1. Geographic Scale -The explicit physical scale of an air quality model affects more abstract levels of scale of data inputs Atmospheric Chemistry -The dynamic interaction of chemicals and meteorology Modeling Visibility in the National Parks -Modeling at the regional scale – Long range transport in addition to chemistry Using the Results, Dealing With Uncertainty -Modeling complex systems rarely yields definitive results Tyler Cruickshank Patrick Barickman 4/5/05

2. Atmospheric Chemistry Modeling Logan, Utah Particulate Air Pollution NH 3 NO 2 NO NH 3 +HNO 3 NH 4 NO 3 83% -21° 250m SO 2 NO 2 +O 3 NO 3 OH+NO 2 HNO 3 Emissions Meteorology Chemistry A Box Model Approach

3. Atmospheric Chemistry Modeling

4. Dirty pix

5. Atmospheric Chemistry Modeling News conference pix Source: M. Lipsett, California Office of Environmental Health Assessment Particulate Matter (PM 2.5 )

6. Atmospheric Chemistry Modeling This image shows a magnified view of aerosol particles collected in the industrial city of Port Talbot, England. Many of the particles measure roughly 2.5 microns across, small enough to easily enter and damage human lungs. (Micrograph adapted from Sixth Annual UK Review Meeting on Outdoor and Indoor Air Pollution Research Sixth Annual UK Review Meeting on Outdoor and Indoor Air Pollution Research 15th–16th April 2002 (Web Report W12), Leicester, UK, MRC Institute for Environment Institute for EnvironmentInstitute for Environment and Healthand Health) and Health

7. Atmospheric Chemistry Modeling

8. Bad news when your town is a USA today feature!

9. Atmospheric Chemistry Modeling Even worse when your town is USA today graphic!

10. Atmospheric Chemistry Modeling Me??

11. Yes, You!!

12. Atmospheric Chemistry Modeling … and us …

13. Atmospheric Chemistry Modeling

14. Open Valley Closed Valley

15. Atmospheric Chemistry Modeling Brief Chemistry Background PM 2.5 typically consists of: Ammonium Nitrate (NH 4 NO 3 ) Ammonium Nitrate (NH 4 NO 3 ) Ammonium Sulfate (NH 4 SO 4 ) Ammonium Sulfate (NH 4 SO 4 ) Organic Carbon Organic Carbon Elemental Carbon Elemental Carbon Sodium, Potassium, Calcium, … Sodium, Potassium, Calcium, … Logan PM 2.5 is ~90% Ammonium Nitrate Lots of chemistry going on. Lots of chemistry going on.

16. Atmospheric Chemistry Modeling Brief Chemistry Background Ammonium Nitrate (NH 4 NO 3 ) NH 3 + HNO 3 NH 4 NO 3 NH 3 + HNO 3 NH 4 NO 3 (Ammonia + Nitric Acid) Ammonium Nitrate Particle Agriculture Chemical transformation of NO x from Cars/combustion Depending on temperature and humidity ammonium nitrate will exist as a: 1)Solid particle (cold and dry) 2)Aqueous droplet (high humidity) 3)Dissociate into gas (warm)

17. Atmospheric Chemistry Modeling Brief Chemistry Background In a strong Cache Valley inversion: 1)Ammonium nitrate concentration rapidly increases when: Temperature < 0° C (Dissociation) Temperature < 0° C (Dissociation) Humidity < ~80% (Deliquescence point) Humidity < ~80% (Deliquescence point) 2)Ammonium nitrate concentration decreases when: Humidity > ~80% (Aqueous droplets larger than PM 2.5 ) Humidity > ~80% (Aqueous droplets larger than PM 2.5 ) 3)Indoor ammonium nitrate concentration rapidly decreases. Temperature is warm (> 0° C ) Temperature is warm (> 0° C )

18. Atmospheric Chemistry Modeling What Kind OF Model Should I Use? Cache Valley: Interested in secondary chemistry (90% NH 4 NO 3 ) Interested in secondary chemistry (90% NH 4 NO 3 ) - NH 3 + HNO 3 NH 4 NO 3 - NH 3 + HNO 3 NH 4 NO 3 - Model must treat this and “lead-up” chemical reactions - Model must treat this and “lead-up” chemical reactions Cache Valley is small and contained. Cache Valley is small and contained. Transport by wind is limited. Weather data is limited. Transport by wind is limited. Weather data is limited. PM 2.5 concentrations uniform throughout valley. PM 2.5 concentrations uniform throughout valley. What is my goal?: 1)Represent average airshed conditions. Valley concentrations are uniform. Valley concentrations are uniform. Don’t need to tie results to widely spaced monitors. Don’t need to tie results to widely spaced monitors. 2) Test NO x, VOC, NH 3 control strategies Basic control strategies are needed. Basic control strategies are needed.

19. Atmospheric Chemistry Modeling Two model options: 1)Complex grid based model. Gridded emissions, meteorology, chemistry. Gridded emissions, meteorology, chemistry. Spatially and temporally oriented. Spatially and temporally oriented. 2) Simple box model. Single volume, no transport, “shake the box”. Single volume, no transport, “shake the box”. Provides average conditions. Provides average conditions. What Kind OF Model Should I Use? Results can be tied to the Logan monitor. Valley concentrations seem mixed and uniform. Valley PM 2.5 problem tied to NO x, VOC, NH 3 dynamics.

