1 / 22

Modeling Data and Source Apportionment Results for TSS Project Team Meeting

This update provides information on the modeling data available on the TSS, data storage methods, scenarios and impacts on visibility, as well as source apportionment results. It also includes details on data formats and storage, appropriate spatial and temporal resolutions, and model performance evaluation measures.

repperson
Télécharger la présentation

Modeling Data and Source Apportionment Results for TSS Project Team Meeting

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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 (??)

More Related