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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Epoch of Giant Planet Migration Planet Search Program. I. Near-infrared Radial Velocity Jitter of Young Sun-like Stars

We present early results from the Epoch of Giant Planet Migration program, a precise radial velocity (RV) survey of more than 100 intermediate-age (∼20–200 Myr) G and K dwarfs with the Habitable Zone Planet Finder spectrograph (HPF) at McDonald Observatory’s Hobby–Eberly Telescope. The goals of this program are to determine the timescale and dominant physical mechanism of giant planet migration interior to the water ice line of Sun-like stars. Here, we summarize results from the first 14 months of this program, with a focus on our custom RV pipeline for HPF, a measurement of the intrinsic near-infrared RV activity of young Solar analogs, and modeling the underlying population-level distribution of stellar jitter. We demonstrate on-sky stability at the sub-2 m s{sup −1} level for the K2 standard HD 3765 using a least-squares matching method to extract precise RVs. Based on a subsample of 29 stars with at least three RV measurements from our program, we find a median rms level of 34 m s{sup −1}. This is nearly a factor of 2 lower than the median rms level in the optical of 60 m s{sup −1} for a comparison sample with similar ages and spectral types as our targets. The observed near-infrared jitter measurements for this subsample are well reproduced with a log-normal parent distribution with μ = 4.15 and σ = 1.02. Finally, by compiling rms values from previous planet search programs, we show that near-infrared jitter for G and K dwarfs generally decays with age in a similar fashion to optical wavelengths, albeit with a shallower slope and lower overall values for ages ≲1 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Advancements in the Representation of Cloud-Aerosol Microphysics in the GEOS-5 AGCM

Despite numerous challenges, the physical parameterization of cloud-aerosol interactions in atmospheric GCMs has become a top priority for advancement because of our need to simulate and understand past, current, and future indirect effects of aerosols on clouds. The challenges stem from the involvement of wide range of cloud-scale dynamics and aerosol activation physical processes. Cloud dynamics modulate cloud areal extent and condensate, while aerosol activation depends on aerosol mass load, size distribution, internal mixing state, and nucleating properties, and ultimately determines cloud optical properties via particle sizes. Both macro- and micro-scale processes are obviously important for cloud-radiation interactions. We will present the main features of cloud microphysical properties in the GEOS- 5 Atmospheric GCM (AGCM) as simulated by the McRAS-AC (Microphysics of Clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction) scheme. McRAS-AC uses Fountoukis and Nenes (2005) aerosol activation for liquid clouds, and has an option for either Liu and Penner (2005) or Barahona and Nenes (2008, 2009) aerosol activation for ice clouds. Aerosol loading (on-line or climatological) comes from GOCART, with an assumed log-normal size distribution. Other features of McRAS-AC are level-by-level cloud-scale thermodynamics, and Seifert-Beheng (2001)-type precipitation microphysics, particularly from moist convection. Results from Single-Column Model simulations will be shown to demonstrate how cloud radiative properties, lifetimes, and precipitation are influenced by different parameterization assumptions. Corresponding fields from year-long simulations of the full AGCM will also be presented with geographical distributions of cloud effective particle sizes compared to satellite retrievals. While the primary emphasis will be on current climate, simulation results with perturbed aerosol loadings will also be shown to expose the radiative sensitivity of the microphysical parameterization.

