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In the pursuit of reducing carbon footprint and in view of increasing energy prices, energy efficiency is more important than ever before. Batch-wise operated aerobic granular sludge reactors consume up to 50% less energy compared to conventional activated sludge systems because pumping energy is reduced and mixing equipment is not needed. Further energy reduction efforts should therefore target aeration energy requirements. The alpha factor is an important factor influencing the oxygen transfer efficiency, however the dynamic behaviour of alpha has hardly been investigated in general and never for an aerobic granular sludge reactor. This study showed that alpha increases during the aeration phase of a cycle due to the influence of different process parameters. Through a data analysis study of 175 batch cycles of the Prototype Nereda® installation in Utrecht over the summer and winter period of 2020–2021, the exchange ratio and temperature were identified as the main influencing factors on the rate of increase of alpha in a batch cycle. A higher exchange ratio was related to a slower increase in alpha over the aeration phase, while a higher temperature was related to a faster increase in alpha. Moreover, alpha was characterized by a same minimal value at the beginning of every aeration phase, which could be explained by the adsorption of soluble biodegradable organic carbon described by a Langmuir adsorption model. Two mathematical models, a decreasing exponential and a first order model, were set up to unravel the dynamic behaviour of alpha. Both models were discussed in view of their practical implications for the design and performance optimization of aerobic granular sludge reactors and other batch-wise operated aerobic wastewater treatment systems., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., BT/Environmental Biotechnology

This study deals with the application of data reconciliation to wastewater treatment processes which are subject to dynamic conditions and therefore do not reach a steady-state behaviour sensu stricto. The SHARON partial nitritation process, which is operated cyclically with alternating aerated and anoxic periods, is studied as an example. The collected data long-term dynamic data set was split up into data subsets corresponding with different pseudo-steady-state operations, which allowed a better gross error detection. Mass balances were set up taking into account off-gas measurements besides liquid phase measurements and including kinetic relations between measurements based on the biological conversions in the reactor. As a result, a higher number of variables could be reconciled, more key variables could be identified, and gross error detection was facilitated. In order to draw conclusions on the process performance in a shorter period of operation, e.g., on the N2O emission factor, the average value of the whole data set should be used with caution. The strong dependence of infiltrated air on the aeration regime and gross error in grab sampling (magnitude of 20%) had a substantial impact on calculating N2O emission. It is recommended that the process performance indicators are derived and checked separately for steady state data subsets to guarantee reliable outcomes., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., BT/Design and Engineering Education, BT/Environmental Biotechnology

This chapter provides a review of the models available for estimating the production and emission of methane from wastewater collection and treatment systems. The details of a number of mechanistic models as well as the simplified empirical models have been summarized. Their limitations have been identified and general methods for calibration and validation have been presented., BT/Environmental Biotechnology