Abstract:
In this work, a comprehensive characterisation and source apportionment of size-segregated aerosol collected using a multistage cascade impactor was performed. The samples were collected during wintertime in Milan (Italy), which is located in the Po Valley, one of the main pollution hot-spot areas in Europe. For every sampling, size-segregated mass concentration, elemental and ionic composition, and levoglucosan concentration were determined. Size-segregated data were inverted using the program MICRON to identify and quantify modal contributions of all the measured components. The detailed chemical characterisation allowed the application of a three-way (3-D) receptor model (implemented using Multilinear Engine) for size-segregated source apportionment and chemical profiles identification. It is noteworthy that - as far as we know - this is the first time that three-way source apportionment is attempted using data of aerosol collected by traditional cascade impactors. Seven factors were identified: wood burning, industry, resuspended dust, regional aerosol, construction works, traffic 1, and traffic 2. Further insights into size-segregated factor profiles suggested that the traffic 1 factor can be associated to diesel vehicles and traffic 2 to gasoline vehicles. The regional aerosol factor resulted to be the main contributor (nearly 50%) to the droplet mode (accumulation sub-mode with modal diameter in the range 0.5-1 μm), whereas the overall contribution from the two factors related to traffic was the most important one in the other size modes (34-41%). The results showed that applying a 3-D receptor model to size-segregated samples allows identifying factors of local and regional origin while receptor modelling on integrated PM fractions usually singles out factors characterised by primary (e.g. industry, traffic, soil dust) and secondary (e.g. ammonium sulphate and nitrate) origin. Furthermore, the results suggested that the information on size-segregated chemical composition in different size classes was exploited by the model to relate primary emissions to rapidly-formed secondary compounds.
摘要:
在这项工作中,对使用多级级联冲击器收集的大小分离的气溶胶进行了全面的表征和来源分配。样本是在米兰(意大利)的冬季收集的,位于宝谷,欧洲主要的污染热点地区之一。对于每一次采样,大小分离的质量浓度,元素和离子组成,并测定了左旋葡聚糖的浓度。使用程序MICRON对尺寸分离的数据进行倒置,以识别和量化所有测量组件的模态贡献。详细的化学表征允许应用三向(3-D)受体模型(使用多线性引擎实现)进行大小隔离的来源分配和化学概况鉴定。值得注意的是,据我们所知,这是首次尝试使用传统级联冲击器收集的气溶胶数据进行三向源分配。确定了七个因素:木材燃烧,工业,重新悬浮的灰尘,区域性气溶胶,建筑工程,交通1和交通2。对大小隔离因子分布的进一步见解表明,交通1因子可以与柴油车辆相关,交通2与汽油车辆相关。区域气溶胶因子是液滴模式(模态直径在0.5-1μm范围内的累积子模式)的主要贡献者(近50%),而与交通相关的两个因素的总体贡献在其他尺寸模式中最重要(34-41%)。结果表明,将3-D受体模型应用于大小分离的样品可以识别局部和区域起源的因素,而对综合PM部分的受体建模通常会挑选出以主要为特征的因素(例如工业,交通,土壤粉尘)和次生(如硫酸铵和硝酸盐)来源。此外,结果表明,该模型利用了不同大小类别中大小分离的化学成分的信息,将初级排放与快速形成的次级化合物联系起来。