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  • Title: Models for predicting carbonaceous disinfection by-products formation in drinking water treatment plants: a case study of South Korea.
    Author: Shahi NK, Maeng M, Dockko S.
    Journal: Environ Sci Pollut Res Int; 2020 Jul; 27(20):24594-24603. PubMed ID: 31243657.
    Abstract:
    Chlorination in a drinking water treatment plant is the critical process for controlling harmful pathogens. However, the reaction of chlorine with organic matter forms undesirable, harmful, and halogenated disinfection by-products. Carbonaceous disinfection by-products, such as trihalomethanes (THMs) and haloacetic acids (HAAs), are genotoxic or carcinogenic and are reported at high concentration in drinking water. This study is aimed at developing a mathematical model for predicting concentration levels of THMs and HAAs in drinking water treatment plants in South Korea because no previous attempts to do so have been reported for the country. The THMs concentration levels ranged from 29 to 39 μg/L, and those for the HAAs from 6 to 7 μg/L. Multiple regression models, i.e., both linear and nonlinear, for THMs and HAAs were developed to predict their concentration levels in water treatment plants using datasets (January 2015 to December 2016) from three treatment plants located in Seoul, South Korea. The constructed models incorporated principal factors and interactive and higher-order variables. The principal factor variables used were dissolved organic carbon, ultraviolet absorbance, residual chlorine, bromide, contact time, chlorine dose and temperature for treated water, and pH for both raw and treated water at the plant. The linear models for both THMs and HAAs were found to give acceptable fits with measured values from the water treatment plants and predictability values were found to be 0.915 and 0.772, respectively. The models developed were validated with a later dataset (January 2017 to July 2017) from the same water treatment plants. In addition, the models were applied to two different water treatment plants. Application and validation results of the constructed model showed no significant differences between predicted and observed values.
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