Increasing the Accuracy of Energy Footprint Predictions for Activated Sludge Processes Using a Rigorous Dynamic Aeration Model

Aeration modeling is essential not only for insuring the correct nitrification and carbon oxidation, but also for reducing energy costs. Activated sludge models (ASMs) use the oxygen transfer coefficient (kLa) and the dissolved oxygen (DO) at saturation in the DO mass balance to predict oxygen transfer. The oxygen transfer efficiency (OTE) depends on: aeration system type, size and geometry; air flow rate; mixing rates and gradients; diffuser submergence; released bubble size and distribution; diffusers time in operation and consequent fouling and scaling. Moreover, due to the dynamic nature of plant influent load, and the therefore variable air flow rate, OTE is variable over the diurnal and seasonal cycles. Also, due to fouling and scaling, OTE declines with increasing time in operation. These effects are not included in current aeration models and although not crucial for modeling the biochemical processes in the activated sludge, they are necessary to quantify and minimize process energy footprint. Furthermore, it is also expected that this will reduce the need for re-calibration of ASM models. In this contribution, we propose an expanded aeration model by including the dependence of aeration efficiency to the aforementioned design and process parameters. The potential for energy footprint reduction during operation was calculated as the resulting energy savings from minimized excess DO.