Comparison of Three Secondary Organic Aerosol Algorithms Implemented in CMAQ

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Comparison of Three Secondary Organic Aerosol
Algorithms Implemented in CMAQ

• Weimin Jiang, Éric Giroux, Dazhong Yin, and
  Helmut Roth
• National Research Council of Canada

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Outline

• SOA calculation in CMAQ
• The three CMAQ SOA algorithms
• Model set-up
• Impact on organic aerosol modelling results
• spatial, temporal, SOA/fine ratios, algorithm
  correlations
• Impact on organic aerosol modelling performance
• comparison with measurements
• Conclusions and discussion

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SOA calculation in CMAQ

• Three major steps
• Steps 1 and 3 Binkowski and Roselle (2003)
  Binkowski and Shankar (1995) US EPA (1999)
• Implementation details Jiang and Roth (2003)
• Step 2 SOA algorithm to calculate SOA mass
  formation rate.

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Three CMAQ SOA algorithms

• Pandis constant AYs for 6 pseudo SOA precursor
  species
• Odum AYs for 4 pseudo species from
• Schell system of equations for 10 condensable
  species derived from 6 pseudo species, with T
  correction for gas phase saturation
  concentrations

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Model set-up the model

• Base model CMAQ 4.1
• Modularized AERO2 by NRC (Jiang and Roth, 2002)
• Schell extracted from AERO3 in CMAQ 4.2 and
  converted to a submodule in AERO2
• Three CMAQ executables different only in SOA
  submodule all other science and code the same

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Modularized aerosol module
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Model set-up domain, period, inputs

• Nested LFV domain, Pacific 93 episode (July 31
  August 7, 1993) see H. Roths presentation
• All model inputs are the same except for organic
  aerosol species
• clean IC and BC for the study of algorithm impact
  on modeling results
• observation-base IC and BC for the study of
  algorithm impact on model performance

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Impact on spatial distribution







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Impact on temporal variation







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Impact on model performance







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Conclusions and discussion
Schell Pandis
Odum Science best among three
simplified not usable SOA-generation n
x Pandis 10n x Odum very
low performance good on average
underestimate dramatic
underestimate Note wide range of
norm.bias Deficiency/problem no partitioning of
org. OAY, not IAY aerosol to gas
phase ? overestimate SOA (corrected in
CMAQ 4.3?)
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Odum algorithm problem OAY vs. IAY

• OAY Overall AY
• average AY
• from DROG0 and M00
• to DROG DROG and M0M0
• IAY Instantaneous AY
• AY at DROG and M0

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OAY equation vs. IAY equation

• Jiang (2003), Atmos. Environ. (in press)

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OAY or IAY A big deal?
Yes, a big deal both conceptually and
quantitatively.
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Acknowledgment

• US EPA Original Models3/CMAQ
• Environment Canada Pollution Data Branch, Air
  Quality Research Branch, Pacific Yukon Region
• Raw emissions and ambient measurement data
• Dr. D. G. Steyn of the University of British
  Columbia Pacific 93 data set
• Program of Energy Research and Development (PERD)
  in Canada
• Funding support

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Thank you !