Water Pollution

Recent Publications and News

Sociodemographic Factors Are Associated with the Abundance of PFAS Sources and Detection in U.S. Community Water Systems

Drinking water contaminated by per- and polyfluoroalkyl substances (PFAS) is a widespread public health concern, and exposure–response relationships are known to vary across sociodemographic groups. However, research on disparities in drinking water PFAS exposures and the siting of PFAS sources in marginalized communities is limited. Here, we use monitoring data from 7873 U.S. community water systems (CWS) in 18 states to show that PFAS detection is positively associated with the number of PFAS sources and proportions of people of color who are served by these water systems.
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Freshwater fish found to have high levels of ‘forever chemicals’

A new study found high levels of toxic “forever chemicals” in freshwater fish nationwide. Compared to store-bought fish, the fish examined in the study had an average of nearly 280 times more of these toxic chemicals called PFAS. Particularly high levels were found in fish caught in urban areas.
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Nitrifying Microorganisms Linked to Biotransformation of Perfluoroalkyl Sulfonamido Precursors from Legacy Aqueous Film-Forming Foams

Per- and polyfluoroalkyl substances (PFAS) are a diverse class of aliphatic organofluorine compounds that include thousands of precursors that can be abiotically and biotically transformed into terminal perfluoroalkyl acids (PFAA) of known health concern.   Widespread human exposures to PFAA through drinking water and dietary sources have been associated with many deleterious health outcomes.
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Soil and water pollution and human health: what should cardiologists worry about?

Pollution of air, water, and soil is responsible for at least 9 million deaths each year. More than 60% of pollution-related disease and death is due to cardiovascular disease. Recognizing the importance of pollution to human health, the European Commission and the EU Action Plan for 2050: A Healthy Planet for All, have determined that air, water, and soil pollution must be reduced to levels that cause no harm to human or ecosystem health.
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The Utility of Machine Learning Models for Predicting Chemical Contaminants in Drinking Water: Promise, Challenges, and Opportunities.

This review aims to better understand the utility of machine learning algorithms for predicting spatial patterns of contaminants in the United States (U.S.) drinking water.
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