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Effect of hydrophobic primary organic aerosols on secondary organic
aerosol formation from ozonolysis of a-pinene
Chen Song,
1
Rahul A. Zaveri,
1
M. Lizabeth Alexander,
2
Joel A. Thornton,
3
Sasha Madronich,
4
John V. Ortega,
2
Alla Zelenyuk,
2
Xiao-Ying Yu,
1
Alexander Laskin,
2
and David A. Maughan
1
Received 17 May 2007; revised 28 August 2007; accepted 14 September 2007; published 16 October 2007.
[1] Semi-empirical secondary organic aerosol (SOA)
models typically assume a well-mixed organic aerosol
phase even in the presence of hydrophobic primary organic
aerosols (POA). This assumption significantly enhances the
modeled SOA yields as additional organic mass is made
available to absorb greater amounts of oxidized secondary
organic gases than otherwise. We investigate the
applicability of this critical assumption by measuring SOA
yields from ozonolysis of a-pinene (a major biogenic SOA
precursor) in a smog chamber in the absence and in the
presence of dioctyl phthalate (DOP) and lubricating oil seed
aerosol. These particles serve as surrogates for urban
hydrophobic POA. The results show that these POA did
not enhance the SOA yields. If these results are found to
apply to other biogenic SOA precursors, then the semi-
empirical models used in many global models would predict
significantly less biogenic SOA mass and display reduced
sensitivity to anthropogenic POA emissions than previously
thought. Citation: Song, C., R. A. Zaveri, M. L. Alexander, J. A.
Thornton, S. Madronich, J. V. Ortega, A. Zelenyuk, X.-Y. Yu,
A. Laskin, and D. A. Maughan (2007), Effect of hydrophobic
primary organic aerosols on secondary organic aerosol formation
from ozonolysis of a-pinene, Geophys. Res. Lett.,34, L20803,
doi:10.1029/2007GL030720.
1. Introduction
[2] Measurements of ambient aerosols have shown that
organic compounds constitute between 20 and 90% of the
dry particle mass [Kanakidou et al., 2005; Zhang et al.,
2007]. Based upon their origin, these species are referred to
as primary organic aerosols (POA), which are directly
emitted into the atmosphere, and secondary organic aerosols
(SOA), which are formed in the atmosphere via gas-to-
particle conversion of myriad semi- and low-volatility
oxidation products of volatile organic compounds (VOC)
of both anthropogenic and biogenic origins. Sources of
POA include industrial emissions, automobile exhaust,
biomass burning, and biological aerosols [Kanakidou et
al., 2005]. While many SOA precursor gases are also
present in industrial and automobile emissions, 90% of
the global SOA budget is thought to result from the
oxidation of biogenic VOCs including isoprene, monoter-
penes, and sesquiterpenes [Kanakidou et al., 2005]. How-
ever, recent studies suggest that anthropogenic SOA
contribution to the global SOA budget may be much higher
than previously estimated [de Gouw et al., 2005; Volkamer
et al., 2006].
[3] The formation mechanisms of SOA and the interac-
tions between urban emissions and biogenic SOA precur-
sors are still poorly understood, resulting in a large
uncertainty in the simulated concentration and distribution
of these features within climate and air quality models
[Kanakidou et al., 2005]. While the development of detailed
and more reliable SOA mechanisms is an area of ongoing
research [Griffin et al., 2005; Pun et al., 2006], much work
has been done to develop computationally inexpensive,
semi-empirical SOA parameterizations for use in 3-D aero-
sol and air quality models based on what is widely referred
to as the ‘‘Odum model’’ [Odum et al., 1996, 1997; Schell et
al., 2001]. The Odum model is based on the Raoult’s Law
for absorption of organic gases in a mixture of organic
liquids [Pankow, 1994]. However, because of the lack of
exact speciation of all the actual SOA species, many model
parameters, such as the gas-phase stoichiometric coeffi-
cients and gas-particle partitioning constants for two or
more ‘‘model surrogate SOA species,’’ are semi-empirically
determined by fitting the model equation to the observed
SOA yield vs. total organic aerosol mass data obtained from
smog chamber experiments [Odum et al., 1996, 1997;
Griffin et al., 1999].
