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Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China

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  • Chuanhe Xiong
  • Shuang Chen
  • Liting Xu

Abstract

STIRPAT (stochastic impact by regression on population, affluence, and technology) model is used to identify the influencing factors of agricultural carbon emissions in Jiangsu province. By referring to Kaya identity and combining with the actual situation of agricultural carbon emissions, four basic influencing factors were obtained: agricultural production efficiency, agricultural structure, agricultural economic development level, and agricultural population size. In addition, urbanization, mechanization, and natural disaster level were listed as influencing factors. The results demonstrated: (a) Urbanization was the first promoting factor of agricultural carbon emissions, indicating a 0.2510% increase in agricultural carbon emissions due to a 1% increase in urbanization. The other three positive factors were, respectively, agricultural mechanization, agricultural structure, and agricultural economic development and their influence indexes were 0.1481, 0.1163, and 0.0845, respectively. (b) Agricultural production efficiency was the most important factor to restrain agricultural carbon emissions. For every 1% increase in agricultural production efficiency, corresponding agricultural carbon emissions would be reduced by 0.3288%. Agricultural population size was also an important factor to reduce agricultural carbon emissions and its influence index was −0.045. Finally, we propose policy recommendations including implementation of orderly urbanization, dependence and development of low carbon technology, establishment of agricultural carbon compensation mechanism, etc.

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  • 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.
    • Handle: RePEc:bla:growch:v:51:y:2020:i:3:p:1401-1416
    DOI: 10.1111/grow.12384
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    18. 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.
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    20. Yihui Chen & Minjie Li, 2024. "How does the digital transformation of agriculture affect carbon emissions? Evidence from China’s provincial panel data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    21. Muziyun Liu & Hui Liu, 2023. "Influence of Climate Change on Carbon Emissions during Grain Production and Its Mechanism," Sustainability, MDPI, vol. 15(13), pages 1-15, June.
    22. Bingbing Huang & Hui Kong & Jinhong Yu & Xiaoyou Zhang, 2022. "A Study on the Impact of Low-Carbon Technology Application in Agriculture on the Returns of Large-Scale Farmers," IJERPH, MDPI, vol. 19(16), pages 1-18, August.

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