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基于产业集聚与减排效应互动视角的区域金属类企业污染减排行为模拟

Simulation of the pollution abatement behavior of regional metal-related enterprises based on the interactive perspective of industrial agglomerations and emission reduction effects.

机构信息

Business School, Central South University of Forestry and Technology of China, Changsha, 410004, China.

Laboratoire Genie Civil et geo-Environnement, Universite de Lille, 59655, Lille, France.

出版信息

Environ Geochem Health. 2022 Mar;44(3):1081-1098. doi: 10.1007/s10653-021-01015-9. Epub 2021 Jun 25.

Abstract

A machine learning method was used to process a multiagent information database to study the spatial distribution characteristics of agglomerations of metal-related enterprises and to analyze the spatial and temporal differentiation characteristics of pollution reduction in metal-related enterprises. Based on the spatial distribution of enterprises and a simulation of their pollution reduction behaviors, the layout of 380 enterprises sample is optimized, and the direction of industrial transfer is planned to give full play to the pollution reduction effect of enterprise agglomeration. The results showed that (1) the metal-related enterprises in the Chang-Zhu-Tan urban agglomeration have obvious spatial heterogeneity and are mainly distributed in the district of Changsha, the Qingshuitang Industrial Zone, Liling city and the Qibaoshan Industrial Zone of Liuyang city, while the metal-related enterprises in Shaoshan city, Zhuzhou County and Liling city are scattered. (2) The pollution emission behaviors of enterprises differ in time and space, and the pollution concentrations are highest in industrial parks such as Qingshuitang and Zhubu Port. (3) There is an interactive relationship between the degree of enterprise agglomeration and the pollution reduction effect. The spatial positive coupling degree between the concentration of metal-related enterprises and the degree of metal-related pollution is significant, accounting for 94.96% of the study area. Low pollution-high agglomeration areas, high pollution-low agglomeration areas, high pollution-high agglomeration areas, and low pollution-low agglomeration area account for 1.01%, 4.03%, 2.87%, and 92.09% of the study area, respectively. Finally, based on the new development concept of dual circulation and the theory of a two-oriented society in the new era, the paper puts forward suggestions and policies for the sustainable development of industrial transfer.

摘要

采用机器学习方法处理多主体信息数据库,研究金属相关企业集聚的空间分布特征,并分析金属相关企业减排的时空分异特征。基于企业的空间分布和对其减排行为的模拟,对 380 家企业样本进行布局优化,规划产业转移方向,充分发挥企业集聚的减排效果。结果表明:(1)长株潭城市群的金属相关企业具有明显的空间异质性,主要分布在长沙市的区、清水塘工业区、醴陵市和浏阳市的七宝山工业区,而韶山市、株洲县和醴陵市的金属相关企业则较为分散。(2)企业的污染排放行为在时间和空间上存在差异,且工业园区如清水塘和株埠港的污染浓度最高。(3)企业集聚程度与减排效果之间存在交互关系。金属相关企业的浓度与金属相关污染程度之间的空间正耦合度显著,占研究区的 94.96%。低污染-高集聚区、高污染-低集聚区、高污染-高集聚区和低污染-低集聚区分别占研究区的 1.01%、4.03%、2.87%和 92.09%。最后,根据双循环新发展理念和新时代两型社会理论,提出了产业转移可持续发展的建议和政策。

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