Abstract
Industrialisation and urbanisation contribute greatly to the deposition of toxic waste and metalloids to the environment. Therefore, the use of efficient and eco-friendly materials such as geopolymers and biopolymers is essential for the adsorption of the toxic metals. The implementation of these low-cost sorbents has fascinated a great deal of interest owing to effectiveness, ease of operation, less environmental impact, etc. In this study, biocomposites were synthesised from bio-treatment of geopolymer (kaolin and palm oil fuel ash) using an anionic biopolymer. The biocomposites were utilised as biosorbent for removal of Cu, Fe and Zn in a multi-component system, with the process parameters optimised. FTIR and SEM/EDX outcomes clearly denoted the microporous framework of geopolymer structures and the presence of bio-molecules from the biopolymer. XRD and XRF techniques on the precursors described suitability for geopolymerisation due to the rich aluminate-silicate content. Based on response surface methodology, the adsorption capacities for Cu, Fe and Zn are 35.01 mg/g, 45.175 mg/g and 44.630 mg/g at optimal conditions of pH (7.5), time (40.5 min), metal ion concentration (80 mg/l), biosorbent dosage (0.2 g) and biopolymer concentration (0.75 g in 50 ml). The multi-component system was apt with the modified competitive Langmuir isotherm which described the homogeneity of the prominent sites of the biocomposites. Based on the adsorption kinetics, Cu was only dominated by the pseudo-first-order reaction (PFOR) while Fe and Zn were influenced by both PFOR and intra-particle diffusion processes. The result obtained from the synthesised biocomposites recommends application to actual wastewater systems.
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The authors wish to acknowledge the immense assistance of Okeugo Dennis and Ikechukwu Okechukwu during the execution of this study.
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Mama, C.N., Nwonu, D.C., Akanno, C.C. et al. Adsorption capacity of composite bio-modified geopolymer for multi-component heavy metal system: optimisation, equilibrium and kinetics study. Environ Monit Assess 194, 134 (2022). https://doi.org/10.1007/s10661-021-09733-4
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DOI: https://doi.org/10.1007/s10661-021-09733-4