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When studying the fault tectonics of the Vychegodskii trough, we detected an area of high concentrations of soil radon, confined to the zone of the Vychegda–Lokchim fault. To localize the radon anomaly, we carried measurements of the volumetric radon activity out over a network of observation points. Air sampling at each point was performed from the wellhead with a depth of 0.5 m and a diameter of 0.1 m. Based on the data obtained, an intense radon anomaly was contoured. At different times, the anomaly changed in the size, shape, and intensity, but its center always remained fixed. According to areal observations, in the central part of the 2 × 2-km anomaly, the radon concentration reached 3800–4800 Bq/m3. The results of continuous daily monitoring in the center of the anomaly showed that the of radon concentration is subject to daily dynamics, which directly depends on meteorological parameters, namely on temperature and humidity. At night, with a decrease in temperature and an increase in air humidity, the level of radon increased to 6000–8000 Bq/m3 on average, in rare cases up to 10 000–12 000 Bq/m3. In the daytime, with an increase in temperature, a decrease in the volumetric radon activity was noted. In addition to the daily dynamics, seasonal variability of the radon field was observed. In autumn, the radon concentration is lower than in summer, which is associated with short-term precipitation and, as a result, the filling of the pore space with water. The Archean–Early Proterozoic basement composed of gneisses, amphibolites, quartzites, and migmatites at a depth of 2 km is considered as the main source of radon. Due to the fact that the anomaly is located in the zone controlled by the Vychegda–Lokchim fault, the latter is considered the main pathway for fluid transport to the surface. [ABSTRACT FROM AUTHOR]

We analyzed the major chemical components, hydrogen (δD) and oxygen isotopes (δ18O), and tritium activity in groundwater from Jiujiang well number 2 (JJ2) as well as atmospheric precipitation and water from the Maweishui spring and Tianhuajing reservoir in the Mt. Lushan region, Eastern China. The results show that the water in JJ2 is of the HCO3-Ca·Mg type, with ionic components mainly arising from calcite and dolomite mineral dissolution. According to the δD and δ18O data, the groundwater of JJ2 mainly comes from atmospheric precipitation, and the recharge elevation is 554 m. Results for tritium activity indicate that JJ2 is fed by both an ancient water supply and a new water supply within a period of 10 years. These results demonstrate that JJ2 has characteristics of both shallow and deep circulating water, which implies that aquifers involving two different recharge sources rise to the well surface via different circulation paths. That is exactly why JJ2 is tectonically sensitive and could display a remarkable gas radon anomaly before the Ruichang-Yangxin ML 5.0 earthquake in 2011. Our results also indicate that ascertaining the hydrological characteristics and cycling process of groundwater are crucial for understanding the earthquake anomalies and judging whether a seismic groundwater monitoring well is reliable or not.

На Петропавловск-Камчатском геодинамическом полигоне работает сеть пунктов мониторинга подпочвенных газов. За время работы сети в поле подпочвенных газов были зарегистрированы аномалии, предваряющие сильные землетрясения с магнитудой М>5. По морфологическим признакам они разделены на два типа А и Б. В работе описывается разработанное программное обеспечение для моделирования возникновения радоновых аномалий на основании математической модели инжекции под воздействием импульсов напряжения изотопов в поток подземных вод с полным поперечным перемешиванием.

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. [ABSTRACT FROM AUTHOR]

This paper reviews the changes in indoor radon concentrations, measured in a university building in Gyeongju, Rep. of Korea, to find the relationship, it exists, between the indoor radon concentrations and the seismic activities in the area neighboring Gyeongju. The measurement period was from June 1, 2017, to May 31, 2019. During this period, numerous seismic activities occurred in the southeastern region of the Korean peninsula. Considering the magnitude and distances from our measurement place to epicenters, 11 earthquakes for analysis were chosen. Among these, nine earthquakes were found to have radon anomalies before their occurrences. Three earthquakes with a magnitude greater than 4.0 were scrutinized for the correlation between radon anomalies. Effects of the environmental variables such as relative humidity, barometric pressure, rainfall, and inlet temperature were also examined. Similar to those found in our previous study, spike-like patterns were also found in the indoor radon concentration distributions before the earthquakes. [ABSTRACT FROM AUTHOR]

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In this study, we use the critical slowing down (CSD) theory to identify the precursory anomalies of groundwater radon based on the 1000-day continuous data from 8 monitoring stations in Yunnan Province, China during the seismically active period of 1993–1996. The low-frequency and high-frequency information were extracted from raw groundwater radon data to calculate their one-step lag autocorrelation (AR-1) and variance, respectively, in order to identify the precursory anomalies. The results show that the anomaly characteristics can be divided into three categories: sudden jump anomalies, persistent anomalies, and fluctuation anomalies. The highest average seismic recognition rate is 72.78%, based on the high-frequency information’s autocorrelation, while the lowest is 45.08%, based on the low-frequency information’s variance. The crustal activity and the change in hydrogeological conditions are possibly the main factors influencing groundwater radon anomalies in the selected period in the study area. There is a positive correlation between the anomaly occurrence time and epicentral distance when epicentral distance is less than 300 km, which may be related to the seismogenic modes and hydrogeological conditions. This study provides a reference for identifying groundwater radon anomalies before earthquakes by mathematical methods.

Groundwater radon concentrations can reflect the changes of crustal stress and strain. Scholars and scientific institutions have also recorded groundwater radon precursor anomalies before earthquakes. Therefore, groundwater radon monitoring is an effective means of predicting seismic activities. However, the variation of radon concentrations within groundwater is not only affected by structural factors, but also by environmental factors, such as air pressure, temperature, and rainfall. This causes difficulty in identifying the possible precursor anomalies. Therefore, the EMD-LSTM model is proposed to identify the radon anomalies. This study investigated the time series data of groundwater radon from well #32 located in Sichuan province. Three models (including the LSTM (Long Short-Term Memory) model with auxiliary data, the EMD-LSTM (Empirical Mode Decomposition Long Short-Term Memory) model with auxiliary data, and the EMD-LSTM model without auxiliary data) were developed in order to predict groundwater radon variations. The results indicated that the prediction accuracy of the EMD-LSTM model was much higher than that of the LSTM model, and the EMD-LSTM model without auxiliary data also can obtain an ideal prediction result. Furthermore, the different durations of seismic activities T (T = ±10, ±30, ±50, and ±100) were also investigated by comparing the identification results. The identification rate of the precursor anomalies was the highest when T = ±30. The EMD-LSTM model identified five possible radon anomalies among the seven selected earthquakes. Taking well #32 as an example, we provided a promising method, that was the EMD-LSTM model, to detect the groundwater radon anomalies. It also suggested that the EMD-LSTM model can be used to identify the possible precursor anomalies within future studies.

The present paper deals with monitoring soil radon-222 concentration at two different locations, designated Site A and Site B, 200 m apart at Jadavpur University campus, Kolkata, India, with a view to find possible precursors for the earthquakes that occurred within a few hundred kilometers from the monitoring site. The solid state nuclear track detector CR-39 has been used for detection of radon gas coming out from soil. Radon-222 time series at both locations during the period August 2012–December 2013 have been analysed. Distinct anomalies in the soil radon time series have been observed for seven earthquakes of magnitude greater than 4.0 M that occurred during this time. Of these, radon anomalies for two earthquakes have been observed at both locations A and B. Absence of anomalies for some other earthquakes has been discussed, and the observations have been compared with some earthquake precursor models. [ABSTRACT FROM AUTHOR]

Monitoring the concentration of radon gas is an established method for geophysical analyses and research, particularly in earthquake studies. A continuous radon monitoring station was implemented in Jooshan hotspring, Kerman province, south east Iran. The location was carefully chosen as a widely reported earthquake-prone zone. A common issue during monitoring of radon gas concentration is the possibility of noise disturbance by different environmental and instrumental parameters. A systematic mathematical analysis aiming at reducing such noises from data is reported here; for the first time, the Kalman filter (KF) has been used for radon gas concentration monitoring. The filtering is incorporated based on several seismic parameters of the area under study. A novel anomaly defined as 'radon concentration spike crossing' is also introduced and successfully used in the study. Furthermore, for the first time, a mathematical pattern of a relationship between the radius of potential precursory phenomena and the distance between epicenter and the monitoring station is reported and statistically analyzed. [ABSTRACT FROM AUTHOR]

Abstract: Radon concentrations were measured in water of 4 wells on the Akşehir-Simav Fault System (ASFS) in Afyonkarahisar province from August 2009 to September 2010 and the relationship between radon anomalies and earthquake magnitudes was examined. Anomalous decreases in radon concentrations in the wells were observed to precede the earthquakes of magnitudes ranging from 2.6 M to 3.9 M. The correlation coefficients (R 2) were 0.79, 0.93, 0.98 and 0.90 for the wells from 1 to 4, respectively, indicating that radon minima and earthquake magnitude were well correlated and suggesting that the groundwater radon, when observed at suitable sites, can be a sensitive tracer for strain changes in crust associated with earthquake occurrences. The relationship between the two parameters can be further improved as additional radon anomalies precursor to possible large earthquakes are recorded in the wells located on the ASFS in the future. This study strongly suggests that the continuous observations of radon concentrations in well water, especially at well 3, should be carried forward. [Copyright &y& Elsevier]

This paper reports the measurement of radon concentration in well water at the site of Jalpaiguri (26°32′N, 88°46′E) near the active fault zone of West Bengal, India. Radon concentration has been measured in well water with the help of solid-state nuclear track detectors (SSNTD). The study indicates a positive correlation between radon anomaly and earthquake. The data of radon content in well water have been compared with that in soil gas at the same site. [ABSTRACT FROM AUTHOR]

The variations of spring water radon concentration and meteorological parameters were analysed in relation to the seismic activities in Garhwal Himalaya, India. The radon anomalies were classified on the basis of statistical treatment of the daily observations. The precise measurements of water discharge rate from the spring have been made along with radon measurements for earthquake precursory study. The earthquakes with epicentral distances less than 150 km were considered by an empirical relationship. Pre-, co-, and post-seismic changes in the radon concentration were taken carefully into account in the empirical relationship to establish this behaviour as a potential earthquake precursor. The empirical relationship has been validated by the radon data recorded from the spring waters. The magnitudes of the earthquakes were estimated by using the empirical relationship by introducing computed correlation coefficient of radon and meteorological parameters. The calculated magnitude of some local earthquakes matches exactly with the magnitude recorded by the laboratory seismograph. The possible mechanisms that may cause a radon anomaly are also discussed. [ABSTRACT FROM AUTHOR]

Abstract: Precursory changes in the radon concentration of groundwater were observed by prior to the 1978 Izu-Oshima-Kinkai earthquake of magnitude 7.0. Mechanisms for interpreting the anomalous radon decrease are examined in this paper. The SKE-1 well is situated in a volcanic-rock fractured aquifer of limited recharge. Given these geological conditions, the dilation of brittle rock mass occurred at a rate faster than the recharge of groundwater and gas saturation developed in newly created cracks preceding the earthquake. Radon volatilization into the gas phase can explain the anomalous decrease of radon precursory to the 1978 earthquake. To support the hypothesis, vapor–liquid two-phase radon-partitioning experiments were conducted at formation temperature (14°C) using formation water from the SKE-1 well. Experimental data indicated that the decrease in radon concentration from 483±3 count/min to 439±7 count/min required a gas saturation of 2.35% developed in rock cracks through the dilatancy process. [Copyright &y& Elsevier]

