Spatial-Temporal Pattern Evolution and Influencing Factors of Agricultural Carbon Emissions in the Process of Rapid Urbanization: A Case Study of the Yangtze River Delta, China
Wei Ma 1
Na Bo 1
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College of Economics and Management, Huaibei Normal University, Huaibei, Anhui, 235000, China
Business School, Yangzhou University, Yangzhou, Jiangsu, 225127, China
Submission date: 2022-06-21
Final revision date: 2022-08-18
Acceptance date: 2022-08-29
Online publication date: 2022-11-02
Publication date: 2022-12-21
Corresponding author
Yue Gao   

Business School, Yangzhou University, Yangzhou, Jiangsu, 225127, China, China
Pol. J. Environ. Stud. 2023;32(1):183–198
Strengthening agricultural carbon emissions (ACE) reduction is an inherent requirement to promote the integrated development of ecological greenery in the Yangtze River Delta (YRD), and it has a significant driving effect and benchmarking significance for China to achieve carbon peaking and carbon neutrality. Based on panel data of 41 cities in the YRD from 2001 to 2019, this study reveals the spatial and temporal evolution pattern of ACE and identifies the influencing factors through methods such as CV, SDE, ESDA and SDM. The results are summarized as follows: (1) the ACE in the YRD show a fluctuating downward trend, and the gap between cities tends to widen; (2) the YRD shows emission characteristics dominated by agricultural material input, with a proportion of over 50% over the years, followed by rice cultivation and livestock breeding with the lowest proportion. In addition, Jiangsu and Anhui have higher proportions, followed by Zhejiang, and Shanghai; (3) these cities with high ACE are mainly located in the northwest regions of the YRD, and those with low ACE are mainly located in the southeast regions of the YRD. Furthermore, cities in the YRD have a positive global spatial autocorrelation, and the local spatial agglomeration pattern has strong characteristics of stability and spatial dependence; (4) the agricultural economic development level has an inverted U-shaped effect on ACE in the YRD. Meanwhile, the total rural population, total power of agricultural machinery, and urbanization level have a significant positive impact, while the agricultural planting structure and trade openness level are not significantly affected, but the rural non-farm employment level have a significantly negative impact on ACE. SDM further supports the influence of various factors, and it can be found that the agricultural economic development level and trade openness level exhibit significant negative spillover effects.