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

Abstract

In the present study, concurrently removal of COD and turbidity from leather processing effluents (LPE) using TiO2–assisted photocatalytic-ozonation were investigated by utilization of Box-Behnken design (BBD) in planning experiments. Effects of ozone dose (OD, mg L-1), catalyst dose (CD, g L-1), and aeration (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 (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

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