Lee, D.↗
DOE OSTI2018

Uncertainty quantification in ToxCast high throughput screening

High throughput screening (HTS) projects like the U.S. Environmental Protection Agency’s ToxCast program are required to address the large and rapidly increasing number of chemicals for which we have little to no toxicity measurements. Concentration-response parameters such as potency and efficacy are extracted from HTS data using nonlinear regression, and models and analyses built from these parameters are used to predict in vivo and in vitro toxicity of thousands of chemicals. How these predictions are impacted by uncertainties that stem from parameter estimation and propagated through the models and analyses has not been well explored. While data size and complexity makes uncertainty quantification computationally expensive for HTS datasets, continued advancements in computational resources have allowed these computational challenges to be met. This study uses nonparametric bootstrap resampling to calculate uncertainties in concentration-response parameters from a variety of HTS assays. Using the ToxCast estrogen receptor model for bioactivity as a case study, we highlight how these uncertainties can be propagated through models to quantify the uncertainty in model outputs. Uncertainty quantification in model outputs is used to identify potential false positives and false negatives and to determine the distribution of model values around semi-arbitrary activity cutoffs, increasing confidence in model predictions. At the individual chemical-assay level, curves with high variability are flagged for manual inspection or retesting, focusing subject-matter-expert time on results that need further input. This work improves the confidence of predictions made using HTS data, increasing the ability to use this data in risk assessment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Impacts of aerosol size-dependent below-cloud scavenging on tropospheric aerosol in the NASA GEOS model

Cloud scavenging is the major sink for a suite of tropospheric aerosols, and thus largely affects the global distribution and lifetime of aerosols as well as the formation of clouds. Simplified model parameterizations of cloud scavenging of aerosols substantially contribute to large uncertainties in the simulated aerosol burdens, spatial distributions, lifetimes, as well as aerosol radiative forcing. Here we evaluate the wet scavenging scheme in the current NASA GEOS model, develop more physically-based parameterizations of below-cloud scavenging, and assess the impacts of the new scavenging parameterizations on the GEOS simulations of aerosols. The current below-cloud scavenging (BCS; washout) scheme uses a first-order removal with a constant scavenging coefficient. We replaced the current scheme with a size-dependent parameterization of Croft et al.(Atmos. Chem. Phys., 2009; hereafter referred to as C09). The C09 BCS parameterizations calculate aerosol below-cloud scavenging coefficients based on a size-dependent collision efficiency between aerosol particles and raindrops (or snow crystals). A look-up table of compiled collision efficiencies provides values for sixty aerosol sizes and nine rain flux rates. Snow-aerosol collision efficiencies are a function of the sixty aerosol sizes only. We assume a log-normal size distribution for aerosols (bulk) in GOCART. The collision efficiencies are then calculated online using a bilinear interpolation from the look-up table for the given aerosol sizes and precipitation flux rates in the model.

aerosols↗
NASA NTRSDate not supplied

Impacts of aerosol size-dependent below-cloud scavenging on tropospheric aerosol in the NASA GEOS model

Wet deposition is the major sink for a suite of tropospheric aerosols, and thus largely affects the global distribution and lifetime of aerosols as well as the formation of clouds in the atmosphere. In this study, we implement the aerosol size-dependent below-cloud scavenging (BCS; washout) parameterization of Croft et al. (Atmos. Chem. Phys., 2009; hereafter referred to as C09) in the GOCART bulk aerosol scheme coupled with the NASA Goddard Earth Observing System (GEOS) model, and evaluate the simulated tropospheric aerosols against surface, airborne, and satellite observations. The current below-cloud scavenging in GOCART employs a first-order removal function with a constant scavenging coefficient that is independent of aerosol sizes and precipitation fluxes. The C09 BCS parameterization instead calculates aerosol below-cloud scavenging coefficients based on a size-dependent collision efficiency between aerosol particles and raindrops (or snow crystals). A look-up table of compiled collision efficiencies provides scavenging coefficients for sixty aerosol sizes and nine rain flux rates. We determine instantaneous coefficients according to the C09 BCS look-up table, precipitation fluxes, and a log-normal size distribution of aerosols. The implemented BCS parameterization tends to result in a large diversity of scavenging coefficient values with higher magnitudes, leading to more efficient scavenging. The model-simulated global mean tropospheric Pb-210 aerosol lifetime decreases from 7.4 days to 5.8 days. The separate consideration of rain and snow conditions in the scavenging coefficient lookup table leads to a bi-mode distribution of scavenging coefficients. These changes also cause increased mass fractions of smaller aerosols compared to the current simulation. We examine the impacts of the C09 BCS parameterization on the simulated aerosol vertical profiles, tropospheric lifetimes, and deposition fluxes through comparisons with NASA aircraft measurements (ATom), surface observations of aerosol concentrations (IMPROVE) and wet deposition fluxes (NADP and APQMP), and MODIS aerosol optical depth (AOD) retrievals.

