1. Georgia Institute of Technology Air Pollutant Transport, Control and Modeling Issues in the Eastern United States Ted Russell Air Resources Engineering Center Georgia Tech August 26, 2003

2. Georgia Institute of Technology Acknowledgements GIT Colleagues –T. Odman, J. Boylan, A. Hakami, M. Bergin, D. Cohan, Y. Hu, A. Unal, D. Tian, M. Kahn, H. Park, A. Marmur, J. Wilkinson, M. Chang, et al. SAMI –Financial support and, particularly, intellectual contributions and guidance RFF Colleagues –J-S. Shih and A. Krupnick NSF and EPA

3. Georgia Institute of Technology Issues Ozone modeling morphing in to multi-pollutant models –Confidence for ozone (?) –How about other species? What are the major uncertainties, and what is being done? Long range and near-field impacts of air pollutants –Is it me or my next door neighbor, or the guy down the street? Georgia EAC Modeling –Issues –Preliminary results Other bits of interest –Reactivity, VOC vs. NOx (it never dies)

4. Georgia Institute of Technology AQM State of the Science: Where are We? “One atmosphere”/“3rd generation” urban-to- regional/continental models are at the forefront –Combined gas/aerosol/deposition & nested/multiscale/adaptive (?) –Some built in diagnostic features Process analysis Sensitivity analysis Dominant PM models –REMSAD (simplified) –Models 3/CMAQ –CAMX-PM (less application for PM) Regional Multiscale Model

5. Georgia Institute of Technology Grids Nested Multiscale Adaptive

6. Georgia Institute of Technology How Good Are They? All evidence suggests that they describe the processes most affecting the evolution of ozone and (if equipped) particulate matter (o.k., many components of PM) after pollutant emission Science (chemistry/physics) Mathematics Computational implementation Evaluation Uncertainties Limitations & uncertainties Limitations Uncertainties, lack of confidence Holes lead to: Application Uncertainties, poor results

7. Georgia Institute of Technology Confidence? Should go in as a skeptic, however Current models rather accurately (not perfectly) simulate ozone and (most) associated species –Multiple, very different areas: Urban (L.A., Mexico City, NY, Tokyo, …) Regional (Eastern U.S., NW, Europe, Asia, …) –Different meteorologies Across seasons, high, mid, low ozone Explain observed trends –10 year trend in NO x, VOC, CO and ozone in Switzerland Doesn’t come easy: –60% emissions, 30% meteorology, 5% model development, 5% model application/evaluation Emissions still most uncertain Expect “rapid” advances in PM –Supersites, RPO modeling, EPA-funded research

8. Georgia Institute of Technology Performance (Good) 35% Ozone Sulfate

9. Georgia Institute of Technology Performance (Not so good) PM Performance (Seignuer et al., 2003) –Errors from recent studies using CMAQ, REMSAD Organic carbon: 50-140% error Nitrate: 50-2000% error –Understand the reason for much of the error in nitrate Deposition, heterogeneous reaction Ammonia emissions still rather uncertain –OC more difficult Understand part (most?) More complex mixture Primary/precursor emissions uncertain Organic Carbon

10. Georgia Institute of Technology Long vs. Short Range Impacts What is the relative contribution of local vs. nearby vs. distant emission sources? Approach –Apply air quality model with sensitivity analysis to develop a matrix of interstate and intrastate impacts of NOx and SO2 emissions on ozone and PM2.5, respectively. NOx emissions had minimal impact on PM2.5 because the aerosol is relatively acidic (for now) Periods –RFF »May, 1995: typical levels of ozone and sulfate »July, 1995: High levels of sulfate and ozone –Southern Appalachians Mountains Initiative: Year average Sources: Shih et al., (2003) and Boylan et al., (2003)

11. Georgia Institute of Technology July 12 July 14 Ground LevelElevated Example: Impact of Michigan NOx emissions downwind:

12. Georgia Institute of Technology 8-hour Ozone change for 30% Elevated Source NOx Reduction

13. Georgia Institute of Technology  g/m 3 /1000 tons/day May-July episodes Sulfate Sensitivity to SO 2 Emissions

14. Georgia Institute of Technology

15. Long Range vs. Near Field While long-range transport is important, near field impacts are major –Both SO2/sulfate and NOx/ozone Interstate transport very episode specific –SAMI looked at annual average, even stronger conclusion about importance of local (near-field) controls

16. Georgia Institute of Technology Georgia EAC Modeling Cities/Episodes –Augusta, North Georgia –Primary: August 2000 (episode selection suggests representative) –Coming: August 1999, July 2001 Issues –Modification of inventory (NET96  NEI99) –Default vertical diffusivity Performance –Ozone –Precursors Preliminary 2007

17. Georgia Institute of Technology 36-km 4-km 12-km

18. Georgia Institute of Technology Problem 1: Minimum vertical eddy diffusivity CMAQ Defaul of 1.0 m2/s Plot of Simulated and Observed Surface Ozone Concentrations in Columbus, GA, Using a minimum vertical eddy diffusivity of 1.0m2/s.

