EUROPEAN JOURNAL OF SUSTAINABLE DEVELOPMENT RESEARCH
Research Article
Jul 19, 2020 752 491

An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce

Joshua O. Ighalo 1 * ,
Adewale George Adeniyi 1 *
1 Department of Chemical Engineering, Faculty of Engineering and Technology, University of Ilorin, Ilorin, P. M. B. 1515, NIGERIA* Corresponding Author
European Journal of Sustainable Development Research, 2020, 4(4), em0137, https://doi.org/10.29333/ejosdr/8407
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ABSTRACT

In the current investigation, a temperature sensitivity analysis of hard and softwood pyrolysis was conducted on an in silico platform. The selected samples were beech (hardwood), ailanthus (soft hardwood) and spruce (softwood). Upon the successful development of the model on ASPEN Plus v8.8, the results of the model prediction showed that the yield of bio-oil reduced with a rise in process temperature. Beech had the highest bio-oil yield of the feedstock investigated. At 350oC, oil yield was 36.72%, 35.13% and 32.89% for beech, ailanthus and spruce respectively. The syn-gas yield was 39.99%, 38.25% and 35.82% and bio-char yield was 45.44%, 47.58% and 50.77% for beech, ailanthus and spruce respectively (at 650oC). For the entirety of the temperature range studied, a gentle fall in char yield was observed for all feedstock type (though more significant at temperatures above 500oC). The model also predicted the yield of volatiles (bio-oil and syn-gas) to be higher for the hard and soft hardwood than for the softwood and this was vice versa for the char yield.

KEYWORDS

ASPEN Plus Pyrolysis Beech Spruce Ailanthus

CITATION (APA)

Ighalo, J. O., & Adeniyi, A. G. (2020). An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce. European Journal of Sustainable Development Research, 4(4), em0137. https://doi.org/10.29333/ejosdr/8407
Harvard
Ighalo, J. O., and Adeniyi, A. G. (2020). An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce. European Journal of Sustainable Development Research, 4(4), em0137. https://doi.org/10.29333/ejosdr/8407
Vancouver
Ighalo JO, Adeniyi AG. An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce. EUR J SUSTAIN DEV RES. 2020;4(4):em0137. https://doi.org/10.29333/ejosdr/8407
AMA
Ighalo JO, Adeniyi AG. An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce. EUR J SUSTAIN DEV RES. 2020;4(4), em0137. https://doi.org/10.29333/ejosdr/8407
Chicago
Ighalo, Joshua O., and Adewale George Adeniyi. "An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce". European Journal of Sustainable Development Research 2020 4 no. 4 (2020): em0137. https://doi.org/10.29333/ejosdr/8407
MLA
Ighalo, Joshua O. et al. "An In Silico Temperature Sensitivity Study of the Pyrolysis of Beech, Ailanthus and Spruce". European Journal of Sustainable Development Research, vol. 4, no. 4, 2020, em0137. https://doi.org/10.29333/ejosdr/8407

