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

被引:55
作者
Charbonnet, Joseph A. [1 ]
Rodowa, Alix E. [2 ]
Joseph, Nayantara T. [3 ]
Guelfo, Jennifer L. [4 ]
Field, Jennifer A. [5 ]
Jones, Gerrad D. [6 ]
Higgins, Christopher P. [1 ]
Helbling, Damian E. [3 ]
Houtz, Erika F. [7 ]
机构
[1] Colorado Sch Mines, Dept Civil & Environm Engn, Golden, CO 80401 USA
[2] NIST, Biochem & Exposure Sci Grp, Charleston, SC 29412 USA
[3] Cornell Univ, Sch Civil & Environm Engn, New York, NY 14853 USA
[4] Texas Tech Univ, Dept Civil Environm & Construct Engn, Lubbock, TX 79409 USA
[5] Oregon State Univ, Dept Environm & Mol Toxicol, Corvallis, OR 97331 USA
[6] Oregon State Univ, Dept Biol & Ecol Engn, Corvallis, OR 97331 USA
[7] Arcadis, San Francisco, CA 94104 USA
关键词
per- and polyfluoroalkyl substances; environmental forensics; conceptual site models; multivariate statistics; source tracking; high-resolution mass spectrometry; FILM-FORMING FOAM; AFFF-IMPACTED GROUNDWATER; FIRE-TRAINING AREAS; PERFLUOROALKYL SUBSTANCES; AEROBIC BIOTRANSFORMATION; SUBSURFACE TRANSPORT; SPATIAL-DISTRIBUTION; ALKYL SUBSTANCES; PFASS; WATER;
D O I
10.1021/acs.est.0c08506
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:7237 / 7245
页数:9
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