Normal seasonal variations for atmospheric radon concentration: a sinusoidal model

Detection of atmospheric radon concentration anomalies and their potential for earthquake prediction using Random Forest analysis

Various anomalies occurring before earthquakes are currently being studied to predict seismic events, with one of them being the radioactive element radon (222Rn). Radon concentrations in the soil, water, and atmosphere fluctuate in response to crustal movement. Recent research has statistically detected anomalies by analyzing the fluctuations in radon concentrations before earthquakes and conducting quantitative evaluations of radon. However, the method used to determine the parameters in the analysis was problematic. Therefore, in this study, we compared observed atmospheric radon concentration data with predicted values based on typical annual patterns using Random Forest analysis. We conducted a more objective analysis by employing this method and statistically determining anomalies using thresholds. This analysis was conducted using atmospheric radon concentration observation data obtained at Kobe Pharmaceutical University (KPU) before the 1995 Kobe Earthquake, and ionization currents emitted when radon decays were obtained at Fukushima Medical University (FMU) before the 2011 Tohoku-oki Earthquake. Consequently, before the major earthquakes occurred at both locations, the difference between the predicted and observed values exceeded the standard deviation by a factor of three. These results indicate the potential of Random Forest analysis to identify anomalies in atmospheric radon concentrations before earthquakes occur.

Earthquake precursors: A review of key factors influencing radon concentration

Many factors influence the accurate identification of radon anomalies triggered by earthquakes to varying degrees. Therefore, this paper primarily provides a comprehensive review of the various factors influencing radon concentrations over the past two decades. In addition to examining the individual effects of these factors on radon concentrations, it explores the interactions among multiple factors, particularly the correlations among radon anomalies and seismic events as well as the environmental context. This review mainly includes the classification of groundwater radon anomalies and their potential formation mechanisms, the environmental impact on radon concentrations, the effects of soil and rock structures on radon migration, and the application of machine learning in detecting radon anomalies induced by earthquakes.

Estimating atmospheric radon deviation using statistical coefficients: Sulaymaniyah city, Iraq, as a case of study

The authors studied the atmospheric radon concentration with associated meteorological parameters variation during the dust events from July to November 2017. We obtained the meteorological parameters data in weather station of Sulaymaniyah city, Iraq. In the environmental monitoring plan, the atmospheric radon fluctuated from 15 to 48 Bq m^-3 around the mean value of 31.5 ± 7 Bq m^-3 within the summer. In autumn, varied from 22 to 46 Bq m^-3 with a mean value of 34 ± 12 Bq m^-3. We employed this to determine the radon level anomalously. Using the modified statistical coefficients, such as the residual deviation (RD), residual fluctuation ratio (RFR), F-test, and p-value coefficients. Among the atmospheric radon fluctuation values, particularly one anomalous (42 Bq m^-3) on 25 July was determined because the excessive value of the RD was 1.9 σ, and the RFR value was 66 %. Corresponding to our coefficients criteria, the minimum level of atmospheric radon (22 Bq m^-3) does not consider anomalous because of increasing wind speed. Based on this, our method for determining the atmospheric radon anomalies that are influenced by the missed factors beyond the mentioned meteorological parameters is accurate.

Preseismic atmospheric radon anomaly associated with 2018 Northern Osaka earthquake

Despite the challenges in identifying earthquake precursors in intraplate (inland) earthquakes, various hydrological and geochemical measurements have been conducted to establish a possible link to seismic activities. Anomalous increases in radon (²²²Rn) concentration in soil, groundwater, and atmosphere have been reported prior to large earthquakes. Although the radon concentration in the atmosphere is lower than that in groundwater and soils, a recent statistical analysis has suggested that the average atmospheric concentration over a relatively wide area reflects crustal deformation. However, no study has sought to determine the underlying physico-chemical relationships between crustal deformation and anomalous atmospheric radon concentrations. Here, we show a significant decrease in the atmospheric radon concentration temporally linked to the seismic quiescence before the 2018 Northern Osaka earthquake occurring at a hidden fault with complex rupture dynamics. During seismic quiescence, deep-seated sedimentary layers in Osaka Basin, which might be the main sources of radon, become less damaged and fractured. The reduction in damage leads to a decrease in radon exhalation to the atmosphere near the fault, causing the preseismic radon decrease in the atmosphere. Herein, we highlight the necessity of continuous monitoring of the atmospheric radon concentration, combined with statistical anomaly detection method, to evaluate future seismic risks.

Results of the simultaneous measurements of radon around the Black Sea for seismological applications

Results of measurements of radon around of the Black Sea are shown. Radon stations in zones of active faults were placed. Simultaneous hourly measurements of soil radon in 2005 were carried out in the Sivrice Fault Zone that is a segment of East Anatolian Fault System, in the town of Tbilisi (Georgia) and in the South Russia. In 2008 simultaneously hourly measurements of soil radon were carried out in the Western Caucasus (Russia) and in the Mytilene Island (Greece). In 2013 radon in underground waters simultaneously in midday was measuring in Crete (Greece), in the Pamukkale geothermal region (Southwest Turkey) and in the Western Caucasus. Measurements of radon concentration in the points located around of the Black Sea have shown identical regularities in changes of the data. Influence of meteorological, tidal and solar factors on changes of water radon concentrations and soil radon concentrations was observed in all researches points. But this influence was insignificant. Seismological application of observed results also was considered. Various mathematical methods of definition of anomaly in the radon data during earthquakes were considered. During researches in the Black Sea region basically earthquakes with M from 2.0 up to 5.0 and in a depth about 10 km were occurred. For these earthquakes method of daily subtraction of the data of the next and previous day was used. This method has allowed solving a problem with a choice of average value. Probability up to 0.69 (number of earthquakes with radon anomalies/total number of earthquakes) of detection of radon anomalies before earthquakes was achieved applying this method. Changes of radon maps before regional earthquakes were also observed. The frequency analysis of variations of the radon data on the basis of the Wavelet analysis was carried out. Occurrence of the short periods (about 2 days) was observed during regional earthquakes.

Non-parametric detection of atmospheric radon concentration anomalies related to earthquakes

Anomalous phenomena related to earthquakes have been studied to aid in the forecasting of large earthquakes. Radon (²²²Rn) concentration changes are known to be one of those phenomena. Many studies have quantified radon anomalies to identify physical aspects of radon emanations related to earthquakes. Here, we apply singular spectrum transformation, non-parametric analysis to estimate change points in time series, to atmospheric radon concentration. From 10 years of data from continuous observation of the atmospheric radon concentration over northeastern Japan and Hokkaido, we identify anomalies in the atmospheric radon concentration related to the moment releases of large earthquakes. Compared with a conventional model-based method, the singular spectrum transformation method identifies more anomalies. Moreover, we also find that change points in the atmospheric radon concentration prior to the 2011 Tohoku-Oki earthquake (M_w 9.0; 11 Mar. 2011, N38.1°, E142.9°) coincided with periods of other anomalous precursory phenomena. Our results indicate that singular spectrum transformation can be used to detect anomalies in atmospheric radon concentration related to the occurrences of large earthquakes.

Anomalous changes in atmospheric radon concentration before and after the 2011 northern Wakayama Earthquake (Mj 5.5)

A significant increase in atmospheric radon concentration was observed in the area around the epicentre before and after the occurrence of the shallow inland earthquake in the northern Wakayama Prefecture on 5 July 2011 (Mj 5.5, depth 7 km) in Japan. The seismic activity in the sampling site was evaluated to identify that this earthquake was the largest near the sampling site during the observation period. To determine whether this was an anomalous change, the atmospheric daily minimum radon concentration measured for a 13-year period was analysed. When the residual radon concentration values without the seasonal radon variation and the linear trend was > 3 standard deviations of the residual radon variation corresponding to the normal period, the values were deemed as anomalous. As a result, an anomalous increase in radon concentration was determined before and after the earthquake. In conclusion, anomalous change related to earthquakes with at least Mj 5.5 can be detected by monitoring atmospheric radon near the epicentre.

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.