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The Association between Intermodal (PM1-2.5) and PM1, PM2.5, Coarse Fraction and Meteorological Parameters in Various Environments in Central Europe

机译:中欧各种环境中的联运模式(PM1-2.5)与PM1,PM2.5,粗分数和气象参数之间的关联

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Fine and coarse fractions of atmospheric aerosol overlap in the particle size range of about 1–2.5 μm (aerodynamic diameter). Sources of both fractions contribute to PM1-2.5 to different extents due to meteorological and spatial conditions. Therefore, there is ongoing discussion as to whether PM2.5 or PM1 should be included for monitoring as a fine particulate pollutant by the national ambient air quality standard (NAAQS). The aim of the presented study is to examine the association between the intermodal and PM1, PM2.5, coarse fraction, and meteorological parameters in various environments. Outdoor 24-h mass concentrations of size-resolved PM and meteorological conditions were measured at 12 sites within 42 campaigns between 11/2005 and 3/2015. The data set was divided into 10 environments reflecting season, locality, total measured PM, and placement of the impactor. We used two types of statistic methods: nonparametric correlation analysis and multiple linear regression (MLR). Median PM1-2.5 in PM10 or TSP percentages were 7% and 6% in summer and 7% and 9% in winter. On the other hand, PM1-2.5 accounted for a higher mass portion of PM2.5 during summer. Stronger positive correlation and relationship were identified between PM1-2.5 and the coarse fraction than between PM1-2.5 and PM1 in all environments. MLR confirmed the dependence of PM1-2.5 on PM1 in only 3 environments. This study found that PM1-2.5 in Central Europe represents mostly the “tail” of the coarse mode and probably has the same sources. Therefore, PM1 should be considered by the NAAQS as a fine particulate pollutant in Central Europe.
机译:大气气溶胶的细颗粒和粗颗粒在大约1–2.5μm(空气动力学直径)的粒径范围内重叠。由于气象和空间条件,这两个部分的来源对PM1-2.5的贡献程度不同。因此,目前正在讨论是否应将PM2.5或PM1纳入国家环境空气质量标准(NAAQS)的监测中,作为细颗粒污染物。本研究的目的是研究各种环境中的联运与PM1,PM2.5,粗粒分数和气象参数之间的关联。在11/2005年至3/2015年之间的42次运动中的12个地点测量了室外24小时按尺寸分辨的PM和气象条件的质量浓度。数据集分为10个环境,分别反映季节,地点,总测得的PM和冲击器的位置。我们使用了两种类型的统计方法:非参数相关分析和多元线性回归(MLR)。夏季PM10或TSP中PM1-2.5的中位数分别为7%和6%,冬季为7%和9%。另一方面,PM1-2.5在夏季占PM2.5的较高质量部分。在所有环境中,PM1-2.5与粗颗粒之间的正相关性和关联性均强于PM1-2.5与PM1。 MLR仅在3种环境中证实了PM1-2.5对PM1的依赖性。这项研究发现,中欧的PM1-2.5主要代表粗模式的“尾部”,并且可能具有相同的来源。因此,NAAQS应该将PM1视为中欧的细颗粒污染物。

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