학술논문

A Bayesian hierarchical model for estimating national PFAS drinking water occurrence.
Document Type
Article
Source
AWWA Water Science. May/Jun2022, Vol. 4 Issue 3, p1-13. 13p.
Subject
*BAYESIAN analysis
*DRINKING water
*PERFLUOROOCTANE sulfonate
*DATA analysis
*FLUOROALKYL compounds
Language
ISSN
2577-8161
Abstract
Per‐ and polyfluoroalkyl substances (PFAS) in U.S. drinking water are currently a significant topic of public health concern. Data collection efforts have been undertaken to better understand PFAS occurrence, though limited data observed above reporting limits leaves considerable uncertainty. This work presents a hierarchical Bayesian model developed to estimate national PFAS occurrence in drinking water with a simple model structure and assumptions. Here the model is limited to the occurrence of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS), and perfluoroheptanoic acid (PFHpA). This model estimates national PFAS exposure while capturing uncertainty, provides information on system‐level PFAS co‐occurrence, and creates an expandable foundation for generating future national estimates of PFAS occurrence. National estimates based on currently available data and model assumptions indicated population‐weighted mean exposure to the sum of mean PFOS, PFOA, PFHpA, and PFHxS around 4.7–5.2 ppt while all four chemicals generally had moderate‐to‐strong correlations among system‐level means. [ABSTRACT FROM AUTHOR]