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Aerosol Size Distribution Modeling for the Pacific Northwest

Aerosol Size Distribution Modeling for the Pacific Northwest. Robert Elleman Ph.D. Defense March 9, 2007 Department of Atmospheric Sciences University of Washington. 30 Second Overview of Project. Simulate aerosol size distributions in the Pacific Northwest with regional air quality model

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Aerosol Size Distribution Modeling for the Pacific Northwest

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  1. Aerosol Size Distribution Modeling for the Pacific Northwest Robert Elleman Ph.D. Defense March 9, 2007 Department of Atmospheric Sciences University of Washington

  2. 30 Second Overview of Project • Simulate aerosol size distributions in the Pacific Northwest with regional air quality model • Test against unique observational dataset • Make improvements to model science

  3. Aerosol Overview epochtimes.com • Aerosol = particle suspended in atmosphere • Importance • Human health effects • Visibility and ecological health • Climate – direct and indirect effects • Composition • SO42-, NH4+, NO3-, OC, EC, metals • Size spans 4-5 orders of magnitude (1 nm to 100 mm) science..nasa.gov earthobservatory.nasa.gov www.berriman-usa.com www.dec.state.ny.us

  4. Accumulation Aitken Coarse Nucleation PM2.5 Ultrafine Particles Adapted From US EPA Criteria Document for PM, 2004

  5. Importance of Aerosol Size for Human Health Oberdörster et al., EHP, 2005

  6. Importance of Aerosol Size for Light Scattering Seinfeld and Pandis, 1998

  7. Aerosol Properties • Aerosol = particle suspended in atmosphere • Importance • Human health effects • Visibility and ecological health • Climate – direct and indirect effects • Composition • SO42-, NH4+, NO3-, OC, EC, metals • Size spans 4-5 orders of magnitude (1 nm to 100 mm) • Can often be described as 3, overlapping lognormal modes • Describe the entire size distribution with 9 numbers

  8. Importance of Size Distribution Modeling Bukowiecki et al., Atmos. Environ., 2002 15 Minute Drive around Zurich

  9. Motivation, Goals and Methodology • Aerosol size distribution is spatially heterogeneous • Difficult to measure adequately • Goal is to more accurately model aerosol size distribution • Focus on ultrafine particle range (< 100 nm) • Test state-of-the-art model in Pacific Northwest • Make improvements as needed

  10. CMAQCommunity Multiscale Air Quality modeling system Initial Conditions Emissions Database Emit Primary Pollutants Boundary Conditions Advect and Diffuse Meteorology Input Chemical Reactions Output: Hourly 3-D gridded concentrations for gases and aerosols

  11. CMAQ Simulation • CMAQ v4.4 (September 2004) • 4 km horizontal resolution • 22 levels -- lowest layer is ~30 meters • 4 day spin-up • 3 day simulation • 00 UTC 08/26 – 00 UTC 08/29, 2001

  12. Observational Datasets Pacific 2001 PNW 2001

  13. Duvall N/W-PS Olympia Tacoma Spiral E/N-PS Olympia Mud Mt Stampede Number Underprediction Flight track Pacific Standard Time = UTC - 8

  14. CowlitzValley Enumclaw Seattle Everett SJuans Pt Ang. Everett Number Underprediction Flight track Pacific Standard Time = UTC - 8

  15. N-PS Bremerton Double-Pass E/N-PS SkykomishValley S-PS Spiral Brem. E/N-PS S-PS Number Underprediction Flight track Pacific Standard Time = UTC - 8

  16. Size Errors by Species • No Single Species Accounts for Size Distribution Errors 08/26 08/28 08/26 08/28 08/26 08/28

  17. Possible Explanations for Number Underprediction • Meteorology • Temperature • Mixing depth • Dry deposition • Aerosol Module • Errors in aerosol mass and/or composition • Condensation • Coagulation • Modal merging • Cloud processing • Chemical Environment • Oxidizing capacity • Missed plumes • Other…

