Issue |
EPJ Web Conf.
Volume 288, 2023
ANIMMA 2023 – Advancements in Nuclear Instrumentation Measurement Methods and their Applications
|
|
---|---|---|
Article Number | 06002 | |
Number of page(s) | 4 | |
Section | Nuclear Safeguards, Homeland Security and CBRN | |
DOI | https://doi.org/10.1051/epjconf/202328806002 | |
Published online | 21 November 2023 |
https://doi.org/10.1051/epjconf/202328806002
A portable aerosol monitor with a novel linear deconvolution algorithm for fast and accurate detection of alpha emitters
1 ELSE NUCLEAR Srl, Italy
2 ENEA C. R. Casaccia, Italy
* luca.ferrante@elsenuclear.com
Published online: 21 November 2023
Radiochemistry laboratories and nuclear power plants are required to install aerosol monitors for real-time detection of alpha-particle emitters in air. However, common radioactive aerosol monitors are unsuited for rapid emergency response, since they are neither portable nor easily deployable. Moreover, their spectrometric capabilities are usually limited, showing particularly poor performance of radioisotope identification, which makes it difficult to correctly assess the alpha-emitter concentration in air. We developed a rugged and compact radioactive aerosol monitor, fully battery powered, which can be quickly deployed in field, as well as used as a fixed station for routine monitoring. The monitor is equipped with a silicon detector, and the acquired alpha-particle spectra are analyzed employing a patented linear deconvolution algorithm. A prototype of this device was tested to evaluate its performance of radioisotope identification by using artificial alpha-emitters. Initial encouraging tests provide evidence for alpha-emitters identification with multi-line mixed-isotope alpha sources, and in energy-degraded low-countingstatistics conditions.
Key words: Alpha-particle spectroscopy / Radioactive aerosol monitor / Linear deconvolution algorithm
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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