19. Georgia Institute of Technology Figure 6.11 Midnight Surface Ozone Concentrations on August 17 th, 2000 in the FAQS 12-km Grid Using the Minimum Vertical Eddy Diffusivity of 1.0m 2 /s. Still very high at midnight in most urban and suburban areas, over 30ppb and 60ppb

20. Georgia Institute of Technology Simulated and Observed Surface NO Concentrations in the FAQS 12-km Grid for the Episode of August 11 th - 20 th,2000, the Minimum Vertical Eddy Diffusivity of 1.0m 2 /s was used in CMAQ. Underestimate at night

21. Georgia Institute of Technology Figure 6.14 Midnight Surface Ozone Concentrations on August 17 th, 2000 in the FAQS 12-km Grid Using the Minimum Vertical Eddy Diffusivity of 10 -4 m 2 /s. Minimum diffusivity reset to 10 -4 m2/s (McNider and Pielke, 1981) Corrected !

22. Georgia Institute of Technology Time Series Plot of Simulated and Observed Surface Ozone Concentrations in Columbus, GA, the Minimum Vertical Eddy Difusivity of 10 -4 m 2 /s was used in CMAQ.

23. Georgia Institute of Technology Figure 6.17 Simulated and Observed Surface NO Concentrations in the FAQS 12-km Grid for the Episode of August 11 th - 20 th,2000, the Minimum Vertical Eddy Difusivity of 10 -4 m 2 /s was used in CMAQ. Corrected !

24. Georgia Institute of Technology Late Afternoon Surface Ozone Concentrations on August 17 th, 2000 in the FAQS 12-km Grid Using the Minimum Vertical Eddy Diffusivity of 10 -4 m 2 /s. Isolated strange hot spots?

25. Georgia Institute of Technology Time Series Plot of Simulated and Observed Surface Ozone Concentrations in Santa Rosa County, FL, the Minimum Vertical Eddy Difusivity of 10 -4 m 2 /s was used in CMAQ. Extremely high ozone happened in the grid cells over mixed land-use where water is the majority

26. Georgia Institute of Technology Problem 2: Atmosphere too stable over cells with mixed water/other landuses Stability determined by land-use with largest fraction Cell vertical diffusion went very stable over lakes and coastal sites Used 9-point averaging in such cells

27. Georgia Institute of Technology Late Afternoon Surface Ozone Concentrations on August 17 th, 2000 in the FAQS 12-km Grid Using the Minimum Vertical Eddy Diffusivity of 10 -4 m 2 /s and a 9-point averaging method. A 9-point averaging method was used to smooth …

28. Georgia Institute of Technology Time Series Plot of Simulated and Observed Surface Ozone Concentrations in Santa Rosa County, FL, the Minimum Vertical Eddy Diffusivity of 10 -4 m 2 /s and a 9-point averaging method

29. Georgia Institute of Technology Surface Ozone Daily MNB during the Episode of August 11 th -20 th, 2000 for the 106 Stations in the 12-km Grid or the 25 Stations in the 4-km Grid Surface Ozone Daily MNE during the Episode of August 11 th -20 th, 2000 for the 106 Stations in the 12-km Grid or the 25 Stations in the 4- km Grid Daily Bias and Errors of Ozone

30. Georgia Institute of Technology Time Series Plot of Simulated and Observed Surface NO Concentrations at PAMS Station NO Diurnal Plots Time Series Plot of Simulated and Observed Surface NOZ Concentrations at PAMS Station NOy

31. Georgia Institute of Technology Time Series Plot of Simulated and Observed Surface ARO1 Concentrations at PAMS Station ARO1 Time Series Plot of Simulated and Observed Surface ALK1 Concentrations at PAMS Station ALK1

32. Georgia Institute of Technology Estimated Change in Daily Maximum Ozone Concentrations in the 12km grid (on the left) and the 4-km grid (on the right) from August 17 th 2000 to 2007 under the existed Federal Control Strategies. Difference of Daily Maximum Ozone: 2007-2000 Reductions typically 8-14 ppb

33. Georgia Institute of Technology NOx vs. VOC: Did the Pendulum Swing Too Far? Are VOC controls beneficial, and where? Is attainment dependent upon NOx controls? What are the additional issues?

