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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Highlights from 4STAR Sky-Scanning Retrievals of Aerosol Intensive Optical Properties from Multiple Field Campaigns with Detailed Comparisons of SSA Reported During SEAC4RS

The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument combines airborne sun tracking capabilities of the Ames Airborne Tracking Sun Photometer (AATS-14) with AERONET (Aerosol Robotic Network)-like sky-scanning capability and adds state-of-the-art fiber-coupled grating spectrometry to yield hyperspectral measurements of direct solar irradiance and angularly resolved sky radiance. The combination of sun-tracking and sky-scanning capability enables retrievals of wavelength-dependent aerosol optical depth (AOD), mode-resolved aerosol size distribution (SD), asphericity, and complex refractive index, and thus also the scattering phase function, asymmetry parameter, single-scattering albedo (SSA), and absorption aerosol optical thickness (AAOT). From 2012 to 2014 4STAR participated in four major field campaigns: the U.S. Dept. of Energy's TCAP (Two-Column Aerosol Project) I & II campaigns, and NASA's SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) and ARISE (Arctic Radiation - IceBridge Sea & Ice Experiment) campaigns. Establishing a strong performance record, 4STAR operated successfully on all flights conducted during each of these campaigns. Sky radiance spectra from scans in either constant azimuth (principal plane) or constant zenith angle (almucantar) were interspersed with direct beam measurements during level legs. During SEAC4RS and ARISE, 4STAR airborne measurements were augmented with flight-level albedo from the collocated Shortwave Spectral Flux Radiometer (SSFR) providing improved specification of below-aircraft radiative conditions for the retrieval. Calibrated radiances and retrieved products will be presented with particular emphasis on detailed comparisons of ambient SSA retrievals and measurements during SEAC4RS from 4STAR, AERONET, HSRL2 (High Spectral Resolution Lidar), and from in situ measurements.

Radiance↗
NASA NTRS2015

4STAR Sky-Scanning Retrievals of Aerosol Intensive Optical Properties from Multiple Field Campaigns with Detailed Comparisons of SSA Reported During SEAC4RS

The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument combines airborne sun tracking capabilities of the Ames Airborne Tracking Sun Photometer (AATS-14) with AERONET-like sky-scanning capability and adds state-of-the-art fiber-coupled grating spectrometry to yield hyper spectral measurements of direct solar irradiance and angularly resolved sky radiance. The combination of sun-tracking and sky-scanning capability enables retrievals of wavelength-dependent aerosol optical depth (AOD), mode-resolved aerosol size distribution (SD), asphericity, and complex refractive index, and thus also the scattering phase function, asymmetry parameter, single-scattering albedo (SSA), and absorption aerosol optical thickness (AAOT).From 2012 to 2014 4STAR participated in four major field campaigns: the U.S. Dept. of Energy TCAP I II campaigns, and NASAs SEAC4RS and ARISE campaigns. Establishing a strong performance record, 4STAR operated successfully on all flights conducted during each of these campaigns. Sky radiance spectra from scans in either constant azimuth (principal plane) or constant zenith angle (almucantar) were interspersed with direct beam measurements during level legs. During SEAC4RS and ARISE, 4STAR airborne measurements were augmented with flight-level albedo from the collocated Shortwave Spectral Flux Radiometer (SSFR) providing improved specification of below-aircraft radiative conditions for the retrieval. Calibrated radiances and retrieved products will be presented with particular emphasis on detailed comparisons of ambient SSA retrievals and measurements during SEAC4RS from 4STAR, AERONET, HSRL2, and from in situ measurements.

Flynn, Connor↗
NASA NTRS2016

Planning, Implementation, and Scientific Goals of the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) Field Missions

The Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission based at Ellington Field, Texas, during August and September 2013 employed the most comprehensive airborne payload to date to investigate atmospheric composition over North America. The NASA ER-2, DC-8, and SPEC Inc. Learjet flew 57 science flights from the surface to 20 km. The ER-2 employed seven remote sensing instruments as a satellite surrogate and eight in situ instruments. The DC-8 employed 23 in situ and five remote sensing instruments for radiation, chemistry, and microphysics. The Learjet used 11 instruments to explore cloud microphysics. SEAC4RS launched numerous balloons, augmented Aerosol RObotic NETwork, and collaborated with many existing ground measurement sites. Flights investigating convection included close coordination of all three aircraft. Coordinated DC-8 and ER-2 flights investigated the optical properties of aerosols, the influence of aerosols on clouds, and the performance of new instruments for satellite measurements of clouds and aerosols. ER-2 sorties sampled stratospheric injections of water vapor and other chemicals by local and distant convection. DC-8 flights studied seasonally evolving chemistry in the Southeastern U.S., atmospheric chemistry with lower emissions of NOx and SO2 than in previous decades, isoprene chemistry under high and low NOx conditions at different locations, organic aerosols, air pollution near Houston and in petroleum fields, smoke from wildfires in western forests and from agricultural fires in the Mississippi Valley, and the ways in which the chemistry in the boundary layer and the upper troposphere were influenced by vertical transport in convective clouds.

