The Impact of Atmospheric and Tectonic Constraints on Radon-222 and Carbon Dioxide Flow in Geological Porous Media - A Dozen-Year Research Summary

Introduction

Overview

Previous research on radon has been carried out in the last 45 years in various geological environments such as soil (e.g., Akerblom et al., 1984; Schubert and Schultz, 2002; Fujiyoshi et al., 2006; Muga, 2017; Cannelli et al., 2018; Siino et al., 2019), solid rocks (e.g., Vulkan et al., 1992; Steinitz et al., 2007; Barbosa et al., 2010), fans of erosion streams (e.g., Steinitz et al., 1992), subterranean structures such as caves, tunnels and mines (e.g., Hakl et al., 1996; Przylibski, 2001; Muramatsu et al., 2002; Cigna, 2005; Richon et al., 2005; Mentes and Eper-Pápai, 2015; Sahu et al., 2016) and groundwater (e.g., Igarashi et al., 1995; Atkins et al., 2016; Barberio et al., 2018). The main objective of such studies was either to examine the association between radon concentration changes in shallow surface environments and the health risk of radon in augmenting lung cancer, or to investigate the connection between radon and geodynamics (e.g., Mogro-Campero et al., 1977; Fleischer, 1981; Monnin et al., 1993; Trique et al., 1999; Steinitz et al., 2003; Zafrir et al., 2003; Groves-Kirkby et al., 2004; Cicerone et al., 2009; Ghosh et al., 2009; Vaupotič et al., 2010; Oh and Kim, 2015; Riggio et al., 2015; Zafrir et al., 2016; Fu et al., 2017; Singh et al., 2017) and volcanic eruptions (e.g., Eff-Darwich et al., 2002; Martin-Luis et al., 2015; Falsaperla et al., 2017; Torres-Gonzalez et al., 2019).

The available techniques for the measurement of radon and its decay products (RDPs) in sub-ground media are based on the interaction of either alpha particles or gamma-rays with the sensor material. The most common means for the measurement of radon is through the detection of alpha particle emission from the decay of Rn-222 (5.49 MeV), Po-218 (6.00 MeV) and Po-214 (7.69 MeV), or gamma ray radiation from radon decay products (RDPs) mainly Bi-214 and Pb-214 (e.g., Ivanovich and Harmon, 1982). The detection process includes recording of the alpha or gamma radiation for sequential time intervals (seconds to hours). Electronic automatic radon monitoring station are known to be operated in diverse places such as Japan (e.g., Noguchi and Wakita, 1977), China (e.g., King, 1986), and Europe (e.g., Koch and Heinicke, 1994). Most of these stations measure radon in water or soil using either Lucas cells (based on ZnS for detection of alpha particles) or NaI (for gamma detection).

A wide variety of measuring methods are presented in the literature (e.g., Knoll, 2000). For example, for passive detection, activated charcoal that adsorbs radon and its decay products from air (e.g., George, 1984) and alpha-sensitive CR-39 or LR-115 nuclear track films (e.g., Fleischer et al., 1984; Jönsson, 1997; Wertheim et al., 2010). Sealed metal cells covered with scintillator as zinc sulphide (Lucas cells, Lucas, 1957) used to measure pumped radon samples as well as ionization chambers (e.g., Ichitsubo and Yamada, 2004), and silicon photodiodes (e.g., George, 1990). Gamma sensors including Geiger-Mueller counters, scintillation light detection devices (e.g., Vulkan et al., 1995; Walia et al., 2005; Zafrir et al., 2009; Zafrir et al., 2011) and silicon photodiodes (e.g., Pinault and Baubron, 1996), have been exploited during the last 30 years, for radon detection.

In continuous long-term radon measurements, the mandatory essential condition is not to violate the natural thermodynamic equilibrium nor the radon and RDPs secular equilibrium, by pumping and grabbing radon samples from the geological porous media below the surface. The measurement technologies that allow working in passive mode are the alpha-particles sensors based on silicon photodiodes or ionization chambers, and gamma detectors based on various scintillation materials. It enables tracking temporal radon fluctuations under natural stable internal conditions, with a high-resolution sampling rate from once every few seconds up to several minutes.

