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The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) experiment was a multi‐agency, inter‐disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground‐based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC‐8 and two NOAA Twin Otter aircraft. The high‐altitude NASA ER‐2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC‐8 investigated 87 smaller fires in the Southeast with remote and in‐situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels. Plain Language Summary: The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) experiment was aimed at understanding how fuel and fire conditions at the point of emission influence the chemistry of smoke, what conditions and processes control the rise of smoke plumes, what happens to smoke as it is distributed in the atmosphere, and how chemical transformation of smoke impacts air quality, weather, and climate downwind. Lessons learned from FIREX‐AQ will also be used to assess and improve the effectiveness of satellites for estimating the emissions from wildfires and prescribed burns and to reduce uncertainties associated with modeling and forecasting of smoke. Here we present an overview of the FIREX‐AQ effort, its motivation and design, with detailed descriptions of the measurements and analyses carried out, their connections to FIREX‐AQ science goals, and the early findings of this exceptionally broad effort to understand fire and its many impacts on the atmosphere. Key Points: This work is an overview of the NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) field experimentFIREX‐AQ investigated biomass burning emissions and chemistry and smoke transportFIREX‐AQ was a multi‐platform mission that also utilized fire modeling and satellite detections and validation [ABSTRACT FROM AUTHOR]

The 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment obtained a diverse set of in situ and remotely sensed measurements before and during a pyrocumulonimbus (pyroCb) event over the Williams Flats fire in Washington State. This unique dataset confirms that pyroCb activity is an efficient vertical smoke transport pathway into the upper troposphere and lower stratosphere (UTLS). The magnitude of smoke plumes observed in the UTLS has increased significantly in recent years, following unprecedented wildfire and pyroCb activity observed worldwide. The FIREX-AQ pyroCb dataset is therefore extremely relevant to a broad community, providing the first measurements of fresh smoke exhaust in the upper troposphere, including from within active pyroCb cloud tops. High-resolution remote sensing reveals that three plume cores linked to localized fire fronts, burning primarily in dense forest fuels, contributed to four total pyroCb "pulses." Rapid changes in fire geometry and spatial extent dramatically influenced the magnitude, behavior, and duration of pyroCb activity. Cloud probe measurements and weather radar identify the presence of large ice particles within the pyroCb and hydrometers below cloud base, indicating precipitation development. The resulting feedbacks suggest that vertical smoke transport efficiency was reduced slightly when compared with intense pyroCb events reaching the lower stratosphere. Physical and optical aerosol property measurements in pyroCb exhaust are compared with previous assumptions. A large suite of aerosol and gas-phase chemistry measurements sets a foundation for future studies aimed at understanding the composition of smoke plumes lifted by pyroconvection into the UTLS and their role in the climate system. [ABSTRACT FROM AUTHOR]

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS‐C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground‐based observations. The AVIRIS‐C instrument acquired data from onboard NASA's high altitude ER‐2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal‐estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground‐based AERONET observations demonstrates that AVIRIS‐C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke. Key Points: Imaging spectroscopy enables continuous maps of smoke aerosol and surface properties across heterogeneous terrain and dense plumesInformation content analyses reveal sensitivity of imaging spectroscopy to broad aerosol categoriesSpectra from the complete Visible Shortwave Infrared range, including the shortwave infrared regions, contribute to accurate aerosol characterizations [ABSTRACT FROM AUTHOR]

Motivated by the ongoing debates about the relative contribution of specific North African dust sources to the transatlantic dust transport to the Amazon Basin, the current study integrates a suite of satellite observations into a novel trajectory analysis framework to investigate dust transport from the leading two North African dust sources, namely, the Bodélé depression and El Djouf. In particular, this approach provides observation‐constrained quantification of the dust's dry and wet deposition along its transport pathways and is validated against multiple satellite observations. The current large ensemble trajectory simulations identify favorable transport pathways from the El Djouf across the Atlantic Ocean with respect to seasonal rain belts. The limited potential for long‐range transport of dust from the Bodélé depression is attributed to the currently identified extensive near‐source dust removal primarily by dry and wet deposition during boreal winter and summer, respectively. Plain Language Summary: North African deserts have been reported to export ~200 million tons of dust per year to the tropical Atlantic Ocean, degrading air quality over the Caribbean Islands in boreal summer and supplying nutrients to fertilize the Amazon Rainforest in boreal winter and spring through transatlantic dust transport. It has been assumed that the Bodélé depression is the main contributor to this transatlantic dust transport and Amazonian dust fertilization in boreal winter. However, these claims have not been supported by geochemical analysis. Here, we integrate a suite of satellite observations into a novel trajectory analysis framework to investigate dust transport from the leading two North African dust sources, namely, the Bodélé depression and El Djouf, and provide the first ever observation‐constrained quantification of the dust's dry and wet deposition along its transport pathways. The approach yields the novel observational finding that the El Djouf is the preferred source of intercontinental transport across the Atlantic Ocean rather than the Bodélé depression, bridging the geochemical impact of North African minerals on the Amazon Basin to the specific dust origin. Key Points: The current trajectory simulations quantify observation‐derived dust deposition and capture the observed three‐dimensional dust distributionEl Djouf is the preferred source of the transatlantic dust transport, due to favorable transport pathways with respect to seasonal rain beltsExtensive near‐source dust deposition supports the observed limited potential for long‐range transport of dust from the Bodélé depression [ABSTRACT FROM AUTHOR]

