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  • 6491_Kong

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Freshwater shallow lake ecosystems provide valuable ecological services to human beings. However, these systems are subject to severe contamination from anthropogenic sources. Per- and polyfluoroalkyl substances (PFASs), including perfluorooctanoic acid (PFOA) and perfluorooctane sulphonate (PFOS), are among the contaminants that have received substantial attention, primarily due to abundant applications, environment persistence, and potential threats to ecological and human health. Understanding the environmental behavior of these contaminants in shallow freshwater lake environments using a modeling approach is therefore critical. Here, we characterize the fate, transport and transformation of both PFOA and PFOS in the fifth largest freshwater lake in China (Chaohu) during a two-year period (2013–2015) using a fugacity-based multimedia fate model. A reasonable agreement between the measured and modeled concentrations in various compartments confirms the model's reliability. The model successfully quantifies the environmental processes and identifies the major sources and input pathways of PFOA and PFOS to the Chaohu water body. Sensitivity analysis reveals the critical role of nonlinear Freundlich sorption, which contributes to a variable fraction of the model true uncertainty in different compartments (8.1%–93.6%). Through additional model scenario analyses, we further elucidate the importance of nonlinear Freundlich sorption that is essential for the reliable model performance. We also reveal the distinct composition of emission sources for the two contaminants, as the major sources are indirect soil volatilization and direct release from human activities for PFOA and PFOS, respectively. The present study is expected to provide implications for local management of PFASs pollution in Lake Chaohu and to contribute to developing a general model framework for the evaluation of PFASs in shallow lakes.
Original languageEnglish
Pages (from-to)339-347
JournalEnvironmental Pollution
Volume237
Issue numberJune
DOI
StatePublished - 2018

    Research areas

  • international

ID: 6264489