Effect of Torrefaction Treatment in Energy Content Enhancement of Solid Fuel Properties from Teak Biomass Waste
Keywords:
Energy content, teak biomass, solid biofuel, carbon content, heating valuesAbstract
Torrefaction of biomass produces high-grade solid biofuel from woody biomass or agricultural waste, resulting in high-quality solid biofuel. The study aims to enhance the energy content and efficiency of solid biofuel from waste teak biomass, addressing global energy needs and sustainable alternatives. A 60.8-liter reactor carbonized 5 kg of biomass per batch at 350°C and 400°C, with 40 minutes and 1 hour of residence time. Torrefied biomass was collected and characterized for energy content. Increases in torrefied temperature (TT) and residence time (RT) lead to a significant increase of 15 – 50 % in total carbon content while decreasing hydrogen, oxygen, and moisture content compared to untreated biomass. The study reveals that the energy yield of torrefied biomass is higher than its mass yield and that increasing TT leads to an increase in its bulk density content. The study found that torrefied products had heating values up to 70% higher than unprocessed biomass and a maximum calorific value of around 30 MJ/kg. This research suggests that the solid fuel produced could potentially reduce the release of pollutants into the atmosphere compared to fossil fuels. The biomass teak sample under examination has shown significant potential for efficient energy generation and combustion applications.
References
Basu, P. (2018). Biomass Gasification, Pyrolysis and Torrefaction: Practical Design and Theory. 3rd Edition, Academic Press, Elsevier.
Bhar, R., Tiwari, B. R., Sarmah, A.K., Brar, S.K., and Dubey, B. K. (2022). A comparative life cycle assessment of different pyrolysis-pretreatment pathways of wood biomass for levoglucosan production. Bioresource Technology, 356, 127305. http://doii.org/1016/j.biortech.2022.127305
Cahyanti, M. N., Doddapaneni, T. R., and Kikas, T. (2020). Biomass torrefaction: An overview on process parameters, economic and environmental aspects and recent advancements. Bioresource Technology, 301, 122737. https://doi.org/10.1016/j.biortech.2020.122737
Cai, J., He, Y., Yu, X., Banks, S.W., Yang, Y., Zhang, X., Yu, Y., Liu, R. and Bridgwater, A.V. (2017). Review of physicochemical properties and analytical characterization of lignocellulosic biomass. Renew. Sustain. Energy Rev., 76, 309–322.
Chen, W.H., Peng, P., and Bi, X.T. (2015). A state-of-the-art review of biomass torrefaction, densification and applications, Renewable and Sustainable Energy Reviews, 44(2), 847-866
Chin, K., Ibrahim, S., Hakeem, K., H’ng, P., Lee, S., and Mohd L.M. (2017). Bioenergy production from bamboo: Potential source from Malaysia’s perspective. Bio. Res. 12(3), 6844-6867.
García, R., González-Vázquez, M.P., Martín, A.J. and Pevida, C. and Rubiera, F. (2020). Pelletization of torrefied biomass with solid and liquid bio-additives Renew. Energy, 151, 175-183
Gaurav, G.K., Mehmood, T., Cheng, L., Klemeš, J.J. and Shrivastava, D.K. (2020). Water hyacinth as a biomass: a review. J. Clean. Prod., 277, Article 122214
Güleç, F., Pekaslan, D., Williams, O. and Lester, E. (2022). Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses: A comprehensive study of artificial neural network applications. Fuel, 320, 123944.
Heredia S.M., Tarelho, L.A.C., Rivadeneira, D., Ramírez, V. and Sinche, D. (2020) Energetic valorization of the residual biomass produced during Jatropha curcas oil extraction Renew. Energy, 146, pp. 1640-1648
Ibitoye, S.E., Jen, T.C. Mahamood, R.M. and Akinlabi, E.T. (2021). Generation of Sustainable Energy from Agro-residues through Thermal Pretreatment for Developing Nations: A Review. Adv. Energy Sustain. Res., 2, Article 2100107.
Ighalo, J.O., Adeniyi, A.G., Marques, G. (2020). Application of linear regression algorithm and stochastic gradient descent in a machine- learning environment for predicting biomass higher heating value. Biofuels Bioprod, 14, 1286–1295.