20. Atmospheric Chemistry Modeling Fixed X Fixed Y Emissions In Model Prediction Chemistry Performed NOx SO4 H2O NH3 NO VOC NH3 SO4 NOx Box Model Variable Z

21. Atmospheric Chemistry Modeling Emissions NO2 NO2 NO NO VOC VOC NH3 NH3 Predictions NO2 NO2 NO NO O3 O3 Model Volume How big a box? How big a box? Meteorology Temperature Temperature RH RH Photolysis Photolysis Are my emissions reasonable? Are my emissions reasonable relative to the box size? Meteorology is measured and hence, fixed. How does the meteorology impact the chemistry? Represent the whole valley? Just the populated portion? Do my predictions look reasonable? No? Why not? Try again …

22. Atmospheric Chemistry Modeling Model Chemistry – How, exactly, does it work? Inputs: Initial Concentrations: NO, NO 2, CO, etc... Hourly Emissions: NO, NO 2, CO, etc … Chemistry: Carbon Bond-IV Chemical Mechanism - Used for urban smog modeling - About 80 different reactions ie. NO 2 + Sunlight NO+O NO 2 + Sunlight NO+O O 3 + NO O 3 O 3 + NO O 3 NO 2 + O 3 NO 3 NO 2 + O 3 NO 3

23. Atmospheric Chemistry Modeling Results !!!

24. Atmospheric Chemistry Modeling NO appears to be progressively depleted. Some Problems …

25. Atmospheric Chemistry Modeling NO 2 appears to be progressively depleted. Some Problems …

26. Atmospheric Chemistry Modeling O 3 progressively increases. O 3 depleted at night. Some Problems …

27. Atmospheric Chemistry Modeling What Might Explain My Problems? #1 : NO 2 appears to be progressively depleted. Is our “box” too big relative to emissions coming in? Is our “box” too big relative to emissions coming in? Is there too much photochemistry happening – NO 2 depletion? Is there too much photochemistry happening – NO 2 depletion? #2 : O 3 progressively increases. Is the “box” not big enough – too much VOC? Is the “box” not big enough – too much VOC? Is the photochemistry happening too quickly? Is the photochemistry happening too quickly? What else is increasing to allow O 3 to build? What else is increasing to allow O 3 to build? #3 : O 3 depleted at night. Is there a reaction happening too fast? Is there a reaction happening too fast? Does subtle meteorology explain the discrepancy? Does subtle meteorology explain the discrepancy?

28. Atmospheric Chemistry Modeling I must remember that: The model cannot capture the subtleties. The model cannot capture the subtleties. I shouldn’t expect to match the observations exactly. I shouldn’t expect to match the observations exactly. The model results represent average airshed conditions. The model results represent average airshed conditions. What Might Explain My Problems? Considering the above: I want my ratios to be reasonable - NO x :NH 3, NO:NO 2 I want my ratios to be reasonable - NO x :NH 3, NO:NO 2 Trends match observations. Trends match observations. Does it make sense? Does it make sense?

29. Atmospheric Chemistry Modeling Identify dynamics behind AQ problem. Identify dynamics behind AQ problem. Identify scale of AQ problem. Identify scale of AQ problem. Select model as appropriate to above and goals. Select model as appropriate to above and goals. Understand uncertainty. Understand uncertainty. AQ modeling is not a research project – it is applied modeling. AQ modeling is not a research project – it is applied modeling. What’s the Skinny?

30. Atmospheric Chemistry Modeling What’s the Skinny?

31. Geographic Scale -The explicit physical scale of an air quality model affects more abstract levels of scale of data inputs Atmospheric Chemistry -The dynamic interaction of chemicals and meteorology Modeling Visibility in the National Parks -Modeling at the regional scale – Long range transport in addition to chemistry Using the Results, Dealing With Uncertainty -Modeling complex systems rarely yields definitive results Tyler Cruickshank Patrick Barickman 4/5/05

32. http://www.wrapair.org/

33. http://coha.dri.edu/index.html

34. Overall Goal of the Regional Haze Rule (CAA, 1990)

36. MM5 Modeling at the Continental Scale

37. Emissions Inventory

38. What is the model trying to evaluate? Light Extinction (B ext ): The attenuation of light due to scattering and absorption as it passes through a medium Benefit: Light extinction can be directly related to gaseous and aerosol concentrations. Drawback: Light extinction is non-linearly related to a person perception of changes in haze. How is it done? The model converts concentrations of pollutants into the extinction coefficients These are based on known relationships between the type of particle and its effect on visibility How is the evaluation made?

39. http://vista.cira.colostate.edu/views/ Observations in the National Parks and Wilderness Areas

40. Geographic Scale -The explicit physical scale of an air quality model affects more abstract levels of scale of data inputs Atmospheric Chemistry -The dynamic interaction of chemicals and meteorology Modeling Visibility in the National Parks -Modeling at the regional scale – Long range transport in addition to chemistry Using the Results, Dealing With Uncertainty -Modeling complex systems rarely yields definitive results Tyler Cruickshank Patrick Barickman 4/5/05

43. The Weight of Evidence Approach The Causes of Haze Data for each state’s Regional Haze State Implementation Plan (RH SIP) Sulfates and Nitrates Uncertainty in the model results require supporting evidence Two models used Tagged Species Source Apportionment (TSSA) Trajectory Regression Attribution Method

44. Back Trajectory Analysis

45. Utah Emissions Inventory S0 2 + NH 3 = SO 4 No x + NH 3 = NH 3

46. Weight of Evidence This is a descriptive approach that is narrative and qualitative rather than purely quantitative

47. Tyler Cruickshank Patrick Barickman 4/5/05 Summary Complex System – “One not describable by a single rule. Structure exists on many scales… not reducible to only one level of description.” http://www.calresco.org/glossary.htm Usually not possible to give definitive answers – a conceptual model puts the results in context

48. Atmospheric Chemistry Modeling