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.

A low-cost automated titration system for colorimetric endpoint detection

“…The Bland-Altman plot 36,37 for raw water (Fig. 5A) has difference scattered around the mean difference with no sign of a proportional difference.…”

“…The average difference (auto titratormanual) between the two methods was found to be −1.2 ± 4.6 mg L −1 CaCO 3 in raw and −0.6 ± 4.6 mg L −1 CaCO 3 in finished water. The Bland-Altman plot 36,37 for raw water (Fig. 5A) has difference scattered around the mean difference with no sign of a proportional difference.…”