Introduction
Tropospheric fine aerosol particles are known to cause several environmental
impacts, including adverse health effects and radiative forcing on climate
(Hallquist et al., 2009; IPCC, 2013). Organic compounds contribute a
significant percentage (from 20 to 90 %) of the total submicron aerosol
mass and secondary organic aerosol (SOA) accounts for a substantial fraction
of this organic mass (Kanakidou et al., 2005; Zhang et al., 2007). SOA
formation results from the atmospheric oxidation of volatile organic
compounds (VOCs) leading to the formation of less volatile oxidation
products that can undergo gas to particle conversion. Some of these oxidized
species contain acid, hydroxyl and/or aldehyde functional groups that
increase their water solubility, and thus explain their presence in cloud
droplets (Herckes et al., 2013; Herrmann et al., 2015). Clouds cover
∼ 70 % of the earth surface on average (Stubenrauch et
al., 2013; Wylie et al., 2005) and only ∼ 10 % of them
precipitate while the remaining ∼ 90 % dissipate, leading to
evaporation of volatile compounds and condensation of lower-volatility
species (Herrmann et al., 2015).
In the aqueous phase, soluble organic compounds can react with hydroxyl
radicals (OH) and/or by direct photolysis, similar to reactions in the gas
phase but in a depleted NOx environment. Aqueous-phase chemical
pathways thus lead to enhanced production of acids, such as oxalic acid,
(Carlton et al., 2007, 2006), and
oligomers that have been observed from the photooxidation of pyruvic acid
(Reed Harris et al., 2014), glyoxal (Carlton et
al., 2007), methylglyoxal (Lim et al., 2013; Tan et al., 2012),
methacrolein (MACR) and methyl vinyl ketone (MVK) (Liu et al.,
2012b), and glycolaldehyde (Perri et al., 2009). The produced
oligomers and/or humic-like substances (HULIS) are low volatility species and may remain in the
particle phase after water evaporation (Ervens et al., 2014;
Lim et al., 2013), leading to the formation of new SOA from aqueous phase,
called aqSOA (Ervens et al., 2011).
Recent laboratory (Lim et al., 2013; Liu et al., 2012b), field
(Dall'Osto et al., 2009; Huang et al., 2006; Lee et al., 2012; Lin et
al., 2010; Peltier et al., 2008) and modelling studies (Carlton and
Turpin, 2013; Couvidat et al., 2013; Ervens et al., 2008) suggest that this
additional SOA formation pathway can be considered important in terms of
quantity (up to +42 % of carbon yields (Ervens et al.,
2008)) and composition (Ervens et al., 2011);
however, these processes have never been directly experimentally
demonstrated.
Indeed, previous experiments from the literature evaluating an SOA source in
the aqueous phase were only carried out in homogeneous phases separately.
Studies were performed in homogeneous aqueous phases to observe oligomers and
low volatility organic acids formation (Altieri et al., 2008; Carlton et
al., 2006; Liu et al., 2012b), in homogeneous aqueous phase solutions with
nebulization and drying of the solutions to evaluate aqSOA formation (El
Haddad et al., 2009; Ortiz-Montalvo et al., 2012), and in the gas phase with
SOA (called gasSOA) formation followed by immersion of these gasSOA in homogeneous
aqueous phases (Bateman et al., 2011; Liu et al., 2012a). Previous
experimental studies have not been performed on a multiphase system and, as
a result, they only refer to the amount of precursor consumed in aqueous
phase to determine formation yields. Consequently, and contrary to SOA
yields obtained in gaseous phase (gasSOA), these yields cannot be directly
implemented in multiphase models because the link between aqueous and
gaseous phases (transfer between the two phases) is not taken into account.
These works thus lead generally to an overestimation of yields associated
with gaseous precursors, whose concentrations depend on the relative
importance of their loss in the gaseous phase and their transfer in the
aqueous phase. Furthermore, Daumit et al. (2014)
recently showed that the reactivity in a multiphase system may be
substantially different from reactivity in homogeneous aqueous phase,
highlighting the need to study controlled multiphase systems, which are more
realistic for the atmosphere.
In the present study, taking advantage of the ability to artificially
produce clouds in the CESAM simulation chamber
(Wang et al., 2011), dedicated multiphase
experiments were carried out to study SOA multiphase formation from isoprene
in order to experimentally observe and quantify the impact of cloud-phase
reactions on SOA formation. Isoprene was chosen as the precursor because it
is highly reactive and it represents the most emitted VOC globally. Isoprene
gas-phase oxidation is known to lead to low yields of gasSOA
(Brégonzio-Rozier et al., 2015; Dommen et al., 2006; Edney et al.,
2005; Kleindienst et al., 2006; Kroll et al., 2005; Zhang et al., 2011) and
to large amounts of volatile water soluble compounds (such as methylglyoxal,
glyoxal, glycolaldehyde and pyruvic acid), which can interact with the
aqueous phase in the atmosphere and potentially lead to the formation of
aqSOA after water evaporation. In this study, the formation of aqSOA from
isoprene photooxidation in the presence of clouds is investigated by
studying the concentration and chemistry of gaseous, aqueous and particulate
phases as well as the chemical exchanges between these phases.
Experimental section
Experiments were carried out in the CESAM chamber as described in detail by
Wang et al. (2011), and
Brégonzio-Rozier et al. (2015). Briefly,
it is a 4.2 m3 stainless steel reactor equipped with three xenon arc
lamps and Pyrex® filters of 6.5 mm thickness.
