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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Polarimetric Radar Variables in Snowfall at Ka- and W-Band Frequency Bands: A Comparative Analysis

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (ZDR) specific differential phase shift (K DP ) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, KDP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

42 ENGINEERING↗
DOE OSTI2021

Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS)

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility.

Krishnan, Venkat↗
DOE OSTI2021

Emission Inventories from Natural Gas Storage Facilities using Regional Frequency Comb Laser Monitoring and Aircraft Flyovers. Final Report

The project centers around a ground-based regional methane sensor developed by the CU/NIST team members under the DOE ARPA-E MONITOR program, and sophisticated aircraft measurement techniques developed by the UCD/Scientific Aviation team (responsible for a recent Science publication quantifying the Aliso Canyon storage field release). The dual frequency-comb spectrometer is an invisible, eye-safe laser capable of measuring atmospheric methane concentrations along beam paths 1+ miles in length with high precision and stability (<1 ppb methane over 1 mile). The CU/NIST team has developed a unique approach to using a single, central spectrometer to locate and size methane emissions as small as 6 scfh from specific gas field structures within the 1+ mile range of the laser. Deployment involves the stationing of small cubic mirrors at strategic locations across the gas storage site. The mirrors direct light from the spectrometer back to a detector, where methane concentrations are recorded based on light absorption at specific wavelengths. The measurements are coupled with high resolution gas transport models based on meteorological measurements (wind, etc.) to determine the precise location and emission rate of methane sources. The calibration-free and continuous nature of dual frequency-comb spectrometer measurements means that a large area can be monitored continuously for temporal variability of emissions over long periods of time. The aircraft measurements involve spiral flights around storage facilities with a sensitive ethane/methane measurement package. Upwind/downwind concentration comparisons and wind data provide total facility emissions data. During this project, a new micrometeorological package was integrated onto the Scientific Aviation aircraft to provide even greater emissions quantification capability. In this project, the ground-based measurement system was deployed for 11 months (to capture seasonal variability) at a West Coast storage facility, together with a campaign of twice monthly aircraft total facility emissions flights. The data from these two modalities was combined to quantify the methane emissions from the facility with first-of-its-kind temporal and spatial detail. Concurrent with this deployment, the aircraft team performed flights to quantify emissions at a wider array of previously un-surveyed storage sites. The ground-based measurement system was then moved to an additional site of differing total storage and delivery capacity. Aircraft mass balance flights continued, repeatedly surveying (twice monthly) this site, as well as surveying a large number of previously un-assessed sites spanning a variety of size, reservoir type and age. Assessment of ground-based, temporally and spatially detailed methane emissions information alongside aircraft-derived methane total facility emissions information led to an improved understanding of emissions, relevant for inventories of the natural gas storage sector. In particular, this work provided temporal detail (seasonal of emissions and frequency of leaks) to stakeholders and personnel responsible for updates to the EPA’s GHGI. The impact of the proposed work has been a dramatic improvement in the temporal, spatial, and site- and type- specific detail and quantification of emissions inventories for the natural gas storage sector. This work directly benefits the EPA’s GHGI, directly ameliorates the environmental impacts and public health and safety of the natural gas storage sector, and aids policymakers and industry to make sound choices with respect to management and regulation.

03 NATURAL GAS↗
DOE OSTI2023

Understanding the Shift of Drivers of Soil Erosion and Sedimentation Based on Regional Process-Based Modeling in the Mississippi River Basin During the Past Century

Soil erosion and sedimentation problems remain a major water quality concern for making watershed management policies in the Mississippi River Basin (MRB). It is unclear whether the observed decreasing trend of stream suspended sediment loading to the mouth of the MRB over the last eight decades truly reflects a decline in upland soil erosion in this large basin. Here, for this work, we improved a distributed regional land surface model, the Dynamic Land Ecosystem Model, to evaluate how climate and land use changes have impacted soil erosion and sediment yield over the entire MRB during the past century. Model results indicate that total sediment yield significantly increased during 1980–2018, despite no significant increase in annual precipitation and runoff. The increased soil erosion and sediment yield are mainly driven by intensified extreme precipitation (EP). Spatially, we found notable intensified EP events in the cropland-dominated Midwest region, resulting in a substantial increase in soil erosion and sediment yield. Land use change played a critical role in determining sediment yield from the 1910s to the 1930s, thereafter, climate variability increasingly became the dominant driver of soil erosion, which peaked in the 2010s. This study highlights the increasing influences of extreme climate in affecting soil erosion and sedimentation, thus, water quality. Therefore, existing forest and cropland Best Management Practices should be revisited to confront the impacts of climate change on water quality in the MRB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A search for ultrahigh-energy neutrinos associated with astrophysical sources using the third flight of ANITA

