Comparison of NOx Emissions and NO2 Concentrations From a Regional Scale Air Quality Model (CMAQ-DDM/3D) With Satellite NO2 Retrievals (SCIAMACHY) Over the Continental U.S.
Abstract
Estimated NOx emissions and CMAQ simulated NO2 concentrations obtained from these emissions over the continental U.S. were compared with NO2 total tropospheric columns obtained from SCIAMACHY satellite-based sensor for July-August 2004. Two CMAQ simulations were performed, one with and one without lightning emissions. Simulated NO2 columns were mostly lower than observed, though highly correlated (R2=0.61-0.65) in the west, while in the eastern U.S., column amounts were comparable but had a lower correlation (R2=0.30-0.39). Comparison of NO2 columns by state found additional eastern states where simulated levels were lower than the satellite observations as well as most western states. Additional comparisons according to land use - "urban", "rural" and "rural-point" - found that NO2 total columns derived from satellite correlate well with simulated NO2 concentrations for "rural" regions but the correlation is lower for "urban" and "rural-point" regions. Simulated NO2 columns in Los Angeles are significantly lower than observed which may indicate a retrieval/analysis error, a bias in emission estimates specific to that region (or, conversely biases in the other regions), or modeling issues specific to that area. Lower correlations in "rural-point" regions are surprising with their emissions being viewed as relatively well known. Potential reasons for this discrepancy are 1) the transport of NOx out of the small satellite scan area and 2) insufficient time for conversion of NO to NO2 in power plant plumes. High correlation of "rural" regions is promising for estimating the following types of NOx emissions which is hard to capture otherwise: 1) area emissions that are sparse and poorly quantified, 2) lightning emissions and 3) prescribed or wildfire emissions. This work gives information on use of the satellite retrievals in data assimilation for regional air quality models and their potential to further improve the emission inventories by assessing the accuracy and consistency of current estimates. Data assimilation using satellite retrievals will also be performed for NOx emissions to identify errors in emission inventories which is key to developing effective environmental policies and improving our understanding of atmospheric processes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2008
- Bibcode:
- 2008AGUFM.A21B0130K
- Keywords:
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- 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0345 Pollution: urban and regional (0305;
- 0478;
- 4251);
- 3355 Regional modeling;
- 3360 Remote sensing;
- 9350 North America