Evidence map›Paper›PMID 34170458›Full record

ArticleEnvironmental geochemistry and health2022

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

Li-Xin Xiong, Jia-Jun Ning, Yun-He Dong, Meng-Meng Dai

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Article in Environmental geochemistry and health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Li-Xin XiongBusiness School, Central South University of Forestry and Technology of China, Changsha, 410004, China. xionglixin@csu.edu.cn.ORCID http://orcid.org/0000-0003-2318-8301
Jia-Jun NingBusiness School, Central South University of Forestry and Technology of China, Changsha, 410004, China.
Yun-He DongBusiness School, Central South University of Forestry and Technology of China, Changsha, 410004, China.
Meng-Meng DaiBusiness School, Central South University of Forestry and Technology of China, Changsha, 410004, China.

Funding

National Natural Science Foundation of China 17CJY022
6 · The paper itself

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.

Indexed as

Environmental PollutionIndustryChinaCitiesMetalsSustainable DevelopmentMetalsMachine learning methodMetal pollutionMetal-related enterprise agglomerationWater pollution simulation

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