Karl J Ellefsen
Karl Ellefsen is an Emeritus with the Geology, Geophysics, and Geochemistry Science Center.
Science and Products
Distribution of Fibrous Erionite in the United States and Implications For Human Health
Fibrous erionite, a zeolite mineral, has been designated as a human carcinogen by the World Health Organization and is believed to be the cause of extraordinarily high rates of malignant mesothelioma and other asbestos - related diseases in several villages in Central Turkey. A recent study by the University of Hawaii in collaboration with the U. S. Environmental Protection Agency in Dunn County,
Bayesian modeling of NURE airborne radiometric data for the conterminous United States: predictions and grids
This data release includes estimates of potassium (K), equivalent uranium (eU), and equivalent thorium (eTh) for the conterminous United States derived from the U.S. Geological Survey's national airborne radiometric data compilation (Duval and others, 2005). Airborne gamma ray spectrometry (AGRS) measures the gamma-rays that are emitted from naturally occurring radioactive isotopes found in rocks
Data for generating statistical maps of soil lanthanum concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of lanthanum in the soil C horizon of the conterminous United States (Smith and others, 2013). The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent
Data for generating statistical maps of soil lithium concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of lithium in the soil C horizon of the conterminous United States. The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent mean for the concentration
Data for generating statistical maps of soil cobalt concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of cobalt in the soil C horizon of the conterminous United States (Smith and others, 2013). The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent me
Selected Data from Preliminary Report on the Timmins-Kirkland Lake Area Gold Deposits File
Data on gold deposits are extracted from an existing publication to enable analysis. The data comprise selected portions of a data set that are published by C.J. Hodgson in "Preliminary Report on the Timmins-Kirkland Lake Area Gold Deposits File," which is available online as a digital image of a report. As an image, the data set cannot be analyzed. Consequently, selected portions of the data set
Titanium concentrations in stream sediments from the Atlantic Coastal Plain of the southeastern U.S. (1975-1999)
The titanium concentrations were obtained from a data set that is called the "National Geochemical Survey." This data set, as well as its documentation, are available in U.S. Geological Survey Open-File Report 2004-1001 (https://mrdata.usgs.gov/geochem/doc/home.htm). The titanium concentrations were measured in 3,457 samples of stream sediments from the coastal plain of the southeastern United Sta
Filter Total Items: 64
Evaluation of the analytical methods used to determine the elemental concentrations found in the stream geochemical dataset compiled for Alaska
A recent U.S. Geological Survey data compilation of stream-sediment geochemistry for Alaska contains decades of analyses collected under numerous Federal and State programs. The compiled data were determined by various analytical methods. Some samples were reanalyzed by a different analytical method than the original, resulting in some elements having concentrations reported by multiple analytical
Authors
Bronwen Wang, Karl J. Ellefsen, Matthew Granitto, Karen D. Kelley, Susan M. Karl, George N. D. Case, Douglas C. Kreiner, Courtney L. Amundson
User guide to the bayesian modeling of non-stationary, univariate, spatial data using R language package BMNUS
Bayesian modeling of non-stationary, univariate, spatial data is performed using the R-language package BMNUS. A unique advantage of this package is that it can map the mean, standard deviation, quantiles, and probability of exceeding a specified value. The package includes several R-language classes that prepare the data for the modeling, help select suitable model parameters, and help analyze th
Authors
Karl J. Ellefsen, Margaret A. Goldman, Bradley S. Van Gosen
Bayesian modeling of non-stationary, univariate, spatial data for the Earth sciences
Some Earth science data, such as geochemical measurements of element concentrations, are non-stationary—the mean and the standard deviation vary spatially. It is important to estimate the spatial variations in both statistics because such information is indicative of geological and other Earth processes. To this end, an estimation method is formulated as a Bayesian hierarchical model. The method r
Authors
Karl J. Ellefsen, Bradley S. Van Gosen
Geochemical and mineralogical maps, with interpretation, for soils of the conterminous United States
Between 2007 and 2013, the U.S. Geological Survey conducted a low-density (1 site per 1,600 square kilometers, 4,857 sites) geochemical and mineralogical survey of soils in the conterminous United States. The sampling protocol for the national-scale survey included, at each site, a sample from a depth of 0 to 5 centimeters, a composite of the soil A horizon, and a deeper sample from the soil C hor
Authors
David B. Smith, Federico Solano, Laurel G. Woodruff, William F. Cannon, Karl J. Ellefsen
Effect of size-biased sampling on resource predictions from the three-part method for quantitative mineral resource assessment—A case study of the gold mines in the Timmins-Kirkland Lake area of the Abitibi greenstone belt, Canada:
