Suspect screening to support source identification and risk assessment of organic micropollutants in the aquatic environment of a Sub-Saharan African urban center

•Suspect screening prioritized 157 OMPs in Kampala water samples for target analysis.•Hierarchical clustering established the source-related co-occurrence patterns of OMPs.•Critical evaluation of literature data from SSA revealed 69 newly quantified OMPs.•Nitrate and protein-like fluorescent organic matter correlated with the level of OMPs.•Screening-level risk assessments identified OMPs with the potential for biological effects. Organic micropollutants (OMPs) are contaminants of global concern and have garnered increasing attention in Africa, particularly in urban and urbanizing areas of Sub-Saharan Africa (SSA). In this work, we coupled suspect screening enabled by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with multivariate analysis to characterize OMPs in wastewater, surface water, and groundwater samples collected from Kampala, the capital and largest city of Uganda. Suspect screening prioritized and confirmed 157 OMPs in Kampala samples for target quantification. Many OMPs detected in Kampala samples occurred within concentration ranges similar to those documented in previous studies reporting OMP occurrence in SSA, but some have never or rarely been quantified in environmental water samples from SSA. Hierarchical cluster analysis established the source-related co-occurrence profiles of OMPs. Partial least squares regression and multiple linear regression analyses further pinpointed the concentration of nitrate and the content of a fluorescent organic matter component with excitation/emission maxima around 280/330 nm as predictors for the sample-specific cumulative concentrations of OMPs, suggesting the likely contribution of diffuse runoff and wastewater discharges to OMP occurrence in the aquatic environment of Kampala. Parallel calculations of exposure-activity ratios and multi-substance potentially affected fractions provided insights into the potential for biological effects associated with OMPs and highlighted the importance of expanded analytical coverage for screening-level risk assessments. Overall, our study demonstrates a versatile database-driven screening and data analysis methodology for the multipronged characterization of OMP contamination in a representative SSA urban center. [Display omitted]