Photo-Fenton process under sunlight irradiation for textile wastewater degradation: monitoring of residual hydrogen peroxide by spectrophotometric method and modeling artificial neural network models to predict treatment

Abstract

In this work, a procedure was elaborated to quantify hydrogen peroxide (H2O2) after degradation tests of dyes present in a synthetic textile matrix. For this purpose, based on the intensity of radiation absorption of the peroxovanadium cation, which was formed by the reaction between the oxidant and vanadate ions, ultraviolet/visible spectrophotometry technique was used. The most suitable experimental condition was composed of concentrations of 0.05 mol L−1 (NH4VO3) and 0.3 mol L−1 (H2SO4). The system for dye treatment involved the photo-Fenton process under simulated sunlight. In this case, concentrations of 900 mg L−1 (H2O2) and 4 mg L−1 (iron) in pH 3 were the most efficient for degrading contaminants. An efficiency of 94.49% was obtained after 180 min of reaction, the time in which the presence of the oxidant was no longer verified. The kinetic monitoring showed a two-stage degradation, described with accuracy greater than 96% by the linear and non-linear kinetic models of pseudo-first order. Additionally, the degradation under natural solar radiation was also studied, which resulted in an efficiency of 92.45% after 360 min and in the presence of the residual oxidant. Finally, via mathematical modeling and employing a Multilayer Perceptron neural network, with a 3-10-2 topology and BFGS 387 training algorithm, it was possible to predict the degradation and H2O2 residual concentration with an accuracy greater than 98%. Therefore, the degradation study developed and the proposed methodology for determining residual H2O2 proved to be adequate and capable of contributing positively to related research.