1. Improving an Air Quality Decision Support System through the Integration of Satellite Data with Ground-based, Modeled, and Emissions Data NASA ROSES 2007: Decision Support through Earth Science Research Results Design Workshop, May 12 – 13: Cooperative Institute for Research in the Atmosphere

2. Workshop Objectives Introduce end users to project team, objectives, and high-level details Solicit end user feedback regarding each project task to help plan and design effective DSS enhancements Brainstorm ideas for tasks and schedule, information exchange, and the creation of a “road map” document Identify relevant databases and key contacts at NASA centers and in the broader user community Synthesize the ideas generated during the workshop into a practical and successful project plan

4. Overall Project Goal To enhance and add value to a currently operational air quality decision support system (VIEWS/TSS) by integrating and utilizing satellite data from NASA satellites Aura, Terra, Aqua, and CALIPSO. Specific Project Goals Improve methods for identifying pollutant sources and their respective contributions to visibility impairment in Federal Class I Areas Improve fire emissions data used for current and future-year air quality assessments through calibration of a stochastic fire prediction model Facilitate interpretative analyses of ground-based, modeled, and emissions data by providing requirements for advanced analysis tools integrated in the DSS. Demonstrate the augmented system capabilities to end users via observations, emissions data, and outputs from the Community Multiscale Air Quality model from historic and future-year applications.

5. VIEWS The Visibility Information Exchange Web System http://vista.cira.colostate.edu/views  Developed by the five Regional Planning Organizations (RPOs) in 2002  For RPOs, States, Tribes, Federal Land Managers, and local agencies  Used by researchers, analysts, planners, regulators, stakeholders, and students  Provides online access to data from over fifty monitoring networks and studies  The primary source for IMPROVE Regional Haze Rule data  Offers tools for exploring, downloading, visualizing, and analyzing data  Has over 1200 registered users  Serves over 300 organizations, institutions, and companies  New version being launched in the summer of 2008

6. TSS WRAP Technical Support System http://vista.cira.colostate.edu/tss  Developed by the WRAP for Western States, Tribes, and air quality agencies  Serves as an access point for regional technical data, guidance, and results  Provides tools and support for the development of SIPs and TIPs  Describes the technical methods used in implementation plans  Helps assess the impact of other areas on local Class I Areas  Provides ongoing tracking and assessment of emissions control strategies  Will adapt to and serve the future regional technical needs of WRAP members  Built upon the database and software infrastructure of VIEWS

9. VIEWS/TSS Decisions: End Users & Benefits Federal Land Managers: Better air quality evaluation More accurate source apportionment More meaningful impact assessment Informed permitting and regulation Improved air quality in ecosystems EPA and RPOs: Effective emissions control evaluation Practical and equitable standards Leveraging of existing efforts Improved synergy with States and Tribes Valuable case studies and precedents More effective application of resources States, Tribes, and Local Agencies: Effective Implementation Plans Defensible and achievable control strategies Uniform and reasonable progress Better air quality in Class I Areas Researchers, Students, & Stakeholders: Better insight into the decision process Real life evidence of successes & failures Incorporation of feedback into next generation products Increasing expertise in developing decision support tools

10. VIEWS/TSS Data Value Chain

11. Dynamic Contour Maps

12. Dynamic Data Maps

13. Network Inter-comparison Parameter: Nitrate Ion Concentrations Location: Bondville, IL Networks: IMPROVE, STN, and CASTNet Graphs: Time Series and Scatter Plot

14. Model Performance Evaluation CMAQ Model Performance vs. Monitored Worst 20% Days in 2002

15. Source Apportionment  Mass source apportionment by source category and region  From regional photochemical model with comprehensive emissions inputs  Species mass for various time periods – directly comparable to monitoring data

16. Glide Slope and Uniform Rate of Progress

17. Multidimensional Analysis  Multiple NAAQS indicators, multiple time periods, multiple locations  Displayed with consistent, comparable graphics in the same tool

18. Emissions Review Tool Available Parameters: –Sulfur Dioxide –Sulfur Oxides (gas and particulate) –Nitrogen Oxides (gas) –Nitrogen Oxides (gas and particulate) –Other species from SMOKE Multiple dimensions: –Parameters –Emissions Scenarios –Source Categories –Regions of Interest Future plans: –Display regional summaries as well as state-level emissions

19. Raw Data

20. VIEWS/TSS Objectives: Analyze current and historic air quality conditions Aerosol composition for best & worst visibility days Estimates of natural background visibility conditions Modeled projections of visibility in future years Identify pollutant sources among biogenic, federal/international, and controllable anthropogenic categories, as well as their relative contributions to visibility impairment Determine Reasonable Progress goals for reducing emissions Develop long term control strategies for achieving natural visibility conditions in protected ecosystems by 2064

21. Overall Project Premise…

22. Project Tasks Task 1: Integrate Satellite Data into the TSS Database Task 2: Enhance Existing TSS Tools for Satellite Data Access Task 3: Add Additional Satellite-Data Enhanced Analysis Tools Task 4: Calibrate the Fire Scenario Builder with MODIS Fire Data Products Task 5: Demonstrate Key Applications of the Enhanced TSS Task 6: Engage End Users, Transfer Technology, and Provide Training

23. Project Schedule: Year One Organize design workshop to solicit system end user requirements Create “road map” document including performance metrics for enhanced DSS Acquire/QA Level 2 or gridded OMI and CALIPSO data from UMBC Enhance TSS database to import satellite data Attend NASA Science Team meeting and other project-relevant meetings for communication with end users and satellite data experts Examine MODIS fire data for 2006 or later from RRS to import into DSS Begin modifying pyPA to include particulate species modeled in CMAQ Prepare fire model inputs for Western U.S. ecoprovinces for ’06-’07 timeframe Run FSB simulations and calibrate against MODIS fire data Enhance AMET for comparison with CALIPSO aerosol data

24. Project Schedule: Year Two Complete data import of CALIPSO and OMI into DSS and begin beta tests Complete data import of MODIS fire data products into DSS Attend NASA Science Team meetings and other project-relevant meetings for communication with end users and satellite data experts Complete AMET and pyPA installation in DSS Produce emissions of ’06 or ’07 fires for Western U.S. and compare with NEI 2005 fire inventory Produce base and future-year emissions for CMAQ including predicted fires Test pyPA with archived CMAQ outputs from RPO simulations Test AMET analysis tools with archived CMAQ Send links to beta version of DSS to end users Incorporate feedback from beta testing

25. Project Schedule: Year Three Prepare CMAQ lateral and vertically varying boundary conditions for ’06 or ’07 from satellite data for Continental US and Western domain Performance-test nested simulations with satellite-data enhanced emissions (fire sources) and QA Attend NASA Science Team meetings and other project-relevant meetings for communication with end users and satellite data experts Perform base- and future-year simulations for 2 nested domains for 2 representative seasons Analyze results / evaluate against 3D measurements Send links to end users for beta testing, and incorporate feedback Archive results in DSS database and QA Convene Final Demonstration Workshop and update DSS database as needed Attend all-investigator meeting at NASA HQ to present project results

26. Thanks!