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Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China

Author

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  • Jinyu Han

    (National Science Library (Chengdu), Chinese Academy of Sciences, Chengdu 610299, China)

  • Jiansheng Qu

    (National Science Library (Chengdu), Chinese Academy of Sciences, Chengdu 610299, China
    College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Dai Wang

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Tek Narayan Maraseni

    (Institute for Agriculture and the Environment, University of Southern Queensland, Toowoomba, QLD 4350, Australia)

Abstract

The synergistic greenhouse gas (GHG) emission reduction of the crop production (CP) and livestock farming (LF) sectors is of great significance for food security and low-carbon development, especially for China, the world leader in agricultural production. In this paper, the GHG emissions from the CP and LF sectors are accounted for and compared, and the spatial econometric model is adopted for comparative study based on the panel data from 1997 to 2021. The results show that: (1) The total amount and intensity of GHG emissions from both sectors showed obvious spatial heterogeneity and spatial dependence, and the spatial distribution pattern was relatively stable. (2) The influence of each factor on the GHG intensity and spatial characteristics of CP and LF varies widely. For the CP sector, economic development (local effect −0.29, adjacent effect +1.13), increased urbanization rate (−0.24, +0.16), agricultural structure (−0.29, +0.05), and urban-rural disparity (−0.03, +0.17) all reduce the GHG intensity of local region, while increasing the GHG intensity of its adjacent areas, signifying leakage. The economic structure (+0.06, +0.16), agricultural finance support (+0.02, +0.26), mechanization level (+0.05, +0.03), and land occupancy rate (+0.54, +0.44) all play a role in increasing the GHG intensity of CP in the local region and its adjacent areas. The disaster degree (−0.03, −0.03) also reduced the GHG intensity of CP. For the LF sector, economic structure (+0.08, +0.11), urban-rural disparity (+0.11, +0.21), agricultural development level (+0.03, +0.50), and increased land occupancy rate (+0.05, +0.01) can improve the GHG intensity of the one region and adjacent areas. Economic development (+0.03, −0.15), urbanization rate (+0.04, −0.30), agricultural structure (+0.09, −0.03), and disaster degree (+0.02, −0.06) can increase the GHG intensity of the local region while reducing the GHG intensity of adjacent areas. Based on the results, under the background of carbon peaking and carbon neutralization(dual-carbon) goals, this study first puts forward collaborative emission reduction measures for CP and LF, respectively, then further rises to sector synergy and regional synergy, and constructs the countermeasure system framework of collaborative emission reduction from three levels, to provide guidance and reference for the realization of dual goals of agricultural GHG reduction and food security.

Suggested Citation

  • Jinyu Han & Jiansheng Qu & Dai Wang & Tek Narayan Maraseni, 2023. "Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China," Land, MDPI, vol. 12(9), pages 1-18, September.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1787-:d:1240171
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    References listed on IDEAS

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    1. Haoyue Wu & Hanjiao Huang & Jin Tang & Wenkuan Chen & Yanqiu He, 2019. "Net Greenhouse Gas Emissions from Agriculture in China: Estimation, Spatial Correlation and Convergence," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    2. Yanqiu He & Hongchun Wang & Rou Chen & Shiqi Hou & Dingde Xu, 2022. "The Forms, Channels and Conditions of Regional Agricultural Carbon Emission Reduction Interaction: A Provincial Perspective in China," IJERPH, MDPI, vol. 19(17), pages 1-22, September.
    3. Chuanhe Xiong & Shuang Chen & Liting Xu, 2020. "Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China," Growth and Change, Wiley Blackwell, vol. 51(3), pages 1401-1416, September.
    4. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    5. Yanqiu He & Xueying Cheng & Fang Wang & Ya Cheng, 2020. "Spatial correlation of China’s agricultural greenhouse gas emissions: a technology spillover perspective," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 2561-2590, December.
    6. Wu, Huijun & Yuan, Zengwei & Geng, Yong & Ren, Jingzheng & Jiang, Songyan & Sheng, Hu & Gao, Liangmin, 2017. "Temporal trends and spatial patterns of energy use efficiency and greenhouse gas emissions in crop production of Anhui Province, China," Energy, Elsevier, vol. 133(C), pages 955-968.
    7. Wenfeng Zhou & Jia He & Shaoquan Liu & Dingde Xu, 2023. "How Does Trust Influence Farmers’ Low-Carbon Agricultural Technology Adoption? Evidence from Rural Southwest, China," Land, MDPI, vol. 12(2), pages 1-14, February.
    8. Yihui Chen & Minjie Li & Kai Su & Xiaoyong Li, 2019. "Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China," Energies, MDPI, vol. 12(16), pages 1-23, August.
    9. Yong Zhu & Congjia Huo, 2022. "The Impact of Agricultural Production Efficiency on Agricultural Carbon Emissions in China," Energies, MDPI, vol. 15(12), pages 1-22, June.
    10. Robert H. Beach & Benjamin J. DeAngelo & Steven Rose & Changsheng Li & William Salas & Stephen J. DelGrosso, 2008. "Mitigation potential and costs for global agricultural greenhouse gas emissions-super-1," Agricultural Economics, International Association of Agricultural Economists, vol. 38(2), pages 109-115, March.
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