Evaluating trihalomethane content in drinking water on the basis of common monitoring parameters: regression models.

The presence of trihalomethanes (THMs) in potable-water sources is an issue of great interest because of the negative impact THMs have on human health. The objective of this study was to correlate the presence of trihalomethanes with more routinely monitored parameters of water quality, in order to facilitate THM control. Water samples taken at various stages of treatment from a water treatment plant were analyzed for the presence of trihalomethanes with the Fujiwara method. The data collected from these determinations were compared with the values obtained for free-residual-chlorine and combined-residual-chlorine levels as well as standard physico-chemical and microbiological indicators such as chemical oxygen demand (by the KMnO4 method), total chlorophyll, conductivity, pH, alkalinity, turbidity, chlorides, sulfates, nitrates, nitrites, phosphates, ammonia, calcium, magnesium, heterotrophic bacteria count, Pseudomonas spp., total and fecal coliforms, and fecal streptococci. The data from these determinations were compiled, and statistical analysis was performed to determine which variables correlate best with the presence and quantity of trihalomethanes in the samples. Levels of THMs in water seem to correlate directly with levels of combined residual chlorine and nitrates, and inversely with the level of free residual chlorine. Statistical analysis with multiple linear regression was conducted to determine the best-fitting models. The models chosen incorporate between two and four independent variables and include chemical oxygen demand, nitrites, and ammonia. These indicators, which are commonly determined during the water treatment process, demonstrate the strongest correlation with the levels of trihalomethanes in water and offer great utility as an accessible method for THM detection and control.