1 / 33

Improving emission inventories using direct flux measurements and modeling

This overview discusses improving emission inventories using direct flux measurements and modeling, with a focus on energy exchange fluxes, CO2, criteria pollutants, and VOCs. The text outlines the challenges faced at urban flux sites, presents selected results, and covers EPA STAR funded activities and measurements.

havyn
Télécharger la présentation

Improving emission inventories using direct flux measurements and modeling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Improving emission inventories using direct flux measurements and modeling Gunnar Schade, PI Don Collins, Qi Ying (Co-PIs) Texas A&M University EPA STAR Meeting, 16 Nov. 2010

  2. Overview • Brief Introduction • The Yellow Cab tower • challenges of an urban flux site • Selected results from previous measurements • Energy exchange fluxes • CO2 and criteria pollutants • VOCs • EPA STAR fund activities and measurements

  3. Introduction, I • Regional Air Quality (AQ) modeling improved • uses submodels for • emissions distribution (“inventory”) • atmospheric transport and chemistry • Emissions Inventory (EI) often assumed as being known well • Ambient AQ measurements challenge some EI assumptions; inadequate? • Can the EI be improved?

  4. Introduction, II • Past efforts of EI improvement • multivariate source apportionment using ambient AQ (concentration) data • ‘real-world’ emission measurements (tunnel studies) • AQ model studies • Our approach • micrometeorological flux measurements • top-down – bottom-up comparison • EI model AND AQ model testing

  5. Site Description, I

  6. Site Description, IIland use land cover

  7. Hardy / Elysian Roads

  8. Traffic Counts Hardy (south bound) Elysian (north bound) Quitman Road (east/west bound)

  9. How it looks like

  10. Tower Measurement Setup WS/WD aspirated T/RH Tower N PAR pyranometer w net radiation 60 m 50 m 40 m 20 m 13 m Sonic PC 20-m gradient DL Wind data (10 Hz) 3/8’’ and 1/4“ OD PFA Tubes Relaxed Eddy Accumulation Base Building GC- FID EC CO2 / H2O gradient Lag time ≈ 9 s slow: CO, NOx, O3

  11. Tower installations

  12. The challenge ‘Ordinary’ flux site Urban flux site heterogeneous land cover ill-defined footprint roughness sublayer ill-defined flux contributors high variability limited access private property undocumented activities ‘chaos’ studies attention to averages/medians • homogeneous land cover • well-defined footprint (MO theory) • well-defined flux contributors • limited variability • access to surface sites • upscaling / downscaling • targeted manipulations • process studies • attention to detail

  13. Energy exchange fluxes, I

  14. Energy exchange fluxes, II summer winter • delayed sensible heat flux • significant latent cooling • large heat storage and release (with hysteresis)

  15. Carbon dioxide (CO2) fluxes, I winter summer

  16. Carbon dioxide (CO2) fluxes, II weekdays weekends

  17. Carbon dioxide (CO2) fluxes, III

  18. Criteria Pollutant Fluxes, I Summertime (multi-month) medians

  19. Criteria Pollutant Fluxes, II

  20. Criteria Pollutant Fluxes, III CO-Flux ≈ ∆CO/∆CO2 x FCO2 rush-hour only

  21. Criteria Pollutant Fluxes, IV TexAQS 2006

  22. VOC fluxes, I

  23. VOC fluxes, II

  24. VOC fluxes, II

  25. STAR grant activities • continued (improved) measurements (G. Schade) • criteria pollutants (ongoing) and VOCs (2011+2012) • gradient (CP, ongoing) and REA flux (VOCs, 2011+2012) • potentially EC CO fluxes (loaned instrument; 2011) • additional aerosol (flux) measurements (D. Collins) • particle number fluxes (2011+2012) • modeling (G. Schade, Qi Ying)(ongoing) • (more detailed) ground survey • GIS improvements (ongoing) • roadside measurements (2011 or 2012) • ‘undocumented’ emissions (2011)

  26. Aerosol flux measurements, I Novel REA particle flux setup

  27. Aerosol flux measurements, II • approx. 80 m SS tubing, laminar flow • insulated • size-dependent line loss tests • one or two instruments • Initial measurement with DMA • accumulate density measurements over 30 min • APS installed and to be used if losses not excessive • particle flux per size range per half hour

  28. Modeling, I • GIS data • footprint models overlay • ground survey of sources • tracer release experiment

  29. Modeling, II • Source apportionment • concentration AND flux data • CMB and PMF methods • MOBILE6 vs. MOVES • CMAQ episode modeling • alternate input based on measurements • hindcast optimization

  30. MOBILE6 versus MOVES: Population normalized emission factors with vehicle speed (2-axle vehicles)

  31. Roadside measurements • chemistry? depositional loss? • A&M trailer; line power from pole • subset of instruments • simultaneous traffic counts • QUIC plume modeling

  32. Expected Results • Identify (and characterize) EI short-falls • example: missing isoprene and MACR emissions • Temporal and spatial characterization of emissions, including CP and VOCs • example: road versus non-road • Improve modeling hindcasts • characterize needed EI changes • Improve forecasts

  33. Acknowledgements • Greater Houston Transportation Company (Yellow Cab) • Texas Air Research Center (TARC) • EPA • Bernhard Rappenglück, UH • TCEQ

More Related