Predicting heating value of lignocellulosic biomass based on elemental analysis
Journal
Energy
Journal Volume
191
Date Issued
2020
Author(s)
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. © 2019 Elsevier Ltd
Subjects
Elemental analysis; Heating value; Lignocellulosic biomass
Other Subjects
Calorific value; Chemical analysis; Feedstocks; Forecasting; Fossil fuels; Heating; Lignocellulosic biomass; Municipal solid waste; Sewage sludge; Coefficient of determination; Elemental compositions; Heating value; Higher heating value; New correlations; Oxygen content; Percentage error; Relative errors; Biomass; bioenergy; biomass; cellulose; chemical analysis; heating; lignin; prediction
Type
journal article