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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
NASA NTRS2023

Compact Lightweight Aerial Sensor System (CLASSy)

In the wake of increasingly intense wildfires, innovative solutions are imperative to enhance wildfire mitigation strategies. Current technological integrations have hit a communicative limit. Between limited flight time, computational expenses as well as financial expenses, there is a hole in the market for an effective, low-tech, and disposable solution. The Compact Lightweight Aerial Sensor System (CLASSy) is designed to revolutionize active disaster operations through comprehensive decision support. CLASSy consists of a lightweight launch mechanism and a flight body equipped with a sensor package and parachute. The assembly integrates sensor networks with data analytics to provide real-time, high-resolution information to incident commanders, directly facilitating decision-making and resource allocation. Infrared imagery and temperature differentials are processed and analyzed throughout flight, offering valuable insights into fire behavior, hotspot detection, and fire spread trajectories. CLASSy is intended to meet a variety of natural disaster mitigation needs through its variable launch height and disposability. CLASSy’s goal is to assist wildfire fighting without taking up any human or material resources. As a result, CLASSy is as lightweight as possible, easily expendable, inexpensive to manufacture, and only requires one operator for effective use. CLASSy’s integrated sensor suite, real-time analytics, and closed loop active communications empower firefighting teams to proactively address wildfire challenges. As the frequency of wildfires continues to rise, technological innovations like CLASSy are crucial to effective wildfire management systems.

Kyleigh Anderson↗
NASA NTRSDate not supplied

Mapping Surface Vapor Pressure Deficits From Geostationary Satellites for Fire Weather Monitoring

The increase in the wildfires were observed globally in accordance with global warming, and to real- time monitoring of wildfire risk in broad scale is demanded for wildfire management to prevent the spread of wildfires. Scientists invented a lot of indices to assess the wildfire risk. Vapor Pressure Deficit (VPD) is one of the most important meteorological components for those indices. Compared to other components of fire weather indices, VPD can change quickly from lower risk to higher risk even in sub-hourly. Therefore, real-time fire risk monitoring requires high-resolution and high- temporal VPD spatial map. Here, we developed VPD estimation method using the GOES Advanced Baseline Imager (ABI) data. Unlike the polar-orbital satellite data, the ABI can observe target region every 10 minutes, so that we can estimate VPD for fire weather in real-time. The method used to estimate VPD is same with the algorithm of NASA Earth Exchange Gridded Daily Meteorology (NEX- GDM), which estimate meteorological variables from ground weather observation and spatial variables based on random forest (RF). We calculated RF importance to select bands of ABI as input of the model. To validate our results, we compared the spatial pattern of our VPD data with the Real- Time Mesoscale Analysis (RTMA) data over the conterminous USA. We sought possibility of applying our method to the region where no real-time high-resolution weather data is available, such as South America. The developed method can produce real-time high-resolution high-frequent VPD data in the continental scale. The derived data from GOES ABI could contribute to improve the fire weather monitoring and lead to prevent wildfires.

Hirofumi Hashimoto↗
DOE OSTI2024

Estimating Carbon Dioxide Emissions in Two California Cities Using Bayesian Inversion and Satellite Measurements

NASA's Orbiting Carbon Observatories (OCO-2 and OCO-3) provide measurements of column-averaged carbon dioxide concentrations (XCO 2 ) with sufficient spatial resolution and precision to constrain bottom-up estimates of CO 2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO 2 fluxes in the South Coast Air Basin (SoCAB) which surrounds Los Angeles, and in the San Francisco Bay Area Air Basin (SFBA). We study 2020 to understand the impact of the COVID-19 lockdowns and an active wildfire season. Our results indicated that a 50% (30%) reduction in CO 2 emissions relative to 2015 during the COVID-19 lockdown period was consistent with OCO measurements for SFBA (SoCAB). We find that posterior wildfire emissions differed significantly from the prior at the scale of individual wildfires, though with large uncertainties, and that wildfire emissions in SFBA are significant, attributing 72% of the region's CO 2 emissions during August 2020 to wildfires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Storm and Annual Time Scale Hydrological Data for the Russian River Watershed 1996-2022

