XRF Analysis of Air Filters Under Grazing Incidence Condition

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作者

Paola Cirelli¹ , Fabjola Bilo² , Laura Borgese²

1. Department of Information Engineering, University of Brescia, via Branze, 38, 25123, Brescia, Italy
2. SMART SOLUTIONS s.r.l, via Corfù, 106, 25124, Brescia, Italy

会议/活动

European Conference on X-ray Spectrometry, June 2022 (Bruges, Belgium)

海报摘要

There is an urgent need of air quality monitoring, to ensure that the concentration of pollutants in air does not exceed the limits established in the two EU Ambient Air Quality Directives. Particulate matter (PM) is usually collected on air filtering PTFE membranes to determine mass and chemical composition. Besides the analytical methods, X-ray Fluorescence analysis (XRF) has emerged as a valid technique for the determination of PM composition. Filters are measured in XRF under grazing incidence condition, after a preparation procedure called Smart Store®. This consists in sandwiching the sample between two adhesive polymeric foils, to avoid material loss and sample contaminations. Quantitative data can be obtained thanks to the external calibration approach, by means of calibration lines that are built comparing the known elemental concentration of samples and the detected fluorescence intensity. This procedure requires the use of reference samples, consisting in air filters with known mass deposition.

关键词

Air quality, XRF, Air filters, Heavy metals, PM

研究领域

Chemical Engineering, Environmental Engineering, Environmental Sciences

参考文献

1. L. Borgese, F. Bilo, A. Zacco, et al., Spectrochim. Acta - Part B At. Spectrosc. 167 (2020)
2. S. Yatkin, M. Gerboles, A. Borowiak, JRC Sci. Tech. Reports. (2011).
3. EU, Directive 2008/50/EC, Off. J. Eur. Union. L 152/1 (2008).
4. EU, Directive 2004/107/EC, Off. J. Eur. Union. L 023 (2004).

基金

暂无数据

补充材料

暂无数据

附加信息

利益冲突

No competing interests were disclosed.

数据可用性声明

The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.

知识共享许可协议

Copyright © 2022 Cirelli et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.