The three-part method for quantitative mineral resource assessment is used by the U.S. Geological Survey to predict, within a specified assessment area, the number of undiscovered mineral deposits and the quantity of mineral resources in those undiscovered deposits. The effects of size-biased sampling on such predictions are evaluated in a case study that involves gold mines from the Timmins-Kirkl
Authors
Karl J. Ellefsen
Shear-wave seismic reflection studies of unconsolidated sediments in the near surface
We have successfully applied of SH-wave seismic reflection methods to two different near-surface problems targeting unconsolidated sediments. At the former Fort Ord, where the water table is approximately 30m deep, we imaged aeolian and marine aquifer and aquitard stratigraphy to a depth of approximately 80m. We identified reflections from sand/clay and sand/silt interfaces and we mapped these int
Authors
Karl J. Ellefsen, Seth S. Haines
Titanium mineral resources in heavy-mineral sands in the Atlantic coastal plain of the southeastern United States
This study examined titanium distribution in the Atlantic Coastal Plain of the southeastern United States; the titanium is found in heavy-mineral sands that include the minerals ilmenite (Fe2+TiO3), rutile (TiO2), or leucoxene (an alteration product of ilmenite). Deposits of heavy-mineral sands in ancient and modern coastal plains are a significant feedstock source for the titanium dioxide pigment
Authors
Bradley S. Van Gosen, Karl J. Ellefsen
Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches
We combined geophysical, geochemical, mineralogical, and geological data to evaluate the regional presence of rare earth element (REE)−bearing minerals in heavy mineral sand deposits of the southeastern U.S. Coastal Plain. We also analyzed regional differences in these data to determine probable sedimentary provenance. Analyses of heavy mineral separates covering the region show strong correlation
Authors
Anjana K. Shah, Carleton R. Bern, Bradley S. Van Gosen, David L. Daniels, William Benzel, James R. Budahn, Karl J. Ellefsen, Adam T. Karst, Richard Davis
Probability calculations for three-part mineral resource assessments
Three-part mineral resource assessment is a methodology for predicting, in a specified geographic region, both the number of undiscovered mineral deposits and the amount of mineral resources in those deposits. These predictions are based on probability calculations that are performed with computer software that is newly implemented. Compared to the previous implementation, the new implementation i
Authors
Karl J. Ellefsen
User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments
MapMark4 is a software package that implements the probability calculations in three-part mineral resource assessments. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of this user’s guide are bundled together in R’s unit of shareable code, which is called a “package.” This user’s guide includes step-by-s
Authors
Karl J. Ellefsen
Feasibility study for the quantitative assessment of mineral resources in asteroids
This study was undertaken to determine if the U.S. Geological Survey’s process for conducting mineral resource assessments on Earth can be applied to asteroids. Successful completion of the assessment, using water and iron resources to test the workflow, has resulted in identification of the minimal adjustments required to conduct full resource assessments beyond Earth. We also identify the types
Authors
Laszlo P. Keszthelyi, Justin Hagerty, Amanda Bowers, Karl J. Ellefsen, Ian Ridley, Trude King, David Trilling, Nicholas Moskovitz, Will Grundy
Coastal deposits of heavy mineral sands; Global significance and US resources
Ancient and modern coastal deposits of heavy mineral sands (HMS) are the principal source of several heavy industrial minerals, with mining and processing operations on every continent except Antarctica. For example, HMS deposits are the main source of titanium feedstock for the titanium dioxide (TiO2) pigments industry, obtained from the minerals ilmenite (Fe2+TiO3), rutile (TiO2) and leucoxene (
Authors
Bradley S. Van Gosen, Donald I. Bleiwas, George M. Bedinger, Karl J. Ellefsen, Anjana K. Shah
Software for Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data (Program BMRGSU)
BMRGSU is software developed by the U.S. Geological Survey for Bayesian mapping of regionally-grouped, sparse, univariate, Earth-science data. This software implements an algorithm that smooths the estimated property across regions so that the deleterious effects of sparse data are mitigated. The algorithm can account for measurements that are censored, it can process multiple datasets with differ
Software for SIR 'Effect of Data Pooling on Predictions From the Three-Part Method for Quantitative Mineral Resource Assessment-An Investigation of a Previous U.S. Geological Survey Assessment'
The Three-Part Method for Quantitative Mineral Resource Assessment has been used by the USGS to predict mineral resources since at least 1975. These predictions use pooled data, and the effects of the pooling on the predictions is investigated and reported in the forthcoming USGS publication. The calculations and figures for this report are performed with software that will be permanently stored i
Science and Products
Distribution of Fibrous Erionite in the United States and Implications For Human Health
