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

• Published in: Environmental science & technology 2024-02, Vol.58 (5), p.2468-2478
• Main Authors: Brunelle, Laura D., Batt, Angela L., Chao, Alex, Glassmeyer, Susan T., Quinete, Natalia, Alvarez, David A., Kolpin, Dana W., Furlong, Edward T., Mills, Marc A., Aga, Diana S.
• Format: Article
• Language: English
• Subjects: Analytical chemistry; Chemicals; Cluster analysis; Clustering; Contaminants; Drinking water; Drinking Water - analysis; Environmental Monitoring - methods; Occurrence, Fate, and Transport of Aquatic and Terrestrial Contaminants; Organic chemicals; Organic Chemicals - analysis; Organic chemistry; Receiving waters; Samplers; Sampling; Screening; Surface water; Vector quantization; Wastewater; Wastewater discharges; Water discharge; Water flow; Water Pollutants, Chemical - analysis; Water Purification; Water reuse; Water treatment; Water treatment plants
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/acs.est.3c07514

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. Nontargeted 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 flow path representative of de facto water reuse. The goal of this work was to examine the fate of CECs along the study flow path 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 insights into 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 across both sampling sites and sampling events. Chemical features that occurred frequently or survived drinking water treatment were prioritized for identification, resulting in the probable identification of over 100 CECs in the watershed and 28 CECs in treated drinking water.