Raw water with natural organic matters produces a variety of halogenic organic compounds after liquid chlorine or sodium hypochlorite disinfection

known as disinfection by-products (DBPs). Among them

the generation of trichloromethane (TCM) has attracted extensive attention. Factors affecting its formation including the organic content

pH

water temperature

chlorine dosage

disinfection contact time

and so on. According to survey

the scale of the water treatment plants in many cities and counties in northeast China is mainly small with a daily production capacity of less than 50 000 t/d. Moreover

due to the problems of testing capability and cost

it is impossible to detect TCM continuously in effluent water

and once the raw water quality changes

the safety of the effluent water quality will not be guaranteed. Therefore

the establishment of the prediction model between TCM and conventional parameters will help water treatment plants with no TCM detection abilities to predict the generation of TCM. In this study

taking a large water treatment plant in northeast China as an example

the contents of each parameter were detected using national standard methods. With the method of multiple linear regression analysis

the parameters which concern with the characteristics of raw water and disinfection processes

such as water temperature

pH

turbidity

potassium permanganate index

and chlorine dose

were added to the establishment of the TCM generation model. The multiple regression model provides a good prediction method for the generation of TCM in small and medium-sized water treatment plants with similar raw water characteristics and disinfection processes.