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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 04 Feb 2020

Submitted as: research article | 04 Feb 2020

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A revised version of this preprint is currently under review for the journal AMT.

Inter-comparison of MAX-DOAS measurements of tropospheric HONO slant column densities and vertical profiles during the CINDI-2 Campaign

Yang Wang1, Arnoud Apituley2, Alkiviadis Bais3, Steffen Beirle1, Nuria Benavent4, Alexander Borovski5, Ilya Bruchkouski6, Ka Lok Chan7,8, Sebastian Donner1, Theano Drosoglou3, Henning Finkenzeller9,10, Martina M. Friedrich11, Udo Frieß12, David Garcia-Nieto4, Laura Gómez-Martín13, François Hendrick11, Andreas Hilboll14, Junli Jin15, Paul Johnston16, Theodore K. Koenig9,10, Karin Kreher17, Vinod Kumar1, Aleksandra Kyuberis18, Johannes Lampel12,19, Cheng Liu20, Haoran Liu20, Jianzhong Ma21, Oleg L. Polyansky22,18, Oleg Postylyakov5, Richard Querel16, Alfonso Saiz-Lopez4, Stefan Schmitt12, Xin Tian23,24, Jan-Lukas Tirpitz12, Michel Van Roozendael11, Rainer Volkamer9,10, Zhuoru Wang8, Pinhua Xie24, Chengzhi Xing25, Jin Xu24, Margarita Yela13, Chengxin Zhang25, and Thomas Wagner1 Yang Wang et al.
  • 1Max Planck Institute for Chemistry, Mainz, Germany
  • 2Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
  • 3Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 4Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano (CSIC), Madrid, Spain
  • 5A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia
  • 6National Ozone Monitoring Research and Education Center BSU (NOMREC BSU), Belarusian State University, Minsk, Belarus
  • 7Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
  • 8Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
  • 9Department of Chemistry, University of Colorado Boulder, Boulder, CO, USA
  • 10Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA
  • 11Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
  • 12Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany
  • 13National Institute of Aerospatial Technology, Madrid, Spain
  • 14Institute of Environmental Physics, University of Bremen, Bremen, Germany
  • 15Meteorological Observation Center, China Meteorological Administration, Beijing, China
  • 16National Institute of Water & Atmospheric Research (NIWA), Lauder, New Zealand
  • 17BK Scientific, Mainz, Germany
  • 18Institute of Applied Physics, Russian Academy of Sciences, Nizhny Novgorod, Russia
  • 19Airyx GmbH, Justus-von-Liebig-Str. 14, 69214 Eppelheim, Germany
  • 20Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui, China
  • 21Chinese Academy of Meteorology Science, China Meteorological Administration, Beijing, China
  • 22Department of Physics and Astronomy, University College London, Gower St, London WC1E 6BT, UK
  • 23Institutes of Physical Science and Information Technology, Anhui University, Hefei, 230601, China
  • 24Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
  • 25School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui, China

Abstract. We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different MAX-DOAS instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2), in September 2016, at Cabauw, The Netherlands (51.97° N, 4.93° E). Systematic discrepancies of HONO delta SCDs are observed in the range of ±0.3 × 1015 molecules cm−2, which is half of the typical random discrepancy of 0.6 × 1015 molecules cm−2. For a typical high HONO delta SCD of 2 × 1015 molecules cm−2, the relative systematic and random discrepancies are about 15 % and 30 %, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of ~ ±0.5 × 1015 molecules cm−2 and ~ ±0.1 ppb (typically ~ 20 %). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by ~ 5 %. However, some data sets with substantial larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than ~ 3 × 1015 molecules cm−2. The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of ~ 0.4 ppb) often appeared in the early morning and below 0.2 km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 ppb and 0.07 ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can well reproduce the different HONO profile shapes. Therefore we conclude that the feature of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to well represent the ambient HONO profiles.

Yang Wang et al.

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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Yang Wang et al.

Yang Wang et al.


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