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DOE OSTI2022

The X-ray view of optically selected dual AGN

We present a study of optically selected dual Active Galactic Nuclei (AGN) with projected separations of 3–97 kpc. Using multiwavelength (MWL) information (optical, X-ray, mid-IR), we characterized the intrinsic nuclear properties of this sample and compared them with those of isolated systems. Among the 124 X-ray-detected AGN candidates, 52 appear in pairs and 72 as single X-ray sources. Through MWL analysis, we confirmed the presence of the AGN in >80 per cent of the detected targets in pairs (42 out of 52). X-ray spectral analysis confirms the trend of increasing AGN luminosity with decreasing separation, suggesting that mergers may have contributed to triggering more luminous AGN. Through X-ray/mid-IR ratio versus X-ray colours, we estimated a fraction of Compton-thin AGN (with 10 22 cm −2 < N H < 10 24 cm −2 ) of about 80 per cent, while about 16 per cent are Compton-thick sources (with N H > 10 24 cm −2 ). These fractions of obscured sources are larger than those found in samples of isolated AGN, confirming that pairs of AGN show higher obscuration. This trend is further confirmed by comparing the de-reddened [O III ] emission with the observed X-ray luminosity. However, the derived fraction of Compton-thick sources in this sample at the early stages of merging is lower than that reported for late-merging dual-AGN samples. Comparing N H from X-rays with that derived from E(B − V ) from narrow-line regions, we found that the absorbing material is likely to be associated with the torus or broad-line regions. We also explored the X-ray detection efficiency of dual-AGN candidates, finding that, when observed properly (at on-axis positions and with long exposures), X-ray data represent a powerful way to confirm and investigate dual-AGN systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Temporal, Spatial, and Temperature Controls on Organic Carbon Mineralization and Methanogenesis in Arctic High-Centered Polygon Soils

Warming temperatures in continuous permafrost zones of the Arctic will alter both hydrological and geochemical soil conditions, which are strongly linked with heterotrophic microbial carbon (C) cycling. Heterogeneous permafrost landscapes are often dominated by polygonal features formed by expanding ice wedges: water accumulates in low centered polygons (LCPs), and water drains outward to surrounding troughs in high centered polygons (HCPs). These geospatial differences in hydrology cause gradients in biogeochemistry, soil C storage potential, and thermal properties. Presently, data quantifying carbon dioxide (CO 2 ) and methane (CH 4 ) release from HCP soils are needed to support modeling and evaluation of warming-induced CO 2 and CH 4 fluxes from tundra soils. This study quantifies the distribution of microbial CO 2 and CH 4 release in HCPs over a range of temperatures and draws comparisons to previous LCP studies. Arctic tundra soils were initially characterized for geochemical and hydraulic properties. Laboratory incubations at −2, +4, and +8°C were used to quantify temporal trends in CO 2 and CH 4 production from homogenized active layer organic and mineral soils in HCP centers and troughs, and methanogen abundance was estimated from mcrA gene measurements. Results showed that soil water availability, organic C, and redox conditions influence temporal dynamics and magnitude of gas production from HCP active layer soils during warming. At early incubation times (2–9 days), higher CO 2 emissions were observed from HCP trough soils than from HCP center soils, but increased CO 2 production occurred in center soils at later times (>20 days). HCP center soils did not support methanogenesis, but CH 4 -producing trough soils did indicate methanogen presence. Consistent with previous LCP studies, HCP organic soils showed increased CO 2 and CH 4 production with elevated water content, but HCP trough mineral soils produced more CH 4 than LCP mineral soils. HCP mineral soils also released substantial CO 2 but did not show a strong trend in CO 2 and CH 4 release with water content. Knowledge of temporal and spatial variability in microbial C mineralization rates of Arctic soils in response to warming are key to constraining uncertainties in predictive climate models.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Stress-sensitivity of fracture conductivity of Tuscaloosa Marine Shale cores