For radon measurement by alpha detectors, the prime concealed problem is the ability of radon gas to move out from the solid grain to the intergranular space in the bedrock (emanation), and then to flow out to the air space (exhalation) in order to be perceived and measured by the detector. By taking into consideration that less than 32 percent of the radon content in rock emanate from the solid grains to the porous media (Hassan et al., 2009) and that the radon exhalation greatly depends on the features of the investigated media, such as its thickness, the internal structure as well as the moisture content of the solid phase, the amount of the radon gas being exhaled to the air and that may temporally be detected is less than 10%.

In addition, when an alpha detector is set inside a borehole, for example, it has to respond to radon particles that first have to enter by diffusion from the air space into the detector’s sensing volume (dozens of cm³). Then the alpha radiation which is emitted by the Rn-222 and its RDPs, Po-218 and Po-214, has to reach the internal silicon solid state sensor to produce counting signals. This process greatly reduces the efficiency of the measurement.

On the other side, there is an intrinsic distinction between the alpha and the gamma measurement, related to the sensing capabilities. When a gamma detector is installed, inside a borehole, within a geological formation, it responds to the radon existing within a surrounding spherical body of bedrocks of a radius of R + 35 cm (where R is the borehole radii and the 35 cm is the average gamma absorption length). In addition to the three-scale difference in the size of sensing volume, the gamma detection method enables principally the measurement of radon content directly inside the country rock media. Thus, it is the ideal passive method for measuring radon concentration under natural and undisturbed conditions, suitable for resolving small temporal changes provided that the gamma detectors have high detection sensitivity which is essential to distinguish between minor variations in amplitudes and time.

In light of the above, it is possible to summarize in general the important requirements to be taken into account in choosing radon detection systems for long-time monitoring as follows:

• The ability to discern small changes in the intensity of measured signals high resolution capability with high signal to noise ratio

• The ability to discern small changes in the variability of the signals at a high level of time separation, at a measurement rate of at least a few seconds high temporal resolution

• Reliability in measurements over time—a stable measurement capacity for months to years

• Automatic data collection and remote data transmission

The rules listed above rule out the use for long-time radon monitoring of the techniques based on alpha particles detection by nuclear track films or active charcoal, or even radon extraction and grabbing from subsurface soil or rocks into ionization or Lucas cells, since the results are not continuous, the measurement times are too long, and the devices may reach saturation. Radon monitoring ionization chambers and silicon photodiodes-based alpha particle detectors that do not disturbed the local environments, and crystal scintillation-based gamma detectors are the most suitable sensors for passive long-term measurements.

If there is a priority to make measurements deeper than the shallow surface and monitor radon and other natural gases at a depth of tens of meters, it is necessary to adapt the detector to this configuration.

Finally, all studies based on radon monitoring are confronted with identifying the mechanisms that control radon temporal changes produced within the geological subsurface media. The models that were developed are based on the conventional assumptions that concentration and pressure gradients within the air-filled pores within soil porous media are the main guiding-forces for radon flow by diffusion and advection. For this, a time dependent radon transport equation for the air-filled part of the porous media that combines generation, radioactive decay, diffusion, and advection of radon in porous media, was the best model developed so far (Rogers and Nielson, 1991; Van der Spoel et al., 1998).

This radon transport model for the air-filled part of the porous media as formulated by Van der Spoel (1998) is reproduced below:

$\beta \frac{\partial Ca}{\partial t}=\nabla \cdot (D\nabla Ca)+\frac{k}{\mu }(\nabla p\cdot \nabla Ca)-\beta \lambda Ca+\Phi$

$\beta$ is the partition-corrected porosity, $Ca$ is the radon concentrations in the air-phase (Bq/m³), D is the radon diffusion coefficient in air-filled pores (m²/s), k is the isotropic air-filled permeability (m²), μ is the air-filled dynamic viscosity (kg/m¹s¹), p is the air pressure (Pa) λ is the decay constant of radon (2.1/10⁶ s¹), $\Phi =\lambda \eta {\rho }_b{C}^{Ra}$ is the radon production rate from the immediate parent Ra-226 (Bq/m³s¹), $\nabla \cdot (D\nabla Ca)$ is the diffusive bulk flux density of radon which is proportional to the bulk radon concentration gradient $\nabla Ca$, $\frac{k}{\mu }(\nabla p\cdot \nabla Ca)$ is the radon advective flux density with velocity u, produced by a local gradient in pressure $\nabla p$ (deviation from the aerostatic absolute pressure) calculated from Darcy’s law: $\nabla p=-\frac{\mu }{k}u$.

