ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-8-5603-2008 A method for evaluating spatially-resolved NO<sub>x</sub> emissions using Kalman filter inversion, direct sensitivities, and space-based NO<sub>2</sub> observations Napelenok S. L. 1 Pinder R. W. 1 Gilliland A. B. 1 Martin R. V. 2 3 Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, in partnership with the United States Environmental Protection Agency, 109 T. W. Alexander Drive, Research Triangle Park, NC 27711, USA Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA 19 09 2008 8 18 5603 5614 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/8/5603/2008/acp-8-5603-2008.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/8/5603/2008/acp-8-5603-2008.pdf

An inverse modeling method was developed and tested for identifying possible biases in emission inventories using satellite observations. The relationships between emission inputs and modeled ambient concentrations were estimated using sensitivities calculated with the decoupled direct method in three dimensions (DDM-3D) implemented within the framework of the Community Multiscale Air Quality (CMAQ) regional model. As a case study to test the approach, the method was applied to regional ground-level NO<sub>x</sub> emissions in the southeastern United States as constrained by observations of NO<sub>2</sub> column densities derived from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite instrument. A controlled "pseudodata" scenario with a known solution was used to establish that the methodology can achieve the correct solution, and the approach was then applied to a summer 2004 period where the satellite data are available. The results indicate that emissions biases differ in urban and rural areas of the southeast. The method suggested slight downward (less than 10%) adjustment to urban emissions, while rural region results were found to be highly sensitive to NO<sub>x</sub> processes in the upper troposphere. As such, the bias in the rural areas is likely not solely due to biases in the ground-level emissions. It was found that CMAQ was unable to predict the significant level of NO<sub>2</sub> in the upper troposphere that was observed during the NASA Intercontinental Chemical Transport Experiment (INTEX) measurement campaign. The best correlation between satellite observations and modeled NO<sub>2</sub> column densities, as well as comparison to ground-level observations of NO<sub>2</sub>, was obtained by performing the inverse while accounting for the significant presence of NO<sub>2</sub> in the upper troposphere not captured by the regional model.

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