Low frequency ultrasonic‐assisted Fenton oxidation of textile wastewater: process optimization and electrical energy evaluation

Abstract

Worldwide, there is a continuous need to develop alternative treatment methods to replace conventional processes for textile wastewater. In this regard, Fenton oxidation, with the potential of hydroxyl radical production, is an efficient method. Nevertheless, pH dependence, high chemical consumption and sludge production are a few aspects that limit its wide application. Therefore, to overcome these limits, integration of Fenton oxidation with other advanced oxidation processes is considered a viable option. Therefore, in this study, Ultrasonic-assisted Fenton oxidation was investigated to observe the increase in degradation efficiency of Fenton oxidation. For this purpose, low frequency ultrasonic water bath was used and malachite green dye was used as a model pollutant. Central composite design was used for experimental design, and [OP] ini , OP:Fe +2 (wt/wt), H 2 O 2 :Fe +2 (wt/wt) and pH were used as control factors. Based on experimental results, maximum of 97.5% Chemical Oxidation Demand (COD) reduction was obtained at the process conditions of [OP] ini : 100 mg/L, OP:Fe +2 : 50, H 2 O 2 :Fe +2 : 1.5 and pH:3. Furthermore, 10 times reduction in the consumption of hydrogen peroxide was obtained. According to Pareto analysis, organic pollutant (OP) in interaction with OP is the most significant while pH was identified as the least. The process followed pseudo-first order kinetics (k = 0.0196 min −1) with electrical energy order of 26.21 kWh/m 3 and the maximum energy consumption per COD removal of 0.8 kJ/COD, lower than those available in the literature. The results suggested that US-assisted Fenton oxidation could be considered as an efficient method for treating the recalcitrant wastewater.

Photocatalytic degradation of p‐nitrophenol in wastewater by heterogeneous cobalt supported ZnO nanoparticles: Modeling and optimization using response surface methodology

“…The experimental values were fitted to a second‐degree polynomial equation and analysis of variance (ANOVA) was employed to examine the model validity and the interactive effects of the independent factors 43 . F ‐test was employed for determining the model fitting whereas regression and adjusted regression co‐efficient ( R 2 and Adj.…”