But even though the existing model proved to be quite satisfactory for non-isothermal radon transport, it had one major flaw: physical equations do not include temperature, which is one of the most significant parameters affecting gas thermodynamics.

This work builds the experimental basis for extending the above model in order to include explicitly the connection between the temperature gradient and the radon movement.

The data base of the last dozen years will serve to further model radon variability by eventually determining an additional function F(Ca, ΔT, κ, E_k, T, t) to effectively describe and quantify the radon thermal flux from the surface heated by the Sun, to the subsurface porous rock and vice versa. It will allow to determine the gas flux, its direction and range, as a function of: Ca—the concentration of radon in the porous media airspaces, ΔT—the temperature gradient, κ—the thermal conductivity of the gas, E_k—the transitional kinetic energy of the radon atoms as a function of the temperature T (E_k = 3/2k_BT), and t—the time.

The Goals of This Work

In this article we intend to summarize the research and achievements, carried out in 7 phases over the past dozen years, in connection with the following subjects:

The radon and CO₂ temporal periodic variability patterns; Differentiating between the effect of atmospheric temperature and pressure on radon and CO₂ flow through a variety of sub terrains media; Eliminating the climatic-induced periodic contributions in order to identify within the measured time series the portion of the signals that could be associated with the regional geodynamic pre-seismic evolution.

The seven stages of work are described below.

Phase I

Response of subsurface Rn-222 to a 20-ton blast experiment investigated at shallow levels during seismic calibration explosion experiment, simulating a 2.6-M_L earthquake, in order to investigate the influence of the explosive blast and the transitory seismic wave fields on the radon transport in the country rock, adjacent to the focus of the explosion (Zafrir et al., 2009).

Phase II

The analysis of the temporal behavior of radon and environmental parameters measured continuously at the Amram tunnel, near Eilat (Gulf of Aqaba). The analysis of the results over a period of several years shows radon variability at multiple time scales, associated with the air temperature outside the tunnel, specifically the temperature gradient between the external environment and the more stable environment inside the tunnel (Barbosa et al., 2010).

Phase III

Study of the suitability of silicon photodiodes alpha particles detectors, gamma scintillation sensors and ionization chamber detectors, for utilization in long-term radon monitoring in sub terrain geological media. A comparison of the efficiency and sensitivity, the capability to resolve signal to noise, background, stability, and reliability of their long-term measurements was presented (Zafrir et al., 2011).

Phase IV

Long-term high-resolution collection of radon time series carried out in the southern part of Israel. It shows that long-term radon monitoring based on simultaneous alpha and gamma measurement enables to differentiate between the impact of ambient temperature and pressure on radon transportation within porous media (Zafrir et al., 2013).

Phase V

Concurrent radon measurements by gamma and alpha detection systems in a deep drilling hole served as a proxy for studying radon movement within the shallow and deep subsurface, as well as for analyzing the effect of various environmental and tectonic parameters on the radon transport pattern. The technique enabled measuring, for the first time, the radon vertical velocity in the subsurface geologic media as 25 m/hr, and the recovery of a preseismic radon anomalous signal apparently associated with a regional geodynamic process (Zafrir et al., 2016).

Phase VI

Open deserted drillings and abandoned wells are an interacting interface between the subsurface hydrosphere, lithosphere, and biosphere to the atmosphere above it. The effect of atmospheric conditions, namely atmospheric pressure and temperature, on air, CO₂, and Rn-222 transport across the borehole-ambient atmosphere interface, was investigating inside a 110 m deep by 1 m diameter borehole in northern Israel. The air exchange rate of these features was analyzed and, consequently their contribution as sources for greenhouse gas (GHG) emissions to the atmosphere was quantified (Levintal et al., 2020).