Abstract: Recent years have seen an ever increasing interest in studying the usefulness of radon measurements in earth sciences. Radon emissions that are enhanced by forthcoming geophysical events as earthquakes or volcanic activity have been observed all over the world. The abnormal radon exhalation from the interior of earth, as a precursory phenomenon related to earthquakes and as an indicator of underlying geological faults, is an important field of investigation. For this purpose a number of active and passive methods for getting radon signals have been developed. Several models have been proposed as an explanation of the experimental field data. This paper gives a brief review of the progress made in the field of radon measurements in earth sciences specially in predicting earthquakes. Radon anomalies that have been observed in soil gas as well as groundwater or spring prior to earthquakes have been reviewed in this paper. The models proposed in relating precursor time, epicentral distance, magnitude of earthquake have also been discussed. [Copyright &y& Elsevier]

In this study, we use the critical slowing down (CSD) theory to identify the precursory anomalies of groundwater radon based on the 1000-day continuous data from 8 monitoring stations in Yunnan Province, China during the seismically active period of 1993–1996. The low-frequency and high-frequency information were extracted from raw groundwater radon data to calculate their one-step lag autocorrelation (AR-1) and variance, respectively, in order to identify the precursory anomalies. The results show that the anomaly characteristics can be divided into three categories: sudden jump anomalies, persistent anomalies, and fluctuation anomalies. The highest average seismic recognition rate is 72.78%, based on the high-frequency information's autocorrelation, while the lowest is 45.08%, based on the low-frequency information's variance. The crustal activity and the change in hydrogeological conditions are possibly the main factors influencing groundwater radon anomalies in the selected period in the study area. There is a positive correlation between the anomaly occurrence time and epicentral distance when epicentral distance is less than 300 km, which may be related to the seismogenic modes and hydrogeological conditions. This study provides a reference for identifying groundwater radon anomalies before earthquakes by mathematical methods. [ABSTRACT FROM AUTHOR]

Groundwater radon concentrations can reflect the changes of crustal stress and strain. Scholars and scientific institutions have also recorded groundwater radon precursor anomalies before earthquakes. Therefore, groundwater radon monitoring is an effective means of predicting seismic activities. However, the variation of radon concentrations within groundwater is not only affected by structural factors, but also by environmental factors, such as air pressure, temperature, and rainfall. This causes difficulty in identifying the possible precursor anomalies. Therefore, the EMD-LSTM model is proposed to identify the radon anomalies. This study investigated the time series data of groundwater radon from well #32 located in Sichuan province. Three models (including the LSTM (Long Short-Term Memory) model with auxiliary data, the EMD-LSTM (Empirical Mode Decomposition Long Short-Term Memory) model with auxiliary data, and the EMD-LSTM model without auxiliary data) were developed in order to predict groundwater radon variations. The results indicated that the prediction accuracy of the EMD-LSTM model was much higher than that of the LSTM model, and the EMD-LSTM model without auxiliary data also can obtain an ideal prediction result. Furthermore, the different durations of seismic activities T (T = ±10, ±30, ±50, and ±100) were also investigated by comparing the identification results. The identification rate of the precursor anomalies was the highest when T = ±30. The EMD-LSTM model identified five possible radon anomalies among the seven selected earthquakes. Taking well #32 as an example, we provided a promising method, that was the EMD-LSTM model, to detect the groundwater radon anomalies. It also suggested that the EMD-LSTM model can be used to identify the possible precursor anomalies within future studies. [ABSTRACT FROM AUTHOR]

Abstract: The real time radon monitoring is an extensively studied area in order to give premonitory signs prior to an earthquake. The strain changes that occurred within the earth surface during earthquake is expected to enhance the radon concentration in soil gas. In order to support this theoretical view, we have performed an experiment on measuring radon concentration in soil gas with the use of CR-39—solid state nuclear track detector (SSNTD). The study has been performed at Jadavpur University, Kolkata, India. This paper reports essentially the observation of radon anomaly for the earthquakes that occurred during the period of November 2005–October 2006 within the range of 1000km from the measuring site and of . The study is important as no such work has been done at Kolkata, India, which is a relatively geologically stable area. [Copyright &y& Elsevier]

