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Spatiotemporal Patterns and Influencing Factors of Agriculture Methane Emissions in China

Author

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  • Guofeng Wang

    (Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Pu Liu

    (Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Jinmiao Hu

    (Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Fan Zhang

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

Explaining the methane emission pattern of Chinese agriculture and the influencing factors of its spatiotemporal differentiation is of great theoretical and practical significance for carbon neutrality. This paper uses the IPCC coefficient method to measure and analyze the spatial and temporal differentiation characteristics of agricultural methane emission, clarify the dynamic evolution trend of the kernel density function, and reveal the key influencing factors of agricultural methane emission with geographical detectors. The results show that China’s agricultural methane emissions showed a first increasing and then declining trend. Agricultural methane emissions decreased from 21.4587 million tons to 17.6864 million tons, with an upward trend from 2000 to 2005, a significant decline in 2006, a slow change from 2007 to 2015, and a significant decline from 2015 to 2019. In addition, the emissions pattern of the three major grain functional areas is characteristic; in 2019, agricultural methane emissions from main producing area, main sales area, and balance area were 10.8406 million tons, 1.2471 million tons, and 5.599 million tons, respectively. The main grain producing area is the main area of methane emissions, and the emission pattern will not change in the short term. The variability of grain functional areas is the decisive factor for the difference in agricultural methane emissions. The state of industrial structure is the key influencing factor for adjusting the spatial distribution—the explanatory power of the industrial structure to the main producing areas reached 0.549; the level of agricultural development is the most core influencing factor of the spatial pattern of the main grain sales area—the explanatory power reached 0.292; and the level of industrialization and the industrial structure are the core influencing factors of the spatial pattern of the balance area—the explanatory power reached 0.545 and 0.479, respectively.

Suggested Citation

  • Guofeng Wang & Pu Liu & Jinmiao Hu & Fan Zhang, 2022. "Spatiotemporal Patterns and Influencing Factors of Agriculture Methane Emissions in China," Agriculture, MDPI, vol. 12(10), pages 1-17, September.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1573-:d:928910
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    References listed on IDEAS

    as
    1. Mompoloki Seketeme & Othusitse R. Madibela & Thabo Khumoetsile & Innocent Rugoho, 2022. "Ruminant contribution to enteric methane emissions and possible mitigation strategies in the Southern Africa Development Community region," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(7), pages 1-26, October.
    2. Ying Liu & Haiying Tang & Aamer Muhammad & Guoqin Huang, 2019. "Emission mechanism and reduction countermeasures of agricultural greenhouse gases – a review," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 9(2), pages 160-174, April.
    3. John Lynch & Tara Garnett, 2021. "Policy to Reduce Greenhouse Gas Emissions: Is Agricultural Methane a Special Case?," EuroChoices, The Agricultural Economics Society, vol. 20(2), pages 11-17, August.
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    Cited by:

    1. Xidong Zhang & Juan Zhang & Chengbo Yang, 2023. "Spatio-Temporal Evolution of Agricultural Carbon Emissions in China, 2000–2020," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    2. Masanori Saito & Etelvino Henrique Novotny & Yinglong Chen, 2023. "Soil Carbon and Microbial Processes in Agriculture Ecosystem," Agriculture, MDPI, vol. 13(9), pages 1-3, September.

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