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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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At least 19 records

Airborne measurements of western U.S. wildfire emissions: Comparison with prescribed burning and air quality implications: Western U.S. Wildfire Emissions

Wildfires emit significant amounts of pollutants that degrade air quality. Plumes from three wildfires in the western U.S. were measured from aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), both in summer 2013. This study reports an extensive set of emission factors (EFs) for over 80 gases and 5 components of submicron particulate matter (PM 1 ) from these temperate wildfires. These include rarely, or never before, measured oxygenated volatile organic compounds and multifunctional organic nitrates. The observed EFs are compared with previous measurements of temperate wildfires, boreal forest fires, and temperate prescribed fires. Furthermore, the wildfires emitted high amounts of PM 1 (with organic aerosol (OA) dominating the mass) with an average EF that is more than 2 times the EFs for prescribed fires. The measured EFs were used to estimate the annual wildfire emissions of carbon monoxide, nitrogen oxides, total nonmethane organic compounds, and PM 1 from 11 western U.S. states. The estimated gas emissions are generally comparable with the 2011 National Emissions Inventory (NEI). However, our PM 1 emission estimate (1530 ± 570 Gg yr -1 ) is over 3 times that of the NEI PM2.5 estimate and is also higher than the PM2.5 emitted from all other sources in these states in the NEI. This study indicates that the source of OA from biomass burning in the western states is significantly underestimated. Additionally, our results indicate that prescribed burning may be an effective method to reduce fine particle emissions.

54 ENVIRONMENTAL SCIENCES↗

Meteorological environments associated with California wildfires and their potential roles in wildfire changes during 1984-2017

California has been seeing more wildfires in recent years, resulting in huge economic losses and threatening human health. Clarifying the meteorological environments of wildfires is foundational to improving the understanding and prediction of wildfires and their impacts. Here, 1535 California wildfires during 1984-2017 are systematically investigated. Based on two key meteorological factors - temperature and moisture anomalies - all wildfires are classified into four groups: hot-dry, hot-wet, cold-dry, cold-wet. Most (~60%) wildfires occurred on hot-dry days. Compositing the large-scale environments of the four groups shows that persistent high pressure and strong northeasterly wind descending from inland favor hot-dry conditions for wildfires. This analysis also reveals an important role of anomalies in southerly onshore flow that supports stronger convection, accompanied by more lightning flashes that provide a triggering mechanism for wildfires under hot-wet conditions. Self-organizing map analysis lends confidence in the large-scale meteorological pattern for dominating hot-dry wildfires in California. Besides wildfire occurrence, wildfire size is also influenced by meteorological anomalies through their magnitudes. Among them, moisture anomaly explains the largest fraction (~69%) of variability in wildfire sizes. Large-scale meteorological anomalies are found to play an important role in the devastating 2018 wildfire season in California. During 1984-2017, wildfire burned area has significantly increased by ~3.6% per year, indicating a doubling of burned area in 2017 relative to 1984, with the trend dominated by hot-dry wildfires in summer. Drying and warming in conjunction with strengthening of the high pressure in summer support more frequent and larger wildfires in California.

58 GEOSCIENCES↗

Impact of Wildfires on Solar Generation, Reserves and Energy Prices

Wildfire seasons in the Western U.S. become more prolonged and intense in recent years bringing significant variability and uncertainty of solar generation. It greatly challenges the bulk power system and electricity market operation managed by California Independent System Operator (CAISO) as California leads both the wildfire records and the solar power integration. This study presents a screening-level analysis of the impact of wildfires on solar generation, operating reserve and energy prices applying historical real-world wildfire and market operation data. To the best of the authors knowledge, it is a first-of-its-kind study and will lay the foundation for market impact quantification and wildfire mitigation strategies design based on projected wildfire activities in future years.

electricity price↗

Using Satellite‐Derived Fire Arrival Times for Coupled Wildfire‐Air Quality Simulations at Regional Scales of the 2020 California Wildfire Season

