15A.4 Estimation of Surface NO2 Using Remote Sensing Data and CMAQ Model Output from DISCOVER-AQ Campaigns

Thursday, 16 January 2020: 4:15 PM
206B (Boston Convention and Exhibition Center)
K. E. Pickering, Univ. of Maryland, College Park, College Park, MD; and L. N. Lamsal, M. Follette-Cook, D. Allen, W. H. Swartz, S. J. Janz, K. W. Appel, and G. Pfister

Satellite-based observations of NO2 vertical column densities have enabled development of long-term global NO2 datasets at reasonably high spatial resolution. However, these column data are underutilized by air quality specialists, who need surface concentrations to augment sparse ground measurement networks. We describe a method for inferring estimates of surface-level NO2 from retrievals of NO2 tropospheric column density. This methodology is first applied to airborne remotely sensed NO2 column data from the four NASA DISCOVER-AQ field campaigns. We use high-resolution CMAQ simulations to provide a priori information for the retrievals. The spatially and temporally varying relationship between surface and column from the CMAQ model is used in estimating surface NO2 from the column observations. These estimates are evaluated against in-situ surface concentrations during the NASA DISCOVER-AQ field campaigns. Uncertainties in the estimates are addressed through evaluation of the CMAQ NO2 profile shapes using in-situ profile data from the NASA P-3B aircraft. A similar method is then applied to OMI NO2 column data to yield estimates of surface NO2 mixing ratios over larger-scale regions. The method utilized here can be considered a prototype for potential use in estimating surface NO2 from column data observed by the future TEMPO geostationary air quality satellite instrument.
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