These files contains observed and simulated hydrological data (discharge, precipitation) that have been aggregated to the storm-event scale and to the annual time scale for the Russian River Watershed (RRW), California. Observed data are obtained from 12 different USGS hydrological stations located throughout the watershed, and discharge is simulated using the GR5H hourly hydrological model. Precipitation data are obtained from the NASA NLDAS NOAH Community Land Surface Model. All simulated and observed discharge are aggregated to the storm and annual time scales. We investigated changes in watershed hydrological conditions in the Russian River Watershed, a Mediterranean, drought prone, wildfire-adapted ecosystem, following eleven wildfires that occurred from 2017-2020. We ask two research questions: 1) How do interacting wildfire events, drought, and atmospheric rivers impact hydrological conditions of the watershed and in particular streamflow?, and 2) What percentage of new and/or cumulative wildfire disturbance is required to initiate hydrological change? We hypothesize that sub-watersheds of the RRW Mediterranean ecoregion have not burned beyond an intrinsic, and still unknown, threshold required to initiate change. Using a series of paired burned/unburned catchments nested within the larger watershed, we examined temporal and spatial patterns of pre-and-post wildfire water hydrology using a rainfall runoff hydrological model compared with data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Reviews and syntheses: Arctic fire regimes and emissions in the 21st century

In recent years, the pan-Arctic region has experienced increasingly extreme fire seasons. Fires in the northern high latitudes are driven by current and future climate change, lightning, fuel conditions, and human activity. In this context, conceptualizing and parameterizing current and future Arctic fire regimes will be important for fire and land management as well as understanding current and predicting future fire emissions. The objectives of this review were driven by policy questions identified by the Arctic Monitoring and Assessment Programme (AMAP) Working Group and posed to its Expert Group on Short-Lived Climate Forcers. This review synthesizes current understanding of the changing Arctic and boreal fire regimes, particularly as fire activity and its response to future climate change in the pan-Arctic have consequences for Arctic Council states aiming to mitigate and adapt to climate change in the north. The conclusions from our synthesis are the following. (1) Current and future Arctic fires, and the adjacent boreal region, are driven by natural (i.e. lightning) and human-caused ignition sources, including fires caused by timber and energy extraction, prescribed burning for landscape management, and tourism activities. Little is published in the scientific literature about cultural burning by Indigenous populations across the pan-Arctic, and questions remain on the source of ignitions above 70_ N in Arctic Russia. (2) Climate change is expected to make Arctic fires more likely by increasing the likelihood of extreme fire weather, increased lightning activity, and drier vegetative and ground fuel conditions. (3) To some extent, shifting agricultural land use and forest transitions from forest–steppe to steppe, tundra to taiga, and coniferous to deciduous in a warmer climate may increase and decrease open biomass burning, depending on land use in addition to climate-driven biome shifts. However, at the country and landscape scales, these relationships are not well established. (4) Current black carbon and PM2:5 emissions from wildfires above 50 and 65_ N are larger than emissions from heanthropogenic sectors of residential combustion, transportation, and flaring. Wildfire emissions have increased from 2010 to 2020, particularly above 60_ N, with 56% of black carbon emissions above 65_ N in 2020 attributed to open biomass burning – indicating how extreme the 2020 wildfire season was and how severe future Arctic wildfire seasons can potentially be. (5) What works in the boreal zones to prevent and fight wildfires may not work in the Arctic. Fire management will need to adapt to a changing climate, economic development, the Indigenous and local communities, and fragile northern ecosystems, including permafrost and peatlands. (6) Factors contributing to the uncertainty of predicting and quantifying future Arctic fire regimes include underestimation of Arctic fires by satellite systems, lack of agreement between Earth observations and official statistics, and still needed refinements of location, conditions, and previous fire return intervals on peat and permafrost landscapes. This review highlights that much research is needed in order to understand the local and regional impacts of the changing Arctic fire regime on emissions and the global climate, ecosystems, and pan-Arctic communities.

