Search USGS⌕ Search

SEARCH · Search USGS

Search Search USGS

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

6 recordsLinked to original sources
USGS2025

Relating systematic molecular and textural properties of graptolite pyrolyzed via gold tube hydrous pyrolysis: Implications for thermal proxies in lower Paleozoic marine shales

A series of gold tube pyrolysis experiments (72 h, 300–550 °C, 50 MPa) conducted on a graptolite-rich lower Paleozoic marine shale generated pyrolysis residues for a comprehensive evaluation of the molecular and structural variability of three types of graptolite periderm. Organic petrology, Raman spectroscopy, and field emission scanning electron microscopy (FE-SEM) with energy dispersive spectroscopy (EDS) were combined to evaluate the thermal evolution process. The three types of graptolite periderm, namely granular, non-granular, and nodular graptolite, were analyzed by Raman spectroscopy wherein point measurements were obtained after the maceral was identified and the location verified by organic petrology. Distinct thermal evolution pathways among non-granular, granular, and nodular graptolite periderms were recorded. The evolution patterns of the Raman parameters, particularly D1 and G bands, highlight the differences in geochemical composition of the graptolite periderm types and the alteration of molecular structure with increasing thermal maturity. Raman parameters D1 (position of the D1 peak), G-FWHM (full width at half maximum of the G peak), and ratios D1-FWHM/G-FWHM (full width at half maximum of the D1 peak ratioed to G-FWHM) and A D1 /A G (ratio of D1 and G peak intensities) showed effectiveness in assessing thermal maturity. Bireflectance with increasing gold tube pyrolysis temperature followed a hierarchy: non-granular > granular > nodular, reflecting different molecular alignment intensities. Qualitative FE-SEM evaluation showed that fine-grained mineral inclusions (primarily Fe-sulfide as determined via EDS) were associated with the graptolite populations, with granular graptolite containing greater amounts of coarser-grained (e.g., ∼300–1400 nm) mineral inclusions relative to non-granular and nodular graptolite, which contain finer-grained (e.g., ∼100–200 nm) inclusions difficult to resolve with optical microscopy. These findings are investigated to highlight the mechanisms that drive organic matter evolution within graptolite during thermal maturation, as well as to explore some of the limitations of using spectroscopic parameters as thermal maturity proxies.

International Journal of Coal Geology↗
USGS2025

Confocal laser-scanning microscopy (CLSM)-based thermal maturity of Tasmanites and progress in standardization of fluorescence microspectrometry

Evaluation of thermal maturity in vitrinite-free or vitrinite-deficient sediments via fluorescence microspectrometry can provide relevant information related to petroleum exploration and thermal history assessment. However, variation in spectral fluorescence properties of alginite macerals with increasing thermal maturity is largely underexplored. Here, authors of this study have applied confocal laser-scanning microscopy (CLSM) in conjunction with fluorescence microspectrometry to a maturity series of marine Upper Devonian Tasmanites algae from the Ohio Shale (Huron Member) and a single sample from the Marcellus Formation of the Appalachian Basin. Spectral fluorescence properties of Tasmanites were evaluated in relation to orientation, measurement location, and the number of measurements per sample, and were compared to published literature. Emission spectra of Tasmanites from continuous wave laser excitation (405 nm) were acquired from sections perpendicular and parallel to bedding and at different positions within individual Tasmanites bodies. The results showed a progressive red-shift in emission maxima (λ max ) in a large sample sized maturity series ( N = 19), e.g., 493 to 578 nm for the perpendicular section at middle position. Further, blue-shifted apex and mineral-adjacent positions within sections perpendicular to bedding were observed, with the latter being reported here for the first time. While blue-shift at apex positions can be attributed to mechanical deformation-induced reorientation of photoselected fluorophores, the blue-shifted mineral-adjacent positions could result from strain loading and development of a plastic deformation region at the mineral contact zone with Tasmanites . A decrease in standard deviation with increasing number of measured emission maxima is well-observed, and 15 to 20 individual measurements per sample appears sufficient for low standard deviation and coefficient of variance. CLSM-derived thermal maturity parameters indicated that a moderate positive correlation of red/green quotient (Q 650/500 ; R 2 = 0.67) with solid bitumen reflectance (BR o in %) exists. For reproducible results, the determination of λ max and Q 650/500 should be conducted exclusively in the middle position at perpendicular and parallel sections of the polished whole-rock pellets, where the lowest standard deviation in measurement was observed. These results strengthen the suitability and relevance of the CLSM technique in thermal maturity studies of dispersed organic matter (DOM) and contribute to the standardization of fluorescence microspectrometry methods in organic petrology investigation.

Kentucky, Ohio, Virginia, West Virginia↗
USGS2025

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

Mitigating climate change by abating coal mine methane: A critical review of status and opportunities

Methane has a short atmospheric lifetime compared to carbon dioxide (CO 2 ), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr −1 and 33 ± 5 Tg yr −1 , respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.

International Journal of Coal Geology↗
USGS2024

Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania

Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH 4 ± CO 2 saturated aqueous fluids and CH 4 ± CO 2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH 4 ± CO 2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re -equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.

Pennsylvania↗