Abstract Pyrolysis transforms bulky and heterogeneous lignocellulosic biomass into more easily-handled oils that can be upgraded into bio-based transportation fuels. Existing systems for monitoring pyrolysis processes and characterizing their products rely on slow and time-consuming wet chemical analyses. On-line near-infrared (NIR) spectroscopy could potentially replace such analyses, providing real-time data and reducing costs. To test the usefulness of NIR methods in characterizing pyrolysis oils and processes, biomass from conifers, Salix, and reed canary grass was milled and pyrolyzed at 675, 750, and 775 °C. Two separate pyrolytic fractions (aerosol and condensed) were produced in each experiment, and NIR spectra were collected for each fraction. Multivariate modelling of the resulting data clearly showed that the samples’ NIR spectra could be used to accurately predict important properties of the pyrolysis oils such as their energy values, main organic element (C, H and O) contents, and water content. The spectra also contained predictive information on the samples’ origins, fraction, and temperature treatment, demonstrating the potential of on-line NIR techniques for monitoring pyrolytic production processes and characterizing important properties of pyrolytic oils from lignocellulosic biomass.

中文翻译：

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通过近红外光谱数据表征快速热解生物油的特性

摘要 热解将庞大且异质的木质纤维素生物质转化为更易于处理的油，这些油可以升级为生物基运输燃料。用于监测热解过程和表征其产品的现有系统依赖于缓慢且耗时的湿化学分析。在线近红外 (NIR) 光谱可能会取代此类分析，提供实时数据并降低成本。为了测试 NIR 方法在表征热解油和过程中的有用性，将来自针叶树、柳属和金丝雀草的生物质在 675、750 和 775 °C 下研磨和热解。在每个实验中产生两个单独的热解馏分（气溶胶和冷凝），并为每个馏分收集 NIR 光谱。结果数据的多变量建模清楚地表明，样品的 NIR 光谱可用于准确预测热解油的重要特性，例如它们的能量值、主要有机元素（C、H 和 O）含量和水含量。光谱还包含有关样品来源、馏分和温度处理的预测信息，证明了在线 NIR 技术在监测热解生产过程和表征木质纤维素生物质热解油的重要特性方面的潜力。