Modelling the fate of organic micropollutants in stormwater ponds

Abstract

Urban water managers need to estimate the potential removal of organic micropollutants (MP) in stormwater treatment systems to support MP pollution control strategies. This study documents how the potential removal of organic MP in stormwater treatment systems can be quantified by using multimedia models. The fate of four different MP in a stormwater retention pond was simulated by applying two steady-state multimedia fate models (EPI Suite and SimpleBox) commonly applied in chemical risk assessment and a dynamic multimedia fate model (Stormwater Treatment Unit Model for Micro Pollutants -STUMP). The four simulated organic stormwater MP (iodopropynyl butylcarbamate -IPBC, benzene, glyphosate and pyrene) were selected according to their different urban sources and environmental fate. This ensures that the results can be extended to other relevant stormwater pollutants. All three models use substance inherent properties to calculate MP fate but differ in their ability to represent the small physical scale and high temporal variability of stormwater treatment systems. Therefore the three models generate different results. A Global Sensitivity Analysis (GSA) highlighted that settling/resuspension of particulate matter was the most sensitive process for the dynamic model. The uncertainty of the estimated MP fluxes can be reduced by calibrating the dynamic model against total suspended solids data. This reduction in uncertainty was more significant for the substances with strong tendency to sorb, i.e. glyphosate and pyrene and less significant for substances with a smaller tendency to sorb, i.e. IPBC and benzene. The results provide support to the elaboration of MP pollution control strategies by limiting the need for extensive and complex monitoring campaigns targeting the wide range of specific organic MP found in stormwater runoff.Please cite the published version of this article as: . Modelling the fate of organic micropollutants in stormwater ponds.

Stormwater Ponds in the Southeastern U.S. Coastal Plain: Hydrogeology, Contaminant Fate, and the Need for a Social-Ecological Framework

“…Sedimentation in particular is an important process that protects downstream water quality, and is influenced by pond design (e.g., geometry, forebay or other installation), hydrology (e.g., retention time, potential for short-circuiting), the nature of suspended solids (e.g., allochthonous, autochthonous, and carbon or mineral composition), management activities that impact particle capture (e.g., vegetation planting/control or dredging maintenance), and even storm event-specific characteristics (e.g., hydrograph, wind speed and direction) (Greb and Bannerman, 1997;Anderson et al, 2002;Scholes et al, 2008;Vezzaro et al, 2011;Gold et al, 2017a;Moore et al, 2017). In a study of 14 stormwater wet detention ponds in coastal SC in residential urban and suburban communities, Schroer et al (2018) measured sedimentation rates spanning 0.06-0.5 cm y −1 and detected sequestration of carbon and nitrogen through burial.…”

“…Given the complexity of environmental systems and the number of variables involved, site-specific models may help elucidate wet detention pond function. Knowledge of fate and transport mechanisms has been translated into models that aim to predict pollutant concentrations and loads through stormwater systems to inform engineering and management (Elliot and Trowsdale, 2007;Vezzaro et al, 2011Vezzaro et al, , 2012Fletcher et al, 2013;Bell et al, 2019). However, it has been reviewed that improvement of biophysical models will require more monitoring data for calibration and field testing, and improved understanding of fate processes and management outcomes for a wider selection of environmental contaminants (Bertrand-Krajewski, 2007;Elliot and Trowsdale, 2007;Gold et al, 2019).…”

Evaluation of stormwater micropollutant source control and end-of-pipe control strategies using an uncertainty-calibrated integrated dynamic simulation model

“…2 ensures a reduction of the uncertainty in the results of the STUMP submodel in situations when TSS measurements are available but MP data are scarce. (Vezzaro et al, 2011).…”

Dynamic Transport and Fate Models for Micro-pollutants in Integrated Urban Wastewater Systems

“…Eriksson et al, 2007;Lützhøft et al, 2008). More details on this study can be found in Vezzaro et al (2009).…”