During each experiment, the reactive mixture is maintained at a constant
temperature with a liquid coolant circulating inside the chamber double wall
and monitored by a thermostat (LAUDA, Integral T10000 W). Temperature and
relative humidity (RH) are continuously monitored in the chamber using a
Vaisala HUMICAP HMP234 probe.
Experimental protocols
Cloud generation
To investigate the influence of a cloud on SOA formation, a specific
protocol allowing cloud generation with a lifetime close to droplet lifetime
in the atmosphere (∼ 2–30 min,
Colvile et al., 1997) in
the presence of light was designed. Clouds were generated by adding water
vapour into the chamber up to saturation: at 22 ∘C, ca. 81 g of
water vapour was introduced to reach saturation and to observe cloud
formation. The ultrapure water used was obtained fresh from an Elga Stat
Maxima Reverse Osmosis Water Purifier system, which includes reverse
osmosis, micro-filtration, nuclear-grade deionization, activated carbon
modules and an irradiation module at 254 nm leading to a resistivity greater
than 18.2 MΩ. As described in detail by Wang et al. (2011), water vapour was
pressurized in a small, 5 L, stainless steel vessel located below the chamber.
This small reactor was filled halfway with ultrapure water and heated to
reach a relative pressure of 1000 mbar. Half-inch stainless steel tubing
equipped with a valve was used to connect the vessel to the chamber and
allowed water vapour injection near the chamber's fan. Due to the 1000 mbar
pressure difference between the small reactor and the chamber, opening the
valve induced an instantaneous adiabatic cooling of the water vapour in the
chamber. Prior to injection in the chamber, the pressurized reactor was
purged at least five times to eliminate any residual air. Using this
procedure, starting from dry conditions in the chamber (< 5 %
RH), the first water vapour injection allowed the chamber to reach 80 %
RH within less than 1 min. A second water vapour injection leads to
water saturation in the chamber and cloud formation. The obtained clouds
were monitored, and Table 1 shows that their mean physical properties were
close to those of typical atmospheric clouds. A typical droplet mass size
distribution is also shown in Fig. S1 in the Supplement. Using the above described
procedure, several clouds could be generated during one experiment
(typically 2 or 3).
Comparisons of cloud properties between clouds generated in CESAM
(23 clouds) and atmospheric clouds (Colvile et al., 1997; Herrmann, 2003).
CESAM
Atmosphere
Droplet lifetime (min)
6–13∗
≈ 2–30
Liquid water content (g m-3)
Maximum: 0.01–1.48 Average: 0.005–0.62
0.05–3
Mean mass-weighed diameter (µm)
3.5–8
1–25
Number concentration (droplet cm-3)
Maximum: 1 × 103–5 × 104Average: 4 × 102–1 × 104
102–103
Mean number-weighed diameter (µm)
2–4
1–25
* Droplet lifetimes correspond to cloud lifetimes.
Cleaning and control experiments
In order to avoid any contamination from semi-volatile organic compounds
(SVOCs) off-gassing from the walls, a manual cleaning of the chamber walls
was performed prior each experiment. To this purpose, lint free wipes
(Spec-Wipe® 3) soaked in ultrapure water (18.2 MΩ, ELGA Maxima) were used. To complete this manual cleaning, the
walls were heated at 40 ∘C, and the chamber was pumped down to
secondary vacuum in the range of 6 × 10-4 mbar for 2 h
at a minimum. After pumping, the chamber was cooled down to 20–22 ∘C, and a control experiment was performed by generating a cloud in the
presence of a N2 / O2 mixture (80 % / 20 %), under
irradiation. All of the instruments were connected to the chamber during the
entire control experiment which lasted for ∼ 1 h after
cloud generation. The aim of these control experiments was to monitor aqSOA
formation arising from the dissolution of any remaining water soluble VOCs
off-gassing from the walls or from contaminants introduced with water
vapour. After this control experiment, the temperature of the chamber walls
was increased to 50 ∘C before starting overnight pumping. The
amount of particulate matter observed during all the control experiments was
fairly reproducible with an average value of 1.5 ± 0.4 µg m-3 of dried particles formed during a cloud event (Table S1 in the Supplement).
Cloud experiments
Two types of cloud experiments were performed to study the impact of clouds
on isoprene-SOA formation: (i) clouds generated during the first stages of
isoprene photooxidation, prior any gasSOA formation; and (ii) clouds
generated during later stages of the reaction, when gasSOA mass reached its
maximum. For each type of experiment, the protocol followed before beginning
irradiation was the same as the one described in
Brégonzio-Rozier et al. (2015). After
overnight pumping, synthetic air was injected into the chamber to reach
atmospheric pressure. This air was comprised of approximately 80 %
N2, produced from the evaporation of pressurized liquid nitrogen, and
around 20 % O2 (Linde, 5.0). A known pressure of isoprene, leading
to a mixing ratio of 800–850 ppb in the chamber, was then introduced using a
known volume glass bulb. Nitrous acid (HONO) was used as the OH source. HONO
was produced by adding sulfuric acid (10-2 M) dropwise into a solution
of NaNO2 (0.1 M) and flushed into the chamber using a flow of N2.
NOx was also introduced as a side product during HONO injection.
Photooxidation of the system was then initiated by turning on the lamps
(reaction time 0 corresponds to the irradiation start). Table 2 shows all of
the experimental initial conditions, the number of generated clouds during
each experiment and their maximum liquid water contents (LWCmax) for both
types of experiments.
Initial experimental conditions, maximum aerosol mass obtained
under dry conditions and information on the generated clouds.
