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A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers
It’s vital to explore critical indicators when identifying potential pollution sources of urban rivers. However, the variations of urban river water qualities following temporal and spatial disturbances were highly local-dependent, further complicating the understanding of pollution emission laws. I...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062557/ https://www.ncbi.nlm.nih.gov/pubmed/33888742 http://dx.doi.org/10.1038/s41598-021-87671-4 |
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author | Yang, Sihang Liang, Manchun Qin, Zesheng Qian, Yiwu Li, Mei Cao, Yi |
author_facet | Yang, Sihang Liang, Manchun Qin, Zesheng Qian, Yiwu Li, Mei Cao, Yi |
author_sort | Yang, Sihang |
collection | PubMed |
description | It’s vital to explore critical indicators when identifying potential pollution sources of urban rivers. However, the variations of urban river water qualities following temporal and spatial disturbances were highly local-dependent, further complicating the understanding of pollution emission laws. In order to understand the successional trajectory of water qualities of urban rivers and the underlying mechanisms controlling these dynamics at local scale, we collected daily monitoring data for 17 physical and chemical parameters from seven on-line monitoring stations in Nanfeihe River, Anhui, China, during the year 2018. The water quality at tributaries were similar, while that at main river was much different. A seasonal ‘’turning-back” pattern was observed in the water quality, which changed significantly from spring to summer but finally changed back in winter. This result was possibly regulated by seasonally-changed dissolved oxygen and water temperature. Linear mixed models showed that the site 2, with the highest loads of pollution, contributed the highest (β = 0.316, P < 0.001) to the main river City Water Quality Index (CWQI) index, but site 5, the geographically nearest site to main river monitoring station, did not show significant effect. In contrast, site 5 but not site 2 contributed the highest (β = 0.379, P < 0.001) to the main river water quality. Therefore, CWQI index was a better index than water quality to identify potential pollution sources with heavy loads of pollutants, despite temporal and spatial disturbances at local scales. These results highlight the role of aeration in water quality controlling of urban rivers, and emphasized the necessity to select proper index to accurately trace the latent pollution sources. |
format | Online Article Text |
id | pubmed-8062557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80625572021-04-23 A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers Yang, Sihang Liang, Manchun Qin, Zesheng Qian, Yiwu Li, Mei Cao, Yi Sci Rep Article It’s vital to explore critical indicators when identifying potential pollution sources of urban rivers. However, the variations of urban river water qualities following temporal and spatial disturbances were highly local-dependent, further complicating the understanding of pollution emission laws. In order to understand the successional trajectory of water qualities of urban rivers and the underlying mechanisms controlling these dynamics at local scale, we collected daily monitoring data for 17 physical and chemical parameters from seven on-line monitoring stations in Nanfeihe River, Anhui, China, during the year 2018. The water quality at tributaries were similar, while that at main river was much different. A seasonal ‘’turning-back” pattern was observed in the water quality, which changed significantly from spring to summer but finally changed back in winter. This result was possibly regulated by seasonally-changed dissolved oxygen and water temperature. Linear mixed models showed that the site 2, with the highest loads of pollution, contributed the highest (β = 0.316, P < 0.001) to the main river City Water Quality Index (CWQI) index, but site 5, the geographically nearest site to main river monitoring station, did not show significant effect. In contrast, site 5 but not site 2 contributed the highest (β = 0.379, P < 0.001) to the main river water quality. Therefore, CWQI index was a better index than water quality to identify potential pollution sources with heavy loads of pollutants, despite temporal and spatial disturbances at local scales. These results highlight the role of aeration in water quality controlling of urban rivers, and emphasized the necessity to select proper index to accurately trace the latent pollution sources. Nature Publishing Group UK 2021-04-22 /pmc/articles/PMC8062557/ /pubmed/33888742 http://dx.doi.org/10.1038/s41598-021-87671-4 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 Yang, Sihang Liang, Manchun Qin, Zesheng Qian, Yiwu Li, Mei Cao, Yi A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title | A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title_full | A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title_fullStr | A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title_full_unstemmed | A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title_short | A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
title_sort | novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062557/ https://www.ncbi.nlm.nih.gov/pubmed/33888742 http://dx.doi.org/10.1038/s41598-021-87671-4 |
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