High Spatiotemporal Model-Based Tracking and Environmental Risk-Exposure of Wastewater-Derived Pharmaceuticals across River Networks in Saxony, Germany

Abstract

Wastewater treatment plants represent relevant point sources of environmental-adverse pharmaceuticals in river systems. Extensive monitoring and substance-routing models are crucial for environmental risk assessment and river planning. However, most current models assume long-term and large spatial averaged values of pharmaceutical consumption and river discharge flows. This study describes a detailed tracking of pharmaceutical occurrence across river networks with high spatiotemporal resolution to assist better environmental risk assessments. Using high spatiotemporal prescription data of four (pseudo-) persistent pharmaceuticals and river discharge characterization, an adjusted graph-theory-based model was implemented to efficiently evaluate the impact of the effluents of 626 wastewater treatment plants across nine river networks located in Saxony, Germany. Multisite calibration results demonstrated the model capability to satisfactorily predict daily pharmaceutical loads and concentrations with high spatial discretization. Based on minimal river dilution and mean predicted concentrations, the risk exposure revealed carbamazepine and ciprofloxacin as the most critical pharmaceuticals and Vereinigte Mulde as the most risk-exposed river network with up to 34.0% and 23.7% of its river length exceeding half and the total of ecotoxicological criteria, respectively. In comparison, other river networks showed less than 23.5% and 15.0% of their river lengths exceeding half and the total of ecotoxicological criteria of all four selected pharmaceuticals, respectively.

Keywords

• wastewater-derived pharmaceuticals
• river monitoring and modeling
• substance-flow routing
• graph theory
• environmental risk assessment