Experimenta,b
[Isoprene]i
[NO]i
[NO2]ic
[HONO]i
ΔM0d
Ti
Number of
LWCmaxe
(ppb)
(ppb)
(ppb)
(ppb)
(µg m-3)
(∘C)
clouds
(g m-3)
Diphasic experiments
D300113
817
95
71
161
–
21
2
0.87 0.45
D010213
800
103
49
133
–
21.1
2
1.41 0.74
D190313
831
123
58
99
–
19.8
3
0.49 0.77 0.57
Triphasic experiments
T160113
846
143
27
15
< 0.1
21.5
1
0.47
T280113
833
88
45
125
2.8
18.3
2
0.81 0.88
T130313
840
66
< 1
45
2.4
17.5
1
n.m.f
T250313
802
137
48
121
0.15
19.7
2
0.02 0.01
a All experiments were carried out at initial RH < 5 %.
b Experimental IDs starting with “D” indicate diphasic experiments and
experimental IDs starting with “T” indicate triphasic experiments.
c Corrected for HONO interference.
d gasSOA mass concentration using an effective density of 1.4 g cm-3 (Brégonzio-Rozier et al.,
2015). There is no initial gasSOA formation for diphasic experiments.
e LWCmax of each cloud generated.
f not measured.
In the first type of experiment, a diphasic system (gas–cloud), the aim was
to produce evapo–condensation cycles in the presence of gaseous isoprene
oxidation products prior to any gasSOA formation. This type of experiment
started under dry conditions (< 5 % RH), and the first water
vapour injection, leading to ∼ 80 % RH, was performed after
2 h of irradiation. This time corresponded to ∼ 80 % of
isoprene consumption and to the maximum concentration of the first
generation isoprene gaseous reaction products
(Brégonzio-Rozier et al., 2015) . After
ca. 10 min, the second water vapour injection, allowing cloud formation
by saturation, was made. Two to three clouds were generated during each
diphasic experiment (gas–cloud).
In the second type of experiment, a triphasic system (gas-SOA-cloud), we
tested the influence of cloud generation on isoprene photooxidation during a
later stage of the reaction, i.e. when the first generation oxidation
gaseous products of isoprene were mostly consumed, and when maximum gasSOA
mass concentration was reached. In this case, in addition to the dissolution
of gaseous species in the aqueous phase, some of the condensed matter could
also dissolve in droplets. In this type of experiment, the formation of
gasSOA was monitored under dry conditions (< 5 % RH), and the
first cloud was generated when the maximum gasSOA mass concentration was
reached, generally after 7 to 9 h of irradiation, in a system containing
more oxidized species than in the diphasic system. One to two clouds were
generated during each triphasic experiment (gas-SOA-cloud). The variation of
species under dry conditions for triphasic experiments presented here can be
seen in Brégonzio-Rozier et al. (2015).
Measurements
A Fourier Transform Infra-Red spectrometer (FTIR,
Brucker®, TENSOR 37) was used to measure
concentrations of isoprene, MVK, MACR, formaldehyde, methylglyoxal,
peroxyacetyl nitrate (PAN), formic acid, carbon monoxide (CO) and NO2
during dry conditions. Complementary to FTIR measurements, a proton-transfer
time of flight mass spectrometer (PTR-ToF-MS 8000, Ionicon
Analytik®) was used for online gas-phase measurements in the
m/z range 10–200 including isoprene, the sum of MACR and MVK, 3-methylfuran
(3 M-F), acetaldehyde, the sum of glycolaldehyde and acetic acid, acrolein,
acetone, hydroxyacetone, and a few other oxygenated VOCs (de Gouw
et al., 2003a). The PTR-ToF-MS was connected to the chamber through a 120 cm
long Peek™ capillary heated at 100 ∘C. Its signal was
calibrated using a certified gas standard mixture (EU Version TO-14A
Aromatics 110L, 100 ppbV each). Considering the high amounts of water in the
sampled air during and after cloud events, the sum of the primary
H3O+ and cluster ion H2O⚫ H3O+ signal
derived from H318O+ (m/z 21.023) and
H218O⚫ H3O+ (m/z 39.033) count rate was taken
into account for quantification (de Gouw and Warneke, 2007; de Gouw et
al., 2003b; Ellis and Mayhew, 2014). A commercial UV absorption monitor
(Horiba®, APOA-370) was used to measure ozone. NO
was monitored by a commercial chemiluminescence NOx analyser
(Horiba®, APNA-370). During humid conditions, the
NO2 signal from the NOx monitor was used to determine NO2
mixing ratios, a correction was applied to take into account interferences
due to the presence of NOy during the experiments
(Dunlea et al., 2007). An
instrument developed in-house (NitroMAC), based on the wet chemical
derivatization technique and HPLC–VIS (high-performance liquid chromatography – visible) detection (Zhou et al.,
1999) and described in detail by Michoud
et al. (2014), was used to measure nitrous acid (HONO).
Aerosol size distribution from 10.9 to 478 nm, total number and volume
concentration of the particles were measured by a Scanning Mobility Particle
Sizer (SMPS). This instrument includes a Differential Mobility Analyzer
(DMA, TSI, model 3080) coupled with a Condensation Particle Counter (CPC,
TSI, model 3010). A high resolution time-of-flight aerosol mass spectrometer
(HR-ToF-AMS, Aerodyne) was used to measure chemical composition of
non-refractory particulate matter, such as organics, nitrate and ammonium
(Canagaratna et al., 2007; De Carlo et al., 2006). The HR-ToF-AMS was
used under standard operating conditions (vaporizer at 600 ∘C and
electron ionization at 70 eV). Standard AMS calibration procedures using
ammonium nitrate particles performed regularly, including the brute force
single particle (BFSP) ionization efficiency calibration and size
calibration. For HR-ToF-AMS data analysis, Squirrel (ToF-AMS Analysis 1.51H)
and PIKA (ToF-AMS HR Analysis 1.10H) packages for the software IGOR Pro 6.21
were used. The ionization efficiency obtained during BFSP calibration was
used to calculate mass and standard adjustments were used to account for the
relative ionization efficiency of each class of compounds (nitrate, sulfate,
ammonium, and organics) (Canagaratna et al., 2007). The standard
fragmentation table was adjusted to correct for the corrected air fragment
column for the carrier gas. A collection efficiency of 0.5 was used for the
organics to adjust for particle bounce at the heater
(Middlebrook et al., 2012).