  18. Emission Size Distribution • Can cause consistent number underprediction • Outdated science in model biases fewer, larger particles • Nucleation – New Particle Formation from Vapors • Can cause consistent number underprediction • Outdated science in model could underpredict new particle production

  19. From: Mozurkewich et al., 2004 New Particle Formation • Nucleation based on binary H2SO4-H2O • New Particles are monodisperse with Dg = 2.0 nm • Binary nucleation is not chemically complete • Not capturing nucleation mode dynamics Kulmala et al., 1998: Parameterizations for sulfuric acid/water nucleation rates. J. Geophys. Res.

  20. Ternary Parameterization Napari et al. 2002: Parameterization of ternary nucleation rates for H2SO4-NH3-H2O vapors. J. Geophys. Res. • NH3-H2SO4-H2O nucleation • Nucleation rate strong function of : • Input [NH3]g,Temperature, Input [H2SO4]g • Need to determine nucleation in Aitken range ~5 million particles per hour

  21. Accumulation Aitken Coarse Nucleation PM2.5 Ultrafine Particles Adapted From US EPA Criteria Document for PM, 2004

  22. Nucleation Mode Parameterization “Condensation Sink” Race Against Time: Growth to a stable size vs. Loss to the Larger Modes Loss to Existing Particles Growth Rate H2SO4 Growth Rate Survival Rate Kerminen and Kulmala, 2002: Analytical formulae connecting the “real” and the “apparent” nucleation rate and the nuclei number concentration for atmospheric nucleation events. J. Aerosol Sci.

  23. Ternary w/Proc obs Binary/None Ternary w/Proc Binary/None Nucleation Model Number Concentrations

  24. Nucleation Model Size Distributions • Ternary nucleation with processing to 10 nm best simulates the shape of the size distribution and the Aitken mode diameter

  25. Conclusions from Nucleation • Ternary nucleation • Produces urban concentrations in the millions but few of these particles survive to observable sizes • Processing to 10 nm eliminates most new particles • Highlights importance of nucleation mode physics. • Size distributions are more realistic • Residual issues None ≈ Binary Ternary (10nm) Observations

  26. Emission Size Distribution • Can cause consistent number underprediction • Outdated science in model biases fewer, larger particles • Nucleation – New Particle Formation from Vapors • Can cause consistent number underprediction • Outdated science in model could underpredict new particle production

  27. Spatial Scale of Emissions centimeters 1-5 m 10 m 5 km 50 km Engine Vehicle Road Neighborhood Region “Emission” is a process for parameterizing everything that happened on a smaller scale than your interest or ability to measure.

  28. 4 km Improve Emissions Size Distributions • Scale to 4 km grid • All processes < 4 km scale must be parameterized • Gather measurements of major sources at ~4km scale • Mostly generalized urban sources Emissions Sensitivity Matrix

  29. Effect of Emission Size Distribution Number Enhancement Size Parameters

  30. Conclusions from Emissions • New emission size distributions represent scale of model grid • Apportion much higher amount of emitted mass into Aitken mode • Increase number of modeled particles by up to 4 • At most a factor of 10-15 with upper bound scenario • Minor compared to base case underprediction • Modeled size distributions are more realistic None ≈ Binary New Emission s.d. Observations

  31. Combined Update

  32. Ternary Ternary w/Processing Updated CMAQ Combined Update Emission Size Dist. CMAQ v4.4 Conclusions

  33. Conclusions continued • Size distributions are more realistic • Regional nucleation and emission of Aitken mode particles are important for the Pacific Northwest • Errors remain, especially in accumulation mode

  34. It Takes a Village • Dave and Cliff • Committee – Jeff, Tim, and Alison • Others – Rob Wilson, Brian Lamb, Jack Chen, PM Center, NW-AIRQUEST, CMAQ developers in NC • Family and Friends • Parents • Jen Kay, Team Icy, Grads00, others too numerous to mention

  35. Questions?

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