Assessment of natural radioactivity and radon exhalation rate associated with rock properties used for construction in greater Accra region, Ghana

Assessment of indoor radon distribution and seasonal variation within the Kpando Municipality of Volta Region, Ghana

This study uses CR-39 radon detectors to examine radon distributions, seasonal indoor radon variations, correction factors, and the influence of building materials and characteristics on indoor radon concentration in 120 dwellings. The study also determines the spatial distribution of radon levels using the ArcGIS geostatistical method. Radon detectors were exposed in bedrooms from April to July (RS), August to November (DS); December to March (HS), and January-December (YS) from 2021 to 2022. The result for the radon levels during the weather seasons were; 32.3 to 190.1 Bqm-3 (80.9 ± 3.2 Bq/m3) for (RS), 30.8 to 151.4 Bqm-3 (68.5 ± 2.7 Bqm-3) for HS and 24.8 to 112.9 Bqm-3(61.7 ± 2.1 Bqm-3) for DS, and 25.2 to 145.2 Bq/m3 (69.4 ± 2.7 Bqm-3). The arithmetic mean for April to July season was greater than August to November. The correction factors associated with this study ranged from 0.9 to 1.2. The annual effective dose (AE) associated with radon data was varied from 0.6 to 4.04 mSv/y (1.8 ± 0.1 mSv/y). The April to July period which was characterized by rains recorded the highest correlation coefficient and indoor radon concentration. Distribution and radon mapping revealed radon that the exposure to the occupant is non-uniformly spread across the studied dwellings. 15.4% of the studied data exceeded WHO reference values of 100 Bq/m3. The seasonal variation, dwelling age, and building materials were observed to have a substantial impact on the levels of radon concentration within the buildings.

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.

Radiological assessment in beach sediment of coastline, Ghana

The natural and artificial radioactivity in beach sediment sampled from the coastline of Ghana were analyzed using High Purity Germanium gamma ray detector. The overall average activity concentrations of ²²⁶Ra, ²³²Th, ⁴⁰K and ¹³⁷Cs were estimated to be 43 ± 6, 22 ± 1, 393 ± 74 and 8.4 ± 0.5 Bqkg^-1, respectively. Apart from ²²⁶Ra the mean activity concentrations of the measured radionuclides were below the world averages of 32, 45, 412 and 18.2 Bqkg^-1 respectively. High ¹³⁷Cs mean concentration of 109.8 Bqkg^-1 was observed for one of the locations, which might be due to the occurrence of a nuclear incidence or other factors. The evaluated radiological parameters also had values below world averages, except for some coastal areas which recorded Annual Gonadal Dose Equivalent (AGDE) values higher than the reference level of 300 μSvy^-1. There was no significant risk associated with the radionuclide activities evaluated along the coast of Ghana. The correlation between the radionuclides and the radiological parameters were analyzed with the Pearson correlation matrix, cluster and PCA analysis, and they all showed similar outcomes. Spatial distribution maps were also created using ArcGIS software for a pictorial view of the distribution of radionuclides along the study area.

Radon mapping, correlation study of radium, seasonal indoor radon and radon exhalation levels in communities around Ghana atomic energy commission

Radon mapping and seasonal radon studies have been carried out within the communities around the Ghana Atomic Energy Commission (GAEC), using ArcMap geostatistical interpolation tool. The correlation analysis was done using Pearson's correlation tools. Average seasonal indoor radon variations for C_R (rainy) and C_D (dry) with mean values ranging from 28.9 to 177.2 Bq/m³ (78.1 ± 38.7 Bq/m³) and 24.4-125.5 Bq/m³ (69.9 ± 24.2 Bq/m³). Average seasonal soil radon exhalation for E_R (rainy) and E_D (dry) with mean values ranging from 39.6 to 100.3 (68.9 ± 24.2 μBq/m² h) and 55.2 to 111.9 (77.1 ± 18.7 μBq/m² h). Radium concentrations ranged from 8.1 to 42.2 Bq/kg (21.3 ± 9.9 Bq/kg). Annual effective dose and resultant effective dose to lungs were found to be 0.9 to 2.9 (1.9 ± 0.8 mSv/yr), 2.1 to 9.2 (4.6 mSv/yr). The study recorded the highest and lowest positive correlation coefficient was found in the study with higher and lower coefficient values of 0.81 and 0.47 recorded in radium concentration with radon exhalation and indoor radon concentration within the dry season respectively. Pearson correlation result recorded values 0.81 and 0.47 as the highest and lowest positive coefficient values for the radium concentration correlation between radon exhalation and indoor radon concentration. One directional principal component was observed in radium concentration, seasonal radon exhalation, and indoor radon concentration. Two clusters originated from radium and seasonal radon concentrations present in dwellings as well as soils. Pearson's correlation results were in agreed with the principal component and cluster factor analysis. The study obtained the highest and lowest indoor radon concentrations with radon exhalation in rainy and dry seasons. Radium concentration was found to have a considerable effect on indoor radon and radon exhalation in dwellings and soils.

Effect of heat treatment on the emission rate of radon from red sandstone

High temperature and pore structure are important factors affecting the emission rate of radon in rocks. This study mainly focused on the correlation between radon emission rate and temperature in red sandstone. The results showed that in the temperature range of 25-400 °C, as the temperature increased, the connectivity of the internal pores of the sample became better, resulting in a significantly increased radon emission rate. The radon emission rate at 400 °C was 2.86 times the original. To explain the changes that occurred in the internal structure of the samples, the porosity characteristics of the samples after heat treatment were studied by nuclear magnetic resonance (NMR). It was found that the pore structure was also an important factor affecting the rate of radon emission. The smaller pore size of the micropores (r < 0.1 μm) inhibited the emission of radon in the sandstone. These results helped in understanding the mechanism of radon emission rate and provide an important basis for predicting rock fragmentation and coal fire.