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 (??)