Optimization of Catalytic Ozonation Process by Using Fe/MgO Nanoparticle in Removal of Phenol from Aqueous Solution with Design of Experiments Based on Taguchi Statistical Modeling

The presence of phenol in effluents may cause risk to human health. By Taguchi statistical model, the process can be optimized by certain number of experiments. The aim of this study was optimization of catalytic ozonation process in removal of phenol from aqueous environments by Nano Fe / MgO with Taguchi statistical model. In this experimental study, experiment design was set based on the statistical model. Parameters such as pH (3, 5, 9, and 11), initial concentration of pollutant (500, 1000, 1500, and 2000 mg/L), reaction time (10, 20, 30, and 40 min) and catalytic dose (0.1, 0.2, 0.3 and 0.4 g/L) in 4 layers and 4 levels were investigated. Data were analyzed with Minitab ver.16 software. Residual concentration of phenol was measured according to standard method book. The results showed that, efficiency of phenol removal depends on various operational parameters. The optimum conditions of phenol removal was obtained at reaction time=30 min, pH=5, the phenol initial concentration of 1000 mg/L and catalyst dose of 0.1 g/L. Among the factors investigated; initial concentration of phenol has the maximum effect (69.5%) and reaction time the minimum (3.2%) effect in optimum conditions. S/N ratio of 39.39 was estimated at optimum conditions. By using Taguchi statistical model, phenol removal was optimized in certain number of experiments. Ozonation process has high capability in phenol removal.