A new methodology for inferring surface ozone from multispectral satellite measurements

Over the past two decades, satellite instruments have provided unprecedented information on global air quality, and yet the remote sensing of surface ozone remains elusive. Here we propose a new method to infer spatial variability in surface ozone by combining multispectral ozone retrievals using radiances from the tropospheric emission spectrometer thermal infrared instrument and the ozone monitoring instrument ultratraviolet/visible instrument with a chemical reanalysis. We find that our inferred surface ozone in summertime China and the United States has regional biases of less than 4 ppb and a high spatial correlation when validated against independent surface measurements. Over the broader Asia region, our analysis results in a spatial pattern of summertime surface ozone that can largely be explained by a combination of the Asian monsoon circulation and NOx emissions. Our results show the potential of combining satellite measurements and chemical reanalyses to provide critical air quality information in regions of limited surface networks, thereby enhancing the global air quality observing system.