Updates to the Treatment of Secondary Organic Aerosol in CMAQv4.7 Sergey L.
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Transcript Updates to the Treatment of Secondary Organic Aerosol in CMAQv4.7 Sergey L.
Updates to the Treatment of Secondary
Organic Aerosol in CMAQv4.7
Sergey L. Napelenok, Annmarie G. Carlton, Prakash V. Bhave,
Golam Sarwar, George Pouliot, Robert W. Pinder,
Edward O. Edney, Marc Houyoux, Kristen M. Foley
U.S. Environmental Protection Agency
Research Triangle Park, NC
7th Annual CMAS Conference
Chapel Hill, NC
Office of Research and Development
6 October 2008
Covered Topics
• Previous SOA module (CMAQv4.6)
• Updated SOA module (CMAQv4.7)
• Additions/Enhancements
–
–
–
–
–
–
New precursors
SOA from aromatics under low-NOx conditions
Acid catalyzed SOA
Oligomerization of semi-volatile material
SOA from in-cloud oxidation
Parameterization changes
• Preliminary Results
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Previous Modeled Reactive Organic Gases and SOA (CMAQv4.6)
Sources
Anthropogenic:
Alkanes
Xylene
Cresol
Toluene
Biogenic:
Monoterpenes
5 Precursors
Products
Aitken Mode ASOA (AORGAI)
Accumulation Mode ASOA (AORGAJ)
Aitken Mode BSOA (AORGBI)
Accumulation Mode BSOA (AORGBJ)
4 SOA Species
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Current Reactive Organic Gases and SOA (CMAQv4.7)
Sources
Anthropogenic:
Alkanes
Xylene
Toluene
Benzene
Products (Accumulation Mode Only)
low-NOx
Biogenic:
Monoterpenes
Isoprene
Sesquiterpenes
Cloud:
Glyoxal/Methylglyoxal
density
update
high-NOx
MEGAN
emission
factors in
2-product
BEIS 3.14
model
8 Precursors
unchanged
AALKJ
AXYL1J, AXYL2J, AXYL3J
ATOL1J, ATOL2J, ATOL3J
ABNZ1J, ABNZ2J, ABNZ3J
AOLGAJ
acid catalyzed
ATRP1J, ATRP2J
AISO1J, AISO2J,
ASQTJ
AISO3J
“aged” SOA
AOLGBJ
AORGCJ
cloud produced
19 SOA Species
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NOx Dependence
• Under low-NOx conditions, aromatic peroxy radicals preferentially react with HO2
(and not NO)
• The resulting SOA formed from these reactions is considered non-volatile
• For example, benzene:
OH
BENZENE OH k
OH BENZRO2 other products
NO
BENZRO2 NO k
BENZENENO
HO2
BENZRO2 HO2
BENZENEHO2
k
• The pathway determines the type of SOA formed
– ΔBENZENENO partitions according to the 2-product Odum model
– ΔBENZENEHO2 becomes non-volatile SOA
• Parameterization was adapted from Ng et al. (2007)
• Implemented for SAPRC99 and CB05
• Changes to emissions processing are required to produce “delumped” benzene
emissions
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Acid Catalyzed Reactions
• Under acidic conditions, SOA production from isoprene is enhanced
• CMAQ parameterization is based on a series of chamber experiments
where the acidity of the seed aerosol was controlled (Surratt et al., 2007)
• Acidity enhancement is approximated by
normalizing the empirical relationship:
0.0389
0
H
SOCisop SOCisop
1
10.733
• The hydrogen ion concentration is
computed from a charge balance and
limited by the range of the experimental
conditions [ 0.0, 530.0 ] nmol/m3
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Condensed-Phase Reactions
• Semi-volatile SOA is converted to low-volatility products through
polymerization processes
• Kalberer et al. (2004) estimated that after 20 hours of aging, 50% of
organic particle mass consists of polymers
• CMAQ semi-volatile species are “aged” by transferring the mass into two
separate non-volatile species:
– Anthropogenic Oligomers from alkanes, xylene, toluene, and benzene
– Biogenic Oligomers from monoterpenes, isoprene, sesquiterpenes
• The SOA/SOC ratio for these products was set at 2.1 according to Turpin
& Lim (2001) for non-urban areas
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Cloud-Produced SOA
• Most air quality models predict lower OC concentrations aloft than are
suggested by measurements
• Models also predict less spatial and temporal variability
• CMAQ implementation:
– Glyoxal and Methylglyoxal as precursors, based on Carlton et al.