Lee, J.W., Kim, Y.H., Lee, S.M., and Lee, H.W. (2012). Optimizing the Torrefaction of Mixed Softwood by Response Surface Methodology for Biomass Upgrading to High Energy Density. Bioresour. Tech. 116, 471–476. doi: 10.1016/j.biortech, 03.122
Manouchehrinejad, M., Bilek, E. M. T., & Mani, S. (2021). Techno-economic analysis of integrated torrefaction and pelletization systems to produce torrefied wood pellets. Renewable Energy, 178, 483–493. https://doi.org/10.1016/j.renene.2021.06.064
Nieto, P.J., García-Gonzalo, E., Lasheras, F.S., Paredes-Sánchez, J.P. and Fernández, P.R. (2019). Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques. J. Comput. Appl. Math, 357, 284–301.
Qian, C., Li, Q., Zhang, Z., Wang, X., Hu, J. and Cao, W. (2020). Prediction of higher heating values of biochar from proximate and ultimate analysis. Fuel, 265, 116925.
Qian, C., Li, Q., Zhang, Z., Wang, X., Hu, J. and Cao, W. (2020). Prediction of higher heating values of biochar from proximate and ultimate analysis. Fuel, 265, 116925.
Razi, A. Mohd-Azlan M. I., Khudzir, I. and Nur-Nasulhah, K. (2018). Influence of Torrefaction on Gasification of Torrefied Palm Kernel Shell. Advances in Science, Technology and Engineering Systems Journal, 3(5), 166-170.
Romero, J.A., Daniele, D., Vittorio, M., Sara D.S., Carmine D. F. and Giuseppe, T. (2023) Preliminary Study on the Thermal Behavior and Chemical-Physical Characteristics of Woody Biomass as Solid Biofuels. Department of Agricultural, Food and Environmental Sciences, Università Politecnica Delle Marche, Via Brecce Bianche, 60131 Ancona, Italy. Processes 2023, 11(1), 154; https://doi.org/10.3390/pr11010154
San M.G, Sánchez, F., Pérez, A. and Velasco, V. (2022). One-step torrefaction and densification of woody and herbaceous biomass feedstocks Renew. Energy, 195, 825-840.
Taki, M and Rohani, A. (2017). Machine learning models for prediction the higher heating value (HHV) of municipal solid waste (MSW) for waste-to-energy evaluation. Case Stud. Therm. Eng., 31, 101823.
Tan, P., Zhang, C., Xia, J., Fang, Q.Y. and Chen, G. (2015). Estimation of higher heating value of coal based on proximate analysis using support vector regression. Fuel Process Technol., 138, 298–304.
Tilahun, F.B., Bhandari, R. and Mamo, M. (2021). Design optimization of a hybrid solar-biomass plant to sustainably supply energy to industry: methodology and case study. Energy, 220, Article 119736.
Uddin, M.N., Taweekun, J., Techato, K., Rahman, M.A. Mofijur, M. and Rasul, M.G. (2019). Sustainable biomass as an alternative energy source: Bangladesh perspective. Energy Procedia, 160, 648-654.
Umenweke, G.C., Afolabi, I.C., Epelle, E.I. and Okolie, J.A. (2022). Machine learning methods for modelling conventional and hydrothermal gasification of waste biomass: A review. Bioresour. Technol. Rep, 17, 100976.
Uzun, H., Yıldız, Z., Goldfarb, J. L., and Ceylan, S. (2017). Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis. Bioresource Technology, 234, 122-130. https://doi.org/10.1016/j.biortech.2017.03.015
Wild, M., and Calderon, C. (2021). Torrefied biomass and where is the sector currently standing in terms of research, technology development, and implementation. Bioenergy and Biofuels, 9, Article 678492.
Yoo, H.M., Park, S.W., Seo, Y.C. and Kim, K.H. (2019). Applicability assessment of empty fruit bunches from palm oil mills for use as bio-solid refuse fuels. J. Environ. Manag., 234, 1-7.
Yue, Y., Singh, H., Singh, B., and Mani, S. (2017). Torrefaction of sorghum biomass to improve fuel properties. Bioresource technology, 232, 372-379.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Oginni, O.T.
This work is licensed under a Creative Commons Attribution 4.0 International License.
