A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers

Abstract 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 emissio...

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Autores principales:	Sihang Yang, Manchun Liang, Zesheng Qin, Yiwu Qian, Mei Li, Yi Cao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c9c55850e717419c8b11239801f6efc1
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spelling	oai:doaj.org-article:c9c55850e717419c8b11239801f6efc12021-12-02T17:32:58ZA novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers10.1038/s41598-021-87671-42045-2322https://doaj.org/article/c9c55850e717419c8b11239801f6efc12021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87671-4https://doaj.org/toc/2045-2322Abstract 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.Sihang YangManchun LiangZesheng QinYiwu QianMei LiYi CaoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sihang Yang Manchun Liang Zesheng Qin Yiwu Qian Mei Li Yi Cao A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers
description	Abstract 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	article
author	Sihang Yang Manchun Liang Zesheng Qin Yiwu Qian Mei Li Yi Cao
author_facet	Sihang Yang Manchun Liang Zesheng Qin Yiwu Qian Mei Li Yi Cao
author_sort	Sihang Yang
title	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_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_sort	novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c9c55850e717419c8b11239801f6efc1
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A novel assessment considering spatial and temporal variations of water quality to identify pollution sources in urban rivers

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