Aerosols↗
DOE OSTI2022

Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site

Abstract. Complex distributions of aerosol properties evolve in space and time as a function of emissions, new particle formation, coagulation, condensational growth, chemical transformation, phase changes, turbulent mixing and transport, removal processes, and ambient meteorological conditions. The ability of chemical transport models to represent the multi-scale processes affecting the life cycle of aerosols depends on their spatial resolution since aerosol properties are assumed to be constant within a grid cell. Subgrid-scale-dependent processes that affect aerosol populations could have a significant impact on the formation of particles, their growth to cloud condensation nuclei (CCN) sizes, aerosol–cloud interactions, dry deposition and rainout and hence their burdens, lifetimes, and radiative forcing. To address this issue, we characterize subgrid-scale variability in terms of measured aerosol number, size, composition, hygroscopicity, and CCN concentrations made by repeated aircraft flight paths over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystem (HI-SCALE) campaign. Subgrid variability is quantified in terms of both normalized frequency distributions and percentage difference percentiles using grid spacings of 3, 9, 27, and 81 km that represent those typically used by cloud-system-resolving models as well as the current and next-generation climate models. Even though the SGP site is a rural location, surprisingly large horizontal gradients in aerosol properties were frequently observed. For example, 90 % of the 3, 9, and 27 km cell mean organic matter concentrations differed from the 81 km cell around the SGP site by as much as ∼ 46 %, large spatial variability in aerosol number concentrations and size distributions were found during new particle formation events, and consequently 90 % of the 3, 9, and 27 km cell mean CCN number concentrations differed from the 81 km cell mean by as much as ∼ 38 %. The spatial variability varied seasonally for some aerosol properties, with some having larger spatial variability during the spring and others having larger variability during the late summer. While measurements at a single surface site cannot reflect the surrounding variability of aerosol properties at a given time, aircraft measurements that are averaged within an 81 km cell were found to be similar to many, but not all, aerosol properties measured at the ground SGP site. This analysis suggests that it is reasonable to directly compare most ground SGP site aerosol measurements with coarse global climate model predictions. In addition, the variability quantified by the aircraft can be used as an uncertainty range when comparing the surface point measurements with model predictions that use coarse grid spacings.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Model of statoconia accumulation in gravireceptors of mollusks

The kinetics of formation and accumulation of statoconia are different for Aplysia californica and Biomphalaria glabrata. In Aplysia californica, the fast growth of statoconia number occurs after the critical size (approximately 45 micrometers) of statocyst is reached; then the increase of statoconia number is proceeding with the nonmonotonic rate during the life of an animal. In Biomphalaria the growth of statoconia number occurs only in the initial phase. Then long-term evolution of statoconia in the absence of their generation is the result of their growth in the cyst lumen. In the case of Aplysia californica it is not clear whether a temporal change of the statoconia size distribution (SSD) is caused by statoconia growth in the cyst lumen similar to that in Biomphalaria (Model 1) or statoconia growth takes place in supporting cells until their release into the cyst lumen occurs. (Model 2). This problem is of practical importance because the majority of experiments related to the development of molluscan gravireceptors in altered gravity dealt with an initial phase of statoconia evolution in Aplysia californica and Biomphalaria glabrata. The purpose of the present work is the application of mathematical modeling to the analysis of mechanisms of statoconia formation by supporting cells.

Non-NASA Center↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
NASA NTRS2001

Yb fiber laser pumped mid-IR source based on difference frequency generation and its application to ammonia detection

A Yb fiber laser pumped cw narrow-linewidth tunable mid-IR source based on a difference frequency generation (DFG) in a periodically poled LiNbO3 (PPLN) crystal for trace gas detection was demonstrated. A high power Yb fiber laser and a distributed feedback (DFB) laser diode were used as DFG pump sources. This source generated mid-IR at 3 microns with a powers of ~2.5 microW and a spectral linewidth of less than 30 MHz. A frequency tuning range of 300 GHz (10 cm-1) was obtained by varying the current and temperature of the DFB laser diode. A high-resolution NH3 absorption Doppler-broadened spectrum at 3295.4 cm-1 (3.0345 microns) was obtained at a cell pressure of 27 Pa from which a detection sensitivity of 24 ppm m was estimated.

