SEARCH · Engineering Papers

Results for “spatial heterogeneity”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

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

At least 181 records · Page 10

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Evaluating crown scorch predictions from a computational fluid dynamics wildland fire simulator

Abstract Background Crown scorch—the heating of live leaves, needles, and buds in the vegetative canopy to lethal temperatures without widespread combustion—is one of the most common fire effects shaping post-fire canopies. Despite the ability of computational fluid dynamic models to finely resolve fire activity and buoyant plume dynamics including heterogenous 3D distributions of forest canopy heating, these models have had only limited use in simulating fire effects and have not been used to evaluate crown scorch. Here, we demonstrate a method of evaluating crown scorch using a computational fluid dynamics model, FIRETEC, and validate this approach by simulating the experiments that were used to develop Van Wagner’s 1973 crown scorch model. Results The average scorch height prediction from FIRETEC compares well with the empirical model derived by Van Wagner, which is the most widely used empirical model for crown scorch. We further find that the 3D buoyant plume dynamics from a steady and homogeneous idealized heat source on the ground results in a spatially heterogenous crown scorch pattern reflecting complex heating dynamics that are best represented by percent scorch rather than height of scorch. Conclusions The ability of the computational fluid dynamics model to capture variation in crown scorch due to 3D buoyant plume dynamics provides direct links between forest structure, fire behavior, and fire effects that can be used by forest managers and researchers to better understand how fires result in crown damage under various environmental and management scenarios.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Heterogeneous Distribution of Chromium on Mercury

Measurements made with geochemical instruments on the MESSENGER spacecraft revealed that Mercury's crust is surprisingly rich in volatile elements, including S, Na, K, Cl, and C, and that it is enriched in Mg and depleted in Al, Ca, and Fe, relative to other terrestrial planets. Geochemical maps also indicated the presence of a number of distinct geochemical terranes. The MESSENGER X-ray Spectrometer (XRS) detected X-ray fluorescence, induced by incident solar X-rays, from the top approx. 10s of micrometers of Mercury's surface. Like Fe, Cr was only detectable by XRS during large solar flares. However, accurate Cr measurements are more susceptible to systematic errors than other elements measured by the XRS. Therefore, to date, Cr data have been published for only 11 XRS measurements, but we have recently derived a map of Cr/Si across Mercury's surface. This map is based on data acquired through the complete MESSENGER mission and reveals clear spatial heterogeneity in Cr.

Nittler, L. R.↗

NASA NTRS2010

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

Mascaro, Giuseppe↗

DOE OSTI2024

Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0

Abstract. The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations.

58 GEOSCIENCES↗

DOE OSTI2026

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗

NASA NTRSDate not supplied

Airborne High Spectral Resolution Lidar Measurements of Aerosol Distributions and Properties During the NASA CAMP2Ex Mission

The NASA Clouds, Aerosols and Monsoon Processes-Philippines Experiment (CAMP2Ex) occurred during August-October, 2019,primarily over the ocean near the Philippines, including the ocean west of Luzon. CAMP2Ex attempts to characterize the role of anthropogenic and natural aerosol particles in modulating warm and mixed-phase precipitation in the maritime continent during the Southwest Monsoon. This mission is also examining relationships between spatial heterogeneity in the aerosol and cloud fields and radiative heating rates and studying the effects of aerosol concentration and composition on the microphysical properties of shallow cumulus and cumulus congestus clouds. Critical to the successful investigation of these objectives is profiling of aerosol, cloud and meteorological properties throughout the atmospheric column. For the CAMP2Ex experiment, we deployed the second generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) on the NASA P-3 aircraft to obtain profile measurements of aerosol and thin cloud extinction and optical thickness via the HSRL technique at 355 and 532 nm, and of backscatter and depolarization at 355, 532, and 1064 nm. The HSRL technique allows for the independent measurement of extinction and backscatter without the need to assume modeled lidar ratios. Additional HSRL-2 data products include aerosol type, mixed layer depth, and range-resolved aerosol microphysical parameters. The HSRL measurements reveal the temporal, spatial, and vertical variability of aerosol optical properties over these locations. The HSRL-2 measured these backscatter, extinction, and depolarization profiles during all nineteen science flights and the transit flights to and from the aircraft operations base at Clark International Airport.In this presentation, we use these HSRL-2 measurements to show the horizontal and vertical distributions of aerosols in the CAMP2Ex operational area as well as provide insight into the optical and physical characteristics of these aerosols. We also discuss how these aerosols are distributed within and above the mixed layer.

