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Optimizing entropy weight model to accurately predict variation of pharmaceuticals and personal care products in the estuaries and coasts of the South China.
Xie, Yuxin; Diao, Jieyi; Meng, Jing; Wang, Jianwen; Zhang, Jiaer; Zhang, Jingru; Zhang, Lulu; Leung, Jonathan Y S; Bi, Ran; Liu, Wenhua; Wang, Tieyu.
Affiliation
  • Xie Y; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Diao J; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Meng J; Key Laboratory of Environment Nanotechnology and Health Effects, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100084, China.
  • Wang J; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Zhang J; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Zhang J; Laboratory of New Pollutants Risk Assessment & Control, Guangdong Provincial Academic of Environmental Science, Guangzhou 510045, China.
  • Zhang L; Laboratory of New Pollutants Risk Assessment & Control, Guangdong Provincial Academic of Environmental Science, Guangzhou 510045, China.
  • Leung JYS; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Bi R; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Liu W; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China.
  • Wang T; Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Protection, Shantou University, Shantou 515063, China; Institute of Marine Sciences, Shantou University, Shantou 515063, China. Electronic address: wangt@stu.edu.cn.
Mar Pollut Bull ; 207: 116825, 2024 Oct.
Article in En | MEDLINE | ID: mdl-39142051
ABSTRACT
Pharmaceuticals and personal care products (PPCPs) have raised increasing concern worldwide due to their continuous release and potential hazards to the ecosystem and human health. This study optimized the entropy weight model (EW-WRSR) that combines entropy weight with multi-criteria decision analysis to investigate pollution patterns of PPCPs in the coasts and estuaries. The results revealed that occurrences of PPCPs from the 1940s to the present were consistent with using PPCPs, different types of human activities, and local urban development. This helped better understand the history of PPCP contamination and evaluate the uncertainty of EW-WRSR. The model predicted hotspots of PPCPs that were consistent with the actual situation, indicating that PPCPs mainly enter the nearshore ecosystem by the form of sewage discharge and residual aquaculture. This study can provide method that identifying highly contaminated regions on a global scale.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Pollutants, Chemical / Environmental Monitoring / Estuaries / Entropy / Cosmetics Country/Region as subject: Asia Language: En Journal: Mar Pollut Bull Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Water Pollutants, Chemical / Environmental Monitoring / Estuaries / Entropy / Cosmetics Country/Region as subject: Asia Language: En Journal: Mar Pollut Bull Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom