Estimating bio-kinetics for nitrogen source oxidation processes using online measurements in activated sludge

In-depth understanding of bio-kinetic parameters corresponding to organic and inorganic nitrogen oxidation is essential for the improvement of the operation systems of nitrogen removal in wastewater treatment plants. Researchers have been trying to unravel carbon and nitrogen removal mechanisms in activated sludge for the last two decades by upgrading existing bio-kinetic models to make them capable in explaining the real scenario of substrate biodegradation processes. In most cases, the nitrification models are found to be calibrated assuming constant carbon dioxide transfer rate (CTR) in the model structure, though it is inherently a non-linear process which has an impact on the titrimetric modeling. As a consequence, a complete two-step nitrification model has been developed recently paying attention to organic nitrogen source degradation pathway along with due consideration given for non-linear CTR process occurring in activated sludge system. In this research paper, it is aimed to estimate the nitrification process kinetics for organic nitrogen (urea) and inorganic nitrogen (ammonium) where the recently developed two-step nitrification model was calibrated with experimentally observed on-line measurements. Tests were performed in simple batch reactor equipped with respirometric and titrimetric set-up. For both the urea and ammonium nitrification studies, the bio-kinetic model was calibrated using three different calibration approaches: using respirometric measurements alone, titrimetric measurements alone and combined respirometric-titrimetric measurements. A non-linear technique employing the algorithms in the optimization toolbox included in MATLAB was used during the parameter estimation process. Estimated parameters (both the kinetic and stoichiometric) obtained from all three stated combinations (calibration approaches) were statistically evaluated and compared for confirming the accuracy of model calibration process. Moreover, the relationship between substrate concentration and short-term biochemical oxygen demand (BODst) was checked for the verification of the respirometric method of the nitrification model