University of Alberta, Department of Chemistry, Edmonton, T6G2G2, Alberta, Canada.
University of Alberta, Department of Chemistry, Edmonton, T6G2G2, Alberta, Canada; University of British Columbia, Department of Medicine, Vancouver, V6T1Z4, British Columbia, Canada.
Chemosphere. 2024 Oct;366:143445. doi: 10.1016/j.chemosphere.2024.143445. Epub 2024 Oct 4.
Biomass burning is a global source of climate- and health-affecting emissions. The impacts of biomass burning emissions (BBE) are tied to their complex and variable chemical makeup. For instance, the nitrogen content of BBE influences their capacity to absorb light, and therefore affect the Earth's radiative budget. Factors such as temperature, biomass type, or air flow rate during the combustion all modify the composition of BBE, making accurate characterization challenging. Herein, for the first time, principal component analysis (PCA) was applied to emissions gathered during laboratory-based combustion of wood and cow dung biomass in a tube furnace. A thermal desorption two dimensional time-of-flight gas chromatography mass spectrometry (TD-GC × GC-ToF-MS) setup was employed to separate and identify chemical species. By combining these techniques with a feature selection algorithm, we determined that low temperature and air flow rate lead to greater feature separation on PCA scores plots. Of the 729 variables used to construct the plots, 61 were identified as significant. These species - including sugars such as d-Allose and melezitose, as well as tracers such as levoglucosan and guaiacol - significantly differentiated emissions from wood versus cow dung biomass, especially at lower temperatures. In particular, combustion of either fuel at 0.2 slpm and 500 °C, lead to 20 times the variability in levoglucosan peak area over more efficient furnace parameters. Chemical species evolved only from dung burning contained on average 0.595 nitrogen atoms versus 0.515 for wood, indicating that a higher nitrogen content of the base fuel may not necessarily translate into emission of unique nitrogen containing species, potentially causing the underestimation of dung burning impacts. Overall, TD-GC × GC-ToF-MS coupled to PCA reliably separated emissions from wood and dung biomass while simultaneously identifying significant chemical features, displaying the suitability of this combination of techniques towards characterizing complex BBE matrices in the future.
生物质燃烧是一种影响气候和健康的全球性排放源。生物质燃烧排放物（BBE）的影响与其复杂且多变的化学成分有关。例如，BBE 的氮含量会影响其吸收光的能力，从而影响地球的辐射收支。在燃烧过程中，温度、生物质类型或空气流速等因素都会改变 BBE 的组成，这使得准确描述变得具有挑战性。在此，首次将主成分分析（PCA）应用于在管式炉中进行的基于实验室的木材和牛粪生物质燃烧所收集的排放物。采用热解吸二维时间飞行气相色谱质谱联用（TD-GC×GC-ToF-MS）装置来分离和识别化学物质。通过将这些技术与特征选择算法相结合，我们确定低温和空气流速会导致 PCA 得分图上的特征分离度更大。在所构建的 729 个变量中，有 61 个被确定为显著变量。这些物质-包括 d-Allose 和 melezitose 等糖，以及左旋葡聚糖和愈创木酚等示踪剂-明显区分了木材与牛粪生物质的排放物，尤其是在较低温度下。特别是，在 0.2 slpm 和 500°C 下燃烧这两种燃料，导致左旋葡聚糖峰面积的可变性增加了 20 倍，而在更有效的炉内参数下则可忽略不计。仅由粪便燃烧产生的化学物质平均含有 0.595 个氮原子，而木材则含有 0.515 个氮原子，这表明基础燃料的较高氮含量不一定会转化为独特的含氮物质的排放，这可能导致低估粪便燃烧的影响。总体而言，TD-GC×GC-ToF-MS 与 PCA 相结合能够可靠地分离木材和粪便生物质的排放物，同时同时鉴定出重要的化学特征，显示出这种技术组合在未来用于描述复杂 BBE 矩阵的适用性。
