HR: 0800h
AN: A21A-0014    [Abstracts]
TI: Integrating Kalman Filter Inverse Modeling and Direct Sensitivities to Evaluate NOx Emission Inventory Biases Based on Satellite-Derived NO2 columns
AU: * Napelenok, S L
EM: napelenok.sergey@epa.gov
AF: Atmospheric Sciences Modeling Division, Air Resources Laboratory, NOAA, in partnership with the US EPA, 109 T.W. Alexander Drive, RTP, NC 27711, United States
AU: Pinder, R W
EM: pinder.rob@epa.gov
AF: Atmospheric Sciences Modeling Division, Air Resources Laboratory, NOAA, in partnership with the US EPA, 109 T.W. Alexander Drive, RTP, NC 27711, United States
AU: Gilliland, A B
EM: gilliland.alice@epa.gov
AF: Atmospheric Sciences Modeling Division, Air Resources Laboratory, NOAA, in partnership with the US EPA, 109 T.W. Alexander Drive, RTP, NC 27711, United States
AU: Martin, R V
EM: randall.martin@dal.ca
AF: Department of Physics and Atmospheric Science, Dalhousie University, Sir James Dunn Building, Halifax, NS B3H3J5, Canada
AB: Regional air quality models are used to develop control strategies for reducing the ambient concentrations of harmful pollutants such as ozone and fine particulate matter. Regional models rely on detailed emission inventories, and these inventories still have a substantial amount of uncertainty despite continuing efforts for improvement. It is important to reduce nitrogen oxide (NO_x) emission uncertainties, because these compounds regulate the levels of ozone in the troposphere, lead to formation of nitric acid, and impact the levels of hydroxyl radicals. A method was developed to constrain ground-level NO_x emissions using an iterative Kalman filter inverse modeling technique and SCIAMACHY satellite observations of NO₂. For the inverse modeling calculations, the relationship between emissions and modeled ambient concentrations was developed using sensitivities provided by the decoupled direct method in three dimensions (DDM-3D). The method was successfully tested using a controlled emissions scenario with a known synthetic solution (i.e., pseudodata test), and then applied to a summer 2004 episode where emissions of NO_x were examined over a region covering the southeastern United States. The results indicate that while ground level NO_x emission estimates in urban areas appear to be only slightly too high, rural emissions need to increase by a factor of two in order to produce the NO₂ column densities observed by the satellite. However, over rural areas, the inverse is highly sensitive to NO₂ concentrations in the upper troposphere where its origins are likely to be from lightning emissions of NO. Regional models often ignore lightning emissions, because these have been shown to have negligible impacts on boundary layer pollutant concentrations. But if satellite emissions are to be used to any extent in the context of regional inverse modeling or data assimilation, the upper level sources need to be better quantified. Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.
DE: 0365 Troposphere: composition and chemistry
DE: 0368 Troposphere: constituent transport and chemistry
DE: 3315 Data assimilation
DE: 3355 Regional modeling
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting