ACP Atmospheric Chemistry and Physics ACP Atmos. Chem. Phys. 1680-7324 Copernicus Publications Göttingen, Germany 10.5194/acp-13-11005-2013 Inverse modeling of Texas NO<sub>x</sub> emissions using space-based and ground-based NO<sub>2</sub> observations Tang W. 1 Cohan D. S. 1 Lamsal L. N. 3 2 Xiao X. 1 Zhou W. 1 Department of Civil and Environmental Engineering, Rice University, 6100 Main Street MS 519, Houston, TX 77005, USA NASA Goddard Space Flight Center, Greenbelt, MD, USA Goddard Earth Sciences Technology & Research, Universities Space Research Association, Columbia, MD, USA 12 11 2013 13 21 11005 11018 Copyright: © 2013 W. Tang et al. 2013 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://acp.copernicus.org/articles/13/11005/2013/acp-13-11005-2013.html The full text article is available as a PDF file from https://acp.copernicus.org/articles/13/11005/2013/acp-13-11005-2013.pdf

Inverse modeling of nitrogen oxide (NO<sub>x</sub>) emissions using satellite-based NO<sub>2</sub> observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO<sub>2</sub> column densities are used to conduct inverse modeling of NO<sub>x</sub> emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NO<sub>x</sub> emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO<sub>2</sub> over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO<sub>2</sub>-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NO<sub>x</sub> emissions in most regions by factors of 1.02 to 1.84, leading to 3–55% increase in modeled NO<sub>2</sub> column densities and 1–7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NO<sub>x</sub> emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO<sub>2</sub> or ground-level ozone (O<sub>3</sub>) concentrations.

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