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USGS2025

Characterizing Meteor Crater impact melts through geochemistry and textural analysis

The U.S. Geological Survey Astrogeology Science Center houses the Meteor Crater sample collection, an assemblage of over 2,500 meters of cuttings from 161 drill holes into Meteor Crater’s rim, flanks, and ejecta blanket. We have utilized this unique collection to study the composition and spatial distribution of impact-generated materials from within the ejecta blanket. Meteor Crater has historically been known to have generated only a relatively small amount of impact melt compared to other terrestrial craters of similar size. A detailed compositional and textural dataset of impact-derived melts from this impact can therefore be a useful asset in improving our understanding of crater formation, and in particular impact melt formation. We have characterized 42 impact-melt particles from Meteor Crater using a scanning electron microscope and an electron microprobe for textural and compositional analysis. We analyzed samples from six drill holes in the ejecta blanket, situated to the northwest, southeast, south, and southwest of the crater (ejecta northeast of the crater is devoid of impact melts). Impact melts were collected from drill cuttings at various depths within the ejecta blanket, ranging from a few centimeters below the surface down to ~6.5 meters. Backscattered electron (BSE) images were acquired for each analyzed impact-melt particle. To characterize the various textures and phases present in each impact melt, we also took many detailed BSE images. Our geochemical analyses include full spectral profiles using energy dispersive X-ray spectrometry and well-calibrated wavelength dispersive spectrometry for a number of phases, including minerals (olivine, pyroxene, and so on), pristine glass, and metallic inclusions. The full dataset is available in ScienceBase as a data release (Gullikson and others, 2024), accessible at https://doi.org/10.5066/P9OGAJ8P . Our goal for this Open-File Report is to provide a summary of this immense dataset, details on data collection, descriptions of the different phases observed within impact-melt particles (both geochemically and texturally), and observable trends.

Arizona↗

USGS1976

Detailed investigation of a coastal plain-Piedmont fault contact in northeastern Virginia

A trench across the Dumfries fault of the Stafford fault zone near Stafford, Virginia (see Mixon and Newell, 1976) exposed a high-angle reverse fault juxtaposing Paleozoic Quantico Slate and Cretaceous Potomac Group rocks. A system of subsidiary reverse faults and small scale normal faults disrupt the Coastal Plain strata adjacent to the main fault. Cross-cutting relations and stratigraphic details indicate that the subsidiary faults in the Cretaceous rocks document a history of episodic deformation, in part active during accumulation of the Coastal Plain strata. Slickensides and stereo net analysis of theorientation of subsidiary reverse faults, normal faults, and bedding indicate that, through time, faulting consistently included right lateral separation.