Fibrous erionite, a zeolite mineral, has been designated as a human carcinogen by the World Health Organization and is believed to be the cause of extraordinarily high rates of malignant mesothelioma and other asbestos - related diseases in several villages in Central Turkey. A recent study by the University of Hawaii in collaboration with the U. S. Environmental Protection Agency in Dunn County,
Bayesian modeling of NURE airborne radiometric data for the conterminous United States: predictions and grids
This data release includes estimates of potassium (K), equivalent uranium (eU), and equivalent thorium (eTh) for the conterminous United States derived from the U.S. Geological Survey's national airborne radiometric data compilation (Duval and others, 2005). Airborne gamma ray spectrometry (AGRS) measures the gamma-rays that are emitted from naturally occurring radioactive isotopes found in rocks
Data for generating statistical maps of soil lanthanum concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of lanthanum in the soil C horizon of the conterminous United States (Smith and others, 2013). The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent
Data for generating statistical maps of soil lithium concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of lithium in the soil C horizon of the conterminous United States. The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent mean for the concentration
Data for generating statistical maps of soil cobalt concentrations in the conterminous United States
The product data are six statistics that were estimated for the chemical concentration of cobalt in the soil C horizon of the conterminous United States (Smith and others, 2013). The estimates are made at 9998 locations that are uniformly distributed across the conterminous United States. The six statistics are the mean for the isometric log-ratio transform of the concentrations, the equivalent me
Selected Data from Preliminary Report on the Timmins-Kirkland Lake Area Gold Deposits File
Data on gold deposits are extracted from an existing publication to enable analysis. The data comprise selected portions of a data set that are published by C.J. Hodgson in "Preliminary Report on the Timmins-Kirkland Lake Area Gold Deposits File," which is available online as a digital image of a report. As an image, the data set cannot be analyzed. Consequently, selected portions of the data set
Titanium concentrations in stream sediments from the Atlantic Coastal Plain of the southeastern U.S. (1975-1999)
The titanium concentrations were obtained from a data set that is called the "National Geochemical Survey." This data set, as well as its documentation, are available in U.S. Geological Survey Open-File Report 2004-1001 (https://mrdata.usgs.gov/geochem/doc/home.htm). The titanium concentrations were measured in 3,457 samples of stream sediments from the coastal plain of the southeastern United Sta
Filter Total Items: 64
Evaluation of the analytical methods used to determine the elemental concentrations found in the stream geochemical dataset compiled for Alaska
A recent U.S. Geological Survey data compilation of stream-sediment geochemistry for Alaska contains decades of analyses collected under numerous Federal and State programs. The compiled data were determined by various analytical methods. Some samples were reanalyzed by a different analytical method than the original, resulting in some elements having concentrations reported by multiple analytical
Authors
Bronwen Wang, Karl J. Ellefsen, Matthew Granitto, Karen D. Kelley, Susan M. Karl, George N. D. Case, Douglas C. Kreiner, Courtney L. Amundson
User guide to the bayesian modeling of non-stationary, univariate, spatial data using R language package BMNUS
Bayesian modeling of non-stationary, univariate, spatial data is performed using the R-language package BMNUS. A unique advantage of this package is that it can map the mean, standard deviation, quantiles, and probability of exceeding a specified value. The package includes several R-language classes that prepare the data for the modeling, help select suitable model parameters, and help analyze th
Authors
Karl J. Ellefsen, Margaret A. Goldman, Bradley S. Van Gosen
Bayesian modeling of non-stationary, univariate, spatial data for the Earth sciences
Some Earth science data, such as geochemical measurements of element concentrations, are non-stationary—the mean and the standard deviation vary spatially. It is important to estimate the spatial variations in both statistics because such information is indicative of geological and other Earth processes. To this end, an estimation method is formulated as a Bayesian hierarchical model. The method r
Authors
Karl J. Ellefsen, Bradley S. Van Gosen
Geochemical and mineralogical maps, with interpretation, for soils of the conterminous United States
Between 2007 and 2013, the U.S. Geological Survey conducted a low-density (1 site per 1,600 square kilometers, 4,857 sites) geochemical and mineralogical survey of soils in the conterminous United States. The sampling protocol for the national-scale survey included, at each site, a sample from a depth of 0 to 5 centimeters, a composite of the soil A horizon, and a deeper sample from the soil C hor
Authors
David B. Smith, Federico Solano, Laurel G. Woodruff, William F. Cannon, Karl J. Ellefsen
Effect of size-biased sampling on resource predictions from the three-part method for quantitative mineral resource assessment—A case study of the gold mines in the Timmins-Kirkland Lake area of the Abitibi greenstone belt, Canada:
