Atmospheric particulate water is ubiquitous, affecting particle transport and
uptake of gases. Yet, research on the effect of water on secondary organic
aerosol (SOA) mass yields is not consistent. In this study, the SOA mass
yields of an α-pinene and m-xylene mixture, at a concentration of
60 µg m-3, were examined using an oxidation flow reactor
operated at a relative humidity (RH) of 60 % and a residence time of 160 s. Wet or dried
ammonium sulfate and ammonium nitrate seed particles were used. By varying
the amount of seed particle surface area, the underestimation of SOA
formation induced by the short residence time in flow reactors was confirmed.
Starting at a SOA mass concentration of ∼5µg m-3, the
maximum yield increased by a factor of ∼2 with dry seed particles and on
average a factor of 3.2 with wet seed particles. Hence, wet particles increased
the SOA mass yield by ∼60 % compared to the dry experiment. Maximum
yield in the reactor was achieved using a surface area concentration of ∼1600µm2 cm-3. This corresponded to a condensational
lifetime of 20 s for low-volatility organics. The O:C ratio of SOA on
wet ammonium sulfate was significantly higher than when using ammonium
nitrate or dry ammonium sulfate seed particles, probably due to differences
in heterogeneous chemistry.
Introduction
The atmospheric aerosol is a dynamic mixture of organic and inorganic
species. A large fraction of the organic aerosol is formed as a result of
atmospheric processing of volatile organic compounds (VOCs), with products
condensing onto pre-existing particles, forming secondary organic aerosol
(SOA) (Hallquist et al., 2009). The partitioning of semivolatile organic
species from gas to particles can be either adsorptive or absorptive
depending on the chemical composition and phase of the particles
(Pankow, 1994). Despite the complexity of the atmospheric aerosol,
SOA mass yields (mass of formed particles divided by the mass of VOCs
reacted) have traditionally been parameterized in models using simplified
and relatively dry laboratory experiments.
Although not always measured, water is ubiquitous in the atmospheric aerosol,
influencing particle size, scattering, transportation/deposition and uptake
of gases, ultimately affecting both climate and health effects of particles
(Pilinis et al., 1989; Nguyen et al., 2016). The aerosol liquid water content
at subsaturation of water vapor depends on the relative humidity (RH), dry
particle chemical composition and size. The most abundant inorganic aerosol
compounds in submicron aerosol particles are the salts, ammonium sulfate (AS)
and ammonium nitrate (AN), which are mostly of anthropogenic origin (e.g.,
Pöschl, 2005; Zhang et al., 2007). A portion of the water in particles
can be regarded as anthropogenic water since both nitrate and sulfate
generally increase particle hygroscopicity (Carlton and Turpin, 2013; Hodas
et al., 2014), which in turn facilitates SOA formation of water-soluble
organic compounds. This particle formation pathway is believed to be
especially important for isoprene SOA, since isoprene's first-generation
oxidation products are relatively small molecules with high-saturation vapor
pressures compared to the oxidation products of other common SOA precursors
(Carlton et al., 2009; Ervens et al., 2011; Sareen et al., 2017). Also, the
electrolyte solution of ammonium sulfate and ammonium nitrate is acidic
since ammonia is a weak base, which increases the reactive uptake of several
SOA species (Jang et al., 2002; Gao et al., 2004).
SOA research has been substantial during the last two decades, and the
effects of relative humidity and aerosol liquid water on particle yields have
been investigated in numerous studies. From partitioning theory, it can be
shown (Seinfeld et al., 2001; Hallquist et al., 2009; Pankow, 2010) that
there should be a clear SOA mass yield dependence with RH, especially at low
precursor concentrations, if an activity coefficient of 1 is assumed.
Hennigan et al. (2008) showed that in an urban region dominated by biogenic
emissions, partitioning to liquid water may be a significant contributor to
SOA mass. However, adding water to laboratory oxidation experiments
complicates the interpretation, since both gas- (Jonsson et al., 2006; Warren
et al., 2009) and particle-phase (Ervens et al., 2011) chemistry may change.
Furthermore, the yield variation with different RH can be
NOx dependent (Ervens et al., 2011). For isoprene, both
particulate water and acidity are believed to have strong effects on the SOA
yield (Surratt et al., 2007; Carlton et al., 2009). Wong et al. (2015) showed
that wet ammonium sulfate seed particles resulted in 60 % more isoprene
SOA being formed compared to a system with dry seed particles at the same RH.
However, laboratory studies using other SOA precursors are somewhat
inconsistent. Prisle et al. (2010) saw no influence of RH (up to near
100 %) on α-pinene ozonolysis SOA yields with ammonium sulfate
seeds. Cocker et al. (2001a), investigating the same system but using dry
or wet seed particles, found that mass yields varied little with RH but
decreased if the seed particles were wet. In similar studies, the SOA yields
of m-xylene, 1,3,5-trimethylbenzene (Cocker et al., 2001b) and toluene (Edney et al., 2000) have been
found to be unaffected by the aerosol liquid water content. Lu et al. (2009)
found no effect on m-xylene SOA yields with wet or dry neutral seed
particles, while the yield was increased with dry acidic seed particles. In
contrast, other studies have found that higher RH significantly increases the
SOA mass yield of toluene and xylenes (Kamens et al., 2011; Zhou et al.,
2011). Also, more recently, Stirnweis et al. (2017) assessed the influence of
NOx and RH on α-pinene SOA with different seed
particles and concluded that particulate water significantly increases the
organic mass yields. Further, Faust et al. (2017) found 13 % and 19 %
increases in SOA yield from α-pinene and toluene, respectively, when
SOA was formed on wet salt particles. It can be difficult to compare the
results of different SOA oxidation experiments, since the conditions used are
rarely the same. SOA yields can depend on, e.g., temperature,
NOx concentrations, precursor concentration, oxidant
exposure and type, seed particle concentration and composition.
In the following work, we report SOA yields from a mixture of α-pinene
and m-xylene oxidized in a potential aerosol mass (PAM) oxidation flow reactor (OFR) (Kang et al.,
2007; Lambe et al., 2011a), in the presence of wet or dry ammonium sulfate
and ammonium nitrate seed particles. In contrast to many other studies
looking into the effect of particulate water on SOA mass yields, the RH was
held constant at 60 %, while the seed particles were either dried below
an RH of 10 % or kept in their droplet state. Previous studies have shown
that SOA produced in the reactor is similar to that produced in traditionally
used smog chambers (Bruns et al., 2015; Lambe et al., 2015). The reactor can
produce a more oxidized aerosol, which is strongly linked to the
hygroscopicity of organic aerosols (Pang et al., 2006; Chang et al., 2010;
Lambe et al., 2011b). Due to the fast processing in flow reactors, several
studies have discussed the potential problem with low condensation sinks
resulting in lower yields (Lambe et al., 2015; Palm et al., 2016; Ahlberg et
al., 2017; Jathar et al., 2017; Simonen et al., 2017; Zhao et al., 2018).
This effect was systematically investigated during the course of the
experiments by using different seed particle concentrations.
MethodsExperimental setup
All experiments consisted of introducing a constant flow of SOA precursors
with a varying concentration of seed particles into an oxidation flow
reactor. The experimental setup is shown in Fig. 1. Seed particles were
formed from atomization of a ∼1 g L-1 solution of ammonium
sulfate (Sigma Aldrich, ≥99 %) or ammonium nitrate (Sigma Aldrich,
≥99.5 %) in molecular-grade water. The size distribution of seed
particles had a maximum volume concentration at a mobility diameter between
∼150 and 200 nm. Although the molality of the solutions and pressure in
the atomizer were similar in all experiments, the output number size
distributions were not identical. The number of particles per volume unit, as
measured by the scanning mobility particle sizer (SMPS), increased in the following order: dry AS > wet
AS > dry AN > wet AN. The RH in the reactor was chosen between the
deliquescence and efflorescence points of ammonium sulfate (Seinfeld and
Pandis, 2006) and sodium chloride (experiments not reported here due to
instrument failure) so that the hysteresis effect could be used to alternate
between aqueous and dry particles. Ammonium nitrate has a reported
deliquescence RH of 61.8 % (Tang and Munkelwitz, 1993) but efflorescence
is not observed (Svenningsson, 1997; Lightstone et al., 2000). Seed particle
mass concentrations of ∼0–100 µg m-3 were achieved by
pulling a varying flow (0–0.7 L min-1) from
the atomizer through the reactor.