[4] Among the various simplifications made in the Odum
model is the explicit assumption that all organic species in a
particle form a well-mixed liquid organic phase which is
collectively able to absorb more organic vapors than would
be possible if all the organic species were present in separate
individual phases. This is a reasonable assumption for the
SOA species, because most of them are oxygenated polar
organic compounds which are likely to be miscible with one
another. However, when applied to the ambient atmosphere,
the Odum model continues to assume a single organic phase
even in the presence of anthropogenic/urban POA, a large
fraction of which is composed of hydrophobic non-polar
species [Canagaratna et al., 2004]. As a result, the well-
mixed SOA+POA phase in the model facilitates absorption
of more SOA species than if SOA and POA were to form
two separate phases.
[5] This assumption has major implications for the mod-
eled yields of SOA in the real atmosphere from anthropo-
genic precursors, which by definition are in the same air
GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L20803, doi:10.1029/2007GL030720, 2007
Click
Here
for
Full
A
rticl
e
1
Atmospheric Science and Global Change Division, Pacific Northwest
National Laboratory, Richland, Washington, USA.
2
Environmental Molecular Science Laboratory, Pacific Northwest
National Laboratory, Richland, Washington, USA.
3
Department of Atmospheric Sciences, University of Washington,
Seattle, Washington, USA.
4
Atmospheric Chemistry Division, National Center for Atmospheric
Research, Boulder, Colorado, USA.
Copyright 2007 by the American Geophysical Union.
0094-8276/07/2007GL030720$05.00
L20803 1of5
masses as the hydrophobic POA, as well as in situations
where hydrophobic POA from urban sources mixes with
biogenic SOA precursors. Several SOA modeling studies
have estimated the regional and global biogenic SOA
budgets based on this assumption and have concluded that
biogenic SOA yields would continue to increase with
increases in anthropogenic POA emissions in the future
[Kanakidou et al., 2000; Chung and Seinfeld, 2002;
Tsigaridis et al., 2006; Liao et al., 2007]. However, the
dependence of SOA yield for any known precursor hydro-
carbon gas on pre-existing organic seed aerosol has not been
systematically explored so far. In almost all the previous
smog chamber studies, SOA was either allowed to form via
homogeneous nucleation or by condensation on pre-existing
inorganic aerosols [Odum et al., 1996, 1997; Griffin et al.,
1999; Kroll et al., 2007]. Therefore, the assumption of a well-
mixed SOA+POA organic phase in the Odum model has
never been verified.
[6] We present here the first results from a set of smog
chamber experiments designed to investigate the effect of
pre-existing organic seed aerosols on the yield of SOA from
the ozonolysis of a-pinene (a major biogenic SOA precur-
sor). The organic seed aerosols used in this study were
generated from dioctyl phthalate (DOP) and lubricating oil,
which have been selected as proxies for urban hydrophobic
POA [Tobias et al., 2001; Canagaratna et al., 2004]. Our
results call into question the fidelity of the semi-empirical
SOA parameterizations commonly used in large-scale 3-D
models to estimate the regional and global biogenic SOA
budget, its sensitivity to anthropogenic POA emissions, and
its impact on climate.
2. Experimental Methods
[7] All experiments were performed in the indoor 8 m
3
Teflon smog chamber facility at Pacific Northwest National
Laboratory, Richland, WA. a-Pinene (Aldrich, 98% purity)
was gently warmed in a 200 ml glass bulb to volatilize into
a pure N
2
stream, which subsequently transported a-pinene
vapor into the chamber. A broad range of initial a-pinene
mixing ratios (6 to 82 ppbv), typically used to parameterize
the Odum model [Griffin et al., 1999], was used in this
study as well. DOP (Aldrich, 99% purity) and lubricating oil
(commercially available SAE 15W-40) were injected into a
glass tube heated to about 70– 80°C. A pure N
2
stream
carried the DOP or lubricating oil vapor through a 6 mm ID
Teflon tube where the cooled vapor nucleated to form
particles with peak diameters ranging from 150 to 200 nm.