Arctic↗
DOE OSTI2023

Metal toxin threat in wildland fires determined by geology and fire severity

Accentuated by climate change, catastrophic wildfires are a growing, distributed global public health risk from inhalation of smoke and dust. Underrecognized, however, are the health threats arising from fire-altered toxic metals natural to soils and plants. Here, we demonstrate that high temperatures during California wildfires catalyzed widespread transformation of chromium to its carcinogenic form in soil and ash, as hexavalent chromium, particularly in areas with metal-rich geologies (e.g., serpentinite). In wildfire ash, we observed dangerous levels (327-13,100 µg kg -1 ) of reactive hexavalent chromium in wind-dispersible particulates. Relatively dry post-fire weather contributed to the persistence of elevated hexavalent chromium in surficial soil layers for up to ten months post-fire. The geographic distribution of metal-rich soils and fire incidents illustrate the broad global threat of wildfire smoke- and dust-born metals to populations. Our findings provide new insights into why wildfire smoke exposure appears to be more hazardous to humans than pollution from other sources.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Life-cycle carbon footprint and total production potential of cross-laminated timber from California’s wildland-urban interface

The frequency, scale, and severity of wildfires are steadily increasing in the Western United States. Sustainable forest management practices through forest thinning could reduce the impact of wildfires and provide lumber for wood-based, long-lived, and low-carbon building materials. This study explores the potential for harvesting biomass in California (CA) to mitigate wildfire risk and provide multi-decade carbon storage in the form of cross-laminated timber (CLT) for use in buildings. First, we assessed biomass resource availability, finding that the total live hardwood and live softwood available in the wildland-urban interfaces (WUIs) across CA sums to 14.1 million metric tons (MMT) and 34.9 MMT, respectively, which contains the equivalent of 90 MMT of atmospheric carbon dioxide. Then, we conducted a life cycle assessment of CLT considering softwood and hardwood sources to provide insights into emissions and energy demand associated with utilization of the wood removed for wildfire risk management. We found that the net life cycle carbon footprint of live hardwood and softwood when including biogenic carbon storage/emissions is 414 and 317 kg CO2e/m3 CLT, respectively. To incorporate the timing of these emissions and uptake, we have also conducted a cradle-to-grave time-dependent global warming potential (GWP) analysis. The time-adjusted GWP for live hardwood and live softwood is −227 and −104 kg CO2e/m3 CLT, respectively. In terms of total CLT production potential, 0.03 and 0.005 million m3 CLT can be sourced from live softwood and hardwood, respectively, in WUI on gentle slopes in CA. The resulting insights and approaches from this study are broadly applicable to other forested regions and WUIs across the US and the world, and provide a holistic approach to use forest thinning as a wildfire mitigation strategy in combination with a novel approach for life cycle assessment of building materials with a limited dataset.

Bose, Baishakhi↗
DOE OSTI2023

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

Abstract Background Prescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients’ hospital utilization. Methods We used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients’ primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI). Results Associations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies. Conclusions Area-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Raab, Henry↗
DOE OSTI2024

Effects of fire and fire-induced changes in soil properties on post-burn soil respiration

Boreal forests cover vast areas of land in the northern hemisphere and store large amounts of carbon (C) both aboveground and belowground. Wildfires, which are a primary ecosystem disturbance of boreal forests, affect soil C via combustion and transformation of organic matter during the fire itself and via changes in plant growth and microbial activity post-fire. Wildfire regimes in many areas of the boreal forests of North America are shifting towards more frequent and severe fires driven by changing climate. As wildfire regimes shift and the effects of fire on belowground microbial community composition are becoming clearer, there is a need to link fire-induced changes in soil properties to changes in microbial functions, such as respiration, in order to better predict the impact of future fires on C cycling. We used laboratory burns to simulate boreal crown fires on both organic-rich and sandy soil cores collected from Wood Buffalo National Park, Alberta, Canada, to measure the effects of burning on soil properties including pH, total C, and total nitrogen (N). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and its resulting changes in soil properties on soil respiration. Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events. We found that burning increased pH and caused small decreases in C:N in organic soil. Overall, respiration per gram total (post-burn) C in burned soil cores was 16% lower than in corresponding unburned control cores, indicating that soil C lost during a burn may be partially offset by burn-induced decreases in respiration rates. Simultaneously, burning altered how remaining C cycled, causing an increase in the proportion of C represented in the modeled slow-cycling vs. fast-cycling C pool as well as an increase in fast-cycling C decomposition rates. Together, our findings imply that C storage in boreal forests following wildfires will be driven by the combination of C losses during the fire itself as well as fire-induced changes to the soil C pool that modulate post-fire respiration rates. Moving forward, we will pair these results with soil microbial community data to understand how fire-induced changes in microbial community composition may influence respiration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics

Abstract. African and South American (ASA) wildfires account for more than 70 % of global burned areas and have strong connection to local climate for sub-seasonal to seasonal wildfire dynamics. However, representation of the wildfire–climate relationship remains challenging due to spatiotemporally heterogenous responses of wildfires to climate variability and human influences. Here, we developed an interpretable machine learning (ML) fire model (AttentionFire_v1.0) to resolve the complex controls of climate and human activities on burned areas and to better predict burned areas over ASA regions. Our ML fire model substantially improved predictability of burned areas for both spatial and temporal dynamics compared with five commonly used machine learning models. More importantly, the model revealed strong time-lagged control from climate wetness on the burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse in South America in the near future due to climate changes. Our study provides a reliable and interpretable fire model and highlights the importance of lagged wildfire–climate relationships in historical and future predictions.

58 GEOSCIENCES↗
NASA NTRS1993

MAMS: High resolution atmospheric/surface properties

The Multispectral Atmospheric Mapping Sensor (MAMS) has been used for a number of investigations over the last 8 years. It has served as the basis for retrieval technique development, for atmospheric process studies, and to retrieve geophysical parameters at the surface (land and ocean). It was used most recently to collect high resolution visible and infrared imagery for the CaPE and STORMFEST experiments during FY91 and FY92. The Wildfire spectrometer (similar to MAMS but with different infrared channels) was also used during STORMFEST. The goals of MAMS during CaPE were: (1) to collect MAMS data to support the overall CaPE science objectives; (2) refine techniques for the retrieval of atmospheric moisture and surface geophysical parameters; (3) map the moisture distributions associated with the sea breeze front over Florida with MAMS ancillary satellite data on a case study basis; (4) identify surface features which may serve as local sources of heat and moisture and influence preferential convective regions over Florida, and (5) process MAMS data and derived relevant geophysical parameters to support other CaPE investigators. For STORMFEST both the MAMS and Wildfire spectrometers were used to collect unique multispectral data to study atmospheric processes. The Wildfire objectives were: (1) to collect high quality Wildfire data in conjunction with other in situ and remote measurements available during the STORMFEST field phase (1 February - 15 March 1992); (2) to develop algorithms to retrieve total ozone content and compare with those from TOMS and HIRS (IR); and (3) along with water vapor imagery, use the ozone data to better understand the 3-dimensional structure and dynamics of jet streaks and frontal systems in a case study investigation. The MAMS objectives were: (1) collect MAMS data to support a GSFC investigation of gravity waves; and (2) process the MAMS data to locate gravity wave features, and produce various moisture products in support of the gravity wave investigation. The research activities over the last year are presented and they focused on analyzing the CaPE data sets and collecting and starting preliminary analysis of the STORMFEST MAMS and Wildfire data.

Jedlovec, Gary J.↗
NASA NTRS2014

RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

cloud computing↗
NASA NTRS2020

SMARt-STEReO: Preliminary Model Description

Wildfires have increasingly become major threat to US towns and cities, with California alone having its most destructive wildfire seasons to date in 2017 and 2018 and 2020 already becoming one of the worst fire years on record, causing the large-scale evacuations, the destruction of towns and property, and a significant release of hazardous smoke over the entire west coast. Thus, the U.S. Forest Service recently spent over 50% of its budget on wildfire management – funds which could otherwise be directed to science that could support fire prevention. Aerial support plays a major role in fighting wildfires. Airtankers, helicopters, and other aerial assets support the construction of fire-lines, gather data, and transport crews and equipment. However, presently, aerial firefighting operations rely on relatively unsophisticated technologies for communications, such as over-the-air radios, which limit the ability of pilots and management to relay fire data and coordinate operations. Aerial operations in and around fires are additionally high-risk activities due to the variable, dangerous conditions and complex, technically difficult maneuvers which must be performed to, for example, conduct a retardant drop. Thus, between 2000 and 2013, of the 298 wildland firefighter fatalities, 26% were related to aerial operations. As a result, there is significant potential to both improve the performance and resiliency of wildfire response while reducing risk to human operators.

