A Statistical Approach for Identifying Private Wells Susceptible to Perfluoroalkyl Substances (PFAS) Contamination.

ABSTRACT: Drinking water concentrations of per- and polyfluoroalkyl substances (PFAS) exceed provisional guidelines for millions of Americans. Data on private well PFAS concentrations are limited in many regions and monitoring initiatives are costly and time-consuming. Here we examine modeling approaches for predicting private wells likely to have detectable PFAS concentrations that could be used to prioritize monitoring initiatives. We used nationally available data on PFAS sources, and geologic, hydrologic and soil properties that affect PFAS transport as predictors and trained and evaluated models using PFAS data (n~2300 wells) collected by the state of New Hampshire between 2014 and 2017. Models were developed for the five most frequently detected PFAS: perfluoropentanoate, perfluorohexan

SUBMITTER: Hu XC 

PROVIDER: S-EPMC10312616 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature