Analysis of radon time series recorded during the 2016-2017 central Italy seismic sequence.

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 earthquake precursor, we analyse the radon concentration data recorded by two stations located close to the epicenter of the strongest mainshock (Mw6.5 on October 30th, 2016) of the seismic sequence which affected central Italy from August, 2016. The stations (CTTR and NRCA) operate in the framework of the permanent Italian Radon mOnitoring Network (IRON), and recorded almost continuously since 2012 and 2016, respectively, the latter being installed just after the first mainshock of the sequence (Mw6 on August 24th, 2016). An increase of radon emanation is clearly visible about 2 weeks before the Mw6.5 event on both the time series, more pronounced on NRCA, nearer to the epicenter, 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 Mw6.5 mainshock on NRCA time series, while on CTTR data it allows to forecast the Mw6 event, with epicenter closer to this station. The resulting time advance with respect to earthquake occurrence is consistent with that obtained using a Bayesian approach to compute the a posteriori probability of multiple change points. Finally, a preliminary correction of the bias introduced by variations of meteorological parameters (radon anomalies of non-tectonic origin look similar to tectonic ones) does not affect our main finding of an increase in radon concentration before the seismic moment release during the earthquake sequence considered. Although much work is still needed, our study confirms that a monitoring approach based on a permanent dense network is crucial for making radon time series analysis a complement to traditional seismological tools.