TSS Data Preparation Update

WRAP TSS Project Team Meeting

Ft. Collins, COMarch 28-31, 2006

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?

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

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.

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

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

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

Time-series plots of measured and modeled species concentrations

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

Scatter plots of model predictions vs. ambient data

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

Spatial plots with ambient data overlaid on model predictions

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

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

Source Apportionment Results

• PSAT

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?

Emissions Data

Emission inventories available on the TSS

• Base02a(b)• Plan02b• Base18b• Strat18a; Strat18b; etc…

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

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?

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)

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 ??

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 (??)