The SMPS and the HR-ToF-AMS were connected to the chamber through the same
sampling line and dried with a 60 cm Nafion® tube
(Permapure™, model MD-110). The relative humidity was
continuously measured after drying and was never above 22 % RH at the
outlet of the Nafion® tube. Systematically
maintaining the relative humidity in the sampling line lower than the
efflorescence point of any expected particulate matter was a critical
parameter to effectively detect additional SOA and not a water uptake due to
the change in relative humidity in the chamber. It is hence important to
consider that all the SOA quantity, size distribution or AMS analysis
discussed later in this paper concern dried SOA.
The size distributions of cloud droplets were determined by a white light
optical particle counter (Welas® 2000, Palas)
using the refractive index of water (1.33+0i). The particle size range of
this sensor was 0.6–40 µm. The Welas optical particle counter was
calibrated using a calibration dust (CalDust 1100) exhibiting the same index
of refraction as polystyrene latex (PSL) spheres.
Results and discussion
The aim of these experiments was to evaluate the influence of clouds on SOA
formation in the isoprene / NOx / air / light system. This system was already
characterized in detail under dry conditions in the same chamber by
Brégonzio-Rozier et al. (2015). To that
purpose, as stated above, two new protocols were tested: a diphasic and a
triphasic system. The corresponding results are shown in Figs. 1 to 4, and
discussed hereafter.
SOA formation in the presence of a cloud
Effects of liquid phase clouds on SOA mass concentrations during
two cloud events for typical diphasic (D300113, left panel) and triphasic
(T280113, right panel) systems. Time profiles of (a and a') dried SOA mass
concentration, (b and b') dried SOA mass size distribution, (c and c') cloud
droplet mass size distribution and relative humidity in the simulation
chamber. A particle density of 1.4 µg m-3 was assumed.
Summary of the maxima increases of the total particle mass
concentration observed during cloud events for diphasic and triphasic
experiments.
Experiment∗
Increase in mass
Cloud lifetime
(µg m-3)
(min)
Diphasic experiments
D300113 1st cloud
8.0
12
D300113 2nd cloud
5.1
9
D010213 1st cloud
6.1
13
D010213 2nd cloud
1.9
9
D190313 1st cloud
3.9
11
D190313 2nd cloud
2.6
12
D190313 3rd cloud
2.7
11
Triphasic experiments
T160113
6.4
10
T280113 1st cloud
6.5
10
T280113 2nd cloud
5.5
10
T130313
7.2
11
T250313 1st cloud
4.3
9
T250313 2nd cloud
2.1
6
∗ Experimental IDs starting with “D” indicate diphasic
experiments, experimental IDs starting with “T” indicate triphasic
experiments.
During cloud events, a sudden and significant increase in dried SOA mass
concentration was observed in both types of experiments (Fig. 1a and 1a′).
This rise lasted from the outset of the cloud generation until its
evaporation, i.e. during the whole cloud event. Increases in SOA mass
concentrations for diphasic and triphasic experiments observed during cloud
events are presented in Table 3. During the first cloud of each experiment,
an increase in mass ranging from 3.9 to 8 µg m-3 was observed
for diphasic experiments, and from 4.3 to 7.2 µg m-3 for
triphasic experiments, which is more than 3 times higher than the increase
observed in control experiments (Table S1 in the Supplement). The additional SOA formation
observed in diphasic and triphasic experiments are called aqSOA formation
hereafter. In triphasic experiments, no direct link between mass
concentration levels of gasSOA prior to cloud generation and the maximum
value reached by aqSOA during cloud events was observed. The comparison of
triphasic and diphasic experiments shows that the observed increase in SOA
mass concentration was the same order of magnitude, suggesting that the
concentration, or even the initial presence of particulate phase (gasSOA),
had no significant influence on aqSOA formation. The comparison between
diphasic and triphasic experiments also suggests that the presence of a
reacting mixture that underwent more oxidation steps, and thus composed of
more oxidized compounds did not play a significant role in the amount of
aqSOA produced.
The SOA mass size distributions (Fig. 1b) show that, for the diphasic
experiment D300113, the mode of the distribution increased gradually during
the first cloud event, with a maximum mode around 225 nm just before cloud
evaporation. For the triphasic experiment T280113 (Fig. 1b′), the particle
size distribution of the gasSOA formed under dry conditions increased during
the first minute of the first cloud event, then a second mode, with larger
size, was formed. While the initial mode showed no significant variation in
size, the second mode increased in size gradually until reaching a diameter
of around 250 nm before cloud evaporation. A link between high oxidation
stage species and aqSOA formation cannot be highlighted in these experiments
due to the subsistence of the initial mode (corresponding to gasSOA) and the
systematic and reproducible formation of a second mode in all triphasic
experiments. The observation of such a growing second mode, called the
“droplet mode”, has been previously underscored during field observations
in the presence of water (Hering and Friedlander, 1982; John et al.,
1990; Meng and Seinfeld, 1994). This “droplet mode” is hypothesized to be
formed through volume-phase reactions in clouds and wet aerosols
(Ervens et al., 2011) and has been found to
be significantly enriched in highly oxidized organics, nitrates and
organosulfates (Ervens et al., 2011).
