Predicting heating value of lignocellulosic biomass based on elemental analysis

Yu-Fong Huang and Shang-Lien Lo

Energy, 2020, vol. 191, issue C

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.

Keywords: Heating value; Lignocellulosic biomass; Elemental analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544219321966
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:191:y:2020:i:c:s0360544219321966

DOI: 10.1016/j.energy.2019.116501

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().