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NASA NTRSDate not supplied

Advancing Wildland Fire Response with NASA’s Second Shift Capabilities

Novel “Second-Shift” capabilities—leveraging Uncrewed Aerial Systems and Optionally Piloted Vehicles—are identified that could extend wildfire aerial logistics support into night or low-visibility conditions. Expert elicitations with subject-matter experts informed the development of these conceptual capabilities and identified key challenges in wildfire logistics operations. Furthermore, the potential of these capabilities could extend beyond aerial logistics support, encompassing aerial suppression, observation, and emergency extraction support for wildland firefighting. An approach to development, implementation and validation of the novel capabilities is described.

Wildfire logistics↗

NASA NTRSDate not supplied

Advancing Wildland Fire Response with NASA’s Second Shift Capabilities

Wildfire logistics↗

NASA NTRSDate not supplied

Improving Satellite-Based Hotspot Detection Through Deep Learning-Enabled Smoke Recognition

While geostationary satellites, such as the GOES-R series, provide wildland fire hotspot readings at a high temporal resolution, they are prone to false negative readings and decreased confidence. One cause of decreased hotspot confidence is cloud contamination. Smoke produced from wildfire is often misinterpreted as cloud contamination, resulting in inaccurate and unsure sensor readings. To this end, we built a deep learning image segmentation model to identify smoke and cloud in true color satellite images. The model is pre-trained using self-supervised learning on over 10,000 GOES-R images to learn the underlying structure of satellite imagery. Then, the model is fine-tuned on a set of 130 labeled documents using supervised learning. The resulting model performs multi-class image segmentation with 85% accuracy and runs in under a minute on a standard personal computer. When paired alongside hotspot data, the model’s outputs can help increase confidence in wildfire location by identifying cases of cloud contamination that are due to smoke. The resulting model can be deployed in a stand-alone application or bundled in an Open Data Integration for wildland fire management (ODIN) application.

Earth observation↗

NASA NTRSDate not supplied

A Field Campaign to Study Lightning that Ignites the Bush

The impact of recent wildland fires in the United States and Australia have received much attention in the past several years. As a result, NASA has developed a new Earth Science program to better understand, predict, and manage this phenomenon, as well as a future suborbital mission to studying pyro-cumulonimbus clouds and their effects on the Earth system. In Australia, government and philanthropic stakeholders are supporting a series of field campaigns over the next few years to inform science requirements and advance technology for a future satellite mission to monitor Bushfires. Lightning flashes are a major source of wildland fires, but uncertainties remain about the physical characteristics of lightning and their parent thunderstorms responsible for igniting wildfires. It was long believed that most lightning-ignited wildfires are largely caused by positive flashes to the ground (CGs) and multi-stroke CGs, but a recent study looking at 26-years of NLDN data indicate otherwise. Perhaps this finding is due to statistical chance—there are more negative CGs that occur globally—or perhaps there is some unknown electrical property of the thundercloud from which the igniting flashes emanate. Regardless, new observing strategies are needed. Additionally, long continuing current CGs, which are more likely to ignite a fire, can elude detection by operational ground-based lightning location systems, making it difficult to efficiently identify potential wildland fires and manage them before they have adverse impacts. To address these science and operational gaps, NASA’s Lightning Mapping Array along with electric and magnetic field change meters will be deployed for the Australian Bushfire campaign to document the electrical structure and properties of thunderstorms and lightning that occur in a wildland fire susceptible region. Another aspect of the campaign will be the use of NASA’s airborne lightning observatory, which includes a spectrometer and high-speed imager, to document the radiometric attributes of these flashes coincident with the ground-based RF observations. These observations will be used to better understand the properties of lightning that ignite wildland fires as well as inform design of a lightning detection system for the future Bushfire Monitoring satellite mission.