Phase VII

Long-term monitoring method of Rn-222 and CO₂ at a depth of several tens of meters at Sde-Eliezer site, located within one of the Dead Sea Fault Zone (DSFZ) segments in northern Israel, has led to the discovery of the phenomenon that both gases are affected by underground tectonic activity along the DSFZ, possible related to the pre-seismic processes associated with the accumulation and relaxation of lithospheric stress and strain producing earthquakes (Zafrir et al., 2019).

All the technological components used in each of the phases described above included the configuration of a system designed for multi-parametric measurement at a depth of tens of meters, which will be presented in the next section.

Experimental Setting

Each measurement system installed in the above-mentioned sites included at least two radon gamma detectors and, in some sites, also radon alpha detectors.

Several types of gamma detectors have been adopted: standard (2″ diameter) NaI (Tl) gamma scintillation detectors controlled by total count electronic circuit as single channel analyzer (SCA), from two sources—PM-11 system (of Rotem Industries, Israel) and narrow BGO and NaI (Tl) (1.5″ diameter) scintillation detectors (of Scionix, Holland).

These BGO and NaI detectors were chosen after we ascertained, depending on the rules listed above, that they have high sensitivity, stability and suitability for use in a 2-inch diameter exploration drilling holes to a depth of several dozen meters. We have also re-defined the energy range of the SCA used in the Scionix’s gamma detectors to count gamma rays only between 475 and 3,000 keV, cancelling the measurement of gamma radiation in the field of the Compton scattering, between 50 and 475 keV, enabling to improve the ratio of signal to noise by 70% in comparison to the PM-11 detection systems (Figure 1A).

FIGURE 1

FIGURE 1. (A) The Gamma spectra of Uranium, Thorium, and Potassium, measured using a 3″ × 3″ NaI scintillator. It displays the Bi-214 energy (RDP) lines of 609, 1,120, 1,764, and 2,204 keV in the gamma-ray spectra from magmatic rocks. The spectrum includes also energy lines of U-238 and Th-232 decay products and the isotope K-40. The Ba-133 line is due to an artificial source added for the stabilization of the electronic amplification of the MCA (Multi Channel Analyzer). (B) A 10-days measurement exhibiting the total daily gamma variations due to the RDPs, while the gamma level of the thorium decay products within the rock is stable. This demonstrates the use of total gamma measurement to track temporal variations of radon in a soil or country rock media.

The basic principle to choose the SCA for total counting of RDPs gamma rays, is the assumption that radon is the only element within the porous media that can vary in time, under the influence of atmospheric variables or tectonic activity. This fluctuation is observed in addition to the natural gamma radiation from other solid radioactive elements as uranium, thorium and potassium that produce a constant local background (Figure 1B). This validates the use of total counting by gamma detection systems equipped with a SCA for monitoring the temporal variation of radon in geological environment. The sensitivity of Scionix’s gamma detectors is 0.01–0.02 Bq/m³ per 1 count/1 hr (see Zafrir et al., 2011, based on the comparative test with a calibrated AlphaGUARD detection system, of Saphymo GmbH, Germany).

For radon detection by alpha sensing, the Barasol, BT45 N (Algade Inc., France) is a suitable instrument since it was designed to be used in difficult environments and the calibration of the sensor enables to calculate the volume activity of the Rn-222 in the measured airspace, under undisturbed natural condition. The sensor is an implanted silicon detector with a 400 mm² of sensitive area. It enables the counting of Rn-222 and its daughter alpha products by spectrometry of the alpha particles (with energy between 1.5 and 6 MeV) created in the sensing volume. The sensitivity is about 50 Bq/m³ per 1 pulse/1 hr.

For CO₂ monitoring, the detectors that were lowered down for measurements at depth, were the GMD-20 and GMP-252 infrared gas analyzers of Vaisala, Finland, with measurement ranges of 0–2,000, 0–3,000, and 0–10,000 ppm according to the borehole depth. CO₂ sensor accuracy varied between ±40 ppm with a drift of ±60 ppm/year for the lower range, to ±2% and drift of ±150 ppm/year, for the 0–10,000 ppm range.

The meteorological variables are measured at each site and with the same high time resolution, as well as complementary parameters such as temperature and relative humidity at depth.

