Modeling and Simulation of Pollution Removal Efficiency in Activated Sludge Wastewater Treatment Processes

Water pollution is a growing challenge for the environment and ecosystems, necessitating management of Wastewater Treatment Plants (WWTPs). Modeling the dynamical behaviors of these complex systems significantly affects the control and prediction performance. This study compares the performance of three widely used Activated Sludge Models (ASM1, ASM2, and ASM3) in removing key pollutants, mainly including Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5), Total Suspended Solids (TSS), Total Nitrogen (TN), and Hydrogen potential (pH). Each model of the activated sludge process incorporates unique representation of biological and chemical processes like nitrification, denitrification, and phosphorus removal. The results demonstrate significant differences in the models' stability, sensitivity, and effectiveness under varied operational conditions. The ASM3 benchmark consistently performs well in extreme scenarios, ASM1 shows strong stability, and ASM2 balances efficiency and reliability. These findings provide actionable insights for optimizing WWTP's operations, guiding model selection based on specific treatment objectives.