lightning↗

DOE OSTI2023

INL Soil Contamination Areas - Wildland Fire Radiological Hazards

The largest wildland fire on the INL occurred in 2019 and initiated a reassessment of the hazard of wildfires burning through soil contamination areas. In 2020 during the COVID shutdown, the INL Emergency Management Group and the Radiological Control Group worked together to re-evaluate the hazards from these soil contamination areas that were last evaluated in 2001. The new soil sample data was examined, and the areas were mapped for radiation intensity. A new evaluation of the radiological hazards due to wildfire was completed and issued because of this work. This presentation will describe the work and the methodologies used to complete this re-evaluation.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Allometric relationships and trade‐offs in 11 common M editerranean‐climate grasses

Abstract Biomass allocation in plants is the foundation for understanding dynamics in ecosystem carbon balance, species competition, and plant–environment interactions. However, existing work on plant allometry has mainly focused on trees, with fewer studies having developed allometric equations for grasses. Grasses with different life histories can vary in their carbon investment by prioritizing the growth of specific organs to survive, outcompete co‐occurring plants, and ensure population persistence. Further, because grasses are important fuels for wildfire, the lack of grass allocation data adds uncertainty to process‐based models that relate plant physiology to wildfire dynamics. To fill this gap, we conducted a greenhouse experiment with 11 common California grasses varying in photosynthetic pathway and growth form. We measured plant sizes and harvested above‐ and belowground biomass throughout the life cycle of annual species, while for the establishment stage of perennial grasses to quantify allometric relationships for leaf, stem, and root biomass, as well as plant height and canopy area. We used basal diameter as a reference measure of plant size. Overall, basal diameter is the best predictor for leaf and stem biomass, height, and canopy area. Including height as another predictor can improve model accuracy in predicting leaf and stem biomass and canopy area. Fine root biomass is a function of leaf biomass alone. Species vary in their allometric relationships, with most variation occurring for plant height, canopy area, and stem biomass. We further explored potential trade‐offs in biomass allocation across species between leaf and fine root, leaf and stem, and allocation to reproduction. Consistent with our expectation, we found that fast‐growing plants allocated a greater fraction to reproduction. Additionally, plant height and specific leaf area negatively influenced the leaf‐to‐stem ratio. However, contrary to our hypothesis, there were no differences in root‐to‐leaf ratio between perennial and annual or C 4 and C 3 plants. Our study provides species‐specific and functional‐type‐specific allometry equations for both above‐ and belowground organs of 11 common California grass species, enabling nondestructive biomass assessment in California grasslands. These allometric relationships and trade‐offs in carbon allocation across species can improve ecosystem model predictions of grassland species interactions and environmental responses through differences in morphology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Black carbon emissions in Russia: A critical review

Russia has a particularly important role regarding black carbon (BC) emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. This study presents a comprehensive review of BC estimates from a range of studies. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data on Russian associated petroleum gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 689 Gg in 2014, with an uncertainty range between (407-1,416), while OC emissions are 9,228 Gg (with uncertainty between 5,595 and 14,728). Wildfires dominated and contributed about 83% of the total BC emissions, however the effect on radiative forcing is mitigated by OC emissions. We also present an adjusted estimate of Arctic forcing from Russian OC and BC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.

Black carbon↗

DOE OSTI2018

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances--including drought, heat, insect outbreaks, and wildfire--are rising as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.

disequilibrium↗

DOE OSTI2022

Recent Trends in Transport of Surface Carbonaceous Aerosols to the Upper-Troposphere-Lower-Stratosphere Linked to Expansion of the Asian Summer Monsoon Anticyclone

Using Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2) re-analyses, we have examined recent trends (2000–2019) in transport of surface carbonaceous aerosols (CAs), that is, organic carbon and black carbon, to the upper troposphere and lower stratosphere (UTLS) during the Asian summer monsoon (ASM). We find a significant increased concentration of UTLS CA, linked to a linear trend in an expansion of the Asian Summer Monsoon Anticyclone (ASMA). Over core monsoon latitudes (25°–35°N), the trends in UTLS CA are enabled by increased upward transport from surface sources via an intensified monsoon meridional circulation, with increased latent heating over the southern Tibetan Plateau and foothill regions, enhanced by feedback processes associated with radiative heating by UTLS CA. In the extra-tropics, increased UTLS CA stems primarily from an extended source of increased wildfire emissions over eastern Siberia and northern Asia, coincident with a large-scale anomalous anticyclone with enhanced surface warming and drying near (80°–120°E, 55°–70°N). Here, CAs are transported upward from the surface to the ULS, likely by increased pyro-convection associated with enhanced wildfires, and enter the tropical UTLS via increased equatorward transport on the eastern flanks of anomalous upper-level anticyclones, coupled to the expanded ASMA. Overall, the increasing UTLS CA trends associated with expansion of the ASMA are consistent with a hydrostatic expansion of a warming troposphere, reflected in a rise in the tropical tropopause and consequential dynamical adjustments of the ASM subtropical jetstream, modulating the climate of the greater ASM region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Informed Multi‐Scale Approach Applied to the British Columbia Fires of Late Summer 2017

