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At least 19 recordsLinked to original sources
USGS1987

Overview of surface-water quality in Ohio's coal regions

This report is designed to provide the nontechnical audience with some of the results of an 'Assessment of Water Quality in Streams Draining Coal-Producing Areas in Ohio,' by Christine L. Pfaff and others (published by the U.S. Geological Survey in 1981). The purpose of the assessment was to document the occurrence of certain chemical constituents in streams in Ohio's coal region and determine to what extent the presence of these constituents was related to mining. Ohio's most productive coal seams are associated with the Allegheny and Monongahela Formation of Pennsylvanian age. These coals were mined by underground methods very early in Ohio's history. Underground mining continues in the state today; however, surface mining now produces significantly more coal. Acid mine drainage from unreclaimed surface and underground mines has affected surface-water quality in Ohio for many years, and recently has led to establishment of reclamation programs by State and Federal agencies. In their assessment of Ohio's coal region, Pfaff and others sampled 150 sites in small watersheds underlain by the Allegheny and the Monogahela Formations. Each site represented only one of four land-use types (active-mine, unmined, abandoned-mine, or reclaimed). Statistical analysis of data from the unmined, abandoned-mine, and reclaimed sites showed that there were significant differences in pH, specific conductance, alkalinity, and concentrations of sulfate and aluminum among abandoned-mine and unmined sites. Reclaimed sites had average pH values and aluminum concentrations similar to those unmined sites. Average specific conductance and sulfate concentrations were about the same for reclaimed abandoned-mine sites, but were significantly lower at unmined sites; specific conductance and sulfate concentration, in fact, proved to be reliable indicators of basins that had been disturbed by mining. Alkalinity was significantly different for all three land uses, the highest values being found at reclaimed sites. The relationship revealed by this study may be useful in designing future water-quality sampling programs in Ohio's coal region.

Water-Resources Investigations Report↗
USGS2020

Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity

Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.

Statistical Analysis and Data Mining↗
USGS1987

Statistical analysis of surface-water-quality data in and near the coal-mining region of southwestern Indiana, 1957-80

The Surface Mining Control and Reclamation Act of 1977 requires that applications for coal-mining permits contain information about the water quality of streams at and near a proposed mine. To meet this need for information, streamflow, specific conductance, pH, and concentrations of total alkalinity, sulfate, dissolved solids, suspended solids, total iron, and total manganese at 37 stations were analyzed to determine the spatial and seasonal variations in water quality and to develop equations for predicting water quality. The season of lowest median streamflow was related to the size of the drainage area. Median streamflow was least during fall at 15 of 16 stations having drainage areas greater than 1,000 square miles but was least during summer at 17 of 21 stations having drainage areas less than 1,000 square miles. In general, the season of lowest median specific conductance occurred during the season of highest streamflow except at stations on the Wabash River. Median specific conductance was least during summer at 9 of 9 stations on the Wabash River, but was least during winter or spring (the seasons of highest streamflow) at 27 of the remaining 28 stations. Linear, inverse, semilog, log-log, and hyperbolic regression models were used to investigate the functional relations between water-quality characteristics and streamflow. Of 186 relations investigated, 143 were statistically significant. Specific conductance and concentrations of total alkalinity and sulfate were negatively related to streamflow at all stations except for a positive relation between total alkalinity concentration and streamflow at Patoka River near Princeton. Concentrations of total alkalinity and sulfate were positively related to specific conductance at all stations except for a negative relation at Patoka River near Princeton and for a positive and negative relation at Patoka River at Jasper. Most of these relations are good, have small confidence intervals, and will give reliable predictions of the water-quality variables listed above. The poorest relations are typically at stations in the Patoka River watershed. Suspended-solids concentration was positively related to streamflow at all but two stations on the Patoka River. These relations are poor, have large confidence intervals, and will give less reliable predictions of suspended-solids concentration. Predictive equations for the regional relations between dissolved-solids concentration and specific conductance and between sulfate concentration and specific conductance, and the seasonal patterns of water quality, are probably valid for the coal-mining regions of Illinois and western Kentucky.

