-carbon and circular agriculture pilot policies. Furthermore, agricultural GHG emissions can be effectively reduced by increasing national financial investment and administrative orders; however, excessive administrative orders and forced transformation of the agricultural system are likely to harm farmers’ interests in the process of policy implementation.

To achieve the goal of "carbon peak and neutrality," the strict requirements for greenhouse gas (GHG) emissions control in the agricultural sector were recommended in relevant plans for Beijing during the 14th Five-Year Plan period. Through collecting agricultural activity data and calculating and screening the emission factors, the amount and emission characteristics of agricultural GHG emissions in Beijing in 2020 were estimated and set as the baseline condition. On this basis, the GHG emissions in 2025 with optimized measurements implemented, which were selected in combination with the natural conditions and planting-breeding mode of Beijing, were set as the reduction condition. The emission reduction potential and its distribution during the 14th Five-Year Plan Period were predicted simultaneously. Meanwhile, the reduction effects on the GHG emissions of optimized measurements were evaluated. In addition, relevant policy recommendations on GHG reduction were proposed accordingly. The results revealed that the total agricultural GHG emissions in Beijing were estimated to be 456000 t (CO2-eq) in 2020, primarily from sources of animal intestinal fermentation and manure management, with contribution rates of 50.7% and 26.7%, respectively. Spatially, it was mainly distributed in districts with large livestock and poultry breeding scales, such as Shunyi District, Miyun District, and Yanqing District, etc. It was predicted that in 2025, the total agricultural GHG emissions would be 349000 t (CO2-eq), and the emission reduction potential in the 14th Five-Year Plan period would be 107000 t (CO2-eq). Animal intestinal fermentation would be the emission source with the largest reduction potential (60000 tons, CO2-eq), followed by the emission source of animal manure management (37000 tons, CO2-eq). Adjusting fodder composition and optimizing manure management were analyzed to be the most effective optimized measurements for agricultural GHG emission reduction. Moreover, the emission reduction potential of CH4 would be greater than that of N2O. The emission reduction potential would be mainly distributed in Miyun District, Shunyi District, Yanqing District, Fangshan District, Tongzhou District, and other suburbs with large livestock and poultry breeding scales, accounting for more than 10% of the total emission reduction potential for each. These regions with large emission reduction potential should be prioritized and then the assessments should be extended to the whole city. The measurements were recommended as follows:① the research and promotion of technologies such as fodder optimization and the efficient treatment of manure should be strengthened, ② the scope of the combination of planting and breeding model should be expanded to promote the development of circular agriculture, and ③ relevant standards, guidelines, and specifications for green and low-carbon agriculture should be formulated, and the regulatory and policy system for synergy reduction of agricultural pollution and GHG should be developed.

