Degradation of trichloroethylene by sonophotolytic-activated persulfate processes: Optimization using response surface methodology

The efficacies of the sonolytic, photolytic and sonophotolytic activation of persulfate were investigated and compared for degradation of trichloroethylene in aqueous solutions. The effects of the operating variables on trichloroethylene removal efficiency were assessed and optimized by employing a response surface methodology based on central composite design. The investigated parameters include initial pH, persulfate concentration, ultrasound and ultraviolet power at initial concentration of 500 mu g/L TCE. After 20 min, the sonophotolytic activation of persulfate resulted in 96.3% removal efficiency, while the corresponding removal values for the individual photolytic and sonolytic activation of persulfate were only 41.2 and 51.8%. These results indicate that the combination of sonolytic and photolytic activation of persulfate provides a synergistic effect with synergy index of 1.62. It was found that the trichloroethylene removal efficiency was enhanced with increasing persulfate concentrations, ultrasound and ultraviolet power with optimum values of 61 mu mol/L, 95 and 60 W respectively, due to the formation of more reactive radicals. In addition, maximum trichloroethylene removal rate occurred at pH 5.5 and decreased when pH value was either decreased or increased from pH 5.5. At optimum condition, complete degradation of trichloroethylene was obtained at a 20-min reaction time. As indicated by the statistical analysis results, trichloroethylene removal efficiency was satisfactorily predicted using the proposed model developed with a very low probability of 0.0001 at a confidence level of 95%. Moreover, the quadratic model showed high correlation between the predicted and experimental data with high correlation coefficients of 0.9682 and 0.9539 for R-2 and R-adj(2), respectively. The sonophotolytic activation of persulfate for degrading trichloroethylene in an aqueous solution was proven to be an efficient technology. (C) 2018 Published by Elsevier Ltd.