REFERENCES

  1. Abdelouahed, L., Authier, O., Mauviel, G., Corriou, J.-P., Verdier, G. and Dufour, A. (2012). Detailed modeling of biomass gasification in dual fluidized bed reactors under Aspen Plus. Energy & Fuels, 26(6), 3840-3855. https://doi.org/10.1021/ef300411k
  2. Adeniyi, A. G. and Ighalo, J. O. (2019a). Aspen Plus Predictive Simulation of Soft and Hard Wood Pyrolysis for Bio-Energy Recovery. International Journal of Environment and Waste Management, 26(2), 234-244. https://doi.org/10.1504/ijewm.2020.10028695
  3. Adeniyi, A. G. and Ighalo, J. O. (2019b). A review of steam reforming of glycerol. Chemical Papers, 73, 2619-2635. https://doi.org/10.1007/s11696-019-00840-8
  4. Adeniyi, A. G. and Ighalo, J. O. (2020). Computer-Aided Modeling of Thermochemical Conversion Processes for Environmental Waste Management. In: C. M. Hussain (ed) Handbook of Environmental Materials Management (pp 1-16). Springer Nature, Switzerland. https://doi.org/10.1007/978-3-319-58538-3_185-1
  5. Adeniyi, A. G., Ighalo, J. O. and Abdulsalam, A. (2019a). Modelling of Integrated Processes for the Recovery of the Energetic Content of Sugarcane Bagasse. Biofuels, Bioproducts & Biorefining, 13, 1057-1067. https://doi.org/10.1002/bbb.1998
  6. Adeniyi, A. G., Ighalo, J. O. and Aderibigbe, F. A. (2019b). Modelling of integrated processes for the pyrolysis and steam reforming of rice husk (Oryza sativa). SN Applied Sciences, 1, 841. https://doi.org/10.1007/s42452-019-0877-6
  7. Adeniyi, A. G., Ighalo, J. O. and Amosa, K. M. (2019c). Modelling and simulation of banana (Musa spp.) waste pyrolysis for bio-oil production. Biofuels. Published online: 30 Jan 2019. https://doi.org/10.1080/17597269.2018.1554949
  8. Adeniyi, A. G., Ighalo, J. O., Onifade, D. V. and Adeoye, A. S. (2019d). Modelling the Valorisation of Poultry Litter Via Thermochemical Processing. Biofuels, Bioproducts & Biorefining, 14(2), 242-248. https://doi.org/10.1002/bbb.2056
  9. Adeniyi, A. G., Odetoye, T. E., Titiloye, J. and Ighalo, J. O. (2019e). A Thermodynamic Study Of Rice Husk (Oryza Sativa) Pyrolysis. European Journal of Sustainable Development Research, 3(4), em0094. https://doi.org/10.29333/ejosdr/5830
  10. Adeniyi, A. G., Otoikhian, K. S. and Ighalo, J. O. (2019f). Steam Reforming of Biomass Pyrolysis Oil: A Review. International Journal of Chemical Reactor Engineering, 17(4), 20180328. https://doi.org/10.1515/ijcre-2018-0328
  11. Arregi, A., Lopez, G., Amutio, M., Barbarias, I., Bilbao, J. and Olazar, M. (2016). Hydrogen production from biomass by continuous fast pyrolysis and in-line steam reforming. RSC Advances, 6, 25975-25985. https://doi.org/10.1039/C6RA01657J
  12. Asmadi, M., Kawamoto, H. and Saka, S. (2011). Gas-and solid/liquid-phase reactions during pyrolysis of softwood and hardwood lignins. Journal of Analytical and Applied Pyrolysis, 92(2), 417-425. https://doi.org/10.1016/j.jaap.2011.08.003
  13. Block, C., Ephraim, A., Weiss-Hortala, E., Minh, D. P., Nzihou, A. and Vandecasteele, C. (2018). Co-pyrogasifcation of Plastics and Biomass, a Review. Waste and Biomass Valorization, 10, 483-509. https://doi.org/10.1007/s12649-018-0219-8
  14. Collard, F.-X. and Blin, J. (2014). A review on pyrolysis of biomass constituents: Mechanisms and composition of the products obtained from the conversion of cellulose, hemicelluloses and lignin. Renewable and Sustainable Energy Reviews, 38, 594-608. https://doi.org/10.1016/j.rser.2014.06.013
  15. Dabiri Atashbeyk, M., Shahbazi, K. and Fattahi, M. (2018). Pressure Profile Estimation through CFD in UBD Operation Considering with Influx to Wellbore. Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 37(92), 271-283.
  16. Darvishi, A., Davand, R., Khorasheh, F. and Fattahi, M. (2016). Modeling-based optimization of a fixed-bed industrial reactor for oxidative dehydrogenation of propane. Chinese Journal of Chemical Engineering, 24(5), 612-622. https://doi.org/10.1016/j.cjche.2015.12.018
  17. Demirbaş, A. (1997). Calculation of higher heating values of biomass fuels. Fuel, 76(5), 431-434. https://doi.org/10.1016/S0016-2361(97)85520-2
  18. Di Blasi, C. (2008). Modeling chemical and physical processes of wood and biomass pyrolysis. Progress in energy and combustion science, 34(1), 47-90. https://doi.org/10.1016/j.pecs.2006.12.001
  19. Emadi, B., Iroba, K. L. and Tabil, L. G. (2017). Effect of polymer plastic binder on mechanical, storage and combustion characteristics of torrefied and pelletized herbaceous biomass. Applied Energy, 198, 312-319. https://doi.org/10.1016/j.apenergy.2016.12.027
  20. Gani, A. and Naruse, I. (2007). Effect of cellulose and lignin content on pyrolysis and combustion characteristics for several types of biomass. Renewable Energy, 32(4), 649-661. https://doi.org/10.1016/j.renene.2006.02.017
