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Improving the measurement of radon levels to protect people from exposure to harmful radiation

European Directive 2013/59/Euratom requires member states of the European Union to mitigate the exposure to radon (Rn) and its progeny to safeguard citizens. Radon is a radioactive gas naturally emitted from the ground and, over time, can become concentrated inside buildings, especially without adequate ventilation. While improving air exchange and circulation can reduce exposure, ventilation systems can be energy intensive and require consistent maintenance. Smart sensor networks would allow ventilation systems to detect and react to fluctuations in radon levels efficiently and in real time, but there is a lack of robust metrology and traceable calibrations for these types of sensors.

Metrology Partnership project Radon metrology: Sensor networks for large buildings and future cities (23IND07, RadonNET) is working to develop new radon detectors, expanding and merging existing technology to provide regular, reliable radon measurements. It will develop cost-effective sensors with reduced response time, increased sensitivity and lower uncertainty, as well as procedures for in-situ calibration. The project will also develop networks for these sensors which can span large buildings and utilise artificial intelligence.  

New radon detectors developed

Radon can be detected by semiconductor devices, ionisation chambers or scintillation‑based measurement. Before this project, detectors were often costly, based on ageing technologies and not designed to be networked for active radon mitigation. Semiconductor detectors tend to have high sensitivity and fast response times but may be more sensitive to environmental conditions and require careful calibration. Project partners, NUVIA and CMI, have produced the first semiconductor-based radon detector prototype with the potential to become a commercial low-cost detector.  

Work has also progressed on ionisation chambers, which measure the charged particles caused by the radiation ionising gas, and tend to be stable and accurate. Project partner PTB has developed an ionisation chamber with an estimated hardware cost of around EUR 40, significantly lower than other options.  This device is easy to install in any network and is suitable for use by technicians in the laboratory and in the field. Usually commercial devices do not allow access to raw data, but this one has the potential to be an open-source instrument. This gives access to the raw data and the ability to apply calibration and correction factors, and use any connection method.

Project partner USIEG demonstrated a high-sensitivity ionisation chamber suitable for reference-grade or transfer-standard applications.

These innovative, sensitive and reliable operational prototypes are realistic options for cost-effective radon detection and the monitoring of large buildings.  

Test bed established

RadonNET is also beginning to demonstrate what a future quality-assured radon sensor network may look like in practice. The first stage of the test bed at the University of Helsinki has been established, providing the basis for work on data acquisition, calibration transfer, anomaly detection, AI-based data analysis, and integration with other indoor air quality monitoring strategies. This will mean that radon metrology, intelligent calibration, connected building technologies and energy-efficient air management can be combined into a single framework for safer and smarter buildings.

New standard for measuring radon in water

Another significant achievement of RadonNET was the establishment of a new radon‑in‑water standard at CEA. This work was initially undertaken as an experimental study to validate scintillation-based measurement, a detection method where incoming radiation from radon decay produces flashes of light which can be converted into an electrical signal. However, it ultimately led to the design of a new measurement setup capable of producing primary radon-in-water standards, validated through multiple cross-check measurements at CEA with the help of SUBG. This development constitutes a significant metrological achievement and opens new opportunities for traceable radon-in-water measurements.

These improvements in radon detection will promote public health, and the adherence to standards will ensure consistency, comparability and reliability of radon measurements. The longer-term economic, social, and environmental impacts will contribute to a sustainable and resilient future for European cities and communities.

Project co-ordinator, Benoit Sabot, from CEA  said:

“The first technical building blocks of the project are very promising, and in some areas have even exceeded our expectations. The new open-source solutions will make it much easier for us to interpret the results, apply calibration procedures, and develop remote calibration capabilities. In addition, the project has enabled the deployment of two test beds: one in the laboratory at CEA, comprising around thirty sensor nodes, and another under real-world conditions at the University of Helsinki, also comprising around thirty nodes.

The data collected over the coming months will allow us to further develop machine-learning and artificial-intelligence approaches for radon measurement, as well as their integration into smart homes. Overall, after a year and a half of the project, the results are already opening up new avenues for future research projects.”

This Metrology Partnership project has received funding from the European Partnership on Metrology, co-financed by the European Union Horizon Europe Research and Innovation Programme and from the Participating States.

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