Abstract: During the course of an investigation into domestic radon levels in Northamptonshire, two hourly sampling real-time radon detectors were operated simultaneously in separate locations 2.25 km apart in Northampton, in the English East Midlands, for a 25-week period. This period of operation encompassed the period in September 2002 during which the Dudley earthquake (magnitude – 5.0) and smaller aftershocks occurred in the English West Midlands, UK. We report herein our observations regarding the occurrence of simultaneous short-period radon anomalies and their timing in relation to the Dudley, and other, earthquakes which occurred during the monitoring period. Analysis of the radon time-series reveals a short period when the two time-series displayed simultaneous in-phase short-term (6–9 h) radon anomalies prior to the main Dudley earthquake. Subsequent investigation revealed that a similar period occurred prior to another smaller but recorded earthquake in the English Channel. [Copyright &y& Elsevier]

Abstract: The 222Rn concentration profiles in soil have been measured at an anomaly spot in Tateishi, Japan. In winter, the concentrations were low and showed a negative gradient with depth, but in other seasons, the concentration had both positive and negative gradients with depth, and dramatically changed by time. On the assumption that there was ventilation in deep layers and with driving forces of wind and temperatures, these phenomena were successfully explained. This finding would contribute to a numerical model for 222Rn transport in soil. [Copyright &y& Elsevier]

Radon concentrations in soil gas were continuously measured by the LR-115 nuclear track detectors during a four-year period. Seismic activities, as well as barometric pressure, rainfall and air temperature were also observed. The influence of meteorological parameters on temporal radon variations was investigated, and a respective equation of the multiple regression was derived. The earthquakes with magnitude ⩾3 at epicentral distances ⩽200 km were recognized by means of radon anomaly. Empirical equations between earthquake magnitude, epicentral distance and precursor time were examined, and respective constants were determined. [Copyright &y& Elsevier]

Radon data accumulated during 1992–1999 in the grid (30–34°N, 74–78°E) in N-W Himalaya have been anlaysed vis a vis seismic data recorded in the same area, supplied by Indian Meteorological Department (IMD) network. In general, there is a positive correlation between the total radon emission and the microseismicity in the area under investigation. The earthquake magnitude has moderate positive correlation with epicentral distance and low positive correlation with amplitude of radon precursory signal, whereas both show low negative correlation between them.Empirical scaling relations are proposed using the best fit straight line from the log-linear graphs between magnitude of the events and log of the product of amplitude of radon anomaly and epicentral distance. The error between the recorded and calculated magnitude is also taken into account. The error range is higher at lower epicentral distances and magnitudes, showing that the local geology and tectonics have predominant influence on radon signals. [Copyright &y& Elsevier]

A radon anomaly in a nuclear track detector placed on a fault was detected prior to the destructive (Ms = 8.1) Mexican earthquake of 19 September 1985. The fault is a structural feature of the geothermal field 'Los Azufres', 260 km NE of the epicentral area. Since no other phenomenon can be found as a possible cause for the radon anomaly, it is proposed that preseismic regional stress perturbations may produce changes in the fluid transport patterns at the fault, suggesting that radon measurements in similar conditions could provide a good precursor in high seismic risk areas. [ABSTRACT FROM AUTHOR]

