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

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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 2

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 3

PM2.5 Source Apportionment Modeling for Milwaukee Pilot Project 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 4

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

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 6

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 8

Total PM2.5 Contribution Estimation

5 4.5

4 1.5

1 0.5

0 3.5

3 2.5

2 1 CMAQ Top Days CAMx Top Days CMAQ All Days

# 1 2 3 4 5 6 7 8 9 10 11

CAMx All Days

Source Region Milwaukee Washington Ozaukee Waukesha Racine Sheboygan + Fond du Lac Dodge + Jefferson + Walworth Kenosha Cook Lake(IL) + McHenry + DuPage + Kane Lake(IN) + Porter + Will

2 3 4 5 6 7 Source Region 8 9 10 11

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

CMAQ CAMx

8 9 10 11 # 1 2 3 4 5 6 7 Source Region Milwaukee Washington Ozaukee Waukesha Racine Sheboygan + Fond du Lac Dodge + Jefferson + Walworth Kenosha Cook Lake(IL) + McHenry + DuPage + Kane Lake(IN) + Porter + Will 10

4-month average total PM2.5 contributions from source areas 1-6

CAMx

Region = 1 2 3 4 5 6

CMAQ

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4-month average total PM2.5 contributions from source areas 7-11

CAMx

Region = 7 8 9 10 11

CMAQ

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Distribution of 24-hr avg Contribution Estimations 13

24-hr avg Contributions estimated by CMAQ and CAMx

Specie SO4 = NO3 NH4 + EC OC *N = 20,111 r 2 0.82

0.59

0.78

0.89

0.93

CV 128 218 132 91 97 14

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 18

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 19

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

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