Abstract Pyrocumulonimbus (PyroCb) clouds have a complex origin dependent on fire dynamics and meteorological conditions. When a pyrocumulonimbus cloud develops and is maintained over a period of time, it can inject significant aerosol into the troposphere and lower stratosphere, resulting in a longer‐term (months to years) occurrence of aerosol in the stratosphere. In this work, we investigate the British Columbia wildfires on 12–13 August 2017 using a multi‐scale simulation framework. We use the output of a physics‐based wildfire model (FIRETEC) with parameterized energy, particle, and gas emissions to drive the upper atmospheric aerosol mass injection within a regional cloud resolving model (HIGRAD). We demonstrate that vertical motions produced by latent heat release of the condensation of ice and cloud particles within the PyroCbs induce another 5 km of lifting of the simulated aerosol plume. Primary black carbon and organic aerosols (OAs) alone may not be enough to explain the observed aerosol burden, thus we show that secondary OA produced via condensation of gases by the fires, ash, and possibly dust can enhance lofted aerosol mass. A simulation with all emission mechanisms active, driven by the observed fuel load and environmental conditions, reasonably reproduces an aerosol profile inferred from observational data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Permafrost Carbon: Progress on Understanding Stocks and Fluxes Across Northern Terrestrial Ecosystems

Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO 2 and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane source and small terrestrial ecosystem CO 2 sink with lower net CO 2 uptake toward higher latitudes, excluding wildfire emissions. For 2002–2014, the strongest CO2 sink was located in western Canada (median: -52 g C m -2 y -1 ) and smallest sinks in Alaska, Canadian tundra, and Siberian tundra (medians: -5 to -9 g C m -2 y -1 ). Eurasian regions had the largest median wetland methane fluxes (16–18 g CH4 m -2 y -1 ). Quantifying the regional scale carbon balance remains challenging because of high spatial and temporal variability and relatively low density of observations. More accurate permafrost region carbon fluxes require: (a) the development of better maps characterizing wetlands and dynamics of vegetation and disturbances, including abrupt permafrost thaw; (b) the establishment of new year-round CO 2 and methane flux sites in underrepresented areas; and (c) improved models that better represent important permafrost carbon cycle dynamics, including non-growing season emissions and disturbance effects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume-rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume-rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling-FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model-observation comparison demonstrates the importance of the plume-rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m –2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no-linear nature in the BBA-induced radiative effect.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Summertime Carbonaceous Aerosol in Interior Versus Coastal Northern Alaska

Abstract Rapid warming is likely increasing primary production and wildfire occurrence in the Arctic. Projected changes in carbonaceous aerosols during the summer will impact atmospheric chemistry and climate, but our understanding of these processes is limited by sparse observations. Here, we characterize carbonaceous aerosol in Alaska, USA: Toolik Field Station in the Interior and the Atmospheric Radiation Measurement facility at Utqiaġvik on the Arctic coast, during the summers of 2022 and 2023. We estimated PM 2.5 and PM 10 concentrations using laser light scattering (PurpleAir sensors) and examined total carbon (TC) and its organic carbon (OC) and elemental carbon (EC) fractions in total suspended particles (TSP). We investigated the dominant sources of carbonaceous aerosol using air mass backward‐trajectories from the NOAA HYSPLIT model and radiocarbon source apportionment of TC. TC concentrations were about twice as high in the Interior compared to the coast, with contemporary sources dominating at both Toolik (95%–99%) and Utqiaġvik (86%–89%) over minor contributions from fossil sources. Elevated PM, TC, OC, and EC concentrations coincided with major boreal forest fire activity in North America that brought smoke to the region. The radiocarbon signature of EC measured at Toolik during these wildfire events indicated that over 90% of the EC came from contemporary sources. Our measurements demonstrate the potential for Arctic aerosol concentrations to respond significantly to climate warming‐induced changes to the landscape and emphasize the need for continuous atmospheric monitoring to advance our understanding of this rapidly changing environment.

