Characterizing the emissions and impact of combined sewer overflows (CSOs) remains one of the key challenges in the field of urban wastewater. Considering the large number of existing CSOs, decision-makers need a pragmatic approach that allows fairly easy, hands-on determination of emissions (particularly loads) without compromising accuracy. This philosophy is incorporated in the Cockle tool presented here, which uses stochastically processed input from a vast amount of pre-registered water quality data (pollutant concentrations) in combination with spill flow time series either generated from hydrodynamic models or converted from monitored overflow water levels. Uncertainty is intrinsically covered by the statistical output range of the reported results. As a fully automated tool, Cockle allows to readily assess emissions within a chosen time frame, facilitating more accurate guidance for further remediation actions and/or mapping of the current state for operational follow-up.

Stormwater runoff is often discharged untreated into receiving waters, a process that is widely recognized as a threat to water quality. To protect water bodies, tools are needed to assess the risk of urban runoff pollution. In this work, a new tool is presented that can be used to model the concentration of the most frequent pollutants in urban runoff, i.e., Zn, Cu, Pb, PAH(1)6, TN, and TP, based not only on the surface type but also on other inputs such as the amount of traffic or the building type. The tool also includes a simple model to evaluate the impact of different SUDS types. The water quality model was evaluated by measurement campaigns in separate sewer systems of a few small catchments in Flanders. The model was able to reproduce the observed time-dependent spread in concentrations in a satisfactory manner. Furthermore, the model also allowed for the attribution of differences in heavy metal concentrations in catchments very similar to the building types. These are clear improvements compared to previous model approaches.

The problems that arise from hydrogen sulfide formation in sewer rising mains are often dealt with by adding chemicals. The most commonly used chemicals are sodium hydroxide and magnesium hydroxide, ferric (or ferrous) chloride, calcium nitrate and oxygen. As there is a lack of tools to evaluate and compare dosing strategies, it is hard to identify the most appropriate dosing chemical in terms of investment and operating costs. As a consequence, chemical selection is often done ad-hoc. In this study, the average dosing costs (operating and capital) of these chemicals is assessed by simulations with a dynamic mathematical model, describing the transformations of sulfide, carbon and nitrogen in a sewer rising main. Based on the results of the simulations, and other parameters, a systematic approach to selecting dosing products for sewer rising mains is outlined.