Estimator of surface ozone using formaldehyde and carbon monoxide concentrations over the eastern United States in summer


Ye Cheng, Yuhang Wang, Yuzhong Zhang, James H Crawford, Glenn S Diskin, Andrew J Weinheimer, and Alan Fried. 7/2018. “Estimator of surface ozone using formaldehyde and carbon monoxide concentrations over the eastern United States in summer.” Journal of Geophysical Research: Atmospheres. Publisher's Version


Strong correlations of O3‐CH2O, O3‐CO and CO‐CH2O were observed during the DISCOVER‐AQ aircraft experiment in July 2011 over the Washington‐Baltimore area. The linear regression slopes of observed O3‐CH2O, O3‐CO and CO‐CH2O do not vary significantly with time (11 A.M. to 4 P.M.) or altitude in the boundary layer. These observed relationships are simulated well by a regional chemical transport model. Using tagged‐tracer simulations, we find that biogenic isoprene oxidation makes the largest contribution to the regression slope of O3‐CH2O across much of the eastern United States, providing a good indicator for O3 enhanced by biogenic isoprene oxidation. In contrast, the regression slope of O3‐CO is controlled by both anthropogenic and biogenic emissions. Therefore, we use the CO‐CH2O relationship to separate biogenic from anthropogenic contributions to CO. By combining these regressions, we can track the contributions to surface O3 by anthropogenic and biogenic factors and build a fast‐response ozone estimator using near surface CH2O and CO concentrations as inputs. We examine the quality of O3 estimator by increasing or decreasing anthropogenic emissions by up to 50%. The estimated O3 distribution is in reasonably good agreement with the full‐model simulations (R2 >0.77 in the range of ‐30% to +50% of anthropogenic emissions). The analysis provides the basis for using high‐quality geostationary satellites with UV, thermal infrared, or near infrared instruments for observing CH2O and CO to improve surface O3 distribution monitoring. The estimation model can also be applied to derive observation‐derived regional metrics to evaluate and improve full‐fledged 3‐D air quality models.