Before entering the chamber, the semi-volatile organic com-
pounds in lubricating oil aerosol were largely removed by
passing them through a diffusion dryer (TSI Model 3062)
packed with activated charcoal, although the actual removal
efficiency was not quantified. To serve as an OH radical
scavenger, cyclohexane (Aldrich, 99% purity) was intro-
duced into the reactor at sufficient concentrations (20 to
80 ppmv) to ensure its OH reactivity exceeded that of a-
pinene by a factor of 100. Initial concentration of O
3
in
each experiment was set at about twice as high as that of
a-pinene, so that a-pinene concentrations were reduced to
negligible levels at the end of each experiment (2–3 h).
NO, NO
x
and O
3
were monitored by a Thermal Environ-
mental Instruments (TEI) Model 42C chemiluminescence
NO
x
analyzer and a TEI 49C O
3
analyzer, respectively.
a-Pinene decay and gas-phase oxidation products were
measured using a Proton Transfer Reaction Mass Spectrom-
eter (PTR-MS, Ionicon Analytik). Size distribution and
number concentration of aerosols were determined using a
Scanning Mobility Particle Sizer (SMPS, TSI 3696 Series).
Aerosol composition was analyzed using a Time-of-Flight
Aerosol Mass Spectrometer (C-ToF-AMS, Aerodyne Re-
search, Inc.) [Drewnick et al., 2005; DeCarlo et al., 2006].
Before each experiment, the reactor was continuously
flushed with purified air until the aerosol number concen-
trations were less than 5 cm
3
, NO, NO
x
, and O
3
concen-
Table 1. Experimental Conditions and Results
a
Expt. # T, °C
D[a-pinene],
mgm
3
Initial O
3
,
ppbv
Organic Seed
Aerosol
Initial Seed
Aerosol
Mass,
M
SEED, I
,
mgm
3
Estimated
Final Seed
Aerosol
Mass,
b
M
SEED, f
,mgm
3
Initial Aerosol
Number,
N
i
,cm
3
Final
Aerosol
Number,
c
N
f
,cm
3
Final
SOA
Mass,
c
M
SOA
,mgm
3
SOA Yield,
Y,-
1 28.8 - 185.1 Lube oil 79.6 10166 10127 0.0 -
2 27.5 245.3 211.4 No seed 0 0 15514 85.6 0.35
3 27.4 313.4 237.5 No seed 0 0 19161 119.7 0.38
4 27.9 32.7 46.6 No seed 0 0 1510 5.0 0.15
5 27.6 368.5 262.7 No seed 0 0 22470 159.3 0.43
6 27.8 452.2 369.2 No seed 0 0 33664 205.9 0.46
7 28.5 90.2 105.6 No seed 0 0 5398 25.7 0.28
8 28.1 186.1 221.9 No seed 0 0 12074 63.0 0.34
9 28.5 301.4 286.0 No seed 0 0 26898 112.8 0.37
10 28.1 60.3 95.5 Lube oil 14.0 9.0 13869 15454 14.3 0.24
11 28.4 180.1 189.9 Lube oil 46.4 30.9 19521 22875 55.7 0.31
12 27.7 283.9 257.0 Lube oil 86.2 64.4 15129 18730 115.7 0.41
13 28.4 369.2 271.0 Lube oil 136.3 95.4 23497 28335 162.0 0.44
14 27.9 451.1 254.6 Lube oil 175.0 132.2 19350 22588 217.0 0.48
15 27.7 166.8 134.7 DOP 136.1 96.7 5697 6585 57.7 0.35
16 28.0 207.1 178.0 DOP 50.3 39.0 6099 9549 69.8 0.34
17 28.4 94.3 138.7 DOP 52.2 39.2 11284 12869 27.3 0.29
18 27.9 260.5 186.5 DOP 134.4 89.3 14900 17960 88.8 0.34
a
Relative humidity was less than 2% for all experiments.
b
Estimated by applying first-order wall-loss rate to the initial seed mass concentration over a period of 2h.
c
Corrected for wall-loss.
