Systematic evaluation of a dynamic sewer process model for prediction of odor formation and mitigation in large-scale pressurized sewers in Hong Kong.

To evaluate and mitigate odor formation and emission in sewers, several sewer models have been developed. Although these models can predict the immediate effects of chemical dosing on odor emission control, the long-term effects due to the variation of biofilm dynamics were generally underestimated. Therefore, in this study, we developed a dynamic model to simulate sewer processes initiated by sewer. The dynamic sewer process model was calibrated and validated with experimental data collected from two pressurized mains in actual operation in Hong Kong (TCS and MH17). The results show that the dynamic model can satisfactorily predict the dynamic concentrations of sulfide and ammonium (with measured and simulated values differing by less than 6%). The model was employed to systematically assess the long-term effects of three commonly used control strategies, i.e. addition of nitrate salts, addition of biocides, and hydraulic flushing, on sulfide formation and to predict sewer biofilm compositions. The modeling results reveal that the effect of odor mitigation measures on sulfide control varied with time due to the re-establishment of sulfate-reducing bacteria community in sewer biofilm. The long-term effect of nitrate addition would be diminishing because of the growth of heterotrophic denitrifies in sewer biofilms (increased from 7% to 21% after 55 days of nitrate addition) to consumed more nitrate. After dosing biocide or hydraulic flushing in sewers, sulfide production would rebound in the following several days due to the regrowth of sewer biofilms, indicating that the optimization of odor mitigation strategies is necessary. This study highlights that the biofilm dynamics shall be involved in the simulation of odor formation and emission, to evaluate and optimize the long-term effects of mitigation measures.