• Geographical Research
  • Vol. 39, Issue 4, 970 (2020)
Qingqing DENG1、1、2、2, Erling LI1、1、2、2、3、3、*, and Shixin REN1、1、2、2
Author Affiliations
  • 1.Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province/Institute of Agriculture and Rural Sustainable Development/College of Environment and Planning, Henan University, Kaifeng 475004, Henan, China
  • 1.河南大学黄河文明与可持续发展研究中心暨黄河文明传承与现代文明建设河南省协同创新中心/农业与农村可持续发展研究所/环境与规划学院,开封 475004
  • 2.Research Institute of Regional Economic, Henan Province, Kaifeng 475004, Henan, China
  • 2.河南省区域经济研究中心,开封 475004
  • 3.Collaborative Innovation Center of Urban-Rural Coordinated Development, Henan Province/Academician Laboratory for Urban and Rural Spatial Data Mining, Zhengzhou 450000, China
  • 3.城乡协调发展河南省协同创新中心/河南省城乡空间数据挖掘院士工作站,郑州 450000
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    DOI: 10.11821/dlyj020181090 Cite this Article
    Qingqing DENG, Erling LI, Shixin REN. Impact of agricultural agglomeration on agricultural non-point source pollution: Evidences from the threshold effect based on the panel data of prefecture-level cities in China[J]. Geographical Research, 2020, 39(4): 970 Copy Citation Text show less

    Abstract

    The environmental effect of agricultural agglomeration is more complicated than that of other industries, but there is a deficiency of the research on it. This study calculated the level of agricultural agglomeration and the emissions of agricultural non-point pollutants in Chinese prefecture-level cities by using the panel data of these cities on the basis of the theoretical analysis. Then we investigated the spatial and temporal characteristics of agricultural agglomeration and agricultural non-point source pollution and the threshold effect of agricultural agglomeration level on agricultural non-point source pollution based on GIS spatial analysis and econometric model. The main conclusions can be drawn as follows: (1) Agricultural agglomeration and agricultural non-point source pollution of COD, TN and TP show different characteristics in temporal variation, spatial distribution, spatial correlation and spatial trends. (2) Agricultural agglomeration has single threshold effect on COD, TN and TP pollution, and positive correlation with them. When the level of agricultural agglomeration is below the threshold value, it contributes to agricultural pollution significantly, and as the level of agglomeration becomes higher than the threshold value, the situation of rapid pollution will be mitigated. (3) The change from agricultural agglomeration to emissions of three agricultural non-point source pollutants develops in two stages. This change depends on the intensification and restriction of the scale effect, structure effect, technical effect, social effect and cumulative effect on the emissions of agricultural non-point source pollution produced by agricultural agglomeration and it is reflected in the concrete agricultural production behavior. With the increase of agricultural agglomeration, the effect of each effect is obvious and the level of pollution increases significantly, however, the inhibition ability of pollution emission is improved and the external effect of negative environment is weakened at the stage of crossing the threshold. (4) The agricultural economic level and agricultural production conditions aggravate the COD, TN and TP agricultural non-point source pollution to some extent; the structure of animal husbandry industry and environmental regulation have a positive correlation with COD and TP agricultural non-point source pollution; the improvement of producer quality can affect farmers' production behavior and improve the agricultural environment. (5) The effect of agricultural agglomeration on pollution reduction of COD agricultural non-point source pollution is weak and COD agricultural non-point source pollution is more serious and mainly from animal husbandry.
    Qingqing DENG, Erling LI, Shixin REN. Impact of agricultural agglomeration on agricultural non-point source pollution: Evidences from the threshold effect based on the panel data of prefecture-level cities in China[J]. Geographical Research, 2020, 39(4): 970
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