Spatial modeling framework for aquatic exposure assessments of chemicals disposed down the drain: Case studies for China and Japan.

A modeling framework was created for the development of spatially explicit aquatic exposure models for any region or country of interest for chemicals disposed of down the drain. The framework relies on globally available data sets for river flow and population, and locally available data sets for wastewater treatment infrastructure and domestic water use, and leverages the iSTREEM® chemical routing algorithm. The framework was applied to China and Japan as case study countries. Spatially explicit population data were obtained from WorldPop. River flows covering the spatial extent of the two countries were derived from a high‐resolution surface runoff gridded data set that was based on the Curve Number approach and combined with the hydrology network for catchments and rivers from HydroBASINS and HydroSHEDS data sets. Publicly available data from government sources were used for estimating per capita water use and wastewater treatment infrastructure. To demonstrate the framework, the China model was used to predict the levels of the antifungal agent climbazole in rivers across the country, and the Japan model was used to predict river concentrations of linear alkylbenzene sulfonate. For both chemicals, the comparison of measured to modeled values showed good agreement, using linear regression analysis (R2 ≥ 0.96). The framework presented in this study provides a systematic and robust approach to develop spatially resolved exposure models that can be extrapolated to any country or region, allowing more accurate risk assessment of chemicals disposed down the drain by leveraging concentration distributions generated by the model. Integr Environ Assess Manag 2022;18:722–733. © 2021 SETAC Key Points: Modeling framework created for the development of spatially explicit aquatic exposure models for any region or country of interest for chemicals disposed of down the drain.Framework relies on the use of a high‐resolution global flow dataset developed as part of this research.Framework also relies on globally available datasets for population and locally available datasets for wastewater treatment infrastructure and domestic water use.Model framework was successfully applied to two case study countries, China and Japan, which differ significantly in population density, river flow (due to climate and geography), and wastewater treatment infrastructure. [ABSTRACT FROM AUTHOR]