Virginia↗

USGS2024

Volcanic gas monitoring

Introduction As magma rises through the crust, decreasing pressure conditions allow volatiles to exsolve from the magma. These volatiles then migrate upward through the crust, where they can be stored at shallower levels or escape to the atmosphere. Rising magma also heats rock masses beneath volcanic centers, causing water in shallow aquifers and hydrothermal systems to boil and release additional gases and steam (see chapter F , this volume; Ingebritsen and Hurwitz, 2024). The chemistry and quantity of gases that reach the surface during periods of quiescence or volcanic unrest can reveal that gas-rich magma is ascending, crystallizing, or alternatively stalling, with important implications for volcanic hazard (for example, Sutton and others, 1992; Aiuppa and others, 2007, 2021; Werner and others, 2009, 2011, 2012; Moretti and others, 2013; de Moor and others, 2016; Lewicki and others, 2019; Edmonds and others, 2022; Kern and others, 2022; Kunrat and others, 2022). Most volcanoes in Alaska and the western United States are characterized by weak degassing, with one or more low-temperature fumaroles (typically near the local boiling temperature of water) and connect to a deeper and sometimes extensive hydrothermal system (for example, McGee and others, 2001; Symonds and others, 2003a, b). Hydrothermal systems will affect the chemistry of rising gases exsolved from deeper magma (Symonds and others, 2001), including sulfur dioxide (SO 2 ), hydrogen chloride (HCl), and water vapor (for example, Doukas and Gerlach, 1995; Gerlach and others, 1998, 2008; Symonds and others, 2001; Werner and others, 2013). As an example, depending on factors such as temperature, pressure, and oxidation state, rising SO 2 will react with groundwater to form hydrogen sulfide (H 2 S) gas, dissolved sulfate (SO 4 2− ), or elemental sulfur (Christenson, 2000; Symonds and others, 2001; Werner and others, 2008). The reaction and dissolution of SO 2 into shallow groundwater is commonly referred to as scrubbing, and can reduce the likelihood that ascending, degassing magma can be detected. Carbon dioxide, however, in addition to exsolving from magma early in the ascent process, is not easily removed by hydrothermal fluids (Lowenstern, 2001). As scrubbing and other processes take place, the SO 2 /H 2 S, CO 2 /SO 2 , and CO 2 /H 2 S ratios may change. High rates of SO 2 emission indicate that magma has moved to relatively shallow levels in the volcano and that the system has heated up enough to establish dry pathways from depth to the surface. Monitoring multiple gas species and the total output of those species is thereby useful for volcano monitoring during both periods of quiescence, to establish background degassing conditions, and during unrest, when gas geochemistry and emission rates can provide information on changing conditions, such as magma ascent. To provide context for multidisciplinary volcano forecasts, we focus on the following two key required capabilities: (1) characterizing baseline geochemistry and gas discharge from volcanoes and volcanic regions and (2) monitoring changes in gas geochemistry and discharge to inform forecasts of volcanic eruptions and their effects. Sufficient baseline data must be collected to identify and interpret anomalous degassing associated with volcanic unrest (for example, Sorey and others, 1998; Rouwet and others, 2014). Differences in volcano type, baseline degassing rates, local hydrology, and geography (for example, high versus low latitude) will result in a different baseline for each volcano. Volcanoes of any threat level that exhibit one or more degassing phenomena would ideally be monitored by techniques needed to establish baseline degassing data, with the sampling frequency of baseline data dictated by the threat level (table E1). Additional monitoring techniques become necessary during periods of unrest. In general, three of the most important techniques for gas monitoring are (1) direct sampling of fumarole, spring, and soil gases for laboratory geochemical measurements, (2) measurements of the chemical composition of the volcanic plume and emission rates of major gas species (for example, H 2 O, CO 2 , SO 2 , and H 2 S) by satellite, airborne, or ground-based techniques, and (3) measurements of diffuse emissions of CO 2 and other gases through soils. Various methods and instruments may be useful both for baseline studies and during unrest.

Scientific Investigations Report↗

USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗

USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗

USGS2025

Lithium from magma to mine in an early Yellowstone hotspot caldera

Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km 3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.

Idaho, Nevada, Oregon, Wyoming↗

USGS2026

Validating antler- and movement-based estimates of caribou reproduction using video camera collars

Wildlife agencies invest substantial resources in monitoring ungulate reproductive rates given ongoing concerns about population trends and their implications for management. For barren-ground caribou ( Rangifer tarandus ) in the North American Arctic, data on parturition and neonate survival have traditionally been collected using visual observations of antler retention and calf presence from small, fixed-wing aircraft. However, these surveys are weather-dependent, expensive, and dangerous, motivating the development of movement-based approaches that infer reproductive events from global positioning system (GPS) location data. We had the unique opportunity to use video camera collars to validate both antler- and movement-based methods for estimating reproduction in barren-ground caribou, using data from the Porcupine (2018–2023) and Western Arctic (2021, 2023) herds in Alaska, USA, and Yukon, Canada. For the movement-based approaches, we assessed individual-based and population-based methods, which both inferred parturition following a sharp decline in movement and inferred calf loss following a sharp increase in movement. We investigated these approaches using rarified 1-, 2-, 4-, and 8-hour fix intervals. Based on video collar observations, we found that antler retention at the onset of the calving period was highly accurate for predicting parturition (96% accuracy) but became unreliable as calving progressed, as approximately 80% of parturient females shed their antlers during the calving period. In contrast, both movement methods performed marginally for estimating caribou parturition (~70% accuracy), with estimates from the individual-based method exhibiting greater bias than those from the population-based method. The individual-based method also poorly predicted neonate survival (≤49% accuracy for detecting parturition and calf fate for the Porcupine Herd). Video data revealed that inaccuracies with the movement methods often occurred when caribou bedded during storms, rested after traversing mountainous terrain, lost a calf shortly after birth, or increased movement to evade insects. These results have important implications for management agencies using antler- and movement-based methods to estimate caribou reproduction, particularly when informing assessments of population decline or recovery. Our results demonstrate the utility of video collar data for validating reproductive monitoring approaches and provide insights into how these approaches can be improved.

Alaska, Yukon↗

USGS1976

A comparison of electronic particle counting and pipette techniques in routine mud analysis

Electronic particle counting and pipette size-analysis techniques are compared for their relative effectiveness in large-scale routine mud analysis. Optimum laboratory procedures for conducting electronic analyses with a Model TA Coulter Counter are presented. Comparative electronic and pipette analyses conducted on the same samples resulted in equivalent precision for both techniques. Results of electronic analyses consistently showed size distributions significantly coarser than those obtained by pipette analyses. The laboratory efficiency of the relatively rapid electronic technique is far superior to that of the pipette technique, although more extensive precautionary measures are required to maintain a high level of analytical accuracy and precision. The quality of electronic analyses largely depends upon the effectiveness of standardized operational procedures established within the laboratory.

