An evaluation of the effect of greenhouse gas accounting methods on a marginal abatement cost curve for Irish agricultural greenhouse gas emissions

Agricultural Greenhouse Gas (GHG) emissions in Ireland are projected to increase up to 21 Mt CO2eq by 2030 mainly driven by increased dairy cow numbers and increased nitrogen fertiliser use. In response to the growing public awareness of the GHG emissions' environmental impact, the Irish government published the Climate Action Plan in 2019, which identifies the agricultural sector's leading role in reducing GHG emission and increasing carbon removals to achieve the national GHG emission targets by 2030. Marginal Abatement Cost Curves (MACCs) on Irish GHG emissions have projected the total technically feasible mitigation potential for the Irish agriculture, forestry and land use (AFOLU) sector to be sufficient enough to achieve the set targets by 2030. Although these mitigation measures are available and when implemented, would mostly lead to a win-win situation, the voluntary adaptation rate by farmers is low. This study addresses the most significant determinants of voluntary adoption of mitigation measures by systematically examining existing literature on how and to what extent non-price determinants affectthe voluntary adoption rate of technically feasible mitigation measures in the Irish afolu sector. The main identified nonprice determining factors were the degree of farmers' awareness regarding man-made GHG emissions, receiving agrienvironmental advice, implementation costs, profitability and size of farms, land quality and the type of farm enterprise. Integrating the gained results in the former macc analysis enabled us to adopt the implementation rates of the cost-efficient afolu mitigation measures accordingly. The non-price determinants impact the voluntary uptake rate of AFOLU mitigation measures to the extent that the adjusted total Irish AFOLU abatement potential is 47% lower than technically feasible. Considering that 51.6% of the total estimated AFOLU abatement potential in 2030 is offset through Irish forestry, which at current afforestation rate will turn into a net carbon source by 2035, a significant gap occurs to any potential Irish and EU GHG reduction targets. To substantially help bring the nexus between agricultural development and GHG emission targets in Ireland closer together, policy measures, that differentiate between the different type of AFOLU mitigation measures, need to be implemented to enhance the uptake rate of cost-beneficial and cost-effective measures. This would have the potential to reduce the level of agricultural GHG emissions by 2030 in a way that it would converge towards possible EU and Irish GHG emission reduction targets.

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.

Tracking agriculture and land-use greenhouse gas (GHG) emissions is necessary to inform global climate policy, yet UNFCCC country-reported data and three independent global databases show inconsistent estimates of countries’ emissions. Data for developing countries are particularly inconsistent, yet also collectively the largest source of emissions. Here, we provide transparency about available country-level emissions data for agriculture and related land use and characterize their data quality and consistency to enable better understanding of available data and tracking of climate change mitigation. We call for increased consistency in official national agricultural GHG inventory data and transparency about the differences among scientific data sources to enable decision makers to track progress, set priorities and manage emissions.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

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.

Agricultural emissions account for 53% of 2010 global non-CO2 emissions and are projected to increase substantially over the next 20 years, especially in Asia, Latin America and Africa. While agriculture is a substantial source of emissions, it is also generally considered to be a potential source of cost-effective non-CO2 GHG abatement. Previous “bottom-up” analyses provided marginal abatement cost (MAC) curves for use in modeling these options within economy-wide and global mitigation analyses. In this paper, we utilize updated economic and biophysical data and models developed by the US Environmental Protection Agency (EPA) to investigate regional mitigation potential for major sources of agricultural GHG emissions. In addition, we explore mitigation potential available at costs at or below the estimated benefits of mitigation, as represented by the social cost of carbon. Key enhancements over previous regional assessments include incorporation of additional mitigation options, updated baseline emissions projections, greater spatial disaggregation, and development of MAC curves through 2030. For croplands and rice cultivation, biophysical, process-based models (DAYCENT and DNDC) are used to simulate yields and net GHG emissions under baseline and mitigation scenarios while the livestock sector is modeled by applying key mitigation options to baselines compiled by EPA. MAC curves are generated accounting for net GHG reductions, yield effects, livestock productivity effects, commodity prices, labor requirements, and capital costs where appropriate. MAC curves are developed at the regional level and reveal large potential for non-CO2 GHG mitigation at low carbon prices, especially in Asia.

Global warming is a key issue that is related to the sustainable development of various countries, and agricultural sectors are particularly vulnerable to the effects of climate change and increasing climate variability. To obtain a better understanding of agricultural greenhouse gas (GHG) emissions, the estimation method proposed by the Intergovernmental Panel on Climate Change was used to estimate agricultural GHG emissions in 31 provinces in China with respect to five factors: agricultural energy consumption, agricultural farmland utilization, crop cultivation, ruminant feeding, and straw burning. To analyze emission reduction strategy interactions as well as the spillover of agricultural technical information between regions, we used the spatial Durbin model and further explored the different channels of technology spillover. The results obtained were as follows: (1) ruminant feeding and straw burning are the major sources of agricultural GHG emissions in China; (2) emission reduction strategies interact in the various regions, and imitation behaviors are increasing; (3) the correlation of agricultural GHG emission reduction in the different regions in China is not only limited to direct imitation behaviors, and it also reflects the spillover of technical information, i.e., agricultural technological progress plays an important role in the regional linkages of agricultural GHG emissions; (4) a shortening of the economic distance facilitates agricultural technology exchanges between regions. Therefore, to reduce agricultural GHG emissions, it is recommended that all regions should establish regional cooperative emission reduction mechanisms via agricultural technical cooperation.

