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Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models

Pollutant source apportionment is of great significance for water environmental protection. However, it is still challenging to accurately quantify pollutant loads at basin-scale. Refined analytical methods combined the pollution discharge coefficient method (PDCM), field observation, and numerical...

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Autores principales: Zhang, Man, Chen, Xiaolong, Yang, Shuihua, Song, Zhen, Wang, Yonggui, Yu, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656782/
https://www.ncbi.nlm.nih.gov/pubmed/34886207
http://dx.doi.org/10.3390/ijerph182312481
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author Zhang, Man
Chen, Xiaolong
Yang, Shuihua
Song, Zhen
Wang, Yonggui
Yu, Qing
author_facet Zhang, Man
Chen, Xiaolong
Yang, Shuihua
Song, Zhen
Wang, Yonggui
Yu, Qing
author_sort Zhang, Man
collection PubMed
description Pollutant source apportionment is of great significance for water environmental protection. However, it is still challenging to accurately quantify pollutant loads at basin-scale. Refined analytical methods combined the pollution discharge coefficient method (PDCM), field observation, and numerical model (Soil & Water Assessment Tool, SWAT) to make quantitative source appointment in the Tuojiang River, a key tributary of the upper Yangtze River. The chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (N-NH4(+)) were analyzed. Results showed that the urban sewage treatment plant point source has the largest contribution to COD, TN, and N-NH4(+), while TP is mostly from the agricultural sources throughout the year. The total inflowing loads of pollution sources are significantly affected by rainfall. The overall pollution characteristics showed that pollutant loads present in different seasons are as follows: wet season > normal season > dry season. The month with the highest levels of pollutants is July in the wet season. Among the nine cities, the city that contributes the most COD, TN and N-NH4(+), is Neijiang, accounting for about 25%, and the city that contributes the most TP is Deyang, accounting for 23%. Among the sub-basins, the Fuxi River subbasin and Qiuxihe River subbasin contribute the most pollutant loads. The technical framework adopted in this paper can be used to accurately identify the types, administrative regions and sub-basins of the main pollution sources in the watershed, which is conducive to management and governance of the environment.
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spelling pubmed-86567822021-12-10 Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models Zhang, Man Chen, Xiaolong Yang, Shuihua Song, Zhen Wang, Yonggui Yu, Qing Int J Environ Res Public Health Article Pollutant source apportionment is of great significance for water environmental protection. However, it is still challenging to accurately quantify pollutant loads at basin-scale. Refined analytical methods combined the pollution discharge coefficient method (PDCM), field observation, and numerical model (Soil & Water Assessment Tool, SWAT) to make quantitative source appointment in the Tuojiang River, a key tributary of the upper Yangtze River. The chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (N-NH4(+)) were analyzed. Results showed that the urban sewage treatment plant point source has the largest contribution to COD, TN, and N-NH4(+), while TP is mostly from the agricultural sources throughout the year. The total inflowing loads of pollution sources are significantly affected by rainfall. The overall pollution characteristics showed that pollutant loads present in different seasons are as follows: wet season > normal season > dry season. The month with the highest levels of pollutants is July in the wet season. Among the nine cities, the city that contributes the most COD, TN and N-NH4(+), is Neijiang, accounting for about 25%, and the city that contributes the most TP is Deyang, accounting for 23%. Among the sub-basins, the Fuxi River subbasin and Qiuxihe River subbasin contribute the most pollutant loads. The technical framework adopted in this paper can be used to accurately identify the types, administrative regions and sub-basins of the main pollution sources in the watershed, which is conducive to management and governance of the environment. MDPI 2021-11-26 /pmc/articles/PMC8656782/ /pubmed/34886207 http://dx.doi.org/10.3390/ijerph182312481 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Man
Chen, Xiaolong
Yang, Shuihua
Song, Zhen
Wang, Yonggui
Yu, Qing
Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title_full Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title_fullStr Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title_full_unstemmed Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title_short Basin-Scale Pollution Loads Analyzed Based on Coupled Empirical Models and Numerical Models
title_sort basin-scale pollution loads analyzed based on coupled empirical models and numerical models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656782/
https://www.ncbi.nlm.nih.gov/pubmed/34886207
http://dx.doi.org/10.3390/ijerph182312481
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