At the UN climate change conference in Paris in November 2015, Norway committed itself to a 40% reduction in greenhouse gas (GHG) emissions by 2030 compared to 1990 levels. Agriculture accounts for 8% of Norway’s total GHG emissions. If GHGs from drained and cultivated wetland (categorized under land use, land use change and forestry) are included, the share is 13%; this for a sector that accounts for roughly 0.3% of GDP. As is the case in most countries, agriculture is currently exempt from emission reduction measures, including the European Union’s Emissions Trading System (ETS), in which Norway participates. But the country has recently signaled its intention to include agriculture in future emission reduction efforts. Consideration is being given to how best to achieve GHG reductions in the sector. A recent report by the Norwegian Green Tax Commission, established by the government to evaluate policy options for achieving emission reductions, (Government of Norway, 2015) emphasizes the importance of including agriculture. The Commission suggests that agricultural emissions should be taxed at the same rate as for other sectors. It also recommends that reductions in the production and consumption of red meat should be specifically targeted, through cuts in production grants to farmers and the imposition of consumption taxes. Unsurprisingly, this proposed policy shift is extremely controversial and faces resistance, particularly from the farmers’ unions. Farmers argue that the maintenance of domestic agricultural production is crucial for achieving national food security objectives, in addition to pursuing other aims such as the maintenance of economic activity in rural areas and landscape preservation. Food security, which has been a key policy objective since the end of the Second World War, has been interpreted in Norway as requiring high levels of selfsufficiency in basic agricultural commodities. To achieve this, substantial subsidies are provided to farmers and domestic prices of many commodities are kept at high levels by restricting imports. The Organization for Economic Cooperation and Development (OECD) estimates that the total financial support provided to Norwegian agriculture in 2015 was equivalent to 62% of the value of gross farm receipts, which made Norway (along with Switzerland) a leader in the amount of support provided to agriculture by the 50 OECD member and non-member countries monitored by the Organization (OECD, 2016). In this paper we analyze policy options for achieving a 40% reduction in agricultural GHG emissions, consistent with the economy-wide target, while imposing the restriction that national food production measured in calories should be maintained (the food security target). This is consistent with the way that the Norwegian government identifies the country’s food security objective. In section 2 we outline the current situation with respect to GHG emissions in Norwegian agriculture. In section 3 we illustrate the policy issues involved by considering two product aggregates that are intensive in the use of land for crop production (grainland) and grassland, respectively. The aggregates are based on data for the main commodities in Norwegian agriculture relating to GHG emissions, land use, caloric content, subsidies, and costs per unit of production. We show that even though the opportunity set (i.e., the production combinations that are possible within technical constraints) is narrow, a 40% cut in emissions is achievable by substituting from ruminant products that are intensive in the use of grassland to products based on grainland. We also show that the emissions reduction both reduces government budgetary costs and land use, i.e., ruminant products are characterized by relatively high subsidies and land use. Two-dimensional analysis ignores the fact that per unit emissions from dairy production are low compared to other ruminant products (i.e., beef and sheep production). Both in terms of production value and agricultural employment, dairy farming is the most important component of Norwegian agriculture. Consequently, milk production deserves to be separated from ruminant meat production. Finally in section 4, we present a detailed analysis 3 of policy options derived from a disaggregated model that includes all the major products in Norwegian agriculture. In the model-based analysis, we examine first the imposition of a carbon tax, while maintaining existing agricultural support policies and import protection, and achieving the food security (production of calories) target. Since the imposition of a carbon tax in agriculture presents both technical and political challenges, we then examine an alternative approach of changing the existing structure of agricultural support to approximate the same result. We show that it is possible to change current subsidy rates to mimic the carbon tax and calorie target solution. The explanation for this is that ruminant products not only generate high emissions per produced calorie, but they are also the most highly subsidized products. Meat from ruminants is relatively unimportant in achieving Norway’s food security objective of calorie availability.

The increase of agricultural greenhouse gas (GHG) emissions has become a significant issue for China, affecting the achievement of its Nationally Determined Contributions under the Paris Agreement. Expansion of the large-scale multiple cropping system as a consequence of climate warming could be a major driving force of this increase. In this study, life cycle assessment was employed to identify agricultural GHG emissions due to the expansion of the multiple cropping system in the North China Plain and neighboring regions. We found that agricultural greenhouse gas emissions have increased from 41.34 to 120.87 Tg CO2-eq/yr over the past 30 years, and the expansion of the multiple cropping system has contributed to 13.89% of this increment. Furthermore, the increases in straw handling and agricultural inputs which are related to multiple cropping systems have also played an important role. Results of our study demonstrate that the expansion of the multiple cropping system contributes considerably to increases in agricultural GHG emissions in the North China Plain and neighboring regions. Therefore, it can be concluded that the sustained northward expansion of the multiple cropping system will further elevate agricultural GHG emissions in China, and this should be considered while formulating policies to reduce GHG emissions from agriculture.

