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Use of space-based tropospheric NO 2 observations in regional air quality modeling

Use of space-based tropospheric NO 2 observations in regional air quality modeling. Robert W. Pinder 1 , Sergey L. Napelenok 1 , Alice B. Gilliland 1 , Randall V. Martin 2 Atmospheric Sciences and Modeling Division, NOAA, in partnership with USEPA

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Use of space-based tropospheric NO 2 observations in regional air quality modeling

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  1. Use of space-based tropospheric NO2 observations in regional air quality modeling Robert W. Pinder1, Sergey L. Napelenok1, Alice B. Gilliland1, Randall V. Martin2 Atmospheric Sciences and Modeling Division, NOAA, in partnership with USEPA Dalhouise University and Harvard-Smithsonian Center for Astrophysics TROPOMI Workshop KNMI, Utrecht, The Netherlands March 5-6, 2008

  2. Case Study: NOx State Implementation Plan Call • From 2002 – 2005, NOx emission reductions from power plants in Midwestern United States (22% ↓) • Simultaneous gradual reduction in vehicle NOx emissions (18% ↓) • Goal: Use satellite data to infer emission changes

  3. Tools: CMAQ: Community Multi-scale Air Quality Model Surface networks: HNO3, O3, deposition Can satellite data augment these tools? Surface change in total nitrate, 2002-05

  4. 20032004 2005 SCIAMACHY

  5. 20032004 2005 SCIAMACHY

  6. 20032004 2005 SCIAMACHY

  7. How does the change in the satellite observations correspond to changes in emissions? (1) Develop method using air quality model to relate emissions to column density (2) Apply method to relate trend in satellite data to trend in emissions (in development)

  8. Use Air Quality Model and Satellite Data to Infer Emission Change • Begin with a priori emission estimate • Use emissions as input to CMAQ to estimate NO2 column density • Based on difference between CMAQ estimate and observed value, use an inverse technique to derive a new emission estimate • Repeat until emission estimate converges (a posteriori)

  9. Focus on Southeast United States in 2004 • Isolated urban areas • Good spatial coverage in satellite data • High quality surface NO2 observations

  10. Continental US Southeast US CMAQ SCIAMACHY

  11. When paired with aloft measurements from NASA INTEX, CMAQ underpredicts NO2 above the mixed layer On average 1.07 (1015 molecules cm-2) Missing NO2 Aloft

  12. Similar error found in other models Singh, et al. (2007) Reactive Nitrogen Distribution and Partitioning in the North American Troposphere and Lowermost Stratosphere

  13. Continental US Southeast US + INTEX CMAQ SCIAMACHY

  14. RESULTS Urban areas decrease; consistent with updated emissions data Rural areas are sensitive to NO2 aloft

  15. Inverse-adjusted emissions improves agreement with independent surface NO2 observations Sensitivity test demonstrates proper accounting of NO2 aloft is important Inverse improves surface concentrations NO2

  16. Work in Progress: Next Steps • More information is available on ACPD (Napelenok et al., A method for evaluating spatially-resolved NOx emissions using Kalman filter inversion, direct sensitivities, and space-based NO2 observations) • Improve simulation of NOx above the planetary boundary layer • Improve inverse methods to better quantify uncertainty • Apply method to trends in 2003, 2004, and 2005 • Beyond SCIAMACHY NO2 data

  17. Considerations for Future Missions • Consistency across multiple years • Horizontal and vertical resolution • Reduce uncertainty and global daily coverage • Multiple observations per day, but need to consider chemical state • Harmonizing regional models and retrieval • More transparency in retrieval methods and uncertainty calculations to ease interpretation and comparison

  18. ACKNOWLEDGEMENTS:Aloft NOx measurements collected by Ron Cohen and the NASA INTEX team.Helpful comments and advice from Rynda Hudman, Dev Roy, Robin Dennis, David Mobley, and Ann Marie Carlton.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.

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