The Results and the Achievements of the Consecutive Studies

Overview

In Israel, the first radon electronic stations were installed in 1995, in the northwestern sector of the Dead Sea. The measurements, with high temporal resolution of 15 min and with adequate sensitivity, showed the presence of a high and temporally fluctuating radon flux in gravel and water (Vulkan et al., 1995).

A research activity based on cooperation between physicists, geophysics, and geologists has begun in Israel, in 2001, aiming to integrate multi-disciplinary scientific methods in Earth sciences in order to promote the understanding of the processes of earthquake formation and to allow their early prediction (Zafrir et al., 2003).

In the last dozen years, about seven combined and diversified studies have been conducted investigating the impact of temperature, pressure, tectonic and other constrains on radon and CO₂ flow within the subsurface geological media, and they are presented in the following sections.

Phase I: Response of Subsurface Rn-222 to a 20-Ton Seismic Calibration Experiment

An underground 20-ton explosion for the purpose of performing spatial calibration of a seismic systems array in Israel (Gitterman et al., 2005) was utilized to investigate its effect on the radon movement in the shallow geological media, very close to the focal point of the explosion. A network of five radon detectors was set-up, with the radon sensors installed a few meters apart along 150 m from the center of the explosion. All the detectors were lowered to a depth of 2 m, protected by a metal pipe and suitable cushioning (Figures 2A,B).

FIGURE 2

FIGURE 2. (A) Map (Israel grid) showing relation of radon measurement sites relative to 20-ton explosion zone. (B) Radon monitoring was performed at a depth of about 2 m and a “Sensing Volume” of about 0.65 m³. (C) Overview of 15-min resolution time series of five gamma detector systems during the 13-days experiment. It presents the variations in radon concentration in the porous media in Bq/m³ around sensors (By total gamma counting rate per 15 min minus the background counting rate). The time of the explosion is marked with a vertical line. All sensors show build-up of Radon in the porous media within the “Sensing Volume”, and typical daily variations. (D) Radon concentration measured 15 h before and after the explosion, including the high resolution 10-s data averaged to 15 min (in squares). Explosion time is indicated.

Measurements were initiated 4 days before the explosion and carried on for 9 days after the calibration blast with 15 min integration time (Figure 2C). A higher sampling rate of 10 s was inserted in use for few hours before and after the explosion (Figure 2D).

Although it was possible to assume that in the center of the explosion there might be local changes in the radon concentration due to the crushing of the surrounding bedrock, there was no significant change in the radon content along the measuring line of 150 m for the duration of the expansion of the blast wave along this distance, of about 200–400 milliseconds, under acceleration of 1,700 cm/s² (Zafrir et al., 2009).

The calculations showed that in this short period of less than half a second, even under a stronger explosion that would create an earthquake simulation even more powerful than the measured M = 2.6, the radon could not respond and move more than 10 cm. Therefore, no changes were measured in the radon concentration at each of the five detectors.

The original article from 2009 includes a calculation showing that around the gamma detector which was close to 17 m from an explosion of 20 tons of explosive material, developed a huge pressure of about 5 atm that could move radon up to 0.3 m per s. [In comparison to pressure gradient-controlled variations between 10–100 Pa that were sufficient to constrain advective movement within a sand column—Van der Spoel (1998)]. However, the transition time in the explosion that was used for simulating earthquakes with magnitude of 2.6, was 0.25 s. Therefore, the time for the pressure impact on the radon gas, even if the EQ energy would be large in some order of magnitude (M = 4.5), would still be too short to move the radon gas more than a few meters away.

Hence it is possible to conclude from this experiment that the effect in the subsurface radon concentration of a sudden pressure increase associated with an occurring earthquake is very reduced, as a result of the very short distance that radon is able to move in such a short time. This does not contradict the possibility of subsurface radon being affected by a pre-seismic event, as the pressure build-up associated with earthquake preparation processes typically develops over much longer time scales, enabling radon movement over larger distances.

