XRF Analysis of Air Filters Under Grazing Incidence Condition

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Authors

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

Conference / event

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

Poster summary

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.

Keywords

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

Research areas

Chemical Engineering, Environmental Engineering, Environmental Sciences

References

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).

Funding

No data provided

Supplemental files

No data provided

Additional information

Competing interests

No competing interests were disclosed.

Data availability statement

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

Creative Commons license

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.