Veerle Gevaert

An emission time series generator for pollutant release modelling in urban areas

Dynamic priority pollutant (PP) fate models are being developed to assess appropriate strategies for limiting the release of PPs from urban sources and for treating PPs on a variety of spatial scales. Different possible sources of PP releases were mapped and both their release pattern and release factors were quantified as detailed as possible. This paper focuses on the link between the gathered PP sources data and the dynamic models of the urban environment. This link consists of (1) a method for the quantitative and structured storage of temporal emission pattern information, (2) the retrieval of spatial emission source data from a GIS covering the studied urban area, (3) the coupling of the (GIS-based) spatial emission source data with temporal emission pattern information and (4) the generation of PP release time series to feed the dynamic sewer catchment model. Steps 3 and 4 were included as the main features of a dedicated software tool. Finally, this paper also illustrates the methods applicability to generate model input time series for generic pollutants (N, P and COD/BOD) in addition to priority pollutants.

SWAT developments and recommendations for modelling agricultural pesticide mitigation measures in river basins

Abstract Pesticides are useful for agriculture because of their ability to protect crops against pests. At the same time, excessive loading of pesticides in water bodies can produce toxic conditions that harm sensitive aquatic species, and render the water unfit for human consumption. Therefore, measures need to be designed, evaluated and undertaken in order to reduce pesticide pollution. In this study we focus on the Nil catchment, a small basin situated in the centre of Belgium. The necessary database and a watershed model (Soil and Water Assessment Tool—SWAT) were available to simulate different agricultural management scenarios. In order to make the model accurately predict pesticide loading to the river and instream transport, it was necessary to make several modifications to the source code. Special attention was given to implement an estimator for point losses (e.g. cleaning of spray equipment) and droplet drift, and improve the representation of physical processes in filter strips. The closing of mass balances is also described. Once the model was modified and calibrated, it could be used to simulate the pesticide mitigation strategies and evaluate their effectiveness. The simulation results revealed that strip-cropping seems to be more efficient than the sowing of cover crops, contour farming, the construction of filter strips, a 40% reduction of point losses and finally conservation agriculture. Several recommendations are given for further improvement of SWAT for management use.

Evaluating the usefulness of dynamic pollutant fate models for implementing the EU Water Framework Directive

The European Water Framework Directive (WFD) aims at achieving a good ecological and chemical status of surface waters in river basins by 2015. The chemical status is considered good if the Environmental Quality Standards (EQSs) are met for all substances listed on the priority list and eight additional specific emerging substances. To check compliance with these standards, the WFD requires the establishment of monitoring programmes. The minimum measuring frequency for priority substances is currently set at once per month. This can result in non-representative sampling and increased probability of misinterpretation of the surface water quality status. To assist in the classification of the water body, the combined use of monitoring data and pollutant fate models is recommended. More specifically, dynamic models are suggested, as possible exceedance of the quality standards can be predicted by such models. In the presented work, four realistic scenarios are designed and discussed to illustrate the usefulness of dynamic pollutant fate models for implementing the WFD. They comprise a combination of two priority substances and two rivers, representative for Western Europe.

A model library for dynamic transport and fate of micropollutants in integrated urban wastewater and stormwater systems

The increasing efforts in reducing the emission of micropollutants (MP) into the natural aquatic environment require the development of modelling tools to support the decision making process. This article presents a library of dynamic modelling tools for estimating MP fluxes within Integrated Urban Wastewater and Stormwater system (IUWS - including drainage network, stormwater treatment units, wastewater treatment plants, sludge treatment, and the receiving water body). The models are developed by considering the high temporal variability of the processes taking place in the IUWS, providing a basis for the elaboration of pollution control strategies (including both source control and treatment options) at the small spatial scale of urban areas. Existing and well-established water quality models for the different parts of the IUWS (e.g. ASM models) are extended by adding MP fate processes. These are modelled by using substance inherent properties, following an approach commonly used in large-scale MP multimedia fate and transport models. The chosen level of complexity ensures a low data requirement and minimizes the need for field measurements. Next to a synthesis of model applications, a didactic example is presented to illustrate the potential of the use of the developed model library for developing, evaluating and comparing strategies for reduction of MP emissions from urban areas. Display Omitted We created a model library for dynamic modelling of micropollutant fluxes in cities.The IUWS_MP model library includes sewer, treatment options and receiving waters.IUWS_MP combines existing models for evaluating pollution control strategies.Dynamic modelling allows estimation of both MP fluxes and concentrations.A didactic example showing the potential of the developed tool is presented.

A scenario analysis for reducing organic priority pollutants in receiving water using integrated dynamic urban fate models.

The Water Framework Directive (WFD) has the objective of a catchment-oriented water quality protection for all European waters with the purpose of achieving a good ecological and chemical quality status by the year 2015. To that end, necessary measures should be identified and implemented, with the aim of progressively reducing pollution from priority substances. The objective of this paper is to demonstrate how a dynamic model of the integrated urban wastewater system (IUWS) can be used to test different emission reduction strategies for organic priority pollutants (PPs) in a semi-hypothetical case study on di(2-ethylhexyl)phthalate (DEHP). The IUWS is composed of coupled entities: sources, urban catchment surface (run-off/infiltration), sewer system, stormwater treatment unit, wastewater treatment plant (WWTP) including sludge handling, and receiving surface water (river). State-of-the-art dynamic fate models were selected from literature and extended with an organic pollutant fate sub-model. Dynamic DEHP release profiles were estimated using a dynamic model input generator and fed to the model to predict the fate and concentration of DEHP in each IUWS sub-system. The model was then used to test eight scenarios on environmental performance, namely (1) reduction of impervious urban area, (2) reduction of infiltration in the sewer system, (3) input reduction (excluding the main pollutant sources), (4) separating the combined sewer system, (5) treatment of stormwater by stormwater infiltration ponds (separate sewer systems), (6) placement of retention basins at main sewer junctions, (7) sand filtration of secondary effluent, and (8) pre-precipitation of phosphorous. The simulation results revealed that the most effective measure in terms of river water quality improvement for DEHP (annual average and spikiness reduction) and PP concentration in the disposed WWTP sludge, is reducing release of this substance into the environment, not surprisingly. In general, this will heavily depend on the parameterisation of the scenarios.