Ilacqua Vito, Hänninen Otto, Saarela Kristina, Katsouyanni Klea, Künzli Nino, Jantunen Matti
KTL - National Public Health Institute, Kuopio, Finland.
Sci Total Environ. 2007 Oct 1;384(1-3):77-92. doi: 10.1016/j.scitotenv.2007.06.020. Epub 2007 Jul 12.
Apportionment of urban particulate matter (PM) to sources is central for air quality management and efficient reduction of the substantial public health risks associated with fine particles (PM(2.5)). Traffic is an important source combustion particles, but also a significant source of resuspended particles that chemically resemble Earth's crust and that are not affected by development of cleaner motor technologies. A substantial fraction of urban ambient PM originates from long-range transport outside the immediate urban environment including secondary particles formed from gaseous emissions of mainly sulphur, nitrogen oxides and ammonia. Most source apportionment studies are based on small number of fixed monitoring sites and capture well population exposures to regional and long-range transported particles. However, concentrations from local sources are very unevenly distributed and the results from such studies are therefore poorly representative of the actual exposures. The current study uses PM(2.5) data observed at population based random sampled residential locations in Athens, Basle and Helsinki with 17 elemental constituents, selected VOCs (xylenes, trimethylbenzenes, nonane and benzene) and light absorbance (black smoke). The major sources identified across the three cities included crustal, salt, long-range transported inorganic and traffic sources. Traffic was associated separately with source categories with crustal (especially Athens and Helsinki) and long-range transported chemical composition (all cities). Remarkably high fractions of the variability of elemental (R(2)>0.6 except for Ca in Basle 0.38) and chemical concentrations (R(2)>0.5 except benzene in Basle 0.22 and nonane in Athens 0.39) are explained by the source factors of an SEM model. The RAINS model that is currently used as the main tool in developing European air quality management policies seems to capture the local urban fraction (the city delta term) quite well, but underestimates crustal particle levels in the three cities of the current study. Utilizing structural equation modelling parallel with traditional principal component analysis (PCA) provides an objective method to determine the number of factors to be retained in a model and allows for formal hypotheses testing.
将城市颗粒物（PM）的来源进行分配对于空气质量的管理以及有效降低与细颗粒物（PM2.5）相关的重大公共健康风险至关重要。交通是燃烧颗粒物的一个重要来源，但也是再悬浮颗粒物的一个重要来源，这些再悬浮颗粒物在化学组成上类似于地壳，并且不受更清洁汽车技术发展的影响。城市环境空气中相当一部分PM源自城市直接环境以外的长距离传输，包括主要由硫、氮氧化物和氨的气态排放形成的二次颗粒物。大多数源分配研究基于少数固定监测点，能较好地反映人群对区域和长距离传输颗粒物的暴露情况。然而，来自本地源的浓度分布极不均衡，因此这类研究的结果很难代表实际暴露情况。本研究使用了在雅典、巴塞尔和赫尔辛基基于人群随机抽样的居住地点观测到的PM2.5数据，这些数据包含17种元素成分、选定的挥发性有机化合物（二甲苯、三甲苯、壬烷和苯）以及光吸收（黑烟）。在这三个城市中识别出的主要来源包括地壳源、海盐源、长距离传输的无机源和交通源。交通分别与地壳源类别（特别是在雅典和赫尔辛基）以及长距离传输的化学成分类别（所有城市）相关。结构方程模型（SEM）的源因素解释了元素浓度（除巴塞尔的钙为0.38外，R2>0.6）和化学浓度（除巴塞尔的苯为0.22和雅典的壬烷为0.39外，R2>0.5）相当高比例的变异性。目前作为制定欧洲空气质量管理制度主要工具的RAINS模型似乎能很好地捕捉当地城市部分（城市增量项），但低估了本研究中三个城市的地壳颗粒物水平。将结构方程建模与传统主成分分析（PCA）并行使用，提供了一种客观方法来确定模型中应保留的因子数量，并允许进行正式的假设检验。
