Fuel-Type Independent Parameterization of Volatile Organic Compound Emissions from Western US Wildfires.

Volatile organic compounds (VOCs) emitted from biomass burning impact air quality and climate. Laboratory studies have shown that the variability in VOC speciation is largely driven by changes in combustion conditions and is only modestly impacted by fuel type. Here, we report that emissions of VOCs measured in ambient smoke emitted from western US wildfires can be parameterized by high- and low-temperature pyrolysis VOC profiles and are consistent with previous observations from laboratory simulated fires. This is demonstrated using positive matrix factorization (PMF) constrained by high- and low-temperature factors using VOC measurements obtained with a proton-transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) on board the NASA DC-8 during the FIREX-AQ (Fire Influence on Regional and Global Environments and Air Quality) project in 2019. A linear combination of high- and low-temperature factors described more than 70% of the variability of VOC emissions of long-lived VOCs in all sampled wildfire plumes. An additional factor attributable to atmospheric aging was required to parameterize short-lived and secondarily produced VOCs. The relative contribution of the PMF-derived high-temperature factor for a given fire plume was strongly correlated with the fire radiative power (FRP) at the estimated time of emission detected by satellite measurements. By combining the FRP with the fraction of the high-temperature PMF factor, the emission ratios (ERs) of VOCs to carbon monoxide (CO) in fresh wildfires were estimated and agree well with measured ERs (r2 = 0.80-0.93).

Impact of Biomass Burning Organic Aerosol Volatility on Smoke Concentrations Downwind of Fires.

Biomass burning particulate matter (BBPM) affects regional air quality and global climate, with impacts expected to continue to grow over the coming years. We show that studies of North American fires have a systematic altitude dependence in measured BBPM normalized excess mixing ratio (NEMR; ΔPM/ΔCO), with airborne and high-altitude studies showing a factor of 2 higher NEMR than ground-based measurements. We report direct airborne measurements of BBPM volatility that partially explain the difference in the BBPM NEMR observed across platforms. We find that when heated to 40-45 °C in an airborne thermal denuder, 19% of lofted smoke PM1 evaporates. Thermal denuder measurements are consistent with evaporation observed when a single smoke plume was sampled across a range of temperatures as the plume descended from 4 to 2 km altitude. We also demonstrate that chemical aging of smoke and differences in PM emission factors can not fully explain the platform-dependent differences. When the measured PM volatility is applied to output from the High Resolution Rapid Refresh Smoke regional model, we predict a lower PM NEMR at the surface compared to the lofted smoke measured by aircraft. These results emphasize the significant role that gas-particle partitioning plays in determining the air quality impacts of wildfire smoke.

Airborne Emission Rate Measurements Validate Remote Sensing Observations and Emission Inventories of Western U.S. Wildfires.

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r2 = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Quantifying Prescribed-Fire Smoke Exposure Using Low-Cost Sensors and Satellites: Springtime Burning in Eastern Kansas.

Prescribed fires (fires intentionally set for mitigation purposes) produce pollutants, which have negative effects on human and animal health. One of the pollutants produced from fires is fine particulate matter (PM2.5). The Flint Hills (FH) region of Kansas experiences extensive prescribed burning each spring (March-May). Smoke from prescribed fires is often understudied due to a lack of monitoring in the rural regions where prescribed burning occurs, as well as the short duration and small size of the fires. Our goal was to attribute PM2.5 concentrations to the prescribed burning in the FH. To determine PM2.5 increases from local burning, we used low-cost PM2.5 sensors (PurpleAir) and satellite observations. The FH were also affected by smoke transported from fires in other regions during 2022. We separated the transported smoke from smoke from fires in eastern Kansas. Based on data from the PurpleAir sensors, we found the 24-hr median PM2.5 to increase by 3.0-5.3 µg m-3 (based on different estimates) on days impacted by smoke from fires in the eastern Kansas region compared to days unimpacted by smoke. The FH region was the most impacted by smoke PM2.5 compared to other regions of Kansas, as observed in satellite products and in situ measurements. Additionally, our study found that hourly PM2.5 estimates from a satellite-derived product aligned with our ground-based measurements. Satellite-derived products are useful in rural areas like the FH, where monitors are scarce, providing important PM2.5 estimates.

Multitemporal lidar captures heterogeneity in fuel loads and consumption on the Kaibab Plateau.