Open-File Report↗

USGS2025

Bathymetric and acoustic-backscatter mapping of Lake Sammamish, Washington, during USGS field activity 2021-656-FA

In 2021, scientists from the U.S. Geological Survey (USGS) acquired bathymetric and acoustic-backscatter data within Lake Sammamish, Washington. Mapping was completed to find evidence of past earthquakes such as underwater landslides and is part of a larger USGS project to understand the overall geologic hazards history of the Cascadia Margin region. The survey was conducted using the USGS research vessel Parke Snavely outfitted with an interferometric sidescan-sonar system for swath mapping. Three estimates of bathymetric uncertainty were calculated from the post-processed bathymetric data. This report provides a summary of the mapping mission.

Washington↗

USGS2026

USGS Geochron—A database of geochronological and thermochronological dates and data—Technical documentation

Geochronological and thermochronological data are essential for constraining the timing and rates of geological processes, supporting geologic mapping, natural hazard assessment, and resource exploration. The U.S. Geological Survey (USGS) Geochron Database is a centralized, relational database that integrates USGS and State geological survey data in accordance with the National Geologic Mapping Act of 1992 and its reauthorizations. This report documents the structure and development of the database, including its standardized schema, controlled vocabularies, and protocols for compiling legacy and newly published data. The database is designed to adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and currently (2026) includes data from a wide range of geochronological and thermochronological methods. Public access is provided through the USGS Geochron Database Explorer, a browser-based geographic information system (GIS) interface, and through versioned data releases available on ScienceBase, which provide sample-level summary data and detailed analytical information. The USGS Geochron Database is structured to be extensible, supporting the inclusion of additional methods and data types as they are compiled. This format ensures long-term utility and aligns with the Mapping Act’s directive to create a national archive of geochronological information that adds interpretive value to geologic map data. Its design reflects a commitment to data transparency, scientific reproducibility, and national geoscience priorities.

Data Report↗

USGS2025

Rare earth element-mineralized carbonatite in the Bear Lodge Alkaline Complex, USA—Ore genesis implications from fluid inclusion characterization

Rare earth element (REE) resources of the Bear Lodge Alkaline Complex, Wyoming, are hosted in variably leached carbonatite spatially related to diatreme breccia pipes. We investigated the genesis of REE and lesser-known gold resources through fluid inclusion analysis of carbonatite, fluorite breccia, and smoky quartz vein samples. Physicochemical characteristics of inclusion-trapped fluids were evaluated using petrography, microthermometry, Raman spectroscopy, decrepitate mound analysis, energy-dispersive spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and noble gas isotope analysis. Microthermometry results reveal three fluid types that affected carbonatite dikes within deeper zones that escaped near-surface, ore-grade REE enrichment: (1) high-temperature (330–432°C) magmatic fluid captured in fine-grained calcite; (2) REE-enriched alkali bicarbonate-sulfate brine; and (3) low-temperature (117–182°C) diluted magmatic or meteoric water. Multiphase brine-like inclusions contain burbankite, nahcolite, strontianite, celestine and alkali sulfate daughter crystals, linking them to early burbankite mineralization. Peripheral smoky quartz and fluorite occurrences at Smith Ridge, 1.5 km from the central carbonatite dike swarm, contain primary inclusions that are Cl-poor and rich in Na-HCO 3 -SO 4 , similar to secondary and pseudosecondary inclusions in carbonatites. Helium isotopes reveal a MORB-like source for carbonatite samples and an older crust signature at Smith Ridge, consistent with the proximal ridge-top exposures of Archean granite. Results from this fluid inclusion study coupled with previous studies of carbonatite mineral paragenesis, show that light REEs (LREEs) were not mobilized great distances. Instead, burbankite crystallized within carbonatite from alkali bicarbonate fluids. With sodium retained in early burbankite, outward-emanating fluids enriched in potassium relative to sodium (higher K:Na) resulted in potassium–ferric iron metasomatism of silicate host rocks. This alkali fractionation was accompanied by fractionation of LREEs and heavy REEs (HREEs), with LREEs dominating the central carbonatite resources. In contrast, areas of peripheral REE mineralization at Bear Lodge are commonly characterized by higher HREE:LREE ratios. The K:Na ratio of associated fenites or alteration assemblages could be indicative of early crystallized burbankite in carbonatites and REE fractionation processes potentially leading to areas of concentrated HREEs with greater supply vulnerabilities.

