Aerosol and Air Quality Research Laboratory, Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.
Sci Total Environ. 2011 Jun 1;409(13):2642-51. doi: 10.1016/j.scitotenv.2011.03.032. Epub 2011 Apr 14.
Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach.
儿童时期接触交通相关污染与哮喘恶化和哮喘发病率有关。辛辛那提儿童过敏和空气污染研究（CCAAPS）的目的是确定是否接触柴油机排气颗粒与过敏性和呼吸道疾病的发展有关。通过应用正矩阵因子化（PMF）和 UNMIX 受体模型对两个 PM₂.₅数据集进行了详细的受体模型分析：一个数据集由两个碳分量组成，另一个由八个温度分辨的碳分量组成。根据分析中确定的源谱，估计了与交通相关的空气污染标志物：归因于交通的元素碳（ECAT）和归因于柴油车辆排放的元素碳（ECAD）。UNMIX 应用于两个数据集生成了四个源因子：与燃烧有关的硫酸盐、交通、金属加工和土壤/地壳。PMF 应用从分析两个碳分量中生成了六个源因子，从温度分辨的八个碳分量中生成了七个因子。源因子（括号内为质量浓度源贡献估计值）为：燃烧硫酸盐（46.8%）、植被燃烧（15.8%）、二次硫酸盐（12.9%）、柴油车辆排放（10.9%）、金属加工（7.5%）、汽油车辆排放（5.6%）和土壤/地壳（0.7%）。使用八个温度分辨的有机和元素碳分量分离了柴油和汽油车辆排放源。PMF 对两个数据集的应用也区分了富含硫酸盐的源和植被燃烧源，这两个源在 UNMIX 建模中结合在一个单一因子中。在不同位置计算的 ECAT 和 ECAD 值表明，交通源的影响取决于交通量、气象参数以及车辆操作模式等因素，而不仅仅是站点与高速公路的距离。然而，ECAT 和 ECAD 的差异小于一个标准差。因此，在决定采用 8 个或 2 个碳方法的益处时，应考虑成本效益。
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