For the subsequent clouds, smaller increases in SOA mass (from 1.9 to 5.1 µg m-3
for diphasic experiments, and from 2.1 to 5.5 µg m-3 for triphasic experiments, as shown in Table 3) were observed. No link
between increases in SOA mass concentration and surface concentration of
cloud droplets was observed to explain this difference, so a smaller cloud
droplet size and/or lower water concentration was not the reason for these
reduced aqSOA increases. However, it could be due to shorter cloud lifetimes
after the initial cloud generation (Table 3) since aqSOA production stopped
immediately after cloud evaporation in all experiments.
After cloud evaporation, the mode diameter and concentration of the measured
distributions slowly decayed (Fig. 1a and a′). For diphasic experiments,
the gradual decrease in concentration lasted for 25 to 35 min before
reaching a plateau with a value of ca. 0.6 µg m-3, the same
order of magnitude to that observed in control experiments (Fig. S2). A
decay in SOA mass concentration was also observed after cloud evaporation
for triphasic experiments. This gradual decrease lasted for 20 min to 1 h
before reaching a stable SOA mass value close to the one observed before
cloud generation (T280113 and T130313) and to a value of around 0.5–1 µg m-3 for experiments with lower initial gasSOA mass
concentration (T160113 and T250313). This decrease in mass concentration was
explained by a slow decay of the second aerosol size mode which tended to
disappear when a stabilization of SOA mass concentrations was observed
(Fig. 1a′ and b′).
Figure 1b and 1b′ show that, for both types of experiments (diphasic and
triphasic systems), this slow decay in SOA mass observed after cloud
evaporation was due to the shrinkage of particles, and was not linked to a
direct particle wall-loss effect. It seems that this decay was due to wall
re-partitioning of the SVOCs formed during the cloud event. Recently, it has
been shown that losses of semi-volatile species to chamber walls could
affect SOA formation rates during photooxidation experiments, due to a
competition between condensation of SVOCs on the walls and on particles
(Loza et al., 2010; Matsunaga and Ziemann, 2010; Zhang et al., 2014).
SVOCs experience a continuous gas-wall partitioning in chambers, the extent
of this effect depending on the molecular structure of the compound, the
wall material and the experiment's organic loading, humidity and
temperature. If production of additional semi-volatile species occurs in the
droplet during cloud events, Henry's Law equilibrium suggests that these
species are isolated from the walls in the droplets. After cloud
dissipation, additional SOA mass is formed from these SVOCs which, at the
same time, also experience a re-partitioning between particles and the
walls. When the cloud is evaporated, since the available particle surface
area is around 400 times smaller than the geometric wall surface area, the
additional SOA mass decreases due to this equilibrium re-establishment under
humid conditions. Wall-loss kinetics data reported in the literature for a
Teflon chamber (Matsunaga and Ziemann, 2010) have led to a
characteristic time ranging from 1 h for non-polar species to 8 min
for carbonyls: these results are compatible with the rates of the decays
observed in our experiments (20 min to 1 h). Furthermore, pseudo-first
order rates for loss processes of organic compounds found in
Wang et al. (2011) suggest that similar wall-loss kinetics are expected in the CESAM chamber.
Assuming that this observed SOA mass decay is due to wall re-partitioning,
this process will not occur in the atmosphere, and aqSOA production can be
determined using the maximum mass concentration measured at the end of each
cloud event. In that case, aqSOA mass yield from isoprene photooxidation in
the presence of clouds would be between 0.002 and 0.004 considering our
results from the diphasic experiments, or between 2 and 4 times higher
than mass yields observed for isoprene photooxidation experiments carried
out under dry conditions with preliminary manual cleaning
(Brégonzio-Rozier et al., 2015). For
triphasic experiments, the observed increase of total SOA mass concentration
at the end of each cloud event was at least a factor of 2 compared to the
gasSOA mass concentrations reached under dry conditions prior cloud
formation. Hence, it can be assumed that a substantial aqSOA production was
observed in both types of experiments. Furthermore, the fact that additional
SOA mass was formed in the triphasic system (i.e. in the second mode) seems
to demonstrate that the role of cloud chemistry is not just to increase the
rate of gas-phase oxidation reactions but is adding new chemistry.
Dissolution and reactivity of gaseous species in cloud droplets
Time profiles of the gas phase reactants and isoprene oxidation
products during a diphasic experiment (D300113). Blue areas indicate cloud
events and hatched area indicate time needed for the PTR-ToF-MS signal to
stabilize after the start of cloud generation (droplet and memory effects in
the sampling line).
The time profiles of the gas phase reactants and oxidation products during a
diphasic experiment are shown in Fig. 2 (similar profiles were observed
for triphasic systems, see Fig. S3) in which two clouds were generated.