The three-part method for quantitative mineral resource assessment is used by the U.S. Geological Survey to predict, within a specified assessment area, the number of undiscovered mineral deposits and the quantity of mineral resources in those undiscovered deposits. The effects of size-biased sampling on such predictions are evaluated in a case study that involves gold mines from the Timmins-Kirkl
Authors
Karl J. Ellefsen
Shear-wave seismic reflection studies of unconsolidated sediments in the near surface
We have successfully applied of SH-wave seismic reflection methods to two different near-surface problems targeting unconsolidated sediments. At the former Fort Ord, where the water table is approximately 30m deep, we imaged aeolian and marine aquifer and aquitard stratigraphy to a depth of approximately 80m. We identified reflections from sand/clay and sand/silt interfaces and we mapped these int
Authors
Karl J. Ellefsen, Seth S. Haines
Titanium mineral resources in heavy-mineral sands in the Atlantic coastal plain of the southeastern United States
This study examined titanium distribution in the Atlantic Coastal Plain of the southeastern United States; the titanium is found in heavy-mineral sands that include the minerals ilmenite (Fe2+TiO3), rutile (TiO2), or leucoxene (an alteration product of ilmenite). Deposits of heavy-mineral sands in ancient and modern coastal plains are a significant feedstock source for the titanium dioxide pigment
Authors
Bradley S. Van Gosen, Karl J. Ellefsen
Rare earth mineral potential in the southeastern U.S. Coastal Plain from integrated geophysical, geochemical, and geological approaches
We combined geophysical, geochemical, mineralogical, and geological data to evaluate the regional presence of rare earth element (REE)−bearing minerals in heavy mineral sand deposits of the southeastern U.S. Coastal Plain. We also analyzed regional differences in these data to determine probable sedimentary provenance. Analyses of heavy mineral separates covering the region show strong correlation
Authors
Anjana K. Shah, Carleton R. Bern, Bradley S. Van Gosen, David L. Daniels, William Benzel, James R. Budahn, Karl J. Ellefsen, Adam T. Karst, Richard Davis
Probability calculations for three-part mineral resource assessments
Three-part mineral resource assessment is a methodology for predicting, in a specified geographic region, both the number of undiscovered mineral deposits and the amount of mineral resources in those deposits. These predictions are based on probability calculations that are performed with computer software that is newly implemented. Compared to the previous implementation, the new implementation i
Authors
Karl J. Ellefsen
User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments
MapMark4 is a software package that implements the probability calculations in three-part mineral resource assessments. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of this user’s guide are bundled together in R’s unit of shareable code, which is called a “package.” This user’s guide includes step-by-s
Authors
Karl J. Ellefsen
Feasibility study for the quantitative assessment of mineral resources in asteroids
This study was undertaken to determine if the U.S. Geological Survey’s process for conducting mineral resource assessments on Earth can be applied to asteroids. Successful completion of the assessment, using water and iron resources to test the workflow, has resulted in identification of the minimal adjustments required to conduct full resource assessments beyond Earth. We also identify the types
Authors
Laszlo P. Keszthelyi, Justin Hagerty, Amanda Bowers, Karl J. Ellefsen, Ian Ridley, Trude King, David Trilling, Nicholas Moskovitz, Will Grundy
Coastal deposits of heavy mineral sands; Global significance and US resources
Ancient and modern coastal deposits of heavy mineral sands (HMS) are the principal source of several heavy industrial minerals, with mining and processing operations on every continent except Antarctica. For example, HMS deposits are the main source of titanium feedstock for the titanium dioxide (TiO2) pigments industry, obtained from the minerals ilmenite (Fe2+TiO3), rutile (TiO2) and leucoxene (
Authors
Bradley S. Van Gosen, Donald I. Bleiwas, George M. Bedinger, Karl J. Ellefsen, Anjana K. Shah
Software for Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data (Program BMRGSU)
BMRGSU is software developed by the U.S. Geological Survey for Bayesian mapping of regionally-grouped, sparse, univariate, Earth-science data. This software implements an algorithm that smooths the estimated property across regions so that the deleterious effects of sparse data are mitigated. The algorithm can account for measurements that are censored, it can process multiple datasets with differ
Software for SIR 'Effect of Data Pooling on Predictions From the Three-Part Method for Quantitative Mineral Resource Assessment-An Investigation of a Previous U.S. Geological Survey Assessment'
The Three-Part Method for Quantitative Mineral Resource Assessment has been used by the USGS to predict mineral resources since at least 1975. These predictions use pooled data, and the effects of the pooling on the predictions is investigated and reported in the forthcoming USGS publication. The calculations and figures for this report are performed with software that will be permanently stored i