Two-Stage Global Biomass Pyrolysis Model for Combustion Applications: Predicting Product Composition with a Focus on Kinetics, Energy, and Mass Balances Consistency

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Abstract

This work presents a comprehensive model for lignocellulosic biomass pyrolysis, addressing kinetics, energy balances, and gas product composition with the aim of its application in wood combustion. The model consists of a two-stage global mechanism in which biomass initially reacts into tar, char, and light gases (non-condensable gases), which is followed by tar reacting into light gases and char. Experimental data from the literature are employed for determining Arrhenius kinetic parameters and key energy parameters, like tar and char heating values and the specific enthalpy of primary and secondary reactions. A methodology is introduced to derive correlations, allowing the model’s application to diverse biomass types. This work introduces several novel approaches. Firstly, a pyrolysis model that determines the composition of light gases by solving mass, species, and energy balances is developed, limiting the use of correlations from the literature only for tar and char elemental composition. The mass rate of light gases, tar, and char being produced is also determined. Secondly, kinetic parameters for primary and secondary reactions are determined following a Shafizadeh and Chin scheme but with a modified Arrhenius form dependent on (Formula presented.), significantly enhancing the accuracy of product composition prediction. Additionally, correlations for the enthalpies of reactions, both primary and secondary, are determined as a function of pyrolysis temperature. Primary reactions exhibit an overall endothermic behavior, while secondary reactions exhibit an overall exothermic behavior. Finally, the model is validated using cases reported in the literature, and results for light gases composition are presented.

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Navarrete Cereijo, G., Galione Klot, P., & Curto-Risso, P. (2024). Two-Stage Global Biomass Pyrolysis Model for Combustion Applications: Predicting Product Composition with a Focus on Kinetics, Energy, and Mass Balances Consistency. Energies, 17(19). https://doi.org/10.3390/en17194982

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