Radon in groundwater has long been recognized as a sensitive indicator of crustal stress. Significant changes in groundwater radon concentration before earthquakes have been documented in many studies. However, the radon concentration in groundwater may be affected by many interference factors. The anomalies before seismic activities may not be large enough to be clearly identified by the conventional statistical method. Therefore, new methods are needed to identify the possible pre-seismic anomalies. In this study, we investigated 38 years' worth of radon time series data (1977–2015) in a hot spring to identify the possible precursor anomalies. We first identify the factors that may affect the radon fluctuations by wavelet coherence analysis, spring discharge, water temperature, rainfall and barometric pressure. All are found to be closely related to the radon fluctuation. The time series (1980–2008) were used for further decision tree analysis as a high correlation in the duration. Following this, we constructed the decision tree models based on these factors to model the "background" radon fluctuation and identify the anomalies by comparing the difference between the observed radon changes and the "background" fluctuations. The modeled "background" fluctuation is closely related to the observed data during the non-seismic activity period, with the correlation coefficient of 0.8. Following this, we compared the modeled "background" fluctuation of the radon time series with the observed one during the seismic activities period. The decision tree could identify 15 possible radon anomalies among the 24 chosen earthquakes. The identified anomalies are also supported by the anomaly changes in water temperature and spring discharge. Therefore, we believe that the decision tree method could be an efficient way to identify the possible precursor anomalies in future studies. Additionally, we explore the mechanism of radon anomalies. The plausible mechanism for the anomalous increase is that radon is continuously supplied from newly formed internal surfaces of the crack to the aquifer system. For the anomalous decrease, it might be related to radon partitioning into the gas phase and the change of mixing ratio of shallow and depth water. • 38 years' radon time series data (1977–2015) in a hot spring was investigated. • Factors affect the radon fluctuations was identified by wavelet coherence analysis. • Decision tree models was applied in order to identify the possible radon anomalies. • 15 possible radon anomalies among the 24 chosen earthquakes was identified. [ABSTRACT FROM AUTHOR]

The seasonal variations of radon exhalation rate from soil surface were studied in two seismically active regions of the Russian Federation - the Baikal rift and the North Caucasus. In each region, monthly measurements of the radon exhalation have been carried out at two relatively proximal sites, one of which was located within the active fault zone and the other outside of the fault zone. The Open Charcoal Chamber Method was used. Very high radon exhalation rate values were found in the fault zones at both regions. At the Baikal rift, the radon exhalation reached 1.4 Bq m−2 s−1, and at the Caucasian region in some periods it even achieved 24 Bq m−2 s−1, which is an extremely high value. The same pattern of seasonal variations of radon levels with abnormal high radon exhalation rate values in summer and extremely low in winter were observed in both the Baikal and Caucasus regions. Clear correlation between radon exhalation and air temperature were also revealed. The obtained data and simulation results indicate that seasonal fluctuations in the radon exhalation rate are caused by the inversion of the direction of convective air flow in the fractured zones of the rock massif. In summer, the convective air flow is directed from the rock massif to the atmosphere and in winter, vice versa, from the atmosphere to the rock massif. This phenomenon is similar to the well-known "chimney effect", i. e. in winter there is a direct draft in the system of fractures, and in summer — the reverse one. Thus, the detected radon anomalies are due to near-surface convective air circulation in permeable zones of the mountain ranges and most probably are not associated with deep crustal or mantle degassing. Seasonal thermally induced radon anomalies should be taken into account both in the radon risk mapping and in the application of radon as a tracer of natural processes in various fields of geology and geophysics. • Radon exhalation rate from soil surface and radionuclide content in soils are measured in a fault zones in the two seismically active regions of the Russian Federation — the Baikal rift and the North Caucasus. • Same pattern of seasonal variations of radon exhalation with abnormal high radon exhalation rate values in summer and extremely low in winter are observed in both the Baikal and Caucasus regions. • Clear correlation between radon exhalation and air temperature were revealed. • Seasonal variations of the radon exhalation rate in fault zones are caused by the inversion of the direction of convective air flow in the fractures. This phenomenon is similar to the well-known "chimney effect", i. e. in winter there is a direct draft in the system of fractures, and in summer — the reverse one. [ABSTRACT FROM AUTHOR]

Abstract: The detection system KATERINA has been used in the National Laboratory of Gran Sasso (close to L’ Aquila) in Italy for short term continuous monitoring of radon daughter concentrations in a groundwater path. The system was immersed in an water tank which was supplied with groundwater discharged from the mountain of Gran Sasso. The system offers quantitative results using calibration parameters obtained by reference sources and appropriate system efficiency simulation. Measurements were performed in two periods (December 2005 and November 2007) exhibiting almost constant radon level 2.8Bq/l in the first period, while in the second period it increased up to 6.8Bq/l. This gradual enhancement of radon background level could be attributed to the increase of microseismicity that occurred from late of 2007 till April 2009. [ABSTRACT FROM AUTHOR]