Effect of soil’s porosity and moisture content on radon and thoron exhalation rates

Effect of hygroscopicity of typical powder solid wastes on their radon exhalation characteristics

The characteristics of radon exhalation in the hygroscopic properties of powder solid wastes are immensely significant for environmental safety and their transportation, storage, and landfill. This study detected the radon concentration of superfine cement and five kinds of powder solid waste: fly ash, silica fume, coal gangue, S95 mineral powder, and molybdenum tailing powder, at different hygroscopic times for 1-5 d under 95 % relative humidity. Additionally, the influence of particle size and porosity of solid waste on radon exhalation characteristics was analyzed using a laser particle size analyzer and nitrogen adsorption technology. The results show that the radon exhalation rate of the solid waste was at a low level in dry conditions. Although the presence of water due to the increased moisture absorption rate inhibited the radon exhalation to a certain extent, it was higher than that in dry conditions. The reciprocal of the moisture absorption rate had a strong linear relationship with the ratio between the radon exhalation rate after hygroscopy and radon exhalation rate from dry materials. The pore structure has a significant effect on the exhalation rate of radon, and the macropores inhibits the exhalation rate of radon. The results of this study have guiding significance for the reuse of solid waste and the prevention of radiation risk of radon exhalation during transportation.

Outdoor Radon Dose Rate in Canada's Arctic amid Climate Change

Decades of radiation monitoring data were analyzed to estimate outdoor Radon Dose Rates (RnDRs) and evaluate climate change impacts in Canada's Arctic Regions (Resolute and Yellowknife). This study shows that the RnDR involves dynamic sources and complex environmental factors and processes. Its seasonality and long-term trends are significantly impacted by temperatures and soil-and-above water contents. From 2005 to 2022, Yellowknife's RnDR increased by +0.35 ± 0.06 nGy/h per decade, with the fastest increases occurring in cold months (October to March). The rise is largely attributable to water condition changes over time in these months, which also caused enhanced soil gas emissions and likely higher indoor radon concentrations. In Resolute, the RnDR increased between 2013 and 2022 at +0.62 ± 0.19 nGy/h (or 16% relatively) per decade in summer months, with a positive temperature relationship of +0.12 nGy/h per °C. This work also demonstrates the relevance of local climate and terrain features (e.g., typical active layer depth, precipitation amount/pattern, and ground vegetation cover) in researching climate change implications. Such research can also benefit from using supporting monitoring data, which prove effective and scientifically significant. From the perspective of external exposure to outdoor radon, the observed climate change effects pose a low health risk.

Climate change as observed through the IMS radionuclide station in Spitzbergen

The International Monitoring System (IMS), installed and maintained by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) with the support of States Signatories, is a global system of monitoring stations based on four complementary technologies: seismic, hydroacoustic, infrasound and radionuclide. One of the IMS radionuclide stations is located in Spitzbergen, the largest island of the Norwegian Svalbard Archipelago, which borders the Barents Sea and the Northern Atlantic Ocean. It has been demonstrated that signs of climate change are particularly noticeable in that region. As many other radionuclides observed in environmental measurements, 212Pb is always observed at IMS stations, in varying quantities. This is also the case for the IMS station RN49, Spitzbergen, where it can be demonstrated that the average concentration of the measured lead 212Pb increases. This is observable specifically October through December. This paper demonstrates the asset of IMS data to study climate change effects. Our conclusions are supported by global temperature anomaly data from NOAA's Global Surface Temperature Analysis, covering the period 1850 to 2023.

Temperature-humidity evolution and radon exhalation mechanism of red clay-bentonite covering layer in uranium mill tailings pond

To ensure the safety and stability of the beach surface of the decommissioned uranium mill tailings pond, this paper uses red clay-bentonite and red clay (1:1) to carry out covering layer radon reduction simulation experiments to study the temperature, humidity, and radon reduction effect of the covering layer under natural conditions. The results show that the radon exhalation rate of red clay-bentonite cover layer is only 0.32 times that of red clay, which has a better radon reduction effect. The red clay-bentonite cover layer has better water retention and comparable heat preservation effect than red clay cover layer. The red clay-bentonite and red clay temperature curves follow the same evolution trend and were close together in the same outdoor conditions, and the humidity curves showed a difference of 1% to 3%. Soil temperature is the dominant factor affecting the variation of radon exhalation of red clay-bentonite and red clay covering layer with unsaturated water content.

Assessment of natural radioactivity, radon gas and soil characteristics along the Volta Lake in the Kpando municipality of Volta region, Ghana

Assessment of radionuclides, indoor radon (222RnI), radon exhalation (222Rnex), and soil characteristics in the coastal part of Kpando has been studied using HPGe, CR-39 and sieving techniques. Statistical analysis between radionuclides, radon levels and soil characteristics was done using Pearson's correlation. The mean radionuclide concentration, radon levels and soil characteristics were obtained as 226Ra (23.1 ± 1.4 Bq per kg), 232Th (34.6 ± 2.9 Bq per kg), 40K (187.1 ± 13.7 Bq per kg), 222RnI (64.70 ± 2.7 Bq per m3), 222Rnex (7.9 ± 0.5 μBq per m2h), sandy (45.9 ± 3.9%), silt (40.7 ± 3.1%), clay (13.5 ± 0.8%), porosity (0.6 ± 0.1) and moisture (7.6 ± 0.8%). Radiological effects estimated were within recommended limits. The maximum positive and negative coefficients exist between 222Ra/222Rnex (1.0) and 222Rnex/MC (-0.9), respectively. Radon exhalation correlates better with soil characteristics. The statistical analysis indicated that soil characteristics have significant effects on radionuclides and radon levels in soils and dwellings.

Unraveling the complex interplay between soil characteristics and radon surface exhalation rates through machine learning models and multivariate analysis

This research seeks to elucidate the intricate interplay between soil characteristics and the rates of radon surface exhalation rate. To achieve this aim, Light Gradient Boosting Machine (LightGBM) and eXtreme Gradient Boosting (XGBoost) machine learning (ML) algorithms are employed, supported by Multivariate Analysis (MA). An analysis was performed on a collection of soil samples, examining radon surface exhalation rates and other pertinent properties such as moisture content, particle size distributions, and the concentrations of Ra-226, Th-232, and K-40. The analysis revealed several key factors influencing radon exhalation rates, namely Ra-226 concentration, moisture content, and larger soil particles. To visualize the intricate relationships between these variables, contour plots of experimental and ML-generated data were created. These visual representations demonstrated that elevated soil moisture levels decrease radon exhalation rates. In contrast, higher concentrations of Ra-226 and a greater proportion of large soil particles led to an increase in exhalation rates. This endeavor presents these complex relationships in an accessible manner, furthering our understanding of the factors in radon surface exhalation. MA techniques, including Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were initially employed to investigate the complex interactions of soil attributes on radon exhalation. HCA identified three distinct clusters but faced limitations in detecting strong negative impacts. PCA successfully captured these inverse effects, indicating that the first two principal components accounted for approximately 80% of the total variance, primarily attributed to Ra-226 concentration, moisture content, and the percentage of large soil particles. However, neither technique could quantify the effects of soil attributes on radon exhalation rates. LightGBM outperformed XGBoost, but both successfully quantified the impacts of the studied soil characteristics on radon exhalation. Sensitivity analysis confirmed the robustness and accuracy of both models. This study highlights that XGBoost and LightGBM algorithms can effectively quantify radon exhalation rates based on soil characteristics, providing valuable insights for environmental policies, land use planning, and radon mitigation strategies.