1. 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 1.Atmospheric Sciences and Modeling Division, NOAA, in partnership with USEPA 2.Dalhouise University and Harvard-Smithsonian Center for Astrophysics TROPOMI Workshop KNMI, Utrecht, The Netherlands March 5-6, 2008

2. Case Study: NO x State Implementation Plan Call From 2002 – 2005, NO x emission reductions from power plants in Midwestern United States (22% ↓) Simultaneous gradual reduction in vehicle NO x emissions (18% ↓) Goal: Use satellite data to infer emission changes

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

4. 2003 2004 2005 SCIAMACHY

5. 2003 2004 2005 SCIAMACHY

6. 2003 2004 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 NO 2 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 NO 2 observations

10. Continental US Southeast US CMAQ SCIAMACHY

11. Missing NO 2 Aloft When paired with aloft measurements from NASA INTEX, CMAQ underpredicts NO 2 above the mixed layer On average 1.07 (10 15 molecules cm -2 )

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

13. SCIAMACHY CMAQ Continental US Southeast US + INTEX

14. Emissions (tons NO x day -1 ) Comparison of CMAQ and SCIAMACHY r2r2 Atlanta Birmingham Georgia Alabama a priori 0.68 513202574852 a posteriori CMAQ 0.89 48218211711718 a posteriori CMAQ + INTEX 0.93 435138364782 RESULTS Urban areas decrease; consistent with updated emissions data Rural areas are sensitive to NO 2 aloft

15. Inverse improves surface concentrations Inverse-adjusted emissions improves agreement with independent surface NO 2 observations Sensitivity test demonstrates proper accounting of NO 2 aloft is important NO 2

16. Work in Progress: Next Steps More information is available on ACPD (Napelenok et al., A method for evaluating spatially-resolved NO x emissions using Kalman filter inversion, direct sensitivities, and space-based NO 2 observations) Improve simulation of NO x above the planetary boundary layer Improve inverse methods to better quantify uncertainty Apply method to trends in 2003, 2004, and 2005 Beyond SCIAMACHY NO 2 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 NO x 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.