Production decline from wells producing from shale rocks is typically quite rapid. One possible factor responsible for such decline is loss in fracture conductivity. This is true in the case of the Tuscaloosa Marine shale reservoir. In this work, the stress-dependent fracture conductivity of TMS core samples is investigated using five propped cores under varying stress conditions. In addition, the effects of static rock mechanical properties and rock mineralogy on conductivity decline are investigated. The mineralogy of each core sample was determined by X-ray Diffraction analysis. Fracture conductivity was measured using a Hassler-type pressure core holder with a pressure rating of 15,000 psi (103.42 MPa). Estimated rock mechanical properties showed that shale anisotropy could affect fracture conductivity. The time decline in conductivity revealed two possible decline trends, a) decline from the reduction in induced fracture width, and b) decline from the healing of developed micro-cracks. An exponential decline in fracture conductivity with increasing confinement pressure was observed with an average decline rate constant of 3.15 x 10 -10 mPa -1 . While rock mineralogy did not have any clear relationship with conductivity decline, the effects of rock mechanical properties were only important at 10.34 MPa confinement pressure and above. The observation showed that a high Young's modulus correlate to high conductivity, whereas a high Poisson's ratio correlate to low conductivity. This study provides useful observations for optimizing fracture design to enhance well productivity in the TMS.

02 PETROLEUM↗

DOE OSTI2021

Application of Point Precipitation Frequency Estimates to Watersheds

This report documents work sponsored by the U.S. Nuclear Regulatory Commission (NRC) at the Oak Ridge National Laboratory (ORNL) as part of the RES project, “Application of Point Precipitation Frequency Estimates to Watersheds.” This project was implemented as part of the Probabilistic Flood Hazard Assessment (PFHA) Research Program. The objective of the PFHA Research Program is to develop tools and guidance on the use of PFHA methods to risk-inform NRC’s licensing of new facilities as well as licensing and oversight of currently operating facilities as they relate to flooding hazards. Many nuclear power plants (NPPs) are located on or near rivers so riverine flooding hazards need to be considered in their design and operation. Probabilistic riverine flood models are important tools for realistic assessment of flooding risks. However, these models require areal estimates of the depth, duration, and frequency of rainfall distributed over the watershed, which are not often available. Point precipitation frequency estimates are more widely available. For example, the National Oceanic and Atmospheric Administration (NOAA) has published NOAA Atlas 14, which provides point precipitation frequency estimates for 5-minute through 60-day durations at average recurrence intervals of 1-year through 1,000-year. The research documented in this report addresses areal reduction factors (ARFs), which can be used to convert the widely available point precipitation frequency estimates, to estimates of areal precipitation frequency over a watershed. The most widely used ARF source is Technical Paper 29 (TP-29) published by the then U.S. Weather Bureau in 1958. However, both the methods and the underlying precipitation data used to produce TP-29 are seriously out of date. For example, due to the small gauge network available at the time of TP-29’s compilation, ARF estimates developed are only for watersheds smaller than about 400 square miles. Due to the relatively short record lengths of precipitation data available, frequency considerations could not be accurately determined. Other factors such as regional climate and seasonality were not addressed. Several newer methods have been published since TP-29 was developed and both the type and quantity of precipitation data have increased significantly, along with computational resources and analytical tools such as geographic information systems. This report reviewed and assessed the available precipitation products and methods for conducting ARF analysis. The work applied up-to-date precipitation data products and analysis methods with a novel watershed-based approach to investigate how ARF estimates vary across different methods, data sources, geographical locations, return periods, and seasons. The overall findings reported here regarding basic ARF trends are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. This study found significant differences among the available ARF methods. This work also found a strong geographical variability across different US hydrologic regions, suggesting that the ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of data record length, especially for high return level ARFs. The work reported in NUREG/CR-7271 will assist NRC staff in assessing different classes of ARF methods in conjunction with available rainfall data sets. It will also support the development of guidance for application of point precipitation data in PFHAs. It should be noted that the ARF values presented in this report for any location or region were developed for the purposes of comparing methods and investigating the factors that influence ARFs. They should not be considered official and should not be used in leu of a site-specific analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Estimating carrying capacity for juvenile salmon using quantile random forest models