Experimental setup. Seed particles were either dried or maintained
in a liquid droplet. By changing the drain flow, the flow from the atomizer
was varied without perturbing the VOC concentrations in the reactor. Total
flow through the reactor was 5 L min-1 and RH was kept constant at
60 % by varying the RH of the humid flow.
VOCs were introduced into the reactor using a diffusion system with thin
capillaries, described in Ahlberg et al. (2017). VOCs were chosen to get a
mix of biogenic (α-pinene) and anthropogenic (m-xylene) SOA. The flow
of VOCs was held constant throughout an experiment. A relatively low SOA mass
concentration of ∼5µg m-3 without seed particles was
aimed for so that the nucleated particles would not be the dominant
condensation sink. The VOC concentration was determined after the experiments
by the liquid weight loss during 4 weeks. During these weeks, the
evaporation rate declined, probably due to VOC oxidation or VOC condensation
inside the capillaries. Therefore, the values of the first weighing were used.
If the decline during the first week, prior to the first weighing, was the
same as consecutive weeks, it would result in an overestimation of 13 %
in the summed yield. Since the timescales of an experiment (∼8 h) were
much shorter, oxidation or condensation inside capillaries is not expected to
have taken place. The total concentration of VOCs at the reactor inlet was
calculated to be 60 µg m-3 (5.2 ppb α-pinene and
6.7 ppb m-xylene); hence, the SOA mass yield with no seeds was ∼8 %, in agreement with previous measurements of the same mixture
(Ahlberg et al., 2017), albeit at slightly different VOC ratios.
SOA formation
SOA was produced using a PAM oxidation flow reactor, which has been
extensively used in laboratory and field measurements
(https://sites.google.com/site/pamwiki/, last access: 24 January 2019). The reactor, which is a 13.2 L horizontal
aluminium cylinder with passivated walls, produces very high concentrations
of ozone and hydroxyl radicals (OH) from UV lights mounted inside (Kang et
al., 2007; Lambe et al., 2011a). In recent years, measurements and modeling
have significantly advanced the knowledge of the reactor and best practices
during use have been developed (Ortega et al., 2013; Li et al., 2015; Peng et
al., 2015, 2016; Palm et al., 2016). Briefly, the reactor should not be used
with too-high OH reactivity (defined as the concentration of reactant
multiplied by the OH reaction rate) input, since OH may be suppressed. The
same problem may arise if the OH exposure is low due to low lamp voltage or
low absolute humidity. In this work, the flow was set to 5 L min-1 and
only one lamp was used. Lamp voltage was adjusted to reach an O3
concentration of 2.7–3 ppm. RH in the reactor was held constant at 60 %
by proportional–integral–derivative (PID) regulation of a humidified flow. With these settings, the OH exposure,
calibrated offline using 10 ppb of SO2 (for the detailed procedure,
see Lambe et al., 2011a), was 7×1011 molec. cm-3 s,
with an experimental uncertainty (1σ) of 5 %. The total OH
reactivity was 9.4 s-1, which is not believed to have induced
significant OH suppression (Peng et al., 2015, 2016). The temperature
increase inside the reactor due to the lamp was measured to 1–2 ∘C
prior to the experiments using a thermocouple inserted into the reactor. With
an RH of 60 % at 22 ∘C (room temperature), RH inside the reactor
is expected to be 53 %, which is above the efflorescence point of
ammonium sulfate at the same temperature.
Particle losses depend on reactor settings and particle sizes but are
generally lower than 10 % on a mass basis (Martinsson et al., 2015;
Karjalainen et al., 2016; Ortega et al., 2016; Palm et al., 2016). Ortega et
al. (2013) found that most of the particle losses take place at the inlet of
the reactor. In this work, losses at the inlet are not of importance, since
we look at SOA formed inside the reactor only. Palm et al. (2016) constructed
a model for the fate of low-volatility organic compounds (LVOCs) in the
reactor, in which four loss terms are competing: condensation onto particles,
wall loss, fragmentation (assumed after reacting with OH five times) and
outflow from the reactor. The model was compared with the SOA mass yields
at different seed concentrations. For the reactor settings used, the modeled
LVOC fate as a function of seed particle area is shown in Fig. 2. For model
sensitivity tests and uncertainties, the reader is referred to the original
paper.
The fractional fate of LVOCs as a function of particle surface
area concentration, using the model of Palm et al. (2016), with the same OH
reaction rate (1×10-11 cm3 molec.-1 s-1) and assuming
fragmentation after reaction with OH five times. For reactor settings, see
text.
Particle measurements
After oxidative aging in the reactor, the aerosol was dried below 30 %
RH before size distribution and mass-based chemical composition was measured
using a SMPS (Wiedensohler et al., 2012)
and an Aerodyne high-resolution time-of-flight aerosol mass spectrometer
(AMS; DeCarlo et al., 2006), respectively. The SMPS consisted of a
custom-built differential mobility analyzer (DMA) and a TSI condensation particle counter (CPC) (model 3010). Silica gel driers decreased the
RH of the sheath flow to below 10 %. The DMA voltages were calibrated
prior to experiments and the number size concentration was checked using polystyrene latex
(PSL) spheres. The AMS was calibrated using size-selected ammonium nitrate and
ammonium sulfate particles.
Experimental procedure and data analysis
An overview of the experiments can be seen in Table 1. Before experiments,
the reactor was run with the lamps on without seeds or VOCs until the volume
concentration was below 0.2 µm3 cm-3, as measured by the
SMPS. Before adding VOCs, two to five concentration levels of pure seed particles
were measured to be able to parameterize organic impurities from the atomizer
as a function of salt concentration. Despite using ultrapure water and zero
air (Linde, GT30000), up to 6 % of the total mass of the seed particles
were organic impurities and scaled roughly in a linear way with salt ion
concentration. Pieber et al. (2016) found interferences in the m/z 44
signal from reactions in the ionization region facilitated by inorganic salt
particles. However, in our experiments, the m/z 44 signal was only ∼15 % of the total organic impurity signal. Before calculating SOA
yields, the impurities were removed from the organic signal using the linear
relationship with the salt ions. After adding a constant concentration of
VOCs, SOA was measured at five to eight different seed particle concentrations. For
each seed type, experiments without seed particles were performed to get a
base-level yield. This level was relatively stable between experiments, at
5.0±0.5µg m-3 (1σ). Using data from a similar
mixture in Ahlberg et al. (2017), the difference in base level corresponds to
a difference in VOC concentrations of ±2µg m-3 (±3.3 %). During the dry ammonium nitrate experiment, the base level
drifted from 5 µg m-3 at the start to
6 µg m-3 at the end of the day. For this experiment, a
time-adjusted base level was implemented. The adjustment translated to an increase
in the SOA mass yield by at most 15 % for the lowest seed concentration,
to 1 % at the highest seed concentration.
For each of the four experiments, the table shows dry seed surface
area concentration, collection efficiency (CE) of the AMS for salts without
SOA, initial SOA without seed particles (two replicates where available) and
maximum SOA concentrations (with seed particles).
The SMPS was used to determine the particle number size distribution and
total particle volume and area concentrations. To calculate the input dry
seed particle surface area concentration, a parameterization from pure salt
measurements was made as a function of either sulfate or nitrate
concentration as measured by the AMS. The size distribution was also used to
calculate the condensation sink (CS) (Pirjola et al., 1999). However, we use
area concentration when presenting our data, since this is a measurement more
often used and in these experiments scaled linearly with CS.
AMS data were evaluated using standard AMS analysis programs (Squirrel v1.57
and Pika v1.16). Standard changes to the fragmentation table and
high-resolution spectra were made, including corrections for zero-air
CO2 concentrations and removal of organic peaks overlapping with
either air or salt peaks (m/z 14, 16, 32, 48, 64 for AS and 14, 16, 30, 46
for AN). The ammonium nitrate calibration of the AMS was used to calculate
the relative ionization efficiency (RIE) of ammonium, which was subsequently
used to calculate the RIE of sulfate. The RIE of ammonium was 4, which is
the default value of the AMS, but the RIE of sulfate, at 1.96, was
significantly higher than the default value of 1.2. Although this means that
the measured sulfate mass was decreased during analysis, it does not affect
the seed area calculations since the parameterization and seed mass changes
cancel each other. For organics, the default RIE of 1.4 was used. To evaluate
the AMS collection efficiency (CE) of the different experiments, the volume
concentration as measured by the SMPS was multiplied by particle density
calculated from the AMS chemical composition. A density of 1.4 g cm-3
was used for SOA from previous parameterizations of a similar mixture
(Ahlberg et al., 2017). The collection efficiencies used as a function of SOA
mass fraction can be seen in Fig. S1 in the Supplement. CEs for pure salts are
listed in Table 1. CE of both wet and dry ammonium sulfate increased with
increasing SOA mass fraction, likely due to decreased bounce. For ammonium
nitrate, CE was roughly constant around 1. Pure SOA had a CE of 0.63±0.03 (1σ). The relatively low CE of SOA may not only be a bounce
effect, since these particles were significantly smaller, with a number mode
around 20 nm and a volume mode around 40–50 nm in mobility diameter,
which to a higher degree are lost in the aerodynamic lens inlet of the AMS.
An example of the volume size distributions during an experiment is shown in
Fig. S2. The “improved ambient” parameterization was used to calculate
elemental ratios (Canagaratna et al., 2015). However, the organic portion of
the particles consisted of both SOA and salt impurities. To calculate the
O:C and H:C ratios of SOA only, the elemental ratios of the
impurities only and their fraction of the total organics were used. This
correction increased SOA O:C by ∼8 % and decreased
H:C by ∼0.5 % for AS, while for AN the change in O:C
was below 1 % and H:C decreased 1 %–2 %.
The increase in SOA yield from a mixture of m-xylene and α-pinene at different dry salt seed surface areas, normalized to the yield
from experiments with no seed particles. The corresponding condensation sink
is shown on the top axis. Error bars denote 1σ of the measurements.
The grey area represents ±20 % of the three experiments where the
seeds are not effloresced to illustrate the expected repeatability of the
experiments and the fact that the dry ammonium sulfate results are the only
ones falling outside of this range.
The SOA mass yield is defined as the amount of SOA formed divided by the
amount of VOCs reacted. Assuming constant OH concentration, with our settings
the VOC lifetimes for reaction with OH are short compared to the residence
time (4.3 and 16.2 s for α-pinene and m-xylene, respectively).
Therefore, we assume that all VOCs have reacted. However, comparing yields
only would give a skewed result, since small differences in base SOA level
between the experiments (Table 1) give large differences in yield. Instead, we
compared the ratio of base-level SOA mass to SOA mass at different seed
particle concentrations, which is equal to the relative increase in yield
(unitless). This cancels out the VOC concentrations from the calculations.
The uncertainty in the yield increase was calculated from error propagation
of the standard deviations of the measurements. The fractional uncertainty
with this method was between 6 % and 10 %. However, this only reflects
the precision in one experiment. Although all flow, pressure and OFR
settings were checked repeatedly, a variation larger than single experiment
standard deviation is expected since the setup was highly sensitive to small
perturbations. No experiment was repeated fully, but SOA levels without seeds
were tested twice per day. Replicates of SOA yield with seeds gave a
fractional error of 14 % compared to previous values. Therefore, a
conservative expected repeatability of the experiments is within 20 %.
Results and discussion
Figure 3 shows the increase in yield as a function of dry salt seed particle
surface area concentration. In all experiments, the yield increased
significantly with seed particle surface area, confirming previous findings
(Lambe et al., 2015; Palm et al., 2016; Ahlberg et al., 2017; Jathar et al.,
2017; Zhao et al., 2018). The extent of yield underestimation in these
experiments can be calculated by normalizing the yield with the maximum
yield. Doing this, all experiments follow the same trend with seed surface
area seen in Fig. 4. Also seen in Fig. 4 is the modeled bias (fraction
condensed on particles), following a similar trend but slightly lower, since
the experimental data only consider the condensation sink of the seed
particles, while in the model the total sink (seed plus SOA) is taken into
account. The yield error decreases up to a condensation sink of ∼0.05 s-1, corresponding to a seed surface area of ∼1600µm2 cm-3. Above this value, the LVOC fate model
(Fig. 2) also indicates a slower increase. However, while the LVOC model
yield continues to increase with increased seed area concentration, the
increase in the experimental yields levels off. This could be due to
increased fragmentation losses from heterogeneous oxidation, since a larger
portion of the SOA will be exposed with higher seed particle concentration.
The condensation sink at which the data level off corresponds to a lifetime
(τCS) of 20 s, which is similar to the residence time of the
reactor short circuit (Lambe et al., 2011a; Ahlberg et al., 2017).
SOA yield increase, from a mixture of m-xylene and α-pinene, normalized by the maximum SOA yield increase and plotted against
the dried seed particle condensation sink. Error bars denote the propagated
uncertainties (1σ). The black line shows the fraction of condensed
LVOCs according the model of Palm et al. (2016).
The results suggest that previous measurements using similar reactors have
underestimated the yield at low condensation sinks. Because the error is
larger at low yields, the yield curves will have a steeper increase and reach
a constant yield at lower mass concentrations. Applying corrections to
previous reactor experiments relying on nucleated particles as the only
condensation sink is not trivial, since the condensation sink varies with
time in the reactor. However, at a similar SOA condensation sink as that used
in this study (0.022 s-1), the yields should increase by a factor of 2–3
compared to when no seed is used (Fig. 3). Given the shape of the yield bias
in Fig. 4, at lower concentrations (and condensation sinks) the increase
should be even higher. According to the LVOC fate model a 3-fold increase in
yield (yield/max yield of 0.33) corresponds to a condensation sink of ∼0.006 s-1, suggesting the effective CS at this mass concentration is
approximately one-third (0.006/0.022) of the reactor outlet CS in nucleation experiments.
At half of that condensation sink (0.003 s-1), the model predicts a
5-fold increase in yield, and at 1/10 (0.0006 s-1) the increase could
be as high as a factor of 45. In Fig. 5, we used the LVOC fate model to
recalculate the yields of Ahlberg et al. (2017). The inverse of the fraction
condensed on particles at one-third of the experimental CS was multiplied with
the measured yields and mass concentrations. Because both x and y values
increase (both SOA mass and yields change with the same factor), the change
from the measurements is not as dramatic as when only looking at the absolute
yield increase or if yields were plotted against reacted VOCs. At
10 µg m-3, the increase in yield is estimated, from linear
regression between adjacent data points in Fig. 5, at 67 %, 80 %,
24 % and 94 % for α-pinene, m-xylene, myrcene and isoprene,
respectively, with the differences arising from differences in the size
distribution of each SOA precursor. It is likely that our assumption
that the effective CS is one-third of the output underestimates the yield at low
mass concentrations and overestimates the yield at high mass concentrations,
since higher VOC concentrations also produce a condensation sink faster than
a low-input VOC concentration. Although the calculations may be an
oversimplification, it is clear that the SOA mass yields at low mass
concentrations are biased low and that seed particles have a big impact in
OFR experiments.
