Cited by 121Per- and polyfluoroalkyl substances researchFluorine in Organic ChemistryChemical Analysis and Environmental Impact

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

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Charbonnet, Joseph A., Rodowa, Alix E., Joseph, Nayantara T., Guelfo, Jennifer L., Field, Jennifer A., Jones, Gerrad D., Higgins, Christopher P., Helbling, Damian E. +1 more·2021·Environmental Science & Technology

Abstract

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.

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  1. [14]Kissa E, Ed. Fluorinated Surfactants and Repellents Surfactant Science Series, Second ed., Revised and Expanded; CRC Press: Boca Raton, FL, 2001; Vol. 97.
  2. [87]Dávila-Santiago E Opening Pandora’s Box: Machine Learning Applications for Chemical Forensics and Non-Target Chemical Analyses. Master’s Thesis, Oregon State University, Corvallis, OR, 2020.

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Authors
Charbonnet, J. A., Rodowa, A. E., Joseph, N. T., Guelfo, J. L., Field, J. A., Jones, G. D., Higgins, C. P., Helbling, D. E., & Houtz, E. F.
Affiliations
  • Colorado School of Mines (US)
  • National Institute of Standards and Technology (US)
  • Cornell University (US)
  • Texas Tech University (US)
  • Oregon State University (US)
  • Arcadis, 100 Montgomery Street, Suite 300, San Francisco, California 94104, United States
Corresponding author
Houtz, Erika F.
Venue
Environmental Science & Technology
Published
2021-05-13
Volume
55
Issue
11
Pages
7237-7245
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W3162853600
Cited by
121
References
76
Citations by year
2026: 25 · 2025: 32 · 2024: 25 · 2023: 16 · 2022: 20 · 2021: 3
FWCI
6.06
Type
journal article
Language
en
Open access
Locations
  • Environmental Science & Technology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • U.S. Environmental Protection Agency (83967001-0)
  • U.S. Department of Defense (SERDP ER20-1375)
Topics
  • Physical Sciences › Environmental Science › Environmental Chemistry › Per- and polyfluoroalkyl substances research
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Fluorine in Organic Chemistry
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Chemical Analysis and Environmental Impact
Keywords
per- and polyfluoroalkyl substances, environmental forensics, PFAS contamination, source apportionment, hydrogeochemistry, conceptual site model, PFAS fate and transport, machine learning, high-resolution mass spectrometry
MeSH terms
Fluorocarbons, Water Pollutants, Chemical

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