Ozone, NOx and HONO showed no significant change in their
concentrations during cloud events (Fig. 2b and c), with mixing ratios
remaining at around 5 ppbv for HONO and NO. The concentrations of isoprene,
the sum of MACR and MVK, acetone and C5H8O (compound that may be
attributed to 2-methylbut-3-enal,
Brégonzio-Rozier et al., 2015) also did
not seem to be influenced by cloud generation (Fig. 2a and f), as their
concentrations remained unchanged during cloud events. On the contrary, more
water soluble species (for example, methylglyoxal and formic acid) showed a
sharp decrease in their concentrations during cloud generation (Fig. 2d,
e, g and h). During each cloud event and for 20 additional minutes, the
PTR-ToF-MS signal was not used due to possible droplet impaction in the
heated sampling line. Using the concentrations of VOCs before each cloud
event (Cbefore) and 20 min after (Cafter), we calculated the gas
phase concentration changes during cloud events (ΔCcloud=Cbefore-Cafter, see Table 4). From these data, it can be noted
that the loss of the most water soluble VOCs (e.g. glycolaldehyde, acetic
acid, methylglyoxal, formic acid and hydroxyacetone) was significant during
the cloud events (between 32 and 52 %, see Table 4). Isoprene was
excluded from this calculation as its gas phase photochemical decay did not
seem to be affected by the cloud events.
Comparison between measured VOC loss, potential aqueous phase
dissolution of gas phase species and particle formation during cloud events
of each system.
Diphasic system
Triphasic system
D300113
D010213
T160113
T280113
ΔCclouda (µg m-3) and relative change (%)
KH∗ (M atm-1)
Reference
Isopreneg
0
0
0
0
3.4 × 10-2
Leng et al. (2013)
C4H6Og:
0
0
0
0
MACR MVK
9.5 18
Hilal et al. (2008) Hilal et al. (2008)
Acrolein
1.1 (19 %)
0.9 (16 %)
2.7 (41 %)
2.3 (30 %)
9.5
Hilal et al. (2008)
3-Methylfuran
1.7 (15 %)
1.7 (14 %)
0
0
6.1d
Hilal et al. (2008)
Acetaldehyde
1.3 (3 %)
0.7 (2 %)
4.3 (9 %)
5.6 (11 %)
13
Benkelberg et al. (1995)
Acetoneg
0
0
0
0
33
Poulain et al. (2010)
Formaldehyde
–
–
–
–
3.2 × 103
Staudinger and Roberts (1996)
Methylglyoxal
34.4 (49 %)
32.1 (49 %)
23 (52 %)
31.2 (42 %)
3.7 × 103
Betterton and Hoffmann (1988)
C2H4O2:
59.4 (37 %)
58.4 (36 %)
141.4 (46 %)
143.2 (35 %)
Acetic acidb Glycolaldehyde
4.6 × 103 4.1 × 104
Staudinger and Roberts (2001) Betterton and Hoffmann (1988)
Formic acidb
49.1 (41 %)
47.8 (38 %)
107.8 (49 %)
177.2 (48 %)
6.7 × 103
Staudinger and Roberts (2001)
Hydroxyacetone
15.4 (32 %)
18.2 (37 %)
32.1 (47 %)
26.3 (36 %)
7.8 × 103
Zhou et al. (2009)
C4H6O2 :
1.4 (7 %)
2.2 (11 %)
3.6 (26 %)
3.2 (18 %)
3-Oxobutanalc HydroxyMVKc
1.1 × 104 1.9 × 103
Estimated using GROMHE (Raventos-Duran et al., 2010)
C5H8Og: 2-Methylbut-3-enalc
0
0
0
0
27.1
Estimated using GROMHE (Raventos-Duran et al., 2010)
C5H6O2: 2-Methyl-but-2-enedialc
7.6 (41 %)
8 (39 %)
17.6 (55 %)
3.2 (36 %)
2.0 × 104
Estimated using GROMHE (Raventos-Duran et al., 2010)
C5H4O3c
4.6 (43 %)
5 (46 %)
8.2 (69 %)
3.2 (54 %)
≫ 104
–
Measured VOCs loss after cloud evaporatione (µg m-3)
176
175
341
395
Expected VOCs dissolution in water at cloud startf (µg m-3)
136
198
121
272
Maximum particle mass concentration enhancement measured during cloud event (µg m-3)
8.0
6.1
6.4
6.5
LWCmax first cloud (g m-3)
0.87
1.41
0.47
0.81
a ΔCcloud=Cbefore-Cafter. Cafter
corresponds to mixing ratios measured 20 min after cloud evaporation,
when the PTR-ToF-MS signal was stabilized for all compounds.
b The acids were considered undissociated.
c C4H6O2 was attributed to 3-oxobutanal and hydroxyMVK;
C5H8O and C5H6O2 were attributed to
2-methylbut-3-enal and 2-methyl-but-2-enedial respectively, and
C5H4O3 could not be attributed to any known isoprene product
(Brégonzio-Rozier et al., 2015).
d Effective Henry's Law constant of 3-methylfuran was assumed identical
to the one of 2-methyltetrahydrofuran.
e Total VOC loss (∑ΔCcloud) as measured by the
PTR-ToF-MS (excluding formaldehyde for which the strong humidity-dependent
sensitivity was not assessed) 20 min after cloud evaporation.
f Dissolution of VOCs is calculated assuming Henry's Law equilibrium at
cloud start (see Supplement Sect. S1). Formaldehyde cannot be accurately
quantified by PTR-MS under highly variable humidity conditions
(Warneke et al., 2011). As a result, formaldehyde mixing
ratios used for calculations were taken at low relative humidity, before
water vapour injection.
g These species were excluded from VOCs loss calculation as their decay
from gas phase chemistry did not sounded affected by the cloud events.