Recalculated SOA mass yields from Ahlberg et al. (2017) as a
function of organic aerosol mass concentration (COA). Assuming an
effective condensation sink of one-third of the reactor output, the inverse of
the fraction condensed in the LVOC fate model from Palm et
al. (2016) was multiplied with the measured yields.
Colored symbols are recalculated values, and original values are represented
with the same symbol but no color. Dashed lines show the VBS models
constructed from the original data.
The second main result, also seen in Fig. 3, is that the increase in yield
with increased seed concentration is lower for the dry ammonium sulfate
experiment. Since ammonium nitrate does not effloresce (Svenningsson, 1997;
Lightstone et al., 2000), it is likely that both wet and dry AN adjusted to
the RH of the reactor, and thus these experiments are essentially the same.
Also, while the yield increase is highest for wet AS, this experiment had a
lower base-level SOA mass concentration, making it harder to rank the three
wet experiments. The grey area in the figure represents ±20 % of the
three experiments where the seed particles did not effloresce and is added to
emphasize the similarities between them. Dry ammonium sulfate was the only
crystalline particle, with a yield bias of a factor of ∼2, while the other
three experiments were similar given the experimental uncertainty, with a
yield bias factor of 2.9–3.5. Hence, wet seed particles increased the yield
by 45 %–75 %, with an average of 60 %, compared to the dry seed
experiment.
The difference between wet and dry experiments can be due to either
differences in partitioning, reactive uptake or both. Julin et al. (2014)
showed that the mass accommodation coefficient of several different organic
molecules is unity, regardless of the particle-phase state. In their study,
the condensed and gaseous phases consisted of the same molecules, which is
not the case in the present study. However, as soon as a layer of organics
has condensed on the crystalline AS particles, the mass accommodation for
uptake at the surface should approach unity. If an aqueous phase is to
increase the yield by equilibrium partitioning, the organic molecules need to
be water soluble and SOA mass concentration needs to be low enough to retain
an appreciable amount in the gas phase (Hallquist et al., 2009; Pankow,
2010). Several studies have shown that organic aerosol particles may undergo
liquid–liquid phase separation (Song et al., 2012b; You et al., 2012; Zuend
and Seinfeld, 2012). However, the water solubility of organic molecules
increases with decreasing molecular weight and increasing polarity
(O:C) (Varutbangkul et al., 2006; Massoli et al., 2010; Duplissy et
al., 2011), both of which are favored in OFR experiments compare to smog
chambers. It has been shown (Song et al., 2012a, b) that liquid–liquid phase
separation rarely occurs at O:C ratios higher than 0.7 in systems
containing organics, water and AS. In the present study, O:C was always
higher than 0.7, which is seen in Fig. 6 that shows the elemental ratios in
Van Krevelen space as measured by the AMS.
Van Krevelen diagram showing the elemental ratios of SOA from a
mixture of m-xylene and α-pinene, with different seed particles. The
white markers represent SOA without seeds for corresponding symbol
experiments. In general, O:C increased with increasing seed particle
concentration. The dotted lines represent the Ng triangle
(Ng et al., 2011a) translated to the improved ambient
elemental ratio parameterization (Canagaratna et al., 2015), to orientate
the reader. The insert shows the same figure with different axis ranges,
illustrating the fact that all data are within a relatively narrow range
compared to, e.g., ambient values.
The elemental ratios of all experiments fall within a relatively narrow range
(Fig. 6). The difference between wet and dry AN and dry AS is similar to the
difference between pure SOA on different days (white symbols), with
O:C within 0.83±0.08 (1σ) and H:C within 1.33±0.05 (1σ). The wet AS experiment however reaches higher O:C
values and spans a larger range. The O:C value increases with
increasing SOA mass concentration (and seed particle concentration since
these are connected), which is the opposite to what is expected since more
oxidized molecules tend to be less volatile (Shilling et al., 2009). The
increase is mostly due to the mass fragments with m/z 28 and 44. Several
acid-catalyzed oligomerization reactions change the elemental ratios of SOA
but with lower O:C as a result (Jang et al., 2002; Chen et al., 2011).
Also, saturated AN and AS solutions have similar pH (4.5 and 4.2,
respectively, according to the E-AIM model; Clegg et al., 1998); hence, there should be no
big difference between the wet experiments. A more likely explanation to the
change in O:C with SOA mass is heterogeneous oxidation. Increasing the
seed particle number concentration also decreases the SOA mass fraction per
particle. It follows that SOA mass then is spread out on more particles,
leaving less organics per particle, which enhances the area exposed to
oxidation. Kroll et al. (2015) showed that heterogeneous OH oxidation of
organic particles may increase the carbon oxidation state, however, at the
expense of SOA mass. The water uptake (growth factor) of AN and AS is
slightly different at 60 % RH, with an area increase of ∼1.4 and
∼1.7, respectively. However, the O:C increase with increasing area
is much larger for wet AS than for any other experiment; hence, a chemical
explanation is needed. To the best of our knowledge, there are no
measurements on differences between OH radical uptake on different salt
solution surfaces. Wang et al. (2016) found that the salting out effect
(pushing dissolved molecules out of the water phase) of several different
organic molecules is stronger in sulfate compared to nitrate solutions.
However, the compounds used were not similar to the SOA used in this study
and this effect should cause opposite results since the yield increase is
slightly higher for wet AS than for the AN experiments. Takami et al. (1998)
showed that below a pH of 7 the uptake coefficient of OH increases with
acidity. Given the small difference in acidity between saturated AN and AS it
is uncertain if this can explain the measurements. Wick and Dang (2006) found
that solvation of OH was correlated with increasing NaCl salt concentration.
A possible pathway for differences in reactive uptake of OH between the salt
solutions is the reaction with HSO4-, forming sulfate radicals
(Jiang et al., 1992). Sulfate radicals have been shown to be an important
source of organosulfates (Noziere et al., 2010; Schindelka et al., 2013).
However, sulfate from organics is indistinguishable from inorganic sulfate
in the AMS mass spectra since the fragmentation patterns are the same (Farmer
et al., 2010) and thus should not affect the calculated O:C ratios.
If sulfate aerosols affect the organic portion, this should be seen in
ambient samples. Indeed, several studies have shown that the more oxidized
SOA (LV-OOA) is correlated with sulfate (Ng et al., 2011b; Zhang et al.,
2011; Crippa et al., 2013; Hao et al., 2014), but a more straightforward
explanation to this is that both are secondary aerosol constituents.
Conclusions
Experiments were conducted with two aims: (i) to investigate the influence of
an aerosol liquid water phase on SOA yields and (ii) verifying and
quantifying the underestimation of SOA production in oxidation flow reactors
due to limited time for condensation. It was found that in all cases there
was a strong increase in yield with increased seed surface area
concentration and that the yield with wet seed particles was
45 %–74 % higher compared to dry seed particles. The yield increase
leveled off at a dry seed particle condensation sink of ∼0.05 s-1, corresponding to a surface area concentration of ∼1600µm2 cm-3. This value will be different for
different reactor geometries and settings (such as OH exposure and residence
time) and implies that it is crucial that the condensation sink is evaluated
in all OFR experiments where the absolute SOA mass is of interest.
