Ruyle Bridger J, Thackray Colin P, McCord James P, Strynar Mark J, Mauge-Lewis Kevin A, Fenton Suzanne E, Sunderland Elsie M
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States.
Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, United States.
Environ Sci Technol Lett. 2021 Jan 12;8(1):59-65. doi: 10.1021/acs.estlett.0c00798.
Hundreds of public water systems across the United States have been contaminated by the use of aqueous film-forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS) during firefighting and training activities. Prior work shows AFFF contain hundreds of polyfluoroalkyl precursors missed by standard methods. However, the most abundant precursors in AFFF remain uncertain, and mixture contents are confidential business information, hindering proactive management of PFAS exposure risks. Here, we develop and apply a novel method (Bayesian inference) for reconstructing the fluorinated chain lengths, manufacturing origin, and concentrations of oxidizable precursors obtained from the total oxidizable precursor (TOP) assay that is generally applicable to all aqueous samples. Results show virtually all (median 104 ± 19%) extractable organofluorine (EOF) in contemporary and legacy AFFF consists of targeted compounds and oxidizable precursors, 90% of which are 6:2 fluorotelomers in contemporary products. Using high-resolution mass spectrometry, we further resolved the 6:2 fluorotelomers to assign the identity of 14 major compounds, yielding a priority list that accounts for almost all detectable PFAS in contemporary AFFF. This combination of methods can accurately assign the total PFAS mass attributable to AFFF in any aqueous sample with differentiation of gross precursor classes and identification of major precursor species.
在美国,数百个公共供水系统在消防和训练活动中因使用含有全氟和多氟烷基物质(PFAS)的水成膜泡沫(AFFF)而受到污染。先前的研究表明,AFFF含有数百种标准方法未检测到的多氟烷基前体。然而,AFFF中含量最高的前体仍不确定,且混合物成分属于商业机密信息,这阻碍了对PFAS暴露风险的主动管理。在此,我们开发并应用了一种新方法(贝叶斯推理)来重建从总可氧化前体(TOP)分析中获得的氟化链长度、生产来源以及可氧化前体的浓度,该方法普遍适用于所有水性样品。结果表明,当代和遗留AFFF中几乎所有(中位数为104±19%)的可提取有机氟(EOF)都由目标化合物和可氧化前体组成,其中90%是当代产品中的6:2氟调聚物。使用高分辨率质谱,我们进一步解析了6:2氟调聚物,确定了14种主要化合物的身份,得出了一个优先级列表,该列表涵盖了当代AFFF中几乎所有可检测到的PFAS。这种方法组合可以准确地确定任何水性样品中归因于AFFF的总PFAS质量,区分主要前体类别并识别主要前体物种。