The ANtarctic Impulsive Transient Antenna (ANITA) long-duration balloon experiment is sensitive to interactions of ultrahigh-energy (E>10 18 eV) neutrinos in the Antarctic ice sheet. The third flight of ANITA, lasting 22 days, began in December 2014. We develop a methodology to search for energetic neutrinos spatially and temporally coincident with potential source classes in ANITA data. This methodology is applied to several source classes: the potential IceCube-identified neutrino sources TXS 0506+056 and NGC 1068, flaring high-energy blazars reported by the Fermi All-Sky Variability Analysis, gamma-ray bursts, and supernovae. Among searches within the five source classes, one candidate was identified as associated with SN 2015D, although not at a statistically significant level. Finally, we proceed to place upper limits on the source classes. We further comment on potential application of this methodology to more sensitive future instruments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Development of a Beam Halo Monitor

Muons, Inc. proposed improved Residual-Gas luminescent Beam Profile Monitors for Intense Beams by adding novel features including a mirascope, a light collecting device devised in the 16th century by an inventor of the telescope. A modern mirascope consists of 2 paraboloids. Light generated by the beam is collected by the paraboloids and creates a beam image. By placing a lens near the image it is possible to collect almost 100% of the emitted light, up to ten times better than existing fluorescence profilometers. Intense (multi-MW) proton beams pose a challenge for beam profile measurements. Solid-based beam intercepting instrumentation produces unallowable levels of radiation at these high powers. An alternative is to use a zero-or-low mass device such as a residual-gas profile monitor, either through collection of ionization or fluorescence. Fluorescence has an intrinsic advantage over the usual collection of ionized electrons in that it is not affected by the strong and variable electric and magnetic fields created by the beam that can distort profiles and make calibration difficult. For this reason, we proposed the fluorescence technique using the mirascope and other methods to enhance light collection and versatility by modifying the residual gas and its spatial distribution. In Phase I, we designed a mirascope and its electronics for commissioning and beam tests in a proposed Phase II. The design was based on optical simulations done in Phase I, and a physics run plan was developed for optimizing and testing. The Phase II experimental site and program have been planned and our goal is to produce a universal low cost Mirascope Residual-Gas Luminescent Beam Profile Monitor that can replace all other profile monitors currently used in accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗
DOE OSTI2026

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗
DOE OSTI2023

Response of Extreme Rainfall to Atmospheric Warming and Wetting: Implications for Hydrologic Designs Under a Changing Climate

Understanding the processes of rainfall extremes and their response to anthropogenic climate change is pivotal for improved adaptation of unprecedented flood hazards around the world. Here we take the record-breaking 20 July 2021 storm over central China as an example. We investigate the response of this particular storm to atmospheric warming (i.e., increase in air temperature) and wetting (i.e., increase in atmospheric moisture content) based on a series of convection-permitting model simulations. Our results show non-monotonic changes of the space-time rainfall variability to either increased temperature or atmospheric moisture content. The most extreme rain rate is produced when relative humidity is increased by 20~40 % or temperature is increased by less than 2°C. The non-monotonic rainfall response is more clearly revealed at fine spatial (100-1000 km 2 ) and temporal scales (less than 6 hours) rather than over the entire domain (~10 4 km 2 ) and aggregated over the storm duration (around two days). This is mainly attributable to the distinct feedbacks from atmospheric dynamics (i.e., moisture convergence and interaction with regional topography) rather than regulated by thermodynamic changes alone. Furthermore, atmospheric warming poses notable changes in the vertical structure of storm cells, contributing to reduced areal reduction factors at small spatial scales and short durations, while atmospheric wetting additionally modifies storm evolution properties. Our modeling analyses challenge the existing practices for hydrologic designs under a changing climate, highlighting particular vulnerability for cities or small basins to short-duration rainfall extremes and the resultant flash flood hazards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interactions between macro‐ and micro‐climate: Effects on phenolic compound production in Nardus stricta at high elevations

