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Nowadays a wastewater treatment plant (WWTP) is not only expected to remove traditional pollutants from the wastewater; other emerging challenges have arisen as well. A WWTP is now, among other things, expected to also minimise its carbon footprint and deal with micropollutants. Optimising the performance of a WWTP can be done with mathematical models that can be used in simulation studies. The Benchmark Simulation Model (BSM) framework was developed to compare objectively different operational/control strategies. As different operational strategies of a WWTP will most likely have an effect on the greenhouse gas (GHG) emissions and the removal rate of micropollutants (MPs), modelling these processes for dynamic simulations and evaluation seems to be a promising tool for optimisation of a WWTP. Therefore, in this thesis the BSM is upgraded with processes describing GHG emissions and MPs removal. Regarding GHGs emissions, the focus is placed on the production of nitrous oxide (N2O). As micropollutants comprise a wide range of chemicals, pharmaceuticals are selected here as specific examples to be studied. Different nitrification models containing N2O producing processes are tested and used for an extension of the BSM. Various challenges were encountered regarding the mathematical structure and the parameter values when expanding the BSM. The N2O models produced different results due to the assumptions on which they are based. In addition, pH and inorganic carbon concentrations have been demonstrated to significantly influence the nitrification. Therefore a physicochemical model in combination with a N2O model is calibrated with data from a full‐scale sequencing batch reactor (SBR) to gain insight into the N2O production pathways. Most likely the pathways of nitrifier denitrification and hydroxylamine oxidation alternated during the nitrification phase in the SBR. The BSM framework is also extended with the occurrence, transport and fate of pharmaceuticals. The occurrence is modelled with a phenomenological approach for pharmaceuticals, including a daily pattern and a stochastic approach for pharmaceuticals with a more random occurrence. Different sewer conditions demonstrated effects on the occurrence of the pharmaceuticals as influent patterns at the inlet of the WWTP were smoothed or delayed. The fate in the WWTP showed that operational conditions can influence the biotransformation, retransformation and sorption rates. In addition, inhibition and co‐metabolic effects can have opposite effects on the removal rates. A phenomenological influent generator has been successfully calibrated with high frequency data for traditional variables and data on the occurrence of pharmaceuticals and metabolites. The excretion pathways as well as in‐sewer transformation processes proved to be of importance when calibrating the daily patterns. Upgrading the BSM framework with these calibrated models can help to optimise the performance of a WWTP by not only taking operational costs and effluent quality into account, but also by including the GHG emissions and removal rates of pharmaceuticals.
|Place of Publication||Kgs. Lyngby|
|Publisher||Technical University of Denmark|
|Number of pages||164|
|Publication status||Published - 2015|