Open-source kinetic modelling of downdraft biomass gasification in Python: validation and parametric analysis of syngas quality

IF 7 2区生物学 Q1 AGRICULTURAL ENGINEERING

Biomass & Bioenergy Pub Date : 2026-08-01 Epub Date: 2026-03-06 DOI:10.1016/j.biombioe.2026.109216

Daniel Chuquín-Vasco , Juan Ignacio Torregrosa-López , Vanesa G. Lo-Iacono-Ferreira

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Abstract

An open-source, kinetic model for downdraft biomass gasification was developed in Python to provide a transparent and reproducible reactor-scale framework. The approach integrates coupled mass and energy balances with a 26-reaction kinetic set describing drying, multi-stage pyrolysis, oxidation, reduction, and tar cracking in a plug-flow configuration. Validation against laboratory-scale experimental data for Scots pine under air-blown conditions yielded an average mean absolute percentage error (MAPE) of 3.03% and a root mean square error (RMSE) of 0.6693 for major syngas species (CO, CO₂, H₂, CH₄). Additional validation using Miscanthus briquettes and rubber wood confirmed predictive robustness without parameter re-tuning, maintaining RMSE values below the established acceptance threshold (RMSE <1.60). Parametric analysis was conducted across representative ranges of equivalence ratio (ER), addition of steam(S/B), and pyrolysis temperature. Increasing ER reduced tar from 27.63 to 1.21 g Nm⁻³ but decreased syngas energy content beyond the optimal point (ER ≈ 0.32). The higher heating value (HHV) ranged from 4.02 to 5.24 MJ Nm⁻³, while lower heating value (LHV) reached 4.97 MJ Nm⁻³ at elevated pyrolysis temperatures. Steam addition increased H₂ up to 12.99 vol% (≈37% increase) with limited tar reduction (<5%). Temperature exerted the strongest influence, promoting near-complete tar conversion (99.7%). Overall, the proposed framework supports parametric, and reproducible model-based design of downdraft gasifiers.

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Python下气流生物质气化的开源动力学建模：合成气质量的验证和参数分析

在Python中开发了一个开源的向下气流生物质气化动力学模型，以提供透明和可复制的反应堆规模框架。该方法将耦合的质量和能量平衡与26个反应动力学集集成在一起，描述了塞流配置中的干燥、多阶段热解、氧化、还原和焦油裂解。根据实验室规模的实验数据对吹气条件下的苏格兰松进行验证，对主要合成气物种（CO, CO2, H2, CH4）的平均绝对百分比误差（MAPE）为3.03%，均方根误差（RMSE）为0.6693。使用芒草型煤和橡胶木进行的进一步验证证实了预测的稳健性，无需重新调整参数，将RMSE值保持在既定的可接受阈值（RMSE <1.60）以下。在等效比（ER）、蒸汽添加量（S/B）和热解温度的代表性范围内进行参数分析。增加ER可使焦油从27.63 g Nm−3降低到1.21 g Nm−3，但使合成气能含量降低到最佳点（ER≈0.32）以上。较高的热值（HHV）为4.02 ~ 5.24 MJ Nm−3，较高的热值（LHV）为4.97 MJ Nm−3。水蒸气的加入使H2增加到12.99 vol%(≈37%)，而焦油的减少量有限（<5%）。温度的影响最大，促进了近完全的焦油转化（99.7%）。总体而言，所提出的框架支持参数化和可重复的基于模型的下吸式气化炉设计。

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来源期刊

Biomass & Bioenergy 工程技术-能源与燃料

CiteScore

11.50

自引率

3.30%

发文量

258

审稿时长

60 days

期刊介绍： Biomass & Bioenergy is an international journal publishing original research papers and short communications, review articles and case studies on biological resources, chemical and biological processes, and biomass products for new renewable sources of energy and materials. The scope of the journal extends to the environmental, management and economic aspects of biomass and bioenergy. Key areas covered by the journal: • Biomass: sources, energy crop production processes, genetic improvements, composition. Please note that research on these biomass subjects must be linked directly to bioenergy generation. • Biological Residues: residues/rests from agricultural production, forestry and plantations (palm, sugar etc), processing industries, and municipal sources (MSW). Papers on the use of biomass residues through innovative processes/technological novelty and/or consideration of feedstock/system sustainability (or unsustainability) are welcomed. However waste treatment processes and pollution control or mitigation which are only tangentially related to bioenergy are not in the scope of the journal, as they are more suited to publications in the environmental arena. Papers that describe conventional waste streams (ie well described in existing literature) that do not empirically address ''new'' added value from the process are not suitable for submission to the journal. • Bioenergy Processes: fermentations, thermochemical conversions, liquid and gaseous fuels, and petrochemical substitutes • Bioenergy Utilization: direct combustion, gasification, electricity production, chemical processes, and by-product remediation • Biomass and the Environment: carbon cycle, the net energy efficiency of bioenergy systems, assessment of sustainability, and biodiversity issues.