Department of Chemistry, Faculty of Science, University of Duhok, Zakho Street 38, 42001 Duhok, Kurdistan Region, Iraq; Institute of Chemistry, University of Rostock, Dr.-Lorenz-Weg 1, D-18051 Rostock, Germany; Joint Mass Spectrometry Centre - Cooperation Group "Comprehensive Molecular Analytics", Helmholtz Zentrum München, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany.
Joint Mass Spectrometry Centre - Cooperation Group "Comprehensive Molecular Analytics", Helmholtz Zentrum München, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany.
Chemosphere. 2014 May;103:263-73. doi: 10.1016/j.chemosphere.2013.12.015. Epub 2013 Dec 31.
Daily PM10 samples were collected during a one-month sampling campaign from February 13 to March 12, 2008 at eight different sampling sites in Augsburg, Southern Germany. Source apportionment was performed to identify the main sources and related contributions by analysis of organic and inorganic tracers. Nine factors were separated comprising: solid fuel combustion, traffic-related emissions, secondary inorganics, and mixed sources. Spatiotemporal variation of the source contributions was evaluated using the Pearson correlation coefficient (r) and coefficient of divergence (COD). All factors (except hopanes and mixed sources) showed moderate to high (0.6
每天 PM10 样本在 2008 年 2 月 13 日至 3 月 12 日一个月的采样活动中从德国南部奥格斯堡的八个不同采样点采集。通过分析有机和无机示踪剂进行来源分配,以确定主要来源和相关贡献。分离出 9 个因子,包括:固体燃料燃烧、交通相关排放、二次无机物和混合源。使用 Pearson 相关系数(r)和发散系数(COD)评估源贡献的时空变化。所有因子(除藿烷和混合源外)在八个站点之间均表现出中等至高(0.6