Because of an increasing need to balance health risks for pathogen control and disinfection by-product (DBP) formation in water supplies, utilities are forced to closely examine and optimize their disinfection practices. The authors provide a simple mechanistic model to predict total trihalomethane (TTHM) and the sum of nine haloacetic acids (HAA9) formation based on chlorine demand. To evaluate this modeling approach, eight Missouri surface waters (raw and alum-treated) were used in DBP formation and chlorine decay kinetic studies. A parallel first-order reaction model was used to fit the chlorine decay data, and the model coefficients were used to predict THM and HAA formation.Yield coefficients for TTHMs and HAA9 were obtained from fitting the DBP kinetic data. On average, the TTHM and HAA9 yield coefficients for all raw surface waters tested were about 40 µg TTHM/mg Cl 2 and 25 µg HAA9/mg Cl 2 consumed, respectively. In waters subjected to alum coagulation, the average TTHM and HAA9 yield coefficients were 30 µg TTHM/mg Cl 2 and 17 µg HAA9/mg Cl 2 consumed, respectively. The DBP predictive model introduced in this study provided a simple, reliable basis to evaluate treatment options by focusing on chlorine demand. This model can be readily calibrated to local conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.