4.7 Article

Presumptive Contamination: A New Approach to PFAS Contamination Based on Likely Sources

期刊

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.estlett.2c00502

关键词

per-and polyfluoroalkyl substances (PFAS); presumptive contamination; PFAS testing and investigation; AFFF; PFAS waste and disposal

资金

  1. National Science Foundation [SES-1827817, SES-2120510]
  2. National Institute of Environmental Health Sciences [2-T32-ES023769-06, R01ES028311]
  3. Marisla Foundation
  4. Tides Foundation [TF2101-096968]

向作者/读者索取更多资源

Despite increased research and regulatory attention, data on the scale, scope, and severity of PFAS releases and contamination in the United States are incomplete. This paper argues that in the absence of high-quality testing data, PFAS contamination can be presumed around certain types of facilities. By integrating nationwide data sets, 57,412 sites of presumptive PFAS contamination are identified, including industrial facilities, wastewater treatment plants, military sites, and airports.
While research and regulatory attention to per-and polyfluoroalkyl substances (PFAS) has increased exponentially in recent years, data are uneven and incomplete about the scale, scope, and severity of PFAS releases and resulting contamination in the United States. This paper argues that in the absence of high quality testing data, PFAS contamination can be presumed around three types of facilities: (1) fluorinated aqueous film-forming foam (AFFF) discharge sites, (2) certain industrial facilities, and (3) sites related to PFAS-containing waste. While data are incomplete on all three types of presumptive PFAS contamination sites, we integrate available geocoded, nationwide data sets into a single map of presumptive contamination sites in the United States, identifying 57,412 sites of presumptive PFAS contamination: 49,145 industrial facilities, 4,255 wastewater treatment plants, 3,493 current or former military sites, and 519 major airports. This conceptual approach allows governments, industries, and communities to rapidly and systematically identify potential exposure sources.

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