Two years of radon-222 observations collected at L’Aquila (Italy) in the atmospheric surface layer during 2004–2006 were analyzed in correlation with meteorological data and other atmospheric tracers. A box model was developed to better understand the mechanisms of diurnal and seasonal variability of the tracer and to indirectly assess the magnitude of the monthly averaged radon soil flux in the L’Aquila measurement site. The model was successfully validated with measurements, with a 0.8 average correlation coefficient between hourly values for the whole period of radon observations. Measurements taken during March 2009 were analyzed to find possible signs of perturbation due to the ongoing seismic activity that would have reached its peak on the 6 April 2009 destructive earthquake. Contrary to the professed (and unpublished) dramatic increases of radon activity unofficially announced to the inhabitants at that time, the study presented here shows that no radon activity increase took place in L’Aquila with respect to a previous ‘seismically unperturbed’ year (same month with similar meteorological conditions), but that an average 30 % decrease was experienced. This conclusion is reached from a direct comparison of observed data and also as a result of the previously validated radon box model constrained by actual meteorological data, from which an indirect estimate of a 17 % reduction of the radon soil flux is obtained.
Atmospheric tracers Box model In situ measurements Radon variability Meteorology
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Allen DJ, Rood RB, Thompson AM, Hudson RD (1996) Three dimensional radon-222 calculations using assimilated meteorological data and a convective mixing algorithm. J Geophys Res 101:6871–6881CrossRefGoogle Scholar
Cicerone RD, Ebel JE, Britton J (2009) A systematic compilation of earthquake precursors. Tectonophys 476:371–396CrossRefGoogle Scholar
Considine DB, Bergmann DJ, Liu H (2005) Sensitivity of global modeling initiative chemistry and transport model simulations of radon-222 and lead-210 to input meteorological data. Atmos Chem Phys 5:3389–3406CrossRefGoogle Scholar
Dentener F, Feichter J, Jeuken A (1999) Simulation of the transport of Rn-222 using on-line and off-line global models at different horizontal resolutions: a detailed comparison with measurements. Tellus 51B:573–602CrossRefGoogle Scholar
Di Carlo P, Pitari G, Mancini E, Gentile S, Pichelli E, Visconti G (2007) Evolution of surface ozone in central Italy based on observations and statistical model. J Geophys Res 112:10316–10330. doi:10.1029/2006JD007900CrossRefGoogle Scholar
Jacob DJ, Prather MJ (1990) Radon-222 as a test of convective transport in a general circulation model. Tellus 42B:118–134CrossRefGoogle Scholar
Jordan TH et al (2011) Operational earthquake forecasting: state of knowledge and guidelines for utilization, report by the international commission on earthquake forecasting (ICEF) for civil protection. Ann Geophys 54:4. doi:10.4401/ag-5350Google Scholar
Lee HN, Feichter J (1996) An intercomparison of wet precipitation scavenging schemes and the emission rates of Rn-222 for the simulation of global transport and deposition of Pb-210. J Geophys Res 100:253–270Google Scholar
Megumi K, Mamuro T (1973) Radon and thoron exhalation from the ground. J Geophys Res 78:1804–1808CrossRefGoogle Scholar