NASA Discipline Environmental Health↗
DOE OSTI2014

Massive star-forming host galaxies of quasars on Sloan digital sky survey stripe 82

The stellar properties of about 800 galaxies hosting optically luminous, unobscured quasars at z < 0.6 are analyzed. Deep co-added Sloan Digital Sky Survey (SDSS) images of the quasars on Stripe 82 are decomposed into nucleus and host galaxy using point spread function and Sérsic models. The systematic errors in the measured galaxy absolute magnitudes and colors are estimated to be less than 0.5 mag and 0.1 mag, respectively, with simulated quasar images. The effect of quasar light scattered by the interstellar medium is also carefully addressed. The measured quasar-to-galaxy ratio in total flux decreases toward longer wavelengths, from ∼8 in the u band to ∼1 in the i and z bands. We find that the SDSS quasars are hosted exclusively by massive galaxies (stellar mass M {sub star} > 10{sup 10} M {sub ☉}), which is consistent with previous results for less luminous narrow-line (obscured) active galactic nuclei (AGNs). The quasar hosts are very blue and almost absent on the red sequence, showing stark contrast to the color-magnitude distribution of normal galaxies. The fact that more powerful AGNs reside in galaxies with higher star-formation efficiency may indicate that negative AGN feedback, if it exists, is not concurrent with the most luminous phase of AGNs. We also find positive correlation between the mass of supermassive black holes (SMBHs; M {sub BH}) and host stellar mass, but the M {sub BH}-M {sub star} relation is offset toward large M {sub BH} or small M {sub star} compared to the local relation. While this could indicate that SMBHs grow earlier than do their host galaxies, such an argument is not conclusive, as the effect may be dominated by observational biases.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

The high-latitude cloud MBM 7. I. H I and CO observations

The high-latitude cloud (HLC) MBM 7 has been observed in the 21 cm H I line and the 12CO(1-0) and 13CO(1-0) lines with similar spatial resolutions. The data reveal a total mass approximately 30 M solar for MBM 7 and a complex morphology. The cloud consists of a cold dense core of 5 M solar surrounded by atomic and molecular gas with about 25 M solar, which is embedded in hotter and more diffuse H I gas. We derive a total column density N(H I + 2H2) of 1 x 10(21) cm-2 toward the center and 1 x 10(20) cm-3 toward the envelope of MBM 7. The CO line indicates the existence of dense cores [n(H2) > or = 2000 cm-3] of size (FWHM) approximately 0.5 pc. The morphology suggests shock compression from the southwest direction, which can form molecular cores along the direction perpendicular to the H I distribution. The H I cloud extends to the northeast, and the velocity gradient appears to be about 2.8 km s-1 pc-1 in this direction, which indicates a systematic outward motion which will disrupt the cloud in approximately 10(6) yr. The observed large line widths of approximately 2 km s-1 for CO suggest that turbulent motions exist in the cloud, and hydrodynamical turbulence may dominate the line broadening. Considering the energy and pressure of MBM 7, the dense cores appear not to be bound by gravity, and the whole cloud including the dense cores seem to be expanding. The distance to HLCs suggest that they belong to the galactic plane, since the scale height of the cloud is < or approximately equal to 100 pc. Compared to the more familiar dense dark clouds, HLCs may differ only in their small mass and low density, with their proximity reducing the filling factor and enhancing the contrast of the core and envelope structure.

