Atmospheric Measurement Techniques (May 2020)

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

  • S. Choi,
  • S. Choi,
  • L. N. Lamsal,
  • L. N. Lamsal,
  • M. Follette-Cook,
  • M. Follette-Cook,
  • J. Joiner,
  • N. A. Krotkov,
  • W. H. Swartz,
  • K. E. Pickering,
  • K. E. Pickering,
  • C. P. Loughner,
  • W. Appel,
  • G. Pfister,
  • P. E. Saide,
  • R. C. Cohen,
  • A. J. Weinheimer,
  • J. R. Herman,
  • J. R. Herman

DOI
https://doi.org/10.5194/amt-13-2523-2020
Journal volume & issue
Vol. 13
pp. 2523 – 2546

Abstract

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NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) 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 the 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 datasets 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 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, 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 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (>312 km2).