O-Anisidines (OAs) are extensively used as an intermediate for chemical reactions to produce various triphenylmethane and azo dyes, and also in manufacturing numerous pigments. They are found to be highly toxic and have carcinogenic properties, so it is imperative to treat OA solutions before disposal. In this study a promising approach to degrade OA solutions has been carried out using Fenton’s reagent. Oxidation trials were conducted for 24 hours and various parameters – OA removal, pH, effect of H2O2 and Fe2+, and COD removal – were analysed to understand the oxidative degradation of OA. For varying initial OA concentrations, the OA and COD removal efficiencies of 72 to 85% and 62 to 74%, respectively, were obtained at pH = 3, and at different optimum H2O2 and Fe2+ doses. Lower initial concentrations of OA showed better removal efficiencies. The reaction time was estimated to 360 minutes after which there was negligible degradation occurs.

Immobilizing of zero-valent iron in mono- and bi-metallic systems on the bentonite clay surface as new nanocatalyst were synthesized and used to degrade model acidic dyes from aqueous media. The Fourier-transform infrared spectroscopy, scanning electron microscopy-energy dispersive X-ray spectroscopy, transmission electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller analysis were used to characterize the synthesized nanocomposites, which demonstrated successful loading of nanoscale Fe-Cu bi-metallic onto bentonite support. Different variables controlling the congo red, methyl orange and methyl red dyes degradation using zero-valent iron based bimetallic nanoparticle on the bentonite clay surface as new nanocatalyst were concurrently optimized through an experimental design. Basic evaluations proved the nanocatalyst quantity, medium pH, initial dye concentration, and contact time as the most important variables influencing the degradation phenomenon and hence a response surface methodology based on the central composite design was conducted to determine the relations between the variables and the degradation efficiencies. The statistical factors (e.g. R2 and F-value) of the derived models were considered. Using response surface plots obtained through the models, the effects of the variables on the degradation efficiencies for each dye were assessed. Also, the Nelder-Mead non-linear optimizations were performed and the optimal degradation efficiencies at a 95% confidence level were determined which were found to comply with the respective experimental response values.