Abstract The rising detection of contaminants of emerging concern (CECs) in aquatic environments necessitates robust prioritization strategies to guide further testing and potential inclusion in monitoring programs. Existing CEC prioritization methods typically compare environmental concentrations to toxicity data (e.g., whole-organism or high-throughput assays) to identify “high-priority” chemicals, but integrating mechanistic insights into adverse effects remains limited. Here, a CEC prioritization framework which combined exposure−activity ratios (EARs) with adverse outcome pathways (AOPs) was developed and applied in the Yangtze River Basin in China. A total of 162 CECs across 9 categories in surface water samples from Yangtze River Basin were evaluated, and the most sensitive assay endpoints of these CECs were identified. Results showed that among all target CECs (nd-12,300 ng/L), 11 chemicals exhibited a 100% detection rate, with moclobemide (12,510 ng/L) and venlafaxine (12,300 ng/L) having the highest concentrations. Based on EAR and detection status, triisobutyl phosphate, aldicarb, methomyl, acetamiprid, perfluorodecanoic acid, nalidixic acid, and moclobemide were identified as “Level 1” priority chemicals. By linking high-exposure-activity ratio (high-EAR) molecular targets to validated AOPs, we connected analytical chemistry data with predictions of specific adverse outcomes, including endocrine-disruption-associated reproductive failure, porphyria-like metabolic disorders, and impairments in cognitive function and growth, which not only provide a mechanistic basis for analyzing the diverse biological effects induced by high-risk chemicals but also facilitate the screening-level prediction of potential associated ecological and human health risks.
Wang et al. (Sat,) studied this question.