Abstract Phenolic compounds are key to plant defence, offering protection as antioxidants, UV shields, and antimicrobials. Their production is largely shaped by environmental conditions. It is believed that plants at lower elevations increase phenolic content to counter herbivory, while those at higher elevations rely on phenolics to manage abiotic stresses, such as climate variability. Microhabitat warming also affects phenolic levels, but responses differ, depending on broader climatic contexts: plants in warmer, lower‐elevation environments show limited adaptability, whereas high‐elevation plants demonstrate greater plasticity. Despite the importance of these environmental interactions, many small‐scale abiotic studies lack sufficient spatial replication across broader gradients like elevation or latitude, while large‐scale studies frequently overlook microscale factors. This study investigated the effects of macroclimate factors and microhabitat warming on phenolic production in Nardus stricta across five semi‐natural grassland sites (1546–1875 m a.s.l.) in Portugal's Serra da Estrela. Warming was simulated using open‐top chambers over two growing seasons, after which leaf samples were analysed for phenolic compounds, and soil nutrients were measured. The N. stricta plants at the highest elevation site contained significantly higher leaf flavonoid concentrations. Microhabitat warming led to a significant decrease in flavonoid concentrations, but only at the highest elevation site. These effects occurred independently of soil nutrient levels, suggesting direct thermal effects or stress responses might be involved. Our findings highlight the complex interactions between macro‐ and microenvironmental factors in shaping plant chemistry, underscoring critical considerations for plant resilience in the face of climate change. This understanding is essential for developing strategies to support plant and ecosystem adaptation to changing climates.

Moreira, X. [Misión Biológica de Galicia (MBG‐CSIC↗
DOE OSTI2024

Rapid Optimization of Total Variation with Applications in Imaging, Additive Manufacturing, and Qualification

Total Variation optimization penalizes the gradient of a control variable or state. While this work focuses on image processing in particular, it has also found applications in inverse problems and topology optimization. In image processing, the goal is to maintain faithfulness to the original image while denoising and/or deblurring. Additionally, bilevel optimization over the spatially varying regularization weights can illuminate interfaces such as damage regions and other anomalies. We will address two fundamental challenges with TV-optimization: (i) the typical slow convergence of existing TV-optimization methods, and (ii) the selection of spatially varying TV parameters to promote interface detection. Additionally, we will apply such techniques to image data collected in additive manufacturing. In said context, stochasticity in build events induces flaws in the manufactured piece, compromising the integrity of said part. There is a critical need for in-situ monitoring to spot anomalies once they form, and in this setting we apply our total variation and hyperparameter solvers. We will develop a customized algorithm based on for extreme-scale TV-optimization that achieves super-linear or quadratic-convergence, a critical property for real-time, image-by-image analysis. A worst-case outcome is a preprocessing step that enhances image quality in-situ, specifically for out-of-focus and noisy images.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulations of divertor designs that spatially separate power and particle exhaust using mid-leg divertor particle pumping

Predictive design modeling of a Dissipation-Focused Divertor for future operation in DIII-D reveals that increasing the poloidal distance of the pump duct entrance from the target surface along the low-field side divertor baffle increases neutral compression and modifies the spatial distribution of power dissipation. With a divertor pump located mid-leg between the target and the X-point, SOLPS-ITER boundary plasma simulations without drifts predict the formation of a dense neutral cloud near the target with > 30x higher neutral compression in detachment, a more stable detachment front located further from the target, and ~25% lower outer midplane separatrix density required for detachment onset, compared to a pump located in the scrape-off layer at the target surface. Up to 19 MW of power flowing into the divertors is modeled using the following two numerical implementations for particle pumping: a specified fraction of particles incident on variable wall sections of the plasma grid is removed from the computational domain (so-called albedo pumping), and a pump duct is modeled which includes dynamics of kinetic neutrals in the duct. The simulations show that the detachment front is located between the divertor target and the X-point and is relatively stable near the pump entrance, without a strong dependence on gas puff rate or injected power. The mid-leg pump design spatially separates the two primary functions of a divertor (power handling and particle exhaust), with the majority of power dissipation occurring near the target plate and particle exhaust taking place further upstream. The benefit of enhanced dissipation using mid-leg pumping comes at the cost of a higher outer midplane separatrix density for a given amount of particle injection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Spatial and Temporal Interpolation Analysis Process of Shock Loading

The following document serves to describe the current process that is utilized by W-13 analysts to approximate the pressure-time boundary condition seen by a test object from shock tube loading. The intent of this report is to capture the current capability and to encourage continued growth and development. Information on the required input variables, mapping process, and generated output information is covered in the following sections. Throughout the document, gaps and weaknesses of the mapping process are noted to encourage future development efforts.

