Department of Physics, Università degli Studi di Milano and INFN Milan, Italy.
Department of Physics, Università degli Studi di Milano and INFN Milan, Italy.
Environ Pollut. 2018 Feb;233:679-689. doi: 10.1016/j.envpol.2017.10.059. Epub 2017 Nov 6.
In this paper, results from receptor modelling performed on a well-characterised PM dataset were combined to chemical light extinction data (b) with the aim of assessing the impact of different PM components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM components and major sources. PM samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (b) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively.
在本文中，我们将对经过充分表征的 PM 数据集进行受体建模的结果与化学消光数据（b）相结合，旨在评估不同 PM 成分和来源对欧洲污染城区光衰减和能见度的影响。值得注意的是，在当前的技术水平下，像我们在这里所展示的那样，估计不同排放源对光衰减的影响的论文仍然很少，尽管这是许多污染地区的主要环境挑战之一。遵循著名的 IMPROVE 算法的概念，这里应用了一种针对特定地点的方法（最近由我们小组开发）来评估 PM 成分和主要来源引起的化学消光。在意大利米兰的城区白天和夜间分别采集的 PM 样品进行了元素、主要离子、元素和有机碳以及左旋葡聚糖的化学特征分析。估计了化学消光，结果表明，在所研究的城市地区，它受到硝酸铵和有机物的严重影响。受体建模（即正矩阵因子分解，EPA-PMF 5.0）有效地获得了源分配；发现最可靠的解决方案是使用 7 个因子，这些因子被暂时分配给硝酸盐、硫酸盐、木柴燃烧、交通、工业、细粉尘和富含 Pb 的源。根据解析源分配气溶胶光衰减（b）表明，考虑所有样本，硝酸盐的贡献最大（平均为 41.6%），其次是硫酸盐、交通和木柴燃烧，分别占 18.3%、17.8%和 12.4%。
