Mechanistic Model of Copper Sorption in Engineered Stormwater Filtration Media

Abstract Submission: Knowledge of the capacity of engineered filtration media to remove pollutants is critical for watershed managers seeking to achieve water quality objectives via stormwater control measures. Despite direct implications for the health of downstream receiving waters, water quality modeling of stormwater control measures has lagged behind hydrologic modeling in terms of mechanistic approaches to quantifying pollutant removal and predicting pollutant concentrations in treated effluent. Herein, a mechanistic water quality model, OpenHydroQual, is used to simulate sorption of dissolved copper to generate event-based effluent event mean concentrations and measure the long-term pollutant removal capacity of four engineered media blends. The model was identified as being one of few programs that couple deterministic hydrology with dynamic water quality simulation. The modeled media blends were composed of sand mixed with either a biochar, regenerated activated carbon, or a zeolite representing a wide range of physio-chemical properties, such as cation exchange capacity (CEC), hypothesized to be key factors influencing copper sorption. Sorption aspects of the model were calibrated to laboratory column experiments using artificial stormwater spiked with copper at a concentration representative of urban runoff, and the model was able to represent the experimentally derived breakthrough curve with r2 > 0.9. The OpenHydroQual model improves first-order decay approximations or extrapolations from monitoring data by directly representing the physical processes at play between infiltrating runoff and solid phase filtration media. The next steps for this research are to validate the copper sorption model against field monitoring data and to evaluate it for other contaminants of concern.

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