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Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China
The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense “water network” over rivers and lakes...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966530/ https://www.ncbi.nlm.nih.gov/pubmed/36851044 http://dx.doi.org/10.3390/toxics11020169 |
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author | Zhu, Yan Bai, Yongqing Xiong, Jie Zhao, Tianliang Xu, Jiaping Zhou, Yue Meng, Kai Meng, Chengzhen Sun, Xiaoyun Hu, Weiyang |
author_facet | Zhu, Yan Bai, Yongqing Xiong, Jie Zhao, Tianliang Xu, Jiaping Zhou, Yue Meng, Kai Meng, Chengzhen Sun, Xiaoyun Hu, Weiyang |
author_sort | Zhu, Yan |
collection | PubMed |
description | The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense “water network” over rivers and lakes. In this study, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to simulate the impact of this dense “water network” on a wintertime heavy PM(2.5) pollution event in the THB. On this basis, the regulating effects of density and area of the lake groups, with centralized big lakes (CBLs) and discrete small lakes (DSLs), on PM(2.5) concentrations over the underlying surface of the dense “water network” in the THB were clarified, and the relative contributions of thermal factors and water vapor factors in the atmospheric boundary layer to the variation of PM(2.5) concentrations were evaluated. The results show that the underlying surface of dense “water networks” in the THB generally decreases the PM(2.5) concentrations, but the influences of different lake-group types are not uniform in spatial distribution. The CBLs can reduce the PM(2.5) concentrations over the lake and its surroundings by 4.90–17.68% during the day and night. The ability of DSLs in reducing PM(2.5) pollution is relatively weak, with the reversed contribution between −5.63% and 1.56%. Thermal factors and water vapor–related factors are the key meteorological drivers affecting the variation of PM(2.5) concentrations over the underlying surface of dense “water networks”. The warming and humidification effects of such underlying surfaces contribute positively and negatively to the “purification” of air pollution, respectively. The relative contributions of thermal factors and water vapor–related factors are 52.48% and 43.91% for CBLs and 65.96% and 27.31% for DSLs, respectively. The “purification” effect of the underlying surface with a dense “water network” in the THB on regional air pollution highlights the importance of environmental protection of inland rivers and lakes in regional environmental governance. In further studies on the atmospheric environment, long-term studies are necessary, including fine measurements in terms of meteorology and the environment and more comprehensive simulations under different scenarios. |
format | Online Article Text |
id | pubmed-9966530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99665302023-02-26 Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China Zhu, Yan Bai, Yongqing Xiong, Jie Zhao, Tianliang Xu, Jiaping Zhou, Yue Meng, Kai Meng, Chengzhen Sun, Xiaoyun Hu, Weiyang Toxics Article The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense “water network” over rivers and lakes. In this study, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to simulate the impact of this dense “water network” on a wintertime heavy PM(2.5) pollution event in the THB. On this basis, the regulating effects of density and area of the lake groups, with centralized big lakes (CBLs) and discrete small lakes (DSLs), on PM(2.5) concentrations over the underlying surface of the dense “water network” in the THB were clarified, and the relative contributions of thermal factors and water vapor factors in the atmospheric boundary layer to the variation of PM(2.5) concentrations were evaluated. The results show that the underlying surface of dense “water networks” in the THB generally decreases the PM(2.5) concentrations, but the influences of different lake-group types are not uniform in spatial distribution. The CBLs can reduce the PM(2.5) concentrations over the lake and its surroundings by 4.90–17.68% during the day and night. The ability of DSLs in reducing PM(2.5) pollution is relatively weak, with the reversed contribution between −5.63% and 1.56%. Thermal factors and water vapor–related factors are the key meteorological drivers affecting the variation of PM(2.5) concentrations over the underlying surface of dense “water networks”. The warming and humidification effects of such underlying surfaces contribute positively and negatively to the “purification” of air pollution, respectively. The relative contributions of thermal factors and water vapor–related factors are 52.48% and 43.91% for CBLs and 65.96% and 27.31% for DSLs, respectively. The “purification” effect of the underlying surface with a dense “water network” in the THB on regional air pollution highlights the importance of environmental protection of inland rivers and lakes in regional environmental governance. In further studies on the atmospheric environment, long-term studies are necessary, including fine measurements in terms of meteorology and the environment and more comprehensive simulations under different scenarios. MDPI 2023-02-10 /pmc/articles/PMC9966530/ /pubmed/36851044 http://dx.doi.org/10.3390/toxics11020169 Text en © 2023 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 Zhu, Yan Bai, Yongqing Xiong, Jie Zhao, Tianliang Xu, Jiaping Zhou, Yue Meng, Kai Meng, Chengzhen Sun, Xiaoyun Hu, Weiyang Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title | Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title_full | Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title_fullStr | Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title_full_unstemmed | Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title_short | Mitigation Effect of Dense “Water Network” on Heavy PM(2.5) Pollution: A Case Model of the Twain-Hu Basin, Central China |
title_sort | mitigation effect of dense “water network” on heavy pm(2.5) pollution: a case model of the twain-hu basin, central china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966530/ https://www.ncbi.nlm.nih.gov/pubmed/36851044 http://dx.doi.org/10.3390/toxics11020169 |
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