Modeling of arsenic removal from aqueous solution by means of MWCNT/alumina nanocomposite

In this study, response surface methodology (RSM) was employed for investigating the removal of As(V) from aqueous solution using multiwalled carbon nanotube (MWCNT)/alumina nanocomposite. The synthesized nanocomposite was characterized by scanning electron microscopy and X-ray diffraction. For conducting the experiments, four independent variables of initial As(V) concentration ranging from 0.1 to 0.9 mg L-1, pH 3-11, contact time ranging from 15 to 1,450 min and adsorbent dose 0.5-1.5 g L-1 were selected and consecutively coded as X-1, X-2, X-3, and X-4 at three levels (-1, 0, and 1). A second-order polynomial regression model was then applied to predict responses. Regression analysis showed good fit of the experimental data to the second-order polynomial model with R-2 value of 0.9409 indicates the high correlation between observed and predicted values. At the optimum conditions that were initial As(V) concentration 0.5 mg L-1, pH 7, contact time 80 min, and adsorbent dose 1 g L-1, the As(V) removal efficiency was about 99.4%. This study proved that Box-Behnken design under RSM could efficiently be applied for modeling of As(V) removal by MWCNT/alumina nanocomposite.