Turbidity and COD removal from leather effluents using TiO2–assisted photocatalytic-ozonation by response surface methodology

Authors : Musa Buyukada

Pages : 1-10

View : 18 | Download : 9

Publication Date : 2018-07-01

Article Type : Research Paper

Abstract :In the present study, concurrently removal of COD and turbidity from leather processing effluents insert ignore into journalissuearticles values(LPE); using TiO2–assisted photocatalytic-ozonation were investigated by utilization of Box-Behnken design insert ignore into journalissuearticles values(BBD); in planning experiments. Effects of ozone dose insert ignore into journalissuearticles values(OD, mg L-1);, catalyst dose insert ignore into journalissuearticles values(CD, g L-1);, and aeration insert ignore into journalissuearticles values(A, mL min-1); were performed as explanatory variables. An increase both in doses of ozone and catalyst and a decrease in aeration leaded increases both in removals of COD and turbidity. Values of 96.77% and 95.37% were obtained as the highest COD and turbidity removal efficiencies, respectively. This showed that TiO2-assisted photocatalytic-ozonation process was significantly effective for the treatment of LPE. By using BBD, 2.95 g L-1 of CD, 19.99 mg L-1 of OD, and 1.63 mL min-1 of A were determined as BBD-optimized operating conditions. BBD suggested removals of 96.77% and 94.93% for COD and turbidity, respectively at these optimized conditions. Validation experiments at BBD-optimized conditions were resulted as 95.52%±1.28 and 94.36%±2.52 for COD removal and turbidity removal, respectively. Good agreement between predicted values and experimental results demonstrated the accuracy of BBD in optimization of explanatory variables of TiO2-assisted photocatalytic-ozonation process. Finally, multiple non-linear regression insert ignore into journalissuearticles values(MNLR); studies were performed to state the variation in responses and also to predict the responses. The proposed models predicted COD and turbidity removals with regression coefficients of 99.99% and 99.97%, respectively. These findings also showed that MNLR was an efficient way to model and to predict the response variables of photocatalytic-ozonation process.
Keywords : Leather effluents, Photocatalytic ozonation, COD, Turbidity, Empirical modeling