Abstract Establishing robust methods and metrics to evaluate habitat quality is critical for the recovery of endangered Pacific salmonids ( Oncorhynchus spp.). A variety of modeling approaches are used for status and trend monitoring of anadromous species throughout the Pacific Northwest, USA, but current methods may fail to capture the complex relationship between fish and habitat and are often limited in predictive power beyond specific watersheds. Further, the focus on species distribution and abundance is not easily manipulated to predict carrying capacity and traditional stock‐recruitment analyses are reliant on long‐term data which are not always available. In this study, we developed a quantile random forest model to provide estimates of habitat carrying capacity for Chinook salmon ( O. tshawytscha ) parr during the summer months, at both the site and watershed scale. Quantile random forest models allow for the consideration of noisy data, correlated variables, and non‐linear relationships: common features in fish–habitat datasets. We leveraged Columbia Habitat Monitoring Program data to select habitat co‐variates and predict capacity at those sites. We also identified a set of globally available attributes to extrapolate capacity estimate predictions throughout wadeable streams within the Columbia River basin. Total capacity estimates for watersheds closely matched estimates from alternative fish productivity models. Carrying capacity estimates based on quantile random forest models, like those presented here, provide managers a framework to guide the identification, prioritization, and development of habitat rehabilitation actions to recover salmon populations.

See, Kevin E.↗

DOE OSTI2023

Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction

Floods and heavy precipitation have disruptive impacts worldwide, but their historical variability remains only partially understood at the global scale. This article aims at reducing this knowledge gap by jointly analyzing seasonal maxima of streamflow and precipitation at more than 3,000 stations over a 100‐year period. The analysis is based on Hidden Climate Indices (HCIs). Like standard climate indices (e.g., Nino 3.4, NAO), HCIs are used as covariates explaining the temporal variability of data, but unlike them, HCIs are estimated from the data. In this work, a distinction is made between common HCIs, that affect both heavy precipitation and floods, and specific HCIs, that exclusively affect one or the other. Overall, HCIs do not show noticeable autocorrelation, but some are affected by noticeable trends. In particular, strong and wide‐ranging trends are identified in precipitation‐specific HCIs, while trends affecting flood‐specific HCIs are weaker and have more localized effects. A probabilistic model is then derived to link HCIs and large‐scale atmospheric variables (pressure, wind, temperature) and to reconstruct HCIs since 1836 using the 20CRv3 reanalysis. In turn this allows estimating the probability of occurrence of floods and heavy precipitation at the global scale. This 180‐year reconstruction highlights flood hot‐spots and hot‐moments in the distant past, well before the establishment of perennial monitoring networks. Finally, the approach presented in this study is generic and paves the way for an improved characterization of historical variability by making a better use of long but highly irregular station data sets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Reducing Model Uncertainty of Climate Change Impacts on High Latitude Carbon Assimilation

The Arctic Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO 2 . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models (TBMs) such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region. Furthermore, we review our current understanding and model representation of GPP in northern latitudes, focusing on vegetation composition, phenology and physiology, and consider how climate change alters these three components. We highlight challenges in the ABR for predicting GPP, but also focus on the unique opportunities for advancing knowledge and model representation, particularly through the combination of remote sensing and traditional boots-on-the-ground science.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Spent Nuclear Fuel Mechanical Loads in the General Package Drop Scenario

