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  • Title: Investigating the role of biofilms in trihalomethane formation in water distribution systems with a multicomponent model.
    Author: Abokifa AA, Yang YJ, Lo CS, Biswas P.
    Journal: Water Res; 2016 Nov 01; 104():208-219. PubMed ID: 27525584.
    Abstract:
    Biofilms are ubiquitous in the pipes of drinking water distribution systems (DWDSs), and recent experimental studies revealed that the chlorination of the microbial carbon associated with the biofilm contributes to the total disinfection by-products (DBPs) formation with distinct mechanisms from those formed from precursors derived from natural organic matter (NOM). A multiple species reactive-transport model was developed to explain the role of biofilms in DBPs formation by accounting for the simultaneous transport and interactions of disinfectants, organic compounds, and biomass. Using parameter values from experimental studies in the literature, the model equations were solved to predict chlorine decay and microbial regrowth dynamics in an actual DWDS, and trihalomethanes (THMs) formation in a pilot-scale distribution system simulator. The model's capability of reproducing the measured concentrations of free chlorine, suspended biomass, and THMs under different hydrodynamic and temperature conditions was demonstrated. The contribution of bacteria-derived precursors to the total THMs production was found to have a significant dependence on the system's hydraulics, seasonal variables, and the quality of the treated drinking water. Under system conditions that promoted fast bacterial re-growth, the transformation of non-microbial into microbial carbon DBP precursors by the biofilms showed a noticeable effect on the kinetics of THMs formation, especially when a high initial chlorine dose was applied. These conditions included elevated water temperature and high concentrations of nutrients in the influent water. The fraction of THMs formed from microbial sources was found to reach a peak of 12% of the total produced THMs under the investigated scenarios. The results demonstrated the importance of integrating bacterial regrowth dynamics in predictive DBPs formation models.
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