| Abstract |
In the past, biomass-based waste sources have demonstrated their potential for remediating heavy metals in contaminated soils and water. Nanoparticles have been extensively studied for their ability to absorb and recover heavy metals from the liquid portion of biomass digestate, contributing to a circular economy in biomass plants. By combining nanocomposites with the liquid fraction of biomass digestate, the efficiency and effectiveness of heavy metal remediation using the Multi-Criteria Decision Making (MCDM) technique can be enhanced. The objective of this study is to evaluate and compare different biomass-based nanocomposites for heavy metal remediation using the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method prioritizes and ranks alternatives based on criteria such as heavy metal removal efficiency, production cost, and potential environmental impacts. The investigation reveals that porosity value is the most important criterion (48 %) compared to other parameters, while surface area has the lowest importance (6 %). The TOPSIS method uses distance measures to rank alternatives based on their proximity to the ideal solution. Among the tested nanocomposites, zinc oxide demonstrates optimum performance with removal rates of 92 % for copper, 95 % for lead, and 88 % for nickel. Additionally, an economic analysis of the system reveals a return on investment of approximately 5.9 %. In conclusion, this study presents a sustainable, cost-effective, environmentally friendly, and efficient solution for mitigating heavy metal pollution. |