Non-NASA Center↗
DOE OSTI2016

Simultaneous observations of giant pulses from pulsar PSR B0950+08 at 42 and 74 MHz

We report the detection of giant pulse (GP) emission from PSR B0950+08 in 12 hr of observations made simultaneously at 42 and 74 MHz, using the first station of the Long Wavelength Array. We detected 275 GPs (in 0.16% of the pulse periods) and 465 GPs (0.27%) at 42 and 74 MHz, respectively. The pulsar is weaker and produces less frequent GPs than at 100 MHz. Here, GPs are taken as having ⩾ 10 times the flux density of an average pulse (AP); their cumulative distribution of pulse strength follows a power law, with an index of −4.1 at 42 MHz and −5.1 at 74 MHz, which is much less steep than would be expected if we were observing the tail of a Gaussian distribution of normal pulses. We detected no other transient pulses in a wide dispersion measure range from 1 to 5000 pc cm{sup −3}. There were 128 GPs detected within the same periods from both 42 and 74 MHz, which means more than half of them are not generated in a wide band. The CLEAN-based algorithm was used to deconvolve the the effect of scattering broadening and we have concluded that the scattering effect from the interstellar medium at 42 and 74 MHz is weak and cannot be distinguished from the pulse profiles. We calculated the altitude r of the emission region using the dipolar magnetic field model. We found r(42 MHz) = 29.27 km (0.242% of R{sub LC}) and r(74 MHz) = 29.01 km (0.240% of R{sub LC}) for the AP, while for GPs, r(42 MHz) = 29.10 km (0.241% of R{sub LC}) and r(74 MHz) = 28.95 km (0.240% of R{sub LC}). GPs, which have a double-peak structure, have a smaller mean peak-to-peak separation compared to the AP.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

Comparison of mode estimation methods and application in molecular clock analysis

BACKGROUND: Distributions of time estimates in molecular clock studies are sometimes skewed or contain outliers. In those cases, the mode is a better estimator of the overall time of divergence than the mean or median. However, different methods are available for estimating the mode. We compared these methods in simulations to determine their strengths and weaknesses and further assessed their performance when applied to real data sets from a molecular clock study. RESULTS: We found that the half-range mode and robust parametric mode methods have a lower bias than other mode methods under a diversity of conditions. However, the half-range mode suffers from a relatively high variance and the robust parametric mode is more susceptible to bias by outliers. We determined that bootstrapping reduces the variance of both mode estimators. Application of the different methods to real data sets yielded results that were concordant with the simulations. CONCLUSION: Because the half-range mode is a simple and fast method, and produced less bias overall in our simulations, we recommend the bootstrapped version of it as a general-purpose mode estimator and suggest a bootstrap method for obtaining the standard error and 95% confidence interval of the mode.

Evolution, Molecular↗
DOE OSTI2018

The Central Limit Theorem for Supercritical Oriented Percolation in Two Dimensions

We consider the cardinality of supercritical oriented bond percolation in two dimensions. We show that, whenever the the origin is conditioned to percolate, the process appropriately normalized converges asymptotically in distribution to the standard normal law. This resolves a longstanding open problem pointed out to in several instances in the literature. The result applies also to the continuous-time analog of the process, viz. the basic one-dimensional contact process. We also derive general random-indices central limit theorems for associated random variables as byproducts of our proof.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

SU-D-BRB-02: Combining a Commercial Autoplanning Engine with Database Dose Predictions to Further Improve Plan Quality

Purpose: Database dose predictions and a commercial autoplanning engine both improve treatment plan quality in different but complimentary ways. The combination of these planning techniques is hypothesized to further improve plan quality. Methods: Four treatment plans were generated for each of 10 head and neck (HN) and 10 prostate cancer patients, including Plan-A: traditional IMRT optimization using clinically relevant default objectives; Plan-B: traditional IMRT optimization using database dose predictions; Plan-C: autoplanning using default objectives; and Plan-D: autoplanning using database dose predictions. One optimization was used for each planning method. Dose distributions were normalized to 95% of the planning target volume (prostate: 8000 cGy; HN: 7000 cGy). Objectives used in plan optimization and analysis were the larynx (25%, 50%, 90%), left and right parotid glands (50%, 85%), spinal cord (0%, 50%), rectum and bladder (0%, 20%, 50%, 80%), and left and right femoral heads (0%, 70%). Results: All objectives except larynx 25% and 50% resulted in statistically significant differences between plans (Friedman’s χ{sup 2} ≥ 11.2; p ≤ 0.011). Maximum dose to the rectum (Plans A-D: 8328, 8395, 8489, 8537 cGy) and bladder (Plans A-D: 8403, 8448, 8527, 8569 cGy) were significantly increased. All other significant differences reflected a decrease in dose. Plans B-D were significantly different from Plan-A for 3, 17, and 19 objectives, respectively. Plans C-D were also significantly different from Plan-B for 8 and 13 objectives, respectively. In one case (cord 50%), Plan-D provided significantly lower dose than plan C (p = 0.003). Conclusion: Combining database dose predictions with a commercial autoplanning engine resulted in significant plan quality differences for the greatest number of objectives. This translated to plan quality improvements in most cases, although special care may be needed for maximum dose constraints. Further evaluation is warranted in a larger cohort across HN, prostate, and other treatment sites. This work is supported by Philips Radiation Oncology Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The φ-relation and a simple method to predict how many data points are needed for relevant steady-state detection

