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.
"Solutions found for situation 3: engineer would like to characterize the uncertainty of the quantity and quality of the influent wastewater The necessity of characterizing the uncertainty around the expected influent data profiles has been repeatedly outlined (Friedler and Butler, 1996; Bixio et al., 2002; Benedetti et al., 2008; Gevaert et al., 2009). However, the difficulty of analysing the uncertainty in real data sets (Friedler and Butler, 1996), the short history of uncertainty analysis in water quality modelling (Belia et al., 2009), and the lack of stochastic formulations of biochemical models (Reichert and Mieleitner, 2009) have not yet given rise to standard methodologies with this in mind. "
[Show abstract][Hide abstract] ABSTRACT: This paper makes a critical review of the available techniques for analysing, completing and generating influent data for WWTP modelling. The solutions found in literature are classified according to three different situations from engineering practice: 1) completing an incomplete dataset about the quantity and quality of the influent wastewater; 2) translating the common quality measurements (COD, TSS, TKN, etc.) into the ASM family components (fractionation problem); 3) characterising the uncertainty in the quality and quantity of the influent wastewater. In the first case (Situation 1), generators based on Fourier models are very useful to describe the daily and weekly wastewater patterns. Another specially promising solution is related to the construction of phenomenological models that provide wastewater influent profiles in accordance with data about the catchment properties (number of inhabitant equivalents, sewer network, type of industries, rainfall and temperature profiles, etc.). This option has the advantage that using hypothetical catchment characteristics (other climate, sewer network, etc.) the modeller is able to extrapolate and generate influent data for WWTPs in other scenarios. With a much lower modelling effort, the generators based on the use of databases can provide realistic influent profiles based on the patterns observed. With regard to the influent characterisation (Situation 2), the WWTP modelling protocols summarise well established methodologies to translate the common measurements (COD, TSS, TKN, etc.) into ASM family components. Finally, some statistical models based on autoregressive functions are suitable to represent the uncertainty involved in influent data profiles (Situation 3). However, more fundamental research should be carried out to model the uncertainty involved in the underlying mechanisms related to the wastewater generation (rainfall profiles, household and industries pollutant discharges, assumed daily and weekly patterns, etc.). (C) 2014 Published by Elsevier Ltd.
"Models help identifying measures to achieve a target ecological status, by taking into account possible management options (Kersebaum et al. 2003; Chaplot et al. 2004; Lohmann et al. 2007; Krause et al. 2008; Volk et al. 2009; Scheringer 2009). For example, Brock et al. (2006) assessed ecological protection goals for pesticides risk in surface waters and proposed considering multiple emission scenarios when evaluating ecotoxicological effects in support of EU policies; Zukowska et al. (2005) modeled fate and transport of selected POPs in the Vistula catchment investigating different scenarios of economic development and regulations; Gevaert et al. (2009) discussed scenarios to illustrate the usefulness of models in the implementation of the WFD for 2 priority substances in representative Western European rivers; Holzkämper et al. (2012) proposed the integrated catchment management as a tool to evaluate management options under high complexity and uncertainty; Volk et al. (2009) assessed river water quality depending on land‐use scenarios; the risk of chemicals has been considered for the Mediterranean region under crop‐specific (Ramos et al. 2007) and water scarcity (Petrovic et al. 2011) scenarios. However, the above studies conducted evaluations of policy alternatives with reference to limited areas or specific conditions, whereas it is increasingly important to extend assessments of chemicals over broad policy target areas such as the whole EU or the European continent. "
"Yet, the lack of other long-term online datasets of full-scale nitrous oxide emission makes it impossible to assess to what extent the tremendous variability at Kralingseveer is generally applicable . In two other water-related fields, this lack of data was countered by testing different monitoring scenarios against simulated data from dynamic models of the presence of pollutants in sewers Ort and Gujer (2006) and water bodies Gevaert et al. (2009). For nitrous oxide emission, a reliable mechanistic model that is able to describe the dynamics of nitrous oxide emission from full-scale WWTPs is not available (yet). "
[Show abstract][Hide abstract] ABSTRACT: In the last few years, the emission of nitrous oxide from wastewater treatment plants has become a topic of increased interest, given its considerable impact on the overall climate footprint of wastewater treatment plants. Various sampling strategies to estimate nitrous oxide emission from wastewater treatment plants have been applied in different studies. The present study addresses the influence of sampling strategies on the estimated emission by analysing the variability of an extensive dataset of nitrous oxide emissions resulting from a long-term online monitoring campaign at a full-scale municipal wastewater treatment plant. It is shown that short-term sampling is inadequate to accurately estimate the average nitrous oxide emissions from a particular wastewater treatment plant, while online monitoring is indispensable to capture the short-term variability (diurnal dynamics).
Water Research 03/2013; 47(9). DOI:10.1016/j.watres.2013.03.016 · 5.53 Impact Factor
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