Regression models evaluating THMs, HAAs and HANs formation upon chloramination of source water collected from Yangtze River Delta Region, China

Abstract Present study aimed to generate multiple regression models to estimate the formation of trihalomethanes (THMs), haloacetonitriles (HANs) and haloacetic acids (HAAs) during chloramination of source water obtained from Yangtze River Delta Region, China. The results showed that the regression models for trichloromethane (TCM), dichloroacetonitrile (DCAN), dichloroacetic acid (DCAA), dihaloacetic acids (DHAAs), 5 HAAs species regulated by U.S. EPA (HAA 5 ) and total haloacetic acids (HAA 9 ) have good evaluation ability (prediction accuracy reached 81–94%), while the models for total haloacetonitriles (HAN 4 ), trichloroacetic acid (TCAA), trihaloacetic acids (THAAs) and total trihalomethanes (THM 4 ), they appeared relative low prediction accuracy (58–72%). For THMs, dissolved organic nitrogen (DON) was their key organic precursor, yet for HAN, DHAAs and THAAs, UVA 254 played the dominant role. The other key factors influencing DBP formation included the bromide (THM 4 , DHAAs and HAA 9 ), reaction time (DCAN, HAN 4 ), chloramine dose (TCM, DCAA, TCAA, HAA 5 and THAAs). These results provided important information for water works to optimize the water treatment process to control DBPs, and give an evaluating method for DBPs levels when estimating the health risks related with DBP exposure during chloramination.