The aim of this work was to test the efficiency of a new photocatalytic reactor made of recycled materials. To perform this stu dy a textile effluent was treated by different AOPs and the solar/H2O2/TiO2suported method showed the higher percentage of degradation after the reaction time. Through a...

The aim of this work was to test the efficiency of a new photocatalytic reactor made of recycled materials. To perform this stu dy a textile effluent was treated by different AOPs and the solar/H2O2/TiO2suported method showed the higher percentage of degradation after the reaction time. Through a factorial design, it was possible to find the more significant variable in order to reach higher percentages of degradation. The performance of the reactor with recirculation allowed obtaining degradation kinetics parameters by adjusting the removals to a second order model, with k dyes = 0.175 L. mol(-1). s(-1) and 90% of dye removal after 30 min for the solar/H2O2/TiO2suported system. The use of artificial neural network was proven to be efficient to predict the degradation of a real effluent, with an absolute error of 0.02266. Other parameters such as COD, apparent color and nitrate were importantly reduced after treatment. The use of the reactor made of recycled material (PET) brings economic advantages, due to the low cost of the used materials and its respective easy construction. The treatment with the new reactor is suitable for the removal of contaminants from textile effluents since it presented higher efficiency than the conventional treatment used in the textile industry under study

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