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Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications.
Wang, Luqi; Liu, Dongsheng; Sun, Yifan; Zhang, Yinsheng; Chen, Wei; Yuan, Yi; Hu, Shengchao; Li, Sen.
Affiliation
  • Wang L; Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China.
  • Liu D; Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China.
  • Sun Y; Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China.
  • Zhang Y; Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China; School of Artificial Intelligence and Automation, Huazhong University of Sc
  • Chen W; Yangtze Clean Energy Conservation and Environmental Protection Co., Ltd, Shanghai 201718, PR China.
  • Yuan Y; Yangtze Clean Energy Conservation and Environmental Protection Co., Ltd, Shanghai 201718, PR China.
  • Hu S; Research Center for Environmental Ecology and Engineering, School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, PR China. Electronic address: hushengcao@126.com.
  • Li S; Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin, School of Environmental Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, China. Electronic address: senli@hust.edu.cn.
Ecotoxicol Environ Saf ; 283: 116815, 2024 Aug 01.
Article in En | MEDLINE | ID: mdl-39094459
ABSTRACT
Sediments are important heavy metal sinks in lakes, crucial for ensuring water environment safety. Existing studies mainly focused on well-studied lakes, leaving gaps in understanding pollution patterns in specific basins and influencing factors.We compiled comprehensive sediment contamination data from literature and public datasets, including hydro-geomorphological, climatic, soil, landscape, and anthropogenic factors. Using advanced machine learning, we analyzed typical pollution factors to infer potential sources and migration pathways of pollutants and predicted pollution levels in basins with limited data availability. Our analysis of pollutant distribution data revealed that Cd had the most extensive pollution range, with the most severe pollution occurring in the Huaihe and Yangtze River basins. Furthermore, we identified distinct groups of driving factors influencing various heavy metals. Cd, Cr, and Pb were primarily influenced by human activities, while Cu and Ni were affected by both anthropogenic and natural factors, and Zn tended more towards natural sources. Our predictions indicated that, in addition to the typical highly polluted areas, the potential risk of Cd, Cu and Ni is higher in Xinjiang, and in Tibet and Qinghai, the potential risk of Cd, Cr, Cu and Ni is higher. Pb and Zn presented lower risks, except in the Huaihe and Yangtze River Basins. Temperature, wind, precipitation, precipitation rate, and the cation exchange capacity of soil significantly impacted the predictions of heavy metal pollution in sediments, suggesting that particulate migration, rainfall runoff, and soil erosion are likely the main pathways for pollutant migration into sediments. Considering the migration, pathways, and sources of pollutants, we propose strategies such as low-impact development and promoting sustainable transportation to mitigate pollution. This study provides the latest insights into heavy metal pollution in Chinese lake sediments, offering references for policy-making and water resource management.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Ecotoxicol Environ Saf Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Ecotoxicol Environ Saf Year: 2024 Document type: Article