Work

The selection of priority control perfluorinated alkyl substances in drinking water source of Guangzhou, China, a case study based on health risks ranking

Year: 2025

Type: article

Abstract: The health risk of perfluorinated alkyl substances (PFASs) in drinking water always deserve attention, which involve the changing evaluation criteria and nonnegligible mixed exposure of multiple PFASs. Currently, the United States Environmental Protection Agency is reducing the maximum contaminant levels. At the same time, insufficient attention to mixed exposure may underestimate the overall risks of PFASs in drinking water. To face these challenges, a scheme, which identify a priority towards the most problematic compounds and accurate manage PFASs in drinking water are warranted. Liuxi River drinking water source was taken as a case study, and the levels of 13 PFASs were analyzed. A data-driven ranking model, which considered new maximum contaminant levels and mixed exposure, was used to choose priority control PFASs. PFASs were divided into four levels according to their health risks and drinking water intake rate; the compounds at Level I (perfluorononanoic acid) need priority control, while compounds at Levels II (perfluorododecanoic acid, perfluorooctane sulfonate, and perfluoroundecanoic acid) and Level III (perfluoroheptanoic acid, perfluorooctanoic acid, and perfluorobutane sulfonate) deserve more attention. This study provides a solid scientific basis for selecting priority control PFASs in drinking water sources, for the purpose of adequately ensuring the safety of drinking water under the lowest management cost. The results also call for more consideration on feasibility of current standards of PFASs in drinking water. • Select priority control PFASs of the drinking water under the lowest management cost. • Data driven model was based on total health risk and the drinking water intake rate. • PFASs were divided into four management levels based on a data-driven ranking model. • PFASs at level I and II deserve priority control and more attention, respectively. • The model helps to reasonable control of PFASs and optimize management efficiency.

Source: Ecotoxicology and Environmental Safety

DOI: 10.1016/j.ecoenv.2025.118092