Following a hypothesis based on the kinetic determination of the
mass transport of VOCs from the gas phase to water droplets
(Schwartz, 1986), Henry's Law equilibrium was considered immediate at
the start of cloud generation. This hypothesis was used to estimate the
theoretical mass of individual VOCs transferred into the aqueous phase (see
Supplement Sect. S1). The estimation was done using the experimental data of
each gaseous VOC concentration prior cloud formation (Cbefore) and using the
measured LWC. The obtained values are summed and the total mass of VOCs
theoretically transferred to the aqueous phase is compared to the mass of
formed aqSOA in Table 4. It can be considered that the estimated transferred
mass represents a lower limit since this calculation only considers the
measured VOCs and thus neglects the contribution of other undetected VOCs
such as the organic nitrates or glyoxal (which should contribute to an
extent comparable to methylglyoxal or glycolaldehyde
(Galloway et al., 2011). However, this lower limit is
much higher than the maximum aerosol mass concentration increase observed
during cloud events by more than 1 order of magnitude. This result thus
suggests that, even if a small part of this dissolved organic matter (i.e.
less than 10 %) would react in the aqueous phase or at the surface of the
droplets during cloud events, leading to the formation of low volatile
species, this would explain the observed amount of aqSOA formed.
Table 4 shows that, for triphasic experiments, the measured VOC losses in
the gas phase during the cloud events (∑ΔCcloud) were between 1.5 and 3 times higher than the theoretical
quantity (Henry's Law equilibrium) transferred from the gas phase to the
droplets. This result suggests the following: (1) a reactive uptake of VOCs toward the
aqueous phase is taking place, shifting the Henry's Law equilibrium and
increasing the amount of VOCs transferred to the droplets, and (2) a large
part of this solubilized organic matter is transformed into semi-volatile
species on the time scale of the cloud event. This result implies a very fast
reactivity in the aqueous phase, which is in agreement with the observed
rapid aqSOA production.
SOA formation details and chemical composition
For both diphasic and triphasic systems, aqSOA production reached a value of
ca. 0.02 µg m-3 s-1 during the first 2 min of the cloud
event (Fig. S4). This value then decreased to approximately 0.005 µg m-3 s-1 until cloud dissipation. Keeping the hypothesis of an
instantaneous Henry's Law equilibrium, the highest aqSOA production
observed at the beginning of the cloud event is probably due to the
dissolution of the soluble species as 2 min is in the order of magnitude
of the mixing time in the CESAM chamber (ca. 100 s, Wang et al., 2011), while the second (lower)
production phase may be related to the shift of this equilibrium due to
possible reactivity in the aqueous phase.
Time profiles of (a and a') O / C, OM / OC and H / C ratios (with the
measurement uncertainty as determined by Aiken et al., 2008), and (b and b') particle density for diphasic (left panel) and
triphasic (right panel) experiments. Blue areas indicate cloud events.
In diphasic experiments, the brevity of the aqSOA formation, the small size
of these aerosols after cloud evaporation (a mass mode diameter of less than
100 nm) and a reduced collection efficiency for particles with a < 100 nm aerodynamic diameter in the HR-ToF-AMS, limit quantitative results.
The results for elemental ratios (O / C, H / C, and OM / OC) were hence restricted
to the first cloud event and around 10 min after, when the diameter mode
of the distribution was sufficiently high enough to achieve a reliable signal from
the HR-ToF-AMS. Temporal variation of elemental ratios and density for aqSOA
in diphasic and triphasic systems for the first cloud event are presented in
Fig. 3. Temporal evolutions of these elemental ratios for each system were
reproducible. A slight increase of O / C and OM / OC ratios was observed between
5 and 10 min after the first cloud generation, but these variations
remain insignificant considering the measurement uncertainties given by
Aiken et al. (2008). The average values of elemental
ratios in diphasic and triphasic systems (calculated using values obtained
during and after the first cloud event of each experiment) showed no
significant difference compared to the results obtained under dry conditions
(Table 5). We observed no change in the density, which remains at 1.40 ± 0.04 µg m-3 as under dry conditions
(Brégonzio-Rozier et al., 2015). The SOA
effective density was obtained by calculation based on the elemental
composition of aerosol from AMS measurements (Kuwata et al., 2012).
Average elemental ratios of SOA from isoprene photooxidation under
dry conditions and after cloud generation (diphasic and triphasic
experiments). Values in parentheses reflect the measurement uncertainty as
determined by Aiken et al. (2008).
O / C
OM / OC
H / C
Reference
0.58 (±0.18)
1.90 (±0.11)
1.45 (±0.15)
Diphasic experiments
0.58 (±0.18)
1.89 (±0.11)
1.39 (±0.14)
Triphasic experiments
0.60 (±0.19)
1.92 (±0.12)
1.43 (±0.14)
Dry conditions (Brégonzio-Rozier et al., 2015)
SOA chemical composition measured by an HR-ToF-AMS during a
triphasic experiment (T280113) (a) before, (b) during and (c) 30 min
after a cloud event. Right panels: mass spectra of dried aerosol averaged
over 10 min (organic fragments are in green, nitrate fragments in blue
and ammonium fragments in orange); Left panels: dried aerosol mass size
distributions.
To complete this SOA composition study, mass spectra and size distribution
measured before, during, and after cloud events in a typical triphasic
experiment are presented in Fig. 4. Comparison of the size distributions
in these various phases of the experiments shows the persistence of the
initial distribution of organic compounds (aerodynamic mode around 100 nm).
When maximum aqSOA mass concentration is reached (Fig. 4b), we note the
presence of a second mode (around 300 nm) corresponding to an aerosol
composed of organics, nitrates and mass fragments interpreted as ammonium.
The particle sizes and compositions observed for this second mode were very
similar to what was observed during cloud events for diphasic experiments
(Fig. S5). In triphasic experiments, the SOA composition, which was around
100 % organics before cloud generation (Fig. 4a), changed to a
composition of organics (39 %), nitrates (48 %) and ammonium (13 %)
during the cloud event (Fig. 4b).
