Assessment of NO<sub>2</sub> observations during DISCOVER-AQ and KORUS-AQ field campaigns

Abstract

Abstract. NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with a goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique data sets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a-priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 33.3 %. These show even larger differences with Pandora, reaching up to 53.1 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of two lower in these highly polluted environments, due in part to inaccurate retrieval assumptions (e.g., a priori profiles), but mostly to OMI’s areal (> 312 km2) averaging.

Explicit and consistent aerosol correction for visible wavelength satellite cloud and nitrogen dioxide retrievals based on optical properties from a global aerosol analysis

“…This enhancement is caused by the combined effect of the explicit aerosol correction on the cloud parameters and clear-sky NO 2 AMFs. This aerosol correction is in line with low biases in the satellite NO 2 retrievals as documented in several publications (Lamsal et al, 2014;Krotkov et al, 2017;Herman et al, 2019;Choi et al, 2019 that OMI NO2 retrievals are about 20% lower as compared to validation measurements even after accounting for the effect of a-priori NO 2 profiles and spatial mismatch using high-resolution NO 2 simulations (Choi et al, 2019). Both studies point to surface reflectivity and other factors in the NO 2 AMF for the low biases in OMI NO 2 retrievals.…”

TROPOMI NO2 in the United States: A Detailed Look at the Annual Averages, Weekly Cycles, Effects of Temperature, and Correlation With Surface NO2 Concentrations

“…The AMF is the most uncertain quantity in the retrieval algorithm (Lorente, Folkert Boersma, et al, 2017) and is a function of the surface reflectance, the NO 2 vertical profile, and scattering in the atmosphere among other factors. Using accurate and high-resolution data (spatially and temporally) as inputs in calculating the AMF can significantly reduce the overall errors of the AMF (S. Choi et al, 2019;Goldberg et al, 2017;Lamsal, 2020;Laughner, Zare, & Cohen, 2016, Laughner, Zhu, & Cohen, 2019Lin et al, 2015;M. Liu et al, 2019;Russell, Perring, et al, 2011;Zhao et al, 2020) and thus the tropospheric vertical column content.…”

Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO<sub>2</sub> measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

“…These results are within the mission requirement of a maximum bias of 50%, but exceed the uncertainty requirement of maximum 0.7 Pmolec/cm 2 , which is however reached for the clean sites ensemble. Pandora data have been used before to validate satellite NO 2 measurements from Aura OMI (Herman et al, 2009;Tzortziou et al, 2014;Kollonige et al, 2018;Choi et al, 2019;Judd et al, 2019;Griffin et al, 2019;Herman et al, 2019;Pinardi et al, 2020) and TROPOMI (Griffin et al, 2019;Ialongo et al, 2020;Zhao et al, 2019). Except at low sun elevation, the footprint of these direct-sun measurements is much smaller than a TROPOMI pixel.…”