Background: Characterization of physical fuel distributions across heterogeneous landscapes is needed to understand fire behavior, account for smoke emissions, and manage for ecosystem resilience. Remote sensing measurements at various scales inform fuel maps for improved fire and smoke models. Airborne lidar that directly senses variation in vegetation height and density has proven to be especially useful for landscape-scale fuel load and consumption mapping. Here we predicted field-observed fuel loads from airborne lidar and Landsat-derived fire history metrics with random forest (RF) modeling. RF models were then applied across multiple lidar acquisitions (years 2012, 2019, 2020) to create fuel maps across our study area on the Kaibab Plateau in northern Arizona, USA. We estimated consumption across the 2019 Castle and Ikes Fires by subtracting 2020 fuel load maps from 2019 fuel load maps and examined the relationship between mapped surface fuels and years since fire, as recorded in the Monitoring Trends in Burn Severity (MTBS) database. Results: R-squared correlations between predicted and ground-observed fuels were 50, 39, 59, and 48% for available canopy fuel, 1- to 1000-h fuels, litter and duff, and total surface fuel (sum of 1- to 1000-h, litter and duff fuels), respectively. Lidar metrics describing overstory distribution and density, understory density, Landsat fire history metrics, and elevation were important predictors. Mapped surface fuel loads were positively and nonlinearly related to time since fire, with asymptotes to stable fuel loads at 10-15 years post fire. Surface fuel consumption averaged 16.1 and 14.0 Mg ha- 1 for the Castle and Ikes Fires, respectively, and was positively correlated with the differenced Normalized Burn Ratio (dNBR). We estimated surface fuel consumption to be 125.3 ± 54.6 Gg for the Castle Fire and 27.6 ± 12.0 Gg for the portion of the Ikes Fire (42%) where pre- and post-fire airborne lidar were available. Conclusions: We demonstrated and reinforced that canopy and surface fuels can be predicted and mapped with moderate accuracy using airborne lidar data. Landsat-derived fire history helped account for spatial and temporal variation in surface fuel loads and allowed us to describe temporal trends in surface fuel loads. Our fuel load and consumption maps and methods have utility for land managers and researchers who need landscape-wide estimates of fuel loads and emissions. Fuel load maps based on active remote sensing can be used to inform fuel management decisions and assess fuel structure goals, thereby promoting ecosystem resilience. Multitemporal lidar-based consumption estimates can inform emissions estimates and provide independent validation of conventional fire emission inventories. Our methods also provide a remote sensing framework that could be applied in other areas where airborne lidar is available for quantifying relationships between fuels and time since fire across landscapes.

Antecedentes: La caracterización de la distribución física de los combustibles a través de paisajes heterogéneos es necesaria para entender el comportamiento del fuego, contabilizar las emisiones de humo, y manejar los ecosistemas para su resiliencia. Las mediciones mediante sensores remotos a varias escalas, aportan mapas para mejorar modelos de fuegos y dispersión de humos. Las mediciones con LIDAR aerotransportados que determinan directamente variaciones en altura y densidad de la vegetación, han probado ser especialmente útiles para el mapeo de la carga y el consumo de combustible a escala de paisaje. Predijimos la carga de combustibles en la planicie de Kaibab en el norte de Arizona, en los EEUU, estimamos el consumo a través de los incendios de Castle e Ikes de 2019, mediante la substracción de la carga de mapas de carga del 2020 menos los de 2019, y examinamos las relaciones entre el mapeo de los combustibles superficiales y años desde el fuego, registrados en la base de datos titulada Monitoreo de las Tendencias de la Severidad de los incendios (MTBS). Resultados: Las correlaciones de R2 entre valores de cargas predichos y aquellos de observaciones de campo fueron 50, 39, 59, y 48% para combustible disponible en el dosel, combustibles de 1 a 1000 h, mantillo y hojarasca por debajo del mantillo (duff), y combustible total superficial (la suma de combustibles de 1 a 1000 h y del mantillo y la hojarasca subyacente), respectivamente. Las medidas del LIDAR que describían la distribución del dosel y su densidad, la densidad del sotobosque, las medidas históricas de fuego provistas por el Landsat y la altura (elevación) fueron predictores importantes. Las cargas de combustibles mapeadas fueron positivamente y no linealmente relacionadas al tiempo desde el fuego, con asíntotas hacia cargas de combustible estables entre 10 y 15 años post fuego. El consumo de la carga de combustibles en superficie promedió 16,1 y 14,0 Mg por ha para los incendios de Castle e Ikes, respectivamente y fue positivamente correlacionada con la diferencia normalizada de la relación de quema (dNBR). Estimamos que el consumo del combustible superficial fue de 125,3 ± 54,6 Gg para el incendio de Castle y 27,6 ± 12,0 Gg para la porción del incendio de Ikes (42%), del cual los datos de LIDAR aerotransportados (pre y post fuego), estaban disponibles. Conclusiones: Demostramos y reforzamos que tanto el dosel como los combustibles superficiales pueden ser predichos y mapeados con una moderada precisión usando datos de LIDAR aerotransportados. Las medidas históricas de fuego provistas por el Landsat ayudaron a determinar la variación espacial y temporal de la carga de los combustibles superficiales y nos permitieron describir tendencias temporales en las cargas de combustible superficiales. Nuestros mapas y métodos de consumo y cargas de combustible son de utilidad para los gestores de recursos e investigadores que necesitan de estimaciones amplias de carga de combustible y emisiones a escala de paisaje. Los mapas de carga de combustibles basados en sensores remotos activos pueden ser usados para informar sobre decisiones de manejo de combustible y determinar metas de estructuras de cargas, promoviendo de esa manera la resiliencia del ecosistema. Las estimaciones de consumo basadas en LIDAR multitemporal pueden informar sobre estimaciones de emisiones y proveer de una validación de inventarios convencionales de emisiones por fuegos. Nuestros métodos también proveen de un marco conceptual de sensores remotos que pueden ser aplicados en otras áreas donde el LIDAR aerotransportado está disponible para cuantificar relaciones entre combustibles y tiempo desde el fuego en diferentes paisajes.