34. Georgia Institute of Technology Chemical Regimes Radical Limited: Abundant NO 2 removes OH, inhibitting oxidation of VOCs and HO 2 /RO 2 formation: Low utilization of NO x emissions Volatile Organic Compounds (VOCs) Nitrogen Oxides (NO x ) Low O 3 Transport NO x Limited: Lack of NO x limits ozone formation via photolysis, increased destruction of HO 2 /RO 2 : High utilization of NO x emissions High O 3

35. Georgia Institute of Technology Influence of Biogenics Volatile Organic Compounds (VOCs) Nitrogen Oxides (NO x ) SE Hot, sunny SE Typical NE Typical

36. Georgia Institute of Technology Biogenic Emissions Day 1Day 2Day 3 Biogenic emissions vary significantly by location and day Source: Hanna et al., 2003

37. Georgia Institute of Technology VOC Sensitivity Anthropogenic VOCIsoprene

38. Georgia Institute of Technology VOCNOX Mobile Non-Mobile Georgia: Even in Atlanta, VOC controls can be effective & some local NOx inhibition (seen in observations, too)

39. Georgia Institute of Technology VOC vs. NOx VOC controls effective for controlling ozone, even on high ozone days –Can be relatively more effective on cooler, lower ozone days –Additional benefits: lower carbonaceous PM, toxics NOx controls key to attainment in high biogenic areas Controlling VOC reactivity may be even more cost- effective –Coming ANPR (California leading)

40. Georgia Institute of Technology Organic Reactivity Assessment Organics behave differently – need a way to quantify the impact each has on the ozone production. –Impact on ozone per mass of VOC emitted can vary by orders of magnitude. More cost effective management possible if one accounts for ozone formation from emissions, not just VOC mass –Allows manufacturers flexibility in formulation –Controls perverse choices Less, but much more reactive VOC Pioneered in California for fuels –Moved to consumer products –Recent studies have shown applicability in eastern US, EPA moving forward Conducted large scale (LA  CA  eastern US) 3-D simulations to assess reactivity –Variability, scales, approaches –Applied URM using SAPRC99.

41. Georgia Institute of Technology Reactivity of organic compounds Reactivity of an organic compound, as a measure of its ozone formation potential can be defined as (Carter, 1994): By definition, reactivity assessment is sensitivity analysis. Assessed reactivities for various organics using URM & DDM-3D –Carter used CAMX and DDM

42. Georgia Institute of Technology Relative Reactivity Metrics, MIR-3D Relative Reactivity

43. Georgia Institute of Technology SOS SOS activities moving towards Texas –Many SOS-affiliated teams applying expertise in the Houston area –UTexas taking lead role State-of-Science document underway No new EPA money for traditional SOS –Significant “individual” investigator work –Funding for Texas studies

44. Georgia Institute of Technology Summary PM models coming of age –Uncertainties, particularly in emissions, organics While interstate transport can be significant… –Local impacts typically large(st) Preliminary EAC modeling for Georgia suggests a 8-14 ppb reduction in ozone regionally –For August 2000 episode –2001, 1999 episodes underway Reactivity appears to work in the East –Some differences than in the West VOC controls effective in cities, if not beyond –Even in Atlanta with all of its isoprene –NOx scavenging found in Atlanta as well Observed and modeled

45. Georgia Institute of Technology FAQS Episodes August 11, 2000 – August 20, 2000 – Primary FAQS period – High ozone statewide – FAQS measurements, Houston Supersite period – Col 8-hr, Mac. 8-hr, Atl&Mac&Col&Aug 8-hr, All 8-hr, Atl. 1-hr August 10, 1999 – August 21, 1999 – High ozone and PM – Atlanta Supersite period – Mac 8-hr, Atl&Mac&Col&Aug 8-hr (part), All 8-hr (part), Aug 8-hr July 5, 2001 – July 20, 2001 – High ozone and PM – FAQS measurements, ESP01 period – Atl 8-hr, Atl 1&8-hr, Atl&Mac&Col&Aug 8-hr, All 8-hr, Aug 8-hr