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Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index
Coal dust is the main pollutant in coal mining areas. Such pollutants easily diffuse and are difficult to monitor, which increases the cost of environmental pollution control. Remote sensing technology can be used to dynamically monitor mining areas at a low cost, and thus, this is a common means of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992999/ https://www.ncbi.nlm.nih.gov/pubmed/35395022 http://dx.doi.org/10.1371/journal.pone.0266517 |
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author | Xia, Nan Hai, Wenyue Song, Gimei Tang, Mengying |
author_facet | Xia, Nan Hai, Wenyue Song, Gimei Tang, Mengying |
author_sort | Xia, Nan |
collection | PubMed |
description | Coal dust is the main pollutant in coal mining areas. Such pollutants easily diffuse and are difficult to monitor, which increases the cost of environmental pollution control. Remote sensing technology can be used to dynamically monitor mining areas at a low cost, and thus, this is a common means of mining area management. According to the spectral characteristics of various ground objects in remote sensing images, a variety of remote sensing indexes can be constructed to extract the required information. In this study, the Wucaiwan open-pit coal mine was selected as the study area, and the Enhanced Coal Dust Index (ECDI) was established to extract the coal dust pollution information for the mining area. A new mining area pollution monitoring method was developed, which can provide technical support for environmental treatment and mining planning in Zhundong. The results of this study revealed the following: (1) Compared with the normalized difference coal index, the ECDI can expand the difference between the spectral information about the coal dust and the surrounding features, so it has a significant recognition ability for coal dust information. (2) From 2010 to 2021, the coal dust pollution in the study area initially increased and then decreased. With the continued exploitation of the coal mines in the study area, the coal dust pollution area increased from 14.77 km(2) in 2010 to 69.49 km(2) in 2014. After 2014, the local government issued various environmental pollution control policies, which had remarkable results. The coal dust pollution area decreased to 36.85 km(2) and 17.85 km(2) in 2018 and 2021, respectively. (3) There was a great deal of pollution around mines and roads, around which the pollution was more serious. Various factors, such as wind, coal type, and the mining, processing, and transportation modes, affect the distribution of the coal dust pollution. |
format | Online Article Text |
id | pubmed-8992999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89929992022-04-09 Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index Xia, Nan Hai, Wenyue Song, Gimei Tang, Mengying PLoS One Research Article Coal dust is the main pollutant in coal mining areas. Such pollutants easily diffuse and are difficult to monitor, which increases the cost of environmental pollution control. Remote sensing technology can be used to dynamically monitor mining areas at a low cost, and thus, this is a common means of mining area management. According to the spectral characteristics of various ground objects in remote sensing images, a variety of remote sensing indexes can be constructed to extract the required information. In this study, the Wucaiwan open-pit coal mine was selected as the study area, and the Enhanced Coal Dust Index (ECDI) was established to extract the coal dust pollution information for the mining area. A new mining area pollution monitoring method was developed, which can provide technical support for environmental treatment and mining planning in Zhundong. The results of this study revealed the following: (1) Compared with the normalized difference coal index, the ECDI can expand the difference between the spectral information about the coal dust and the surrounding features, so it has a significant recognition ability for coal dust information. (2) From 2010 to 2021, the coal dust pollution in the study area initially increased and then decreased. With the continued exploitation of the coal mines in the study area, the coal dust pollution area increased from 14.77 km(2) in 2010 to 69.49 km(2) in 2014. After 2014, the local government issued various environmental pollution control policies, which had remarkable results. The coal dust pollution area decreased to 36.85 km(2) and 17.85 km(2) in 2018 and 2021, respectively. (3) There was a great deal of pollution around mines and roads, around which the pollution was more serious. Various factors, such as wind, coal type, and the mining, processing, and transportation modes, affect the distribution of the coal dust pollution. Public Library of Science 2022-04-08 /pmc/articles/PMC8992999/ /pubmed/35395022 http://dx.doi.org/10.1371/journal.pone.0266517 Text en © 2022 Xia et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Xia, Nan Hai, Wenyue Song, Gimei Tang, Mengying Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title | Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title_full | Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title_fullStr | Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title_full_unstemmed | Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title_short | Identification and monitoring of coal dust pollution in Wucaiwan mining area, Xinjiang (China) using Landsat derived enhanced coal dust index |
title_sort | identification and monitoring of coal dust pollution in wucaiwan mining area, xinjiang (china) using landsat derived enhanced coal dust index |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992999/ https://www.ncbi.nlm.nih.gov/pubmed/35395022 http://dx.doi.org/10.1371/journal.pone.0266517 |
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