Phase II: The Analysis of the Long-Term Temporal Variability of Radon in Research Tunnel

Continuous radon monitoring using co-located alpha and gamma detectors was performed over a period of more than 10 years at the 170 m research tunnel in Mt. Amram. Radon was measured under stable conditions more than 100 m from the tunnel’s entrance and below a rock burden of about 100 m (see Figure 4, “Phase III: A Comparative Assessment of Radon Sensing Systems for Long–Term Monitoring in Sub Terrain Geological Media” section, Figure 5, and “Phase IV: Impact of Atmospheric Aspects on Radon Transportation Within Porous Media” section). This research tunnel in the Arava valley, which is part of the Negev desert, is particularly suitable for the investigation of the factors inducing radon variability, as some of the effects known to influence radon mobility, such as rainfall and soil moisture, are negligible in such a dry (<20 mm/year) environment. The natural environmental conditions in the tunnel are constant, specifically indoor humidity and temperature are kept stable throughout the year. In addition to the radon and environmental parameters which were measured inside the tunnel, air temperature and barometric pressure were also measured outside the tunnel.

The time series resulting from the continuous radon monitoring by both alpha and gamma systems display corresponding temporal variations (Figure 3A). Thus, the simultaneous use of alpha and gamma monitoring systems demonstrated that the detailed signals visible in both time series are genuine signals reflecting radon variability, as they are obtained from different detection systems based on distinct measurement principles.

FIGURE 3

FIGURE 3. Time-series of measurements at the Amram tunnel (15-min temporal resolution), from top to bottom panels: (A) Radon by gamma, and radon by alpha) during 6 years. (B)(left) The similarity between the two seasonal patterns becomes evident when considering the difference between the external temperature and the constant temperature inside the tunnel (temperature gradient). (B)(right) The intra-seasonal variability is also associated with changes in the temperature gradient between the inner part of the tunnel and the outside environment.

The temporal variability is characterized by a clear seasonal pattern, with maximum values in summer. As expected, the temperature and atmospheric pressure measured outside the tunnel also exhibit a clear seasonal pattern, in contrast the temperature measured inside the tunnel, at a distance of 140 m from the tunnel’s entrance, which is very stable along the year with a value of 28 ± 0.3°C. The humidity is also fairly constant and close to 90%.

The temporal variability displayed by the time series of radon and environmental parameters covers multiple time scales, from less than 1 h to years. The decomposition of the time series using the maximal overlap discrete wavelet transform (Percival, 2008) allows to extract the dominant modes of variability and to isolate seasonal, intra-seasonal, and diurnal time scales. The results show that at all the time scales temperature is the main factor responsible for the observed temporal patterns (Barbosa et al., 2010).

At the seasonal scale the variability of radon and temperature is very similar, with both variables displaying a maximum in summer; however, a detailed analysis shows that the temperature outside the tunnel increases since mid-January, while radon concentrations remain low, only increasing slightly in mid-March and then faster by mid-May. However, the similarity between the two seasonal patterns becomes evident when analyzing in detail the difference between the temperature outside the tunnel and the constant temperature inside the tunnel (hereafter noted as temperature gradient), as displayed in Figure 3B, left).

The temporal variability of the temperature gradient also drives intra-seasonal variability. radon anomalies spanning multiple days are only observed when the temperature gradient is positive. This dependence of radon on the temperature gradient is non-linear, as the amplitude of the radon anomaly is not directly related to the amplitude of the temperature gradient, but dependent on the sign of the temperature gradient (Figure 3B, right).

As for the case of seasonal and intra-seasonal variability, the daily variations are closely related to the temperature gradient between the internal part of the tunnel and the exterior. Daily variations are absent in the winter, corresponding to a negative temperature gradient. When the external temperature rises and becomes higher than the temperature in the inner part of the tunnel, the radon time series display daily cycles with maximum at night.

Temperature influences natural ventilation as well as radon transport within the porous media. Thus, the mechanisms through which temperature can influence radon variability include temperature-driven air ventilation, through the air medium, and temperature-driven radon migration by thermal gradient dependent function—in the porous media (Nield and Bejam, 2006; Zafrir et al., 2007; Zafrir et al., 2008).

Phase III: A Comparative Assessment of Radon Sensing Systems for Long-Term Monitoring in Sub Terrain Geological Media

A comparative study between alpha particles radon detectors based on silicon photodiode or passive ionization cells, and gamma-rays radon detectors based on scintillation materials, were performed in order to determine their suitability for long-term monitoring in terms of sensitivity, resolution in the parameters of signals intensity and time, as well as long-term operating reliability (Zafrir et al., 2011).

