Optimization of the Anaerobic-Anoxic-Oxic Process by Integrating ASM2d with Pareto Analysis of Variance and Response Surface Methodology

Abstract

Wastewater treatment plants (WWTPs) are high-energy-consuming units. Reasonable operation strategies can enable WWTPs to meet discharge standards while reducing the operating cost. In this study, the activated sludge model 2d (ASM2d), Pareto analysis of variance (ANOVA), and response surface methodology (RSM) were jointly used to simulate and optimize the operation of a lab-scale anaerobic-anoxic-oxic (AAO) reactor. The optimization objective was to determine the optimal design and operational parameters (DOPs) that could enhance both pollutant removal and energy saving. The DOPs that had significant influence on the optimization objective, such as sludge retention time (SRT), dissolved oxygen (DO), and the ratio of biodegradable chemical oxygen demand to total nitrogen (BCOD/TN), were identified by Pareto ANOVA. The optimal DOPs with SRT of 15 days, DO concentration of 0.5 mg/L, and BCOD/TN of 5.21 were determined by RSM. Under the optimal conditions, the removal efficiencies of NH4+-N, total nitrogen (TN), and total phosphorus (TP) were 96.2%, 76.8%, and 92.8%, respectively, and the annual operating cost was $26.4. Furthermore, this combination of DOPs was validated using a pilot-scale AAO system. The TN and TP removal efficiencies were improved by 11.0% and 5.0%, respectively, and the annual operating cost could be reduced by 15.0%. Overall, this study confirmed that the method integrating ASM2d with Pareto ANOVA and RSM was effective in optimizing wastewater treatment processes.