In the present study, response surface methodology (RSM) was applied to maximize As(V) removal from aqueous solutions by using modified magnetic nanoparticles with ascorbic acid (AA-MNPs). The structural features of the produced material were characterized by means of XRD, N2 adsorption–desorption, FT-IR, VSM, TGA and SEM. More specifically, the effects of pH, temperature, arsenic ion concentration and sorbent dosage were investigated on the arsenic adsorption. A total of 20 sets of experiments were designed by the software to achieve maximum adsorption capacity (qe) and removal efficiency (R). Analysis of variance (ANOVA) of the two-factor interaction (2FI) model suggested that the predicted values were in good agreement with experimental data. The best local maximum values for pH, arsenic concentration and sorbent dosage were found to be 2, 5 mg.l-1 and 0.1 g.l-1, respectively, that yielding maximum qe of 44.99 mg.g-1 and a maximum R of 42.69%. Additionally, the obtained value for desirability was equal to 0.862. The results indicated that the Langmuir model provided the best correlation of the equilibrium data. Moreover, the obtained results revealed that the pseudo-second-order kinetic model could best describe the adsorption kinetics.
