Analysis Of Radon Time Series Research Articles

RADON TIME SERIES IN FOUR FLATS IN ENERGY EFFICIENT MULTI-STOREY BUILDING.

Influence of living habits and meteorological parameters on indoor radon concentration in a new energy efficiency multi-storey flat building typical for Russian cities was studied using radon time series analysis. Continuous indoor radon measurements were conducted in four flats of the same multi-storey residential building in Ekaterinburg, Russia. Factors influencing indoor radon in surveyed building (by rank) are as follows: ventilation regime> indoor/outdoor temperature difference>wind direction. Intentional ventilation frequency, temperature difference and wind direction explain together up to 46% of indoor radon variability in a flat of multi-storey building.

Monitoring soil radon during the 2016\u20132017 central Italy sequence in light of seismicity

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 earthquakes precursor, we analyse the radon concentration data recorded by two stations located close to the epicentre of the strongest mainshock (Mw 6.5 on October 30, 2016) of the seismic sequence which affected central Italy from August 2016. The two stations CTTR and NRCA operate in the framework of the permanent Italian Radon monitoring Network and recorded almost continuously since 2012 and 2016, respectively, the latter being installed just after the first mainshock of the sequence (Mw 6.0 on August 24, 2016). An increase of radon emanation is clearly visible about 2 weeks before the Mw 6.5 event on both the time series, more pronounced on NRCA, nearer to the epicentre, 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 Mw 6.5 mainshock on NRCA time series. The resulting time advance of the alarm is consistent with that obtained using a Bayesian approach to compute the a posteriori probability of multiple change points on the radon time series of NRCA. Moreover, it is in agreement with the delay time which maximizes the correlation between radon and seismic anomalies. Applying the detection algorithm to CTTR time series returns alarms for both the Mw 6.0 event, with epicentre closer to this station, and the stronger Mw 6.5 event, but with a higher number of false detections. Finally, we found that a preliminary correction of the bias introduced by variations of meteorological parameters does not affect our main finding of an increase in radon concentration before the major mainshocks. Our study confirms that, although much work is still needed, a monitoring approach based on a permanent dense network is crucial for making radon time series analysis an effective complement to traditional seismological tools.

Analysis of geophysical and meteorological parameters influencing 222Rn activity concentration in Mladeč caves (Czech Republic) and in soils of Phlegrean Fields caldera (Italy)

The present work concerns a detailed analysis of Radon time series to differentiate endogenous from exogenous phenomena which provide anomalous signals. Two-year data from two sites in Czech Republic and in Italy are analyzed in order to contribute to the prevention of natural hazards. A new hybrid forecasting method is implemented and tuned for the identification of Radon anomalies in the time series. It is based on the combination of Multiple Linear Regressions, Empirical Mode Decomposition and Support Vector Regression methods that decompose the signal and analyze the components to distinguish the variations due to Radon originated in depths from those due to environmental parameters. The possible correlations with fumarolic tremors in the Italian site and the faults microdisplacements in the Czech site have been studied, as well as with the earthquakes that have influence on two studied areas. Results show that: (i) the used method is very effective considering the calculated statistical uncertainties; (ii) the outer temperature is the main influencing Radon driving force; (iii) the extracted Radon anomalies due to endogenous phenomena are well correlated with fault displacements, fumarolic tremors, and with earthquakes under a characteristic delay time for each area; (iv) significant correlations among earthquake magnitude and depth with fault displacement and fumarolic tremor are found.

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

Descriptive analysis and earthquake prediction using boxplot interpretation of soil radon time series data

Correlation of radon anomalies with meteorological parameters and earthquake occurrence has been reported in many studies. This paper reports descriptive statistical analysis and boxplot contingent earthquake prediction based upon soil radon time series data. Data has been collected over a fault line, passing beneath the Muzaffarabad, for the period of one year. Soil radon gas (SRG) was measured using RTM 1688-2 radiometric instrument (made by SARAD GmbH). The range of radon in soil was found to be 14349 Bqm−3, whereas the ranges of temperature, pressure and relative humidity were found as 38.50 C0, 29 mbar and 67% respectively. SRG data shows that time series follows normal distribution. Values of coefficient of variation (CV) indicate the consistency of the recorded values of radon in soil and metrological parameters. Variance inflation factor (VIF) and Durbin Watson test (d) indicate a moderate multicollinearity and autocorrelation between variables. The analysis of radon time series using boxplots and meteorological parameters show specific patterns in radon concentrations (outliers, variant IQRs, first quartile values, and median values) due to pre-earthquake underground seismic activities. On the basis of these patterns earthquake may be more early predicted without using complicated predictive systems. Boxplots also predicted that there is no significant pattern found in dispersion of meteorological factors measured in this study. To the best of our knowledge this is first ever attempt to predict earthquake using boxplot explanation.