L20803 SONG ET AL.: EFFECT OF POA ON SOA FORMATION L20803
2of5
trations were less than 1 ppbv, and the VOC concentrations,
as observed by the PTR-MS, were similar to those measured
directly in purified air.
3. Results and Discussion
[8] Experimental conditions and results for a total of 18
smog chamber experiments are summarized in Table 1.
SOA mass concentration (M
o
) was estimated from the
increase in aerosol volume concentration, which was cal-
culated using the measured aerosol size distributions by
SMPS and an a-pinene SOA particle density of 1.23 ±
0.01 g cm
3
determined using the technique described by
Zelenyuk et al. [2006]. The SOA particles can be assumed
to be spherical based on the narrow vacuum aerodynamic
size distributions observed with the SPLAT (Single Particle
Laser Ablation Time-of-flight) mass spectrometer. The true
particle density was then determined from the ratio of the
particle mobility and vacuum aerodynamic diameters mul-
tiplied by unit density. The reported SOA masses were
corrected for wall loss using the approach described by
Cocker et al. [2001]. Both DOP and lubricating oil organic
seed aerosols are nearly nonvolatile and mimic the hydro-
phobic portion of the urban POA quite well. These seed
aerosols are also not expected to have any direct effects on
the gas-phase oxidation of a-pinene. DOP does not contain
any unsaturated carbon bonds, and therefore does not react
with O
3
. Lubricating oil consists mainly of high molecular
weight n-alkanes, branched alkanes, alkyl-substituted cyclo-
alkanes, and aromatic compounds. Of these, only the
aromatic species could potentially react to a small extent
with O
3
. Results from our first experiment (#1) indicated
that lubricating oil particles were stable in O
3
-rich environ-
ment – the wall-loss corrected number and volume con-
centrations and the shape and peak diameter of the aerosol
size distribution also remained nearly constant for the
duration of the experiment (210 min).
[9] To ensure SOA species were condensed onto the pre-
existing organic seed particles, it was necessary to minimize
the extent of homogeneous nucleation. This was accom-
plished by filling the aerosol chamber with a high concen-
tration of POA before the a-pinene + O
3
reaction was
initiated. Table 1 shows the initial and final aerosol number
concentrations for each experiment; the latter were corrected
for wall loss. The differences between these numbers
indicate the number of SOA particles formed via homoge-
neous nucleation. While homogeneous nucleation of SOA
was still active in the presence of organic seed aerosols, it
was greatly suppressed compared to the unseeded experi-
ments. The estimated SOA mass in the nucleation mode was
1% of the total SOA mass at the end of experiments 10
through 18, while the rest of SOA mass was condensed onto
the pre-existing POA seed particles.
[10] Figure 1 shows the representative AMS mass spectra
of lubricating oil seed particles, pure a-pinene SOA par-
ticles, and a-pinene SOA + lubricating oil particles. Each
spectrum is an average for the entire experiment and
normalized to the total organic aerosol mass. These spectra
can be qualitatively interpreted using the approach of Zhang
et al. [2005], which uses the mass-to-charge ratios (m/z)of
57 (mostly C
4
H
9
+
) and 44 (mostly CO
2
+
) to distinguish
between hydrocarbon-like and oxygenated organic aerosols
Figure 1. Representative normalized AMS organic mass
spectra for (a) lubricating oil seed particles, (b) a-pinene
SOA formed in the absence of any organic seed particles,
and (c) a-pinene SOA formed in the presence of lubricating
oil seed particles.
Figure 2. Comparison of SOA mass produced (wall-
loss corrected) in the absence and presence of DOP
and lubricating oil seed aerosols as a function of amount
of a-pinene reacted. The symbols represent experimental
values and the line is the parameterized Odum model fit to
the no-seed data (i.e., open circles).