Beyond the Ångström Exponent: Probing Additional Information in Spectral Curvature and Variability of In Situ Aerosol Hyperspectral (0.3-0.7 µm) Optical Properties.

Ångström exponents (α) allow reconstruction of aerosol optical spectra over a broad range of wavelengths from measurements at two or more wavelengths. Hyperspectral measurements of atmospheric aerosols provide opportunities to probe measured spectra for information inaccessible from only a few wavelengths. Four sets of hyperspectral in situ aerosol optical coefficients (aerosol-phase total extinction, σ ext, and absorption, σ abs; liquid-phase soluble absorption from methanol, σ MeOH-abs, and water, σ DI-abs, extracts) were measured from biomass burning aerosols (BBAs). Hyperspectral single scattering albedo (ω), calculated from σ ext and σ abs, provide spectral resolution over a wide spectral range rare for this optical parameter. Observed spectral shifts between σ abs and σ MeOH-abs/σ DI-abs argue in favor of measuring σ abs rather than reconstructing it from liquid extracts. Logarithmically transformed spectra exhibited curvature better fit by second-order polynomials than linear α. Mapping second order fit coefficients (a 1, a 2) revealed samples from a given fire tended to cluster together, that is, aerosol spectra from a given fire were similar to each other and somewhat distinct from others. Separation in (a 1, a 2) space for spectra with the same α suggest additional information in second-order parameterization absent from the linear fit. Spectral features found in the fit residuals indicate more information in the measured spectra than captured by the fits. Above-detection σ MeOH-abs at 0.7 µm suggests assuming all absorption at long visible wavelengths is BC to partition absorption between BC and brown carbon (BrC) overestimates BC and underestimates BrC across the spectral range. Hyperspectral measurements may eventually discriminate BBA among fires in different ecosystems under variable conditions.

Wildfire-Induced CO Plume Observations From NAST-I During the FIREX-AQ Field Campaign.

The fire influence on regional to global environments and air quality (FIREX-AQ) field campaign was conducted during August 2019 to investigate the impact of wildfire and biomass smoke on air quality and weather in the continental United States. One of the campaign's scientific objectives was to estimate the composition of emissions from wildfires. Ultraspectrally resolved infrared radiance measurements from aircraft and/or satellite observations contain information on tropospheric carbon monoxide (CO) as well as other trace species present in fire emissions. A methodology for retrieving tropospheric CO from such remotely sensed spectral data has been developed for the National Airborne Sounder Testbed-Interferometer (NAST-I) and is applied herein. Retrievals based on NAST-I measurements are used to demonstrate CO retrieval capability and characterize fire emissions. NAST-I remotely sensed CO from ER-2 flights are evaluated with concurrent in situ measurements from the differential absorption carbon monoxide measurements flown on the NASA DC-8 aircraft. Enhanced CO emissions along with plume evolution and transport from the fire ground site locations were captured by moderate vertical and high horizontal resolution observations obtained from the NAST-I IR spectrometer; these were intercompared and verified by the cloud physics lidar and the enhanced MODIS airborne simulator also hosted on the NASA ER-2 aircraft. This study will be beneficial to the science community for studying wildfire-related topics and understanding similar remotely sensed observations from satellites, along with helping to address the broader FIREX-AQ experiment objectives of investigating the impact of fires on air quality and climate.

Ozone chemistry in western U.S. wildfire plumes.

Wildfires are a substantial but poorly quantified source of tropospheric ozone (O3). Here, to investigate the highly variable O3 chemistry in wildfire plumes, we exploit the in situ chemical characterization of western wildfires during the FIREX-AQ flight campaign and show that O3 production can be predicted as a function of experimentally constrained OH exposure, volatile organic compound (VOC) reactivity, and the fate of peroxy radicals. The O3 chemistry exhibits rapid transition in chemical regimes. Within a few daylight hours, the O3 formation substantially slows and is largely limited by the abundance of nitrogen oxides (NOx). This finding supports previous observations that O3 formation is enhanced when VOC-rich wildfire smoke mixes into NOx-rich urban plumes, thereby deteriorating urban air quality. Last, we relate O3 chemistry to the underlying fire characteristics, enabling a more accurate representation of wildfire chemistry in atmospheric models that are used to study air quality and predict climate.