Prediction of pharmaceuticals removal in activated sludge system under different operational parameters using an extended ASM-PhACs model

Abstract

Removal of pharmaceuticals is essential in wastewater treatment systems due to their release and accumulation in the environment, which are raising issues for the environment and human health. A mathematical model could be used to predict pharmaceuticals removal under various operational parameters and assess the contributions of different removal pathways to pharmaceuticals removal. Here an ASM-PhACs model was established to describe pharmaceuticals removal including diclofenac (DCF), erythromycin (ERY), gemfibrozil (GEM) and carbamazepine (CBZ) removal in activated sludge system. The pharmaceuticals removal processes linked to co-metabolic biodegradation through the growth of ammonia oxidizing bacteria (AOB), metabolic biodegradation through AOB, metabolic biodegradation through heterotrophic bacteria (HB) and sludge adsorption were incorporated into activated sludge model (ASM1) framework. The kinetic equations were established for each pharmaceuticals removal process. To provide the experimental data for model calibration and validation, two sets of batch tests were designed and conducted in the laboratory scale using SBR technology. According to the batch test data and results of sensitivity analysis, the newly added parameters and some original default parameters affecting pharmaceuticals removal processes were screened and calibrated. The model could accurately simulate all the dynamics of chemical oxygen demand, nitrogen and pharmaceuticals under various conditions. To explore the effect of operational parameters on pharmaceuticals removal efficiency, the wide range of operational parameters was analyzed during model simulation. According to the simulation results, both influent NH4+-N concentration and DO were found to be the significant parameters that impact the removal of DCF, ERY and GEM. AOB biodegradation played an important role in DCF, ERY and GEM removal. The developed model framework helps to investigate the removal mechanisms and key influencing factors of pharmaceuticals removal, thus providing guidelines for reactor design, operation and optimization aiming at pharmaceuticals removal.