Optimization of saline wastewater treatment using electrochemical oxidation process: Prediction by RSM method

(2019) Optimization of saline wastewater treatment using electrochemical oxidation process: Prediction by RSM method. MethodsX. pp. 1101-1113. ISSN 2215-0161 (Print) 2215-0161 (Linking)

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Abstract

Response surface methodology (RSM) was applied to find the optimum parameters for COD and TOC removal from saline wastewaters using electrochemical oxidation process. The independent variables considered were reaction time, pH, salt concentration, and voltage. Optimization of parameters was performed by analysis of variance (ANOVA). Quadratic regression equation was suggested as a model for prediction of chemical oxygen demand (COD) and total organic carbon (TOC) removal efficiency. The results indicated that the COD and TOC removal efficiencies at the optimal conditions of pH 7.69, reaction time of 30.71 min, salt content of 30. 94 g/L and voltage of 7.41 V were 91.78 and 68.49, respectively. In terms of COD and TOC removal efficiency, the coefficients of determination were found to be 0.95 and 0.94, respectively. This study suggests that electro-oxidation is an effective process in decreasing COD and TOC from saline wastewaters. Further, RSM was a suitable technique for optimization of the variables involved in COD and TOC removal through electro-oxidation process. *The findings demonstrate that response surface methodology is a good tool for the optimization of parameters of the experimental data.*A quadratic model was suggested as a good model for COD and TOC removal prediction.*The findings proved good agreement between the experimental data and the predicted equation.

Item Type: Article
Keywords: Electrochemical oxidation Optimization Optimization of saline wastewater treatment using electrochemical oxidation process: Prediction by RSM method Rsm Saline wastewater
Subjects: WA Public Health > WA 670-847 Environmental Pollution. Sanitation
Divisions: Faculty of Health > Department of Environmental Health Engineering
Page Range: pp. 1101-1113
Journal or Publication Title: MethodsX
Journal Index: Pubmed
Volume: 6
Identification Number: https://doi.org/10.1016/j.mex.2019.03.015
ISSN: 2215-0161 (Print) 2215-0161 (Linking)
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/10464

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