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Priority screening on emerging contaminants in sediments of the Yangtze River, China

Environmental Sciences Europe 2024 12 citations

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Researchers developed a screening method to rank the 185 most concerning emerging chemical contaminants found in Yangtze River sediments, identifying 7 top-priority chemicals — including 5 pesticides and 2 per- and polyfluoroalkyl substances (PFAS, a class of highly persistent 'forever chemicals'). The framework provides a practical tool for river managers to focus pollution monitoring and regulatory action where it matters most.

Study Type Environmental

Abstract Background Screen the priority of emerging contaminants (ECs) from sediments is essential for risk assessment to aquatic environment and human health. Currently, priority approaches mainly focus on contaminant identification, exposure analysis, risk assessment, and hazard properties. However, there is still far from the reality due to, for instance, limitations on lack of occurrence data and uncertainty analysis. In this study, the multi-criteria screening method on the basis of hazard potential (HP) and exposure potential (EP) integrating with uncertainty analysis was developed for prioritization of 185 ECs, which have been reported to be widely found in the Yangtze River sediment. The HP based on the ecological risk and human health, and the EP according to the occurrence were both quantitatively analyzed. The priority index of these 185 chemicals was the product of the normalized HP and the normalized EP. Results According to the priority ranking scheme, 20 chemicals were identified as the top-priority, and 58 compounds as high-priority, respectively. After uncertainty scoring for each chemical based on data availability, there were 7 compounds (5 pesticides and 2 PFASs) recommended as the major priority ECs. In addition, the current study also emphasized that necessary for further studying some ECs, such as PFAS alternatives, as the data limitation may lead to reduce accurate prioritization. Conclusions Overall, this study provides an efficient approach for screening priority ECs, which is useful for river ecosystem health management.

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