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 concentrations, the standard deviation for the isometric log-ratio transform of the concentrations, the probability of exceeding a concentration of 55 milligrams per kilogram, the 0.95 quantile for the isometric log-ratio transform of the concentrations, and the equivalent 0.95 quantile for the concentrations. Each statistic may be used to generate a statistical map that shows an attribute of the distribution of lithium concentration.

Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. The goal of this work was to calculate the total lithium mass in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas using predicted lithium concentrations from a machine-learning model. This research was completed collaboratively between the U.S. Geological Survey and the Arkansas Department of Energy and Environment—Office of the State Geologist. The Smackover Formation is a laterally extensive petroleum and brine system in the Gulf Coast region that includes locally high concentrations of bromide and lithium in southern Arkansas. This data release contains input files, Python scripts, and an R script used to prepare input files, create a random forest (RF) machine-learning model to predict lithium concentrations, and compute uncertainty in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas. This data release also contains a Python script to calculate the total mass of lithium in brines of the Reynolds oolite unit of the Smackover Formation in southern Arkansas based on porosity. Knowledge of data-science and Python and R programming languages is a prerequisite for executing the workflow associated with this product. Users can execute the scripts to prepare input data, train a RF machine-learning model, compute uncertainty, and calculate lithium mass. Explanatory variables used to train the RF model included geologic, geochemical, and temperature data from either published datasets or created and documented in this data release and the associated companion publication (Knierim and others, 2024). See the associated metadata for details. This data release also includes output files (csvs [comma-delimited, plain-text] and rasters [geospatial grids]) of lithium concentration predictions from the RF model, uncertainty ranges, and lithium mass. The depth of prediction of lithium concentration represents the mid-point depth of the Reynolds oolite unit which varies between approximately 3,500 and 11,300 feet deep (below land-surface datum) and 0 and 400 feet thick across the model domain. For a full explanation of methods and results, see the companion manuscript Knierim and others (2024).

The data provided in this upload is summary data from its Demonstration Plant operation at the geothermal power production plants in the Imperial Valley. The data provided is averaged data for the Elmore Plant and the Featherstone Plant. See average brine composition tab for submitted compositional data. Included is both temperature and analytical data (ICP_OES). Provided is the feed to the Simbol Process, post brine treatment and post lithium extraction.

This data release contains data used to develop and apply a model that estimates the level of direct human-impact on selected groundwater wells in the conterminous United States. An extreme gradient boosting model was developed to estimate the probability of minimal human-impact to water levels in groundwater wells. The model uses human-impact evaluations from regional groundwater specialists at the U.S. Geological Survey and predictor variables that are available in the file GW_class_data.csv. The model is included in this data release in the zipped folder named GW_class_model_archive. The model input data that were used to develop the model and apply the model are in the GW_class_data.csv file. The model output resulting from applying the model to groundwater wells throughout the conterminous United States is included as the file GW_class_predictions in the zipped folder named GW_class_model_archive.

This data release provides the descriptions of approximately 20 U.S. sites that include mineral regions, mines, and mineral occurrences (deposits and prospects) that contain enrichments of lithium (Li). This release includes sites that have a contained resource and (or) past production of lithium metal greater than 15,000 metric tons. Sites in this database occur in Arkansas, California, Nevada, North Carolina, and Utah. There are several deposits that were not included in the database because they did not meet the cutoff requirement, and those occur in Arizona, Colorado, the New England area, New Mexico, South Dakota, and Wyoming. In the United States, lithium was first mined from pegmatite orebodies in South Dakota in the late 1800s. The Kings Mountain pegmatite belt of North Carolina also had significant production from pegmatites, and the area may still contain as much as 750 million metric tons (Mt) of ore containing 5 Mt lithium metal (Kesler and others, 2012). In 2018, U.S. production of lithium was restricted to a single lithium-brine mining operation in Nevada. In 2018, the U.S. had a net import reliance as a percentage of apparent consumption of more than 50 percent for lithium (U.S. Geological Survey, 2019). The U.S. is not a significant producer of lithium, so the commodity is mainly imported from Chile and Argentina to meet consumer demand. Lithium is necessary for strategic, consumer, and commercial applications. The primary uses for lithium are in batteries, ceramics, glass, metallurgy, pharmaceuticals, and polymers (U.S. Geological Survey, 2019). Lithium has excellent electrical conductivity and low density (lithium metal will float on water), making it an ideal component for battery manufacturing. Lithium is traded in three primary forms: mineral concentrates, mineral compounds (from brines), and refined metal (electrolysis from lithium chloride). Lithium mineralogy is diverse; it occurs in a variety of pegmatite minerals such as spodumene, lepidolite, amblygonite, and in the clay mineral hectorite. Current global production of lithium is dominated by pegmatite and closed-basin brine deposits, but there are significant resources in lithium-bearing clay minerals, oilfield brines, and geothermal brines (Bradley and others, 2017). The entries and descriptions in the database were derived from published papers, reports, data, and internet documents representing a variety of sources, including geologic and exploration studies described in State, Federal, and industry reports. Resources extracted from older sources might not be compliant with current rules and guidelines in minerals industry standards such as National Instrument 43-101 (NI 43-101) or the Joint Ore Reserves Committee Code (JORC Code). The inclusion of a particular lithium mineral deposit in this database is not meant to imply that the deposit is currently economic. Rather, these deposits were included to capture the characteristics of the larger lithium deposits in the United States, which are diverse in their geology and resource potential. Inclusion of material in the database is for descriptive purposes only and does not imply endorsement by the U.S. Government. The authors welcome additional published information in order to continually update and refine this dataset. Bradley, D.C., Stillings, L.L., Jaskula, B.W., Munk, LeeAnn, and McCauley, A.D., 2017, Lithium, chap. K of Schulz, K.J., DeYoung, J.H., Jr., Seal, R.R., II, and Bradley, D.C., eds., Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply: U.S. Geological Survey Professional Paper 1802, p. K1–K21, https://doi.org/10.3133/pp1802K. Kesler, S.E., Gruber, P.W., Medina, P.A., Keoleian, G.A., Everson, M.P., and Wallington, T.J., 2012, Global lithium resources—relative importance of pegmatite, brine and other deposits: Ore Geology Reviews, v. 48, October ed., p. 55—69. U.S. Geological Survey, 2019, Mineral commodity summaries 2019:

