Statistical modeling and performance evaluation of biosorptive removal of Nile blue A by lignocellulosic agricultural waste under the application of high-strength dye concentrations

Abstract

In the present work, overripe Abelmoschus esculentus seeds, as agro-food waste was employed for the first time to scrutinize adsorption efficiency of Nile blue A (NBA) dye from the aqueous streams. The influences of biosorptive factors such as biosorbent dosage, solution pH, contact time, and initial NBA concentration on dye adsorption were studied by single-parameter optimization. After that, the central composite design (CCD) approach-based response surface methodology (RSM) analysis was utilized to optimize the NBA adsorption by A. esculentus biomass. The experimental results of the CCD design were further used to obtain a training set for artificial neural network (ANN) methodology. Both the statistical models were well fitted to experimental data (RRSM2 = 0.9907, RANN2 = 0.9958). The appropriate adsorption isotherm for the equilibrium process is Sips model, and the kinetic studies revealed that the adsorption of NBA followed the fractal-like pseudo-first-order kinetic model. The decolorization process was quite fast to be accomplished with a time period varying from 46.7 to 128.7 min obeying normalized Gudermannian kinetic equation also. The NBA adsorption process was observed to be controlled both by film and intra-particle diffusions. The endothermic, spontaneous and physico-chemical nature of the adsorption process was confirmed by the thermodynamic parameters. The three adsorption-desorption cycles explored that A. esculentus was suitable for reuse in the removal of NBA dye molecules. The finding of this paper emphasizes that this bio-waste is an efficient and low-cost adsorbent that can be successfully employed for the treatment of high-strength dye wastewater.