Indiana↗
USGS2023

Groundwater quality in abandoned underground coal mine aquifers across West Virginia

Abandoned underground coal mine aquifers cover a large part of West Virginia and could supply substantial quantities of water for agricultural, industrial, residential, and public use. Several Federal, State, and academic institutions have studied the availability and quality of water stored in abandoned underground coal mine aquifers for a variety of applications, such as economic development, geothermal energy, aquaculture, and wastewater disposal. However, the spatial and stratigraphic controls on water quality produced from abandoned underground coal mine aquifers are still poorly constrained on a state-wide basis. In response to these knowledge gaps, the U.S. Geological Survey initiated a study, in cooperation with the West Virginia Department of Environmental Protection, to understand the applicability of using existing secondary source data for understanding water quality in abandoned underground coal mine aquifers across the State. Results from the calculation of net alkalinity indicated that Upper Pennsylvanian coal beds primarily produce net acidic waters and Lower Pennsylvanian coal beds primarily produce net alkaline waters. Multivariate statistical analysis of elemental data supports the conclusion that abandoned underground coal mine aquifers in the northern part of the State generally produce poor water quality and abandoned underground coal mine aquifers in southern West Virginia primarily produce good water quality. These results substantiate the potential benefits of leveraging abandoned underground coal mine aquifers as a multifaceted resource in West Virginia and can be used as a reconnaissance tool for water managers to characterize abandoned underground coal mine aquifers on a local scale.

West Virginia↗
USGS2023

Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel

Draining mine tunnels contribute contaminants to groundwater and surface water, but remediation strategies may be hindered as hydrogeologic characterization and modeling of these heterogeneous features generally relies on sparse data sets. The Captain Jack mine site in Colorado, USA, presents a unique data set allowing for temporal evaluation of groundwater connectivity in the vicinity of an abandoned mine, where a hydraulic bulkhead is impounding water within the mine workings. This study applied statistical analysis of system pressure responses to bulkheading and used an analytic-element modeling approach to characterize heterogeneity and groundwater flow. Groundwater-level elevation data collected over a period of 4 years, both prior to and after bulkheading, indicate that the mine workings act as a sink to the local groundwater system. Despite groundwater flow being generally oriented towards the mine workings, there are also large vertical and horizontal hydraulic gradients which persist through time. Although the groundwater system is highly compartmentalized, statistical analysis using Kendall’s Tau indicates correlations between hydraulic head changes in the mine workings and several wells completed in crystalline bedrock, indicating the influence of fracture flow. An analytic-element model was parameterized to account for uncertainty in hydraulic conductivity, recharge, and discharge. Model results reproduced the range of observed hydraulic heads in the mine workings and adjacent igneous dikes but failed to closely simulate hydraulic heads in several wells located distal from the mine workings in granitic bedrock. The modeling approach shows potential promise, however, for conducting preliminary modeling to guide data collection at other similar mine sites.

Colorado↗
USGS2025

Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed

Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.

Colorado↗
USGS2014

Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida

The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area. Historical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture. On the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest. Overall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response. An important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.

Florida↗
USGS2006

Mining claim activity on federal land in the contiguous United States, 1976 through 2004

Statistical compilations of mining claim activity on Federal Land derived from the Bureau of Land Management's LR2000 database have been published by the U.S Geological Survey. This report updates Causey (2005) by adding statistics for an additional year of mining claim records, incorporating any corrections in older data done by BLM, adding a Public Land Survey spatial database for South Dakota, and improving correlation of the statistics to spatial databases in Washington and Nevada. The statistics compiled from the LR2000 database are counts of number of active mining claims in a section each year from 1976 to 2004 for all states within the contiguous United States. Claims are broken down by lode and placer types and a dataset is provided summarizing all claims including millsite and tunnel-site claims. One table presents data by case type, case status, and number of claims in a section. This report includes a spatial database for each state in which mining claims were recorded. A field is present in both datasets that allows the statistical data to be joined to the spatial databases so that spatial displays and analysis can be done using appropriate software. The data show how mining claim activity has changed in intensity, space, and time. Variations can be examined on a state, as well as a national level. The data are tied to a section of land, approximately 640 acres, which allows it to be used at regional, as well as local scale. It is restricted in that it only encompasses Federal land.

Arizona, Arkansas, California, Colorado, Florida, ↗
USGS1989

Geochemical processes controlling selenium in ground water after mining, Powder River Basin, Wyoming, U.S.A.

