Preprints
https://doi.org/10.5194/acp-2022-299
https://doi.org/10.5194/acp-2022-299
 
27 Apr 2022
27 Apr 2022
Status: this preprint is currently under review for the journal ACP.

Evaluating NOx emissions and their effect on O3 production in Texas using TROPOMI NO2 and HCHO

Daniel Goldberg1, Monica Harkey2, Benjamin de Foy3, Laura Judd4, Jeremiah Johnson5, Greg Yarwood5, and Tracey Holloway2,6 Daniel Goldberg et al.
  • 1Department of Environmental and Occupational Health, Milken Institute of Public Health, George Washington University, Washington, DC, USA
  • 2Nelson Institute Center for Sustainability and the Global Environment (SAGE), University of Wisconsin-Madison, Madison, WI, USA
  • 3Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, USA
  • 4NASA Langley Research Center, Hampton, VA, USA
  • 5Ramboll, Novato, CA, USA
  • 6Department of Atmospheric & Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite is a valuable source of information to monitor the NOx emissions that adversely affect air quality. We conduct a series of experiments using a 4 × 4 km2 Comprehensive Air Quality Model with Extensions (CAMx) simulation during April–September 2019 in east Texas to evaluate the multiple challenges that arise in reconciling the NOx emissions in model simulations with TROPOMI. We first compare the TROPOMI NO2 version 1.3 and version 2.3.1 algorithms in east Texas and document that tropospheric vertical column NO2 increases +17 % in urban areas, with further increases (~25 %) in the city centers and smaller increases (~5 %) in less polluted areas. We then demonstrate the importance of having lightning NOx emissions in a model simulation that is compared to satellite observations. Lightning NOx can contribute up 24 % of the column NO2 in the areas over the Gulf of Mexico and 8 % in Texas urban areas. NOx emissions, when using locally resolved inputs, agree with TROPOMI NO2 version 2.3.1 to within 20 % in most circumstances, with a small NOx underestimate in Dallas-Fort Worth (– 13 %) and Houston (– 20 %). In the vicinity of large power plant plumes (e.g., Martin Lake and Limestone) we find larger disagreements: the satellite consistently underrepresents the NO2 from measured stack emissions by 40–60 %. We hypothesize that either: 1.) TROPOMI has difficulty capturing narrow point source plumes, 2.) the assumed lifetime to derive the NOx emissions is too long, or 3.) the vertical/horizontal dispersion in the model is too slow. If we assume short effective NO2 lifetimes (< 1 hour), there is better agreement between the satellite-derived NOx emissions and the model. To understand ozone formation regimes in the area, we combine NO2 column information with HCHO column information. For HCHO, we find good agreement in far eastern Texas and an underestimate (– 25 %) in the areas of central Texas that have less biogenic VOC emissions. Ozone formation regimes at the time of the early afternoon overpass are NOx-limited almost everywhere in the domain except the Baytown section of Houston and in the presence of power plant plumes. There are likely NOx-saturated ozone formation conditions in the early morning hours that TROPOMI cannot observe. Having more in situ measurements of the vertical distribution of NO2 in rural and urban areas, and in the presence of power plant plumes would give us more confidence in our results.

Daniel Goldberg et al.

Status: open (until 08 Jun 2022)

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  • RC1: 'Comment on acp-2022-299', Anonymous Referee #1, 26 May 2022 reply

Daniel Goldberg et al.

Daniel Goldberg et al.

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Short summary
We offer recommendations for TROPOMI vs. model evaluations, using Texas as a case study. We find that TROPOMI NO2 version 2.3.1 algorithm increases NO2 +17 % in urban areas compared to version 1.3. Lightning NOx is important to account for and can contribute up 24 % of the column NO2 over the Gulf of Mexico and 8 % in Texas urban areas. Urban NOx emissions agree with TROPOMI NO2 version 2.3.1 to within 20 % in most circumstances. Near large power plants, the satellite appears to underrepresent NO2.
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