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De facto water reuse - Investigating the fate and transport of chemicals of emerging concern from wastewater discharge through drinking water treatment using non-targeted analysis and suspect screening
Citation:
Brunelle, L., A. Batt, A. Chao, S. Glassmeyer, N. Quinete, D. Alvarez, D. Kolpin, E. Furlong, M. Mills, AND D. Aga. De facto water reuse - Investigating the fate and transport of chemicals of emerging concern from wastewater discharge through drinking water treatment using non-targeted analysis and suspect screening. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 58(5):2468-2478, (2024). https://doi.org/10.1021/acs.est.3c07514
Impact/Purpose:
Non-targeted chemical analysis was conducted on samples representative of de facto water reuse, with probable identifications for over 100 Chemicals of Emerging Concern (CECs), including three separate seasonal sampling events of surface water and drinking water. This sampling design included both grab samples taken in a watershed and time integrated samples (POCIS) that were also deployed at the multiple surface water and drinking water locations.
Description:
Wastewater is a source for many contaminants of emerging concern (CECs) and surface waters receiving wastewater discharge often serve as source water for downstream drinking water treatment plants. Non-targeted analysis and suspect screening methods were used to characterize chemicals in residence-time weighted grab samples and companion polar organic chemical integrative samplers (POCIS) collected on three separate hydrologic sampling events along a surface water flowpath representative of de facto water reuse. A goal of this work was to examine the fate of CECs along the study reach as water is transported from wastewater effluent through drinking water treatment. Grab and POCIS samples provided a comparison between residence-time weighted single point and integrative sample results. This unique and rigorous study design coupled with advanced analytical chemistry tools provided important insight on chemicals found in drinking water and their potential sources, which can be used to help prioritize chemicals for further study. K-means clustering analysis was used to identify patterns in chemical occurrences both across sampling sites and sampling events. Chemical features that occurred frequently or survived drinking water treatment were prioritized for identification, resulting in the identification of over 100 CECs in the watershed and 28 CECs in treated drinking water.
