Institute of Environmental Assessment and Water Research (IDÆA) Consejo Superior de Investigaciones Científicas (CSIC), C/ Jordi Girona 18-26, 08034, Barcelona, Spain.
Department of Astronomy and Meteorology, Faculty of Physics, University of Barcelona, C/ Martí i Franquès 1, 08028, Barcelona, Spain.
Environ Sci Pollut Res Int. 2019 Nov;26(31):32114-32127. doi: 10.1007/s11356-019-06199-3. Epub 2019 Sep 7.
Source apportionment of atmospheric PM1 is important for air quality control, especially in urban areas where high mass concentrations are often observed. Chemical analysis of molecular inorganic and organic tracer compounds and subsequently data analysis with receptor models give insight on the origin of the PM sources. In the present study, four source apportionment approaches were compared with an extended database containing inorganic and organic compounds that were measured during an intensive sampling campaign at urban traffic and urban background sites in Barcelona. Source apportionment of the combined database, containing both inorganic and organic compounds, was compared with more conventional approaches using inorganic and organic databases separately. Traffic emission sources were identified in all models for the two sites. The combined inorganic and organic databases provided higher discrimination capacity of emission sources. It identified aerosols generated by regional recirculation of biomass burning, secondary biogenic organic aerosols, harbor emissions, and specific industrial emissions. In this respect, this approach identified a relevant industrial source situated at NE Barcelona in which a waste incinerator plant, a combined-cycle power plant, and an industrial glass complex are located. Models using both inorganic and organic molecular tracer compounds improve the source apportionment of urban PM.
大气 PM1 的来源解析对于空气质量控制非常重要,特别是在城市地区,那里经常观察到高浓度的 PM1。对分子无机和有机示踪化合物进行化学分析,随后使用受体模型进行数据分析,可以深入了解 PM 来源的成因。在本研究中,比较了四种源解析方法,这些方法使用了在巴塞罗那城市交通和城市背景站点进行的强化采样活动中测量的无机和有机化合物的扩展数据库。将包含无机和有机化合物的综合数据库的源解析与更传统的仅使用无机和有机数据库的方法进行了比较。对于这两个站点的所有模型,都识别出了交通排放源。综合无机和有机数据库提高了排放源的区分能力。它识别出了由生物质燃烧的区域再循环、次生生物有机气溶胶、港口排放和特定工业排放产生的气溶胶。在这方面,该方法识别出了位于巴塞罗那东北部的一个相关工业源,其中有一个垃圾焚烧厂、一个联合循环发电厂和一个工业玻璃综合体。使用无机和有机分子示踪化合物的模型可改善城市 PM 的源解析。