An intercomparison of satellite, airborne, and ground-level observations with WRF–CAMx simulations of NO2 columns over Houston, Texas, during the September 2021 TRACER-AQ campaign
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Published:2024-06-10
Issue:11
Volume:24
Page:6719-6741
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Nawaz M. OmarORCID, Johnson JeremiahORCID, Yarwood GregORCID, de Foy BenjaminORCID, Judd Laura, Goldberg Daniel L.ORCID
Abstract
Abstract. Nitrogen dioxide (NO2) is a precursor of ozone (O3) and fine particulate matter (PM2.5) – two pollutants that are above regulatory guidelines in many cities. Bringing urban areas into compliance of these regulatory standards motivates an understanding of the distribution and sources of NO2 through observations and simulations. The TRACER-AQ campaign, conducted in Houston, Texas, in September 2021, provided a unique opportunity to compare observed NO2 columns from ground-, airborne-, and satellite-based spectrometers. In this study, we investigate how these observational datasets compare and simulate column NO2 using WRF–CAMx with fine resolution (444 × 444 m2) comparable to the airborne column measurements. We compare WRF-simulated meteorology to ground-level monitors and find good agreement. We find that observations from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) instrument were strongly correlated (r2 = 0.79) to observations from Pandora spectrometers with a slight high bias (normalized mean bias (NMB) = 3.4 %). Remote sensing observations from the TROPOspheric Monitoring Instrument (TROPOMI) were generally well correlated with Pandora observations (r2 = 0.73) with a negative bias (NMB = −22.8 %). We intercompare different versions of TROPOMI data and find similar correlations across three versions but slightly different biases (from −22.8 % in v2.4.0 to −18.2 % in the NASA MINDS product). Compared with Pandora observations, the WRF–CAMx simulation had reduced correlation (r2 = 0.34) and a low bias (−21.2 %) over the entire study region. We find particularly poor agreement between simulated NO2 columns and GCAS-observed NO2 columns in downtown Houston, an area of high population and roadway densities. These findings point to a potential underestimate of NOx emissions (NOx = NO + NO2) from sources associated with the urban core of Houston, such as mobile sources, in the WRF–CAMx simulation driven by the Texas state inventory, and further investigation is recommended.
Funder
Texas Commission on Environmental Quality National Aeronautics and Space Administration
Publisher
Copernicus GmbH
Reference63 articles.
1. Achakulwisut, P., Brauer, M., Hystad, P., and Anenberg, S. C.: Global, national, and urban burdens of paediatric asthma incidence attributable to ambient NO2 pollution: estimates from global datasets, Lancet Planet. Health, 3, e166–e178, https://doi.org/10.1016/S2542-5196(19)30046-4, 2019. 2. Anenberg, S. C., Mohegh, A., Goldberg, D. L., Kerr, G. H., Brauer, M., Burkart, K., Hystad, P., Larkin, A., Wozniak, S., and Lamsal, L.: Long-term trends in urban NO2 concentrations and associated paediatric asthma incidence: estimates from global datasets, Lancet Planet. Health, 6, e49–e58, https://doi.org/10.1016/S2542-5196(21)00255-2, 2022. 3. Boersma, K. F., Eskes, H. J., Richter, A., De Smedt, I., Lorente, A., Beirle, S., van Geffen, J. H. G. M., Zara, M., Peters, E., Van Roozendael, M., Wagner, T., Maasakkers, J. D., van der A, R. J., Nightingale, J., De Rudder, A., Irie, H., Pinardi, G., Lambert, J.-C., and Compernolle, S. C.: Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project, Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, 2018. 4. Bucsela, E. J., Krotkov, N. A., Celarier, E. A., Lamsal, L. N., Swartz, W. H., Bhartia, P. K., Boersma, K. F., Veefkind, J. P., Gleason, J. F., and Pickering, K. E.: A new stratospheric and tropospheric NO2 retrieval algorithm for nadir-viewing satellite instruments: applications to OMI, Atmos. Meas. Tech., 6, 2607–2626, https://doi.org/10.5194/amt-6-2607-2013, 2013. 5. Cede, A.: Manual for Blick Software Suite 1.8, LUFTBLICK, https://www.pandonia-global-network.org/wp-content/uploads/2020/12/BlickSoftwareSuite_Manual_v1-8-1.pdf (last access: March 2024), 2021.
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