A Predictive PBM-DEAM Model for Lignocellulosic Biomass Pyrolysis

Hongyu Zhu, Zhujun Dong, Xi Yu*, Grace Cunningham, Janaki Umashanker, Xingguang Zhang, Anthony V. Bridgwater, Junmeng Cai*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Pyrolysis is a promising and attractive way to convert lignocellulosic biomass into low carbon-emission energy products. To effectively use biomass feedstock with size distribution to produce biofuels, a comprehensive kinetic model of the process, occurring at particle level, is important. In this study, the population balance model (PBM)-distributed activation energy model (DAEM) coupled model is first time developed to predict biomass pyrolysis. The Population balance model is used to present the variable size distribution of solid, decomposed from virgin biomass to porous char. Two different kinetic models are embedded into the conservation equations of mass and energy. They are compared to demonstrate the prediction performance of heating-up time during the pyrolysis process of biomass with a normal size distribution. It is found that non-isothermal kinetics without and with DEAM capture the intra-particle temperature distribution. There is a noticeable difference of heating-up time between single and distributed particle size.
Original languageEnglish
Article number105231
JournalJournal of Analytical and Applied Pyrolysis
Early online date7 Jun 2021
Publication statusPublished - 1 Aug 2021

Bibliographical note

© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Funding: Junmeng Cai appreciated the financial support of this work from CAS Key Laboratory of Renewable Energy (No. Y807k91001). Hongyu Zhu gratefully acknowledges Doctoral Training Programme fund from College of Engineering and Physical Sciences, Aston University.


  • Distributed activation energy model (DAEM)
  • Population balance model (PBM)
  • Kinetics
  • Biomass pyrolysis
  • Temperature distribution


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