Abstract
Modeling is regarded as a suitable tool to improve biomass pyrolysis in terms of efficiency, product yield, and controllability. However, it is crucial to develop advanced models to estimate products' yield and composition as functions of biomass type/characteristics and process conditions. Despite many developed models, most of them suffer from insufficient validation due to the complexity in determining the chemical compounds and their quantity. To this end, the present paper reviewed the modeling and verification of products derived from biomass pyrolysis. Besides, the possible solutions towards more accurate modeling of biomass pyrolysis were discussed. First of all, the paper commenced reviewing current models and validating methods of biomass pyrolysis. Afterward, the influences of biomass characteristics, particle size, and heat transfer on biomass pyrolysis, particle motion, reaction kinetics, product prediction, experimental validation, current gas sensors, and potential applications were reviewed and discussed comprehensively. There are some difficulties with using current pyrolysis gas chromatography and mass spectrometry (Py-GC/MS) for modeling and validation purposes due to its bulkiness, fragility, slow detection, and high cost. On account of this, the applications of Py-GC/MS in industries are limited, particularly for online product yield and composition measurements. In the final stage, a recommendation was provided to utilize high-temperature sensors with high potentials to precisely validate the models for product yield and composition (especially CO, CO2, and H2) during biomass pyrolysis.
Highlights
The present paper reviewed the modeling and verification of products derived from biomass pyrolysis
According to the reviews on microwave-assisted pyrolysis (MAP) of biomass (Yin, 2012) and pyrolysis carbonization technologies (Si et al, 2015), it could be concluded that MAP would be one of the most promising biomass pyrolysis methods because the microwave dielectric heating could effectively heat biomass feedstocks at the heating stage
Small particle sizes were more favorable during pyrolysis
Summary
There are a handful of review articles focusing on the pyrolysis modeling of biomass In this context, Sharma et al (2015) reviewed the developments of mathematical modeling for particle movement and its interaction with the carrier gas flow during pyrolysis. Papari and Hawboldt (2015) reviewed the biomass pyrolysis mechanisms in large-scale reactors and compared the results with the experimental data obtained from a lab-scale tube reactor. They concluded that the most accurate model for predicting the pyrolysis product yields was the chemical percolation de-volatilization model developed by Lewis and Fletcher (2013). The utilization of the distributed activation energy model (DAEM) in the pyrolysis of biomass was reviewed by Cai et al (2014)
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