Process parameter optimization of engineered biochar for lead (II) removal from water: a case study on agro-waste valorization optimization

Recently, there has been a significant increase in biomass waste and heavy metal contamination, particularly in developing countries. One potential solution to combat heavy metal water pollution is the use of biomass waste, such as biochar, due to its high carbon content, large surface area, and stable structure. The effectiveness of biochar in adsorbing and removing heavy metals varies depending on the type of feedstock and pyrolysis conditions. No studies have been reported about the use of statistical methods integrated with multiobjective optimization for studying Pb²⁺ adsorption using biochar, even though numerous studies have been conducted on Pb²⁺ adsorption from water using biochar. In this study, we coupled response surface methodology with a multi-objective genetic algorithm and performed multi-criteria decision-making to optimize the pyrolysis process conditions for the Pb²⁺ adsorption of areca nut husk biochar. The optimal conditions for adsorption were obtained at 493 °C, 83 min, and a heating rate of 15 °C min⁻¹, and the optimal yield, removal rate, and adsorption capacity were found to be 25.83%, 48.9%, and 11.80 mg g⁻¹, respectively. The study examined the effect of pyrolysis temperature, residence time, and heating rate on the process, identifying optimal values. The optimized biochar displayed strong potential for adsorbing Pb²⁺ from water primarily through chemical adsorption. The honeycomb structure, large pore size, and surface functional groups of the areca nut husk biochar illustrate its effectiveness from removing Pb²⁺ from water.