Geochemical data for samples of overburden from three mines in the Powder River Basin indicate a statistically significant (0.01 confidence level) positive correlation ( r = 0.74) between Se and organic C. Results of factor analysis with varimax rotation on the major and trace element data from the rock samples indicate large (>50) varimax loadings for Se in two of the three factors. In Factor 1, the association of Se with constituents common to detrital grains indicates that water transporting the detrital particles into the Powder River Basin also carried dissolved Se. The large (>50) varimax loadings of Se and organic C in Factor 2 probably are due to the organic affinities characteristic of Se. Dissolved Se concentrations in water samples collected at one coal mine are directly related to the dissolved organic C concentrations. Hydrophilic acid concentrations in the water samples from the mine ranged from 35 to 43% of the total dissolved organic C, and hydrophobic acid concentrations ranged from 40 to 49% of the total dissolved organic C. The largest dissolved organic C concentrations in water from the same mine (34–302 mg/l), coupled with the large proportion of acidic components, may saturate adsorption sites on geothite and similar minerals that comprise the aquifer material, thus decreasing the extent of selenite (SeO 3 2− ) adsorption as a sink for Se as the redox state of ground water decreases.

Wyoming↗
USGS2007

Mining Claim Activity on Federal Land in the United States

Several statistical compilations of mining claim activity on Federal land derived from the Bureau of Land Management's LR2000 database have previously been published by the U.S Geological Survey (USGS). The work in the 1990s did not include Arkansas or Florida. None of the previous reports included Alaska because it is stored in a separate database (Alaska Land Information System) and is in a different format. This report includes data for all states for which there are Federal mining claim records, beginning in 1976 and continuing to the present. The intent is to update the spatial and statistical data associated with this report on an annual basis, beginning with 2005 data. The statistics compiled from the databases are counts of the number of active mining claims in a section of land each year from 1976 to the present for all states within the United States. Claim statistics are subset by lode and placer types, as well as a dataset summarizing all claims including mill site and tunnel site claims. One table presents data by case type, case status, and number of claims in a section. This report includes a spatial database for each state in which mining claims were recorded, except North Dakota, which only has had two claims. A field is present that allows the statistical data to be joined to the spatial databases so that spatial displays and analysis can be done by using appropriate geographic information system (GIS) software. The data show how mining claim activity has changed in intensity, space, and time. Variations can be examined on a state, as well as a national level. The data are tied to a section of land, approximately 640 acres, which allows it to be used at regional, as well as local scale. The data only pertain to Federal land and mineral estate that was open to mining claim location at the time the claims were staked.

Data Series↗
USGS2021

Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis

Coal mine gas originates from the gas emission zone (GEZ) of the mine, as well as the longwall face and pillars. Gas emissions are controlled directly at the sources using horizontal or vertical boreholes drilled from surface or from the entries in advance of mining, or it is captured from the fractured and caved zones (gob) using ventholes during mining. The rest of the gas, especially that gas that originates from the longwall face and caved zone, mixes with the ventilation air and travels through bleeder and return entries before being exhausted to atmosphere from air shafts. Although the gas associated with mining mostly focuses on methane, the gas is not pure methane but is a mixture (where both the components and their quantities vary depending on the sampling location). Understanding the evolution of the composition of the gas from source to different sampling and evaluation points in mines using proper statistical analysis and interpretation methods can lead to better designed degasification and ventilation systems and the selection of the most adequate utilization method for generating energy from the gas. In this work, we present the results of compositional data analysis (CoDa) of gases sampled at different locations in a longwall mine operating in Pennsylvanian coal-bearing strata in the Northern Appalachian coal basin. Sampling locations were from accessible parts of the bleeder entries, returns, bleeder evaluation points and shafts within the mine, and also from gob gas ventholes (GGV) and coal degasification boreholes drilled in the panel areas. In addition, desorbed gas samples from seams that are important for the mine were included in the analyses for comparison. The compositional data analysis showed that the gas composition shifts based on the sampling location, putting in-mine and pure coalbed gases on the opposite ends. Removal of air from the samples did not change this observation suggesting that oxygen is depleted especially for in-mine samples, which is due to oxidation. Results also suggested that desorbed gas samples may not represent the composition of the coal seam gas.

International Journal of Coal Geology↗
USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2001

Standard reference water samples for rare earth element determinations

Standard reference water samples (SRWS) were collected from two mine sites, one near Ophir, CO, USA and the other near Redding, CA, USA. The samples were filtered, preserved, and analyzed for rare earth element (REE) concentrations (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) by inductively coupled plasma-mass spectrometry (ICP-MS). These two samples were acid mine waters with elevated concentrations of REEs (0.45–161 μg/l). Seventeen international laboratories participated in a ‘round-robin’ chemical analysis program, which made it possible to evaluate the data by robust statistical procedures that are insensitive to outliers. The resulting most probable values are reported. Ten to 15 of the participants also reported values for Ba, Y, and Sc. Field parameters, major ion, and other trace element concentrations, not subject to statistical evaluation, are provided.

