Geographic Scale

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 A Box Model Approach Emissions NO2 NO NH3 SO2 Meteorology 83% NH3+HNO3 NH4NO3 -21° NO2+O3 NO3 250m OH+NO2 HNO3 Chemistry

3. Atmospheric Chemistry Modeling

4. Atmospheric Chemistry Modeling Dirty pix

5. Atmospheric Chemistry Modeling Particulate Matter (PM2.5) News conference pix Source: M. Lipsett, California Office of Environmental Health Assessment

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 15th–16th April 2002 (Web Report W12), Leicester, UK, MRC Institute for Environment and Health)

7. Atmospheric Chemistry Modeling

8. Atmospheric Chemistry Modeling 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. Atmospheric Chemistry Modeling Yes, You!!

12. Atmospheric Chemistry Modeling … and us …

13. Atmospheric Chemistry Modeling

14. Atmospheric Chemistry Modeling Open Valley Closed Valley

15. Atmospheric Chemistry Modeling Brief Chemistry Background PM2.5 typically consists of: • Ammonium Nitrate (NH4NO3) • Ammonium Sulfate (NH4SO4) • Organic Carbon • Elemental Carbon • Sodium, Potassium, Calcium, … Logan PM2.5 is ~90% Ammonium Nitrate • Lots of chemistry going on.

16. Atmospheric Chemistry Modeling Brief Chemistry Background Ammonium Nitrate (NH4NO3) NH3 + HNO3NH4NO3 (Ammonia + Nitric Acid) Ammonium Nitrate Particle • Depending on temperature and humidity • ammonium nitrate will exist as a: • Solid particle (cold and dry) • Aqueous droplet (high humidity) • Dissociate into gas (warm) Agriculture Chemical transformation of NOx from Cars/combustion

17. Atmospheric Chemistry Modeling Brief Chemistry Background In a strong Cache Valley inversion: • Ammonium nitrate concentration rapidly increases when: • • Temperature < 0° C (Dissociation) • • Humidity < ~80% (Deliquescence point) • Ammonium nitrate concentration decreases when: • • Humidity > ~80% (Aqueous droplets larger than PM2.5) • Indoor ammonium nitrate concentration rapidly decreases. • • Temperature is warm (> 0° C )

18. Atmospheric Chemistry Modeling What Kind OF Model Should I Use? Cache Valley: • Interested in secondary chemistry (90% NH4NO3) - NH3 + HNO3NH4NO3 - Model must treat this and “lead-up” chemical reactions • Cache Valley is small and contained. • Transport by wind is limited. Weather data is limited. • PM2.5 concentrations uniform throughout valley. • What is my goal?: • Represent average airshed conditions. • • Valley concentrations are uniform. • • Don’t need to tie results to widely spaced monitors. • 2) Test NOx, VOC, NH3 control strategies • • Basic control strategies are needed.

19. Atmospheric Chemistry Modeling What Kind OF Model Should I Use? • Two model options: • Complex grid based model. • • Gridded emissions, meteorology, chemistry. • • Spatially and temporally oriented. • 2) Simple box model. • • Single volume, no transport, “shake the box”. • • Provides average conditions. Results can be tied to the Logan monitor. Valley concentrations seem mixed and uniform. Valley PM2.5 problem tied to NOx, VOC, NH3 dynamics.

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

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

22. Atmospheric Chemistry Modeling Model Chemistry – How, exactly, does it work? Inputs: Initial Concentrations: NO, NO2, CO, etc ... Hourly Emissions: NO, NO2, CO, etc … Chemistry: Carbon Bond-IV Chemical Mechanism - Used for urban smog modeling - About 80 different reactions ie. • NO2 + Sunlight NO+O • O3 + NO O3 • NO2 + O3 NO3

23. Atmospheric Chemistry Modeling Results !!!

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

25. Atmospheric Chemistry Modeling Some Problems … NO2 appears to be progressively depleted.

26. Atmospheric Chemistry Modeling Some Problems … O3 progressively increases. O3 depleted at night.

27. Atmospheric Chemistry Modeling What Might Explain My Problems? #1 : NO2 appears to be progressively depleted. • Is our “box” too big relative to emissions coming in? • Is there too much photochemistry happening – NO2 depletion? #2 : O3 progressively increases. • Is the “box” not big enough – too much VOC? • Is the photochemistry happening too quickly? • What else is increasing to allow O3 to build? #3 : O3 depleted at night. • Is there a reaction happening too fast? • Does subtle meteorology explain the discrepancy?

28. Atmospheric Chemistry Modeling What Might Explain My Problems? I must remember that: • The model cannot capture the subtleties. • I shouldn’t expect to match the observations exactly. • The model results represent average airshed conditions. Considering the above: • I want my ratios to be reasonable -NOx:NH3, NO:NO2 • Trends match observations. • Does it make sense?

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

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

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

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 • S02 + NH3 = SO4 • Nox + NH3 = NH3

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

47. 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 Tyler Cruickshank Patrick Barickman 4/5/05

48. Atmospheric Chemistry Modeling