During the twentieth century, the southeast United States cooled, in direct contrast with widespread global and hemispheric warming. While the existing literature is divided on the cause of this so-called "warming hole," anthropogenic aerosols have been hypothesized as playing a primary role in its occurrence. In this study, unique satellite-based observations of aerosol vertical profiles are combined with a one-dimensional radiative transfer model and surface temperature observations to diagnose how major reductions in summertime aerosol burden since 2001 have impacted surface temperatures in the southeast US. We show that a significant improvement in air quality likely contributed to the elimination of the warming hole and acceleration of the positive temperature trend observed in recent years. These reductions coincide with a new EPA rule that was implemented between 2006 and 2010 that revised the fine particulate matter standard downward. Similar to the southeast US in the twentieth century, other regions of the globe may experience masking of long-term warming due to greenhouse gases, especially those with particularly poor air quality [ABSTRACT FROM AUTHOR]

Many air pollution health effects studies rely on exposure estimates of particulate matter (PM) concentrations derived from remote sensing observations of aerosol optical depth (AOD). Simple but robust calibration models between AOD and PM are therefore important for generating reliable PM exposures. We conduct an in-depth examination of the spatial and temporal characteristics of the AOD-PM2.5 relationship by leveraging data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) field campaign where eight NASA Aerosol Robotic Network (AERONET) sites were co-located with EPA Air Quality System (AQS) monitoring sites in California's Central Valley from November 2012 to April 2013. With this spatiotemporally rich data we found that linear calibration models (R2 = 0.35, RMSE = 10.38 μg/m3) were significantly improved when spatial (R2 = 0.45, RMSE = 9.54 μg/m3), temporal (R2 = 0.62, RMSE = 8.30 μg/m3), and spatiotemporal (R2 = 0.65, RMSE = 7.58 μg/m3) functions were included. As a use-case we applied the best spatiotemporal model to convert space-borne MultiAngle Imaging Spectroradiometer (MISR) AOD observations to predict PM2.5 over the region (R2 = 0.60, RMSE = 8.42 μg/m3). Our results imply that simple AERONET AOD-PM2.5 calibrations are robust and can be reliably applied to space-borne AOD observations, resulting in PM2.5 prediction surfaces for use in downstream applications. [ABSTRACT FROM AUTHOR]

Traditionally, aerosol retrieval algorithms are customized to specific instruments because of the diverse nature of remote sensing hardware architectures and data formats. This diversity can hinder the utilization of lower-level data products. Furthermore, a generalized aerosol retrieval approach has the potential to allow simultaneous use of observations from multiple platforms within a single retrieval framework. In this work, a comprehensive set of solutions for integrating open-source aerosol retrieval software and publicly available multiangle spectropolarimetric data products is presented as a complementary software program (CSP). This CSP is adaptable to observations obtained from various instruments, including the Airborne Multiangle Spectropolarimetric Imager (AirMSPI) and the upcoming Multiangle Imager for Aerosols (MAIA) (Diner et al., 2013); (Maia, 2022). Established methods for reconciling coordinate systems, curating data, and structuring data for input to the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) open-source software are addressed by the CSP (Grasp-open, 2023).The CSP provides the functionality to compute multiple GRASP aerosol retrievals from the same polarimetric observations by varying the user-defined coordinate system selection. Each coordinate system is defined by a unique reference plane, which rotates the reported polarization orientation but does not alter the information content. Therefore retrieving aerosol values from different coordinate systems is suggested as a tool for: (1) verifying the coordinate systems of the instrument and algorithm have been properly reconciled and (2) quantifying numerical variations in the retrieval's optimization algorithm. The CSP is demonstrated using AirMSPI data from the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign (Diner et al., 2013); (Warneke, 2019). Aerosol retrievals performed with the meridian versus the scattering reference plane differed up to 0.068 in aerosol optical depth and 0.015 in single scattering albedo. These variations in smoke properties from multiangle spectropolarimetric observations quantify uncertainty which is applicable for cross-validation instrument comparisons and studies of different retrieval algorithms. • Polarimetric Geometry Reconciliation Validation Using Two Reference Planes. • Merging Multiangle Polarimetric Data and a Generalized Radiative Transfer Algorithm. • GRASP Aerosol Retrievals of AirMSPI FIREX-AQ Data. • Python Code to Prepare Data for GRASP Input. [ABSTRACT FROM AUTHOR]

