Abstract
BackgroundDischarge of grey wastewater into the ecological system causes the negative impact effect on receiving water bodies.MethodsIn this present study, electrocoagulation process (EC) was investigated to treat grey wastewater under different operating conditions such as initial pH (4–8), current density (10–30 mA/cm2), electrode distance (4–6 cm) and electrolysis time (5–25 min) by using stainless steel (SS) anode in batch mode. Four factors with five levels Box-Behnken response surface design (BBD) was employed to optimize and investigate the effect of process variables on the responses such as total solids (TS), chemical oxygen demand (COD) and fecal coliform (FC) removal.ResultsThe process variables showed significant effect on the electrocoagulation treatment process. The results were analyzed by Pareto analysis of variance (ANOVA) and second order polynomial models were developed in order to study the electrocoagulation process statistically. The optimal operating conditions were found to be: initial pH of 7, current density of 20 mA/cm2, electrode distance of 5 cm and electrolysis time of 20 min.ConclusionThese results indicated that EC process can be scale up in large scale level to treat grey wastewater with high removal efficiency of TS, COD and FC.
Highlights
Discharge of grey wastewater into the ecological system causes the negative impact effect on receiving water bodies
Extensive literature survey shows that none of researchers studied the optimization of the EC process using a stainless steel electrode to treat grey wastewater
Selection of suitable mathematical model The experimental data was analyzed by model summary statistics in order to obtain regression models and decide about the adequacy of various models to represent the EC process significantly
Summary
Discharge of grey wastewater into the ecological system causes the negative impact effect on receiving water bodies. Most studies on the optimization of wastewater treatment process have focused on the traditional one-factor-at-atime approach. This approach, which does not take into account cross effects from the factors considered, is time consuming and results in poor optimization results [13]. In this study, Box-Behnken response surface design (BBD) coupled with Derringer’s desired function methodology was used to optimize and investigate the influence of the key process variables of EC such as initial pH, current density, electrode distance and electrolysis time (independent variables) on total solids (TS) removal, chemical oxygen demand (COD) removal and fecal coliforms (FC) removal (dependent variables)
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