Glyoxal tropospheric column retrievals from TROPOMI – multi-satellite intercomparison and ground-based validation
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Published:2021-12-10
Issue:12
Volume:14
Page:7775-7807
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ISSN:1867-8548
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Container-title:Atmospheric Measurement Techniques
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language:en
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Short-container-title:Atmos. Meas. Tech.
Author:
Lerot ChristopheORCID, Hendrick François, Van Roozendael Michel, Alvarado Leonardo M. A.ORCID, Richter AndreasORCID, De Smedt IsabelleORCID, Theys Nicolas, Vlietinck Jonas, Yu Huan, Van Gent JeroenORCID, Stavrakou Trissevgeni, Müller Jean-François, Valks Pieter, Loyola DiegoORCID, Irie Hitoshi, Kumar VinodORCID, Wagner Thomas, Schreier Stefan F.ORCID, Sinha VinayakORCID, Wang Ting, Wang Pucai, Retscher Christian
Abstract
Abstract. We present the first global glyoxal (CHOCHO) tropospheric column
product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on
board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results
from the oxidation of other non-methane volatile organic compounds (NMVOCs)
and from direct emissions caused by combustion processes. Therefore, this
product is a useful indicator of VOC emissions. It is generated with an
improved version of the BIRA-IASB scientific retrieval algorithm relying on
the differential optical absorption spectroscopy (DOAS) approach. Among the
algorithmic updates, the DOAS fit now includes corrections to mitigate the
impact of spectral misfits caused by scene brightness inhomogeneity and
strong NO2 absorption. The product comes along with a full error
characterization, which allows for providing random and systematic error
estimates for every observation. Systematic errors are typically in the
range of 1 ×1014–3 ×1014 molec. cm−2 (∼30 %–70 % in emission regimes) and originate mostly from a priori data uncertainties
and spectral interferences with other absorbing species. The latter
may be at the origin, at least partly, of an enhanced glyoxal signal over
equatorial oceans, and further investigation is needed to mitigate them.
Random errors are large (>6×1014 molec. cm−2)
but can be reduced by averaging observations in space and/or time.
Benefiting from a high signal-to-noise ratio and a large number of
small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are
also generated from the Ozone Monitoring Instrument (OMI) on Aura and from
the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and
Metop-B. Those four data sets are intercompared over large-scale regions
worldwide and show a high level of consistency. The satellite glyoxal
columns are also compared to glyoxal columns retrieved from ground-based
Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In
general, the satellite and MAX-DOAS instruments provide consistent glyoxal
columns both in terms of absolute values and variability. Correlation
coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where
satellite data appear to be biased low during wintertime. The mean absolute
glyoxal columns from satellite and MAX-DOAS generally agree well for
low/moderate columns with differences of less than 1×1014 molec. cm−2. A larger bias is identified at two sites where
the MAX-DOAS columns are very large. Despite this systematic bias, the
consistency of the satellite and MAX-DOAS glyoxal seasonal variability is
high.
Funder
European Space Agency European Organization for the Exploitation of Meteorological Satellites Belgian Federal Science Policy Office Deutsches Zentrum für Luft- und Raumfahrt Austrian Science Fund Deutsche Forschungsgemeinschaft
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference124 articles.
1. Abbot, D. S., Palmer, P. I., Martin, R. V., Chance, K. V., Jacob, D. J., and
Guenther, A.: Seasonal and interannual variability of North American
isoprene emissions as determined by formaldehyde column measurements from
space, Geophys. Res. Lett., 30, 1886, https://doi.org/10.1029/2003GL017336, 2003. 2. Aliwell, S. R., Van Roozendael, M., Johnston, P. V., Richter, A., Wagner,
T., Arlander, D. W., Burrows, J. P., Fish, D. J., Jones, R. L.,
Tørnkvist, K. K., Lambert, J. C., Pfeilsticker, K., and Pundt, I.:
Analysis for BrO in zenith-sky spectra: An intercomparison exercise for
analysis improvement, J. Geophys. Res.-Atmos., 107, 4199,
https://doi.org/10.1029/2001JD000329, 2002. 3. Alvarado, L. M. A., Richter, A., Vrekoussis, M., Wittrock, F., Hilboll, A., Schreier, S. F., and Burrows, J. P.: An improved glyoxal retrieval from OMI measurements, Atmos. Meas. Tech., 7, 4133–4150, https://doi.org/10.5194/amt-7-4133-2014, 2014. 4. Alvarado, L. M. A., Richter, A., Vrekoussis, M., Hilboll, A., Kalisz Hedegaard, A. B., Schneising, O., and Burrows, J. P.: Unexpected long-range transport of glyoxal and formaldehyde observed from the Copernicus Sentinel-5 Precursor satellite during the 2018 Canadian wildfires, Atmos. Chem. Phys., 20, 2057–2072, https://doi.org/10.5194/acp-20-2057-2020, 2020a. 5. Alvarado L., Richter, A., and Lerot, C.: Sentinel-5p+Innovation: Theme 1; Glyoxal Retrievals from TROPOMI (GLYRETRO): Product Validation Report, v1.1, S5p+I_CHOCHO_BIRA_VR, 19 November 2020, available at: https://glyretro.aeronomie.be/ProjectDir/documents/GLYRETRO_validation_report_v1.1.pdf (last access: 6 December 2021), 2020b.
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