Development of statistical model for predicting terrestrial gamma radiation dose
Natural environmental radioactivity aroused mainly from primordial radionuclides such as 40K and 238U and 232Th decay series, and have been present in varying concentrations within the earth and in the tissue of every living being. Natural radioactivity can be found everywhere, in the soil, public w...
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Main Authors: | , , , , |
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Format: | Article |
Published: |
Taylor and Francis Ltd.
2023
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Online Access: | http://eprints.utm.my/106871/ http://dx.doi.org/10.1080/15275922.2021.1976316 |
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Summary: | Natural environmental radioactivity aroused mainly from primordial radionuclides such as 40K and 238U and 232Th decay series, and have been present in varying concentrations within the earth and in the tissue of every living being. Natural radioactivity can be found everywhere, in the soil, public water supplies, oil, and the atmosphere and it poses a measurable exposure to human beings. The present study developed a statistical model that can be used to predict the Terrestrial Gamma Radiation Dose rates (TGRD) based on soil types and geological formations irrespective of the environment. About 295 TGRD measurements were taken using a micro-Roentgen survey meter (model 19) manufactured by Ludlum, from different locations within the study area. Statistical Package for Social Sciences (SPSS) was utilized in establishing the relationships between TGRD with underlying geological formations and soil types as well as in the development of the model. The developed model was tested by predicting the TGRD value over different combinations of soil types and geological formations, and it was found to fit in well with more than 80% degree of accuracy which is within the acceptable limit. The developed model in this study, may help in establishing the background radioactivity levels in a terrestrial environment that can be used to evaluate any changes that may arise as a result of any release due to both natural and or human activities in a certain area. |
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