Toxicity-weighted source prioritization of PFAS and antibiotics in an urban watershed.

Abstract

Emerging contaminants (ECs), particularly PFAS and antibiotics, occur as mixtures in urban rivers, yet conventional mass-based receptor models provide limited support for toxicity-oriented source-category prioritization. Here, we apply a PMF-SRC workflow that integrates toxicity weighting into receptor modeling to enable comparative source-associated risk prioritization across chemically distinct classes. Applied to an urbanized watershed in central China, the workflow revealed substantial differences between mass-based and toxicity-weighted rankings in both campaigns. Under base-flow, the factors interpreted as livestock/aquaculture-associated accounted for the largest reconstructed mass share (51.3%), whereas factors associated with municipal wastewater and industrial sources contributed 46.6% and 40.9% of the screening-level risk index, respectively. Under higher-flow, municipal-wastewater-associated factors accounted for 30.7% of mass but 64.4% of the screening-level risk index, while urban-runoff-associated factors were associated with 13.3% of mass and 25.6% of the risk index. PFOS drove the higher-flow contrast, contributing 67.0% of the screening-level risk index on average despite representing only 1.9% of the measured mass concentration. Overall, the PMF-SRC reveals that the dominant contributors to contaminant mass are not necessarily the dominant contributors to screening-level risk index, suggesting toxicity-weighted comparison may offer complementary information beyond mass-based apportionment alone when identifying priority source categories in chemically complex urban watersheds.