Modeling Bacterial Regrowth and Trihalomethane Formation in Water Distribution Systems

Abstract

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.

Influence of Hydraulic Model Complexity on Results of Water Age and Quality Simulation in Municipal Water Supply Systems

“…Abhijith et al [30] have proven that it is indeed possible to simulate things such as bacterial regrowth and THM formations in water distribution systems. This could be achieved by more complex iteration of EPANET software.…”

Natural Organic Matter Character in Drinking Water Distribution Systems: A Review of Impacts on Water Quality and Characterization Techniques

“…Elevated TOC suggests a high potential for microbial regrowth, and as such a focus on TOC reduction has been demonstrated to be a potent method for controlling bacterial activity. For instance, reducing TOC levels can potentially have a more substantial impact on suppressing bacterial proliferation than maintaining a chlorine residual [81]. However, TOC as a broad measure has limitations in accurately predicting the biodegradable fraction of NOM that directly contributes to microbial growth.…”

Predictive capability of THM models for drinking water treatment and distribution

“…6 Other THM models exist outside of the one used in this research; however they tend to be mechanistic in nature. [40][41][42] Mechanistic models require system-specific parameters for accurate prediction and may not capture the impact of omitted water quality variables on THM formation. For example, reaction rate coefficients have been used in some models to relate changes in water quality variable concentrations to THM formation.…”