IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v191y2020ics0360544219321966.html
   My bibliography  Save this article

Predicting heating value of lignocellulosic biomass based on elemental analysis

Author

Listed:
  • Huang, Yu-Fong
  • Lo, Shang-Lien

Abstract

Heating value is one of the most important properties for bioenergy recovery from lignocellulosic biomass. Various correlations have been established to predict the heating value. This study presents a new correlation to predict the higher heating value (HHV) of lignocellulosic biomass based on its elemental composition: HHV = 0.3443C + 1.192H-0.113O–0.024 N + 0.093S. Compared with the correlations reported in the literature, the relative error of the correlation proposed in this study is lowest, and its coefficient of determination (R2) is highest. Therefore, the new correlation should be capable of providing more accurate HHV prediction than other correlations. For most of the lignocellulosic biomass feedstocks, the absolute percentage errors between the measured HHV and those predicted by using the correlation can be less than approximately 3%. The HHV prediction by using the correlation is satisfactory not only for lignocellulosic biomass feedstocks but also for biochar and various kinds of fossil fuels. Besides, the correlation can be also used for predicting the HHV of other organic matters such as municipal solid waste, industrial waste, and sewage sludge, after the modification of the coefficient before oxygen content based on the characteristics of the matter.

Suggested Citation

  • Huang, Yu-Fong & Lo, Shang-Lien, 2020. "Predicting heating value of lignocellulosic biomass based on elemental analysis," Energy, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:energy:v:191:y:2020:i:c:s0360544219321966
    DOI: 10.1016/j.energy.2019.116501
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219321966
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116501?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
    2. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alex Borges Pereira & Antonio José Vinha Zanuncio & Amélia Guimarães Carvalho & Angélica de Cassia Oliveira Carneiro & Vinícius Resende de Castro & Ana Marcia Macedo Ladeira Carvalho & Olivia Pereira , 2024. "Sustainable Solid Biofuel Production: Transforming Sewage Sludge and Pinus sp. Sawdust into Resources for the Circular Economy," Sustainability, MDPI, vol. 16(11), pages 1-11, May.
    2. Agata Borowik & Jadwiga Wyszkowska & Magdalena Zaborowska & Jan Kucharski, 2024. "Energy Quality of Corn Biomass from Gasoline-Contaminated Soils Remediated with Sorbents," Energies, MDPI, vol. 17(21), pages 1-18, October.
    3. Catarina Viegas & Catarina Nobre & Ricardo Correia & Luísa Gouveia & Margarida Gonçalves, 2021. "Optimization of Biochar Production by Co-Torrefaction of Microalgae and Lignocellulosic Biomass Using Response Surface Methodology," Energies, MDPI, vol. 14(21), pages 1-23, November.
    4. Marcin Cichosz & Sławomir Łazarski & Andrzej Butarewicz & Urszula Kiełkowska, 2023. "Biogas Production—The Effect of the Zinc Concentration on the Profile of Volatile Fatty Acids in Fermentation Mixtures," Energies, MDPI, vol. 16(21), pages 1-24, November.
    5. Kartal, Furkan & Özveren, Uğur, 2022. "Prediction of torrefied biomass properties from raw biomass," Renewable Energy, Elsevier, vol. 182(C), pages 578-591.
    6. Hongli Chen & Liqiang Zhang & Zhongliang Huang & Zijian Wu & Mengjiao Tan & Xuan Zhang & Longbo Jiang & Xiaoli Qin & Jing Huang & Hui Li, 2022. "Effect of Anoxic Atmosphere on the Physicochemical and Pelletization Properties of Pinus massoniana Sawdust during Storage," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
    7. Mollanoori, Mohammad & Dehghan, Ali Akbar, 2024. "Estimating the higher heating value and chemical exergy of solid, liquid, and natural gas fossil fuels," Energy, Elsevier, vol. 302(C).
    8. Carvalho, Pollyana R. & Medeiros, Samuel L.S. & Paixão, Raul L. & Figueredo, Igor M. & Mattos, Adriano L.A. & Rios, M. Alexsandra S., 2023. "Thermogravimetric pyrolysis of residual biomasses obtained post-extraction of carnauba wax: Determination of kinetic parameters using Friedman's isoconversional method," Renewable Energy, Elsevier, vol. 207(C), pages 703-713.