Toon, Owen B.↗
NASA NTRS2014

Research Scanning Polarimeter (RSP): Retrievals from PODEX and SEAC4RS

We illustrate our methods on examples from the recent NASA's field campaigns POlarimeter Definition EXperiment (PODEX, based in Palmdale, California, January - February 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, based in Houston, Texas in August - September 2013). During these campaigns the RSP was onboard the NASA's long-range high-altitude ER-2 aircraft together with an array of other remote sensing instrumentation. Correlative sampling measurements from another aircraft were also available. The data obtained during these campaigns provides an excellent opportunity to study cloud properties in variety of locations and atmospheric conditions. We present examples of boundary layer cumulus and stratocumulus clouds, liquid altostratus clouds, and fogs. In the latter two cases the droplet size distribution derived from RFT analysis exhibited multiple modes corresponding to different cloud layers, as supported by the correlative lidar atmospheric profiles.

climate↗
NASA NTRS2015

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha−x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

fires↗
NASA NTRS2016

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

ozone↗
NASA NTRS2016

Agricultural Fires in the Southeastern U.S. During SEAC4RS: Emissions of Trace Gases and Particles and Evolution of Ozone, Reactive Nitrogen, and Organic Aerosol

Emissions from 15 agricultural fires in the southeastern U.S. were measured from the NASA DC-8 research aircraft during the summer 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. This study reports a detailed set of emission factors (EFs) for 25 trace gases and 6 fine particle species. The chemical evolution of the primary emissions in seven plumes was examined in detail for ~1.2 h. A Lagrangian plume cross-section model was used to simulate the evolution of ozone (O3), reactive nitrogen species, and organic aerosol (OA). Observed EFs are generally consistent with previous measurements of crop residue burning, but the fires studied here emitted high amounts of SO2 and fine particles, especially primary OA and chloride. Filter-based measurements of aerosol light absorption implied that brown carbon (BrC) was ubiquitous in the plumes. In aged plumes, rapid production of O3, peroxyacetyl nitrate (PAN), and nitrate was observed with (Delta)O3/(Delta)CO, (Delta)PAN/(Delta)NOy, and (Delta)nitrate/(Delta)NOy reaching approx. 0.1, approx. 0.3, and approx.0.3. For five selected cases, the model reasonably simulated O3 formation but underestimated PAN formation. No significant evolution of OA mass or BrC absorption was observed. However, a consistent increase in oxygen-to-carbon (O/C) ratios of OA indicated that OA oxidation in the agricultural fire plumes was much faster than in urban and forest fire plumes. Finally, total annual SO2, NOx, and CO emissions from agricultural fires in Arkansas, Louisiana, Mississippi, and Missouri were estimated (within a factor of approx. 2) to be equivalent to approx. 2% SO2 from coal combustion and approx. 1% NOx and approx. 9% CO from mobile sources.

OA mass or BrC absorption↗
NASA NTRS2020

A Classification of Ice Crystal Habits Using Combined Lidar and Scanning Polarimeter Observations during the SEAC4RS Campaign

Using collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses a K-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such as CALIPSO and POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

Natalie Midzak↗
NASA NTRS2014

Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.

Aerosol-Climate↗
NASA NTRS2014

Wildfire Emissions and Their Interaction with Urban and Rural Pollution: Data and Simulations

In recent years NASA has conducted a series of airborne campaigns (e. g. SEAC4RS*, ARCTAS, INTEX-A/B) over North America using an instrumented DC-8 aircraft equipped to measure a very large number of gaseous and aerosol constituents including several unique tracers. In these campaigns wild fires were extensively sampled near source as well as downwind after aging. The data provided detailed information on the composition and chemistry of fire emissions under a variety of atmospheric conditions as well as their interactions with rural and urban air pollution. Major fires studied including the California Rim fire in 2013 (SEAC4RS), the 2008 California wildfires (ARCTAS), and the Alaskan fires downwind over eastern US (INTEX-A). Although some fire plumes contained virtually no O3 enhancement, others showed significant ozone formation. Over Los Angeles, the highest O3 mixing ratios were observed in fire influenced urban air masses. Attempts to simulate these interactions using state of the art models were only minimally successful and indicated several shortcomings in simulating fire emission influences on urban smog formation. A variety of secondary oxidation products (e. g. O3, PAN, HCHO) were substantially underestimated. We will discuss the data collected in fire influenced air masses and their potential air quality implications.

