Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation to drinking water systems. As datasets of PFAS drinking water sampling continue to grow as part of evolving regulatory requirements, we used this Kentucky dataset as an example to promote the reuse of this dataset and others like it. We incorporated the FAIR (Findable, Accessible, Interoperable, and Reusable) principles by creating a Figshare item that includes all data and associated metadata with these five ArcGIS maps.
As health‐based drinking water standards for per‐ and polyfluorinated alkyl substances (PFAS) continue to evolve, public health and environmental protection decision‐makers must assess exposure risks associated with all public drinking water systems in the United States (US). Unfortunately, current knowledge regarding the presence of PFAS in environmental systems is limited. In this study, a screening approach was established to: (1) identify and direct attention toward potential PFAS hot spots in drinking water sources, (2) prioritize sampling locations, and (3) provide insights regarding the potential PFAS sources that contaminate groundwater and surface water. Our approach incorporates geospatial data from public sources, including the US Environmental Protection Agency's Toxic Release Inventory, to identify locations where PFAS may be present in drinking water sources. An indicator factor (also known as “risk factor”) was developed as a function of distance between potential past and/or present PFAS users (e.g., military bases, industrial sites, and airports) and the public water system, which generates a heat map that visualizes potential exposure risks. A binomial logistic regression model indicates whether PFAS are likely to be detected in public water systems. The results obtained using the developed screening approach aligned well (with a 76% overall model accuracy) with PFAS sampling and chemical analysis data from 81 public drinking water systems in the state of Kentucky. This study proposes this screening model as an effective decision aid to assist key decision‐makers in identifying and prioritizing sampling locations for potential PFAS exposure risks in the public drinking water sources in their service areas.
- NSF-PAR ID:
- 10387095
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Integrated Environmental Assessment and Management
- Volume:
- 19
- Issue:
- 1
- ISSN:
- 1551-3777
- Page Range / eLocation ID:
- p. 163-174
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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