Applied Geochemistry↗
USGS1997

Geochemical modeling of water-rock interactions in mining environments

Geochemical modeling is a powerful tool for evaluating geochemical processes in mining environments. Properly constrained and judiciously applied, modeling can provide valuable insights into processes controlling the release, transport, and fate of contaminants in mine drainage. This chapter contains 1) an overview of geochemical modeling, 2) discussion of the types of models and computer programs used, 3) description of a procedure for screening water analyses for modeling input, and 4) examples of the application of modeling for interpreting geochemical processes in mining environments. Three general strategies in current use to interpret water-rock interactions are statistical analysis, “inverse” modeling, and “forward” modeling. Multivariate correlation analysis, factor analysis, cluster analysis, and other statistical techniques can group water-chemistry data into sets that may relate to hydrogeochemical processes (Drever, 1988; Puckett and Bricker, 1992). In the field of geochemical exploration, statistical analysis is used widely to treat large data sets of rock and sediment chemistry (e.g., Garrett, 1989). No physical or chemical principles are involved directly in these statistical treatments, hence they are not considered further in this chapter. Nevertheless, statistical analysis can be a useful tool in organizing complex geochemical data for interpretation.

Book chapter↗
USGS2015

Shift in Global Tantalum Mine Production, 2000–2014

Introduction Tantalum has a unique set of properties that make it useful in a number of diverse applications. The ability of the metal to store and release electrical energy makes it ideally suited for use in certain types of capacitors that are widely used in modern electronics. Approximately 60 percent of global tantalum consumption is in the electronics industry. The ductility and corrosion resistance of the metal lends itself to application in the chemical processing industry, and its high melting point and high strength retention at elevated temperatures make it an important component of super alloys used in aircraft engines. As a major industrialized nation, the United States is a leading consumer of tantalum and tantalum-containing products. Domestic deposits typically are of low grade, and no tantalum has been recovered from mining activities in the United States since 1959. Consequently, the United States is nearly completely reliant on imports to meet its domestic consumption of tantalum for economic and national security needs. The recovery of tantalum from mine production is economically viable in only a few countries. Although developed countries dominated tantalum mine production in the early 2000s, production today is dominated by countries in the Great Lakes Region of Africa. There is concern that the sales of minerals, including columbite-tantalite or “coltan,” a mineral from which tantalum is derived, have helped finance rebel groups accused of violating human rights as part of the continuing armed conflict in the Democratic Republic of the Congo (DRC) and neighboring countries. These accusations have prompted the passage of legislation in the United States to curb the procurement of these mineral commodities, referred to as “conflict minerals,” from the DRC. Specifically, section 1502 of the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act (Public Law 111–203, 124 Stat. 2213–2218) requires companies that source tantalum, tin, tungsten, and gold (3TG) to perform due diligence on their supply chains to determine if the materials they use originate from the DRC or adjoining countries (defined as sharing a border with the DRC). The DRC, Rwanda, and surrounding countries are not globally significant sources of tin, tungsten, or gold, accounting for only about 2 percent of the mined world supply for each of these elements. The region has, however, evolved to become the world’s largest producer of mined tantalum. A further complication of the production of tantalum stems from the opacity of the tantalum market. Unlike most base and precious metals, tantalum concentrates are not publicly traded through commodities exchanges but are bought and sold through networks of dealers and on contract between producers and consumers, some of whom may not provide accurate statistical data concerning the amounts, origins, and destination of the concentrates. Some price data can be found in trade journals or in other publications; however, there are no recognized official set exchange prices for either concentrate or tantalum metal. Because price is determined by negotiation between buyer and seller, published prices for concentrate are probably not representative of global prices paid for concentrate. The development of a mine-to-market supply-chain analysis is complicated and difficult because many of the industry participants that produce, trade, and consume tantalum do not publish statistical information, contracts are long term between miners and buyers, and much of the industry is vertically integrated. As a result of these and other considerations, tantalum is considered by many to be a “critical” commodity. This fact sheet identifies and addresses the major geographic shifts in the source of mine production of tantalum which have occurred over the past 15 years, some of the factors that drove this shift, and some of the related consequences. One of the activities of the U.S. Geological Survey National Minerals Information Center (USGS-NMIC) is to analyze global supply chains and characterize major components of mineral and material flows from ore extraction through processing to first tier products. These analyses support the core mission of the USGS-NMIC as the Federal entity responsible for the collection, analysis, and dissemination of objective, unbiased, factual information on minerals essential to the U.S. economy and national security.

