Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Oberschleißheim, Germany.
Analytical Chemistry, Institute of Chemistry, University of Rostock , 18059 Rostock 12, Germany.
Environ Sci Technol. 2016 Sep 20;50(18):10073-81. doi: 10.1021/acs.est.6b01571. Epub 2016 Sep 6.
Residential wood combustion emissions are one of the major global sources of particulate and gaseous organic pollutants. However, the detailed chemical compositions of these emissions are poorly characterized due to their highly complex molecular compositions, nonideal combustion conditions, and sample preparation steps. In this study, the particulate organic emissions from a masonry heater using three types of wood logs, namely, beech, birch, and spruce, were chemically characterized using thermal desorption in situ derivatization coupled to a GCxGC-ToF/MS system. Untargeted data analyses were performed using the comprehensive measurements. Univariate and multivariate chemometric tools, such as analysis of variance (ANOVA), principal component analysis (PCA), and ANOVA simultaneous component analysis (ASCA), were used to reduce the data to highly significant and wood type-specific features. This study reveals substances not previously considered in the literature as meaningful markers for differentiation among wood types.
居民木材燃烧排放是全球颗粒物和气态有机污染物的主要来源之一。然而,由于其高度复杂的分子组成、不理想的燃烧条件和样品制备步骤,这些排放物的详细化学成分特征描述很差。在这项研究中,使用热解原位衍生化结合 GCxGC-TOF/MS 系统,对使用三种类型的原木(山毛榉、桦木和云杉)的砖石加热器产生的颗粒有机排放物进行了化学特征描述。使用全面的测量方法进行非靶向数据分析。使用单变量和多变量化学计量学工具,如方差分析(ANOVA)、主成分分析(PCA)和 ANOVA 同时成分分析(ASCA),将数据简化为高度显著且与木材类型特异性相关的特征。这项研究揭示了以前在文献中没有被认为是区分木材类型的有意义标志物的物质。