Using dynamic alpha factors for oxygen transfer optimization in WRRFs

Due to the importance of wastewater aeration in meeting treatment requirements and due to its elevated energy intensity, it is important to describe the real nature of an aeration system to improve design and specification, performance prediction, and process sustainability. Since high hydraulic loadings drive aeration efficiency to its lowest value when the oxygen demand (energy) is the highest, the implications of dynamic control on energy costs are of utmost importance. A dynamic model aimed at identifying conservation opportunities is presented. The model developed describes the hydraulic loading dependence of the α factor in activated sludge fine-pore aeration. The ASM model structure has been extended to include the dynamic re-calculation of air flow as a function of the load and of the actual (not estimated) oxygen transfer.The model was applied to two water reclamation plants, and was calibrated and validated with time-sensitive databases. Our improved aeration model structure increases the quality of prediction of field data through the recognition of the dynamic nature of the alpha factor as a function of the applied COD concentration. For the cases presented here, the model prediction of air flow improved by 20-35% when dynamic alpha is used. Our results offer a quantitative tool for the prediction of energy demand and for minimizing aeration design uncertainty.