aerosol↗

NASA NTRS2024

Northern Brazil Agriculture: Measuring Soybean Yields in Northern Brazil During El Niño-Southern Oscillation Conditions to Evaluate Trends in Agricultural Production and Support Crop Forecasting, 1984 – 2023

As one of the largest agricultural exporters in the world, Brazil’s crop productivity is highly influential to the world’s food supply. Crop productivity across Brazil is heavily influenced by climatic factors, such as the El Niño-Southern Oscillation (ENSO), which drives spatially heterogenous effects on growing conditions. To understand the relationship between ENSO conditions and staple crop productivity, the team used 1984 – 2023 climatic data and vegetation indices for four Brazilian states: Bahia, Mato Grosso, Pará, and Tocantins. The team focused on soybean growing areas in each state derived from annual land use/land cover classifications. Monthly mean Normalized Difference Vegetation Index (NDVI) per state were calculated using multispectral imagery from the Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imagery (OLI) sensors. In addition, the team used crop production indices, ENSO anomalies, temperature, and precipitation data in this study. The team found that although monthly ENSO anomaly did have a positive relationship between temperature and a slight negative relationship with precipitation, ENSO and monthly soy NDVI were not significantly correlated. Results find no association between ENSO conditions and NDVI in the study area at the state level spatial resolution during the study period. Furthermore, the team found that there was no correlation between cumulative growing season soy NDVI and detrended soy production yield for this study region at the spatial and temporal scale of the analysis. Findings from this project will be used by the United States Department of Agriculture’s Foreign Agriculture Service to inform crop productivity forecasting.

remote sensing↗

DOE OSTI2026

Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra: Modeling Archive

This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION↗

DOE OSTI2020

A Bezier Curve Informed Melt Pool Geometry to Model Additive Manufacturing Microstructures Using SPPARKS

Additive manufacturing is a transformative technology with the potential to manufacture designs which traditional subtractive machining methods cannot. Additive manufacturing offers fast builds at near final desired geometry; however, material properties and variability from part to part remain a challenge for certification and qualification of metallic components. AM induced metallic microstructures are spatially heterogeneous and highly process dependent. Engineering properties such as strength and toughness are significantly affected by microstructure morphologies resulting from the manufacturing process Linking process parameters to microstructures and ultimately to the dynamic response of AM materials is critical to certifying and qualifying AM built parts and components and improving the performance of AM materials. The AM fabrication process is characterized by building parts layer by layer using a selective laser melt process guided by a computer. A laser selectively scans and melts metal according to a designated geometry. As the laser scans, metal melts, fuses, and solidifies forming the final geometry in a layerwise fashion. As the laser heat source moves away, the metal cools and solidifies forming metallic microstructures. This work describes a microstructure modeling application implemented in the SPPARKS kinetic Monte Carlo computational framework for simulating the resulting microstructures. The application uses Bzier curves and surfaces to model the melt pool surface and spatial temperature profile induced by moving the laser heat source; it simulates the melting and fusing of metal at the laser hot spot and microstructure formation and evolution when the laser moves away. The geometry of the melt pool is quite flexible and we explore effects of variances in model parameters on simulated microstructures.