L20803 SONG ET AL.: EFFECT OF POA ON SOA FORMATION L20803
3of5
(HOA and OOA), respectively. As expected, the m57/m44
ratio is 8.9 for lubricating oil particles, indicating that they
are mainly composed of hydrocarbon-like species. The
relatively large m/z43 peak in these particles is likely due
to C
3
H
7
+
. On the other hand, the m57/m44 ratio is 0.08 for
pure a-pinene SOA, indicating that it is primarily composed
of highly oxygenated organic species. The a-pinene SOA
also contains a relatively large contribution from m/z43,
which could arise due to either C
3
H
7
+
or C
2
H
3
O
+
or both.
Finally, the a-pinene SOA+lubricating oil mass spectrum
clearly shows the presence of both the individual mass
spectra as expected, with an average m57/m44 ratio of
0.85.
[11] Figure 2 shows a plot of observed SOA mass
(symbols) as a function of the amount of a-pinene reacted
for all the experiments listed in Table 1. The SOA yield (Y)
shown in Table 1 is defined as Y=M
SOA
/D[a-pinene],
where M
SOA
(mgm
3
) is the mass concentration of
SOA formed and D[a-pinene] (mgm
3
) is the amount of
a-pinene reacted with O
3
. The two-product, semi-empirical
Odum model equation shown below was fit to the yield vs.
M
o
data for the smog chamber experiments in the absence of
any seed aerosols (baseline cases):
Y¼Mo
a1Kom;1
1þKom;1Mo
þa2Kom;2
1þKom;2Mo
;ð1Þ
where M
o
is the organic aerosol mass (mgm
3
), a
1
and a
2
are the mass stoichiometric coefficients of the two surrogate
products that are assumed to form from ozonolysis of
a-pinene, and K
om,1
and K
om,2
(m
3
mg
1
) are their gas-
particle (organic phase) partitioning coefficients. The
resulting fitted baseline parameter values are a
1
= 0.985,
a
2
= 0.30, K
om,1
= 0.00095, and K
om,2
= 0.207, with a
correlation coefficient R
2
= 0.99. Figure 2 also shows the
modeled M
SOA
vs. D[a-pinene] curve (line) generated using
these baseline model parameter values in the Odum model.
[12] Note that all the M
SOA
observations for experiments
with DOP or lubricating oil seed aerosols fall on the same
baseline curve that was obtained for the unseeded experi-
ments. These results indicate that the presence of DOP and
lubricating oil seed aerosols do not enhance the formation of
SOA mass by providing additional absorbing mass, as is
typically assumed in SOA models based on the Odum
parameterization [Kanakidou et al., 2000; Schell et al.,
2001; Chung and Seinfeld, 2002; Liao et al., 2007].
[13] Using the baseline model parameters and including
initial organic seed mass in the Odum model (i.e., M
o
=
M
SEED,i
+M
SOA
) to predict SOA for the seeded experiments
leads to overestimation of the SOA mass relative to the
observed values by 13– 44%, which represent the upper
limit. In practice, the organic seed mass available for SOA
condensation decreases as a function of time as the aerosol
particles are gradually lost to the chamber walls. Using the
estimated final organic seed mass in the baseline Odum
model (i.e., M
o
=M
SEED,f
+M
SOA
), it still overestimates the
SOA mass by 9– 34%, which represent the lower limit. This
analysis illustrates that atmospheric models that make this
assumption may erroneously predict high SOA yields. It
therefore appears that the condensed SOA species form a
separate organic phase, which then behaves in the same
manner as the homogeneously nucleated SOA with regard
to the gas-particle partitioning coefficients.