If seed particles are used to drive the partitioning to the particle phase,
the choice of seed may affect the results due to differences in
heterogeneous chemistry and water uptake. This makes translation of lab
results to atmospheric relevance more difficult since a much higher seed
particle concentration is needed in a reactor than in the atmosphere to make
the condensed fractions comparable. To further study and parameterize the
effects of the condensation sink on OFR SOA, future experiments should focus
on different VOC concentrations with varying seed particle surface area, as
well as using different seeds or seed mixtures.
Using dry ammonium sulfate seed particles, the maximum yield increase was
approximately a factor of 2, while all wet experiments were similar and induced
an increase above a factor of 3. Hence, the wet particles produced around
60 % more SOA mass. The O:C ratio increased with decreasing SOA
mass fraction. Also, O:C was higher with wet AS compared to other
seeds, something which needs further research to fully explain but is likely
due to heterogeneous chemistry. These results point to the importance of
anthropogenic water as an important source of SOA.
Data availability
Data are available upon request from the corresponding
author.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-2701-2019-supplement.
Author contributions
EA designed the study with BS and PR. EA conducted the
experiments with AE. EA analyzed the data and prepared the manuscript draft. AE,
PR, BS and WHB critically reviewed the manuscript and conclusions.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
This work was financed by the Swedish research council Formas (grant 2011-00732). Edited by: Barbara Ervens Reviewed by: two
anonymous referees
References
Ahlberg, E., Falk, J., Eriksson, A., Holst, T., Brune, W. H., Kristensson,
A., Roldin, P., and Svenningsson, B.: Secondary organic aerosol from VOC
mixtures in an oxidation flow reactor, Atmos. Environ., 161, 210–220, 2017.Bruns, E. A., El Haddad, I., Keller, A., Klein, F., Kumar, N. K., Pieber, S.
M., Corbin, J. C., Slowik, J. G., Brune, W. H., Baltensperger, U., and
Prévôt, A. S. H.: Inter-comparison of laboratory smog chamber and
flow reactor systems on organic aerosol yield and composition, Atmos. Meas.
Tech., 8, 2315–2332, 10.5194/amt-8-2315-2015, 2015.Canagaratna, M. R., Jimenez, J. L., Kroll, J. H., Chen, Q., Kessler, S. H.,
Massoli, P., Hildebrandt Ruiz, L., Fortner, E., Williams, L. R., Wilson, K.
R., Surratt, J. D., Donahue, N. M., Jayne, J. T., and Worsnop, D. R.:
Elemental ratio measurements of organic compounds using aerosol mass
spectrometry: characterization, improved calibration, and implications,
Atmos. Chem. Phys., 15, 253–272, 10.5194/acp-15-253-2015,
2015.Carlton, A. G. and Turpin, B. J.: Particle partitioning potential of organic
compounds is highest in the Eastern US and driven by anthropogenic water,
Atmos. Chem. Phys., 13, 10203–10214,
10.5194/acp-13-10203-2013, 2013.Carlton, A. G., Wiedinmyer, C., and Kroll, J. H.: A review of Secondary
Organic Aerosol (SOA) formation from isoprene, Atmos. Chem. Phys., 9,
4987–5005, 10.5194/acp-9-4987-2009, 2009.Chang, R. Y.-W., Slowik, J. G., Shantz, N. C., Vlasenko, A., Liggio, J.,
Sjostedt, S. J., Leaitch, W. R., and Abbatt, J. P. D.: The hygroscopicity
parameter (κ) of ambient organic aerosol at a field site subject to
biogenic and anthropogenic influences: relationship to degree of aerosol
oxidation, Atmos. Chem. Phys., 10, 5047–5064,
10.5194/acp-10-5047-2010, 2010.Chen, Q., Liu, Y. J., Donahue, N. M., Shilling, J. E., and Martin, S. T.:
Particle-Phase Chemistry of Secondary Organic Material: Modeled Compared to
Measured O:C and H:C Elemental Ratios Provide Constraints,
Environ. Sci. Technol., 45, 4763–4770, 2011.Clegg, S. L., Brimblecombe, P., and Wexler, A. S.: Thermodynamic model of the
system H+-NH4+-SO42--NO3--H2O
at tropospheric temperatures, J. Phys. Chem. A, 102, 2137–2154, 1998.
Cocker, D. R., III, Clegg, S. L., Flagan, R. C., and Seinfeld, J. H.: The effect
of water on gas-particle partitioning of secondary organic aerosol. Part I:
alpha-pinene/ozone system, Atmos. Environ., 35, 6049–6072, 2001a.
Cocker, D. R., III, Mader, B. T., Kalberer, M., Flagan, R. C., and Seinfeld, J.
H.: The effect of water on gas-particle partitioning of secondary organic
aerosol: II. m-xylene and 1,3,5-trimethylbenzene photooxidation systems,
Atmos. Environ., 35, 6073–6085, 2001b.
Crippa, M., El Haddad, I., Slowik, J. G., DeCarlo, P. F., Mohr, C., Heringa,
M. F., Chirico, R., Marchand, N., Sciare, J., Baltensperger, U., and
Prévôt, A. S. H.: Identification of marine and continental aerosol
sources in Paris using high resolution aerosol mass spectrometry, J. Geophys.
Res.-Atmos., 118, 1950–1963, 2013.
DeCarlo, P. F., Kimmel, J. R., Trimborn, A., Northway, M. J., Jayne, J. T.,
Aiken, A. C., Gonin, M., Fuhrer, K., Horvath, T., Docherty, K. S., Worsnop,
D. R., and Jimenez, J. L.: Field-deployable, high-resolution, time-of-flight
aerosol mass spectrometer, Anal. Chem., 78, 8281–8289, 2006.Duplissy, J., DeCarlo, P. F., Dommen, J., Alfarra, M. R., Metzger, A.,
Barmpadimos, I., Prevot, A. S. H., Weingartner, E., Tritscher, T., Gysel, M.,
Aiken, A. C., Jimenez, J. L., Canagaratna, M. R., Worsnop, D. R., Collins, D.
R., Tomlinson, J., and Baltensperger, U.: Relating hygroscopicity and
composition of organic aerosol particulate matter, Atmos. Chem. Phys., 11,
1155–1165, 10.5194/acp-11-1155-2011, 2011.Edney, E. O., Driscoll, D. J., Speer, R. E., Weathers, W. S., Kleindienst, T.
E., Li, W., and Smith, D. F.: Impact of aerosol liquid water on secondary
organic aerosol yields of irradiated
toluene/propylene/NOx/(NH4)(2)SO4/air
mixtures, Atmos. Environ., 34, 3907–3919, 2000.Ervens, B., Turpin, B. J., and Weber, R. J.: Secondary organic aerosol
formation in cloud droplets and aqueous particles (aqSOA): a review of
laboratory, field and model studies, Atmos. Chem. Phys., 11, 11069–11102,
10.5194/acp-11-11069-2011, 2011.
Farmer, D. K., Matsunaga, A., Docherty, K. S., Surratt, J. D., Seinfeld, J.
H., Ziemann, P. J., and Jimenez, J. L.: Response of an aerosol mass
spectrometer to organonitrates and organosulfates and implications for
atmospheric chemistry, P. Natl. Acad. Sci. USA, 107, 6670–6675, 2010.
Faust, J. A., Wong, J. P. S., Lee, A. K. Y., and Abbatt, J. P. D.: Role of
Aerosol Liquid Water in Secondary Organic Aerosol Formation from Volatile
Organic Compounds, Environ. Sci. Technol., 51, 1405–1413, 2017.
Gao, S., Ng, N. L., Keywood, M., Varutbangkul, V., Bahreini, R., Nenes, A.,
He, J. W., Yoo, K. Y., Beauchamp, J. L., Hodyss, R. P., Flagan, R. C., and
Seinfeld, J. H.: Particle phase acidity and oligomer formation in secondary
organic aerosol, Environ. Sci. Technol., 38, 6582–6589, 2004.Hallquist, M., Wenger, J. C., Baltensperger, U., Rudich, Y., Simpson, D.,
Claeys, M., Dommen, J., Donahue, N. M., George, C., Goldstein, A. H.,
Hamilton, J. F., Herrmann, H., Hoffmann, T., Iinuma, Y., Jang, M., Jenkin, M.