Dust from North Africa has been reported to affect the air quality over Caribbean Islands and southeastern United State, as well as supplying nutrients to fertilize the Amazon forest. However, the relative contribution from North Africa dust sources, namely the Bodélé depression and West African deserts, has been debated among different observational and modeling studies. In the current study, dust transport from the Bodélé depression and West African desert are investigated using an observationally constraint, advanced trajectory model that quantifies both dry and wet deposition along trajectory, based on observations of precipitation amount and cloud properties, and is initiated by stereo observations of dust plume height from the Multiangle Imaging SpectroRadiometer (MISR) instrument. Our advanced trajectory model provides an encouraging tool for investigating dust transport, given its capability at successful capturing the observed horizontal and vertical structures of dust transport across the Atlantic.Based on the advanced trajectory modeling, we found the West African deserts contributes substantially more dust than the Bodélé depression to the trans-Atlantic transport in both boreal winter and summer. The relatively contribution from the two North African dust sources are mainly due to differentiated dust transport pathways. For dust particles emitted from both dust sources, wet deposition, primarily driven by substantial rainfall associated with Intertropical Convergence Zone over ocean and intertropical rainbelt over land, overwhelms dry deposition and largely reduces the amount of dust transport to south America in boreal winter and Central and North Americas in boreal summer. According to the precise observation of dust plume height and motion by MISR, substantial removal and suppression of dust plumes occur near the Bodélé depression, supporting the limited potential for long-range transport of dust from the Bodélé depression revealed by the current advanced trajectory modeling. [ABSTRACT FROM AUTHOR]

Ulaanbaatar (UB), the capital city of Mongolia, has extremely poor wintertime air quality with fine particulate matter concentrations frequently exceeding 500 μg/m3, over 20 times the daily maximum guideline set by the World Health Organization. Intensive use of sulfur-rich coal for heating and cooking coupled with an atmospheric inversion amplified by the mid-continental Siberian anticyclone drive these high levels of air pollution. Ground-based air quality monitoring in Mongolia is sparse, making use of satellite observations of aerosol optical depth (AOD) instrumental for characterizing air pollution in the region. We harnessed data from the Multi-angle Imaging SpectroRadiometer (MISR) Version 23 (V23) aerosol product, which provides total column AOD and component-particle optical properties for 74 different aerosol mixtures at 4.4 km spatial resolution globally. To test the performance of the V23 product over Mongolia, we compared values of MISR AOD with spatially and temporally matched AOD from the Dalanzadgad AERONET site and find good agreement (correlation r = 0.845, and root-mean-square deviation RMSD = 0.071). Over UB, exploratory principal component analysis indicates that the 74 MISR AOD mixture profiles consisted primarily of small, spherical, non-absorbing aerosols in the wintertime, and contributions from medium and large dust particles in the summertime. Comparing several machine learning methods for relating the 74 MISR mixtures to ground-level pollutants, including particulate matter with aerodynamic diameters smaller than 2.5 μm ( PM 2.5 ) and 10 μm ( PM 10 ), as well as sulfur dioxide ( SO 2 ), a proxy for sulfate particles, we find that Support Vector Machine regression consistently has the highest predictive performance with median test R 2 for PM 2.5 , PM 10 , and SO 2 equal to 0.461, 0.063, and 0.508, respectively. These results indicate that the high-dimensional MISR AOD mixture set can provide reliable predictions of air pollution and can distinguish dominant particle types in the UB region. [ABSTRACT FROM AUTHOR]