Performance verification of different advanced oxidation processes in the degradation of the dye acid violet 17: reaction kinetics, toxicity and degradation prediction by artificial neural networks

The contamination of water resources due to the presence of persistent organic pollutants, such as dyes, is a cause for concern, since these substances are resistant to conventional treatments adopted in wastewater treatment plants. In this context, the present work evaluated the degradation of the dye AV17, used in sanitizing industries, through different advanced oxidation processes (AOP). AOP of photoperoxidation, Fenton and photo-Fenton were employed. It was found that the photoperoxidation/UV-C system was more efficient in the treatment of the dye, reaching degradations of 68.27%, 88.16% and 99.35% for the characteristic wavelengths of 254, 307, 548 nm, respectively. The Fenton process and the photo-Fenton/solar system, especially with natural solar irradiation, only managed to promote the discoloration of the solution by degrading the chromophore group. The kinetic study indicated a better adjustment of the experimental data to the pseudo-first order model, with R 2 > 0.94 for the mentioned AOP. The modeling by ANN allowed to predict the degradation of AV17 through an MLP 5-6-3 BFGS 297 type network, with R 2 values higher than 0.9864 for training, testing and validation. Toxicity tests with Lactuca sativa seeds showed that the treatment via photoperoxidation/UV-C and photo-Fenton/solar led to a reduction in the toxicity of the solution contaminated by the dye. However, for the solution treated by Fenton process, toxicity was observed.