Susan A Csiszar, Chiara Maria Vitale, Raghu Vamshi, Kyle S Roush, Brenna Kent, Ryan Heisler, Heather Summers, Emily E Burns, Iain Davies, Darius Stanton, Spatially referenced environmental exposure model for down-the-drain substance emissions across European rivers for aquatic safety assessments, Integrated Environmental Assessment and Management, 2025;, vjaf119, https://doi.org/10.1093/inteam/vjaf119
Abstract
A spatially referenced environmental exposure model for down-the-drain substance emissions was developed for Europe, including the 27 European Union Member States, Norway, Switzerland, and the United Kingdom. The model builds upon the global modeling framework that leverages the well-established iSTREEM model for the United States and further expands global coverage of the framework. The data are parameterized using European Union data on wastewater treatment plants, locations, infrastructure, and global spatial datasets on population and river flow rates and routing. The model provides substance concentration distributions based on the spatial variability of these parameters across Europe while taking into account river connectivity, chemical routing between rivers, and in-stream decay. Chemical-specific model inputs include wastewater treatment removals, in-stream decay rates, and emissions. The model is demonstrated for four case study chemicals that are used in consumer products with down-the-drain disposal routes: linear alkylbenzene sulfonate and alkyl sulfate are common surfactants used in laundry detergents, and oxybenzone and octinoxate are ultraviolet (UV)-filters used in personal care products. Monitoring data were collected to represent spatial variability across Europe as a comparison to modeled values. Modeled concentrations were found to be predictive while still being conservative, with 90th percentile modeled concentrations agreeing with monitored concentrations within a factor of two to eight across the case study substances. We further demonstrate how the model can be applied in prospective safety assessments by comparing modeled concentrations to previously established predicted no-effect concentrations, and also demonstrate how the model is consistent with tiered risk assessment approaches when compared to the monitoring data assessments.