Articles | Volume 16, issue 23
https://doi.org/10.5194/acp-16-15247-2016
https://doi.org/10.5194/acp-16-15247-2016
Research article
 | 
09 Dec 2016
Research article |  | 09 Dec 2016

Effects of daily meteorology on the interpretation of space-based remote sensing of NO2

Joshua L. Laughner, Azimeh Zare, and Ronald C. Cohen

Abstract. Retrievals of tropospheric NO2 columns from UV–visible observations of reflected sunlight require a priori vertical profiles to account for the variation in sensitivity of the observations to NO2 at different altitudes. These profiles vary in space and time but are usually approximated using models that do not resolve the full details of this variation. Currently, no operational retrieval simulates these a priori profiles at both high spatial and high temporal resolution. Here we examine the additional benefits of daily variations in a priori profiles for retrievals already simulating a priori NO2 profiles at sufficiently high spatial resolution to identify variations of NO2 within urban plumes. We show the effects of introducing daily variation into a priori profiles can be as large as 40 % and 3 × 1015 molec. cm−2 for an individual day and lead to corrections as large as −13 % for a monthly average in a case study of Atlanta, GA, USA. Additionally, we show that NOx emissions estimated from space-based remote sensing using daily, high-spatial-resolution a priori profiles are  ∼ 100 % greater than those of a retrieval using spatially coarse a priori profiles, and 26–40 % less than those of a retrieval using monthly averaged high-spatial-resolution profiles.

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Short summary
Satellite measurements of the atmosphere provide global information on pollutants that play an important role in air quality. These measurements require assumed knowledge about the vertical profile of these pollutants, which are often simulated at coarse resolution in space and time. We find that simulating these inputs with better spatial and temporal resolution alters individual measurements by up to 40 % and the average measurement by up to 13 %, and increases derived emissions by up to 100 %.
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