Calcined biomass-bentonite composites as eco-friendly adsorbents for the treatment of toxic anionic and cationic dye wastewater

Adsorption is a suitable technique for decontamination of organic dye wastewaters. Herein, we comparatively investigated the adsorption performance of bentonite (BEN) and its modification with groundnut shell (BGS) and palm kernel shell (BPS) for methylene blue (MB) and congo red (CR) dyes removal from aqueous solution. BGS and BPS were prepared by calcination at 300 °C for 6 h and were characterized using BET, SEM, EDS and FTIR to determine their textural properties, morphologies, elemental compositions, and functional groups. The BET surface examination revealed that the surface area of BEN was enhanced from 78 m2/g to 195 m2/g and 141 m2/g after modification with groundnut shell (BGS) and palm kernel shell (BPS), respectively. The adsorption process in a batch system was subjected to comprehensive experimentation to investigate the effect of adsorbent dosage, contact time, temperature, initial concentration, and pH. The adsorption was fitted to adsorption isotherm and kinetic models and the results revealed that the adsorption process of BEN, BGS, and BPS towards MB and CR adsorption can be best described by Temkin, Freundlich and pseudo-second order kinetic models. The adsorption capacities (qmax) for uptake of MB by BEN, BGS and BPS are 10.61, 10.85 and 10.93 mg, while CR exhibited 8.83, 6.87 and 5.86 mg/g, respectively. The thermodynamics study revealed that the adsorption process was spontaneous, feasible, endothermic in nature. The adsorption process is governed by electrostatic attraction with the involvement of physical and chemical adsorption. This study suggests that biomass-modified bentonite is a sustainable, cost-effective, non-toxic, and greener approach for eliminating MB and CR from aqueous solution. Furthermore, the modification method does not only achieve substantial removal of MB and CR dyes, but also offers considerable energy savings and operational cost reductions in real-time based on water quality data. This study does present a novel, sustainable approach to improve natural water treatment efficiency and compliance.