36 MATERIALS SCIENCE↗

NASA NTRS2000

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Steyaert, Lou↗

DOE OSTI2025

Hidden Features: How Subsurface and Landscape Heterogeneity Govern Hydrologic Connectivity and Stream Chemistry in a Montane Watershed

ABSTRACT Hydrologic connectivity is defined as the connection among stores of water within a watershed and controls the flux of water and solutes from the subsurface to the stream. Hydrologic connectivity is difficult to quantify because it is goverened by heterogeniety in subsurface storage and permeability and responds to seasonal changes in precipitation inputs and subsurface moisture conditions. How interannual climate variability impacts hydrologic connectivity, and thus stream flow generation and chemistry, remains unclear. Using a rare, four‐year synoptic stream chemistry dataset, we evaluated shifts in stream chemistry and stream flow source of Coal Creek, a montane, headwater tributary of the Upper Colorado River. We leveraged compositional principal component analysis and end‐member mixing to evaluate how seasonal and interannual variation in subsurface moisture conditions impacts stream chemistry. Overall, three main findings emerged from this work. First, three geochemically distinct end members were identified that constrained stream flow chemistry: reach inflows, and quick and slow flow groundwater contributions. Reach inflows were impacted by historic base and precious metal mine inputs. Bedrock fractures facilitated much of the transport of quick flow groundwater and higher‐storage subsurface features (e.g., alluvial fans) facilitated the transport of slow flow groundwater. Second, the contributions of different end members to the stream changed over the summer. In early summer, stream flow was composed of all three end members, while in late summer, it was composed predominantly of reach inflows and slow flow groundwater. Finally, we observed minimal differences in proportional composition in stream chemistry across all four years, indicating seasonal variability in subsurface moisture and spatial heterogeneity in landscape and geologic features had a greater influence than interannual climate fluctuation on hydrologic connectivity and stream water chemistry. These findings indicate that mechanisms controlling solute transport (e.g., hydrologic connectivity and flow path activation) may be resilient (i.e., able to rebound after perturbations) to predicted increases in climate variability. By establishing a framework for assessing compositional stream chemistry across variable hydrologic and subsurface moisture conditions, our study offers a method to evaluate watershed biogeochemical resilience to variations in hydrometeorological conditions.

Johnson, Keira [College of Earth, Ocean, and Atmos↗

DOE OSTI2022

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S ppt with different satellite products: S ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S ppt . Our finding of the overall decline in S ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2026

South Asian Monsoon Response to Regional Aerosol Emission Reductions: Insights From RAMIP

Anthropogenic aerosol and associated precursor gas emissions are already declining in many regions and are likely to decline significantly by 2050, with major implications for regional climate. Unlike greenhouse gases, aerosol impacts are spatially heterogeneous and can influence climate both near emission sources and through remote teleconnections. This is particularly important for the South Asian monsoon system, where both local and remote aerosol changes can significantly affect precipitation patterns. Using simulations from the Regional Aerosol Model Intercomparison Project, we examine how local and remote aerosol emission reductions influence South Asian climate across both pre-monsoon and monsoon seasons, including weakening of the elevated heat pump (EHP) mechanism during pre-monsoon months. Our analysis employs 10-member ensembles from 10 CMIP6-era models to compare three experiments with global, South Asian, and East Asian aerosol reductions relative to a high-emission baseline (SSP3-7.0). This experimental design allows us to isolate and quantify the distinct impacts of regional emission changes. Results reveal that global aerosol reductions produce a larger all-India precipitation increase (+0.28 mm day −1 ) than South Asian reductions alone (+0.19 mm day −1 ), with the strongest regional responses over the northern Bay of Bengal, the Western Ghats and Indo-Gangetic Plains. East Asian reductions show uncertain but modest precipitation reductions of 0.2-0.6 mm day −1 over parts of west-central and eastern Indian regions. Pre-monsoon carbonaceous aerosol reductions systematically weaken the EHP, cooling the mid-troposphere over the Himalayan foothills by up to 0.4 K and producing localised anomalous descent that opposes the climatological pre-monsoon ascent. Substantial inter-model diversity exists in the spatial patterns and magnitudes of these responses, highlighting key uncertainties in aerosol–monsoon interactions. The South Asian precipitation response is driven by enhanced land–sea thermal contrast, while the pre-monsoon EHP weakening is attributable exclusively to local South Asian carbonaceous aerosol forcing rather than remote teleconnections. These findings have direct implications for air quality and climate adaptation planning across South Asia as regional aerosol emissions diverge under different development pathways.

