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 in | Journal of environmental radioactivity Vol. 165; no. C; pp. 68 - 85 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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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. |
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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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CitedBy_id | crossref_primary_10_1016_j_radphyschem_2021_109589 crossref_primary_10_1007_s13762_022_04054_6 crossref_primary_10_1016_j_net_2024_11_044 crossref_primary_10_1007_s10653_024_01963_y crossref_primary_10_1016_j_jenvrad_2017_01_020 crossref_primary_10_1016_j_jenvrad_2019_106038 crossref_primary_10_1007_s12040_019_1166_x crossref_primary_10_1016_j_jenvrad_2020_106338 |
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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 |
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