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Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China

In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural n...

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Autores principales: Li, Yan, Zhou, Shenglu, Jia, Zhenyi, Ge, Liang, Mei, Liping, Sui, Xueyan, Wang, Xiaorui, Li, Baojie, Wang, Junxiao, Wu, Shaohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313624/
https://www.ncbi.nlm.nih.gov/pubmed/30477150
http://dx.doi.org/10.3390/ijerph15122628
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author Li, Yan
Zhou, Shenglu
Jia, Zhenyi
Ge, Liang
Mei, Liping
Sui, Xueyan
Wang, Xiaorui
Li, Baojie
Wang, Junxiao
Wu, Shaohua
author_facet Li, Yan
Zhou, Shenglu
Jia, Zhenyi
Ge, Liang
Mei, Liping
Sui, Xueyan
Wang, Xiaorui
Li, Baojie
Wang, Junxiao
Wu, Shaohua
author_sort Li, Yan
collection PubMed
description In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural network (BRBPNN) to analyze the typical pollutants (i.e., cadmium (Cd) and benzopyrene (BaP)) for Taihu Lake, a typical Chinese freshwater lake. For the periods 1950–2003 and 1950–2015, the neural network model estimated the BaP concentration for the database with Nash-Sutcliffe model efficiency (NS) = 0.99 and 0.99 and root-mean-square error (RMSE) = 3.1 and 9.3 for the total database and the Cd concentration for the database with NS = 0.93 and 0.98 and RMSE = 45.4 and 65.7 for the total database, respectively. In the model of extensive economic development, the concentration of pollutants in the sediments of Taihu reached the maximum value at the end of the twentieth century and early twenty-first century, and there was an inflection point. After the early twenty-first century, the concentration of pollutants was controlled under various environmental policies and measures. In 2015, the environmental protection ratio of Cd and BaP reached 52% and 89%, respectively. Without environmental protection measures, the concentrations of Cd and BaP obtained from the neural network model is projected to reach 2015.5 μg kg(−1) and 407.8 ng g(−1), respectively, in 2030. Based on the results of this study, the Chinese government will need to invest more money and energy to clean up the environment.
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spelling pubmed-63136242019-06-17 Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China Li, Yan Zhou, Shenglu Jia, Zhenyi Ge, Liang Mei, Liping Sui, Xueyan Wang, Xiaorui Li, Baojie Wang, Junxiao Wu, Shaohua Int J Environ Res Public Health Article In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural network (BRBPNN) to analyze the typical pollutants (i.e., cadmium (Cd) and benzopyrene (BaP)) for Taihu Lake, a typical Chinese freshwater lake. For the periods 1950–2003 and 1950–2015, the neural network model estimated the BaP concentration for the database with Nash-Sutcliffe model efficiency (NS) = 0.99 and 0.99 and root-mean-square error (RMSE) = 3.1 and 9.3 for the total database and the Cd concentration for the database with NS = 0.93 and 0.98 and RMSE = 45.4 and 65.7 for the total database, respectively. In the model of extensive economic development, the concentration of pollutants in the sediments of Taihu reached the maximum value at the end of the twentieth century and early twenty-first century, and there was an inflection point. After the early twenty-first century, the concentration of pollutants was controlled under various environmental policies and measures. In 2015, the environmental protection ratio of Cd and BaP reached 52% and 89%, respectively. Without environmental protection measures, the concentrations of Cd and BaP obtained from the neural network model is projected to reach 2015.5 μg kg(−1) and 407.8 ng g(−1), respectively, in 2030. Based on the results of this study, the Chinese government will need to invest more money and energy to clean up the environment. MDPI 2018-11-23 2018-12 /pmc/articles/PMC6313624/ /pubmed/30477150 http://dx.doi.org/10.3390/ijerph15122628 Text en © 2018 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
Li, Yan
Zhou, Shenglu
Jia, Zhenyi
Ge, Liang
Mei, Liping
Sui, Xueyan
Wang, Xiaorui
Li, Baojie
Wang, Junxiao
Wu, Shaohua
Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title_full Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title_fullStr Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title_full_unstemmed Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title_short Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China
title_sort influence of industrialization and environmental protection on environmental pollution: a case study of taihu lake, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313624/
https://www.ncbi.nlm.nih.gov/pubmed/30477150
http://dx.doi.org/10.3390/ijerph15122628
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