Per- and polyfluoroalkyl substances research
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Abstract
Abstract
Abstract Per- and polyfluoroalkyl substances (PFASs) are globally detected in humans, yet regional variations in PFAS exposure remain insufficiently characterized. Herein, by utilizing target and nontarget analysis with machine learning, differences in PFAS exposure were assessed based on 1088 serum samples of the population from SX, GD, HeB, and HuB regions in China. Nontarget analysis identified 49 PFASs, among which bis(trifluoromethane)sulfonimide (Ntf2), C8 per- and polyfluoroalkyl ether carboxylic acid, C12 hydrogen-substituted polyfluoroalkyl (linear) carboxylic acid, 8:2 fluorotelomer unsaturated carboxylic acid, 1-hydroxy-6:2 fluorotelomer sulfonic acid, haloxyfop, and leflunomide were reported in human serum for the first time. Target analysis indicated total PFAS concentrations of 9.4, 17, 25, and 29 ng/mL in the SX, GD, HeB, and HuB regions, respectively, with compositional profiles differing in the proportions of specific PFAS classes. Machine learning classifiers achieved an accuracy of 0.89 in distinguishing samples from the four regions, revealing significant interregional disparity. Furthermore, PFNA, Ntf2, PFOA, and 6:2 Cl-PFESA were identified as distinctive exposure biomarkers for SX, GD, HeB, and HuB, respectively, each being closely associated with local industrial activities. Overall, this study elucidates the region-specific characteristics of human PFAS exposure in China, providing a scientific basis for regionally tailored health risk assessment and pollution control strategies.
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@article{Li2026Characterizing,
title = {Characterizing Regional Variation of PFAS Profiles in Human Serum from China by Integrated Target and Nontarget Analysis with Machine Learning},
author = {Guiying Li and Taicheng An and Huikang Lin and Chang He and Anna Ji and Xiaohui Yu and Xiaoping Wang},
journal = {Environmental Science & Technology},
year = {2026},
doi = {10.1021/acs.est.6c04503},
url = {https://doi.org/10.1021/acs.est.6c04503}
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