cmip6↗

NASA NTRS2014

The Surface Compositions of Pluto and Charon

The surface of Pluto as it is understood on the eve of the encounter of the New Horizons spacecraft (mid-2015) consists of a spatially heterogeneous mix of solid N2, CH4, CO, C2H6, and an additional component that imparts color, and may not be an ice. The known molecular ices are detected by near-infrared spectroscopy. The N2 ice occurs in the hexagonal crystalline b-phase, stable at T greater than 35.6 K. Spectroscopic evidence for wavelength shifts in the CH4 bands attests to the complex mixing of CH4 and N2 in the solid state, in accordance with the phase diagram for N2 + CH4. Spectra obtained at several aspects of Plutos surface as the planet rotates over its 6.4-day period show variability in the distribution of CH4 and N2 ices, with stronger CH4 absorption bands associated with regions of higher albedo, in correlation with the visible rotational light curve. CO and N2 ice absorptions are also strongly modulated by the rotation period; the bands are strongest on the anti-Charon hemisphere of Pluto. Longer term changes in the strengths of Plutos absorption bands occur as the viewing geometry changes on seasonal time-scales, although a complete cycle has not been observed. The non-ice component of Plutos surface may be a relatively refractory material produced by the UV and cosmic-ray irradiation of the surface ices and gases in the atmosphere, although UV does not generally penetrate the atmospheric CH4 to interact with the surface. Laboratory simulations indicate that a rich chemistry ensues by the irradiation of mixtures of the ices known to occur on Pluto, but specific compounds have not yet been identified in spectra of the planet. Charons surface is characterized by spectral bands of crystalline H2O ice, and a band attributed to one or more hydrates of NH3. Amorphous H2O ice may also be present; the balance between the amorphization and crystallization processes on Charon remains to be clarified. The albedo of Charon and its generally spatially uniform neutral color indicate that a component, not yet identified, is mixed in some way with the H2O and NH3nH2O ices. Among the many known small bodies in the transneptunian region, several share characteristics with Pluto and Charon, including the presence of CH4, N2, C2H6, H2O ices, as well as components that yield a wide variety of surface albedo and color. The New Horizons investigation of the Pluto-Charon system will generate new insight into the physical properties of the broader transneptunian population, and eventually to the corresponding bodies expected in the numerous planetary systems currently being discovered elsewhere in the Galaxy.

surface composition↗

DOE OSTI2025

Discharge Rate‐Driven Li 2 O 2 Growth Exhibits Unconventional Morphology Trends in Solid‐State Li‐O 2 Batteries

Solid-state lithium oxygen batteries (LOBs) are known for their enhanced safety, higher electrochemical stability, and improved energy density compared to liquid-state LOBs. However, the investigation of solid-state LOBs is limited with little understanding of their discharge and charge processes. In this work, a polymer-based solid-state LOB is used to investigate the effect of discharge rate on lithium peroxide (Li 2 O 2 ) formation, the oxygen evolution reaction (OER), and cycle performance. Notably, we observe a counterintuitive trend: Li 2 O 2 particle size increases with increasing discharge current density, in contrast to liquid systems. This behavior arises from inherent space charge layers that restrict Li⁺ transport under high current, and spatially heterogeneous active sites at the solid electrolyte–cathode interface, directly evidenced by small angle X-ray scattering (SAXS), which govern nucleation accessibility and promote site-selective Li 2 O 2 growth. Furthermore, higher current densities improve ORR and OER efficiency but accelerate anode degradation, while lower currents promote side reactions. These opposing effects result in a trade-off that defines an optimal discharge rate (0.1 mA cm -2 ) for maximizing cycle life. This study provides a new mechanistic perspective on discharge-driven processes in solid-state LOBs and offers practical guidelines for performance optimization in future high-energy battery systems.