Agricultural materials input (fertilizer and pesticide, etc.), together with straw burning, rice planting, and livestock breeding, constitute the sources of agricultural greenhouse gas (GHG) emissions. However, most related studies have discussed the total amount of agricultural GHG emissions or the role of straw burning and rice planting in agricultural GHG emissions and few studies on agricultural GHG emissions from Agricultural materials. Based on the data of 31 provinces in China from 2003 to 2018, this paper explored the evolution process of agricultural GHG emissions from Agricultural materials. Our research turned up some interesting findings. For example, firstly, Agricultural materials play an increasingly important role in agricultural GHG emissions. Agricultural GHG emissions due to Agricultural materials account for an increasing proportion of the total agricultural GHG emissions. Secondly, there are regional differences in the evolution trend of agricultural GHG emissions caused by agricultural materials. Especially after the urbanization rate broke through the critical line of 50% around 2010 in China.

A worldwide shift from current diets to the planetary health diet proposed by the EAT-Lancet Commission would have direct implications for agricultural greenhouse gas (GHG) emissions. By modelling the trajectory of food from cradle to farm gate while accounting for international trade, we estimate that agricultural GHG emissions would decrease in 101 countries as well as globally. Yet, in primarily low- and middle-income countries, agricultural GHG emissions would increase by 12-283%. Country-specific impacts of dietary transitions should be considered in climate change mitigation policy.

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions — Application of system dynamics modeling for the case of Latvia

Greenhouse gas (GHG) emissions from agriculture contribute to climate change. The consequences of unsustainable agricultural activity are polluted water, soil, air, and food. The agricultural sector has become one of the major contributors to global GHG emissions and is the world’s second largest emitter after the energy sector, which includes emissions from power generation and transport. Latvian and Lithuanian agriculture generates about one fifth of GHG emissions, while Estonia generates only about one tenth of the country’s GHG emissions. This paper investigates the GHG trends in agriculture from 1995 to 2019 and the driving forces of changes in GHG emissions from the agricultural sectors in the Baltic States (Lithuania, Latvia, and Estonia), which are helpful for formulating effective carbon reduction policies and strategies. The impact factors have on GHG emissions was analysed by using the Logarithmic Mean Divisia Index (LMDI) method based on Kaya identity. The aim of this study is to assess the dynamics of GHG emissions in agriculture and to identify the factors that have had the greatest impact on emissions. The analysis of the research data showed that in all three Baltic States GHG emissions from agriculture from 1995 to 2001–2002 decreased but later exceeded the level of 1995 (except for Lithuania). The analysis of the research data also revealed that the pollution caused by animal husbandry activities decreased. GHG intensity declined by 2–3% annually, but the structure of agriculture remained relatively stable. The decomposition of GHG emissions in agriculture showed very large temporary changes in the analysed factors and the agriculture of the Baltic States. GHG emissions are mainly increased by pollution due to the growing economy of the sector, and their decrease is mainly influenced by two factors—the decrease in the number of people employed in the agriculture sector and the decreasing intensity of GHGs in agriculture. The dependence of the result on the factors used for the decomposition analysis was investigated by the method of multivariate regression analysis. Regression analysis showed that the highest coefficient of determination (R2 = 0.93) was obtained for Estonian data and the lowest (R2 = 0.54) for Lithuanian data. In the case of Estonia, all factors were statistically significant; in the case of Latvia and Lithuania, one of the factors was statistically insignificant. The identified GHG emission factors allowed us to submit our insights for the reduction of emissions in the agriculture of the Baltic States.

