Modelling the removal of micropollutants (MPs) in stormwater treatment systems is essential in a context that is characterized by a general lack of measurements. This paper presents an innovative dynamic model for the prediction of the removal of MPs in stormwater treatment systems (Stormwater Treatment Unit model for Micro Pollutants—STUMP). The model, based on a conceptual model of two-compartment (water and sediment) serial Continuous Stirred-Tank Reactors (CSTRs), can predict the fate of MPs based on their inherent properties, which are often the only information available regarding this kind of substances. The flexible structure of the model can be applied to a wide range of treatment units and substances. Based on the most relevant removal processes (settling, volatilization, sorption, biodegradation, and abiotic degradation), the model allows the dynamic simulation of the MP behaviour in the different compartments of stormwater treatment systems. The model was tested for heavy metals (copper and zinc) and organic substances (benzene and di(2-ethylhexyl)phthalate). The results show that volatilization plays a big role for removal of benzene while the removal of substances with high sorption capacity is mainly driven by settling. The model was proven to be able to predict the importance of the various fate processes for selected substances with different inherent properties. A thorough assessment of the influence of the various fate process parameters will allow a reliable assessment of the treatment performances for a wide range of MPs.
Keywords: best management practice, fate processes modelling, micropollutants, stormwater treatment, surface runoff