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Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case
The River Chief Policy (RCP) is an innovative water resource management system in China aimed at managing water pollution and improving water quality. Though the RCP has been piloted in some river basins of China, few scholars have studied the effects of the policy. We built a differential game mode...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246944/ https://www.ncbi.nlm.nih.gov/pubmed/32365618 http://dx.doi.org/10.3390/ijerph17093103 |
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author | Xu, Xia Wu, Fengping Zhang, Lina Gao, Xin |
author_facet | Xu, Xia Wu, Fengping Zhang, Lina Gao, Xin |
author_sort | Xu, Xia |
collection | PubMed |
description | The River Chief Policy (RCP) is an innovative water resource management system in China aimed at managing water pollution and improving water quality. Though the RCP has been piloted in some river basins of China, few scholars have studied the effects of the policy. We built a differential game model under random interference factors to compare the water pollution in Chaohu Lake under the RCP and without the RCP, and we explored the conditions to ensure the effectiveness of the RCP. The results showed that: (1) The average effect of water pollution control under the RCP was greater than under non-RCP; (2) the higher the rewarding excellence and punishing inferiority coefficient ([Formula: see text]) was, the better the water pollution control effect under the RCP; (3) the greater the random interference coefficient ([Formula: see text]) and rewarding excellence and punishing inferiority coefficient ([Formula: see text]) were, the bigger the fluctuation of the water pollution control effect was; (4) when using the stochastic differential game, when [Formula: see text] , [Formula: see text] , or [Formula: see text] , [Formula: see text] , the RCP must be effective for water pollution control. Therefore, we can theoretically adjust the rewarding excellence and punishing inferiority coefficient ([Formula: see text]) and the random interference coefficient ([Formula: see text]) to ensure the effective implementation of the RCP and achieve the purpose of water pollution control. |
format | Online Article Text |
id | pubmed-7246944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72469442020-06-02 Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case Xu, Xia Wu, Fengping Zhang, Lina Gao, Xin Int J Environ Res Public Health Article The River Chief Policy (RCP) is an innovative water resource management system in China aimed at managing water pollution and improving water quality. Though the RCP has been piloted in some river basins of China, few scholars have studied the effects of the policy. We built a differential game model under random interference factors to compare the water pollution in Chaohu Lake under the RCP and without the RCP, and we explored the conditions to ensure the effectiveness of the RCP. The results showed that: (1) The average effect of water pollution control under the RCP was greater than under non-RCP; (2) the higher the rewarding excellence and punishing inferiority coefficient ([Formula: see text]) was, the better the water pollution control effect under the RCP; (3) the greater the random interference coefficient ([Formula: see text]) and rewarding excellence and punishing inferiority coefficient ([Formula: see text]) were, the bigger the fluctuation of the water pollution control effect was; (4) when using the stochastic differential game, when [Formula: see text] , [Formula: see text] , or [Formula: see text] , [Formula: see text] , the RCP must be effective for water pollution control. Therefore, we can theoretically adjust the rewarding excellence and punishing inferiority coefficient ([Formula: see text]) and the random interference coefficient ([Formula: see text]) to ensure the effective implementation of the RCP and achieve the purpose of water pollution control. MDPI 2020-04-29 2020-05 /pmc/articles/PMC7246944/ /pubmed/32365618 http://dx.doi.org/10.3390/ijerph17093103 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Xia Wu, Fengping Zhang, Lina Gao, Xin Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title | Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title_full | Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title_fullStr | Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title_full_unstemmed | Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title_short | Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case |
title_sort | assessing the effect of the chinese river chief policy for water pollution control under uncertainty—using chaohu lake as a case |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246944/ https://www.ncbi.nlm.nih.gov/pubmed/32365618 http://dx.doi.org/10.3390/ijerph17093103 |
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