Modelling uncertainties in the diffusion-advection equation for radon transport in soil using interval arithmetic

A sensitive system based on radon amplification at soil-air interface: Aiming to advance earthquake precursor research

Radon, a natural radioactive gas, serves as a valuable tracer in geophysical research and atmospheric science such as detecting stress induced signal in bedrock. However, the conventional radon monitoring methods often lack the sensitivity required to accurately capture such signals. This limitation, coupled with interference from meteorological effects, poses challenges in distinguishing genuine stress-induced signals. In this study, we propose a novel approach utilizing radon concentration gradients at the soil-air interface to enhance sensitivity and detect stress induced radon signals more effectively. Drawing from pressure diffusion models, we demonstrate how seismic stress accumulation in bedrock alters radon profiles in the sub-soil, providing insights into the mechanisms underlying stress-induced radon variations. Building upon this theoretical framework, we introduce the "Bhabha Radon Observatory for Seismic Application (BhaROSA)," a remote sensing, solar-powered radon observatory designed for widespread deployment and continuous unattended monitoring for big database generation. Field experiments comparing BhaROSA's performance to conventional soil probe techniques validate and confirm the superior sensitivity in line with theoretical predictions. This innovative approach holds promise for improving our understanding of stress dynamics in bedrock and has potential applications in various geophysical and atmospheric science such as earthquake precursory research, geo-genic radon potential and risk assessment. To progress, we propose international alliance and application of deep learning to a big database of precursor signals, which may lead to more informed conclusions on earthquake predictability-an enduring and unsolved challenge for humanity.

Radon exhalation behavior and determination of diffusion migration parameters in spherical porous emanation media

There is a significant impact of the radon diffusion coefficient and the free radon production rate on the exhalation of radon from porous materials that can be regarded as spheres, hexahedrons, or cylinders. To understand this effect, the radon exhalation rules of spherical porous media with different radii were studied according to the radon diffusion migration theory. A specialized method for simultaneous determination of the radon diffusion coefficient and the free radon production rate of the spherical porous media was proposed, and applied to determine the above two parameters for two hemispherical test blocks with different radii. The results show that:(1) For spherical porous media with a certain radon diffusion length (Ld), as the radius (r0) of the sphere increases, the radon exhalation rate first increases, and tends to stabilize at r0≥6Ld; The free radon release share gradually decreases from approximately 1, and drops to a steady state at r0≥18Ld. (2) Compared with conventional methods, the relative error of the free radon production rate determined by the proposed method is within 3.9%, which verifies the reliability of the new method.

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.

Field performance of the radon-deficit technique to detect and delineate a complex DNAPL accumulation in a multi-layer soil profile

The performance of the radon (²²²Rn)-deficit technique has been evaluated at a site in which a complex DNAPL mixture (mostly hexachlorocyclohexanes and chlorobenzenes) has contaminated all four layers (from top to bottom: anthropic backfill, silt, gravel and marl) of the soil profile. Soil gas samples were collected at two depths (0.8 m and 1.7 m) in seven field campaigns and a total of 186 ²²²Rn measurements were performed with a pulse ionization detector. A statistical assessment of the influence of field parameters on the results revealed that sampling depth and atmospheric pressure did not significantly affect the measurements, while the location of the sampling point and ground-level atmospheric temperature did. In order to remove the bias introduced by varying field temperatures and hence to be able to jointly interpret ²²²Rn measurements from different campaigns, ²²²Rn concentrations were rescaled by dividing each individual datum by the mean ²²²Rn concentration of its corresponding field campaign. Rescaled ²²²Rn maps showed a high spatial correlation between ²²²Rn minima and maximum contaminant concentrations in the top two layers of the soil profile, successfully delineating the surface trace of DNAPL accumulation in the anthropic backfill and silt layers. However, no correlation could be established between ²²²Rn concentrations in superficial soil gas and contaminant concentration in the deeper two layers of the soil profile. These results indicate that the ²²²Rn-deficit technique is unable to describe the vertical variation of contamination processes with depth but can be an effective tool for the preliminary characterization of sites in which the distance between the inlet point of the sampling probe and the contaminant accumulation falls within the effective diffusion length of ²²²Rn in the affected soil profile.