A method to determine the spatial resolution required to observe air quality from space

14Citations
Citations of this article
31Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Satellite observations have the potential to provide an accurate picture of atmospheric chemistry and air quality on a variety of spatial and temporal scales. A key consideration in the design of new instruments is the spatial resolution required to effectively monitor air quality from space. In this paper, vario-grams have been used to address this issue by calculating the horizontal length scales of ozone within the boundary layer and free troposphere using both in situ aircraft data from five different NASA aircraft campaigns and simulations with an air-quality model. For both the observations and the model, the smallest scale features were found in the boundary layer, with a characteristic scale of about 50 km which increased to greater than 150 km above the boundary layer. The length scale changes with altitude. It is shown that similar length scales are derived based on a totally independent approach using constituent lifetimes and typical wind speeds. To date, the spaceborne observations of tropospheric constituents have been from several instruments including TOMS, GOME, MOPITT, TES, and OMI which, in general, have different weighting functions that need to be considered, and none really measures at the surface. A further complication is that most satellite measurements (such as those of OMI and GOME) are of the vertically integrated column. In this paper, the length scales in the column measurements were also of the order of 50 km. To adequately resolve the 50-km features, a horizontal resolution of at least 10 km would be desirable. © 2007 IEEE.

Cite

CITATION STYLE

APA

Loughner, C. P., Lary, D. J., Sparling, L. C., Cohen, R. C., DeCola, P., & Stockwell, W. R. (2007). A method to determine the spatial resolution required to observe air quality from space. IEEE Transactions on Geoscience and Remote Sensing, 45(5), 1308–1313. https://doi.org/10.1109/TGRS.2007.893732

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free