Degradation of Reactive Black 5 dye by photo-Fenton process with modeling and optimization using ANN

Abstract

The annual world production of dyes is 800,000 tonnes, of which 50% are azo dyes such as Reactive Black 5 dye (RB5). Is estimated that about 15% of synthetic dyes from the textile industry are lost during its manufacture or use in industrial processes. About 160 m³ of water is spent per ton of fiber during textile processing operations such as bleaching, mercerizing, dyeing and washing. Then it is important to treat effluent from textile industry to enable water reuse and consequently reduction of water consumption and wastewater generation. The treatment a model wastewater containing Reactive Black 5 (RB5) was carried out in a PTC tubular reactor with black light (UVA) using photo-Fenton technique. An experimental design (2³) was used, with H₂O₂, Fe²⁺ and RB5 dye as independent variables and the conversion of total organic carbon (TOC) and RB5 degradation as the response variables. The modelling and process optimization was performed using artificial neural network (ANN). The optimized condition for maximum TOC conversion was obtained with molar concentration [H₂O₂]₀:[Fe²⁺]₀:[RB5]₀ equal to 119:19:1 after 90 minutes of reaction. Experimental runs were conducted under optimized conditions, obtaining a 90% conversion of TOC confirming the adequate performance of the ANN model to predict the results of textile effluent treatment.