In the present study, the treatment of tannery wastewater was performed by electrocoagulation method (EC) using aluminium and steel electrodes. Response surface methodology (RSM) with three factors; current density (I), electrolysis time (t) and pH, with each factor at five levels, was used to optimize the factors for higher chemical oxygen demand (COD) and total suspended solids (TSS) removal. Operational parameters I, t and pH were varied between 22–110 mA/cm2, 5-45 min and 3-7, respectively. For the optimal parameter values, the removal efficiency of COD and TSS attained respectively 82.2% and 85.5% for aluminium electrodes and 67.4% and 86.2% for steel electrodes. Analysis of variance (ANOVA) showed a high variance coefficient (R2) value of 0.96 and 0.81, for COD and TSS removal, respectively, thus ensuring a satisfactory adjustment of the second-order regression model with the experimental data. Corresponding energy consumption was found to be 2.92 €/m3 and 8.18 €/m3, for COD removal by using aluminium and steel electrodes, respectively.
Varank, G., Erkan, H., Yazýcý, S., Demir, A., & Engin, G. (2014). Electrocoagulation of Tannery Wastewater using Monopolar Electrodes:
Process Optimization by Response Surface Methodology. International Journal of Environmental Research, 8(1), 165-180. doi: 10.22059/ijer.2014.706
MLA
G. Varank; H. Erkan; S. Yazýcý; A. Demir; G. Engin. "Electrocoagulation of Tannery Wastewater using Monopolar Electrodes:
Process Optimization by Response Surface Methodology", International Journal of Environmental Research, 8, 1, 2014, 165-180. doi: 10.22059/ijer.2014.706
HARVARD
Varank, G., Erkan, H., Yazýcý, S., Demir, A., Engin, G. (2014). 'Electrocoagulation of Tannery Wastewater using Monopolar Electrodes:
Process Optimization by Response Surface Methodology', International Journal of Environmental Research, 8(1), pp. 165-180. doi: 10.22059/ijer.2014.706
VANCOUVER
Varank, G., Erkan, H., Yazýcý, S., Demir, A., Engin, G. Electrocoagulation of Tannery Wastewater using Monopolar Electrodes:
Process Optimization by Response Surface Methodology. International Journal of Environmental Research, 2014; 8(1): 165-180. doi: 10.22059/ijer.2014.706