The overall goal of this project is to develop and validate a forensic approach for source allocation of per and polyfluoroalkyl substances (PFAS) present in impacted waters so as to differentiate PFAS impacts associated with the use of aqueous film forming foam (AFFF) versus non-AFFF sources. This work is predicated on the assumption that there is significant overlap in terms of the types of terminal perfluoroalkyl acids (PFAAs) formed from environmental transformations of polyfluoroalkyl substances released from various sources. Because of this, we posit that significant differences in the relative abundances of the various PFAS, particularly polyfluoroalkyl substances, will exist between types of sources such that a general chemical “fingerprint” of each source can be developed for the purpose of differentiating AFFF from non-AFFF sources.
Advanced analytical techniques such as high resolution mass spectrometry (HRMS) are likely to be invaluable for forensic fingerprinting of PFAS. However, more routine analyses by standard liquid chromatography tandem mass spectrometry (LC-MS/MS) are also likely to be important if a suite of PFAS that represent endmember PFAS sources can be identified. The research team hypothesize that a targeted method measuring relatively few PFAS contained in a “Forensic LC-MS/MS PFAS Panel” can differentiate between most AFFF and non-AFFF sources. This forensic panel will be bolstered by a careful analysis of other chemical constituents derived from PFAS sources that may leave an additional fingerprint as well as appropriate contextualization of the PFAS results through a comprehensive transformation pathway map.
The research team will develop a set of tools for use in forensic PFAS source allocation including:
The development of a database, pathway map, and HRMS library will provide additional context and rigor to any source apportionment analysis and furthermore, these tools will enable more definitive identification of PFAS sources if the LC-MS/MS-based method provides ambiguous results. Library development and validation will occur across three commonly used HRMS platforms, and the library efforts will include clearly articulated criteria for identifying PFAS by HRMS. Additionally, the HRMS library will be formatted for delivery to the National Institute of Standards and Technology (NIST). This 3-year project will build from significant efforts already underway by the project team.
Successful completion of the project research will provide the Department of Defense (DoD), site managers, and other stakeholders with a scientifically defensible and statistically sound approach for allocating PFAS in impacted waters to various AFFF and non-AFFF sources. Building from the significant body of literature on environmental chemical forensics, the suite of tools that will be developed will enable stakeholders to access as much detail as needed for a particular site of interest. Overall, when coupled with site-specific information, this research will ensure robust management decisions are made with respect to identifying responsible parties for PFAS-impacted water supplies. (Anticipated Project Completion - 2024)
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Charbonnet, J.A., A.E. Rodowa, N.T. Joseph, J.L. Guelfo, J.A. Field, G. Jones, C.P. Higgins, D.E. Helbling, and E.F. Hotz. 2021. Environmental Science & Technology, 55(11):7237-7245. doi.org/10.1021/acs.est.0c08506.
Charbonnet, J.A., C.A. McDonough, F. Xiao, T. Schwichtenberg, D. Cao, S. Kaserzon, K. Thomas, P. Dewapriya, B. Place, E. Schymanski, J.A. Field, D. Helbling, and C.P. Higgins. 2022. Communicating Confidence of Per- and Polyfluoroalkyl Substance (PFAS) Identification via High Resolution Mass Spectrometry. Environmental Science & Technology Letters, 9(6):473-481. doi.org/10.1021/acs.estlett.2c00206.
Choi, Y.J., D. Helbling, J. Liu, C.I. Olivares, and C.P. Higgins. 2022. Microbial Biotransformation Of Aqueous Film-Forming Foam Derived Polyfluoroalkyl Substances. Science of the Total Environment, 824:153711. doi.org/10.1016/j.scitotenv.2022.153711.
Dávila-Santiago, E., C. Shi, G. Mahadwar, B. Medeghini, L. Insinga, R. Hutchinson, S. Good, and G.D. Jones. 2022. Machine Learning Applications for Chemical Fingerprinting and Environmental Source Tracking Using Non-Target Chemical Data. Environmental Science and Technology, 56(7):4080–4090. doi.org/10.1021/acs.est.1c06655.
Jacob, P., R. Wang, C. Ching, and D.E. Helbling, 2021. Evaluation, Optimization, and Application of Three Independent Suspect Screening Workflows for the Characterization of PFAS in Water. Environmental Science: Processes and Impacts, 23:1554-1565. doi.org/10.1039/D1EM00286D.
Titaley, I. A., J. Khattak, J. Dong, C.I. Olivares, B. DiGuiseppi, C.C. Lutes, and J.A. Field. 2022. Neutral Per- and Polyfluoroalkyl Substances, Butyl Carbitol, and Organic Corrosion Inhibitors in Aqueous Film-Forming Foams: Implications for Vapor Intrusion and the Environment. Environmental Science and Technology, 56, 10785-10797. doi.org/10.1021/acs.est.2c02349.