[14] Polar multifunctional organic compounds such as
aldehydes, carboxylic acids, hydroxy-carboxylic acids and
hydroxy-aldehydes are the major aerosol phase compounds
that have been identified from the oxidation of a-pinene by
ozone [Yu et al., 1999]. On the other hand, DOP as well as
the components of lubricating oil aerosol are non-polar and
may not be miscible with the polar SOA species. To
independently verify this, cis-pinonic acid (Sigma Aldrich,
98% purity), a known a-pinene SOA species, was added to
DOP and lubricating oil, respectively, at mass ratios of
1:100. After vigorously shaking the mixture for more than
10 min, the cis-pinonic acid crystals still remained as a
separate phase in both the mixtures. In contrast, cis-pinonic
acid crystals readily dissolved in water and in ethyl alcohol.
Similar tests could not be conducted for other major a-
pinene oxidation products as most of them are not com-
mercially available. Nevertheless, it is very likely that other
polar organic species present in a-pinene SOA would
behave in a similar manner. Atmospheric oxidation process-
es of other biogenic and anthropogenic SOA precursors
typically also produce compounds containing polar func-
tional groups, which are likely absorbed into the polar
organic phase of ambient aerosols rather than the non-polar
organic phase consisting of hydrophobic POA. On the other
hand, oxidized POA species and anthropogenic SOA
formed from the gas-phase oxidation of various precursor
species as well as semi-volatile POA species [e.g., Robinson
et al., 2007] may be able to absorb additional biogenic
SOA. Urban wood smoke and biomass burning POA
containing polar organic species may also be able to
efficiently absorb biogenic SOA species. Effects of these
types of POA on SOA formation should be explored via
controlled laboratory experiments in the future.
4. Conclusions and Implications
[15] The experimental data presented here show that SOA
yields from ozonolysis of a-pinene were insensitive to the
pre-existing dioctyl phthalate and lubricating oil seed aero-
sols, which were used to represent the urban hydrophobic
POA. These results suggest that a-pinene SOA species
condensed on pre-existing hydrophobic POA formed a
separate phase rather than a single well-mixed organic phase
with the POA species. These results are at odds with the
widely used semi-empirical SOA formulations that assume
a single well-mixed SOA+POA organic phase, which sig-
nificantly enhances the modeled SOA yields due to the
availability of additional organic mass to absorb greater
amounts of oxidized secondary organic gases.
[16] Recent studies show that, despite this assumption,
these semi-empirical models severely underpredict SOA
formation in ambient urban atmosphere as well as in the
upper troposphere [Heald et al., 2005; de Gouw et al., 2005;
Volkamer et al., 2006]. If the results presented here are found
to apply to other biogenic SOA precursors, then these models
would also predict less biogenic SOA mass at regional and
global scales than previously estimated and display reduced
sensitivity to the future increases in anthropogenic POA
emissions than previously thought [Kanakidou et al., 2000;
L20803 SONG ET AL.: EFFECT OF POA ON SOA FORMATION L20803
4of5
Chung and Seinfeld, 2002; Tsigaridis et al., 2006; Liao et al.,
2007].
[17] This conclusion underscores the need to fully under-
stand the actual chemical and physical processes for SOA
formation in the ambient atmosphere at urban, regional, and
global scales. It is not only necessary to develop the new
detailed SOA process modules based on smog chamber
experiments carried out under atmospherically relevant
conditions, but their fidelity and parametric sensitivities
must also be verified using field observations before they
can be simplified and reliably applied in regional and global
models. Focused laboratory studies and carefully designed
field studies downwind of urban centers located within or
upwind of forested areas are therefore needed to unravel the
interactions between anthropogenic and biogenic emissions
leading to SOA formation.
[18]Acknowledgments. We thank J. Birnbaum (PNNL) for support
with the smog chamber facility; M. Newburn (EMSL) and S. Garland (U.C.
Davis) for help with the C-ToF-AMS and PTR-MS measurements; Q.
