Satellite remote-sensing capability to assess tropospheric-column ratios of formaldehyde and nitrogen dioxide: case study during the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) field campaign
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Published:2023-05-16
Issue:9
Volume:16
Page:2431-2454
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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:
Johnson Matthew S., Souri Amir H., Philip Sajeev, Kumar RajeshORCID, Naeger Aaron, Geddes Jeffrey, Judd Laura, Janz Scott, Chong Heesung, Sullivan JohnORCID
Abstract
Abstract. Satellite retrievals of tropospheric-column formaldehyde (HCHO) and nitrogen dioxide (NO2) are frequently used to investigate the sensitivity of ozone (O3) production to emissions of nitrogen oxides
and volatile organic carbon compounds. This study inter-compared the
systematic biases and uncertainties in retrievals of NO2 and HCHO, as well as
resulting HCHO–NO2 ratios (FNRs), from two commonly applied
satellite sensors to investigate O3 production sensitivities (Ozone
Monitoring Instrument, OMI, and TROPOspheric Monitoring Instrument,
TROPOMI) using airborne remote-sensing data taken during the Long Island
Sound Tropospheric Ozone Study 2018 between 25 June and 6 September 2018.
Compared to aircraft-based HCHO and NO2 observations, the accuracy of
OMI and TROPOMI were magnitude-dependent with high biases in clean
environments and a tendency towards more accurate comparisons to even low
biases in moderately polluted to polluted regions. OMI and TROPOMI NO2 systematic biases were similar in magnitude (normalized median bias, NMB = 5 %–6 %; linear regression slope ≈ 0.5–0.6), with OMI having a high median bias and TROPOMI resulting in small low biases. Campaign-averaged uncertainties in the three satellite retrievals (NASA OMI; Quality Assurance for Essential Climate Variables, QA4ECV OMI; and TROPOMI) of NO2 were generally similar, with TROPOMI retrievals having slightly less spread in the data compared to OMI. The three satellite products differed more when evaluating HCHO retrievals. Campaign-averaged tropospheric HCHO retrievals all had linear regression slopes ∼0.5 and NMBs of 39 %, 17 %, 13 %, and 23 % for NASA OMI, QA4ECV OMI, and TROPOMI at finer (0.05∘×0.05∘) and coarser (0.15∘×0.15∘)
spatial resolution, respectively. Campaign-averaged uncertainty values (root mean square error, RMSE) in NASA and QA4ECV OMI HCHO retrievals were
∼9.0×1015 molecules cm−2
(∼ 50 %–55 % of mean column abundance), and the higher-spatial-resolution retrievals from TROPOMI resulted in RMSE values ∼30 % lower. Spatially averaging TROPOMI tropospheric-column HCHO, along with NO2 and FNRs, to resolutions similar to the OMI reduced the
uncertainty in these retrievals. Systematic biases in OMI and TROPOMI
NO2 and HCHO retrievals tended to cancel out, resulting in all three
satellite products comparing well to observed FNRs. However, while
satellite-derived FNRs had minimal campaign-averaged median biases,
unresolved errors in the indicator species did not cancel out in FNR
calculations, resulting in large RMSE values compared to observations.
Uncertainties in HCHO retrievals were determined to drive the unresolved
biases in FNR retrievals.
Funder
National Aeronautics and Space Administration
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference90 articles.
1. Acarreta, J. R., De Haan, J. F., and Stammes, P.: Cloud pressure retrieval
using the O2–O2 absorption band at 477 nm, J. Geophys. Res.-Atmos., 109, D05204, https://doi.org/10.1029/2003JD003915, 2004. 2. Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017. 3. Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for
tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311,
https://doi.org/10.1029/2003JD003962, 2004. 4. Boersma, K. F., Eskes, H. J., Veefkind, J. P., Brinksma, E. J., van der A, R. J., Sneep, M., van den Oord, G. H. J., Levelt, P. F., Stammes, P., Gleason, J. F., and Bucsela, E. J.: Near-real time retrieval of tropospheric NO2 from OMI, Atmos. Chem. Phys., 7, 2103–2118, https://doi.org/10.5194/acp-7-2103-2007, 2007. 5. Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011, 2011.
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