(2007) and Altieri et al. (2008)
kH
GLY / MGLY( g )
GLY / MGLY( aq )
GLY / MGLY(aq) OH(aq )
cloud SOA other products
• Yield is estimated to be 4% based on laboratory data
• OM/OC = 2.0
• Cloud-produced SOA is considered non-volatile
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Parameterization Changes - ΔHvap
• Enthalpy of vaporization has a role in the dependence of the partitioning
coefficient, Kom, on temperature:
H vap,i
T
K om ,i T K om ,i Tref
exp
Tref
R
1
1
T T
ref
• Previously, 156kJ/mol was used for all SOA species in CMAQ
• Values that appear in literature and are used in other models range from
15-88 kJ/mol, depending on the compound.
• The old CMAQ value was too large and was partly to blame for
exaggerated night-time and wintertime SOA peaks
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Impact of New ΔHvapValues
Compound
Ethalpy of
vaporization
(kJ/mol)*
SV ALK
40
SV XYL
32
SV TOL
18
SV BNZ
18
SV TRP
40
SV ISO
40
SV SQT
40
*based on lab measurements (Offenberg
et al., 2006)
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Interpreting SOA Results – OM/OC ratios
• Model calculates total organic mass
• OM/OC ratios are necessary for comparisons with measurements
CMAQv4.7
OM/OC
AALK
1.56
AXYL, ATOL, ABNZ
2.0
AISO1 & AISO2
1.6
AISO3
2.7
ATRP
1.4
ASQT
2.1
AORGC
2.0
AOLGA
2.1
AOLGB
2.1
AORGPA
1.0
CMAQv4.6
OM/OC
AORGA
1.67
AORGB
1.47
AORGPA
1.2
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Preliminary Module Evaluation
• Seasonal comparisons over eastern United States
– January and August 2006
– More reasonably predicted higher concentrations in the summer
(previously winter was higher)
• Model configuration:
– 12km resolution
– CMAQv4.6 “increment” with previous and new SOA treatment
– CB05 chemistry (EBI solver)
– “yamo” advection
– “acm2” diffusion
– “acm” clouds
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Anthropogenic SOA (monthly average, μg/m3)
January 2006
August 2006
Change to enthalpy of
vaporization
SOA model updates
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Biogenic SOA (monthly average, μg/m3)
January 2006
August 2006
Change to enthalpy of
vaporization
SOA model updates
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Preliminary Module Evaluation (Part 2)
• Carbon Tracer comparison at a site in RTP, NC
– Four 48 hour measurements during August/September 2003
– Speciated biogenic SOA (isoprene, monoterpene, sesquiterpene) and
aromatics
– Improvement over the old model is evident, but concentrations are still
much lower than indicated by tracer measurements
– Uncertainty in the tracer measurements: can laboratory measured
tracer/SOC ratios be applied to atmospheric conditions?
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Comparison to Carbon Tracer Measurements – RTP 2003
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Summary
• Major changes to CMAQ SOA module
– New precursors
– New processes
– Updated parameters
– Only moderate CPU time requirement increase – 17%
• Preliminary evaluation suggests several improvements
– Better seasonal trends
– Better diurnal trends
– Better science!
• Total OC mass did not increase much
– TRP SOA is lower due to lower ΔHvap offsetting gains from new precursors
– Intercontinental transport (boundary conditions) of longer-lived species?
– Role of intermediate VOCs?
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Current and Future Plans
• Continue SOA Module Evaluation
•
•
•
•
– RTP tracer data comparison
– LADCO data set analysis
– Sensitivity Analysis
Parameterization Updates
– Yields, Hvap, non-volatile rates, etc.
Rosenbrock solver for aqueous chemistry
More sophisticated oligomerization treatment
Further investigation in current and possible new precursors
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you are here!
Contact: [email protected]
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BONUS SLIDES
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Model CPU Time is Important!
