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Evaluation of the number of first-order reactions required to accurately model biomass pyrolysis

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2021-03-15
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Abstract
Thermogravimetric analysis (TGA) experimental measurements, combined with modeling techniques, are widely employed for the characterization of the pyrolysis process of all kinds of biomass. The present work evaluates the number of reactions required to accurately model the pyrolysis process of lignocellulosic biomass, microalgae, and sewage sludge. A model with different number of parallel first-order reactions, from a single reaction up to ten reactions, is tested to fit the experimental TGA pyrolysis results, obtained for constant heating rates, and to determine the required optimal number of reactions for each type of biomass. The results show that the optimal number of reactions to precisely model the kinetics of lignocellulosic biomass is 5, whereas a model of 6 reactions is optimal for the characterization of microalgae and 8 reactions are required to accurately model the pyrolysis of sewage sludge. The outcome of the model, expressed in terms of the pyrolysis kinetics parameters and the relative contribution of each of the parallel reactions on the overall process, can be successfully extrapolated to the use of inverse exponential temperature increases, which are characteristic of pyrolysis processes occurring in isothermal reactors. Under these circumstances, the model is also capable of accurately reproducing the experimental results for all the different maximum temperatures and exponential temperature increases tested, demonstrating its robustness and applicability to pyrolysis processes occurring under non-linear temperature increases.
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Biomass Pyrolysis, Kinetic Modeling, Microalgae, Lignocellulosic, Biomass, Sewage Sludge
Bibliographic citation
Cano-Pleite, E., Rubio-Rubio, M., Riedel, U., & Soria-Verdugo, A. (2021). Evaluation of the number of first-order reactions required to accurately model biomass pyrolysis. Chemical Engineering Journal (Lausanne, Switzerland: 1996), 408(127291), 127291