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Abstract. Glyoxal (CHOCHO), the simplest dicarbonyl in thetroposphere, is a potential precursor for secondary organic aerosol (SOA)and brown carbon (BrC) affecting air quality and climate. The airbornemeasurement of CHOCHO concentrations during the KORUS-AQ (KORea–US AirQuality study) campaign in 2016 enables detailed quantification of lossmechanisms pertaining to SOA formation in the real atmosphere. Theproduction of this molecule was mainly from oxidation of aromatics (59 %)initiated by hydroxyl radical (OH). CHOCHO loss to aerosol was found to bethe most important removal path (69 %) and contributed to roughly∼ 20 % (3.7 µg sm−3 ppmv−1 h−1,normalized with excess CO) of SOA growth in the first 6 h in SeoulMetropolitan Area. A reactive uptake coefficient (γ) of∼ 0.008 best represents the loss of CHOCHO by surface uptakeduring the campaign. To our knowledge, we show the first field observationof aerosol surface-area-dependent (Asurf) CHOCHO uptake, which divergesfrom the simple surface uptake assumption as Asurf increases in ambientcondition. Specifically, under the low (high) aerosol loading, the CHOCHOeffective uptake rate coefficient, keff,uptake, linearly increases(levels off) with Asurf; thus, the irreversible surface uptake is areasonable (unreasonable) approximation for simulating CHOCHO loss toaerosol. Dependence on photochemical impact and changes in the chemical andphysical aerosol properties “free water”, as well as aerosol viscosity,are discussed as other possible factors influencing CHOCHO uptake rate. Ourinferred Henry's law coefficient of CHOCHO, 7.0×108 M atm−1, is ∼ 2 orders of magnitude higher than thoseestimated from salting-in effects constrained by inorganic salts onlyconsistent with laboratory findings that show similar high partitioning intowater-soluble organics, which urges more understanding on CHOCHO solubilityunder real atmospheric conditions. 

Abstract. Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns and can help improve the online calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NOx emissions using the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI) NO2 dataset. Advancements and improvements to the satellite-based determination of forest fire NOx emissions are discussed, including information on plume height and effects of aerosol scattering and absorption on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an exponentially modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime, and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses.The effect of smoke aerosols on TROPOMI NO2 columns (via air mass factors, AMFs) is estimated, and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO2 columns improves the agreement with the aircraft observations (by about 10 %–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well; however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NOx e-folding time of 2 ±1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NOx are 1.3 to 1.5 times greater than the satellite-derived NO2 emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NOx emissions from the satellite retrievals of NO2.