Hybrid Photo-Fenton oxidation and biosorption for petroleum wastewater treatment and optimization using Box-Behnken Design

This study investigates the treatment of petroleum wastewater (PWTP) effluent using hybrid techniques (photo-Fenton oxidation and adsorption) to remove organic pollutants such as chemical oxygen demand (COD) and phenol. All the experiments were carried out in batch mode. The effects of pH, ferrous salt (Fe2+), and H2O2 oxidation factors on the photo-Fenton process were studied. The response surface methodology (RSM) approach for experiment design and optimization yielded maximum COD and phenol removal at Fe2+, H2O2, pH of 20 mM, 400 mM, and 3.8, respectively. In this optimal scenario, phenol reduction from the initial value of COD 12654.6 mg/L, phenol 213.0 mg/L was accomplished by 69.97% and 95.66%, respectively. Response surface methodology (RSM) photofenton based modeling and optimization was done using a Box-Behnken. The high coefficient of regression R-2 = 0.97 and 0.98 for COD and phenol oxidation is suggested by variance analysis (ANOVA). The PWTP effluent treated by Fenton oxidation with COD 4139.1 mg/L and phenol 70.1 mg/L was treated with Phragmites australis. Phragmites australis was chosen as an adsorbent. Phragmites australis was analyzed and characterized using several techniques, including Fourier transform infrared spectroscopy, Scanning Electron Microscopy, Zeta potential, and particle size distribution. The adsorption process step followed the photo-Fenton treatment process. The adsorption process achieved 69.04 % and 95.80% for COD and phenol removal. Kinetic studies showed that the statistics match very well in the nonlinear pseudo-first and second-order models based on the correlation coefficients (R-2 = 0.999) and (R-2 = 0.996), respectively, for COD and phenol removal in the adsorption phase. The severe adsorption potential for COD and phenol removal is 14421.97 mg/g and 374.90 mg/g, respectively. Finally, as a natural material, P. australis is a promising adsorbent material. (C) 2021 Elsevier B.V. All rights reserved.