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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Large-eddy Simulations of Spray Variability Effects on Flow Variability in a Direct-injection Spark-ignition Engine Under Non-combusting Operating Conditions

Large-eddy Simulations (LES) have been carried out to investigate spray variability and its effect on cycle-to-cycle flow variability in a direct-injection spark-ignition (DISI) engine under non-reacting conditions. Initial simulations were performed of an injector in a constant volume spray chamber to validate the simulation spray set-up. Comparisons showed good agreement in global spray measures such as the penetration. Local mixing data and shot-to-shot variability were also compared using Rayleigh-scattering images and probability contours. The simulations were found to reasonably match the local mixing data and shot-to-shot variability using a random-seed perturbation methodology. After validation, the same spray set-up with only minor changes was used to simulate the same injector in an optically accessible DISI engine. Particle Image Velocimetry (PIV) measurements were used to quantify the flow velocity in a horizontal plane intersecting the spark plug gap. The engine was operated in a skip-fired operating mode and comparisons focused on cycles that included fuel injection, but no spark event and therefore no combustion. 105 total LES engine cycles were simulated using a parallel cycle simulation approach and 3 different perturbation methods in an attempt to isolate the effects of shot-to-shot spray variability and the initial turbulent flow field as well as their interaction effects on overall engine CCVs. The experimental mean and standard deviations were reasonably well matched by the simulations, though quantitative comparisons near the injection event during the intake stroke were difficult due to the high uncertainty in the PIV measurements at these crank angles. The 3 simulation perturbation methods resulted in very similar results, though further analysis found the current parallel cycle approach may be limiting the ability of the simulations to isolate the spray and flow effects.

Cycle-to-cycle Variability↗
DOE OSTI2020

A regional nuclear conflict would compromise global food security

A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of a Nitrogen and Magnesium Oxide based Class A, B & D Suffocating Fire System (SFSS) for Gloveboxes

Testing related to the development and performance of a “Proof of Concept” Nitrogen/Magnesium Oxide Suffocating Fire System (SFSS) was conducted at Fire and Pump Service Group (FPSG) located in Rancho Dominguez, California. The SFSS Engineering Team (SFSSET), consisting of FPSG and Los Alamos National Laboratory (LANL) personnel researched, developed a prototype, and conducted testing to determine effective means to deliver magnesium oxide (MgO) sand into a glovebox (GB) in a class D fire event. The prototypes development also established the effective coverage area of a magnesium oxide suppression system as well as demonstrated that the GB inert atmosphere could be maintained during and after the release of the MgO sand to control Class A, B and D fires. Previous testing conducted on nitrogen based SFSS provided evidence that the nitrogen based SFSS controlled Class A and B fires (Ralph Clayton, Los Alamos National Laboratory, Brandon Troc and Frank Broidy, Fire and Pump Service Group 2020).Final testing was conducted within a mock GB capable of simulating an inert glovebox atmosphere. Testing demonstrated that the inert atmosphere can be maintained during and after discharge of the MgO sand over a coverage area.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Modelling of transport processes in concrete exposed to elevated temperatures – An alternative formulation for sorption isotherms

There is a significant need to understand, analyse and assess moisture transport in cementitious materials exposed to elevated temperatures in order to confidently predict the behaviour and ultimately the development of damage in safety critical applications such as nuclear reactor vessels, structures exposed to fire and well bore grouts. In view of this need a rigorous and robust formulation to describe water retention curves (sorption isotherms) as a function of temperature based on the evolution of physical parameters is presented. The model formulation is successfully validated against independent sets of experimental data up to temperatures of 80 °C. It is then further validated under isothermal drying conditions and then high temperature conditions through the numerical reproduction of laboratory experiments following implementation in a fully coupled hygro-thermo-mechanical finite element model. The new formulation is found to work well under a variety of conditions in a variety of cementitious material types.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics

Core Ideas Development of a 300‐km 2 mountainous headwater testbed began in 2016 in the East River. The testbed can be used to explore how watershed changes impact downgradient water availability and quality. System‐of‐system, scale‐adaptive approaches can potentially improve watershed dynamics simulation. We have new approaches to monitor and simulate water partitioning and system responses. The East River watershed has been developed as a “community” testbed. Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrology‐driven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300‐km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system‐of‐systems perspective and a scale‐adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long‐term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effect of Split-Injection Strategies on Engine Performance and Emissions under Cold-Start Operation

The recently concluded partnership for advancing combustion engines (PACE) was a US Department of Energy consortium involving multiple national laboratories focused on addressing key efficiency and emission barriers in light-duty engines. Generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior was a major pillar in this program. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon, and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster three-way catalyst light-off, and engine out emissions during that period. In this study, engine performance, emissions, and catalyst warmup potential were monitored while the engine was operated using a single direct injection (baseline case) as well as a two-way-equal-split direct injection strategy. These injection strategies were analyzed at a range of cold-start-operation relevant retarded spark timings of up to 25 degrees after top dead center of firing (dATDCf). A stoichiometric 2-bar NIMEP steady-state condition was used for all cases to simulate cold-start operation. Significant improvement in engine stability was observed with the two-way-split injection strategy at the retarded spark timings allowing for up to 2.5x increase in exhaust heat rate when engine operation is stability constrained. Similar fuel-loss-to-oil trends with exhaust heat rate were observed for both single and two-way-split injection strategies. However, the two-way split injection was observed to produce higher NOx emissions per unit exhaust heat rate. A single data point run with three-way-split direct injection at a very retarded spark-timing of 30 dATDCf pointed to further improvements in engine stability and reduction in fuel-loss-to-oil as compared to single injection strategy. Engine stability decreased as spark timing was initially retarded with a single injection but was observed to plateau and stabilize beyond spark timing of 10 dATDCf. Finally, for the two-way-split-injection strategy, retarding the start of injection (SOI) timing of the second injection led to a decrease in engine stability as well as an increase in soot emissions.

42 ENGINEERING↗
DOE OSTI2019

Optical properties and radiative forcing of fractal-like tar ball aggregates from biomass burning

Tar balls are frequently found in slightly aged biomass burning plumes. They are spherical in shape, have diameters between ~100 and 300 nm, are amorphous and composed mostly of oxygen and carbon. Tar balls are light absorbing and considered to be a component of brown carbon. Tar balls have been typically reported and analyzed as individual spheres; however, in a recent study, we reported the presence of significant fractions of fractal-like tar ball aggregates in fire plumes from different geographical locations. Aggregation affects the optical properties of particles; therefore, we use T-Matrix and Lorenz-Mie simulations to explore the effects of aggregation on the tar balls’ optical properties in the 350 – 1150 nm wavelength range. We also evaluate the effects of different index of refraction values available from the literature, different monomer numbers, and monomer sizes, as these are key factors determining the aggregates optical properties. Furthermore, we estimate the direct radiative forcing for low and high surface albedos. The single scattering albedo of aggregates exceed by up to 77% that of individual tar balls. The hemispherical upscatter fraction of tar ball aggregates are more than 100% larger than for individual tar balls in many cases. The top of the atmosphere simple forcing efficiency over dark surfaces shows large variabilities with differences up to ~53% between the tar ball aggregates and individual tar balls. These results demonstrate that aggregation of tar balls can have a significant impact on their optical properties and radiative forcing.

Tar balls, aggregates, brown carbon, biomass burni↗
DOE OSTI2013

Dynamic Modeling and Control Studies of a Two-Stage Bubbling Fluidized Bed Adsorber-Reactor for Solid-Sorbent CO{sub 2} Capture