    9. Chen, Xiaoling & Zhang, Yongxing & Xu, Baoshen & Li, Yifan, 2022. "A simple model for estimation of higher heating value of oily sludge," Energy, Elsevier, vol. 239(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    2. Govind, Ajit & Chen, Jing Ming & Bernier, Pierre & Margolis, Hank & Guindon, Luc & Beaudoin, Andre, 2011. "Spatially distributed modeling of the long-term carbon balance of a boreal landscape," Ecological Modelling, Elsevier, vol. 222(15), pages 2780-2795.
    3. Eliseev, Alexey V. & Mokhov, Igor I., 2008. "Eventual saturation of the climate–carbon cycle feedback studied with a conceptual model," Ecological Modelling, Elsevier, vol. 213(1), pages 127-132.
    4. Brovkin, Victor & Cherkinsky, Alexander & Goryachkin, Sergey, 2008. "Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia," Ecological Modelling, Elsevier, vol. 216(2), pages 178-187.
    5. Ulaganathan, Kandasamy & Goud, Sravanthi & Reddy, Madhavi & Kayalvili, Ulaganathan, 2017. "Genome engineering for breaking barriers in lignocellulosic bioethanol production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1080-1107.
    6. Brazhnik, Ksenia & Shugart, H.H., 2016. "SIBBORK: A new spatially-explicit gap model for boreal forest," Ecological Modelling, Elsevier, vol. 320(C), pages 182-196.
    7. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
    8. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    9. Ouardighi, Fouad El & Sim, Jeong Eun & Kim, Bowon, 2016. "Pollution accumulation and abatement policy in a supply chain," European Journal of Operational Research, Elsevier, vol. 248(3), pages 982-996.
    10. Kim, Hyeyoung & House, Lisa A. & KIm, Tae-Kyun, 2016. "Consumer perceptions of climate change and willingness to pay for mandatory implementation of low carbon labels: the case of South Korea," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(4), October.
    11. Guoju, Xiao & Weixiang, Liu & Qiang, Xu & Zhaojun, Sun & Jing, Wang, 2005. "Effects of temperature increase and elevated CO2 concentration, with supplemental irrigation, on the yield of rain-fed spring wheat in a semiarid region of China," Agricultural Water Management, Elsevier, vol. 74(3), pages 243-255, June.
    12. Sogol Moradian & Farhad Yazdandoost, 2021. "Seasonal meteorological drought projections over Iran using the NMME data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1089-1107, August.
    13. Viola, Flavio M. & Paiva, Susana L.D. & Savi, Marcelo A., 2010. "Analysis of the global warming dynamics from temperature time series," Ecological Modelling, Elsevier, vol. 221(16), pages 1964-1978.
    14. Farrelly, Damien J. & Everard, Colm D. & Fagan, Colette C. & McDonnell, Kevin P., 2013. "Carbon sequestration and the role of biological carbon mitigation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 712-727.
    15. Marc Kennedy & Clive Anderson & Anthony O'Hagan & Mark Lomas & Ian Woodward & John Paul Gosling & Andreas Heinemeyer, 2008. "Quantifying uncertainty in the biospheric carbon flux for England and Wales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 109-135, January.
    16. Yonghua Li & Song Yao & Hezhou Jiang & Huarong Wang & Qinchuan Ran & Xinyun Gao & Xinyi Ding & Dandong Ge, 2022. "Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China," Land, MDPI, vol. 11(12), pages 1-22, December.
    17. Sara J. Germain & James A. Lutz, 2020. "Climate extremes may be more important than climate means when predicting species range shifts," Climatic Change, Springer, vol. 163(1), pages 579-598, November.
    18. Xiongwen Chen & Wilfred Post & Richard Norby & Aimée Classen, 2011. "Modeling soil respiration and variations in source components using a multi-factor global climate change experiment," Climatic Change, Springer, vol. 107(3), pages 459-480, August.
    19. Wang, Tao & Yu, Wei & Le Moullec, Yann & Liu, Fei & Xiong, Yili & He, Hui & Lu, Jiahui & Hsu, Emily & Fang, Mengxiang & Luo, Zhongyang, 2017. "Solvent regeneration by novel direct non-aqueous gas stripping process for post-combustion CO2 capture," Applied Energy, Elsevier, vol. 205(C), pages 23-32.
    20. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:191:y:2020:i:c:s0360544219321966. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.