The test system was installed in the research tunnel at Mt. Amram near Eilat, within a closed room at a depth of 140 m (Rn1 and Rn2 in Figure 4A). The constant internal temperature of 28 ± 0.3°C in the tunnel’s rooms have enabled the comparison of the various radon detectors under the same environmental conditions. The setup included: Five gamma-ray systems with different dimensions (noted A–E, Rotem, Israel, and Scionix, Holland), one silicon photodiode alpha detector (noted F, Algade, France) and one calibrated ionization chamber (noted G, Saphymo, Germany). All the detectors were exposed over several days to the same natural radioactivity levels under undisturbed thermodynamic equilibrium between the air space and the tunnel walls, recording count rates with high time resolution of every 15 or 30 min (Figure 4B).

FIGURE 4

FIGURE 4. (A) Radon setup in the Amram tunnel. (B) Variations of radon from 20 February to March 18, 2009, as measured simultaneously by seven different radon sensors. The AlphaGUARD system(G), which stopped measuring on March 12, presents the radon concentration in Bq/m³ per 60 min measurement cycle time, while the rest present the CR (Counting Rate) per 30 min (A), or per 15 min (B–F). Two radon anomalies occurred: a small (in amplitude) and short (in time) one for almost two days from 26 to 28 February and a predominant one from 4 to March 18, 2009. (C) a conversion scale that enable to evaluate the counting rate, CR, per 15 or 30 min of the various detectors sensors (A–F)at peaks in Bq/m³.

A conversion scale that enable to evaluate the counting rate (CR) per 15 or 30 min of the various detectors sensors (A–F) at peaks in Bq/m³, is included in Figure 4 (Figure 4C).

The main result was that gamma detectors have a high sensitivity between 2 and 4 times in relation to the alpha detectors, enabling the detection of low sub-diurnal radon fluctuations.

In relation to the alpha detector, it was found that the statistical error during the measurements was higher than 20%, because of the low sensitivity (see Figure 4B), even in sampling intervals of 30 min [0.022 counts per 1 h for 1 Bq/m³ by the Barasol (F)]. Therefore, in order to identify variations with a required statistical accuracy of at least 5% (which can be obtained easily with each one of the gamma detectors), it is necessary to take measurements with this alpha detector in time periods of at least 8 h or even more.

There is another advantage of using a gamma detector for the measurement of radon temporal fluctuations within the geologic environment: gamma detectors do not violate environmental thermodynamic conditions or the radon secular equilibrium, as happens when grabbing or pumping radon samples. Therefore, the gamma detectors have the highest priority regarding the alternative detectors that were examined in this work. Furthermore, even mechanically it is also harder to handle and lower ionization chambers to typical depths of narrow exploration boreholes.

Phase IV: Impact of Atmospheric Aspects on Radon Transportation Within Porous Media

Long-term high-resolution Rn-222 time series, were collected in the subsurface of the southern area of Israel, at the Mt. Amram research tunnel near Eilat and in shallow and deep drillings at Gevanim site in Makhtesh Ramon (Steinitz and Piatibratova, 2009; Zafrir et al., 2013).

In general, if the radon measurements are performed at a tightly closed site, as in the Amram tunnel, the radon within the air space will be in undisturbed environmental conditions and will reach temporal thermodynamic equilibrium with the radon in the bedrocks as well as secular equilibrium with its RDPs, as encountered in the previous “Phase III: A Comparative Assessment of Radon Sensing Systems for Long-Term Monitoring in Sub Terrain Geological Media” section, Figure 4.

Then, the radon time series in the tunnel, exhibit daily and seasonal radon levels varying periodically and depending on the climatic temperature gradient outside the rock surface, 100 m above the horizontal tunnel (Figures 3BFigures 5BFigures 6A,B). The Fourier amplitude spectrum of temperature and of the “summer Radon” is greatly similar (Figures 6C,E), and the radon diurnal periodical variations are canceled during the winter (Figure 6F).

FIGURE 5

Figure 5. The Amram tunnel cross-section (A) and scheme (B).