Steady–state detection is of vital importance for experiments and simulations in chemical engineering, as well as also other fields of science, engineering, and finance—particularly when the full timescale of interest cannot be measured or simulated. We present a breakthrough for estimating the number of data points required before successful steady–state detection is feasible. Using an initial window of data, the method enables predicting the prerequisites for steady state detection (ppSSD), given as a number of data points. The method is shown to be accurate for data with realistic distributions (uniform, normal, and sine–wave), and data from actual kinetic Monte Carlo simulations. In conclusion, users need only to use the algebraic equations derived and provided in this work to estimate the required number of data points for relevant steady–state detection.

42 ENGINEERING↗
DOE OSTI2024

Measurement of differential ZZ + jets production cross sections in pp collisions at $ \sqrt{s} $ = 13 TeV

Diboson production in association with jets is studied in the fully leptonic final states, pp → (Z/γ$^{*}$)(Z/γ$^{*}$) + jets → 2ℓ2ℓ′ + jets, (ℓ, ℓ′ = e or μ) in proton-proton collisions at a center-of-mass energy of 13 TeV. The data sample corresponds to an integrated luminosity of 138 fb$^{−1}$ collected with the CMS detector at the LHC. Differential distributions and normalized differential cross sections are measured as a function of jet multiplicity, transverse momentum p$_{T}$, pseudorapidity η, invariant mass and ∆η of the highest-p$_{T}$ and second-highest-p$_{T}$ jets, and as a function of invariant mass of the four-lepton system for events with various jet multiplicities. These differential cross sections are compared with theoretical predictions that mostly agree with the experimental data. However, in a few regions we observe discrepancies between the predicted and measured values. Further improvement of the predictions is required to describe the ZZ+jets production in the whole phase space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Evaluation of trace elements in U.S. coals using the USGS COALQUAL database version 3.0. Part I: Rare earth elements and yttrium (REY)

Coal is a potential source of valuable elements such as rare earth elements and yttrium (REY). In this work, REY concentrations in U.S. domestic coals were evaluated using data from the USGS COALQUAL Database Version 3.0. The database contains a total of 7657 non-weathered, full-bed coal samples. The number of samples containing REY data points varies among elements. Assessment of data quality indicates that some of the REY data are semi-quantitative and should be used with caution. Different analytical instruments and methods with varying accuracies and precisions are thought to be the main sources of errors. Inclusion of qualified data also accounts for the sawtooth pattern of the UCC-normalized REY distribution. A new set of Q factor values was thus proposed to adjust qualified data. Consequently, mean concentrations of REY in U.S. coals were obtained with a total REY concentration of 65.5 ppm on a moisture-free whole coal basis. Further evaluation of REY in 5378 selected coal samples indicates that about 9–13% of the samples fall into the combined category of promising and highly promising coals for REY, according to the classification of Dai et al. (2017). Taking sampling bias into consideration, we further found that bituminous coal, particularly from the central Appalachian region, has the highest probability of being a source for beneficial recovery of REY. More specifically, bituminous coal from eastern Kentucky is likely to be the best option. Lastly, we conclude that U.S. domestic coal is a promising, alternative source for beneficial recovery of REY to meet the U.S. REY demand for economic growth.

01 COAL, LIGNITE, AND PEAT↗