42 ENGINEERING↗
DOE OSTI2024

Multizone Modeling of Black Hole Accretion and Feedback in 3D GRMHD: Bridging Vast Spatial and Temporal Scales

Simulating accretion and feedback from the horizon scale of supermassive black holes (SMBHs) out to galactic scales is challenging because of the vast range of scales involved. Elaborating on H. Cho et al., we describe and test a "multizone" technique, which is designed to tackle this difficult problem in three-dimensional general relativistic magnetohydrodynamic (GRMHD) simulations. While short-timescale variability should be interpreted with caution, the method is demonstrated to be well-suited for finding dynamical steady states over a wide dynamic range. We simulate accretion on a nonspinning SMBH ($a\ast$ = 0) using initial conditions and the external galactic potential from a large-scale galaxy simulation and achieve a steady state over eight decades in radius. As found in H. Cho et al., the density scales with radius as ρ ∝ r –1 inside the Bondi radius R B , which is located at R B = 2 × 10 5 r g (≈60 pc for M87), where r g is the gravitational radius of the SMBH; the plasma-β is ~ unity, indicating an extended magnetically arrested state; the mass accretion rate $\dot{M}$ is ≈1% of the analytical Bondi accretion rate ${\dot{M}}_{{\rm{B}}};$ and there is continuous energy feedback out to ≈100R B (or beyond > kpc) at a rate $\approx 0.02\dot{M}{c}^{2}$. Surprisingly, no ordered rotation in the external medium survives as the magnetized gas flows to smaller radii, and the final steady solution is very similar to when the exterior has no rotation. Using the multizone method, we simulate GRMHD accretion over a wide range of Bondi radii, R B ~ 10 2 –10 7 r g , and find that $\dot{M}/{\dot{M}}_{{B}}\approx {({R}_{{B}}/6\,{r}_{g})}^{-0.5}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗
DOE OSTI2026

Ammonia in northeast Colorado is increasing, rising most quickly in regions close to confined animal feeding operations

The Colorado Front Range urban corridor and nearby agricultural operations are important source regions of atmospheric ammonia (NH 3 ). Upslope flows periodically transport these emissions into Rocky Mountain National Park (RMNP), located 50 km west of the urban corridor, where wet and dry deposition of excess reactive nitrogen (N) impacts ecosystems. Here, we use a combination of in situ passive NH 3 measurements and NH 3 vertical column density retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) to assess variability and changes in NH 3 across three land use categories in the northeast Colorado source region (agricultural, urban, and remote) during the period 2013-2023. A strong seasonal cycle is present across the region with increased NH 3 during summer months. Elevated NH 3 is spatially correlated with the number of permitted animal units in confined animal feeding operations (CAFOs) within 12 km. Ground-level NH 3 concentrations are strongly positively correlated with monthly gridded IASI satellite column densities. Satellite retrievals reveal an increasing trend in NH 3 column amounts of ∼3% per year in agricultural and ∼2% per year in urban sub-regions. The magnitude of the trend observed in NH 3 columns averaged over the agricultural sub-region is > 3 times larger than observed near and over Denver. The largest increases in NH 3 are closely aligned with the distribution of CAFOs. Reductions in particle sulfate associated with declining sulfur dioxide (SO 2 ) emissions could account for only ∼0.1% per year increase in gaseous NH 3 . Wildfire smoke across the region has increased but appears unlikely to explain the majority of the observed NH 3 increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Coupled Deep Learning Model for Estimating Surface NO 2 Levels from Remote Sensing Data: 15-Year Study Over the Contiguous United States

This study proposes a novel two-step deep learning (DL) model for estimating surface NO 2 concentrations using satellite data over the contiguous United States (CONUS) from 2005 to 2019. The first phase of the model uses partial convolutional neural network (PCNN), an advanced DL model that accurately imputes gaps between surface NO 2 stations and creates 5,478 daily-mean NO 2 grids (PCNN-NO 2 ) of the 2005-2019 period over the study area. We then feed the PCNN-NO 2 , along with other predictor variables, into a deep neural network (DNN) to estimate surface NO 2 levels, achieving exceptional performance with a correlation coefficient of 0.975 to 0.978, a mean absolute bias of 0.99 ppb to 1.38 ppb, and a root mean square error of 1.47 ppb to 1.97 ppb. Spatial cross-validation results also indicate strong spatial performance of PCNN-DNN surface NO 2 estimates. In addition to its accurate estimates, the PCNN-DNN model consistently generates estimated NO 2 grids without any missing values, improving the quality of various applications such as emission reduction strategies and public health studies. Between 2005 and 2019, the 5,478 daily estimated NO 2 grids over the CONUS reveal significant reductions in NO 2 levels in fourteen major urban environments: Washington D.C. (-43%), New York (-45%), Los Angeles (-38%), Chicago (-25%), Boston (-43%), Houston (-34%), Dallas (-40%), Philadelphia (-41%), Phoenix (-38%), Detroit (-20%), Denver (-23%), Atlanta (-0.7%), Cincinnati (-38%), and Pittsburgh (-56%). Furthermore, the study shows that the denser urban regions that in-situ stations are installed in, the higher the difference between in-situ observations and regional-mean NO 2 levels.

54 ENVIRONMENTAL SCIENCES↗