Modeling of soil gas radon as an in situ partitioning tracer for quantifying LNAPL contamination

Background: Indoor radon represents an important health issue to the general population. Therefore, accurate radon risk maps help public authorities to prioritise areas where mitigation actions should be implemented. As the main source of indoor radon is the soil where the building is constructed, maps derived from geogenic factors ([e.g. geogenic radon potential [GRP]) are viewed as valuable tools for radon mapping. Objectives: A novel indirect method for estimating the GRP at national/regional level is presented and evaluated in this article. Design: We calculate the radon risk solely based on the radon concentration in the soil and on the subsoil permeability. The soil gas radon concentration was estimated using airborne gamma-ray spectrometry (i.e. equivalent uranium [eU]), assuming a secular equilibrium between eU and radium (226Ra). The subsoil permeability was estimated based on groundwater subsoil permeability and superficial geology (i.e. quaternary geology) by assigning a permeability category to each soil type (i.e. low, moderate or high). Soil gas predictions were compared with in situ radon measurements for representative areas, and the resulting GRP map was validated with independent indoor radon data. Results: There was good agreement between soil gas radon predictions and in situ measurements, and the resultant GRP map identifies potential radon risk areas. Our model shows that the probability of having an indoor radon concentration higher than the Irish reference level (200 Bq m-3) increases from c. 6% (5.2% – 7.1%) for an area classified as Low risk, to c. 9.7% (9.1% – 10.5%) for Moderate-Low risk areas, c. 14% (13.4% – 15.3%) for Moderate-High risk areas and c. 26% (24.5% – 28.6%) for High risk areas. Conclusions: The method proposed here is a potential alternative approach for radon mapping when airborne radiometric data (i.e. eU) are available.

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Radon Concentration in Groundwater and Soil Gas Radon in Agbabu Bituminous Deposit Area: Mapping, GR Potential and Health Risks Assessments

Iranian Journal of Science and Technology Transactions A Science ◽

10.1007/s40995-021-01094-4 ◽

2021 ◽

Author(s):

E. B. Faweya ◽

T. Adewumi ◽

Y. Ajiboye ◽

H. T. Akande ◽

H. A. Rasheed

Keyword(s):

Health Risks ◽

Radon Concentration ◽

Soil Gas ◽

Soil Gas Radon

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Radiological Assessment of Indoor Radon and Thoron Concentrations and Indoor Radon Map of Dwellings in Mashhad, Iran

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18010141 ◽

2020 ◽

Vol 18 (1) ◽

pp. 141

Author(s):

Mohammademad Adelikhah ◽

Amin Shahrokhi ◽

Morteza Imani ◽

Stanislaw Chalupnik ◽

Tibor Kovács

Keyword(s):

Limit Of Detection ◽

Indoor Radon ◽

Absolute Error ◽

Soil Gas ◽

Indoor Radon Concentration ◽

Soil Gas Radon ◽

Distance Weighting ◽

The City ◽

Monitoring Devices ◽

Radon Concentrations

A comprehensive study was carried out to measure indoor radon/thoron concentrations in 78 dwellings and soil-gas radon in the city of Mashhad, Iran during two seasons, using two common radon monitoring devices (NRPB and RADUET). In the winter, indoor radon concentrations measured between 75 ± 11 to 376 ± 24 Bq·m−3 (mean: 150 ± 19 Bq m−3), whereas indoor thoron concentrations ranged from below the Lower Limit of Detection (LLD) to 166 ± 10 Bq·m−3 (mean: 66 ± 8 Bq m−3), while radon and thoron concentrations in summer fell between 50 ± 11 and 305 ± 24 Bq·m−3 (mean 115 ± 18 Bq m−3) and from below the LLD to 122 ± 10 Bq m−3 (mean 48 ± 6 Bq·m−3), respectively. The annual average effective dose was estimated to be 3.7 ± 0.5 mSv yr−1. The soil-gas radon concentrations fell within the range from 1.07 ± 0.28 to 8.02 ± 0.65 kBq·m−3 (mean 3.07 ± 1.09 kBq·m−3). Finally, indoor radon maps were generated by ArcGIS software over a grid of 1 × 1 km2 using three different interpolation techniques. In grid cells where no data was observed, the arithmetic mean was used to predict a mean indoor radon concentration. Accordingly, inverse distance weighting (IDW) was proven to be more suitable for predicting mean indoor radon concentrations due to the lower mean absolute error (MAE) and root mean square error (RMSE). Meanwhile, the radiation health risk due to the residential exposure to radon and indoor gamma radiation exposure was also assessed.

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