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Use of a Radar Wind Profiler and Sodar to Characterize PM 2.5 Air Pollution in Cleveland, Ohio

Use of a Radar Wind Profiler and Sodar to Characterize PM 2.5 Air Pollution in Cleveland, Ohio. Clinton P. MacDonald 1 , Adam N. Pasch 1 , Robert Gilliam 2 , Charley A. Knoderer 1 , Paul T. Roberts 1 , and Gary Norris 2 1 Sonoma Technology, Inc. 2 U.S. Environmental Protection Agency

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Use of a Radar Wind Profiler and Sodar to Characterize PM 2.5 Air Pollution in Cleveland, Ohio

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  1. Use of a Radar Wind Profiler and Sodar to Characterize PM2.5 Air Pollution in Cleveland, Ohio Clinton P. MacDonald1, Adam N. Pasch1, Robert Gilliam2, Charley A. Knoderer1, Paul T. Roberts1, and Gary Norris2 1Sonoma Technology, Inc. 2U.S. Environmental Protection Agency Presented at the National Air Quality Conferences March 7-10, 2011 San Diego, CA 4070

  2. About Cleveland • Geography • Population ~430,000 Cleveland • Emissions • Large power plants, steel mills, marine vessels, and on-road vehicles • Non-attainment for PM2.5 Cleveland Regional scale

  3. About EPA’s CMAPS • Cleveland Multiple Air Pollutant Study from August 2009 to August 2010 • identify particulate matter (PM) and mercury (Hg) sources • characterize emissions • understand the role of meteorology • characterize the spatial and temporal variability of multi-pollutant exposures • Two five-week intensives • EPA Principal Investigators include Gary Norris, Matthew Landis, and Ian Gilmour

  4. Complex PM2.5 Concentrations Urban PM2.5 Upwind PM2.5

  5. Understand the Role of Meteorology • Radar wind profiler (RWP) • Radio acoustic sounding system (RASS) • Mini-sodar • Surface meteorology

  6. Special Meteorological Measurements Meteorological tower RASS RWP Mini-sodar 6

  7. Methods • Case Studies • Episodes* versus non-episodes: • Diurnal PM2.5 • Large-scale meteorology • Mixing height • Boundary layer winds • RWP, RASS, and mini-sodar • WRF 4-km backward trajectories (EPA) • Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectories • Representativeness of CMAPS • *24-hr PM2.5 concentrations > 34.4 μg/m3 at St. Theodosis or G.T. Craig 7

  8. Mixing heights PM2.5 Case Study Example: August 15, 2009 (1 of 3) 54 μg/m3 Lake breeze 8

  9. CBL Mixing height Lake boundary layer Case Study Example: August 15, 2009 (2 of 3) 54 μg/m3 Southerly winds aloft 9

  10. Case Study Example: August 15, 2009 (3 of 3) 54 μg/m3 24-hr backward trajectories ending 6:00 PM EST 24-hr backward trajectories ending 12:00 PM EST Trajectory heights were 10 (black), 500 (gray), and 1,300 m agl (light gray). 10

  11. Case Study Example: March 08, 2010 High ventilation driven by moderate winds, but recirculation. 42 μg/m3

  12. Results: Episode vs. Non-episode: PM2.5 12

  13. Results: Episode vs. Non-episode: Peak Mixing Non-Episode Summer Episode Winter

  14. Results: Episode vs. Non-episode: Ventilation Non-Episode Summer Episode Winter

  15. Results: Episode vs. Non-episode: Transport S = 24-hr transport < ~100 km M = 24-hr transport between ~100 and 350 km L = 24-hr transport > ~400 km

  16. Summary of Episodes (1 of 2) • Moderate AQI carryover or transport on all days • Summer episodes (3): high ventilation • High mixing heights and moderate boundary layer winds from the southwest (2) • High mixing heights, but light winds with a lake breeze (1) 16

  17. Summary of Episodes (2 of 2) Winter episodes (7): wide variety of conditions • High ventilation driven by moderate winds, but recirculation (3) • Moderate ventilation driven by moderate west winds (2) • Low ventilation (low mixing and light winds) (2) 17

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