Development and interpretation of disinfection byproduct formation models using the Information Collection Rule database

Multiple linear regression models were used to examine relationships between water quality, treatment, and disinfection byproduct (DBP) formation in Information Collection Rule field data. Finished water models were specified using a cross-validation approach based on data for 225 free chlorine treatment plants. Turbidity, bromide, temperature, alkalinity, total organic carbon, ultraviolet absorbance at 254 nm, pH, chlorine residual, chlorine consumed, and chlorine contact time were employed as independent variables. Important trends within the trihalomethane, dihaloacetic acid, and trihaloacetic acid classes were observed. Bromide was a significant predictor for all DBP species and its influence changed in sign and magnitude with the extent of bromine substitution. A similar pattern followed by alkalinity suggested it plays an important role as an indicator of natural organic matter hydrophobicity and reactivity. Chlorine consumed and organic precursor variables were significant predictors in almost all DBP species models, exhibiting trends opposite to those for alkalinity and bromide. Temperature was the most significant variable in chloroform and chloral hydrate models and its significance declined with increasing bromine substitution within the trihalomethane class. pH had a strong positive influence on chloroform formation, a negative influence on trihaloacetic acid formation, and no influence on dihaloacetic acid formation.