The US Department of Energy Spent Fuel and Waste Science and Technology program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transportation to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. A recent multi-national collaborative test campaign measured SNF assembly impact response to the 30 cm horizontal package drop scenario, which is a common regulatory basis test of SNF package design. Researchers at Pacific Northwest National Laboratory (PNNL) are using the test data to validate explicit finite element models to calculate the mechanical loads and structural response of spent nuclear fuel assemblies in the as-tested 30 cm horizontal package drop scenario. Once the as-tested package drop model is validated, the next step is to apply the model to the general 30 cm drop scenario, which includes all impact angles, all fuel assembly types, and all burnup conditions. PNNL is developing a damage model that will incorporate the results of finite element parametric studies to establish trends in SNF mechanical loading to various input parameters, like impact orientation and burnup. The damage model will have the capability to estimate mechanical loads for any single set of input parameters, but it will first be used to describe the upper bounds of potential SNF loading in the 30 cm drop scenario. This paper describes PNNL’s progress toward developing the general solution to the problem of spent nuclear fuel mechanical loads in the 30 cm package drop scenario and it describes the next steps in closing the knowledge gap.

Klymyshyn, Nicholas A.↗

DOE OSTI2020

Direct Demonstration of Unified Brønsted-Evans-Polanyi Relationships for Proton-Coupled Electron Transfer Reactions on Transition Metal Surfaces

Brønsted-Evans-Polanyi (BEP) relationships, which relate elementary reaction barriers to reaction thermodynamics, have long been discussed in electrochemical science, but demonstration of their existence in heterogeneous electrocatalysis, across many different catalyst surfaces and voltages, is lacking. In this contribution, the BEP model is demonstrated to describe both multiple catalyst surfaces and variable voltages in electrochemical environments. For proton-coupled electron transfer (PCET) to surface nitrogen (N*) and nitric oxide (NO*), reaction energies and activation barriers are calculated using Density Functional Theory (DFT) on a parallel plate capacitor model at three different potentials and for nine different transition metal surfaces. Linear BEP relations that describe all potentials and catalyst surfaces are obtained for these elementary reactions, and the slopes of the correlations are shown to be directly related to the fractional coordinate of the transition states (FCTS) of the reactions. The results, which are explained in terms of Marcus Theory, prove a direct equivalence between unified BEP coefficients, describing both variable catalyst surfaces and voltages, and electrochemical symmetry factors and provide a straightforward means of estimating this quantify for PCET reactions on transition metal surfaces. The resulting relationships, in turn, could lead to predictions of electrocatalytic reactivity trends of enhanced accuracy and efficiency.

Electrochemistry↗

DOE OSTI2021

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Techno-economic analysis and life cycle assessment for the catalytic hydrogenolysis and hydrocracking of polyethylene

Catalytic hydrogenolysis and hydrocracking are promising technologies for the conversion of polyolefin waste into hydrocarbons. Here, to explore the economic and environmental viability of these approaches, we conducted techno-economic analysis and life cycle assessment of polyethylene hydrogenolysis and hydrocracking processes that produce fuel-range products or olefins, respectively. Relative to primary production, the minimum selling price (MSP) of alkanes for linear-chain naphtha was estimated to be 1.8-fold higher, whereas branched-chain naphtha and propylene were shown to be cost competitive. Environmental impacts showed similar trends across scenarios, with propylene production by hydrocracking exhibiting greenhouse gas emissions comparable with conventional propylene due to relatively low hydrogen demand and high yield. Together, these results suggest that innovations in catalysis and reaction engineering will be required to make viable products that are scale matched with today's plastics, such as light olefins for closed-loop recycling.