A one-dimensional, non-isothermal, pressure-driven dynamic model has been developed for a two-stage bubbling fluidized bed (BFB) adsorber-reactor for solid-sorbent carbon dioxide (CO{sub 2}) capture using Aspen Custom Modeler® (ACM). The BFB model for the flow of gas through a continuous phase of downward moving solids considers three regions: emulsion, bubble, and cloud-wake. Both the upper and lower reactor stages are of overflow-type configuration, i.e., the solids leave from the top of each stage. In addition, dynamic models have been developed for the downcomer that transfers solids between the stages and the exit hopper that removes solids from the bottom of the bed. The models of all auxiliary equipment such as valves and gas distributor have been integrated with the main model of the two-stage adsorber reactor. Using the developed dynamic model, the transient responses of various process variables such as CO{sub 2} capture rate and flue gas outlet temperatures have been studied by simulating typical disturbances such as change in the temperature, flowrate, and composition of the incoming flue gas from pulverized coal-fired power plants. In control studies, the performance of a proportional-integral-derivative (PID) controller, feedback-augmented feedforward controller, and linear model predictive controller (LMPC) are evaluated for maintaining the overall CO{sub 2} capture rate at a desired level in the face of typical disturbances.

42 ENGINEERING↗
DOE OSTI2025

FIRE: A Failure-Adaptive RL Framework for Edge Computing Migrations

In edge computing, users' service profiles are migrated between edge servers due to user mobility. Reinforcement Learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE's boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. Here, we extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures.

Edge computing↗
DOE OSTI2025

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Projection of Future Fire Emissions Over the Contiguous US Using Explainable Artificial Intelligence and CMIP6 Models

Abstract Increasing temperature and water cycle changes due to warming climate may increase the frequency and intensity of wildfires. Fire emission projections are useful for informing strategies for adaptation and mitigation of fire impacts on societies and ecosystems. Here, we construct a neural network (NN) model explained by the Shapley Additive explanation to predict fire PM 2.5 emissions change and understand their drivers over the contiguous US (CONUS) in the mid‐21st century under a high greenhouse gas emissions scenario (SSP5‐8.5). Using future meteorology and leaf area index (LAI) simulated by eight global climate models from the Coupled Model Intercomparison Project Phase 6, future population density, and present‐day land use and land cover (LULC) as input to the NN model, the total fire PM 2.5 emissions over CONUS are projected to increase by 4%–75% (model spread). Among different regions, fire emissions in the western US are projected to increase more significantly in June‐July‐August than in other seasons and regions, with the median ratios of future to present‐day fire emissions ranging from 1.67 to 2.86. The increases in fire emissions are mainly driven by increasing normalized temperature (23%–29%) and decreasing soil moisture (2%–10%) in the future. When future LULC change is considered, the projected fire emissions further increase by 58%–83% over the western US compared to projections without LULC change because of future increases in vegetation fraction. The results highlight the important role of warmer temperature, decreasing soil moisture, and LULC change in increasing fire emissions in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗
DOE OSTI2014

SU-E-T-512: Electromagnetic Simulations of the Dielectric Wall Accelerator

Purpose: To characterize and parametrically study the key components of a dielectric wall accelerator through electromagnetic modeling and particle tracking. Methods: Electromagnetic and particle tracking simulations were performed using a commercial code (CST Microwave Studio, CST Inc.) utilizing the finite integration technique. A dielectric wall accelerator consists of a series of stacked transmission lines sequentially fired in synchrony with an ion pulse. Numerous properties of the stacked transmission lines, including geometric, material, and electronic properties, were analyzed and varied in order to assess their impact on the transverse and axial electric fields. Additionally, stacks of transmission lines were simulated in order to quantify the parasitic effect observed in closely packed lines. Particle tracking simulations using the particle-in-cell method were performed on the various stacks to determine the impact of the above properties on the resultant phase space of the ions. Results: Examination of the simulation results show that novel geometries can shape the accelerating pulse in order to reduce the energy spread and increase the average energy of accelerated ions. Parasitic effects were quantified for various geometries and found to vary with distance from the end of the transmission line and along the beam axis. An optimal arrival time of an ion pulse relative to the triggering of the transmission lines for a given geometry was determined through parametric study. Benchmark simulations of single transmission lines agree well with published experimental results. Conclusion: This work characterized the behavior of the transmission lines used in a dielectric wall accelerator and used this information to improve them in novel ways. Utilizing novel geometries, we were able to improve the accelerating gradient and phase space of the accelerated particle bunch. Through simulation, we were able to discover and optimize design issues with the device at low cost. Funding: Morgridge Institute for Research, Madison WI; Conflict of Interest: Dr. Mackie is an investor and board member at CPAC, a company developing compact accelerator designs similar to those discussed in this work, but designs discussed are not directed by CPAC. Funding: Morgridge Institute for Research, Madison WI; Conflict of Interest: Dr. Mackie is an investor and board member at CPAC, a company developing compact accelerator designs similar to those discussed in this work, but designs discussed are not directed by CPAC.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Synthesis of Post-fire Monitoring Activities in the Great Basin Desert, Mojave Desert, and Transition Zones

