Systematic review identifies modeling approaches and gaps in biomass torrefaction research, highlighting improvement needs.
Torrefaction transforms heterogeneous biomass into a carbon-rich, torrefied solid biofuel. This process upgrades raw biomass properties, facilitating its use in gasification and co-pyrolysis, thereby increasing the share of renewable energy and mitigating fossil fuel reliance. Thermogravimetric analysis (TGA) provides kinetic parameters for reactor design and optimization, with precise kinetic models for laboratory-scale applications. However, this field encompasses diverse and often heterogeneous modeling methods that necessitate a systematic mapping of what has been observed in the current literature and where critical gaps exist. This study systematically reviewed 77 research articles from 2019 to 2025, following PRISMA guidelines. The quantitative results reveal a concentration of research in specific geographical areas (China, Brazil, and India), which is linked to a strong focus on traditional raw materials such as wood biomass (36%) and agricultural residues (30%), while invasive and non-native species have not been sufficiently studied. Regarding methodologies, model-free isoconversional methods such as Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO) are widely used and dominate recent torrefaction kinetics studies, with 31.3% of the research due to their advantage in avoiding fixed reaction mechanisms. However, this review also found that 45% of the studies referenced here use only statistical fitting (R²) for validation purposes, with little model comparison occurring; this indicates an increased risk of developing model-dependent kinetic parameters with limited robustness and industrial applicability. In the end, more work is needed to systematically apply multi-model validation strategies with increased raw material diversity, thereby developing comprehensive and reliable results that can be scaled to include commercial efforts.
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Sakhraji et al. (2026) studied this question.
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