Groundwater chemistry data used for assessing the lead (Pb) solubility potential of untreated groundwater of the United States were compiled from the USGS National Water Information System (NWIS) database for groundwater sites sampled between January 1, 2000 and January 1, 2016. Two datasets were compiled: one dataset having 13,324 groundwater sites was used to assess Pb occurrence in untreated groundwater from different well types and a second dataset having 8,313 groundwater sites was used for geochemical modeling (Tables S1 and S2). In both datasets, only the most recent sample was used when multiple water-quality samples were available for a site. Samples were collected in accordance with protocols established by the USGS National Field Manual and the USGS National Water Quality Assessment (NAWQA) project. Samples for Pb, major ions, and nutrients were filtered with 0.45 µm capsule filters prior to analysis. Pb was screened to a common reporting level of 1 µg/L. Non-detections and detected Pb concentrations that were at or below 1 µg/L were recoded to 0.5 µg/L. Non-detections of Pb above 1 µg/L were removed from the dataset. The censoring of reporting levels mainly affected older samples that used analytical methods with higher detection levels. Table 1 includes groundwater samples from sites used for public-supply (PS), domestic (DOM), monitoring, and for other purposes, such as irrigation, stock, or industrial supply. Groundwater sites are mainly wells, but include some springs. From heretofore drinking water supply (DW) sites will be used to refer to DOM and PS sites as a group. The geochemical modeling dataset was compiled to obtain DW samples with a complete set of measured values of pH, calcium, magnesium, sodium, chloride, and sulfate. Alkalinity, fluoride (F), orthophosphate (OP), and bromide were included when available. DW sites were the primary source of data used to evaluate the solubility of Pb in untreated groundwater. Pb that was measured on the same date as the sample used for geochemical modeling was retained for statistical analysis of model output but was not included as input to the geochemical model. In addition, samples with missing alkalinity values were included when pH was at or below 5.5 and cation-anion balances were within 5%, indicating alkalinity was not a major component of the ion chemistry.

Groundwater chemistry data used for assessing the lead (Pb) solubility potential of untreated groundwater of the United States were compiled from the USGS National Water Information System (NWIS) database for groundwater sites sampled between January 1, 2000 and January 1, 2016. Two datasets were compiled: one dataset having 13,324 groundwater sites was used to assess Pb occurrence in untreated groundwater from different well types and a second dataset having 8,313 groundwater sites was used for geochemical modeling (Tables S1 and S2). In both datasets, only the most recent sample was used when multiple water-quality samples were available for a site. Samples were collected in accordance with protocols established by the USGS National Field Manual and the USGS National Water Quality Assessment (NAWQA) project. Samples for Pb, major ions, and nutrients were filtered with 0.45 µm capsule filters prior to analysis. Pb was screened to a common reporting level of 1 µg/L. Non-detections and detected Pb concentrations that were at or below 1 µg/L were recoded to 0.5 µg/L. Non-detections of Pb above 1 µg/L were removed from the dataset. The censoring of reporting levels mainly affected older samples that used analytical methods with higher detection levels. Table 1 includes groundwater samples from sites used for public-supply (PS), domestic (DOM), monitoring, and for other purposes, such as irrigation, stock, or industrial supply. Groundwater sites are mainly wells, but include some springs. From heretofore drinking water supply (DW) sites will be used to refer to DOM and PS sites as a group. The geochemical modeling dataset was compiled to obtain DW samples with a complete set of measured values of pH, calcium, magnesium, sodium, chloride, and sulfate. Alkalinity, fluoride (F), orthophosphate (OP), and bromide were included when available. DW sites were the primary source of data used to evaluate the solubility of Pb in untreated groundwater. Pb that was measured on the same date as the sample used for geochemical modeling was retained for statistical analysis of model output but was not included as input to the geochemical model. In addition, samples with missing alkalinity values were included when pH was at or below 5.5 and cation-anion balances were within 5%, indicating alkalinity was not a major component of the ion chemistry.

Batch tests of lithium imprinted polymers of variable composition to assess their ability to extract lithium from synthetic brines at T = 45 degC. Initial selectivity data are included