Energy-related GHG emission in agriculture of the European countries: An application of the Generalized Divisia Index

Livestock are by far the greatest contributor to Australian agricultural greenhouse gas (GHG) emissions and are projected to account for 72% of total agricultural emissions by 2020. This necessitates the development of GHG mitigation strategies from the livestock sector. Currently there are many research streams investigating the efficacy of GHG mitigation technologies, though most are at the individual animal level. Here we examine the effect of a promising animal-scale intervention - increasing ewe fecundity - on GHG emissions at the whole farm scale. This approach accounts for seasonal climatic influences on farm productivity and the dynamic interactions between variables. The study used a biophysical model and was based on real data from a property in south-eastern Australia that currently runs a self-replacing prime lamb enterprise. The breeding flock was a composite cross-bred genotype segregating for the FecB gene (after the 'fecundity Booroola' trait observed in Australian Merinos), with typical lambing rates of 150-200% lambs per ewe. Lambs were born in mid-winter (July) and were weaned and sold at 18 weeks of age at the beginning of summer (December). Livestock continuously grazed pastures of phalaris, cocksfoot and subterranean clover and were supplied with barley grain as supplementary feed in seasons when pasture biomass availability was low. Biophysical variables including pasture phenology and flock dynamics were simulated on a daily time-step using the model GrassGro with historical weather data from 1970 to 2012. Whole farm GHG emissions were computed with GrassGro outputs and methodology from the Australian National Greenhouse Accounts Inventory (DCCEE, 2012). Increasing ewe fecundity from 1.0 lamb per ewe at birth (equivalent to scanning rates at pregnancy of 80% of ewes with single lambs, 17% with twins and 3% empty) to 1.5 (scanning rates of 20% ewes with singles, 51% with twins, 26% with triplets and 3% empty as observed at the property) reduced mean emissions intensity from 9.3 to 7.3 t CO2-equivalents/t animal product and GHG emissions per animal sold by 32%. Increasing fecundity reduced average lamb sale liveweight from 42 to 40 kg, but this was offset by an increase in annual sheep sales from 8 to 12 head/ha and an increase in average annual meat production from 410 to 540 kg liveweight/ha. A key benefit associated with increasing sheep fecundity is the ability to increase enterprise productivity whilst remaining environmentally sustainable. For the same long-term average annual stocking rate as an enterprise running genotypes with lower fecundity, it was shown that genotypes with high fecundity such as those on the property could either increase meat and wool productivity from 449 to 571 kg/ha (clean fleece weight plus liveweight at sale) with little change in net GHG emissions, or reduce net GHG emissions from 4.1 to 3.2 t CO2-equivalents/ha for similar average annual farm productivity. In either case, GHG emissions intensity was reduced by about 2.1 t CO2-equivalents/t animal product. From a methodological perspective, this study revealed that differences in computing the relative effect of increased fecundity on total farm production, GHG emissions or emissions intensity either within or across years were relatively small. For example, the mean difference in emissions intensity of an enterprise obtaining 1.5 lambs per ewe relative to an enterprise obtaining 1.0 lamb per ewe computed within years was -25%, whereas the relative difference in mean emissions intensity across years was -27%. Such findings justify the traditional approach of previous GHG mitigation studies which compare differences (e.g. abatement potential) between values averaged across multiple-year simulation runs, as opposed to the method of computing the differences between intervention strategies within years then comparing the average difference.

The selection of effective carbon reduction strategies and the management of agricultural greenhouse gas (GHG) emissions are critical issues in climate change mitigation. Different climate actions can lead to varied pathways for agricultural GHG emissions. This study constructs a Computable General Equilibrium (CGE) model for Chinese agriculture to identify which measures can contribute to achieving established climate governance objectives, exploring potential net emission pathways for agricultural GHG. On this basis, we provide a rationale for selecting emission reduction measures. Our findings indicate that: (1) Carbon taxation is an indispensable climate action for achieving China’s “dual carbon” goals and net-zero emissions, necessitating combination with other mitigation strategies; (2) Carbon sequestration, non-agricultural carbon taxation, and CCUS measures can alter the net emission trajectory of agricultural GHG, and carbon sequestration shows the most significant impact; (3) Based on the ‘dual carbon’ or net-zero emission goals, China’s agricultural GHG emission pathway might exhibit a flat M-shaped characteristic, whereas intensifying carbon sequestration efforts could lead to an inverted V-shaped trajectory. Our results offer decision-making support for the formulation of GHG emission reduction measures in China.

