Combination of suspect and nontarget screening with exposure assessment for per- and polyfluoroalkyl substance prioritization in Chinese municipal wastewater

Abstract

Municipal wastewater treatment plants (WWTPs) are significant sources of per- and polyfluoroalkyl substances (PFASs) in aquatic environments, making their identification and priority rank crucial for risk control. Wastewater samples were collected from 148 municipal WWTPs in China to determine the occurrence and risk prioritization of PFASs. A total of 61 PFASs were identified, including 14 legacy and 47 emerging PFASs, using machine learning prediction-enhanced suspect and nontarget screening techniques. PFASs were detected in all wastewater samples, with perfluorocarboxylic acid (PFCA), perfluorosulfonic acid (PFSA), fluoromeric sulfonic acid (FTSA), and perfluoroalkyl sulfonamide-like (PFSM) substances being the predominant classes. The exposure loads of legacy and emerging PFASs to the Chinese population were 71.8 and 52.9 μg·day⁻¹·people⁻¹, respectively, and textile and clothing products might be the primary PFAS exposure pathways. Through a risk prioritization method integrating toxicity and exposure data, ten legacy and five emerging PFASs were flagged as high-priority substances requiring additional attention. As the PFAS risk removal efficiency by conventional biological treatment processes was only 0.7 %, the PFAS risk priority patterns in influent and effluent were similar (r = 0.86, p < 0.01). In addition, there were significant regional differences in the PFAS risk distribution, and the PFAS risk in eastern China was higher than that in other regions. This study offers novel insights for the identification and priority control assessment of PFASs and other emerging environmental contaminants.