The presence of ammonium fragments is difficult to explain and it must be
underlined that its contribution was close to the detection limits of the
AMS. In the gas phase, the corresponding NH3 contribution was far below
the detection limits of the gas phase analytical techniques (PTR-ToF-MS and
FTIR). NH3 contamination has been observed – and remained
unexplained – in a comparable simulation chamber (Bianchi et al.,
2012). By contrast, the presence of nitrates is in good agreement with field
observations (Dall'Osto et al., 2009; Giorio et al., 2015).
The presence of nitrates could be due to the transfer from the gas phase to
the aqueous phase of nitric acid and organonitrates formed by isoprene
photooxidation in the presence of NOx (Darer et al., 2011; Perring et
al., 2013), although no high-resolution organonitrate peaks were observed in
the HR-ToF-AMS data and the NO / NO2 mass peak ratios calculated from the
aerosol mass spectra, proposed to be used to ascertain whether the presence or
absence of organonitrates in HR-ToF-AMS data was the same as that of
inorganic nitrate (Farmer et al., 2010). Even if
organonitrates were present, their hydrolysis in the aqueous phase could
probably not explain the presence of nitrates as
Nguyen et al. (2012) showed that only less than 2 %
of organonitrates derived from isoprene + NOx undergo hydrolysis
within up to 4 h of reaction in the aqueous phase.
After cloud evaporation, a slow decrease of the second aerosol size mode was
observed (Fig. 4c), which can be linked to the aqSOA mass concentration
decay. Photolysis of particulate organonitrates was discarded as a possible
explanation for this decay because controlled experiments have been
performed by switching the light just after cloud evaporation: they lead to
the same observations. Hydrolysis of organonitrates cannot be totally
excluded. Nevertheless, although hydrolysis lifetimes of tertiary
organonitrates have been found to be in the range of a few minutes in diluted
solutions (Darer et al., 2011; Hu et al., 2011; Rindelaub et al., 2015),
as already mentioned, this process is likely slow and of small importance
for a complex mixture of SOA organonitrates derived from isoprene +
NOx (Nguyen et al., 2012). Furthermore, it is
expected that these nitrates lead to polyols (Darer et al.,
2011), which would preferentially remain in the particulate phase due to
their low vapour pressures (Compernolle and Müller,
2014). If polyols formation was observed in our experiments, we would have
observed a loss of nitrates, but not of the associated organic fragments,
which is not consistent with our observations (Fig. 4b and c). As a result,
it suggests that a chemical origin for the decay of the second mode (which
contains a large part of nitrates) is quite unlikely, and thus, that a
re-partitioning between particles and the walls is far more likely.
Atmospheric implications and conclusion
The impact of cloud events on an isoprene / NOx system in the presence of
light and at different oxidation stages was investigated in a stainless
steel simulation chamber. It was observed that a single and relatively short
cloud condensation cycle in the presence of irradiation led to a significant
aqSOA mass yield (0.002–0.004) with values between 2 and 4 times higher
than that observed for isoprene photooxidation experiments carried out
under dry conditions (Brégonzio-Rozier et
al., 2015). Even if no significant changes were noted in the SOA elemental
ratios, it appears that the bulk chemical aerosol composition was
significantly impacted by cloud events since an additional formation of
particulate matter containing organics, nitrate and ammonium fragments was
observed. This formed aqSOA seems to be metastable
in the simulation
chamber environment due to gas phase/wall repartitioning after cloud
dissipation. However, it can be assumed that in a real cloud, in the absence
of walls, the semi-volatile organic matter formed would remain in the
aerosol/hydrometeor phase due to re-condensation on pre-existing aerosol or
condensation/dissolution on the remaining droplets. Since clouds undergo
several evapo–condensation cycles in the atmosphere, this study highlights
the potentially great importance of cloud chemistry on the secondary aerosol
budget. This study also shows the complexity of working with a multiphase
system with cloud generation disturbing equilibria established in dry
conditions. However, as highlighted by Daumit et al. (2014) and the results
obtained in this study, it also shows the importance of investigating that
kind of systems, which is not only more realistic but also which is the only
way to experimentally study the competition between phase transfer, surface
reaction and homogeneous phase transformation.
Aqueous SOA formation was characterized by the appearance of a second mode that can be connected with the “droplet mode”, which has been previously
detected in the ambient atmosphere during early studies (Hering and
Friedlander, 1982; John et al., 1990; Meng and Seinfeld, 1994). Evidence was
obtained by John et al. (1990) that this growing second mode
grew out of the condensation mode by the addition of water and aqueous phase
oxidation products. Our experiment provided here a direct simulation of the
origin of a “droplet mode” in the atmospheric aerosol.
Finally, using the elemental ratios obtained in this study (Fig. 3), the
aqSOA carbon mass yields obtained in this study range between 0.002 to
0.004, which is 1 order of magnitude lower than those predicted by a
multiphase model performed on isoprene multiphase photochemistry under
comparable VOC(ppbC)/ NOx(ppb) ratios (Ervens et al.,
2008). However, the model was run using different initial conditions
compared to our experiments: much lower initial concentrations of isoprene
and NOx (by a factor of ∼ 103 and ∼ 100 respectively), pre-existing wet seed particles, and lower liquid water
content during cloud events were used in the model. The observed difference
between model and experimental results thus supports the great need for the
development of simulation chamber multiphase models in order to accurately
compare experimental results with the known multiphase photochemical
processes. Overall, our results emphasize the need to use the same
integrated multiphase approach on other chemical systems and to
integrate these results in atmospheric chemistry models to improve SOA
formation determinations.