Using automated on-site monitoring to calibrate empirical models of trihalomethanes concentrations in drinking water

Abstract

An automated, on-site trihalomethanes concentration data set from a conventional water treatment plant was used to optimize powdered activated carbon and pre-chlorination doses. The trihalomethanes concentration data set was used with commonly monitored water quality parameters to improve an empirical model of trihalomethanes formation. A calibrated model was used to predict trihalomethanes concentrations the following year. The agreement between the models and measurements was evaluated. The original model predicted trihalomethanes concentrations within ~10 μg·L−1 of the measurement. Calibration improved model prediction by a factor of three to five times better than the literature model.