Radon transport events associated with the impact of a NORM repository in the SW of Europe

Two radon measurement stations located to the north and south of a NORM (Naturally Occurring Radioactive Materials) repository of phosphogypsum (southwest of Europe) were used to monitor radon behavior during 2018. The stations are located at opposing sides of the repository, one in Huelva City to the north and other one in a rural area to the south. This setup aimed to identify the influence of the NORM repository on each station and use radon levels as a marker of atmospheric transport in the local area. To achieve this, a comparison was carried out with other coastal stations in the south of Spain, finding higher average concentrations in Huelva City, ~3.3 Bq m^-3. Hierarchical clustering was applied to identify days with different radon patterns at each Huelva station, detecting possible local radon transport events from the repository. Three events were investigated with WRF (Weather Research and Forecasting) and FLEXPART-WRF (FLEXible PARTicle dispersion model). It was found that both sampling sites required atmospheric stagnant conditions to reach high radon concentration. However, under these conditions the urban station showed high radon regardless of wind direction while the rural station also required radon transport from the repository, either directly or indirectly.

Annual variation in the atmospheric radon concentration in Japan

Anomalous atmospheric variations in radon related to earthquakes have been observed in hourly exhaust-monitoring data from radioisotope institutes in Japan. The extraction of seismic anomalous radon variations would be greatly aided by understanding the normal pattern of variation in radon concentrations. Using atmospheric daily minimum radon concentration data from five sampling sites, we show that a sinusoidal regression curve can be fitted to the data. In addition, we identify areas where the atmospheric radon variation is significantly affected by the variation in atmospheric turbulence and the onshore-offshore pattern of Asian monsoons. Furthermore, by comparing the sinusoidal regression curve for the normal annual (seasonal) variations at the five sites to the sinusoidal regression curve for a previously published dataset of radon values at the five Japanese prefectures, we can estimate the normal annual variation pattern. By fitting sinusoidal regression curves to the previously published dataset containing sites in all Japanese prefectures, we find that 72% of the Japanese prefectures satisfy the requirements of the sinusoidal regression curve pattern. Using the normal annual variation pattern of atmospheric daily minimum radon concentration data, these prefectures are suitable areas for obtaining anomalous radon variations related to earthquakes.

Normal seasonal variations for atmospheric radon concentration: a sinusoidal model

Anomalous radon readings in air have been reported before an earthquake activity. However, careful measurements of atmospheric radon concentrations during a normal period are required to identify anomalous variations in a precursor period. In this study, we obtained radon concentration data for 5 years (2003-2007) that can be considered a normal period and compared it with data from the precursory period of 2008 until March 2011, when the 2011 Tohoku-Oki Earthquake occurred. Then, we established a model for seasonal variation by fitting a sinusoidal model to the radon concentration data during the normal period, considering that the seasonal variation was affected by atmospheric turbulence. By determining the amplitude in the sinusoidal model, the normal variation of the radon concentration can be estimated. Thus, the results of this method can be applied to identify anomalous radon variations before an earthquake.