E., Jimenez, J. L., Kiendler-Scharr, A., Maenhaut, W., McFiggans, G., Mentel,
Th. F., Monod, A., Prévôt, A. S. H., Seinfeld, J. H., Surratt, J. D.,
Szmigielski, R., and Wildt, J.: The formation, properties and impact of
secondary organic aerosol: current and emerging issues, Atmos. Chem. Phys.,
9, 5155–5236, 10.5194/acp-9-5155-2009, 2009.Hao, L. Q., Kortelainen, A., Romakkaniemi, S., Portin, H., Jaatinen, A.,
Leskinen, A., Komppula, M., Miettinen, P., Sueper, D., Pajunoja, A., Smith,
J. N., Lehtinen, K. E. J., Worsnop, D. R., Laaksonen, A., and Virtanen, A.:
Atmospheric submicron aerosol composition and particulate organic nitrate
formation in a boreal forestland–urban mixed region, Atmos. Chem. Phys., 14,
13483–13495, 10.5194/acp-14-13483-2014, 2014.Hennigan, C. J., Bergin, M. H., Dibb, J. E., and Weber, R. J.: Enhanced
secondary organic aerosol formation due to water uptake by fine particles,
Geophys. Res. Lett., 35, L18801, 10.1029/2008gl035046, 2008.
Hodas, N., Sullivan, A. P., Skog, K., Keutsch, F. N., Collett, J. L.,
Decesari, S., Facchini, M. C., Carlton, A. G., Laaksonen, A., and Turpin, B.
J.: Aerosol Liquid Water Driven by Anthropogenic Nitrate: Implications for
Lifetimes of Water-Soluble Organic Gases and Potential for Secondary Organic
Aerosol Formation, Environ. Sci. Technol., 48, 11127–11136, 2014.
Jang, M. S., Czoschke, N. M., Lee, S., and Kamens, R. M.: Heterogeneous
atmospheric aerosol production by acid-catalyzed particle-phase reactions,
Science, 298, 814–817, 2002.
Jathar, S. H., Friedman, B., Galang, A. A., Link, M. F., Brophy, P.,
Volckens, J., Eluri, S., and Farmer, D. K.: Linking Load, Fuel, and Emission
Controls to Photochemical Production of Secondary Organic Aerosol from a
Diesel Engine, Environ. Sci. Technol., 51, 1377–1386, 2017.
Jiang, P. Y., Katsumura, Y., Nagaishi, R., Domae, M., Ishikawa, K., Ishigure,
K., and Yoshida, Y.: Pulse-Radiolysis Study of Concentrated
Sulfuric-Acid-Solutions – Formation Mechanism, Yield and Reactivity of
Sulfate Radicals, J. Chem. Soc. Faraday T., 88, 1653-1658, 1992.Jonsson, Å. M., Hallquist, M., and Ljungström, E.: Impact of humidity
on the ozone initiated oxidation of limonene, Δ3-carene, and α-pinene, Environ. Sci. Technol., 40, 188–194, 2006.
Julin, J., Winkler, P. M., Donahue, N. M., Wagner, P. E., and Riipinent, I.:
Near-Unity Mass Accommodation Coefficient of Organic Molecules of Varying
Structure, Environ. Sci. Technol., 48, 12083–12089, 2014.
Kamens, R. M., Zhang, H. F., Chen, E. H., Zhou, Y., Parikh, H. M., Wilson, R.
L., Galloway, K. E., and Rosen, E. P.: Secondary organic aerosol formation
from toluene in an atmospheric hydrocarbon mixture: Water and particle seed
effects, Atmos. Environ., 45, 2324–2334, 2011.Kang, E., Root, M. J., Toohey, D. W., and Brune, W. H.: Introducing the
concept of Potential Aerosol Mass (PAM), Atmos. Chem. Phys., 7, 5727–5744,
10.5194/acp-7-5727-2007, 2007.Karjalainen, P., Timonen, H., Saukko, E., Kuuluvainen, H., Saarikoski, S.,
Aakko-Saksa, P., Murtonen, T., Bloss, M., Dal Maso, M., Simonen, P., Ahlberg,
E., Svenningsson, B., Brune, W. H., Hillamo, R., Keskinen, J., and
Rönkkö, T.: Time-resolved characterization of primary particle
emissions and secondary particle formation from a modern gasoline passenger
car, Atmos. Chem. Phys., 16, 8559–8570,
10.5194/acp-16-8559-2016, 2016.
Kroll, J. H., Lim, C. Y., Kessler, S. H., and Wilson, K. R.: Heterogeneous
Oxidation of Atmospheric Organic Aerosol: Kinetics of Changes to the Amount
and Oxidation State of Particle-Phase Organic Carbon, J. Phys. Chem. A, 119,
10767–10783, 2015.Lambe, A. T., Ahern, A. T., Williams, L. R., Slowik, J. G., Wong, J. P. S.,
Abbatt, J. P. D., Brune, W. H., Ng, N. L., Wright, J. P., Croasdale, D. R.,
Worsnop, D. R., Davidovits, P., and Onasch, T. B.: Characterization of
aerosol photooxidation flow reactors: heterogeneous oxidation, secondary
organic aerosol formation and cloud condensation nuclei activity
measurements, Atmos. Meas. Tech., 4, 445–461,
10.5194/amt-4-445-2011, 2011a.Lambe, A. T., Onasch, T. B., Massoli, P., Croasdale, D. R., Wright, J. P.,
Ahern, A. T., Williams, L. R., Worsnop, D. R., Brune, W. H., and Davidovits,
P.: Laboratory studies of the chemical composition and cloud condensation
nuclei (CCN) activity of secondary organic aerosol (SOA) and oxidized primary
organic aerosol (OPOA), Atmos. Chem. Phys., 11, 8913–8928,
10.5194/acp-11-8913-2011, 2011b.Lambe, A. T., Chhabra, P. S., Onasch, T. B., Brune, W. H., Hunter, J. F.,
Kroll, J. H., Cummings, M. J., Brogan, J. F., Parmar, Y., Worsnop, D. R.,
Kolb, C. E., and Davidovits, P.: Effect of oxidant concentration, exposure
time, and seed particles on secondary organic aerosol chemical composition
and yield, Atmos. Chem. Phys., 15, 3063–3075,
10.5194/acp-15-3063-2015, 2015.
Li, R., Palm, B. B., Ortega, A. M., Hlywiak, J., Hu, W. W., Peng, Z., Day, D.
A., Knote, C., Brune, W. H., de Gouw, J. A., and Jimenez, J. L.: Modeling the
Radical Chemistry in an Oxidation Flow Reactor: Radical Formation and
Recycling, Sensitivities, and the OH Exposure Estimation Equation, J. Phys.
Chem. A, 119, 4418–4432, 2015.
Lightstone, J. M., Onasch, T. B., Imre, D., and Oatis, S.: Deliquescence,
efflorescence, and water activity in ammonium nitrate and mixed ammonium
nitrate/succinic acid microparticles, J. Phys. Chem. A, 104, 9337–9346,
2000.Lu, Z. F., Hao, J. M., Takekawa, H., Hu, L. H., and Li, J. H.: Effect of high
concentrations of inorganic seed aerosols on secondary organic aerosol
formation in the m-xylene/NOx photooxidation system, Atmos.
Environ., 43, 897–904, 2009.
