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Pelletization of mixed torrefied corn cob and khat stem to enhance the physicochemical and thermal properties of solid biofuel and parametric optimization

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Abstract

Integrated pelletization of torrefied biomass is used to improve the energy density, handling, and combustion properties of produced solid biofuels. The goal of this study was to use a mixture of corn cob and khat stem through a combination of torrefaction and co-pelletization processes. The response surface methodology was used to investigate the optimization of co-pelletization parameters. Torrefied biomass blending ratio and particle size were chosen as independent factors. The dependent variables were heating value, bulk density, and durability of torrefied mixed pellets. According to the analysis of variance, the biomass blending ratio and particle size were discovered to be significant study parameters that influenced the heating value, bulk density, and durability. The interaction effects of the parameters chosen are well fit by the second-order quadratic model equation. For a maximum heating value of 26.4 MJ/kg, a bulk density of 808 kg/m3, and durability of 94.48%, the optimum values of the influencing parameters were 0.33 g/g % mixing ratio and 0.5-mm particle size. The physicochemical properties of the mixed torrefied pellet obtained under optimal conditions were compared to those of torrefied corn cob and khat stem. Pelletization of torrefied bio-residues had a significant effect on all of the properties studied, according to the findings. The torrefied pellet produced had good properties in terms of heating value, bulk density, and durability.

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Acknowledgements

The authors acknowledge all support from the department of Chemical Engineering, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University.

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Correspondence to Bulcha Jifara.

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Jifara, B., Diriba, M. & Mengesha, A. Pelletization of mixed torrefied corn cob and khat stem to enhance the physicochemical and thermal properties of solid biofuel and parametric optimization. Biomass Conv. Bioref. (2022). https://doi.org/10.1007/s13399-022-02627-6

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