Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model
Based on the extended Environmental Kuznets model (EKC) and the spatial econometric method, this paper analyzes the emission intensity data of water pollution of Chinese provinces and cities from 2004 to 2018 to identify the key factors that could result in water pollution by different periods of ti...
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2021-01-01
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doaj-7700ae343e9c49a8bf937f84734efce22021-09-21T15:16:07ZengEDP SciencesE3S Web of Conferences2267-12422021-01-012920304510.1051/e3sconf/202129203045e3sconf_netid21_03045Interpretation of Economic Growth and Water Pollution Intsity Based on EKC modelQiang LiJianmin Huang0Wenrui Wang1Xuerong Wang2Information Engineering College, Lanzhou University of Finance and EconomicsInformation Engineering College, Lanzhou University of Finance and EconomicsInformation Engineering College, Lanzhou University of Finance and EconomicsBased on the extended Environmental Kuznets model (EKC) and the spatial econometric method, this paper analyzes the emission intensity data of water pollution of Chinese provinces and cities from 2004 to 2018 to identify the key factors that could result in water pollution by different periods of time and by different regions as well as to initiate discussions over potential policies to be taken in the future. The results have two implications: on the one hand, water pollution is highly spatially correlated among different Chinese regions and the economic growth indicators such as GDP per capita and the number of lights show an inverted U-shaped nonlinear relationship with the intensity of water pollution emissions. As water pollution demonstrates both leakage effect and spillover effect, it is important to strengthen the implementation strategy featuring comprehensive planning and joint prevention and control. This paper also locates the performance of each region on the EKC curve. As demonstrated in the results, Shanghai, Beijing and Tianjin have become the first ones to manage to cross the inflection point and maintain at this level. Zhejiang, Jiangsu, Shandong and other eastern coastal areas are situated in the peak of the EKC curve, with enormous emission reduction pressure. Most of the provinces in the central region are located at the left side of the peak, and are suffering from serious water pollution resulted from rapid economic growth. Meanwhile, the intensity of water pollution in the western region of China is increasing rapidly. It is integral to seize the opportunity of supply-side reform to speed up the industrial restructuring, and try not to repeat the old lesson of treatment after pollution. In conclusion, it is suggested that governments at all levels should formulate and customize their policies based on their location on the EKC curve, so as to achieve positive dynamics between economic growth and water pollution control.https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/68/e3sconf_netid21_03045.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qiang Li Jianmin Huang Wenrui Wang Xuerong Wang |
spellingShingle |
Qiang Li Jianmin Huang Wenrui Wang Xuerong Wang Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model E3S Web of Conferences |
author_facet |
Qiang Li Jianmin Huang Wenrui Wang Xuerong Wang |
author_sort |
Qiang Li |
title |
Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model |
title_short |
Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model |
title_full |
Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model |
title_fullStr |
Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model |
title_full_unstemmed |
Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model |
title_sort |
interpretation of economic growth and water pollution intsity based on ekc model |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2021-01-01 |
description |
Based on the extended Environmental Kuznets model (EKC) and the spatial econometric method, this paper analyzes the emission intensity data of water pollution of Chinese provinces and cities from 2004 to 2018 to identify the key factors that could result in water pollution by different periods of time and by different regions as well as to initiate discussions over potential policies to be taken in the future. The results have two implications: on the one hand, water pollution is highly spatially correlated among different Chinese regions and the economic growth indicators such as GDP per capita and the number of lights show an inverted U-shaped nonlinear relationship with the intensity of water pollution emissions. As water pollution demonstrates both leakage effect and spillover effect, it is important to strengthen the implementation strategy featuring comprehensive planning and joint prevention and control. This paper also locates the performance of each region on the EKC curve. As demonstrated in the results, Shanghai, Beijing and Tianjin have become the first ones to manage to cross the inflection point and maintain at this level. Zhejiang, Jiangsu, Shandong and other eastern coastal areas are situated in the peak of the EKC curve, with enormous emission reduction pressure. Most of the provinces in the central region are located at the left side of the peak, and are suffering from serious water pollution resulted from rapid economic growth. Meanwhile, the intensity of water pollution in the western region of China is increasing rapidly. It is integral to seize the opportunity of supply-side reform to speed up the industrial restructuring, and try not to repeat the old lesson of treatment after pollution. In conclusion, it is suggested that governments at all levels should formulate and customize their policies based on their location on the EKC curve, so as to achieve positive dynamics between economic growth and water pollution control. |
url |
https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/68/e3sconf_netid21_03045.pdf |
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