The aerobic granular sludge (AGS) process treats wastewater with a significantly lower footprint and energy consumption compared to conventional activated sludge systems. Nevertheless, there is still potential for optimizing its performance, and mathematical models are most valuable tools to this end. Aeration energy consumption deserves particular attention, as it is the largest remaining operating cost for AGS systems. Batch-wisely operated reactors show an increasing oxygen transfer efficiency during aeration, which translates into a dynamic alpha factor. However, the dynamic nature of alpha is neglected in current models. The impact of this simplification on the operating performance was addressed for the first time in this study. Through the development of a novel 1-D biofilm reactor model, calibrated to a full-scale AGS plant, it was shown that the alpha dynamics affect both model structure and calibration, as well as the process performance. The description of the dynamic nature of alpha through the empirical relationship with the soluble biodegradable organic carbon required the addition of the state variable representing soluble slowly biodegradable organic carbon (S_CB) to the biokinetic ASM2d model. Simulation results showed that alpha dynamics significantly influences simultaneous nitrification and denitrification and therefore need to be included in mathematical models to optimize AGS process performance. Different process variables such as volume exchange ratio, aeration capacity and granule size can be manipulated to improve reactor design and performance. The practical application of these new insights were discussed regarding the optimization of AGS systems, as well as other batch-wisely operated aerobic wastewater treatment systems.

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.