Abstract
Textile effluents treatment is one of the important environmental challenges nowadays. Photocatalysis has proven its effectiveness for the removal of recalcitrant compounds, and it is considered as a green technology for the treatment of effluents. However, good photocatalytic yield is strongly related to the operating parameters. In this study, a supported TiO2 on a β-SiC foam was tested for the removal of Rhodamine B (RhB). The photocatalytic discoloration of RhB synthetic solution in our condition was about 90%. The effects of each parameter were assessed through a full factorial design. Sixteen tests were carried out and the response was RhB removal. The most influent parameters were TiO2/β-SiC foam quantity, the concentration of RhB, the volume of H2O2 and pH. Their contributions on RhB removal were, respectively, 53.01, 30.49, 2.7, and 2.48% according to Pareto diagram. Analysis of the coefficients shows that initial concentration of RhB and volume of H2O2 had a negative effect on the response. However, the quantity of TiO2/β-SiC foam and pH had a positive effect on the response. The influence of the flow rate on the process was assessed. The results showed a slight increase in RhB removal. Furthermore, the aging test of TiO2/β-SiC foam on the photocatalytic efficiency was carried out after ten successive photocatalysis tests. Only 6.7% loss of yield was observed. These results are very encouraging for an application at the industrial scale.
Highlights
The agricultural and industrial sectors as well as household release each day a huge amount of pollutants into surface water, making them nonusable (Telegang 2017)
The Pareto analysis of the model terms showed that the photocatalytic process was highly influenced by the number of foam samples (53.01%) and the concentration of Rhodamine (30.49%). only the interaction between Rhodamine B (RhB) concentration and volume of H2O2 has an influence on the removal rate (10.86%)
Analysis of variance showed the high coefficient of determination values (R2 = 0.991), ensuring a satisfactory adjustment of the first-order regression model with the experimental data
Summary
The agricultural and industrial sectors as well as household release each day a huge amount of pollutants into surface water, making them nonusable (Telegang 2017). The most well known are pharmaceutical products, phenolic compounds, and dyes (Bouyarmane 2014). World production of dyes is estimated at 800,000 T/year and about 140,000 T/year is released in the environment during the fabrication and coloring steps of textiles (Mansour et al 2011). Dye effluent may contain chemicals that are toxic, carcinogenic, or mutagenic, to various fish species (Verma et al 2012). It may prevent light penetration in water and photosynthesis, which can drive to a lack of dissolved oxygen and upset the biological metabolism processes (Joshi et al 2004; Assémian et al 2018)
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