Modeling Data and Source Apportionment Results for TSS Project Team Meeting

1. TSS Data Preparation Update WRAP TSS Project Team Meeting Ft. Collins, CO March 28-31, 2006

2. Modeling Data • What model runs will be available on the TSS? • How are data stored ? • Scenarios/IMPROVE Species/Visibility Impacts? • Same Database/Parameters as Monitored data ? • Model performance evaluation results? • What is best spatial/temporal resolution of data? • How to handle source apportionment results? • PSAT, PMF • How to handle BART analysis and results?

3. Modeling Data Model runs available on TSS • Base02a(b) • Used in MPE; EI includes actual fires, CEM point data • Plan02b • 2002 baseline; EI include typical fire, no CEM data • Base18a • 2018 Future year base case • 2018 Control Strategy Simulations • Sensitivity Simulations Model simulation results stored/organized based on impacts on visibility by: • Source Categories • Species

4. Modeling Data Modeled Data • Species mass • Required: Sulfate, Nitrate, OC, EC, Fine soil, PMCoarse • Optional: PM2.5, O3, NO, NO2, CO, SO2, HNO3, Others ? • Visibility measures • Species extinction, Total extinction, Deciview • Differences in: • Modeled parameters for a given year • Base02 – Plan02; Strat18 – Base18; etc. • Modeled parameter for different years • Base18 – Base02; Base18 – Plan02; etc.

5. Modeling Data Modeled Data Storage and Formats • Gridded data stored as ASCIIGRID formats: • One file each by modeled species/parameter and scenario (including difference pairs) • Gridded data stored in GIS Shapefile formats: • One file for each scenario (including difference pairs) • each includes all relevant species/parameters • Modeled data parameters at monitoring sites • Species concentration data as used for MPE • Visibility measures at Class I monitoring sites

6. Modeling Data Most Appropriate Spatial/Temporal Resolution • Spatial Resolution • Gridded, surface layer (3D NetCDF files aggregated vertically) • 36-km (12-km); National or WRAP region ?? • Point data at IMPROVE monitors (interpolated from grid data as used in MPE) • Temporal Resolution • Gridded data: Annual; Seasonal; Monthly (?) • 20% Best/Worst days

7. Modeling Data Model Performance Evaluation • Performance measures to include: • Time-series plots of measured and modeled species concentrations • Scatter plots of model predictions vs. ambient data • Spatial plots with ambient data overlaid on model predictions • Bar plots comparing mean fractional bias (MFB) and/or mean fractional error (MFE) • “Bugle plots” showing model performance variation as a function of the PM species concentration • Stacked-bar plots of contributions to light extinction for the average of the best-20% visibility days or the worst-20% visibility days at each site

8. Time-series plots of measured and modeled species concentrations

9. Stacked-bar time-series plots of measured and modeled contributions to light extinction

10. Scatter plots of model predictions vs. ambient data

11. “Bugle plots” showing model performance variation as a function of the PM species concentration

12. Spatial plots with ambient data overlaid on model predictions

13. Bar plots comparing mean fractional bias (MFB) and/or mean fractional error (MFE)

14. Stacked-bar plots of contributions to light extinction for the average of the best-20% visibility days or the worst-20% visibility days at each site

15. Source Apportionment Results • PSAT

16. Emissions Data • What inventories will be available on the TSS? • How are data stored ? • Scenarios/Species/Source Categories? • Same Database/Parameters as Monitored data? • GIS data layers? • What is best spatial/temporal resolution of data? • What GIS Layers are available for display/query? • Where do the GIS layers reside? How are they accessed?

17. Emissions Data Emission inventories available on the TSS • Base02a(b) • Plan02b • Base18b • Strat18a; Strat18b; etc…

18. Emissions Data Source Categories • For each scenario provide data by: • Major source categories: Stationary Point; Area; On-road; Off-road; Biogenic • Detailed source categories: Point; Area; On-road; Off-road; Offshore area; Offshore point; Offshore shipping; Oil & Gas; Fugitive Dust; WB Dust; Road Dust; Fires (Point/Area; Wild/Prescribed/Ag/Wildland Use); Biogenic

19. Emissions Data Pollutants • For each source category include following species, as appropriate: • NOx = NO + NO2 • SO2 • VOC = ALD2 + ETH + FORM + ISOP + OLE + PAR + TOL + XYL • NH3 • PM2.5 (PMF) • PMCoarse = PM10 – PM2.5 • OC • EC • Do we want/need speciated VOCs?

20. Emissions Data Emission Data Storage and Formats • Data stored as ASCIIGRID formats: • One file each by species, source category, scenario • ~8 species X ~ (4-20) categories = ~32 – 160 files / scenario • Data stored as GIS Shapefile formats: • One file for each source category, scenario • 4 – 20 files/scenario (each includes all relevant pollutants) • Data stored in other formats? (i.e., county-level data)

21. Emissions Data Most Appropriate Spatial/Temporal Resolution • Spatial Resolution • Surface layer (3D NetCDF files aggregated vertically) • Gridded – 36-km; (12-km??) • County-level – from SMOKE data files • IDA (input); SMOKE reports (output) • Temporal Resolution • Annual; Seasonal; Monthly (?) • How to handle fire emissions ??

22. Emissions Data GIS Data Layers • GIS EI data layers for display/query • See ArcIMS demo • Contextual Data • Administrative Boundaries • State/County/Tribal • Class I Area • National/State Parks and Forests • Transportation Networks • Place Names • Landuse/Landcover • GIS data storage and access • GIS data layers stored in ArcIMS • ASCII data stored at CIRA (??)