Characterizing Variability in Lignocellulosic Biomass: A Review

Jipeng Yan, Oluwafemi Oyedeji, Juan Leal, Bryon Donohoe, Troy Semelsberger, Chenlin Li, Amber Hoover, Erin Webb, Elizabeth Bose, Yining Zeng, C. Luke Williams, Kastli Schaller, Ning Sun, Allison Ray, Deepti Tanjore

Research output: Contribution to journalArticlepeer-review

54 Scopus Citations

Abstract

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Currently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We also examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

Original languageAmerican English
Pages (from-to)8059-8085
Number of pages27
JournalACS Sustainable Chemistry and Engineering
Volume8
Issue number22
DOIs
StatePublished - 8 Jun 2020

Bibliographical note

Publisher Copyright:
Copyright © 2020 American Chemical Society.

NREL Publication Number

  • NREL/JA-2700-76162

Keywords

  • Biomass characterization
  • Feedstock variability
  • Operational reliability
  • Physical and chemical properties

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