Advantages of nitrogen fertilizer deep placement in greenhouse gas emissions and net ecosystem economic benefits from no-tillage paddy fields

Based on the data of China’s agricultural greenhouse gas (GHG) emissions from previous national GHG inventories, the Food and Agriculture Organization (FAO) of the United Nations database and related literature, this paper systematically analyzes recent trends in China’s total agricultural GHG sources, sinks and emissions intensity from multiple perspectives. The results show that from 2005 to 2021, China’s annual agricultural GHG emissions increased from 859 million to 931 million tons of carbon dioxide equivalent (MtCO2e), while the net carbon sequestration in agricultural soils grew from 41 MtCO2e to 106 MtCO2e. Specifically, agricultural methane (CH4) emissions accounted for 68%–73% of the total agricultural emissions, higher than agricultural nitrous oxide (N2O) emissions. By sector, livestock production contributed 49%–54% toward total agricultural emissions, exceeding emissions of crop production. According to FAO data, the GHG emissions intensity of China’s agricultural sector is lower than that of developed countries and regions. Furthermore, this paper summarizes China’s mitigation potential in feed and livestock production, manure management, fertilizer application, irrigation and tillage practices, as well as challenges faced by China in implementing existing measures and policies for agricultural carbon mitigation and sequestration. Finally, recommendations for future policies and measures are proposed from technological, institutional, and managerial perspectives.

Agriculture plays a central role in maintaining food security and achieving sustainable development for human society. It is a challenge for the agricultural sector to mitigate greenhouse gas (GHG) emissions and maintain agricultural production. However, dual-level uncertainties exist in the processes of agricultural GHG accounting and emission reduction management. In this research, an integrated approach for identifying adaptation strategies in agricultural GHG emission reduction management was developed through incorporating life cycle analysis (LCA) of agricultural production into a general mathematical programming model. This approach strengthened the applicability of LCA and the comprehensiveness of programming models in generating agricultural adaptive actions under different GHG emission restriction targets. Also, dual-level uncertainties of LCA and adaptation management can be effectively addressed. A case study was proposed to illustrate application of the approach in Dalian City, China. The results indicated that farming patterns in eight districts would change significantly. The total area of maize fields would account for the primary proportion (i.e., 40–45 %) in its agricultural sector. Rice, peanut and cabbage fields would be the minor contributors in terms of GHG emissions. In addition to effective rainfall (i.e., [156, 259] mm/ha), a certain amount of water would be supplied for agricultural irrigation to maximize the city’s agricultural yields. Compared with other agricultural crops, rice fields would need the largest amount of irrigation water (i.e., [153.72, 277.98] Mt) to meet the requirements of local government plans.

The vast majority of the scientific community believe that anthropogenic greenhouse gas (GHG) emissions are the predominant cause of climate change. One of the GHG emission sources is agriculture. Following the International Panel on Climate Change (IPCC) guidelines regarding GHG emission calculation, agriculture is responsible for around 10% of the overall global emissions. Agricultural GHG emissions consist of several emission source categories and several GHGs. In this article were described the results of multivariate statistical analyses performed on data gathered during the period 1990–2017 from the inventories of 43 Annex I countries (parties to the United Nations Framework Convention on Climate Change, UNFCCC, listed in Annex I of the Convention). Trends in the agricultural GHG emissions were analyzed. Generally, the global agricultural GHG emissions are increasing, while the emissions from Annex I countries are decreasing. Apart from the application of urea, emissions from all other sources, such as enteric fermentation, manure management, rice cultivation, agricultural soils, field burning of agricultural residues, and liming are decreasing. Based on multivariate analysis, the most different countries, in terms of GHG emission sources composition in agriculture and emission trends, are Australia, Japan, New Zealand and USA. The rest of the Annex I countries are mostly from Europe and their shares and trends are similar, with slight differences between countries depending, among others, on the date of joining the European Union.