ArticleIntegrated environmental assessment and management2023
A geospatial and binomial logistic regression model to prioritize sampling for per- and polyfluorinated alkyl substances in public water systems.
Article in Integrated environmental assessment and management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Identifying and sharing per-and polyfluoroalkyl substances hot-spot areas and exposures in drinking water.Scientific data · 2023Article
- A proposed FAIR approach for disseminating geospatial information system maps.Scientific data · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
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. Integr Environ Assess Manag 2023;19:163-174. © 2022 SETAC.
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Registered trials
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