Kinetic study of food dyes removal from aqueous solutions by solar heterogeneous photocatalysis with artificial neural networks and phytotoxicity assessment

Abstract

Effluent treatment for food industry wastewater is a subject of growing concern among the scientific community. Synthetic dyes are a major case and their presence can disturb aquatic environments and introduce highly toxic potentials to the ecosystem, even at low concentrations. In this study, the chemical kinetics of a degradation process was studied for the treatment of a Tartrazine (E102) and Brilliant Blue (E133) solution by different methods. First, the efficiency of eight advanced oxidative processes systems was investigated in their treatment. The most efficient result was obtained in a UV-solar/H2O2/TiO2 system, which reached a degradation percentage of 99.36% in 180 min. Second, a 23 factorial planning was used to enhance quantitative degradation in this system and a similar result (99.21%) was reached in 90 min with the optimal conditions. The kinetics of this experiment was fitted in a pseudo-first-order model and the rate constant (k) estimated as 0.0541 min–1. An artificial neural network was developed for the experiment to describe the degradation behaviour over time with a minimum error. Chemical oxygen demand and conductivity were estimated in order to assure the environmental quality of the samples. A Lactuca sativa bioassay revealed an upturn in LC50, the concentration to inhibit 50% of the organism growth, from 39.31% (v/v) to 87.73% (v/v). The result indicates a highly favourable reduction in acute phytotoxicity, that coupled with quantitative efficiency, makes the proposed use of solar light as radiation source and improvements in water quality parameters a suitable tool for large-scale synthetic dye treatment.