Martinsson, J., Eriksson, A. C., Nielsen, I. E., Malmborg, V. B., Ahlberg,
E., Andersen, C., Lindgren, R., Nystrom, R., Nordin, E. Z., Brune, W. H.,
Svenningsson, B., Swietlicki, E., Boman, C., and Pagels, J. H.: Impacts of
Combustion Conditions and Photochemical Processing on the Light Absorption of
Biomass Combustion Aerosol, Environ. Sci. Technol., 49, 14663–14671, 2015.Massoli, P., Lambe, A. T., Ahern, A. T., Williams, L. R., Ehn, M., Mikkila,
J., Canagaratna, M. R., Brune, W. H., Onasch, T. B., Jayne, J. T., Petaja,
T., Kulmala, M., Laaksonen, A., Kolb, C. E., Davidovits, P., and Worsnop, D.
R.: Relationship between aerosol oxidation level and hygroscopic properties
of laboratory generated secondary organic aerosol (SOA) particles, Geophys.
Res. Lett., 37, L24801, 10.1029/2010gl045258, 2010.Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Chhabra, P. S., Seinfeld, J.
H., and Worsnop, D. R.: Changes in organic aerosol composition with aging
inferred from aerosol mass spectra, Atmos. Chem. Phys., 11, 6465–6474,
10.5194/acp-11-6465-2011, 2011a.
Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Zhang, Q., Ulbrich, I. M., and
Worsnop, D. R.: Real-Time Methods for Estimating Organic Component Mass
Concentrations from Aerosol Mass Spectrometer Data, Environ. Sci. Technol.,
45, 910–916, 2011b.
Nguyen, T. K. V., Zhang, Q., Jimenez, J. L., Pike, M., and Carlton, A. G.:
Liquid Water: Ubiquitous Contributor to Aerosol Mass, Environ. Sci. Technol.
Lett., 3, 257–263, 2016.Noziere, B., Ekstrom, S., Alsberg, T., and Holmstrom, S.: Radical-initiated
formation of organosulfates and surfactants in atmospheric aerosols, Geophys.
Res. Lett., 37, L05806, 10.1029/2009gl041683, 2010.Ortega, A. M., Day, D. A., Cubison, M. J., Brune, W. H., Bon, D., de Gouw, J.
A., and Jimenez, J. L.: Secondary organic aerosol formation and primary
organic aerosol oxidation from biomass-burning smoke in a flow reactor during
FLAME-3, Atmos. Chem. Phys., 13, 11551–11571,
10.5194/acp-13-11551-2013, 2013.Ortega, A. M., Hayes, P. L., Peng, Z., Palm, B. B., Hu, W., Day, D. A., Li,
R., Cubison, M. J., Brune, W. H., Graus, M., Warneke, C., Gilman, J. B.,
Kuster, W. C., de Gouw, J., Gutiérrez-Montes, C., and Jimenez, J. L.:
Real-time measurements of secondary organic aerosol formation and aging from
ambient air in an oxidation flow reactor in the Los Angeles area, Atmos.
Chem. Phys., 16, 7411–7433, 10.5194/acp-16-7411-2016, 2016.Palm, B. B., Campuzano-Jost, P., Ortega, A. M., Day, D. A., Kaser, L., Jud,
W., Karl, T., Hansel, A., Hunter, J. F., Cross, E. S., Kroll, J. H., Peng,
Z., Brune, W. H., and Jimenez, J. L.: In situ secondary organic aerosol
formation from ambient pine forest air using an oxidation flow reactor,
Atmos. Chem. Phys., 16, 2943–2970, 10.5194/acp-16-2943-2016,
2016.
Pang, Y., Turpin, B. J., and Gundel, L. A.: On the importance of organic
oxygen for understanding organic aerosol particles, Aerosol Sci. Tech., 40,
128–133, 2006.
Pankow, J. F.: An Absorption-Model of Gas-Particle Partitioning of
Organic-Compounds in the Atmosphere, Atmos. Environ., 28, 185–188, 1994.
Pankow, J. F.: Organic particulate material levels in the atmosphere:
Conditions favoring sensitivity to varying relative humidity and temperature,
P. Natl. Acad. Sci. USA, 107, 6682–6686, 2010.Peng, Z., Day, D. A., Stark, H., Li, R., Lee-Taylor, J., Palm, B. B., Brune,
W. H., and Jimenez, J. L.: HOx radical chemistry in
oxidation flow reactors with low-pressure mercury lamps systematically
examined by modeling, Atmos. Meas. Tech., 8, 4863–4890,
10.5194/amt-8-4863-2015, 2015.Peng, Z., Day, D. A., Ortega, A. M., Palm, B. B., Hu, W., Stark, H., Li, R.,
Tsigaridis, K., Brune, W. H., and Jimenez, J. L.: Non-OH chemistry in
oxidation flow reactors for the study of atmospheric chemistry systematically
examined by modeling, Atmos. Chem. Phys., 16, 4283–4305,
10.5194/acp-16-4283-2016, 2016.Pieber, S. M., El Haddad, I., Slowik, J. G., Canagaratna, M. R., Jayne, J.
T., Platt, S. M., Bozzetti, C., Daellenbach, K. R., Frohlich, R., Vlachou,
A., Klein, F., Dommen, J., Miljevic, B., Jimenez, J. L., Worsnop, D. R.,
Baltensperger, U., and Prevot, A. S. H.: Inorganic Salt Interference on
CO2+ in Aerodyne AMS and ACSM Organic Aerosol Composition Studies,
Environ. Sci. Technol., 50, 10494–10503, 2016.
Pilinis, C., Seinfeld, J. H., and Grosjean, D.: Water-Content of Atmospheric
Aerosols, Atmos. Environ., 23, 1601–1606, 1989.
Pirjola, L., Kulmala, M., Wilck, M., Bischoff, A., Stratmann, F., and Otto,
E.: Formation of sulphuric acid aerosols and cloud condensation nuclei: An
expression for significant nucleation and model comparison, J. Aerosol Sci.,
30, 1079–1094, 1999.
Pöschl, U.: Atmospheric aerosols: Composition, transformation, climate
and health effects, Angew. Chem. Int. Edit., 44, 7520–7540, 2005.Prisle, N. L., Engelhart, G. J., Bilde, M., and Donahue, N. M.: Humidity
influence on gas-particle phase partitioning of alpha-pinene + O-3
secondary organic aerosol, Geophys. Res. Lett., 37, L01802, 10.1029/2009gl041402, 2010.
Sareen, N., Waxman, E. M., Turpin, B. J., Volkamer, R., and Carlton, A. G.:
Potential of Aerosol Liquid Water to Facilitate Organic Aerosol Formation:
Assessing Knowledge Gaps about Precursors and Partitioning, Environ. Sci.
Technol., 51, 3327–3335, 2017.
Schindelka, J., Iinuma, Y., Hoffmann, D., and Herrmann, H.: Sulfate
radical-initiated formation of isoprene-derived organosulfates in atmospheric
aerosols, Faraday Discuss., 165, 237–259, 2013.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from
air pollution to climate change, John Wiley & Sons, Hoboken, New Jersey,
2006.Seinfeld, J. H., Erdakos, G. B., Asher, W. E., and Pankow, J. F.: Modeling
the formation of secondary organic aerosol (SOA). 2. The predicted effects of
relative humidity on aerosol formation in the alpha-pinene-, beta-pinene-,
sabinene-, Delta(3)-Carene-, and cyclohexene-ozone systems, Environ.
Sci.