17% increase
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Results in Context with Other Work – Morris et al., 2006
• Identified several missing pathways
for SOA formation in AQ models
• Implemented three of these into
CMAQ v4.4:
– Polymerization
• Based on Kalberer et al. (2004)
– Production from sesquiterpenes
• Emissions split from BEIS3
TERP
• SOA is nonvolatile
– Production from isoprene
• New volatile species
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Results in Context with Other Work – Henze et al., 2008
• Developed a mechanism to model
competition between low and highyield pathways of SOA formation from
aromatics
– Toluene
– Xylene
– Benzene (new)
• CMAQv4.7 aromatic SOA parameters
are based on this work
• Found benzene to be the most
important aromatic species for SOA
formation
• CMAQv4.7 ΔHvap values are lower
than what was used here (42 kJ/mol)
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Overview of the Underlying SOA Module
• Absorptive Partitioning Theory as adapted by Schell et al. (2001)
• Generally:
ROG OH
OH ,1COH ,1 ... OH ,n COH ,n
ROG O3
O3 ,1CO3 ,1 ... O3 ,n CO3 ,n
ROG NO3
NO3 ,1C NO3 ,1 ... NO3 ,n C NO3 ,n
• Some products, Ci,j, are condensable and contribute to SOA production:
Ctot,i i ROG
• Stoichiometric yield coefficients,
, are obtained from smog-chamber
studies
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Overview of the Underlying SOA Module (continued)
• Partitioning between gas and particle phase is based on saturation
*
concentration, Csat
,i
• Considering a mixture of condensable compounds (Raoult’s Law),
particle phase concentration of each can by calculated by:
C aer ,i Ctot ,i C
*
sat ,i
C aer ,i MWi
n
C POA MWPOA C aer , j MW j
j 1
– Important parameters:
• Stoichiometric yield coefficients:
i
*
• Saturation concentrations: C
(also T and ΔHvap)
sat ,i
• Molecular weights: MWi
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Seasonal Pattern Improves (SOAb)
AERO4
New - Old
August 2006
January 2006
AERO5
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Evaluation of TC results at
Duke Forest (August 2006)
Observations
Previous Incr.
SOA updates
Monthly-averaged TC
concentrations from SOA
Increment are slightly lower
than previous simulations.
Neither model version captures
the peak on 25-Aug.
However, the SOA Increment
exhibits several improvements
relative to previous simulations:
• lower coefficient of variation
• lower daily amplitude
Obs
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Previous SOA
Incr.
update
-------------------------------Total Carbon
mean
4.039 2.654 2.292
stdev
1.614 1.650 1.176
CoV
0.400 0.622 0.513
Daily amplitude [ug/m3]
median
2.610 3.707 2.853
min
0.740 2.144 1.373
max
5.820 6.223 5.318
-------------------------------# paired hours: 246
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# days with complete data: 25
Further Reading Material
Altieri, K.E., S.P. Seitzinger, A.G. Carlton, B.J. Turpin, G.C. Klein, A.G. Marshall, Oligomers
formed through in-cloud methylglyoxal reactions: Chemical composition, properties, and
mechanisms investigated by ultra-high resolution FT-ICR mass spectrometry, Atmos. Environ.,
42, 1476-1490, 2008
Carlton, A.G., B.J. Turpin, K.E. Altieri, A. Reff, S. Seitzinger, H.J. Lim, and B. Ervens,
Atmospheric Oxalic Acid and SOA Production from Glyoxal: Results of Aqueous
Photooxidation Experiments, Atmos. Environ., 41, 7588-7602, 2007.
Henze, D.K., J.H. Seinfeld, N.L. Ng, J.H. Kroll, T.-M. Fu, D.J. Jacob, C.L. Heald, Global modeling
of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield
pathways, Atmos. Chem. Phys., 8, 2405-2420, 2008.
Kalberer, M., D. Paulsen, M. Sax, M. Steinbacher, J. Dommen, A.S.H. Prevot, R. Fisseha, E.
Weingartner, V. Frankevich, R. Zenobi, U. Baltensperger, Identification of polymers as major
components of atmospheric organic aerosols, Science, 303, 1659-1662, 2004.
Morris, R.E., B. Koo, A. Guenther, G. Yarwood, D. McNally, T.W. Tesche, G. Tonnesen, J.
Boylan, P. Brewer, Atmos. Environ., 40, 4960-4972, 2006.
Ng, N. L., J. H. Kroll, A. W. H. Chan, P. S. Chhabra, R. C. Flagan, and J. H. Seinfeld, Secondary
organic aerosol formation from m-xylene, toluene, and benzene, Atmos. Chem. Phys., 7,
3909-3922, 2007.
Schell, B., I. J. Ackermann, H. Hass, F. S. Binkowski, and A. Abel, Modeling the formation of
secondary organic aerosol within a comprehensive air quality modeling system, J. Geophys.
Res., Vol 106, No D22, 28275-28293, 2001.
Surratt, J.D., M. Lewandowski, J.H. Offenberg, M. Jaoui, T.E. Kleindienst, E.O. Edney, J.H.
Seinfeld, Effect of acidity on secondary organic aerosol formation from isoprene, Environ. Sci.
Technol., 41, 5363-5369, 2007.
Turpin, B. J. and H.-J. Lim, Species contributions to PM2.5 mass concentrations: revisiting
common assumptions for estimating organic mass, Aero. Sci. Technol., Vol 35, 602-610, 2001.
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