In the deserts of the American Southwest, fire return intervals of centuries to millennia are being replaced by fire return intervals of decades. This increased burn frequency has implications for post-closure management and long-term stewardship for Soils Corrective Action Units (CAUs) and Corrective Action Sites (CASs) on the Nevada National Security Site (NNSS), Tonopah Test Range, and Nevada Test and Training Range for which the U.S. Department of Energy (DOE), Environmental Management-Nevada (EM-NV) is responsible. For many CAUs and CASs, where closure-in-place alternatives were implemented or are being considered, there is a chance that these sites could burn over while they still pose a risk to the environment or human health given the long half-lives of some of the radionuclide contaminants of concern (COCs) (Shafer et al., 2007; Shafer and Gomes, 2009). Although it would have been ideal to conduct a fire-related study at a radionuclide contaminated site on the NNSS to determine how contaminated soils are transported post-fire, it was more practical to examine fires in environments analogous to where Soils Activity CAUs and CASs exist. Therefore, a series of studies were initiated at three radiologically uncontaminated analog sites to better understand the possible effects of wildfire on erosion and sediment transport by wind and water should vegetation at contaminated sites burn at the NNSS. The studies took place at the sites of the Gleason Fire, a prescribed burn that occurred near Ely, Nevada, which is in the Great Basin ecoregion; the White Rock Fire that occurred near Mesquite, Nevada, which is in the Mojave Desert ecoregion; and the Jacob Fire that occurred near Hiko, Nevada, in the transitional zone between the Great Basin Desert and the Mojave Desert. Each site was representative of one of the three ecoregions found on the NNSS. Erosion and vegetation characteristics were measured multiple times post-fire on both burned and unburned test plots at these study sites to compare and monitor the effects of fire over time. However, at the Mojave Desert site, there was an additional burn from nearly 25 years ago that was also compared with the more recent burned areas from 2013. Also, the time elapsed after the fire and the time when sampling began differed among the ecoregions. For example, at the Great Basin site, samples were collected prior to the fire and less than one month after the fire, whereas data collected at the Mojave Desert site did not occur until 22 months after the fire. The differences between the sample measurements and the time that elapsed after the fire may contribute to the variability in the data and the interpretations of the data. Runoff and water erosion were quantified through a series of rainfall and runoff simulation tests in which controlled amounts of water were delivered to the soil surface. Runoff data were collected from different microhabitats (e.g., undercanopies, interspace soils, ridges, and drainage areas). The data showed soil hydrophobicity (i.e., water repellency) on the Great Basin site for up to 12 months after the fire. The soil structure remained changed and weaker on the burned areas compared with the unburned areas for the three-year study period. Although runoff data at both the Great Basin site and transition zone site were highly variable, the post-fire runoff potential did not generally increase at either location after three years of monitoring. Mojave runoff did not differ much between fire ages or between burned and unburned areas, possibly because of the amount of vegetation growing on all three surfaces and because the fire intensity was likely lower relative to other ecoregions due to the amount of space between plants. Additionally, the measurements conducted on the Mojave fire occurred several years after the fire had burned and not within several months of the burn, which may also account for the lack of differences in runoff between burned and unburned locations. Wind erosion was assessed and quantified with a Portable In-Situ Wind ERosion Lab (PI-SWERL) on both the burned and unburned soils of different microhabitats (e.g., ridges, drainages, interspaces between plants, and plant undercanopies). Estimates of emissions (e.g., particulate matter with aerodynamic diameters less than or equal to 10 micrometers, or PM10) at different wind speeds were collected and filter samples were analyzed for chemical composition. The measurements among the fires were similar and the results of the wind erosion measurements indicate that there were seasonal influences on many parameters, but the potential for PM10 windblown dust emissions was higher on burned areas compared with unburned areas. Among the burned areas, drainages produced the most dust emissions, whereas burned ridges were the least emissive. Emissions at the Mojave site and transition zone site were similar between burned and unburned areas approximately three years after the respective fires. Emissions remained much greater on burned soils at the Great Basin site. However, site selection may have also contributed to the differences of emissions among the three study locations. Post-fire vegetation responses were documented for three years following each fire in different microhabitats (e.g., ridge, drainage, undercanopy, and interspace) at the Great Basin and transition zone sites. In 2013, at the Mojave fire site, random permanent plots were established in newly burned areas, areas that burned approximately 25 years ago, and an unburned control area. At each fire site, the regeneration of native plant species dominated the burned areas, but invasive annual grasses were present at each fire site. During the course of each three-year study, the invasive annual grasses increased in density or percentage at both the Great Basin and transition fire sites but not at the Mojave site, where annual invasive grasses remained high throughout the study period. However, the chronosequence data from the Mojave site indicate a transition to different invasive grass species with time. The post-burn vegetation at all three ecoregions is still in the early stages of succession, and shrub size should increase over time and shrub density should decrease over time. However, the recovery of the plant communities to pre-burn compositions may not occur for decades or centuries, or may not occur because of changes in climate and the presence of invasive annual grasses. Results from the three study locations suggested that contaminated soils on the NNSS that experienced wildfire had the potential for soil erosion and transport of contaminated soils. Both wind and soil runoff studies indicated that locations in the Great Basin and transition zone ecoregions were more susceptible to erosion than the Mojave Desert ecoregion, but the highest levels of erosion occurred during the early portions of the study (the first 24 months) and the Mojave Desert was not measured until 22 months after the burn. Additionally, data from the Great Basin indicated deeper soils may increase susceptibility to wind erosion. Historically, the Great Basin and transition zone ecoregions burned more frequently than the Mojave Desert because of fuel abundance and connectivity—and they continue to burn more frequently, particularly after the introduction of invasive grasses (Davies and Nafus, 2013). However, both ecoregions and the transition zone have burned with extensive, high-severity fires when certain weather and fuel conditions are met. For example, the high abundance and productivity of annual grasses and forbs—which are usually produced by above average winter precipitation—combined with early spring and summer warm, dry conditions. Future climate scenarios predict increased temperatures, variable to reduced precipitation, and larger, more extreme wildfires throughout western North America. These predictions suggest that future fires on the NNSS could increase in frequency, intensity, and severity similar to their analog ecosystems throughout the Great Basin and Mojave Desert (Dennison et al., 2014; Abatzoglou andWilliams, 2016; Westerling, 2016).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Investigation of particle and vapor wall-loss effects on controlled wood-smoke smog-chamber experiments

