Coupling Suspect and Nontarget Screening with Mass Balance Modeling to Characterize Organic Micropollutants in the Onondaga Lake–Three Rivers System

Characterizing the occurrence, sources, and fate of organic micropollutants (OMPs) in lake–river systems serves as an important foundation for constraining the potential impacts of OMPs on the ecosystem functions of these critical landscape features. In this work, we combined suspect and nontarget screening with mass balance modeling to investigate OMP contamination in the Onondaga Lake–Three Rivers system of New York. Suspect and nontarget screening enabled by liquid chromatography–high-resolution mass spectrometry led to the confirmation and quantification of 105 OMPs in water samples collected throughout the lake–river system, which were grouped by their concentration patterns into wastewater-derived and mixed-source clusters via hierarchical cluster analysis. Four of these OMPs (i.e., galaxolidone, diphenylphosphinic acid, N-butylbenzenesulfonamide, and triisopropanolamine) were prioritized and identified by nontarget screening based on their characteristic vertical distribution patterns during thermal stratification in Onondaga Lake. Mass balance modeling performed using the concentration and discharge data highlighted the export of OMPs from Onondaga Lake to the Three Rivers as a major contributor to the OMP budget in this lake–river system. Overall, this work demonstrated the utility of an integrated screening and modeling framework that can be adapted for OMP characterization, fate assessment, and load apportionment in similar surface water systems.