源跟踪
背景(考古学)
跟踪(教育)
鉴定(生物学)
计算机科学
多元统计
环境科学
污染
环境监测
数据科学
水源
生化工程
机器学习
环境工程
工程类
地理
生态学
水资源管理
生物
考古
万维网
教育学
心理学
作者
Joseph A. Charbonnet,Alix E. Rodowa,Nayantara T. Joseph,Jennifer L. Guelfo,Jennifer A. Field,Gerrad D. Jones,Christopher P. Higgins,Damian E. Helbling,Erika Houtz
标识
DOI:10.1021/acs.est.0c08506
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.
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