Zhang (State University of New York, Albany) for assistance in analyzing
the AMS measurements; and C. Berkowitz and C. Geffen (PNNL) for their
support throughout this study. We also gratefully acknowledge the thought-
ful comments and suggestions of two anonymous reviewers. Funding for
this research was provided by the PNNL Laboratory Directed Research and
Development (LDRD) program and by the Environmental Molecular
Sciences Laboratory (EMSL), a national scientific user facility sponsored
by the Department of Energy’s Office of Biological and Environmental
Research and located at PNNL. Pacific Northwest National Laboratory is
operated for the U.S. Department of Energy by Battelle Memorial Institute
under contract DE-AC06-76RLO 1830.
References
Canagaratna, M. R., et al. (2004), Chase studies of particulate emissions
from in-use New York City vehicles, Aerosol Sci. Technol.,38, 555 – 573.
Chung, S. H., and J. H. Seinfeld (2002), Global distribution and climate
forcing of carbonaceous aerosols, J. Geophys. Res.,107(D19), 4407,
doi:10.1029/2001JD001397.
Cocker, D. R., III, R. C. Flagan, and J. H. Seinfeld (2001), State-of-the-art
chamber facility for studying atmospheric aerosol chemistry, Enivron.
Sci. Technol.,35, 2594 – 2601.
DeCarlo, P. F., et al. (2006), Field-deployable, high-resolution, time-of-
flight aerosol mass spectrometer, Anal. Chem.,78, 8281 – 8289.
de Gouw, J. A., et al. (2005), Budget of organic carbon in a polluted
atmosphere: Results from the New England Air Quality Study in 2002,
J. Geophys. Res.,110 , D16305, doi:10.1029/2004JD005623.
Drewnick, F., et al. (2005), A new time-of-flight aerosol mass spectrometer
(ToF-AMS) - Instrument description and first field deployment, Aerosol
Sci. Technol.,39, 637 – 658.
Griffin, R. J., D. R. Cocker III, R. C. Flagan, and J. H. Seinfeld (1999),
Organic aerosol formation from the oxidation of biogenic hydrocarbons,
J. Geophys. Res.,104, 3555– 3567.
Griffin, R. J., D. Dabdub, and J. H. Seinfeld (2005), Development and
initial evaluation of a dynamic species-resolved model for gas phase
chemistry and size-resolved gas/particle partitioning associated with sec-
ondary organic aerosol formation, J. Geophys. Res.,110, D05304,
doi:10.1029/2004JD005219.
Heald, C. L., D. J. Jacob, R. J. Park, L. M. Russell, B. J. Huebert, J. H.
Seinfeld, H. Liao, and R. J. Weber (2005), A large organic aerosol source
in the free troposphere missing from current models, Geophys. Res. Lett.,
32, L18809, doi:10.1029/2005GL023831.
Kanakidou, M., K. Tsigaridis, F. J. Dentener, and P. J. Crutzen (2000),
Human-activity-enhanced formation of organic aerosols by biogenic
hydrocarbon oxidation, J. Geophys. Res.,105, 9243 – 9254.
Kanakidou, M., et al. (2005), Organic aerosol and global climate modelling:
A review, Atmos. Chem. Phys.,5, 1053 – 1123.
Kroll, J. H., A. W. H. Chan, N. L. Ng, R. C. Flagan, and J. H. Seinfeld
(2007), Reactions of semivolatile organics and their effects on secondary
organic aerosol formation, Environ. Sci. Technol.,41, 3545– 3550.
Liao, H., D. K. Henze, J. H. Seinfeld, S. Wu, and L. J. Mickley (2007),
Biogenic secondary organic aerosol over the United States: Comparison
of climatological simulations with observations, J. Geophys. Res.,112 ,
D06201, doi:10.1029/2006JD007813.
Odum, J. R., T. Hoffmann, F. Bowman, D. Collins, R. C. Flagan, and J. H.
Seinfeld (1996), Gas/particle partitioning and secondary organic aerosol
yields, Environ. Sci. Technol.,30, 2580– 2585.
Odum, J. R., T. P. W. Jungkamp, R. J. Griffin, H. J. L. Forstner, R. C.
Flagan, and J. H. Seinfeld (1997), Aromatics, reformulated gasoline, and
atmospheric organic aerosol formation, Environ. Sci. Technol.,31, 1890 –
1897.
