Modeling of organic substrate transformation in the high-rate activated sludge process.

This study describes the development of a modified activated sludge model No.1 framework to describe the organic substrate transformation in the high-rate activated sludge (HRAS) process. New process mechanisms for dual soluble substrate utilization, production of extracellular polymeric substances (EPS), absorption of soluble substrate (storage), and adsorption of colloidal substrate were included in the modified model. Data from two HRAS pilot plants were investigated to calibrate and to validate the proposed model for HRAS systems. A subdivision of readily biodegradable soluble substrate into a slow and fast fraction were included to allow accurate description of effluent soluble chemical oxygen demand (COD) in HRAS versus longer solids retention time (SRT) systems. The modified model incorporates production of EPS and storage polymers as part of the aerobic growth transformation process on the soluble substrate and transformation processes for flocculation of colloidal COD to particulate COD. The adsorbed organics are then converted through hydrolysis to the slowly biodegradable soluble fraction. Two soluble substrate models were evaluated during this study, i.e., the dual substrate and the diauxic models. Both models used two state variables for biodegradable soluble substrate (SBf and SBs) and a single biomass population. The A-stage pilot typically removed 63% of the soluble substrate (SB) at an SRT <0.13 d and 79% at SRT of 0.23 d. In comparison, the dual substrate model predicted 58% removal at the lower SRT and 78% at the higher SRT, with the diauxic model predicting 32% and 70% removals, respectively. Overall, the dual substrate model provided better results than the diauxic model and therefore it was adopted during this study. The dual substrate model successfully described the higher effluent soluble COD observed in the HRAS systems due to the partial removal of SBs, which is almost completely removed in higher SRT systems.