09 BIOMASS FUELS↗

DOE OSTI2026

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

The landscape of disc outflows from black hole–neutron star mergers

ABSTRACT We investigate mass ejection from accretion discs formed in mergers of black holes (BHs) and neutron stars (NSs). The third observing run of the LIGO/Virgo interferometers provided BH–NS candidate events that yielded no electromagnetic (EM) counterparts. The broad range of disc configurations expected from BH–NS mergers motivates a thorough exploration of parameter space to improve EM signal predictions. Here we conduct 27 high-resolution, axisymmetric, long-term hydrodynamic simulations of the viscous evolution of BH accretion discs that include neutrino emission/absorption effects and post-processing with a nuclear reaction network. In the absence of magnetic fields, these simulations provide a lower limit to the fraction of the initial disc mass ejected. We find a nearly linear inverse dependence of this fraction on disc compactness (BH mass over initial disc radius). The dependence is related to the fraction of the disc mass accreted before the ouflow is launched, which depends on the disc position relative to the innermost stable circular orbit. We also characterize a trend of decreasing ejected fraction and decreasing lanthanide/actinide content with increasing disc mass at fixed BH mass. This trend results from a longer time to reach weak freezout and an increasingly dominant role of neutrino absorption at higher disc masses. We estimate the radioactive luminosity from the disc outflow alone available to power kilonovae over the range of configurations studied, finding a spread of two orders of magnitude. For most of the BH–NS parameter space, the disc outflow contribution is well below the kilonova mass upper limits for GW190814.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Monitoring Avian Productivity and Survivorship at the Sandia Wetlands at Los Alamos National Laboratory (2014-2019)

Biologists at Los Alamos National Laboratory completed six years (2014–2019) of demographic monitoring of passerines (songbirds) during the breeding season in Los Alamos, New Mexico. We captured songbirds at a mist netting station located in the Sandia Wetlands in Sandia Canyon (Technical Areas 60 and 61). We identified, measured, and then banded captured birds with federal migratory bird bands. Banding operations took place between May and August of each year, with 10 mist netting sessions annually. We conducted this project as part of the implementation of the Biological Resources Management Plan. The project complies with the 2013 Memorandum of Understanding between the United States Fish and Wildlife Service (USFWS) and the United States Department of Energy regarding the implementation of Executive Order 13186. The overall number of birds and species captured was variable, and we saw no decreases over the course of six years in bird species diversity, abundance, or the percentage of breeding birds. Our results indicate that the Sandia Wetlands support numerous species of breeding birds, including species of conservation concern. We did not see a declining trend for the top 10 most-captured species or for any of the species of conservation concern over time; however, we need more years of data to make robust conclusions about population trends through time. Our results indicated that adult recapture rates at the Sandia Wetlands are at least twice as low when compared with estimated adult survival in migratory passerines from peer-reviewed literature. We also did not recapture any birds that were banded as juveniles in subsequent years throughout the entire six-year period. Low recapture rates for adults and the non-existent recapture rates for juveniles should be explored further. To accurately assess individual species survival rates for adults and juveniles using mark-recapture models, we need a longer dataset, which would allow for a more robust analysis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Combined $\mathrm{APOGEE}$-$\mathrm{GALAH}$ stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilize them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the Cannon data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE-scaled and the other with the GALAH-scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~0.02–0.4 dex) and alpha abundances (~0.02–0.03 dex) for spectra with good signal-to-noise ratio (SNR >; 80 for APOGEE and SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE-scaled case. The final catalogues have been cross-matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Agreement of Analytical and Simulation-Based Estimates of the Required Land Depth in Climate Models

Previous analytical and simulation-based analyses suggest that deeper land surface models are needed to realistically simulate the terrestrial thermal state in climate models, with implications for land-atmosphere interactions. Analytical approaches mainly focused on the subsurface propagation of harmonics such as the annual temperature signal, and a direct comparison with climate-change model output has been elusive. Here, this study addresses the propagation of a harmonic pulse fitted to represent the timescale and amplitude of anthropogenic warming. Its comparison to land model simulations with stepwise increased bottom boundary depth leads to an agreement between the simulation-based and analytical frameworks for long-term climate trends. Any depth increase gradually decreases the relative error in the subsurface thermodynamics, and a minimum depth of 170 m is recommended to simulate the ground climate adequately. The approach provides an accurate estimate of the required land-model depth for climate-change simulations and assesses the relative bias in insufficiently deep land models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