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Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States

112
Citations
November 15, 2024
Published Date

Research Abstract & Technology Focus

Per- and polyfluoroalkyl substances (PFAS), known colloquially as “forever chemicals,” have been associated with adverse human health effects and have contaminated drinking water supplies across the United States owing to their long-term and widespread use. People in the United States may unknowingly be drinking water that contains PFAS because of a lack of systematic analysis, particularly in domestic water supplies. We present an extreme gradient–boosting model for predicting the occurrence of PFAS in groundwater at the depths of drinking water supply for the conterminous United States. Our model results indicate that 71 million to 95 million people in the conterminous United States potentially rely on groundwater with detectable concentrations of PFAS for their drinking water supplies before any treatment.
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What is the core focus of the research titled 'Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States'?

This literature focuses on: Per- and polyfluoroalkyl substances (PFAS), known colloquially as “forever chemicals,” have been associated with adverse human health effects and have contaminated drinking water supplies across the United States owing to their long-term and wides...

Are there commercial applications of 'Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States' in market news publications?

Yes, highly correlated activity was mapped. An entry titled '3M's PFAS exit killed the supply chain for two-phase immersion cooling in DCs' discusses this: Insights and analysis on liquid cooling, immersion cooling, and thermal management for data centers.

What other academic literature is closely related to 'Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States'?

Yes, highly correlated activity was mapped. An entry titled 'Predictive Analysis of Groundwater Resources Using Random Forest Regression' discusses this: The lack of water is one of the most crucial problems of our day; therefore, optimized water resource management and predictions gathered by patron...

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