Technol., 35, 1806–1817, 2001.Shilling, J. E., Chen, Q., King, S. M., Rosenoern, T., Kroll, J. H., Worsnop,
D. R., DeCarlo, P. F., Aiken, A. C., Sueper, D., Jimenez, J. L., and Martin,
S. T.: Loading-dependent elemental composition of α-pinene SOA
particles, Atmos. Chem. Phys., 9, 771–782,
10.5194/acp-9-771-2009, 2009.Simonen, P., Saukko, E., Karjalainen, P., Timonen, H., Bloss, M.,
Aakko-Saksa, P., Rönkkö, T., Keskinen, J., and Dal Maso, M.: A new
oxidation flow reactor for measuring secondary aerosol formation of rapidly
changing emission sources, Atmos. Meas. Tech., 10, 1519–1537,
10.5194/amt-10-1519-2017, 2017.Song, M., Marcolli, C., Krieger, U. K., Zuend, A., and Peter, T.:
Liquid-liquid phase separation and morphology of internally mixed
dicarboxylic acids/ammonium sulfate/water particles, Atmos. Chem. Phys., 12,
2691–2712, 10.5194/acp-12-2691-2012, 2012a.Song, M., Marcolli, C., Krieger, U. K., Zuend, A., and Peter, T.:
Liquid-liquid phase separation in aerosol particles: Dependence on
O:C, organic functionalities, and compositional complexity, Geophys.
Res. Lett., 39, L19801, 10.1029/2012gl052807, 2012b.Stirnweis, L., Marcolli, C., Dommen, J., Barmet, P., Frege, C., Platt, S. M.,
Bruns, E. A., Krapf, M., Slowik, J. G., Wolf, R., Prévôt, A. S. H.,
Baltensperger, U., and El-Haddad, I.: Assessing the influence of
NOx concentrations and relative humidity on secondary
organic aerosol yields from a-pinene photo-oxidation through smog chamber
experiments and modelling calculations, Atmos. Chem. Phys., 17, 5035–5061,
10.5194/acp-17-5035-2017, 2017.
Surratt, J. D., Lewandowski, M., Offenberg, J. H., Jaoui, M., Kleindienst, T.
E., Edney, E. O., and Seinfeld, J. H.: Effect of acidity on secondary organic
aerosol formation from isoprene, Environ. Sci. Technol., 41, 5363–5369,
2007.
Svenningsson, B.: Hygroscopic growth of atmospheric aerosol particles and its
relation to nucleation scavenging in clouds, Division of Nuclear Physics,
Lund University, Box 118, 221 00 Lund, Sweden, 1997.
Takami, A., Kato, S., Shimono, A., and Koda, S.: Uptake coefficient of OH
radical on aqueous surface, Chem. Phys., 231, 215–227, 1998.
Tang, I. N. and Munkelwitz, H. R.: Composition and Temperature-Dependence of
the Deliquescence Properties of Hygroscopic Aerosols, Atmos. Environ. A-Gen.,
27, 467–473, 1993.Varutbangkul, V., Brechtel, F. J., Bahreini, R., Ng, N. L., Keywood, M. D.,
Kroll, J. H., Flagan, R. C., Seinfeld, J. H., Lee, A., and Goldstein, A. H.:
Hygroscopicity of secondary organic aerosols formed by oxidation of
cycloalkenes, monoterpenes, sesquiterpenes, and related compounds, Atmos.
Chem. Phys., 6, 2367–2388, 10.5194/acp-6-2367-2006, 2006.
Wang, C., Lei, Y. D., and Wania, F.: Effect of Sodium Sulfate, Ammonium
Chloride, Ammonium Nitrate, and Salt Mixtures on Aqueous Phase Partitioning
of Organic Compounds, Environ. Sci. Technol., 50, 12742–12749, 2016.
Warren, B., Malloy, Q. G. J., Yee, L. D., and Cocker, D. R.: Secondary
organic aerosol formation from cyclohexene ozonolysis in the presence of
water vapor and dissolved salts, Atmos. Environ., 43, 1789–1795, 2009.
Wick, C. D. and Dang, L. X.: Computational observation of enhanced solvation
of the hydroxyl radical with increased NaCl concentration, J. Phys. Chem. B,
110, 8917–8920, 2006.Wiedensohler, A., Birmili, W., Nowak, A., Sonntag, A., Weinhold, K., Merkel,
M., Wehner, B., Tuch, T., Pfeifer, S., Fiebig, M., Fjäraa, A. M., Asmi,
E., Sellegri, K., Depuy, R., Venzac, H., Villani, P., Laj, P., Aalto, P.,
Ogren, J. A., Swietlicki, E., Williams, P., Roldin, P., Quincey, P., Hüglin,
C., Fierz-Schmidhauser, R., Gysel, M., Weingartner, E., Riccobono, F.,
Santos, S., Grüning, C., Faloon, K., Beddows, D., Harrison, R., Monahan,
C., Jennings, S. G., O'Dowd, C. D., Marinoni, A., Horn, H.-G., Keck, L.,
Jiang, J., Scheckman, J., McMurry, P. H., Deng, Z., Zhao, C. S., Moerman, M.,
Henzing, B., de Leeuw, G., Löschau, G., and Bastian, S.: Mobility particle
size spectrometers: harmonization of technical standards and data structure
to facilitate high quality long-term observations of atmospheric particle
number size distributions, Atmos. Meas. Tech., 5, 657–685,
10.5194/amt-5-657-2012, 2012.
Wong, J. P. S., Lee, A. K. Y., and Abbatt, J. P. D.: Impacts of Sulfate Seed
Acidity and Water Content on Isoprene Secondary Organic Aerosol Formation,
Environ. Sci. Technol., 49, 13215–13221, 2015.
You, Y., Renbaum-Wolff, L., Carreras-Sospedra, M., Hanna, S. J., Hiranuma,
N., Kamal, S., Smith, M. L., Zhang, X. L., Weber, R. J., Shilling, J. E.,
Dabdub, D., Martin, S. T., and Bertram, A. K.: Images reveal that atmospheric
particles can undergo liquid-liquid phase separations, P. Natl. Acad. Sci.
USA, 109, 13188–13193, 2012.Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H.,
Ulbrich, I., Alfarra, M. R., Takami, A., Middlebrook, A. M., Sun, Y. L.,
Dzepina, K., Dunlea, E., Docherty, K., DeCarlo, P. F., Salcedo, D., Onasch,
T., Jayne, J. T., Miyoshi, T., Shimono, A., Hatakeyama, S., Takegawa, N.,
Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S., Demerjian,
K., Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R. J.,
Rautiainen, J., Sun, J. Y., Zhang, Y. M., and Worsnop, D. R.: Ubiquity and
dominance of oxygenated species in organic aerosols in
anthropogenically-influenced Northern Hemisphere midlatitudes, Geophys. Res.
Lett., 34, L13801, 10.1029/2007gl029979, 2007.
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Ulbrich, I. M., Ng, N. L.,
Worsnop, D. R., and Sun, Y. L.: Understanding atmospheric organic aerosols
via factor analysis of aerosol mass spectrometry: a review, Anal. Bioanal.
Chem., 401, 3045–3067, 2011.Zhao, Y., Lambe, A. T., Saleh, R., Saliba, G., and Robinson, A. L.: Secondary
Organic Aerosol Production from Gasoline Vehicle Exhaust: Effects of Engine
Technology, Cold Start, and Emission Certification Standard, Environ. Sci.
Technol., 52, 1253–1261, 2018.
Zhou, Y., Zhang, H. F., Parikh, H. M., Chen, E. H., Rattanavaraha, W., Rosen,
E. P., Wang, W. X., and Kamens, R. M.: Secondary organic aerosol formation
from xylenes and mixtures of toluene and xylenes in an atmospheric urban
hydrocarbon mixture: Water and particle seed effects (II), Atmos. Environ.,
45, 3882–3890, 2011.Zuend, A. and Seinfeld, J. H.: Modeling the gas-particle partitioning of
secondary organic aerosol: the importance of liquid-liquid phase separation,
Atmos. Chem. Phys., 12, 3857–3882, 10.5194/acp-12-3857-2012,
2012.