Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall
With the acceleration of urbanization, the diffusion mechanism of urban non-point source (NPS) pollution caused by extreme rainfall is not clear, which leads to high cost and difficulty in water environment treatment. In view of the shortcomings of dynamic diffusion simulations of mesoscale pollutio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Toxics |
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| Online Access: | https://www.mdpi.com/2305-6304/13/5/385 |
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| author | Ting Wen Chuanxun Li Jiawen Liu Peng Wang |
| author_facet | Ting Wen Chuanxun Li Jiawen Liu Peng Wang |
| author_sort | Ting Wen |
| collection | DOAJ |
| description | With the acceleration of urbanization, the diffusion mechanism of urban non-point source (NPS) pollution caused by extreme rainfall is not clear, which leads to high cost and difficulty in water environment treatment. In view of the shortcomings of dynamic diffusion simulations of mesoscale pollution, this paper proposes a simulation framework based on cellular automata, GIS geographic technology, and a two-dimensional shallow water model. Taking the 500 m × 500 m grid as the unit, we explore the migration laws of nitrogen and phosphorus pollutants and the response relationship between pollutant diffusion and land use under extreme rainfall scenarios. The results show that (i) the pollution risk increases significantly with diffusion, with the maximum pollution load in high-risk areas increasing by 181%, and the diffusion rate is positively correlated with the rate of change in rainfall intensity; (ii) forest land has the highest grid pollution load loss rate, whereas the water grid has the highest accumulation rate; (iii) this method can accurately identify the hot spots of pollution diffusion, providing a basis for the precise control of high-risk areas. This study can support the targeted governance of pollution sources and land planning optimization in urban storm and flood management, and help reduce environmental health risks in extreme climates. |
| format | Article |
| id | doaj-art-e44dbf2983574c769aed273ea558c202 |
| institution | DOAJ |
| issn | 2305-6304 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Toxics |
| spelling | doaj-art-e44dbf2983574c769aed273ea558c2022025-08-20T03:12:04ZengMDPI AGToxics2305-63042025-05-0113538510.3390/toxics13050385Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme RainfallTing Wen0Chuanxun Li1Jiawen Liu2Peng Wang3Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, ChinaFaculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, ChinaFaculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, ChinaFaculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, ChinaWith the acceleration of urbanization, the diffusion mechanism of urban non-point source (NPS) pollution caused by extreme rainfall is not clear, which leads to high cost and difficulty in water environment treatment. In view of the shortcomings of dynamic diffusion simulations of mesoscale pollution, this paper proposes a simulation framework based on cellular automata, GIS geographic technology, and a two-dimensional shallow water model. Taking the 500 m × 500 m grid as the unit, we explore the migration laws of nitrogen and phosphorus pollutants and the response relationship between pollutant diffusion and land use under extreme rainfall scenarios. The results show that (i) the pollution risk increases significantly with diffusion, with the maximum pollution load in high-risk areas increasing by 181%, and the diffusion rate is positively correlated with the rate of change in rainfall intensity; (ii) forest land has the highest grid pollution load loss rate, whereas the water grid has the highest accumulation rate; (iii) this method can accurately identify the hot spots of pollution diffusion, providing a basis for the precise control of high-risk areas. This study can support the targeted governance of pollution sources and land planning optimization in urban storm and flood management, and help reduce environmental health risks in extreme climates.https://www.mdpi.com/2305-6304/13/5/385cellular automataexport coefficient modelextreme rainfallland usenon-point source of pollutionrisk assessment |
| spellingShingle | Ting Wen Chuanxun Li Jiawen Liu Peng Wang Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall Toxics cellular automata export coefficient model extreme rainfall land use non-point source of pollution risk assessment |
| title | Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall |
| title_full | Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall |
| title_fullStr | Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall |
| title_full_unstemmed | Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall |
| title_short | Risk Assessment of Dynamic Diffusion of Urban Non-Point Source Pollution Under Extreme Rainfall |
| title_sort | risk assessment of dynamic diffusion of urban non point source pollution under extreme rainfall |
| topic | cellular automata export coefficient model extreme rainfall land use non-point source of pollution risk assessment |
| url | https://www.mdpi.com/2305-6304/13/5/385 |
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