1. June 15, 2011 Bob Dulla Sierra Research

2. Fairbanks PM 2.5 Design Values* (2006-2010) * 98 th Percentile Concentrations 2

3. Jan/Feb 2008 Episode 3

4. Nov 2008 Episode 4

5. Fairbanks PM 2.5 Modeling  Analytical framework needed to assess how changes in emissions translate into ambient concentrations  Key inputs are accurate representation of time series of meteorology and emissions  Variety of models available  Photochemical  Statistical  Dispersion  Receptor  Due to complexity of weather & chemistry all models being pursued 5

6. Model Contributions to PM 2.5 Attainment Planning 6 Model µg/m 3 ForecastRRF Source Apport Plume Trajectory Secondary Particulate Formation Weight of Evidence CMAQ XXX--XX PCA X?-- ?X CALPUFF -- X X Receptor -- X X

7. Modeling Challenges  Wood Burning  Appears to be the dominant source of directly emitted PM 2.5  Range of acceptable controls is limited Wood stove change out programs Maximizing use of dry wood  Can the models provide reliable estimates of benefits? 7

8. Modeling Challenges (cont.)  Point Sources  Pollutants emitted well above inversion layer  Is SO 2 contributing to sulfate measured at monitors?  Is coal contributing to metals (e.g., Fe) catalyzing sulfate formation?  Will controls provide reductions in ambient concentrations?  What types of controls are needed?  Can models provide reliable estimates of benefits? 8

9. Modeling Challenges (cont.)  Sulfate  Principal sources of emitted sulfur are fuel oil and coal  Second largest share of measured PM 2.5 mass  Will reductions in fuel oil sulfur content produce reductions in sulfate?  Speciation data indicate rich NH 4 environment at temps < -20° F  Will sulfur reductions lower sulfate levels at these temperatures?  Can models provide reliable estimate of benefits? 9

10. Modeling Challenges (cont.)  Organic Carbon  Accounts for 50+% of PM 2.5 mass  Is secondary OC a significant portion of the mass?  Can models provide insight into secondary OC and source contributions? 10

11. Can Benefits for these Controls be Reliably Estimated? 11  Wood Stove Change Out Program  Burning Dry Wood  Episodic Burn Bans  Restricting Residential Coal Use  Point Source SO 2 Controls  Reducing Sulfur Content of Fuel Oil  Waste Oil Burning Controls  Wide Scale Use of Natural Gas Space Heating  Heavy-Duty Diesel Retrofits

12. Fairbanks PM 2.5 SIP Schedule SIP DUE DATE ATTAINMENT DATE CURRENT DATE 12

13. Fairbanks PM 2.5 SIP Schedule (cont.) SIP DUE DATE ATTAINMENT DATE CURRENT DATE Fairbanks PM 2.5 SIP Schedule (cont.) 13

14. Session Goals  Science  Little SIP time left to pursue outstanding questions  Need summary of resolved/unresolved issues  Modeling  Upcoming SIP focus is on control measure analysis  Which science issues are not well represented in modeling?  Given costs and unpopularity of available controls it is critical to understand reliability of benefit estimates 14