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National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division
26 October 2011
Diagnostic Evaluation of Carbon Sources in CMAQ
Sergey L. Napelenok1, Heather Simon1, Prakash V. Bhave1,
George A. Pouliot1, Michael Lewandowski1,
Rebecca Sheesley2
1U.S. Environmental Protection Agency
Research Triangle Park, NC
2Baylor University
Waco, Texas
10th Annual CMAS Conference
Chapel Hill, NC
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1
Sites of interest: Bondville, IL; Northbrook, IL; Detroit, MI; Cincinnati, OHModeling episode: March 2004 – February 2005
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Traditional ModelEvaluation forParticulate Carbon
•Routine monitoring networksmeasure only TEC andTOC.
•For these 4 sites, suchevaluation is consistent withprevious studies.
•Four cases to explore:
Summer bias = -1.7 μg/m3
Northbrook winter bias = -1.4 μg/m3
Detroit spring bias = -0.3 μg/m3
Non-Detroit spring bias = -1.0 μg/m3
•Diagnosing the causes ofmodel bias with only thisdata is difficult.
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More Detailed Measurements
•Over 80 particle-phase organic compounds measured from March 2004to February 2005 at the four Midwestern sites.
•Filter samples collected every 6th day
•Filter extracts were composited on a monthly basis and analyzed bychemical derivitization and gas chromatography - mass spectrometry(GC-MS) for individual organic compounds.
–Hentriacontane, 20R-aaa-cholestane, Fluoranthene, levoglucosan,etc.
•Composites were also analyzed by EPA scientists for highly polarcompounds, which are tracers for SOA species.
–Pinonic acid, 2-methylthreitol, caryophyllinic acid, etc.
•Lewandowski, et al, Primary and Secondary Contributions to Ambient PMin the Midwestern United States, Environ. Sci. Technol., 2008, 42, 3003-3309.
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POA1POA2
POA3POA4
POA5POA6
POA7POA8
POA9POA10
POA11POA12
POA13POA14
POA15POA16
Organic PM2.5
Non-volatile
EMISSIONS
monoterpene
BIOGENIC EMISSIONS
SV_TRP1
SV_TRP2
O3P, NO3
∙OH,O3
ATRP1, ATRP2
Pathways do not contribute to SOA
SV_ISO1, SV_ISO2
SV_SQT
O3,O3P, or NO3
∙OH
∙OH,O3, or NO3
isoprene
sesquiterpenes
ASQT
AISO1, AISO2
AISO3
H+
high-yield
aromatics
long
alkanes
ANTHROPOGENIC EMISSIONS
low-yield
aromatics
benzene
ATOL1, ATOL2
AXYL1, AXYL2
SV_TOL1
SV_TOL2
∙OH/NO
SV_XYL1
SV_XYL2
∙OH/NO
AALK
SV_ALK
∙OH
ABNZ1, ABNZ2
SV_BNZ1
SV_BNZ2
∙OH/NO
AXYL3
ATOL3
ABNZ3
∙OH/HO2
∙OH/HO2
∙OH/HO2
AOLGB
AOLGA
AORGC
∙OH
dissolution
cloud water
glyoxal
methylglyoxal
VOCs
EMISSIONS
EMISSIONS
More Detailed Model (CMAQ v4.7.1 – Similar results expectedwith CMAQv5.0)
POA
Tagged 16 different source categories of EC and OC.
– Onroad Diesel Exhaust– Coal Combustion
– Nonroad Diesel Exhaust– Oil Combustion
– Onroad Gasoline Exhaust– Natural Gas Combustion
– Nonroad Gasoline Exhaust – Food Cooking
– Aircraft Exhaust – Paved Road Dust
– Anthrop Biomass Combustion – Crustal Material
– Wildfires – Misc. Industrial Processes
– Waste Combustion– Other
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PM Carbon Eastern U.S. Emissions Summary
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Example of Source Specific Emissions – January 1, 2005
onroad diesel
oil combustion
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Converting Source Tagged Species to Organic Tracers
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Mobile Sources
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Mobile Sources – Hopanes & Steranes
Calculating change in biasfrom sector correction:
RatioConc Δbias
μg/m3 μg/m3
1.0.820.330.07
2.0.720.190.07
3.0.760.290.09
4.0.490.160.17
0.07
0.17
0.09
0.07
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Biomass Burning - Levoglucosan
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0.38
0.08
-0.07
0.32
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Natural Gas Combustion - Ketones
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-0.04
-0.19
-0.01
-0.01
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Organic Aerosol
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•POC compares reasonablywell to measurements.
•SOA is underestimated forall species.
•Comparison in the Midwestis worse than previousevaluation with tracer datain Research Triangle Park.
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Monoterpenes
Midwest – 2004/2005
RTP – 2003
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Aromatics
Midwest – 2004/2005
RTP – 2003
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Potential Gains From Improvements – Organic Aerosol
•Isoprenes
0.680.000.050.22
Evidence for missing aqueous chemistry pathways
•Monoterpenes
0.310.030.170.13
Needs further analysis and data is available at other sites
•Sesquiterpenes
0.130.200.240.09
Evidence for emissions problems
Aromatics
0.170.040.150.09
Potentially increase the yields
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Concluding Remarks
•Unique comparison on model performance for an annual tracer dataset
•Measured tracer compounds are not inert – some react, degrade, and/orhave secondary sources in the atmosphere
•Measurement uncertainty is ~ 30%
•A valuable dataset for diagnostic evaluation:
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Source
SummerGain
(μgC/m3)
NorthbrookWinter Gain
(μgC/m3)
DetroitSpring Gain
(μgC/m3)
Non-DetroitSpring Gain
(μgC/m3)
SOA
1.29
0.27
0.61
0.53
Biomass Burning
0.38
0.32
-0.07
0.08
Mobile
0.07
0.07
0.09
0.17
Natural Gas
-0.04
-0.01
-0.19
-0.01
“Unexplained”
0.00!!
0.75
-0.14
0.23
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•contact: napelenok.sergey@epa.gov
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Additional Material…
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Model Description
•CMAQ v4.7.1
–SAPRC99 Chemistry
–12km horizontal Eastern US domain nested within 36km continentaldomain
–24 vertical layers up to 100 mb.
–MM5 meteorology
–SMOKE emissions (special treatment for primary TC)
–Hourly Geos-Chem boundary conditions
•Track source specific primary carbon concentrations using the CarbonApportionment option
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Summary/Conclusions
•Comparisons of measured and modeled tracers for primary sources arereasonable considering the uncertainty range of the observations (30%).
•Hopanes and Steranes show the best comparison.
•Levoglucosan is under predicted by the model in the summer indicating apossible missing source (wild fires in Canada?)
•Tracers with high model/obs ratios are known to degrade in theatmosphere (decay process not implemented in the model) e.g. hopanesat the rural site Bondville.
•Higher model/obs ratios in the summer support the possibility of tracervolatilization and degradation.
•Tracers with low model/obs ratios are known to have secondary sourcein the atmopshere e.g. n-Alkanoic Acids.