Spatiotemporal evolution of factors affecting agricultural carbon emissions: empirical evidence from 31 Chinese provinces

Xixian Zheng (), Haixia Tan () and Wenmei Liao ()
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Xixian Zheng: Jiangxi Agricultural University
Haixia Tan: Yunnan Minzu University
Wenmei Liao: Jiangxi Agricultural University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 5, No 44, 10909-10943

Abstract: Abstract Reducing agricultural carbon emissions is a crucial aspect of China's overall carbon emission reduction plan. In this study, we first analyzed the spatiotemporal trends in agricultural carbon emissions across 31 provinces in China from 2007 to 2020. Subsequently, we employed a geographically and temporally weighted regression model to analyze the spatiotemporal evolution of the factors influencing provincial agricultural carbon emissions. Our findings revealed that high carbon emission areas are primarily distributed in the central and northern regions. The center of gravity of carbon emissions is located within Henan Province (112°30′–113°30′ E; 34°10′–33°40′ N) and has gradually shifted in the northwest direction. Therefore, the central, northern, and western regions should become the focal areas for agricultural carbon emission mitigation efforts. The influencing factors demonstrate spatiotemporal heterogeneity in their impacts on agricultural carbon emissions, so differentiated emission mitigation strategies should be formulated according to local conditions. The central and northern regions should prioritize the adoption of green technologies, support zero growth of chemical fertilizers and promotion of organic alternatives, and promote urbanization. Western regions should be encouraged to use less harmful fertilizers and increase mechanization levels. Nationwide, green technology innovation in agriculture should be strengthened to promote sustainable agricultural development.

Keywords: Agricultural carbon emissions; Center of gravity; Geographically and temporally weighted regression; Driving factors (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-04337-z

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