Determination of the apparent rate constants of the degradation of humic substances by ozonation and modeling of the removal of humic substances from the aqueous solutions with neural network.

In this study, the degradation rate constants of humic substances by ozonation under the different empirical conditions such as ozone-air flow rate, ozone generation potential, pH, temperature, powdered activated carbon (PAC) dosage and HCO(3)(-) ions concentration were determined. The ozonation of humic substances in the semi-batch reactor was found to fit pseudo-first-order reaction. The values of apparent rate constant of humic substances degradation increased with the increase of initial ozone-air flow rates, ozone generation potential, pH, temperatures and PAC dosage, but decreased with the increase of HCO(3)(-) concentration of the solution. Using Arrhenius equation, the activation energy (E(a)) of the reaction was found as 1.96 kJ mol(-1). The reaction of ozonation of humic substances under the different temperatures was defined as diffusion control according to E(a). The model based on artificial neural network (ANN) could predict the concentrations of humic substances removal from aqueous solution during ozonation. A relationship between the predicted results of the designed ANN model and experimental data was also conducted. The ANN model yielded determination coefficient of (R(2)=0.995), standard deviation ratio (0.065), mean absolute error (4.057) and root mean square error (5.4967).