Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas
Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas
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DOI：
10.1016/j.envpol.2020.115199
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发表时间：
2020-11-01
影响因子：
8.9
通讯作者：
Eleftheriadis, K.
中科院分区：
文献类型：
--
作者：
Almeida, S. M.;Manousakas, M.;Eleftheriadis, K.
这项工作提出了一个PM2.5源解析研究的结果，在城市背景网站从16个欧洲和亚洲国家。对于一些东欧和中亚城市，这是第一次对污染源对环境颗粒物（PM）的贡献进行定量信息。对2200多个过滤器进行了采样，并通过X射线荧光（XRF）、粒子诱导X射线发射（PIXE）和电感耦合等离子体质谱（ICPMS）进行了分析，以测量细颗粒中化学元素的浓度。还分析了样品的黑碳、元素碳、有机碳和水溶性离子的含量。正矩阵因子受体模型（EPA PMF 5.0）被用来表征相似性和异质性的PM2.5来源和各自的贡献，在收集的样本数量超过75个城市。最后，在16个参与城市中的11个进行了源解析。PM2.5的9个主要来源是：生物质燃烧、二次硫酸盐、交通、燃油燃烧、工业、燃煤、土壤、盐和“其他来源”。从来源贡献的平均值来看，考虑到11个城市，PM2.5的16%归因于生物质燃烧，15%归因于二次硫酸盐，13%归因于交通，12%归因于土壤，8.0%归因于燃油燃烧，5.5%归因于煤炭燃烧，1.9%归因于盐，0.8%归因于工业排放，5.1%归因于“其他来源”，23%归因于不明质量。确定了每个PM2.5源的特征季节模式。由于家庭供暖的影响，冬季所有城市的生物质燃烧，克拉科夫/POL的煤炭燃烧，贝尔格莱德/SRB和巴尼亚卢卡/波黑的石油燃烧增加，而在大多数城市，夏季由于光化学活性的增强，二次硫酸盐达到了较高的水平。在高污染日，细颗粒物的最大来源是生物质燃烧，交通和二次硫酸盐。(C)2020年，任作家。由爱思唯尔有限公司出版。这是一篇在CC BY-NC-ND许可证下的开放获取文章（http：//creativecommons.org/licenses/by-nc-nd/4.0/）。
This work presents the results of a PM2.5 source apportionment study conducted in urban background sites from 16 European and Asian countries. For some Eastern Europe and Central Asia cities this was the first time that quantitative information on pollution source contributions to ambient particulate matter (PM) has been performed. More than 2200 filters were sampled and analyzed by X-Ray Fluorescence (XRF), Particle-Induced X-Ray Emission (PIXE), and Inductively Coupled Plasma Mass Spectrometry (ICPMS) to measure the concentrations of chemical elements in fine particles. Samples were also analyzed for the contents of black carbon, elemental carbon, organic carbon, and water-soluble ions. The Positive Matrix Factorization receptor model (EPA PMF 5.0) was used to characterize similarities and heterogeneities in PM2.5 sources and respective contributions in the cities that the number of collected samples exceeded 75. At the end source apportionment was performed in 11 out of the 16 participating cities. Nine major sources were identified to have contributed to PM2.5: biomass burning, secondary sulfates, traffic, fuel oil combustion, industry, coal combustion, soil, salt and "other sources". From the averages of sources contributions, considering 11 cities 16% of PM2.5 was attributed to biomass burning, 15% to secondary sulfates, 13% to traffic, 12% to soil, 8.0% to fuel oil combustion, 5.5% to coal combustion, 1.9% to salt, 0.8% to industry emissions, 5.1% to "other sources" and 23% to unaccounted mass. Characteristic seasonal patterns were identified for each PM2.5 source. Biomass burning in all cities, coal combustion in Krakow/POL, and oil combustion in Belgrade/SRB and Banja Luka/BIH increased in Winter due to the impact of domestic heating, whereas in most cities secondary sulfates reached higher levels in Summer as a consequence of the enhanced photochemical activity. During high pollution days the largest sources of fine particles were biomass burning, traffic and secondary sulfates. (C) 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).