Optimization of the electrochemical oxidation of textile wastewater by graphite electrodes by response surface methodology and artificial neural network.

In this study, electrochemical oxidation of combed fabric dyeing wastewater was investigated using graphite electrodes. The response surface methodology (RSM) was used to design the experiments via the central composite design (CCD). The planned experiments were done to track color changes and chemical oxygen demand (COD) removal. The experimental results were used to develop optimization models using RSM and the artificial neural network (ANN) and they were compared. The developed models by the two methods were in good agreement with the experimental results. The optimum conditions were found at 150 A/m, pH 5, and 120 min. The removal efficiencies for color and COD reached 96.6% and 77.69%, respectively. The operating cost at the optimum conditions was also estimated. The energy and the cost of 1 m of wastewater required 34.9 kWh and 2.58 US$, respectively. The graphite electrodes can be successfully utilized for treatment of combed fabric dyeing wastewater with reasonable cost.