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Chinese Agricultural Science Bulletin ›› 2023, Vol. 39 ›› Issue (34): 105-113.doi: 10.11924/j.issn.1000-6850.casb2022-0915

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Research on the Temporal and Spatial Evolution and Influencing Factors of Agricultural Non-point Source Pollution in Anhui Province: Based on a Spatial Econometric Model

LU Ci(), LI Minghong, ZHANG Jun   

  1. School of Economics, Anhui University of Finance and Economics, Bengbu, Anhui 233030
  • Received:2022-11-08 Revised:2023-06-09 Online:2023-12-05 Published:2023-11-30

Abstract:

Anhui Province is an important agricultural production base in China, and agricultural non-point source pollution is a major restrictive factor affecting the ecological security of Anhui. The unit survey method and spatial econometric method were used to analyze the current situation and spatial correlation of agricultural pollution in Anhui Province from 2011 to 2020, and the spatial Durbin model was used to explore the influencing factors. The study found that: (1) the total amount of agricultural non-point source pollution in Anhui Province from 2011 to 2020 was U-shaped, the COD and TP emissions were similar to the total, and the TN emission showed a downward trend. (2) There were clear spatial differences in the overall level of non-point source pollution in the 16 cities, and the overall level of non-point source pollution in agriculture was better in each city in 2020. (3) Using two different spatial weight matrices to measure agricultural non-point source pollution in Anhui Province, the spatial correlation of emissions showed that there was a positive spatial correlation, indicating a significant effect of homogeneous variation. (4) The spatial Durbin model was used to verify that the proportion of non-agricultural employment inhibited agricultural non-point source pollution, and the household income of farmers promoted agricultural non-point source pollution. Both have significant spatial effects, with the latter having a greater facilitating effect than the inhibiting effect of the former.

Key words: agricultural non-point source pollution, Moran index, spatial Durbin model, spatial spillover, non-agricultural employment, farm household income