Objectives The correlations between methylbenzene pollution and pH, turbidity, residual chlorine, electrical conductivity and total organic carbon (TOC) of on-line monitoring indices of drinking water were analyzed in order to screen effective indices of on-line monitoring and to establish the pollution concentration prediction model.

Methods The method of adding standard substance in laboratory was used to analyze the correlations between methylbenzene pollution and the drinking water on-line monitoring indices. Five different doses of methylbenzene from low to high concentrations (0.35~5.6) mg/L were added respectively. A multivariate linear regression model was further established to predict the methylbenzene pollution concentration in drinking water.

Results There was a negative correlation between methylbenzene and total organic carbon difference value(R=-0.526 7, P=0.043 6). There were no significant correlations between methylbenzene and pH, turbidity, residual chlorine as well as electrical conductivity difference values(P>0.05). The multivariate linear regression model for predicting the methylbenzene pollution concentration in drinking water was expressed as y=0.09-13.949x₁-11.233x₂-5.642x₃(y=methylbenzene concentration estimated value; x₁=pH difference value; x₂=residual chlorine difference value; x₃=total organic carbon difference value).

Conclusions The pollution concentration prediction may be realized by using the multivariate linear regression model in case of the methylbenzene pollution in drinking water. It should be also further verified and improved in the actual drinking water pollution events.