Here, smog chambers are extensively used to study processes that drive gas and particle evolution in the atmosphere. A limitation of these experiments is that particles and gas-phase species may be lost to chamber walls on shorter timescales than the timescales of the atmospheric processes being studied in the chamber experiments. These particle and vapor wall losses have been investigated in recent studies of secondary organic aerosol (SOA) formation, but they have not been systematically investigated in experiments of primary emissions from combustion. The semi-volatile nature of combustion emissions (e.g. from wood smoke) may complicate the behavior of particle and vapor wall deposition in the chamber over the course of the experiments due to the competition between gas/particle and gas/wall partitioning. Losses of vapors to the walls may impact particle evaporation in these experiments, and potential precursors for SOA formation from combustion may be lost to the walls, causing underestimations of aerosol yields. Here, we conduct simulations to determine how particle and gas-phase wall losses contributed to the observed evolution of the aerosol during experiments in the third Fire Lab At Missoula Experiment (FLAME III). We use the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm coupled with the organic volatility basis set (VBS) and wall-loss formulations to examine the predicted extent of particle and vapor wall losses. We limit the scope of our study to the dark periods in the chamber before photo-oxidation to simplify the aerosol system for this initial study. Our model simulations suggest that over one-third of the initial particle-phase organic mass (41 %) was lost during the experiments, and over half of this particle-organic mass loss was from direct particle wall loss (65 % of the loss) with the remainder from evaporation of the particles driven by vapor losses to the walls (35 % of the loss). We perform a series of sensitivity tests to understand uncertainties in our simulations. Uncertainty in the initial wood-smoke volatility distribution contributes 18 % uncertainty to the final particle-organic mass remaining in the chamber (relative to base-assumption simulation). We show that the total mass loss may depend on the effective saturation concentration of vapor with respect to the walls as these values currently vary widely in the literature. The details of smoke dilution during the filling of smog chambers may influence the mass loss to the walls, and a dilution of ~ 25:1 during the experiments increased particle-organic mass loss by 33 % compared to a simulation where we assume the particles and vapors are initially in equilibrium in the chamber. Finally, we discuss how our findings may influence interpretations of emission factors and SOA production in wood-smoke smog-chamber experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires, including wildfires, harm air quality and essential public services like transportation, communication, and utilities. These fires can also influence atmospheric conditions, including temperature and aerosols, potentially affecting severe convective storms. Here, we investigate the remote impacts of fires in the western United States (WUS) on the occurrence of large hail (size: $\geqslant$ 2.54 cm) in the central US (CUS) over the 20-year period of 2001–20 using the machine learning (ML), Random Forest (RF), and Extreme Gradient Boosting (XGB) methods. The developed RF and XGB models demonstrate high accuracy (> 90%) and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide, particularly in four states (Wyoming, South Dakota, Nebraska, and Kansas). The key contributing variables identified from both ML models include the meteorological variables in the fire region (temperature and moisture), the westerly wind over the plume transport path, and the fire features (i.e., the maximum fire power and burned area). Importantly, the results confirm a linkage between WUS fires and severe weather in the CUS, corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

