To investigate the ability of column (or partial column) information to represent surface air quality, results of linear regression analyses between surface mixing ratio data and column abundances for O₃ and NO₂ are presented for the July 2011 Maryland deployment of the DISCOVER-AQ mission. Data collected by the P-3B aircraft, ground-based Pandora spectrometers, Aura/OMI satellite instrument, and simulations for July 2011 from the CMAQ air quality model during this deployment provide a large and varied data set, allowing this problem to be approached from multiple perspectives. O₃ columns typically exhibited a statistically significant and high degree of correlation with surface data (R² > 0.64) in the P-3B data set, a moderate degree of correlation (0.16 < R² < 0.64) in the CMAQ data set, and a low degree of correlation (R² < 0.16) in the Pandora and OMI data sets. NO₂ columns typically exhibited a low to moderate degree of correlation with surface data in each data set. The results of linear regression analyses for O₃ exhibited smaller errors relative to the observations than NO₂ regressions. These results suggest that O₃ partial column observations from future satellite instruments with sufficient sensitivity to the lower troposphere can be meaningful for surface air quality analysis.
