1 / 21

Comparison of CAMx and CMAQ PM2.5 Source Apportionment Estimates

Comparison of CAMx and CMAQ PM2.5 Source Apportionment Estimates. Kirk Baker and Brian Timin U.S. Environmental Protection Agency, Research Triangle Park, NC Presented at the 2008 CMAS Conference. Background.

phoebe
Download Presentation

Comparison of CAMx and CMAQ PM2.5 Source Apportionment Estimates

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. Comparison of CAMx and CMAQ PM2.5Source Apportionment Estimates Kirk Baker and Brian Timin U.S. Environmental Protection Agency, Research Triangle Park, NC Presented at the 2008 CMAS Conference

  2. Background • Photochemical model source apportionment is a useful tool to efficiently characterize source contribution to PM2.5 • Implemented particulate source apportionment in CMAQv4.6 • Compared the source apportionment results with other model system: CAMx • Existing inputs developed for Milwaukee pilot project used for comparison of source apportionment results

  3. PPTM & PSAT • The Particle and Precursor Tagging Methodology (PPTM) has been implemented in CMAQ v4.6 • Particulate Source Apportionment Technology (PSAT) has been implemented in CAMx v4.5 • Tracks contribution to mercury and PM sulfate, nitrate, ammonium, secondary organic aerosol, and inert species • Estimates contributions from emissions source groups, emissions source regions, and initial and boundary conditions to PM2.5 by adding duplicate model species for each contributing source • These duplicate model species (tags) have the same properties and experience the same atmospheric processes as the bulk chemical species • The tagged species are calculated using the regular model solver for processes like dry deposition and advection as bulk species • Non-linear processes like gas and aqueous phase chemistry are solved for bulk species and then apportioned to the tagged species

  4. CAMx v4.5 and CMAQ v4.6 12 km modeling domain 4 months in 2002: Jan, Apr, Jul, Oct Evaluating 24-hr average contributions from 11 source regions, the rest of the modeling domain, & boundary conditions Emissions processed separately for each source region PM2.5 Source Apportionment Modeling for Milwaukee Pilot Project

  5. Source Regions Region 12 – All non-tagged areas in domain Region 13 – Boundary conditions

  6. Daily 24-hr PM predictions at Milwaukee (550790026) and Waukesha (551330027) county STN monitors over all modeled days Model-Model estimates shown at right CMAQ tends to predict more nitrate than CAMx Model Performance

  7. Model Performance CMAQ CAMx

  8. Contribution Estimation • Evaluated contribution at Milwaukee (5) and Waukesha (1) monitors • PM2.5 = SO4+NO3+NH4+POC+EC • Examined 1) top 10% days, 2) average over all days, and 3) compared daily estimates • Days included in top 10% analysis: Q1=6, Q2=6, Q3=0, Q4=3 • Contribution from 11 source regions (counties), ICBC, all other non-tagged sources • Did not track SOA due to low model estimations and resource constraints

  9. Total PM2.5 Contribution Estimation

  10. 24-hr Avg Total PM2.5 Contribution Estimation: Top 10% Days CMAQ CAMx

  11. 4-month average total PM2.5 contributions from source areas 1-6 CAMx Region = 1 2 3 4 5 6 CMAQ

  12. 4-month average total PM2.5 contributions from source areas 7-11 CAMx Region = 7 8 9 10 11 CMAQ

  13. Distribution of 24-hr avg Contribution Estimations

  14. 24-hr avg Contributions estimated by CMAQ and CAMx

  15. 24-hr avg Contributions estimated by CMAQ and CAMx

  16. 24-hr avg Contributions estimated by CMAQ and CAMx

  17. 24-hr avg Contributions estimated by CMAQ and CAMx

  18. Domain Maximum 24-hr avg Initial Condition Contribution

  19. Remarks • CMAQ estimates more nitrate and as a result estimates larger nitrate contributions • CMAQ seems to estimate larger local contributions from primarily emitted species • Spatial extent of average contributions similar between models • Average contributions over high model days very similar at the Milwaukee/Waukesha monitors • Initial contributions drop out of model after 5-7 days • Would like to compare with CMAQ-DDM for future work

  20. Acknowledgements • Tom Braverman, US EPA • ICF International (Sharon Douglas and Tom Myers)

  21. JAN APR JUL OCT Kenosha County 24-hr max contribution Sulfate Nitrate Primary OC

More Related