Noblet Camille, Lestremau François, Collet Serge, Chatellier Claudine, Beaumont Jérôme, Besombes Jean-Luc, Albinet Alexandre
Institut National de l'Environnement industriel et des RISques (Ineris), 60550, Verneuil en Halatte, France; Université Savoie Mont Blanc, CNRS, EDYTEM, Chambéry, 73000, France.
Institut National de l'Environnement industriel et des RISques (Ineris), 60550, Verneuil en Halatte, France; Hydrosciences Montpellier, Univ Montpellier, IMT Mines Alès, IRD, CNRS, 30100, Alès, France.
Chemosphere. 2024 Mar;352:141242. doi: 10.1016/j.chemosphere.2024.141242. Epub 2024 Jan 25.
Biomass burning is a significant source of particulate matter (PM) in ambient air and its accurate source apportionment is a major concern for air quality. The discrimination between residential wood heating (RWH) and garden green waste burning (GWB) particulate matter (PM) is rarely achieved. The objective of this work was to evaluate the potential of non-targeted screening (NTS) analyses using HRMS (high resolution mass spectrometry) data to reveal discriminating potential molecular markers of both sources. Two residential wood combustion appliances (wood log stove and fireplace) were tested under different output conditions and wood moisture content. GWB experiments were carried out using two burning materials (fallen leaves and hedge trimming). PM samples were characterized using NTS approaches with both LC- and GC-HRMS (liquid and gas chromatography-HRMS). The analytical procedures were optimized to detect as many species as possible. Chemical fingerprints obtained were compared combining several multivariate statistical analyses (PCA, HCA and PLS-DA). Results showed a strong impact of the fuel nature and the combustion quality on the chemical fingerprints. 31 and 4 possible markers were discovered as characteristic of GWB and RWH, respectively. Complementary work was attempted to identify potential molecular formulas of the different potential marker candidates. The combination of HRMS NTS chemical characterization with multivariate statistical analyses shows promise for uncovering organic aerosol fingerprinting and discovering potential PM source markers.
生物质燃烧是环境空气中颗粒物（PM）的一个重要来源，其准确的源解析是空气质量的一个主要关注点。很少能实现对居民用木柴取暖（RWH）和花园绿植废弃物燃烧（GWB）产生的颗粒物（PM）进行区分。这项工作的目的是评估使用高分辨率质谱（HRMS）数据进行非靶向筛查（NTS）分析以揭示这两种来源的潜在鉴别分子标志物的潜力。在不同的输出条件和木材含水量下对两台居民用木质燃烧器具（木柴炉灶和壁炉）进行了测试。使用两种燃烧材料（落叶和树篱修剪废弃物）进行了花园绿植废弃物燃烧实验。使用液相色谱 - 高分辨率质谱（LC - HRMS）和气相色谱 - 高分辨率质谱（GC - HRMS）的非靶向筛查方法对PM样本进行了表征。对分析程序进行了优化以检测尽可能多的物种。将获得的化学指纹图谱结合几种多元统计分析（主成分分析、层次聚类分析和偏最小二乘判别分析）进行比较。结果表明燃料性质和燃烧质量对化学指纹图谱有很大影响。分别发现了31种和4种可能的标志物作为花园绿植废弃物燃烧和居民用木柴取暖的特征。尝试开展补充工作以确定不同潜在标志物候选物的潜在分子式。高分辨率质谱非靶向筛查化学表征与多元统计分析的结合显示出在揭示有机气溶胶指纹图谱和发现潜在的颗粒物源标志物方面具有前景。
