comparison of camx and cmaq pm2.5 source apportionment estimates
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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. - PowerPoint PPT PresentationTRANSCRIPT
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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
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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
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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
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PM2.5 Source Apportionment Modeling for Milwaukee Pilot Project
CAMx v4.5 and CMAQ v4.612 km modeling domain4 months in 2002:
Jan, Apr, Jul, OctEvaluating 24-hr average
contributions from 11 source regions, the rest of the modeling domain, & boundary conditions
Emissions processed separately for each source region
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Region 12 – All non-tagged areas in domainRegion 13 – Boundary conditions
Source Regions
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Model Performance
• 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
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Model Performance
CMAQ CAMx
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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
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Total PM2.5 Contribution Estimation
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0.5
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1.5
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2.5
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3.5
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4.5
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1 2 3 4 5 6 7 8 9 10 11
Source Region
Co
nc
en
tra
tio
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ug
/m3
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CMAQ Top Days CAMx Top Days CMAQ All Days CAMx All Days
# Source Region1 Milwaukee2 Washington3 Ozaukee4 Waukesha5 Racine6 Sheboygan + Fond du Lac7 Dodge + Jefferson + Walworth8 Kenosha9 Cook10 Lake(IL) + McHenry + DuPage + Kane11 Lake(IN) + Porter + Will
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24-hr Avg Total PM2.5 Contribution Estimation: Top 10% Days
# Source Region1 Milwaukee2 Washington3 Ozaukee4 Waukesha5 Racine6 Sheboygan + Fond du Lac7 Dodge + Jefferson + Walworth8 Kenosha9 Cook10 Lake(IL) + McHenry + DuPage + Kane11 Lake(IN) + Porter + Will
CMAQ CAMx
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CMAQ
CAMx
4-month average total PM2.5 contributions from source areas 1-6
Region = 1 2 3 4 5 6
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CMAQ
CAMx
4-month average total PM2.5 contributions from source areas 7-11
Region = 7 8 9 10 11
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Distribution of 24-hr avg Contribution Estimations
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24-hr avg Contributions estimated by CMAQ and CAMx
Specie r2 CVSO4= 0.82 128NO3- 0.59 218NH4+ 0.78 132EC 0.89 91OC 0.93 97*N = 20,111
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24-hr avg Contributions estimated by CMAQ and CAMx
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24-hr avg Contributions estimated by CMAQ and CAMx
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24-hr avg Contributions estimated by CMAQ and CAMx
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Domain Maximum 24-hr avg Initial Condition Contribution
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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
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Acknowledgements
• Tom Braverman, US EPA
• ICF International (Sharon Douglas and Tom Myers)
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Kenosha County 24-hr max contribution
Sulfate
Nitrate
Primary OC
JAN APR JUL OCT