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Exploring Factors Affecting the Inference of Surface-Level NO2 from Orbital and Suborbital Tropospheric Column Observations
Citation:
William, S., L. Lamsal, M. Follette-Cook, K. Pickering, S. Choi, D. Allen, C. Loughner, AND Keith Appel. Exploring Factors Affecting the Inference of Surface-Level NO2 from Orbital and Suborbital Tropospheric Column Observations. American Geophysical Union Fall Meeting 2019, San Francisco, California, December 09 - 13, 2019.
Impact/Purpose:
This work aims to improve the use of satellite estimated tropospheric NO2 by developing a method to infer surface-level NO2 from the satellite column NO2 columns. Satellite data have a greater spatial coverage than ground-level ambient NO2 measurements. As such, this work can help fill in gaps where ambient measurements may not be available. The analysis presented here specifically uses data from the Ozone Monitoring Instrument (OMI), ground-level measurements, aircraft measurements and the CMAQ modeling system.
Description:
Satellite-based observations of NO2 vertical column densities have enabled the construction of long-term global NO2 datasets at reasonably high spatial resolution. However, these data are underutilized by the health and air quality communities, who need global surface concentrations to augment sparse ground measurement networks. We describe how surface-level NO2 may be inferred from retrievals of NO2 tropospheric column density and explore the factors influencing the relationship between column and surface NO2 concentration. Our analysis draws on concurrent, integrated observations of column abundances from orbital (Ozone Monitoring Instrument, OMI), suborbital, and ground-based sensors, vertical profiling from aircraft, and in situ surface concentrations during the DISCOVER-AQ and KORUS-AQ field campaigns. We use high-resolution meteorological and air quality modeling simulations from each campaign to interpret these observations, provide a priori information for NO2 retrievals, and diagnose both the chemistry and meteorology affecting the column-to-surface relationship as well as potential model deficiencies.