Xenon and radon time series analysis: A new methodological approach for characterising the local scale effects at CTBT radionuclide network

A new methodology of time series analysis has been tested on 133Xe and estimated 220Rn activity concentrations in order to characterise the site response of four different CTBT/IMS monitoring stations. Seasonal variability of 133Xe and 220Rn at these IMS stations and the role played by different meteorological parameters on such variability have been quantified. As xenon and radon are both noble gases with similar physical characteristics but very different source terms, the methodology adopted in this comparative study, once coupled to analysis of radioxenon emission time series sampled at nearby NPPs or IPFs and to direct measurements of 220Rn at IMS sites location, might help assess relative influence of near and far field air on IMS radioxenon detections. Possible applications of the adopted methodology to radioxenon categorisation schemes are also discussed.

Preliminary analysis of radon time series before the Ml=6 Amatrice earthquake: possible implications for fluid migration

On August 24, 2016, a Ml=6.0 earthquake occurred in Central Apennines, Italy, between the towns of Norcia and Amatrice, causing severe destruction and casualties in a wide area around the epicenter. We present a preliminary analysis of continuous radon concentration data collected from the second half of 2012 to the day after the earthquake by a long term radon monitoring station, installed at Cittareale (Rieti, Italy), about 11 km south-west of the epicenter. We combine the field data analysis with the outcome of dedicated laboratory experiments, aimed to study real time radon emission dynamics from rock samples subject to normal and shear stress loads in absence of fluid transport and migration phenomena. Our results suggest the possibility of a minor role played by phenomena related to fluid migration for the Amatrice seismic event with respect to other recent Apennine earthquakes.

The Pollino 2012 seismic sequence: clues from continuous radon monitoring

Abstract. The 2012 Pollino (Calabria, Italy) seismic sequence, culminating in the Mw 5.2 earthquake of 25 October 2012, is investigated, exploiting data collected during a long-term continuous radon monitoring experiment performed in the epicentral area from late 2011 to the end of 2014. We analyse data collected both using a phenomenological approach based on quantitative evidence and a purely numerical analysis including the following: (i) correlation and cross-correlation investigations; (ii) an original approach aimed at limiting the impact of meteorological parameters variations on the interpretation of measured radon levels; (iii) a change point analysis; (iv) the implementation of an original detection algorithm aimed at highlighting the connections between radon emission variations and major seismic events occurrence. Results from both approaches suggest that radon monitoring stations can be subject to massive site effects, especially regarding rainfall, making data interpretation harder. The availability of long-term continuous measurements is crucial to precisely assess those effects. Nevertheless, statistical analysis shows a viable approach for quantitatively relating radon emanation variations to seismic energy release. Although much work is still needed to make radon time series analysis a robust complement to traditional seismological tools, this work has identified a characteristic variation in radon exhalation during the preparation process of large earthquakes.

Daily and seasonal radon variability in the underground low-background laboratory in Belgrade, Serbia

Radon time-series analysis, based on the short-term indoor radon measurements performed worldwide, shows two main periodicity: daily and seasonal. The information obtained from time series of the measured radon values is the results of the complex radon dynamics that arises from the influence of the large number of different parameters (the state of the indoor atmosphere (temperature, pressure and relative humidity, aerosol concentration), the exchange rate between indoor and outdoor air and so on). In this paper we considered daily radon variability in the underground low-background laboratory in Belgrade, Serbia. The results are originated from the radon time-series analysis based on the 3 y of the continuous short-term indoor radon measurements. At the same time, we obtained the time series of the temperature, pressure and relative humidity in the laboratory. We also tried to find the correlation between different time series.

Radon time-series analysis in the underground low-level laboratory in Belgrade, Serbia

Measurements of radon concentration in the underground low-level laboratory in Belgrade, Serbia with a discrete sampling (T=2 h) have been performed. From July 2008 to July 2010, the time-series analysis was carried out. Also, the simultaneous measurements of meteorological parameters (temperature, atmospheric pressure and relative humidity) in the laboratory were done. The simultaneous monitoring of these parameters shows the correlation between temporal variations of radon concentration and meteorological parameters. Also, the radon time-series analysis has been used to study the possible correlation between the anomalous behaviour of the radon concentration and the local seismicity.

Identification of tidal and climatic influences within domestic radon time-series from Northamptonshire, UK

Analysis of data from extended radon concentration time-series obtained from domestic and public-sector premises in the vicinity of Northampton, UK, and elsewhere, confirms that, in addition to the generally recognised climatic influences, ‘Earth Tides’ and ‘Ocean Tidal Loading’ drive periodic radon liberation via geophysically driven groundwater level variations. Regression and cross-correlation with environmental parameters showed some degree of association between radon concentration and mean temperature and rainfall. Fourier analysis of radon time-series identified periodicities of the order of 23.9 h (luni-solar diurnal, K1), 24.0 h (solar day, S1), 168 h (1 week) and 661.3 h (lunar month, Mm), while cross-correlation with tidal strength demonstrated periodicity of the order of 14 days (lunar–solar fortnight, Mf). These results suggest that astronomical influences, including tides, play a part in controlling radon release from the soil.