4.7 Article

An assessment of biomass torrefaction severity indexes

Journal

FUEL
Volume 288, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2020.119631

Keywords

Indexes of torrefaction; Eucalyptus grandis wood; Torrefaction performance; Linear regression

Funding

  1. Brazilian National Council for Scientific and Technological Development (CNPq)
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) [001]
  3. Distrito Federal Research Support Foundation (FAPDF)

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This study evaluated five indexes commonly used in torrefaction research and found that the three yield property-based indexes were more effective in predicting torrefied product properties and energy performance parameters, while the two operating condition-based indexes were more effective in analyzing solid product properties.
Previous studies have quantified the efficiency of biomass torrefaction processes by proposing severity indexes to discuss the variability of thermally modified biomass properties. However, comparisons of the accuracy and applicability of those indexes are few in the literature. To fill that gap, this study sought to assess five indexes usually applied in some torrefaction studies: weight loss, index of torrefaction, torrefaction severity index, severity factor, and torrefaction severity factor. These indexes were compared to characterize torrefaction under different conditions, and their accuracy in evaluating, correlating and predicting the physical, chemical and energetical properties of torrefied eucalyptus. As a result, the five evaluated indexes presented R-2 > 0.84 andpvalues <= 0.05 when evaluating basic properties. For all five indexes, there was a statistical significance when evaluating energy performance and R-2 > 0.81. The three yield property-based indexes were more effective in predicting torrefied product properties and energy performance parameters. The two operating condition-based indexes were more effective in analyzing solid product properties than devolatilization. This work provided insight into which index is more appropriate for research and industrial applications.

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