25 research outputs found
Probabilistic modelling and evaluation of wastewater treatment plant upgrades in a water quality based evaluation context
No full textProcess choice and dimensioning of wastewater treatment plants (WWTPs) is difficult while ensuring regulatory standards are met and cost-efficiency is maintained. This step only accounts for a small fraction of the upfront costs, but can lead to substantial savings. This paper illustrates the results of a systematic methodology to evaluate system upgrade options by means of dynamic modelling. In contrast to conventional practice, the presented approach allows the most appropriate trade-off between cost of measures and effluent quality to be chosen and the reliability of a process layout to be assessed by means of uncertainty analysis. In a hypothetical case study, thirteen WWTP upgrade options are compared in terms of their effluent quality and economic performance. A further comparison of two options with regard to the resulting receiving water quality reveals the paramount importance of this aspect, and highlights the inadequacy of evaluation frameworks limited to the performance relative to a sub-system (WWTP effluent) when a wider perspective (as induced by the EU Water Framework Directive) has to be adopted
Modelling of priority pollutants releases from urban areas
No full textIn the framework of the EU project ScorePP (Source Control Options for Reducing Emissions of Priority Pollutants), dynamic PPs (priority pollutants) 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 their loads 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 coupling of GIS-based spatial emission source data with temporal emission pattern information and (3) the generation of PP release time series to feed the dynamic sewer catchment model.
Steps 2 and 3 were included as the main features of a dedicated software tool. Finally, this paper also illustrates the method’s applicability to generate model input timeseries for generic pollutants (N, P and COD/BOD) in addition to priority pollutants
Evaluating the usefulness of dynamic pollutant fate models for implementing the EU Water Framework Directive
No full textThe 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
Detailed dynamic pumping energy models for optimization and control of wastewater applications
No full textDespite the increasing level of detail in wastewater treatment process models, oversimplified energy consumption models (i.e. constant 'average' power consumption) are being used in optimization exercises. A new dynamic model for a more accurate prediction of pumping costs in wastewater treatment has been developed to overcome this unbalance in the coupled submodels. The model is calibrated using two case studies. The first case study concerns the centrifugal influent pumps (Nijhuis RW1-400 . 525A) of the municipal wastewater treatment plants (WWTPs) in Eindhoven (The Netherlands), governed by Waterboard De Dommel. For the second case study, concerning a centrifugal pump (Flygt, type NT3153 . 181) of the intermediate pumping station (pumping primary treated wastewater) of the Mekolalde WWTP, located in Bergara (Guipuzcoa, Spain), a model extension was necessary in order to allow a better description of the pump curve, making the model more generic. Both cases showed good agreement between the model predictions and the measured data of energy consumption. The model is thus far more accurate compared with other approaches to quantify energy consumption, paving the way towards 'global' process optimization and new, improved control strategies for energy reduction at WWTPs
Integration of mathematical models in a decision support system for control of priority pollutants in urban catchments
No full textA decision support system (DSS) for systematic control of priority pollutants (PP) sources, based on economic activities and production (release) processes in urban catchments was recently developed. One of the crucial functionalities of the DSS is evaluation of source control measures, which is based on mathematical models, used for simulating the fate of the PPs in urban catchments under different conditions. This work presents a methodology for efficiently building and integrating dynamic mathematical models into the DSS. A combination of two modelling approaches is proposed: empirical or data-driven and mechanistic or knowledge-driven. Data-driven methods, particularly those from the area of machine learning (ML), are proven to build simple and accurate models, but require a lot of measured data for their construction, which is a problem in the case of PP. Mechanistic models can overcome the data requirement problem by integrating expert domain knowledge in the model formulation. However, they tend to be too complex and computationally slow and thus, not appropriate for DSS. Within the proposed methodology a mechanistic dynamic integrated urban water system (IUWS) model for PPs is used independently of the DSS to simulate various scenarios in observed catchment. Simulated data are used by a ML algorithm for induction of rule-based regression model, which performs similarly as the mechanistic model and is integrated in the DSS. The procedure of model construction, integration, and use in the DSS is successfully illustrated based on semi-hypothetical data