Abstract Wildfire frequency has increased in the Western US over recent decades, driven by climate change and a legacy of forest management practices. Consequently, human structures, health, and life are increasingly at risk due to wildfires. Furthermore, wildfire smoke presents a growing hazard for regional and national air quality. In response, many scientific tools have been developed to study and forecast wildfire behavior, or test interventions that may mitigate risk. In this study, we present a retrospective analysis of 1 month of the 2020 Northern California wildfire season, when many wildfires with varying environments and behavior impacted regional air quality. We simulated this period using a coupled numerical weather prediction model with online atmospheric chemistry, and compare two approaches to representing smoke emissions: an online fire spread model driven by remotely sensed fire arrival times and a biomass burning emissions inventory. First, we quantify the differences in smoke emissions and timing of fire activity, and characterize the subsequent impact on estimates of smoke emissions. Next, we compare the simulated smoke to surface observations and remotely sensed smoke; we find that despite differences in the simulated smoke surface concentrations, the two models achieve similar levels of accuracy. We present a detailed comparison between the performance and relative strengths of both approaches, and discuss potential refinements that could further improve future simulations of wildfire smoke. Finally, we characterize the interactions between smoke and meteorology during this event, and discuss the implications that increases in regional smoke may have on future meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

WildFire Ignition Resistance Estimator (WildFIRE) Wizard Software Development Report

This report describes the development of a software tool, entitled “WildFire Ignition Resistance Estimator Wizard” (WildFIRE Wizard, Version 2.10). This software was developed within the Wildfire Ignition Resistant Home Design (WIRHD) program, sponsored by the U. S. Department of Homeland Security, Science and Technology Directorate, Infrastructure Protection & Disaster Management Division. WildFIRE Wizard is a tool that enables homeowners to take preventive actions that will reduce their home’s vulnerability to wildfire ignition sources (i.e., embers, radiant heat, and direct flame impingement) well in advance of a wildfire event. This report describes the development of the software, its operation, its technical basis and calculations, and steps taken to verify its performance.

97 MATHEMATICS AND COMPUTING↗

Regional Influence of Aerosol Emissions from Wildfires Driven by Combustion Efficiency: Insights from the BBOP Campaign

Abstract Wildfires are important contributors to atmospheric aerosols and a large source of emissions that impact regional air quality and global climate. In this study, wildfire emissions in the Pacific Northwest region of the United States were characterized using real-time measurements near their sources using an aircraft, and farther downwind from a fixed ground site located at the Mt. Bachelor Observatory (~ 2700 m a.s.l.). The characteristics of aerosol emissions were found to depend strongly on the modified combustion efficiency (MCE), a qualitative index of the combustion processes of a fire. Organic aerosol emissions had negative correlations with MCE, whereas the carbon oxidation state of organic aerosol increased with MCE. The relationships between the aerosol properties and MCE were consistent between fresher emissions (~1 hour old) and emissions sampled after atmospheric transport (6 - 45 hours), suggesting that organic aerosol mass loading and chemical properties were strongly influenced by combustion processes at the source and conserved to a significant extent during regional transport. These results suggest that MCE can be a useful metric for describing aerosol properties of regionally transported wildfire emissions and their impacts on regional air quality and global climate.

54 ENVIRONMENTAL SCIENCES↗

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wildfire Produces Transient Minerals: Speciation, Reactivity, and Fate of Iron and Manganese in Surface Soils Post Wildfire

Wildfire leads to the deposition of an ash layer at the land surface. This material typically has alkaline properties, abundant pyrogenic carbon, and elevated metal concentrations compared to surface soils. Here, we compare ash and surface soils collected three weeks and two years after the Glass Fire (St. Helena, California, USA) to determine how wildfire affects the speciation and reactivity of iron (Fe) and manganese (Mn), two micronutrients that influence many soil processes. Synchrotron-based analyses revealed that wildfire generated stable Fe oxides like maghemite (γ-Fe 2 O 3 ) and hematite (α-Fe 2 O 3 ) that likely derived from surface soil or mineral dust rather than the vegetation, and Mn oxides such as hausmannite (Mn 3 O 4 ) and bixbyite (Mn 2 O 3 ) that derived primarily from aboveground biomass. However, these pyrogenic minerals were absent in soils collected two years after the fire. Their loss from the soil surface may result from a combination of erosion, translocation to deeper soil layers, and chemical weathering. The latter hypothesis is supported by the enhanced mobilization of Fe and Mn from ash upon the addition of pyoverdine, a model biogenic ligand. The increased mobility of micronutrients from fire-derived minerals in ash in response to microbial and root exudation may facilitate postfire soil and vegetation recovery.

bixbyite↗

Chemical Imaging of Atmospheric Biomass Burning Particles from North American Wildfires

The effects of biomass burning aerosols (BBA) on radiative forcing and cloud formation depend on chemical composition and the internal structures of individual particles within smoke plumes. To improve our understanding of the chemical and physical properties of BBA emitted at different times of the day and their evolution during atmospheric aging, we conducted a study as a part of the Fire Influence on Regional to Global Environments and Air Quality field campaign. Particle samples were collected onboard a research aircraft from smoke plumes from a wildfire in eastern Oregon during late afternoon and nighttime flights on August 28, 2019. A time-resolved aerosol collector was used to collect samples on substrates for offline spectromicroscopic imaging to investigate the single-particle characteristics of BBA particles. Approximately 20,400 individual particles from 10 selected samples were analyzed using computer-controlled scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, revealing their elemental composition, morphology, and viscosity. Elemental microanalysis indicated that aged potassium is likely found in the form of K 2 SO 4 , KNO 3 , and possible K-organic salts. Further chemical speciation and carbon bonding mapping within individual particles were conducted using synchrotron-based scanning transmission X-ray microscopy (STXM) coupled with near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Real-time, water-soluble light absorption measurements were acquired using a particle-into-liquid sampler instrument coupled to a liquid waveguide capillary cell and total organic analyzer. In the late afternoon samples, 65% of the total particle number population consisted entirely of organic components, compared to 46% in the nighttime particles. These differences were attributed to discrepancies in composition at the time of emission and to the daytime condensation and accumulation of photochemically formed secondary organic material on existing BBA particles, a process that halts at night. Microscopy images indicated that particle viscosity was lower in the nighttime particles (<10 1 Pa·s), likely due to increased relative humidity and a higher contribution from hygroscopic inorganic components. The chemical heterogeneity of individual particles was quantified using STXM-derived mixing state parameters. The nature of carbon bonding within individual particles was inferred from the extent of carbon sp 2 hybridization derived from NEXAFS spectra. Average percentages of sp 2 hybridization range between 40% and 60%, with no noticeable differences between late afternoon and nighttime flights. These findings were compared with the online optical properties of both late afternoon and nighttime smoke plumes, providing valuable insights into the complex relationship between chemical composition and optical properties of BBA particles at different times of the day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2024 Wildfire Danger Rating Update: Analysis of the Wildfire Danger Rating Instruction for Kirtland Air Force Base.

A study of wildfire danger ratings was conducted by the Meteorological Program using the adjective ratings reported to the Weather Information Management System (WIMS). The focus of this study was to identify the shortcomings of Instruction 13-212 from Kirtland Air Force Base with regards to fire danger rating. The goal was to illustrate the benefits of using data from the Sandia National Labs Remote Automated Weather Station (RAWS) to better identify the proper fire danger rating on Kirtland Air Force Base.

54 ENVIRONMENTAL SCIENCES↗

Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management

Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.

54 ENVIRONMENTAL SCIENCES↗

Short-term impacts of 2017 western North American wildfires on meteorology, the atmosphere’s energy budget, and premature mortality

Abstract Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM 2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.

Bernstein, Diana N. (ORCID:0000000308279336)↗

Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets

Wildfires are the dominant disturbance impacting many regions in Alaska and is expected to intensify due to climate change. Accurate tracking and quantification of wildfires are important for climate modeling and ecological studies in this region. Remote sensing platforms (e.g., MODIS, Landsat) are an important tool for mapping wildfires in Alaska at varying spatial and temporal scales. Deep neural networks (DNN) have shown superior performance in many classification problems such as high-dimensional remote sensing data. Detection of wildfires is an imbalanced classification problem where one class contains a much smaller or larger sample size and DNNs performance can decline. We take a known weight-selection strategy during DNN training and apply them to MODIS variables (e.g., NDVI, surface reflectance) for a binary classification (i.e., wildfire or no-wildfire) across Alaska during the 2004 wildfire year, which is one of the largest on record. The method splits the input training data into sets, one for training the DNN to update weights and the other that splits into a validation set that is equally balanced between the wildfire and no-wildfire class. The performance is monitored on the validation set to select the weights based on the best validation-loss score. This approach was applied to two sampled datasets, such as where the no-wildfire class can significantly outweigh the wildfire class. The normal DNN training strategy was unable to map wildfires for the highly imbalanced dataset, however, the weight-selection strategy was able to map wildfires very accurately (0.96 recall score for 78,702 wildfire pixels (500×500 m)).

Langford, Zach↗