Abstract
The agricultural field is a major source of greenhouse gas (GHG) emissions. Therefore, we aimed to estimate agricultural GHG emissions to aid the reduction of GHG emissions from agricultural systems. We used the emission factor method, CLUMondo model to quantitatively calculate agricultural GHG emissions at the interprovincial and regional scales in China. Additionally, we qualitatively analysed the spatial distribution, carbon source structure, and gas types of agricultural GHG emissions at various stages. The results revealed that the spatial pattern of agricultural land in 2035 will generally be consistent with that in 2020 under the natural development scenario. Overall, agricultural GHG emissions will continue to increase. The simulation results showed that in east, south, southwest, and central China, the agricultural GHG emissions remained high, and gradually, the region in the southwest and northeast China emerged as an agglomeration of provinces with high agricultural GHG emissions. Notably, crop farming and animal husbandry acted as the primary source of agricultural GHG emissions in China. Overall, methane emissions increased marginally, nitrous oxide emissions increased substantially, and their proportion gradually approached 50%. Thus, to reduce the agricultural GHG emissions in China, the GHG emissions from crop farming and animal husbandry should be reduced. The target spatial pattern construction should be that of agricultural land with low GHG emissions.
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Funding
This study was supported by the National Natural Science Foundation of China (Grant No. 42171395, No. 41801298), the Natural Science Foundation of Jiangsu Province of China (Grant BK20220126, BK20180348).
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Conceptualization, HY; methodology, HY; investigation, JP; writing—original draft preparation, HY; writing—review and editing, LM. All authors have read and agreed to the published version of the manuscript.
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Yi, H., Penghui, J. & Manchun, L. The impact of agricultural land use change on agricultural GHG emissions in China. Environ Earth Sci 83, 61 (2024). https://doi.org/10.1007/s12665-023-11369-1
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DOI: https://doi.org/10.1007/s12665-023-11369-1