Tracing Wastewater Treatment Plant Influences in an Urban River Using Nontarget Chemical Fingerprints and Source–Receptor Connectivity

Abstract Tracing facility-level influences in urban rivers is challenging because complex contaminant mixtures limit discrimination of individual dischargers. Conventional bulk indicators provide limited source specificity, whereas high-resolution mass spectrometry nontarget analysis (HRMS-NTA) rarely incorporates river-network connectivity. Here, we developed an HRMS fingerprinting framework integrating feature prioritization, chemical fingerprints, directed source connectivity, non-negative least-squares decomposition, and facility discharge to trace wastewater treatment plant (WWTP) influences. Using scenario-matched fingerprints from 13 WWTPs, we evaluated three longitudinal river receptors under base-flow and higher-flow conditions. Across six cases, model-derived Chemical Influence covaried with independently measured PFAS and antibiotic concentrations across 10 relationships; florfenicol, PFOS, and roxithromycin yielded R2 values ranging from 0.862 to 0.955. Hydraulic share and chemical influence were decoupled: under higher-flow conditions, one facility contributed only 9.57% of WWTP discharge but 39.1% of the integrated Chemical Influence at the farthest downstream receptor. Thus, discharge volume or fingerprint correspondence alone may overlook disproportionate chemical influence. The framework advances NTA from broad source-type differentiation toward river-network-informed, facility-level tracing, providing a basis for scenario-specific prioritization in complex urban rivers.