Environmental Source Tracking of Per- and Polyfluoroalkyl Substances within a Forensic Context: Current and Future Techniques

The source tracking of per- and polyfluoroalkyl substances (PFASs) is a new and increasingly necessary subfield within environmental forensics. We define PFAS source tracking as the accurate characterization and differentiation of multiple sources contributing to PFAS contamination in the environmen...

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Veröffentlicht in:Environmental science & technology 2021-06, Vol.55 (11), p.7237-7245
Hauptverfasser: Charbonnet, Joseph A, Rodowa, Alix E, Joseph, Nayantara T, Guelfo, Jennifer L, Field, Jennifer A, Jones, Gerrad D, Higgins, Christopher P, Helbling, Damian E, Houtz, Erika F
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container_end_page 7245
container_issue 11
container_start_page 7237
container_title Environmental science & technology
container_volume 55
creator Charbonnet, Joseph A
Rodowa, Alix E
Joseph, Nayantara T
Guelfo, Jennifer L
Field, Jennifer A
Jones, Gerrad D
Higgins, Christopher P
Helbling, Damian E
Houtz, Erika F
description The source tracking of per- and polyfluoroalkyl substances (PFASs) is a new and increasingly necessary subfield within environmental forensics. We define PFAS source tracking as the accurate characterization and differentiation of multiple sources contributing to PFAS contamination in the environment. PFAS source tracking should employ analytical measurements, multivariate analyses, and an understanding of PFAS fate and transport within the framework of a conceptual site model. Converging lines of evidence used to differentiate PFAS sources include: identification of PFASs strongly associated with unique sources; the ratios of PFAS homologues, classes, and isomers at a contaminated site; and a site’s hydrogeochemical conditions. As the field of PFAS source tracking progresses, the development of new PFAS analytical standards and the wider availability of high-resolution mass spectral data will enhance currently available analytical capabilities. In addition, multivariate computational tools, including unsupervised (i.e., exploratory) and supervised (i.e., predictive) machine learning techniques, may lead to novel insights that define a targeted list of PFASs that will be useful for environmental PFAS source tracking. In this Perspective, we identify the current tools available and principal developments necessary to enable greater confidence in environmental source tracking to identify and apportion PFAS sources.
doi_str_mv 10.1021/acs.est.0c08506
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subjects Computer applications
Contamination
Fluorocarbons - analysis
Forensic science
Homology
Hydrogeochemistry
Isomers
Learning algorithms
Machine learning
Mathematical analysis
Multivariate analysis
Perfluoroalkyl & polyfluoroalkyl substances
Software
Tracking
Water Pollutants, Chemical - analysis
title Environmental Source Tracking of Per- and Polyfluoroalkyl Substances within a Forensic Context: Current and Future Techniques
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