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.

PurposeMitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.Design/methodology/approachThe study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.FindingsAgriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO2e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.Practical implicationsThe Chinese government should consider expanding its national carbon market to cover agricultural sector.Originality/valueExisting studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.

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.

The paper adopts a single-country regional panel dataset to analyse the long-term relationship between agricultural greenhouse gases (GHG) emissions and productivity growth and, consequently, to assess emissions sustainability. The hypothesis of emission sustainability is assessed by estimating alternative panel model specifications with conventional and GMM estimators applied to the highly heterogeneous Italian regional agriculture, whose methane and nitrous oxide emissions are properly reconstructed for the periods 1951–2008 and 1980–2008. The modelling approach and the empirical specification include the environmental Kuznets curve (EKC) as one of the possible outcomes. Results suggest that, when a significant relationship between agricultural GHG emissions and productivity growth occurs, it is often monotonic and, though sustainability is accepted for some GHG, no univocal robust evidence of the EKC emerges across the different specifications, estimators and periods. Policy implications of this empirical evidence are finally drawn.

Agricultural systems contribute nearly one-third of global anthropogenic GHG emissions and are an important source of GHGs globally. The clarification of the GHG emission pattern from agriculture is of paramount importance in the establishment of an agricultural emission reduction mechanism and the realization of China’s dual-carbon target. Based on the life cycle assessment method (LCA), this paper comprehensively quantifies the greenhouse gas emissions from the agricultural system in China, encompassing rice, wheat, and corn cultivation as well as animal husbandry including cows, horses, donkeys, mules, camels, pigs, and sheep. The analysis covers the period 2000–2020 and examines the spatial distribution, temporal trends, and structural changes in the greenhouse gas emissions within China’s agriculture sector. The main results are as follows: (1) from 2000 to 2020, China witnessed a consistent upward trajectory in its total agricultural GHG emissions, exhibiting an average annual growth rate of 0.73%. Notably, methane (CH4) emissions emerged as the largest contributor, displaying an overall fluctuating pattern. Carbon dioxide (CO2) emissions demonstrated intermittent increases with a noteworthy annual growth rate of 3%, signifying the most rapid expansion within this context. Conversely, nitrous oxide (N2O) emissions experienced decline over the specified period. (2) GHG emissions from cultivation demonstrate an upward trajectory, primarily driven by the CH4 emissions originating from rice cultivation and CO2 resulting from straw incineration. Conversely, GHG emissions stemming from animal husbandry declined, with the primary source being CH4 emissions arising from animal enteric fermentation. Agricultural N2O emissions predominantly arise due to manure management and nitrogen fertilizer application. (3) Agricultural greenhouse gas emissions exhibit significant variations in spatial distribution, gradually concentrating towards the North China Plain, the middle and lower reaches of the Yangtze River, and the northeast. Specifically, agricultural CH4 emissions are progressively concentrated in China’s pivotal rice-growing regions, encompassing the middle and lower reaches of the Yangtze River Plain, as well as livestock breeding areas like Inner Mongolia. Agricultural CO2 emissions primarily concentrate in dryland crop production zones such as North China and Northeast China. Meanwhile, Agricultural N2O emissions predominantly occur in Inner Mongolia and the North China Plain. China’s agricultural greenhouse gas emissions in 2020 show a significant spatial clustering effect, with hotspots primarily concentrated in Shandong, Anhui, Henan, and other regions and cold spots focused in the western and southern areas. The emission patterns of agricultural GHGs are closely intertwined with farming practices, regional development levels, and national policy; hence, tailored measures for emission reduction should be formulated based on specific crop types, livestock categories, agricultural production activities, and regional development characteristics.

Comprehending the spatial-temporal characteristics, contributions, and evolution of driving factors in agricultural non-CO2 greenhouse gas (GHG) emissions at a macro level is pivotal in pursuing temperature control objectives and achieving China's strategic goals related to carbon peak and carbon neutrality. This study employs the Intergovernmental Panel on Climate Change (IPCC) carbon emissions coefficient method to comprehensively evaluate agricultural non-CO2 GHG emissions at the provincial level. Subsequently, the contributions and spatial-temporal evolution of six driving factors derived from the Kaya identity were quantitatively explored using the Logarithmic Mean Divisia Index (LMDI) and Geographical and Temporal Weighted Regression (GTWR) methods. The results revealed that the distribution of agricultural non-CO2 GHG emissions is shifting from the central provinces to the northwest regions. Moreover, the dominant driving factors of agricultural non-CO2 GHG emissions were primarily economic factor (EDL) with positive impact (cumulative promotion is 2939.61 million metric tons (Mt)), alongside agricultural production efficiency factor (EI) with negative impact (cumulative reduction is 2208.98 Mt). Influence of EDL diminished in the eastern coastal regions but significantly impacted underdeveloped regions such as the northwest and southwest. In the eastern coastal regions, EI gradually became the absolute dominant driver, demonstrating a rapid reduction effect. Additionally, a declining birth rate and rural-to-urban population migration have significantly amplified the driving effects of the population factor (RP) at a national scale. These findings, in conjunction with the disparities in geographic and socioeconomic development among provinces, can serve as a guiding framework for the development of a region-specific roadmap aimed at reducing agricultural non-CO2 GHG emissions.

CAP payments and agricultural GHG emissions in Italy. A farm-level assessment