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Eco-environmental assessment model of the mining area in Gongyi, China

The ecological environment directly affects human life. One of the ecological environmental issues that China is presently facing is deterioration of the ecological environment due to mining. The pollution produced by mining causes the destruction of land, water bodies, the atmosphere, and vegetatio...

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Autores principales: Wang, Ying, Wu, Xueling, He, Siyuan, Niu, Ruiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413286/
https://www.ncbi.nlm.nih.gov/pubmed/34475428
http://dx.doi.org/10.1038/s41598-021-96625-9
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author Wang, Ying
Wu, Xueling
He, Siyuan
Niu, Ruiqing
author_facet Wang, Ying
Wu, Xueling
He, Siyuan
Niu, Ruiqing
author_sort Wang, Ying
collection PubMed
description The ecological environment directly affects human life. One of the ecological environmental issues that China is presently facing is deterioration of the ecological environment due to mining. The pollution produced by mining causes the destruction of land, water bodies, the atmosphere, and vegetation resources and new geological problems that seriously impact human civilization and life. The main purpose of this study is to present an environmental assessment model of mine pollution to evaluate the eco-environment of mining. This study added mineral species and mining types into the factor layers and built an improved evaluation system to accurately evaluate the impact of mines on the eco-environment. In the non-mining area, the grades of the eco-environment were divided according to the Technical Criterion for Ecosystem Status Evaluation standard document. In the mining area, the grades of the assessment for the eco-environment were classified by a field survey. After comparing the accuracy of various methods, the support vector machine (SVM) model, with an accuracy of 94.8%, was chosen for the mining area, and the classification and regression tree (CART) model, with an accuracy of 89.36%, was chosen for the non-mining area. Finally, environmental assessment maps for the entire study area were generated. The results indicate that the mine environmental assessment system established by this study avoids the subjective limitations of traditional assessment methods, provides an effective method for assessing ecological quality, and will help relevant departments to plan for mine resources.
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spelling pubmed-84132862021-09-03 Eco-environmental assessment model of the mining area in Gongyi, China Wang, Ying Wu, Xueling He, Siyuan Niu, Ruiqing Sci Rep Article The ecological environment directly affects human life. One of the ecological environmental issues that China is presently facing is deterioration of the ecological environment due to mining. The pollution produced by mining causes the destruction of land, water bodies, the atmosphere, and vegetation resources and new geological problems that seriously impact human civilization and life. The main purpose of this study is to present an environmental assessment model of mine pollution to evaluate the eco-environment of mining. This study added mineral species and mining types into the factor layers and built an improved evaluation system to accurately evaluate the impact of mines on the eco-environment. In the non-mining area, the grades of the eco-environment were divided according to the Technical Criterion for Ecosystem Status Evaluation standard document. In the mining area, the grades of the assessment for the eco-environment were classified by a field survey. After comparing the accuracy of various methods, the support vector machine (SVM) model, with an accuracy of 94.8%, was chosen for the mining area, and the classification and regression tree (CART) model, with an accuracy of 89.36%, was chosen for the non-mining area. Finally, environmental assessment maps for the entire study area were generated. The results indicate that the mine environmental assessment system established by this study avoids the subjective limitations of traditional assessment methods, provides an effective method for assessing ecological quality, and will help relevant departments to plan for mine resources. Nature Publishing Group UK 2021-09-02 /pmc/articles/PMC8413286/ /pubmed/34475428 http://dx.doi.org/10.1038/s41598-021-96625-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Ying
Wu, Xueling
He, Siyuan
Niu, Ruiqing
Eco-environmental assessment model of the mining area in Gongyi, China
title Eco-environmental assessment model of the mining area in Gongyi, China
title_full Eco-environmental assessment model of the mining area in Gongyi, China
title_fullStr Eco-environmental assessment model of the mining area in Gongyi, China
title_full_unstemmed Eco-environmental assessment model of the mining area in Gongyi, China
title_short Eco-environmental assessment model of the mining area in Gongyi, China
title_sort eco-environmental assessment model of the mining area in gongyi, china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413286/
https://www.ncbi.nlm.nih.gov/pubmed/34475428
http://dx.doi.org/10.1038/s41598-021-96625-9
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