Statistical Optimization of As(V) Adsorption Parameters onto Epichlorohydrin/Fe3O4 Crosslinked Chitosan Derivative Nanocomposite using Box-Behnken Design

Abstract

In this study, Box-Behnken design (BBD) in response surface methodology (RSM) was employed to optimize As(V) removal from an aqueous solution onto synthesized crosslinked carboxymethylchitosan-epichlorohydrin/Fe3O4 nanaocomposite. The factors like solution pH, adsorbent dose, contact time and temperature were optimized by the method which shows high correlation coefficient (R2 = 0.9406), and a predictive quadratic polynomial model equation. The adequacy of the model and parameters were evaluated by analysis of variance (ANOVA) with their significant factors of Fischer’s F-test (p < 0.05). Seven significant parameters with interaction effects in the experiment with p-value < 0.0001 was observed, having a maximum removal efficiency of As(V) is 95.1%. Optimal conditions of dosage, pH, temperature, initial ion concentration and contact time in the process were found to be 0.7 g, pH 6.5, 308K, 10 mg/L and 60 min respectively. Langmuir isotherm model fitted better than the Freundlich model having a maximum adsorption capacity of 28.99 mg/g, a high regression value of 0.9988, least chi-square value of 0.1781. The process was found to follow monolayer adsorption and pseudo-second-order kinetics. Thermodynamic parameters indicate the process is spontaneous, endothermic and physisorption in nature. Successful regeneration of the adsorbent implies its applicability to the removal of arsenic from real life wastewater.