Modeling of the adsorptive removal of arsenic(III) using plant biomass: a bioremedial approach

Abstract

In the present work, the possibility of using a non-conventional finely ground (250 μm) Azadirachta indica (neem) bark powder [AiBP] has been tested as a low-cost biosorbent for the removal of arsenic(III) from water. The removal of As(III) was studied by performing a series of biosorption experiments (batch and column). The biosorption behavior of As(III) for batch and column operations were examined in the concentration ranges of 50–500 µg L−1 and 500.0–2000.0 µg L−1, respectively. Under optimized batch conditions, the AiBP could remove up to 89.96 % of As(III) in water system. The artificial neural network (ANN) model was developed from batch experimental data sets which provided reasonable predictive performance (R2 = 0.961; 0.954) of As(III) biosorption. In batch operation, the initial As(III) concentration had the most significant impact on the biosorption process. For column operation, central composite design (CCD) was applied to investigate the influence on the breakthrough time for optimization of As(III) biosorption process and evaluation of interacting effects of different operating variables. The optimized result of CCD revealed that the AiBP was an effective and economically feasible biosorbent with maximum breakthrough time of 653.9 min, when the independent variables were retained at 2.0 g AiBP dose, 2000.0 µg L−1 initial As(III) concentrations, and 3.0 mL min−1 flow rate, at maximum desirability value of 0.969.