4.7 Article

Resonant Synchrotron X-ray Diffraction determines markers for iron-rich atmospheric particulate matter in urban region

期刊

CHEMOSPHERE
卷 212, 期 -, 页码 418-428

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2018.08.111

关键词

Particulate matter (PM); Resonant Synchrotron X-ray Diffraction (RSr-XRD); Chemical composition; Crystalline phases; Source apportionment; Source markers

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  1. CAPES
  2. FAPES

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Particulate matter driven health problems are strongly associated with its chemical composition. Despite the benefits of using source apportionment models for air quality management, limitations such as collinearity effects, restrict their application or compromise the accurate separation of sources, particularly for particulate matter with similar chemical profiles. Receptors models also depend on the operator expertise to appropriately classified sources, a subjective process that can lead to biased results. For highly correlated sources, the identification of specific markers is still the best way to achieve proper source apportionment. In this study, Resonant Synchrotron X-ray Diffraction has been applied to the analysis of atmospheric particles to determine markers for industrial and vehicular sources in the Region of Greater Vitoria, Brazil. Total suspended particulate matter, PM10, and PM2.5 samples were analyzed by Resonant Synchrotron X-ray Diffraction showing high levels of iron-based crystalline phases. In comparison to the use of chemical elemental species, the identification of the crystalline phases provided an enhanced approach to classify specific iron-based source markers. For this study, alpha-Fe2O3 was identified with iron-based sources such as iron ore, pelletizing, and sintering; metallic Fe was inferred with blast furnaces and steelmaking; FeS2 was correlated with coal deposits; and K2Fe2O4 was associated to sintering emissions. Elemental carbon with different X-ray diffraction patterns enabled the differentiation of industrial and vehicular sources. The attribution of crystal rather than elemental composition in the identification of sources improves the accuracy of source apportionment studies. (C) 2018 Elsevier Ltd. All rights reserved.

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