Discharge current density↗

DOE OSTI2026

Spatiotemporal Dynamics of the Relative Abundance of Soil Nutrient‐Degrading Enzyme‐Encoding Genes Across Continental US Ecoregions

Understanding the spatiotemporal patterns in the relative abundance of soil extracellular enzyme‐encoding genes is critical for predicting microbial responses to environmental change and their potential role in nutrient cycling. Yet, integrating novel metagenomic observations with spatiotemporal environmental gradients to infer regional patterns and future trajectories has remained unclear. To address this gap, we applied a machine learning (ML) approach, integrating soil metagenomic data with environmental variables—soil properties, topography, vegetation, and climate—to predict the relative abundance of enzyme‐encoding genes for soil carbon (C), nitrogen (N), and phosphorus (P) across surface soils of the continental United States. We assessed potential responses under future emission scenarios (SSP2‐4.5 and SSP5‐8.5) by comparing a baseline (1985–2014) to a future period (2071–2100). The ML model explained 57%–63% of baseline variation. Precipitation was identified as the most influential factor for the relative abundance of C‐ and N‐degrading enzyme‐encoding genes, while slope length, representing horizontal distance that water can travel downslope, was the primary driver for P‐degrading enzyme‐encoding genes abundance. Projections revealed spatially heterogeneous shifts across continental US ecoregions: the relative abundance of C‐ and N‐degrading enzyme‐encoding genes decreased in wetter ecoregions and increased in drier ecoregions under future climate, while P‐degrading enzyme‐encoding genes abundance decreased significantly in semiarid and Mediterranean ecoregions. This study demonstrates the utility of metagenomic data for mapping soil genetic potential and predicting its regional response to environmental change, to inform ecosystem management strategies.

extracellular enzyme-encoding genes↗

DOE OSTI2024

Localization of proteins involved in the biogenesis and repair of the photosynthetic apparatus to thylakoid subdomains in Arabidopsis

Abstract Thylakoid membranes in chloroplasts and cyanobacteria harbor the multisubunit protein complexes that catalyze the light reactions of photosynthesis. In plant chloroplasts, the thylakoid membrane system comprises a highly organized network with several subcompartments that differ in composition and morphology: grana stacks, unstacked stromal lamellae, and grana margins at the interface between stacked and unstacked regions. The localization of components of the photosynthetic apparatus among these subcompartments has been well characterized. However, less is known about the localization of proteins involved in the biogenesis and repair of the photosynthetic apparatus, the partitioning of proteins between two recently resolved components of the traditional margin fraction (refined margins and curvature), and the effects of light on these features. In this study, we analyzed the partitioning of numerous thylakoid biogenesis and repair factors among grana, curvature, refined margin, and stromal lamellae fractions of Arabidopsis thylakoid membranes, comparing the results from illuminated and dark‐adapted plants. Several proteins previously shown to localize to a margin fraction partitioned in varying ways among the resolved curvature and refined margin fractions. For example, the ALB3 insertase and FtsH protease involved in photosystem II (PSII) repair were concentrated in the refined margin fraction, whereas TAT translocon subunits and proteins involved in early steps in photosystem assembly were concentrated in the curvature fraction. By contrast, two photosystem assembly factors that facilitate late assembly steps were depleted from the curvature fraction. The enrichment of the PSII subunit OE23/PsbP in the curvature fraction set it apart from other PSII subunits, supporting the previous conjecture that OE23/PsbP assists in PSII biogenesis and/or repair. The PSII assembly factor PAM68 partitioned differently among thylakoid fractions from dark‐adapted plants and illuminated plants and was the only analyzed protein to convincingly do so. These results demonstrate an unanticipated spatial heterogeneity of photosystem biogenesis and repair functions in thylakoid membranes and reveal the curvature fraction to be a focal point of early photosystem biogenesis.

Chotewutmontri, Prakitchai↗

DOE OSTI2023

Improving evapotranspiration computation with electrical resistivity tomography in a maize field

Abstract Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