Machine learning-enhanced molecular network reveals global exposure to hundreds of unknown PFAS.

Unknown forever chemicals like per- and polyfluoroalkyl substances (PFASs) are difficult to identify. Current platforms designed for metabolites and natural products cannot capture the diverse structural characteristics of PFAS. Here, we report an automatic PFAS identification platform (APP-ID) that screens for PFAS in environmental samples using an enhanced molecular network and identifies unknown PFAS structures using machine learning. Our networking algorithm, which enhances characteristic fragment matches, has lower false-positive rate (0.7%) than current algorithms (2.4 to 46%). Our support vector machine model identified unknown PFAS in test set with 58.3% accuracy, surpassing current software. Further, APP-ID detected 733 PFASs in real fluorochemical wastewater, 39 of which are previously unreported in environmental media. Retrospective screening of 126 PFASs against public data repository from 20 countries show PFAS substitutes are prevalent worldwide.

The occurrence, tissue distribution, and PBT potential of per- and polyfluoroalkyl substances in the freshwater organisms from the Yangtze river via nontarget analysis.

Numerous emerging per- and polyfluoroalkyl substances (PFASs) occur in the aquatic environment, posing a threat to aquatic ecosystems and human health. In this study, we conducted a nontarget analysis on 3 surface water samples and 92 tissue samples of 16 fish collected from the Yangtze River to investigate the patterns, tissue distribution, and environmental impacts of emerging PFASs. A total of 43 PFASs from 11 classes were identified, including 17 legacy PFASs and 26 emerging PFASs. Among the 43 PFASs, seven PFASs were reported in biota for the first time while five PFASs were reported in the environment for the first time. Chlorine substituted perfluoroalyl ether sulfonic acids were the major emerging PFASs detected in organisms. Our results showed that most emerging PFASs tended to accumulate in the liver whereas perfluorinated sulfonamides tended to accumulate in the blood, and all of the emerging PFASs accumulated less in the muscle. Methods for evaluating the persistence, bioaccumulation, and toxicity (PBT) of PFASs were developed by combining the in-silico methods and experimental methods. Long-chain PFASs were found to have extremely high PBT scores compared to short-chain PFASs. Additionally, most emerging PFASs exhibited comparable PBT characteristics with legacy PFASs, especially Cl-substituted PFASs.