South Dakota, Wyoming↗

USGS2025

From hydrated silica to quartz: Potential hydrothermal precipitates found in Jezero crater, Mars

On Earth, silica-rich phases from opal to quartz are important indicators and tracers of geological processes. Hydrated silica, such as opal, is a particularly good matrix for the preservation of molecular and macroscopic biosignatures. Cherts, a type of silica-dominated rocks, provide a unique archive of ancient terrestrial life while quartz is the emblematic mineral of the Earth's continental crust. On Mars, hydrated silica has been detected in several locations based on remote sensing and rover-based studies. In the present article we report on the detection of cobbles made of hydrated silica (opal or chalcedony), as well as well-crystallized quartz. These detections were made with the SuperCam instrument onboard Perseverance (Mars 2020 mission), using a combination of LIBS, infrared and Raman spectroscopy. Quartz-dominated stones are detected unambiguously for the first time on the Martian surface, and based on grain size and crystallinity are proposed to be of hydrothermal origin. Although these rocks were all found as float, we propose that these detections are part of a common hydrothermal system, and represent different depths / temperatures of precipitation. This attests that hydrothermal processes were active in and around Jezero crater, possibly triggered by the Jezero crater-forming impact. These silica-rich rocks, in particular opaline silica, are very promising targets for sampling and return to Earth given their high biosignature preservation potential.

Earth and Planetary Science Letters↗

USGS2024

Analyzing spatial distributions and alignments of pitted cone features in Utopia Planitia on Mars

Martian geomorphology and surface features provide links to understanding past geologic processes such as fluid movement, local and regional tectonics, and feature formation mechanisms. Pitted cones are common features in the northern plains basins of Mars. They have been proposed to have formed from upwelling volatile-rich fluids, such as magma or water-sediment slurries. In this study, we map the spatial distributions of pitted cone features across the Utopia Planitia (UP) basin. Using the Average Nearest Neighbor technique, we find that pitted cone features appear to be clustered across the basin, occurring in a narrow band around the circumferential rim of UP. Additionally, we find that pitted cone features also appear to be aligned in chains that are sub-parallel with the basin margin. Parallel bands of cones generally follow elevation contours of the UP basin, which suggests elevation or a correlated factor plays a major role in pitted cone and cone chain formation. We propose that pitted cones and cone chains may be related to vertical fractures formed around the UP basin rim from subsidence of infilling basin material.

Icarus↗

USGS2016

Sedimentary exhalative (sedex) zinc-lead-silver deposit model

This report draws on previous syntheses and basic research studies of sedimentary exhalative (sedex) deposits to arrive at the defining criteria, both descriptive and genetic, for sedex-type deposits. Studies of the tectonic, sedimentary, and fluid evolution of modern and ancient sedimentary basins have also been used to select defining criteria. The focus here is on the geologic characteristics of sedex deposit-hosting basins that contain greater than 10 million metric tons of zinc and lead. The enormous size of sedex deposits strongly suggests that basin-scale geologic processes are involved in their formation. It follows that mass balance constraints of basinal processes can provide a conceptual underpinning for the evaluation of potential ore-forming mechanisms and the identification of geologic indicators for ore potential in specific sedimentary basins. Empirical data and a genetic understanding of the physicochemical, geologic, and mass balance conditions required for each of these elements are used to establish a hierarchy of quantifiable geologic criteria that can be used in U.S. Geological Survey national assessments. In addition, this report also provides a comprehensive evaluation of environmental considerations associated with the mining of sedex deposits.

Scientific Investigations Report↗

USGS2026

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution↗

USGS2026

Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system

Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.

Colorado↗

USGS2024

Aftershock forecasting

Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple statistical models that were first developed in the 1980s and remain the best available models. We review these statistical models, and the wide-ranging research to advance aftershock forecasting through better statistical, physical, and machine learning methods. Physics-based forecasts based on mainshock stress changes can sometimes match the statistical models in testing, but don’t yet outperform them. Physical models are also hampered by unsolved problems such as the mechanics of dynamic triggering and the influence of background conditions. Initial work on machine learning forecasts shows promise, and new machine learning earthquake catalogs provide an opportunity to advance all types of aftershock forecasts.

Annual Review of Earth and Planetary Sciences↗

USGS2025

Light absorbing particles deposited to snow cover across the Upper Colorado River Basin, Colorado Rocky Mountains, 2013-16: Interannual variations from multiple natural and anthropogenic sources

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Colorado↗