How well do terrestrial biosphere models simulate coarse-scale runoff in the contiguous United States?

Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated gridded (1 spatial resolution) runoff from six terrestrial biosphere models (TBMs), seven reanalysis products, and one gridded surface station product in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of these 14 estimates with stream gauge data, both as depleted flow and corrected for net withdrawals (2005 only), at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71 to 356 mm yr(-1)) relative to observed continental-scale runoff (209 or 280 mm yr(-1) when corrected for net withdrawals). Across all 14 products 8 exhibit Nash-Sutcliffe efficiency values in excess of 0.8 and three are within 10% of the observed value. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regions although two products are systematically biased across all regions and largely scales with water use. Although gridded composite TBM and reanalysis runoff show some regional similarities, individual product values are highly variable. At the coarse scales used here we find that progress in better constraining simulated runoff requires standardized forcing data and the explicit incorporation of human effects (e.g., water withdrawals by source, fire, and land use change). (C) 2015 Elsevier B.V. All rights reserved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Interannual variability and trends of summertime PM2.5-based air quality in the Intermountain West

Abstract Summertime air quality is a growing public health concern in the populated region of Northern Utah. Whereas winter air pollution is highly linked with local atmospheric temperature inversions associated with upper atmospheric high-pressure and radiational cooling in valleys, the relationship between climate factors and the frequency of poor air quality during summer is still unknown. Analyzing the last 20 years of data, we demonstrated that summertime unhealthy days (as defined by PM2.5 air quality index level) in Northern Utah highly correlate with the number of dry-hot days, wildfire size, and an upper atmospheric ridge over the Northwestern United States. The persistent atmospheric ridge enhances lightning-caused fire burned areas in northwestern states and then transports the wildfire smoke toward Northern Utah. Similarly, climate model simulations confirm observational findings, such as an increasing trend of the upper atmospheric ridge and summertime dry days in the northwestern states. Such metrics developed in this study could be used to establish longer-term monitoring and seasonal forecasting for air quality and its compounding factors, which is currently limited to forecasting products for only several days.

54 ENVIRONMENTAL SCIENCES↗