Multiple regression models: a methodology for evaluating trihalomethane concentrations in drinking water from raw water characteristics

Abstract

The presence of trihalomethanes (THMs) in drinking water has attracted the attention of both researchers and professionals, because of the harmful effects of these substances on human health. A multiple regression model was developed to estimate THM concentrations in finished drinking water, using data from the Menidi Treatment Plant of Athens. A number of routinely measured characteristics--including chlorine dose, chlorophyll a, temperature, pH and bromide--of raw water, were used to generate a reliable methodology for predicting both total THM and individual species concentrations. Seasonality effects were also considered during the analysis. In general, these models were found to give acceptable fits, estimating accurately lows and highs over the annual cycle.