Daniel E Hulse↗
NASA NTRSDate not supplied

Long-range Transport of Siberian Biomass Burning Emissions to North America During FIREX-AQ

Biomass burning from wildfires is a significant global source of aerosol and trace gases which impact air quality, tropospheric and stratospheric composition, and climate. During the summer of 2019, wildfire activity in central and eastern Siberia occurred during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign conducted between July 24 and September 6, 2019. Ground-based lidar observations from the Autonomous Mobile Ozone Lidar for Tropospheric Experiments (AMOLITE) system in Alberta, Canada retrieved frequent anomalous ozone (O3) and aerosol lamina in the troposphere and lower stratosphere during this campaign. Data from NASA’s GEOS Composition Forecast (GEOS-CF) coupled chemistry meteorology model, TROPOspheric Monitoring Instrument (TROPOMI), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and ground-based insitu data were used to define the trans-Pacific and trans-Arctic transport pathway of Siberian biomass burning emissions resulting in the enhanced O3 and aerosol lamina observed by AMOLITE in western Canada. Siberian wildfires impacted North American air quality resulting in enhancements of hourly-averaged surface carbon monoxide (CO) (total CO >150 ppb) and fine particulate matter (PM2.5) (>20 μg m-3) in western Canada, however, minimal increases in surface-level O3 were measured as well as modeled by GEOS-CF. The impact in western Canada due to Siberian wildfires was much larger in the free troposphere, demonstrated by GEOS-CF and AMOLITE O3 lamina 30–40 ppb above background values and model-predicted PM2.5 lamina >30 μg m-3. In addition to tropospheric composition effects, the large wildfire activity in Siberia may have influenced the stratosphere as data from AMOLITE, CALIPSO, and GEOS-CF all suggested aerosol layers from the fires were located 13–18 km above ground level (agl). This study shows that the Siberian biomass burning emissions in the summer of 2019 impacted tropospheric/stratospheric composition in western Canada, and potentially could have influenced areas in the vicinity of FIREX-AQ airborne measurements, and future studies of FIREX-AQ chemical composition should consider how this long-range transport could have influenced the background trace gas and aerosol concentrations being investigated.

Biomass↗
NASA NTRS2021

Leveraging NASA Soil Moisture Active Passive for Assessing Fire Susceptibility and Potential Impacts over Australia and California

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influences wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the Soil Moisture Active Passive (SMAP) sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1-2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

Nazmus Sazib↗
NASA NTRS2022

Source and Variability of Formaldehyde (HCHO) at Northern High Latitude: an Integrated Satellite, Aircraft, and Model Study

Here we use satellite observations of formaldehyde (HCHO)vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5°×0.625° resolution), to understand the variability and sources of summertime HCHO better in Alaska. We first evaluate GEOS-Chem with in-situ airborne measurements during Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign. We show reasonable agreement between observed and modeled HCHO, isoprene, monoterpenes and the sum of methyl vinyl ketone and methacrolein (MVK+MACR) in continental boundary layer. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska summer, reprocessed by GEOS-Chem model output for a priori profiles and shape factors. For the year with low wildfire activity (e.g.,2018), we find that HCHO VCDs are largely dominated by background HCHO (58-71%), with minor contributions from wildfires (20-32%) and biogenic VOC emissions (8-10%). For the year with intense wildfires (e.g.,2019), summertime HCHO VCD is dominated by wildfire emissions (50-72%), with minor contributions from background (22-41%) and biogenic VOCs (6-10%). In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit, in part due to the slow HCHO production from isoprene oxidation under low NOx conditions. This work highlights challenges for quantifying HCHO and its precursors in remote pristine regions.

HCHO↗
NASA NTRS2024

Córdoba Wildland Fires: Assessing Fire Risk Factors in Córdoba, Argentina using Earth Observations

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface (WUI), and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the environmental parameters influencing fire behavior and growth. We partnered with the Instituto Nacional de Tecnología Agropecuaria (INTA) to address these gaps by utilizing NASA Earth observing data to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), we created a ten-year baseline using environmental variables to determine anomalies that influenced the fires of 2020. Baseline data were used to calculate the statistical significance of the environmental factors as precursors to wildfires. We found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, we created a wildfire risk map for the province of Córdoba, which can be used to enhance our partner’s fire management strategies and decision-making processes.

wildland fires↗