Welch, Allison M. [Department of Earth System Scie↗

DOE OSTI2023

Geospatial mapping of distribution grid with machine learning and publicly-accessible multi-modal data

Abstract Detailed and location-aware distribution grid information is a prerequisite for various power system applications such as renewable energy integration, wildfire risk assessment, and infrastructure planning. However, a generalizable and scalable approach to obtain such information is still lacking. In this work, we develop a machine-learning-based framework to map both overhead and underground distribution grids using widely-available multi-modal data including street view images, road networks, and building maps. Benchmarked against the utility-owned distribution grid map in California, our framework achieves > 80% precision and recall on average in the geospatial mapping of grids. The framework developed with the California data can be transferred to Sub-Saharan Africa and maintain the same level of precision without fine-tuning, demonstrating its generalizability. Furthermore, our framework achieves a R 2 of 0.63 in measuring the fraction of underground power lines at the aggregate level for estimating grid exposure to wildfires. We offer the framework as an open tool for mapping and analyzing distribution grids solely based on publicly-accessible data to support the construction and maintenance of reliable and clean energy systems around the world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Peatland fires in Alaska will double by the end of the century

During recent summers, warm and dry conditions have increased the occurrence of wildfires and potentially peat-fires across Alaska. Limitations in resolving the fine-scale distribution of peatlands and climate observations have constrained our ability to accurately predict peat-fire dynamics. Using a new high-resolution peatland map of Alaska, we evaluated the climate and environmental controls of past and future peat-fire activity. Ensemble machine learning models identified reduced soil moisture, higher temperatures, and evapotranspiration as key predictors of annual total burned peatland area (tenfold CV R 2 = 0.62, RMSE = 221.1 km 2 ). By the end of the twenty-first century, models forced with climate datasets from representative concentration pathways (RCPs) 4.5, 6.0, and 8.5 emission scenarios project a statewide doubling of burned peatlands (increasing 61–121%), with regional increases ranging from 25–165% in polar, 61–95% in boreal, and 102–106% in maritime ecoregions. These projections indicate that wildfires will progressively encroach further into organic-rich moist and wet peaty soils, potentially amplifying soil carbon release across Alaska.

climate-change ecology↗

DOE OSTI2016

Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia

Vegetation and peatland fires cause poor air quality and thousands of premature deaths across densely populated regions in Equatorial Asia. Strong El-Niño and positive Indian Ocean Dipole conditions are associated with an increase in the frequency and intensity of wildfires in Indonesia and Borneo, enhancing population exposure to hazardous concentrations of smoke and air pollutants. Here we investigate the impact on air quality and population exposure of wildfires in Equatorial Asia during Fall 2015, which were the largest over the past two decades. We performed high-resolution simulations using the Weather Research and Forecasting model with Chemistry based on a new fire emission product. The model captures the spatio-temporal variability of extreme pollution episodes relative to space- and ground-based observations and allows for identification of pollution sources and transport over Equatorial Asia. We calculate that high particulate matter concentrations from fires during Fall 2015 were responsible for persistent exposure of 69 million people to unhealthy air quality conditions. Short-term exposure to this pollution may have caused 11,880 (6,153–17,270) excess mortalities. Results from this research provide decision-relevant information to policy makers regarding the impact of land use changes and human driven deforestation on fire frequency and population exposure to degraded air quality.

Science & Technology - Other Topics↗

DOE OSTI2021

Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Assessing residential PM 2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM 2.5 ). To study PM 2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM 2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM 2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor–indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM 2.5 , such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM 2.5 in monitored residences.

54 ENVIRONMENTAL SCIENCES↗