TY - JOUR ID - 127217 TI - A review on the modeling and validation of biomass pyrolysis with a focus on product yield and composition JO - Biofuel Research Journal JA - BRJ LA - en SN - AU - Xia, Changlei AU - Cai, Liping AU - Zhang, Haifeng AU - Zuo, Lei AU - Shi, Sheldon Q. AU - Lam, Su Shiung AD - Department of Mechanical Engineering, University of North Texas, Denton, Texas 76203, USA. AD - Mechanical Engineering, NSF I/UCRC Center for Energy Harvesting Materials and Systems (CEHMS), Virginia Tech, 311 Durham Hall, Blacksburg, VA 24061, USA. AD - Higher Institution Centre of Excellence (HICoE), Institute of Tropical Aquaculture and Fisheries (AKUATROP), Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia. Y1 - 2021 PY - 2021 VL - 8 IS - 1 SP - 1296 EP - 1315 KW - Bioenergy KW - Lignocellulose KW - Biomass KW - Pyrolysis KW - reaction kinetics KW - Sensor DO - 10.18331/BRJ2021.8.1.2 N2 - 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. UR - https://www.biofueljournal.com/article_127217.html L1 - https://www.biofueljournal.com/article_127217_40f7608342cfa732cada766f9c1cb278.pdf ER -