FIre Emissions↗
NASA NTRS2014

Aerosol Properties Derived from Airborne Sky Radiance and Direct Beam Measurements in Recent NASA and DoE Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions.The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL (Pacific Northwest National Laboratory) with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. The 4STAR instrument operated successfully in the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE (Department of Energy)-sponsored TCAP (Two Column Aerosol Project, July 2012 & Feb. 2013) experiment aboard the DoE G-1 aircraft. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In this presentation, we provide an overview of the new 4STAR capabilities, with an emphasis on 26 high-quality sky radiance measurements carried out by 4STAR in SEAC4RS. We compare collocated 4STAR and AERONET sky radiances, as well as their retrievals of aerosol microphysical properties for a subset of the available case studies. We summarize the particle property and air-mass characterization studies made possible by the combined 4STAR direct beam and sky radiance observations.

DoE↗
NASA NTRS2014

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗
NASA NTRS2016

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

airborne sun photometer↗
NASA NTRS2017

Ground-Based High Spectral Resolution Lidar Observation of Aerosol Vertical Distribution in the Summertime Southeast United States

As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August-September SEAC4RS campaign, the site allowed the regions first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. ''Fair weather'' days exhibited classic planetary boundary layer structure of a mixed layer accounting for approx. 50% of AOT and an entrainment zone providing another 25%. An additional 5-15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0 C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10-15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

HSRL↗
NASA NTRS2019

Towards a Satellite Formaldehyde – in situ Hybrid Estimate for Organic Aerosol Abundance

Organic aerosol (OA) is one of the main components of the global particulate burden and intimately links natural and anthropogenic emissions with air quality and climate. It is challenging to accurately represent OA in global models. Direct quantification of global OA abundance is not possible with current remote sensing technology; however, it may be possible to exploit correlations of OA with remotely observable quantities to infer OA spatiotemporal distributions. In particular, formaldehyde (HCHO) and OA share common sources via both primary emissions and secondary production from oxidation of volatile organic compounds (VOCs). Here, we examine OA–HCHO correlations using data from summertime airborne campaigns investigating biogenic (NASA SEAC4RS and DC3), biomass burning (NASA SEAC4RS), and anthropogenic conditions (NOAA CalNex and NASA KORUS-AQ). In situ OA correlates well with HCHO (r=0.59–0.97), and the slope and intercept of this relationship depend on the chemical regime. For biogenic and anthropogenic regions, the OA–HCHO slopes are higher in low NOx conditions, because HCHO yields are lower and aerosol yields are likely higher. The OA–HCHO slope of wildfires is over 9 times higher than that for biogenic and anthropogenic sources. The OA–HCHO slope is higher for highly polluted anthropogenic sources (e.g., KORUS-AQ) than less polluted (e.g., CalNex) anthropogenic sources. Near-surface OAs over the continental US are estimated by combining the observed in situ relationships with HCHO column retrievals from NASA's Ozone Monitoring Instrument (OMI). HCHO vertical profiles used in OA estimates are from climatology a priori profiles in the OMI HCHO retrieval or output of specific period from a newer version of GEOS-Chem. Our OA estimates compare well with US EPA IMPROVE data obtained over summer months (e.g., slope =0.60–0.62, r=0.56 for August 2013), with correlation performance comparable to intensively validated GEOS-Chem (e.g., slope =0.57, r=0.56) with IMPROVE OA and superior to the satellite-derived total aerosol extinction (r=0.41) with IMPROVE OA. This indicates that OA estimates are not very sensitive to these HCHO vertical profiles and that a priori profiles from OMI HCHO retrieval have a similar performance to that of the newer model version in estimating OA. Improving the detection limit of satellite HCHO and expanding in situ airborne HCHO and OA coverage in future missions will improve the quality and spatiotemporal coverage of our OA estimates, potentially enabling constraints on global OA distribution.

anthropogenic emissions↗