  21. Goyal, H., Seal, D. and Saxena, R. (2008). Bio-fuels from thermochemical conversion of renewable resources: a review. Renewable and Sustainable Energy Reviews, 12(2), 504-517. https://doi.org/10.1016/j.rser.2006.07.014
  22. Gu, H., Tang, Y., Yao, J. and Chen, F. (2018). Study on biomass gasification under various operating conditions. Journal of energy institute, 92(5), 1329-1336. https://doi.org/10.1016/j.joei.2018.10.002
  23. Hosseinpour, S., Aghbashlo, M. and Tabatabaei, M. (2018). Biomass higher heating value (HHV) modeling on the basis of proximate analysis using iterative network-based fuzzy partial least squares coupled with principle component analysis (PCA-INFPLS). Fuel, 222, 1-10. https://doi.org/10.1016/j.fuel.2018.02.126
  24. Ighalo, J. O. and Adeniyi, A. G. (2019). Thermodynamic modelling and temperature sensitivity analysis of banana (Musa spp.) waste pyrolysis. SN Applied Sciences, 1, 1086. https://doi.org/10.1007/s42452-019-1147-3
  25. Ighalo, J. O. and Adeniyi, A. G. (2020). Modelling of thermochemical energy recovery processes for switchgrass (Panicum virgatum). Indian Chemical Engineer. Published online 20 Jan 2020. https://doi.org/10.1080/00194506.2020.1711535
  26. Jahirul, M. I., Rasul, M. G., Chowdhury, A. A. and Ashwath, N. (2012). Biofuels production through biomass pyrolysis—a technological review. Energies, 5(12), 4952-5001. https://doi.org/10.3390/en5124952
  27. Kan, T., Strezov, V. and Evans, T. J. (2016). Lignocellulosic biomass pyrolysis: A review of product properties and effects of pyrolysis parameters. Renewable and Sustainable Energy Reviews, 57, 1126-1140. https://doi.org/10.1016/j.rser.2015.12.185
  28. Khadem-Hamedani, B., Yaghmaei, S., Fattahi, M., Mashayekhan, S. and Hosseini-Ardali, S. M. (2015). Mathematical modeling of a slurry bubble column reactor for hydrodesulfurization of diesel fuel: Single-and two-bubble configurations. Chemical Engineering Research and Design, 100, 362-376.
  29. Licker, D. M. (2003). Dictionary of Engineering (2nd edn.). Chicago: Mc-Graw Hill Publishers.
  30. Mohan, D., Pittman, C. U. and Steele, P. H. (2006). Pyrolysis of wood/biomass for bio-oil: a critical review. Energy & Fuels, 20(3), 848-889. https://doi.org/10.1021/ef0502397
  31. Moradi, F., Kazemeini, M. and Fattahi, M. (2014). A three dimensional CFD simulation and optimization of direct DME synthesis in a fixed bed reactor. Petroleum Science, 11, 323-330. https://doi.org/10.1007/s12182-014-0347-0
  32. Onarheim, K., Solantausta, Y. and Lehto, J. (2014). Process simulation development of fast pyrolysis of wood using aspen plus. Energy & Fuels, 29(1), 205-217. https://doi.org/10.1021/ef502023y
  33. Peters, J. F., Iribarren, D. and Dufour, J. (2013). Predictive pyrolysis process modelling in Aspen Plus. In: 21st Eur biomass conf exhib (pp. 923-927). https://doi.org/10.5071/21stEUBCE2013-2CV.4.8
  34. Peters, J. F., Iribarren, D. and Dufour, J. (2015). Simulation and life cycle assessment of biofuel production via fast pyrolysis and hydroupgrading. Fuel, 139, 441-456. https://doi.org/10.1016/j.fuel.2014.09.014
  35. Qu, T., Guo, W., Shen, L., Xiao, J. and Zhao, K. (2011). Experimental Study of Biomass Pyrolysis Based on Three Major Components: Hemicellulose, Cellulose, and Lignin. Industrial & Engineering Chemistry Research, 50(18), 10424-10433. https://doi.org/10.1021/ie1025453
  36. Santamaria, L., Lopez, G., Arregi, A., Amutio, M., Artetxe, M., Bilbao, J. and Olazar, M. (2018). Influence of the support on Ni catalysts performance in the in-line steam reforming of biomass fast pyrolysis derived volatiles. Applied Catalysis B: Environmental, 229, 105-113. https://doi.org/10.1016/j.apcatb.2018.02.003
  37. Sharma, A., Pareek, V. and Zhang, D. (2015). Biomass pyrolysis—A review of modelling, process parameters and catalytic studies. Renewable and Sustainable Energy Reviews, 50, 1081-1096. https://doi.org/10.1016/j.rser.2015.04.193
  38. Sinha, S., Jhalani, A., Ravi, M. and Ray, A. (2000). Modelling of pyrolysis in wood: A review. SESI Journal, 10, 41-62.
  39. Torabi, A., Kazemeini, M. and Fattahi, M. (2016). Developing a mathematical model for the oxidative dehydrogenation of propane in a fluidized bed reactor. Asia‐Pacific Journal of Chemical Engineering, 11(3), 448-459. https://doi.org/10.1002/apj.1966
  40. Valle, B., Aramburu, B., Benito, P. L., Bilbao, J. and Gayubo, A. G. (2018). Biomass to hydrogen-rich gas via steam reforming of raw bio-oil over Ni/La 2 O 3-αAl 2 O 3 catalyst: Effect of space-time and steam-to-carbon ratio. Fuel, 216, 445-455. https://doi.org/10.1016/j.fuel.2017.11.151

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