Fact Sheet↗
USGS2012

Zinc isotope investigation of surface and pore waters in a mountain watershed impacted by acid rock drainage

The pollution of natural waters with metals derived from the oxidation of sulfide minerals like pyrite is a global environmental problem. However, the metal loading pathways and transport mechanisms associated with acid rock drainage reactions are often difficult to characterize using bulk chemical data alone. In this study, we evaluated the use of zinc (Zn) isotopes to complement traditional geochemical tools in the investigation of contaminated waters at the former Waldorf mining site in the Rocky Mountains, Colorado, U.S.A. Geochemical signatures and statistical analysis helped in identifying two primary metal loading pathways at the Waldorf site. The first was characterized by a circumneutral pH, high alkalinity, and high Zn/Cd ratios. The second was characterized by acidic pHs and low Zn/Cd ratios. Zinc isotope signatures in surface water samples collected across the site were remarkably similar (the δ 66 Zn, relative to JMC 3-0749-L, for most samples ranged from 0.20 to 0.30‰ ± 0.09‰ 2σ). This probably suggests that the ultimate source of Zn is consistent across the Waldorf site, regardless of the metal loading pathway. The δ 66 Zn of pore water samples collected within a nearby metal-impacted wetland area, however, were more variable, ranging from 0.20 to 0.80‰ ± 0.09‰ 2σ. Here the Zn isotopes seemed to reflect differences in groundwater flow pathways. However, a host of secondary processes might also have impacted Zn isotopes, including adsorption of Zn onto soil components, complexation of Zn with dissolved organic matter, uptake of Zn into plants, and the precipitation of Zn during the formation of reduced sulfur species. Zinc isotope analysis proved useful in this study; however, the utility of this isotopic tool would improve considerably with the addition of a comprehensive experimental foundation for interpreting the complex isotopic relationships found in soil pore waters.

Colorado↗
USGS1974

Gravel resources, urbanization, and future land use, Front Range Urban Corridor, Colorado

An assessment of gravel needs in Front Range Urban Corridor markets to 2000 A.D., based on forecast population increases and urbanization, indicates that adequate resources to meet anticipated needs are potentially available, if future land use does not preclude their extraction. Because of urban encroachment onto gravel-bearing lands, this basic construction material is in short supply nationally and in the Front Range Urban Corridor. Longer hauls, increased prices, and use of alternatives, especially crushed rock aggregate, have resulted. An analysis of possible sequential land uses following gravel mining indicates that a desirable use is for 'real estate' ponds and small lakes. A method for computing gravel reserves, based on planimeter measurement of area of resource-bearing lands and statistical analysis of reliability of thickness and size distribution data, was developed to compute reserves in individual markets. A discussion of the qualitative 'usability' of these reserves is then made for the individual markets.

Colorado↗
USGS2024

From exploration to production: Understanding the development dynamics of lithium mining projects

Recently, there has been considerable recent controversy whether current and new lithium mines will be able to supply the rapidly growing needs of the electromobility transition. Mineral exploration projects are typically active for many years, and only some become operational mines. From exploration to production, the projects go through several stages of characterisation and evaluation. At each stage, decisions are made by companies and stakeholders to advance, continue or stop the project. This is a complex process, and even projects with very similar geological and technical characteristics may take very different trajectories, depending on external factors such as global market conditions and local regulatory environments. The present study investigates the dynamics of this process for lithium exploration projects. A global database of 397 lithium projects was compiled, covering their progression through major development stages between 2004 and 2022. Ordinal logistic regression was used for the statistical analysis of this data. Different explanatory variables were tested, including economic, geological, technical, and geographic factors, to identify the best predictors for project progress at each development stage. The results suggest an essential role for lithium carbonate prices, and a variable role for other factors at each stage. Critically, the already elapsed lead time and project economics, which are traditionally considered important for the prediction of the start-up of individual mines, do not appear to be relevant in all cases. The results provide important insights into the dynamics of lithium supply and may eventually allow more realistic forecasts to be made for future lithium market dynamics.

Resources Policy↗