Active Monitoring of Residential Radon in Rome: A Pilot Study.

We present an overview of the potential of active monitoring techniques to investigate the many factors affecting the concentration of radon in houses. We conducted two experiments measuring radon concentration in 25 apartments in Rome and suburban areas for two weeks and in three apartments in the historic center for several months. The reference levels of 300 and 100 Bq/m3 are overcome in 17% and 60% of the cases, respectively, and these percentages rise to 20% and 76% for average overnight radon (more relevant for residents' exposure). Active detectors allowed us to identify seasonal radon fluctuations, dependent on indoor-to-outdoor temperature, and how radon travels from the ground to upper floors. High levels of radon are not limited to the lowest floors when the use of heating and ventilation produces massive convection of air. Lifestyle habits also reflect in the different values of gas concentration measured on different floors of the same building or in distinct rooms of the same apartment, which cannot be ascribed to the characteristics of the premises. However, the finding that high residential radon levels tend to concentrate in the historic center proves the influence of factors such as building age, construction materials, and geogenic radon.

Multi-level continuous monitoring of indoor radon activity.

We present the results of an experiment taking place inside the geophysical museum of Rocca di Papa (Rome, Italy), where the high radon levels detected might pose a risk to the health of workers and of the public audience. As a first step towards the mitigation of potential exposure risk, four active sensors were installed at different floors of the building, in order to continuously monitor not only radon exhalation from the soil but also its transport from the ground up to elevated floors. Collecting more than three years of data of radon concentration enables us to identify fluctuations over both short and seasonal scales and to elucidate the relation between radon variations and changes of internal temperature and relative humidity. The analysis of such dataset reveals how the healthiness of indoor environments in terms of radon concentration is controlled by a number of factors, including the environmental conditions and the use of heating and ventilation systems. Finally, the continuous radon monitoring at different levels of the building provides a unique chance to trace the vertical radon diffusion, allowing to make a first-order estimate of upward radon velocity.

Monitoring soil radon during the 2016-2017 central Italy sequence in light of seismicity.

The radioactive nature of radon makes it a powerful tracer for fluid movements in the crust, and a potentially effective marker to study processes connected with earthquakes preparatory phase. To explore the feasibility of using soil radon variations as earthquakes precursor, we analyse the radon concentration data recorded by two stations located close to the epicentre of the strongest mainshock (Mw 6.5 on October 30, 2016) of the seismic sequence which affected central Italy from August 2016. The two stations CTTR and NRCA operate in the framework of the permanent Italian Radon monitoring Network and recorded almost continuously since 2012 and 2016, respectively, the latter being installed just after the first mainshock of the sequence (Mw 6.0 on August 24, 2016). An increase of radon emanation is clearly visible about 2 weeks before the Mw 6.5 event on both the time series, more pronounced on NRCA, nearer to the epicentre, suggesting the possibility of a direct association with the earthquake occurrence. An independently developed detection algorithm aimed at highlighting the connections between radon emission variations and major earthquakes occurrence succeeds in forecasting the Mw 6.5 mainshock on NRCA time series. The resulting time advance of the alarm is consistent with that obtained using a Bayesian approach to compute the a posteriori probability of multiple change points on the radon time series of NRCA. Moreover, it is in agreement with the delay time which maximizes the correlation between radon and seismic anomalies. Applying the detection algorithm to CTTR time series returns alarms for both the Mw 6.0 event, with epicentre closer to this station, and the stronger Mw 6.5 event, but with a higher number of false detections. Finally, we found that a preliminary correction of the bias introduced by variations of meteorological parameters does not affect our main finding of an increase in radon concentration before the major mainshocks. Our study confirms that, although much work is still needed, a monitoring approach based on a permanent dense network is crucial for making radon time series analysis an effective complement to traditional seismological tools.