10 Nov 2022
10 Nov 2022
Status: this preprint is open for discussion.

Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires

Ruijun Dang1, Daniel J. Jacob1, Viral Shah1,a,b, Sebastian D. Eastham2,3, Thibaud M. Fritz2, Loretta J. Mickley1, Tianjia Liu4, Yi Wang5,6, and Jun Wang5,6 Ruijun Dang et al.
  • 1John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
  • 2Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
  • 3Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
  • 4Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02138, USA
  • 5Center for Global and Regional Environmental Research, Iowa Technology Institute, The University of Iowa, Iowa City, IA 52242, USA
  • 6Department of Chemical and Biochemical Engineering, The University of Iowa, Iowa City, IA 52242, USA
  • anow at: Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
  • bnow at: Science Systems and Applications, Inc., Lanham, MD 20706, USA

Abstract. Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric NO2 background to which satellite measurements are particularly sensitive. Tropospheric NO2 columns from the OMI satellite instrument averaged over the contiguous US (CONUS) show no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background that has not been captured in models. Here we use the GEOS-Chem chemical transport model applied to the simulation of OMI NO2 to better understand the sources and trends of background NO2 over CONUS. Previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis, which increases the model NO2 column by 13 % on an annual basis (25 % in spring), and also increases the air mass factor (AMF) to convert the tropospheric slant columns inferred from the OMI spectra into vertical NO2 columns by 7 % on an annual basis (11 % in spring). The increase in the AMF decreases the retrieved NO2 columns in the satellite observations, contributing to the improved agreement with the model. Accounting for the 2009–2017 increase in aircraft NOx emissions drives only a 1.4 % mean increase in NO2 column over CONUS and a 2 % increase in the AMF, but the combination of decreasing surface NOx emissions and increasing aircraft emissions is expected to drive a 14 % increase in the AMF over the next decade that will be necessary to account for in the interpretation of satellite NO2 trends. Fire smoke identification with the NOAA Hazard Mapping System (HMS) indicates that wildfires contribute 1–8 % of OMI NO2 columns over the western US in June–September and that this contribution has been increasing since 2009, contributing to the flattening of OMI NO2 trends. Future analyses of NO2 trends from satellite data to infer trends in surface NOx emissions must critically consider the effects of a rising free tropospheric background due to increasing emissions from aircraft, fires, and possibly lightning.

Ruijun Dang et al.

Status: open (until 22 Dec 2022)

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Ruijun Dang et al.

Ruijun Dang et al.


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Short summary
Model underestimate of the background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions not only increases the background NO2, but also affects the satellite retrieval by altering the NO2 vertical profile. Increase in wildfire emissions contributes to the flattening of post-2009 OMI NO2 trends in the western US. Our work shows the importance of properly accounting for the free tropospheric background in interpreting satellite NO2 observations.