1. Weight of Evidence Discussion AoH Meeting – Tempe, AZ November 16/17, 2005

2. Overview What do we mean by weight of evidence (WOE) approach? Review of model approach to determine reasonable progress Is model prediction of reasonable progress reasonable? Important factors in visibility assessment at each Class I area Attribution “footprint” concept

3. WOE Definitions EPA suggests WOE is a set of analyses which: –Are supplemental to primary method for measuring attainment Additional AQ modeling Review of trends Other applicable analyses –Are invoked when attainment is not clearly shown WRAP working definition: –Review of all available analyses that bear on Class I area visibility Monitoring data Emissions data Model results Attribution results (combination of multiple methods) Review of episodic (“natural” ?) events Back trajectory and other analyses –Assigning appropriate weight to each analysis (based on relevance and uncertainty) –Ultimately, this will take the form of a checklist of things to review and instructions on how to weigh each piece

4. Use of AQ Model to Measure Reasonable Progress (simplified) Assumption: the AQ model is better at predicting relative changes in concentration than absolute concentrations Model species concentrations for 2002 Model species concentrations for 2018 base and scenarios Determine a species-specific relative reduction factor (RRF) for the average of the 20% worst days (selected from 2002 IMPROVE data): RRF sulfate = 2018 sulfate / 2002 sulfate Select 20% worst days for each year in the baseline period and apply the RRFs: 2018 concentration ~ Avg. [RRF x Baseline concentration ] Calculate 2018 visibility for 20% worst days and compare to the Glide Slope

5. Is Model Prediction of Reasonable Progress… Reasonable? Determine if the major species causing visibility impairment are handled well by the model (e.g., modeled sulfate is more reliable than modeled nitrate) Review attribution source regions and their emissions: –First, how well do attribution methods agree? –If source regions can be identified, do the projected emissions reductions for 2018 support the model’s visibility reductions? Are there episodic events that could justifiably be removed from the data set (e.g., large fire or dust episode during baseline period)? –Calculation of reasonable progress with and without episodic events could set upper and lower bounds to predicted 2018 visibility Even without considering episodic events, the variability in the 5-year baseline could be used as an “error bar” to bound the projected 2018 visibility

6. PMF Mass Budget vs. IMPROVE Extinction Budget for GRCA2 Preliminary PMF Mass (DRI) AoH Phase I IMPROVE Extinction

7. Emissions Reductions by Source Region From: Regional Technical Support Document for the Requirements of the Section 309 Regional Haze Rule

8. Large Episodic Fire Impacts in 2002

9. 2018 Visibility Displayed as a Range Projected 2018 visibility (red bar) displayed as a range bounded by: –Calculation with and without large episodic events –Variability of baseline value

10. Important Factors in Visibility Assessment at Each CIA Does model predict “reasonable progress” in 2018 base or other scenario? Determine relative importance of species in 2002 and 2018? –Generally 1-3 species contribute significantly on the worst days To what degree are the emissions responsible for dominant species anthropogenic and controllable? –Requires review of emissions reductions in source regions identified by attribution analysis How will emissions reductions affect dominant species – reduce impact by 1%, 5%, 50%? What source regions contribute at a “significant” level? –With whom to states need to consult? What if the 2018 assessment makes sense but it does not show reasonable progress? Others??? What is the uncertainty associated with each previous bullet?

11. Attribution “Footprint” Concept

12. Expected Attribution Results The modeled attribution results (CAMx and PSAT method) will tell us how much species mass is likely due to specific source regions (states, Canada, Mexico, Pacific, etc.) The results can be displayed as: –Amount or percent of species mass attributed by a region –Amount or percent of extinction attributed by a region

13. Phase I Attribution Displays Next slides show Phase I attribution displays: –Attribution matrix 1.How much each source region contributes to each class I area (look across rows) 2.How much a given source region contributes to all class I areas (look down columns) –Attribution summary graphics: 1.Pollutant contributions at an individual Class I area attributed to all source regions 2.Pollutant contributions at many Class I areas attributed to an individual state

14. Phase I Attribution Matrix >>>> Contributions (value or %) to CIAs by source regions:  Which source regions affect a given CIA?  Which CIAs does 1 source region affect?  Table can look at contribution to species or total mass/extinction

15. Phase I Attribution Graphics

16. Phase 2 Attribution “Footprint” Maps show mock ups for how to answer these questions in Phase 2 (data shown is from Phase I) Probably too many colors to be effective in the “Sulfate Extinction Attributed to WRAP States (excluding UT, WA, WY)” map, but visual inspection supports the Phase I clustering Non-WRAP contributions highlighted in the final 2 maps

17. Phase I Sulfate and Nitrate Extinction Attributed to Oregon (TSSA Analysis)

18. Phase I Sulfate and Nitrate Extinction Attributed to Arizona (TSSA Analysis)

19. Phase I Sulfate Extinction Attributed to WRAP States (excluding UT, WA, WY) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Phase I clustering based on SO4/NO3 attribution

20. Phase I Sulfate Extinction Attributed to non-WRAP Source Regions

21. Phase I Nitrate Extinction Attributed to non-WRAP Source Regions