Modeling background radiation using geochemical data: A case study in and around Cameron, Arizona

This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions t...

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Published inJournal of environmental radioactivity Vol. 165; no. C; pp. 68 - 85
Main Authors Marsac, Kara E., Burnley, Pamela C., Adcock, Christopher T., Haber, Daniel A., Malchow, Russell L., Hausrath, Elisabeth M.
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 01.12.2016
Elsevier
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Abstract This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions to background radiation for the purpose of emergency response and homeland security operations. The forward models are based on geologic maps and remote sensing multi-spectral imagery combined with two different sources of data: 1) bedrock geochemical data (uranium, potassium and thorium concentrations) collected from national databases, the scientific literature and private companies, and 2) the low spatial resolution NURE (National Uranium Resource Evaluation) aerial gamma-ray survey. The study area near Cameron, Arizona, is located in an arid region with minimal vegetation and, due to the presence of abandoned uranium mines, was the subject of a previous high resolution gamma-ray survey. We found that, in general, geologic map units form a good basis for predicting the geographic distribution of the gamma-ray background. Predictions of background gamma-radiation levels based on bedrock geochemical analyses were not as successful as those based on the NURE aerial survey data sorted by geologic unit. The less successful result of the bedrock geochemical model is most likely due to a number of factors including the need to take into account the evolution of soil geochemistry during chemical weathering and the influence of aeolian addition. Refinements to the forward models were made using ASTER visualizations to create subunits of similar exposure rate within the Chinle Formation, which contains multiple lithologies and by grouping alluvial units by drainage basin rather than age. •Methods for making predictive high resolution gamma-ray background maps were tested.•Successful maps were composed of background radiation units based on bedrock units.•Background unit properties calculated from geochemical data were not successful.•Background unit properties calculated from NURE survey data were successful.•Maps segmented by ASTER imagery were also evaluated.
AbstractList This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions to background radiation for the purpose of emergency response and homeland security operations. The forward models are based on geologic maps and remote sensing multi-spectral imagery combined with two different sources of data: 1) bedrock geochemical data (uranium, potassium and thorium concentrations) collected from national databases, the scientific literature and private companies, and 2) the low spatial resolution NURE (National Uranium Resource Evaluation) aerial gamma-ray survey. The study area near Cameron, Arizona, is located in an arid region with minimal vegetation and, due to the presence of abandoned uranium mines, was the subject of a previous high resolution gamma-ray survey. We found that, in general, geologic map units form a good basis for predicting the geographic distribution of the gamma-ray background. Predictions of background gamma-radiation levels based on bedrock geochemical analyses were not as successful as those based on the NURE aerial survey data sorted by geologic unit. The less successful result of the bedrock geochemical model is most likely due to a number of factors including the need to take into account the evolution of soil geochemistry during chemical weathering and the influence of aeolian addition. Refinements to the forward models were made using ASTER visualizations to create subunits of similar exposure rate within the Chinle Formation, which contains multiple lithologies and by grouping alluvial units by drainage basin rather than age. •Methods for making predictive high resolution gamma-ray background maps were tested.•Successful maps were composed of background radiation units based on bedrock units.•Background unit properties calculated from geochemical data were not successful.•Background unit properties calculated from NURE survey data were successful.•Maps segmented by ASTER imagery were also evaluated.
This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions to background radiation for the purpose of emergency response and homeland security operations. The forward models are based on geologic maps and remote sensing multi-spectral imagery combined with two different sources of data: 1) bedrock geochemical data (uranium, potassium and thorium concentrations) collected from national databases, the scientific literature and private companies, and 2) the low spatial resolution NURE (National Uranium Resource Evaluation) aerial gamma-ray survey. The study area near Cameron, Arizona, is located in an arid region with minimal vegetation and, due to the presence of abandoned uranium mines, was the subject of a previous high resolution gamma-ray survey. We found that, in general, geologic map units form a good basis for predicting the geographic distribution of the gamma-ray background. Predictions of background gamma-radiation levels based on bedrock geochemical analyses were not as successful as those based on the NURE aerial survey data sorted by geologic unit. The less successful result of the bedrock geochemical model is most likely due to a number of factors including the need to take into account the evolution of soil geochemistry during chemical weathering and the influence of aeolian addition. Refinements to the forward models were made using ASTER visualizations to create subunits of similar exposure rate within the Chinle Formation, which contains multiple lithologies and by grouping alluvial units by drainage basin rather than age.
Here, this study compares high-resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability to predict variations in natural background radiation levels should prove useful for those engaged in measuring anthropogenic contributions to background radiation for the purpose of emergency response and homeland security operations. The forward models are based on geologic maps and remote sensing multi-spectral imagery combined with two different sources of data: 1) bedrock geochemical data (uranium, potassium and thorium concentrations) collected from national databases, the scientific literature and private companies, and 2) the low spatial resolution NURE (National Uranium Resource Evaluation) aerial gamma-ray survey. The study area near Cameron, Arizona, is located in an arid region with minimal vegetation and, due to the presence of abandoned uranium mines, was the subject of a previous high resolution gamma-ray survey. We found that, in general, geologic map units form a good basis for predicting the geographic distribution of the gamma-ray background. Predictions of background gamma-radiation levels based on bedrock geochemical analyses were not as successful as those based on the NURE aerial survey data sorted by geologic unit. The less successful result of the bedrock geochemical model is most likely due to a number of factors including the need to take into account the evolution of soil geochemistry during chemical weathering and the influence of aeolian addition. Refinements to the forward models were made using ASTER visualizations to create subunits of similar exposure rate within the Chinle Formation, which contains multiple lithologies and by grouping alluvial units by drainage basin rather than age.
Author Haber, Daniel A.
Malchow, Russell L.
Marsac, Kara E.
Hausrath, Elisabeth M.
Adcock, Christopher T.
Burnley, Pamela C.
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Issue C
Keywords Geology
Gamma-ray
Airborne
Predictive model
Radioactivity
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Snippet This study compares high resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The ability...
Here, this study compares high-resolution forward models of natural gamma-ray background with that measured by high resolution aerial gamma-ray surveys. The...
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SubjectTerms Advanced Spaceborne Thermal Emission and Reflection Radiometer
Airborne
arid zones
Arizona
Background Radiation
bedrock
case studies
gamma radiation
Gamma Rays
Gamma-ray
geochemistry
geographical distribution
Geology
GEOSCIENCES
Mining
Models, Chemical
multispectral imagery
NUCLEAR PHYSICS AND RADIATION PHYSICS
potassium
prediction
Predictive model
private enterprises
Radiation Monitoring
Radioactivity
remote sensing
soil formation
Soil Pollutants, Radioactive - analysis
surveys
thorium
Thorium - analysis
uranium
Uranium - analysis
vegetation
watersheds
weathering
Title Modeling background radiation using geochemical data: A case study in and around Cameron, Arizona
URI https://dx.doi.org/10.1016/j.jenvrad.2016.07.012
https://www.ncbi.nlm.nih.gov/pubmed/27640123
https://www.proquest.com/docview/1836627942
https://www.osti.gov/biblio/1325309
Volume 165
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