Pankow, J. F. (1994), An absorption-model of gas-particle partitioning of
organic compounds in the atmosphere, Atmos. Environ.,28(2), 185 – 188.
Pun, B. K., C. Seigneur, and K. Lohman (2006), Modeling secondary
organic aerosol formation via multiphase partitioning with molecular
data, Environ. Sci. Technol.,40, 4722– 4731.
Robinson, A. L., N. M. Donahue, M. K. Shrivastava, E. A. Weitkamp, A. M.
Sage, A. P. Grieshop, T. E. Lane, J. R. Pierce, and S. N. Pandis (2007),
Rethinking organic aerosols: Semivolatile emissions and photochemical
aging, Science,315, 1259 – 1262.
Schell, B., I. J. Ackermann, H. Hass, F. S. Binkowski, and A. Ebel (2001),
Modeling the formation of secondary organic aerosol within a compre-
hensive air quality model system, J. Geophys. Res.,106, 28,275 – 28,293.
Tobias, H. J., D. E. Beving, P. J. Ziemann, H. Sakurai, M. Zuk, P. McMurry,
D. Zarling, R. Waytulonis, and D. B. Kittleson (2001), Chemical analysis
of diesel engine nanoparticles using a nano-DMA/thermal desorption
particle beam mass spectrometer, Environ. Sci. Technol.,35, 2233 – 2243.
Tsigaridis, K., et al. (2006), Change in global aerosol composition since
preindustrial times, Atmos. Chem. Phys.,6, 5143– 5162.
Volkamer, R., J. L. Jimenez, F. San Martini, K. Dzepina, Q. Zhang,
D. Salcedo, L. T. Molina, D. R. Worsnop, and M. J. Molina (2006), Sec-
ondary organic aerosol formation from anthropogenic air pollution: Rapid
and higher than expected, Geophys. Res. Lett.,33, L17811, doi:10.1029/
2006GL026899.
Yu, J., D. R. Cocker, R. J. Griffin, R. C. Flagan, and J. H. Seinfeld (1999),
Gas-phase ozone oxidation of monoterpenes: Gaseous and particulate
products, J. Atmos. Chem.,34(2), 207– 258.
Zelenyuk, A., Y. Cai, and D. Imre (2006), From agglomerates of spheres to
irregularly shaped particles: Determination of dynamic shape factors from
measurements of mobility and vacuum aerodynamic diameters, Aerosol
Sci. Technol.,40, 197 – 217.
Zhang, Q., M. R. Alfarra, D. R. Worsnop, J. D. Allan, H. Coe, M. R.
Canagaratna, and J. L. Jimenez (2005), Deconvolution and quantification
of hydrocarbon-like and oxygenated organic aerosols based on aerosol
mass spectrometry, Environ. Sci. Technol.,39, 4938 – 4952.
Zhang, Q., et al. (2007), Ubiquity and dominance of oxygenated species in
organic aerosols in anthropogenically-influenced Northern Hemisphere
midlatitudes, Geophys. Res. Lett.,34, L13801, doi:10.1029/
2007GL029979.
M. L. Alexander, A. Laskin, J. V. Ortega, and A. Zelenyuk, Environmental
Molecular Science Laboratory, Pacific Northwest National Laboratory,
Battelle Boulevard, P.O. Box 999, Richland, WA 99352, USA.
D. A. Maughan, C. Song, X.-Y. Yu, and R. A. Zaveri, Atmospheric
Science and Global Change Division, Pacific Northwest National
Laboratory, Battelle Boulevard, P.O. Box 999, Richland, WA 99352,
USA. (rahul.zaveri@pnl.gov)
S. Madronich, Atmospheric Chemistry Division, National Center for
Atmospheric Research, P.O. Box 3000,1850 Table Mesa Drive, Boulder,
CO 80307, USA.
J. A. Thornton, Department of Atmospheric Sciences, University of
Washington, 408 ATG Building, Box 351640, Seattle, WA 98195, USA.
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