Introduction
Atmospheric organic aerosol composition and mass concentrations are
transformed by atmospheric processes including oxidization (Dunlea et al.,
2009; Jimenez et al., 2009; Kroll et al., 2011), cloud processing (Ervens et
al., 2008, 2011; Zhao et al., 2013), and wet or dry deposition (Pöschl,
2005). Oxidation of organic aerosol impacts its lifetime, cloud droplet and
ice nucleation activity (Massoli et al., 2010; Lambe et al., 2011; China et
al., 2017), aerosol morphology, and optical properties (Pöschl, 2005;
China et al., 2015; Laskin et al., 2015 and references therein). As such, the
chemistry of atmospheric aerosol oxidation has received much attention
(George and Abbatt, 2010; Lee et al., 2011; Kroll et al., 2011). Jimenez et
al. (2009) studied the oxidation of anthropogenic organic aerosol emitted
from Mexico City as it was transported downwind. They used an aerosol mass
spectrometer (AMS) instrument on board an aircraft to measure the magnitude
of the m/z 44 fragment as a proxy for the oxidation of organic aerosol.
After 6 h and 63 km of transport, a noticeable increase in the overall
chemical oxidation was observed. Rapid oxidation was also observed in studies
of biomass burning organic aerosol in Africa (Capes et al., 2008; Vakkari et
al., 2014), over the Mediterranean Sea (Bougiatioti et al., 2014), and
Hyytiälä, Finland (Corrigan et al., 2013; Vogel et al., 2013). Other
studies focused on the oxidation of molecular tracers such as levoglucosan
have shown that they can be degraded rapidly after emission, depending on the
atmospheric conditions (Lai et al., 2014; Slade et al., 2014; Arrangio et
al., 2015; Bertrand et al., 2018). These studies all demonstrate the
importance of oxidation to the aging of organic aerosol and provide
motivation for studies of long-range-transported organic aerosol.
A study of predominately Asian anthropogenic aerosol transported in the free
troposphere over the Pacific Ocean found that the oxidation, inferred by the
average oxygen to carbon ratio (O/C), continued to increase over the
course of roughly a week (Dunlea et al., 2009). In a study of biomass burning
aerosol transported in the free troposphere across the North Atlantic Ocean,
Džepina et al. (2015) observed a relatively low O/C ratio (0.46±0.13), considering the aerosol transport time of more than 10 days
(Aiken et al., 2008). Džepina et al. (2015) hypothesized that cloud
processing and other oxidative processes led to the formation and subsequent
removal of oxidized species, leaving behind the more persistent aerosol
species. Other recent studies of long-range-transported brown carbon (BrC)
from biomass burning in the boundary layer found that the aging of aerosol
led to a near-complete depletion of BrC within 24 h (Forrister et al., 2015;
Laing et al., 2016). The remaining BrC was found to lead to a 6 %
increase in BrC over background levels and may represent the ubiquitous BrC
present in the atmosphere far from the source (Forrister et al., 2015). This
leftover BrC aerosol could impact large areas globally because much of it is
located within the free troposphere and above clouds, due to the typically
elevated injection heights of aerosol over wildfires (Val Martin et al.,
2008a). These studies indicate that free tropospheric aerosol chemistry is
particularly important because this aerosol can have a longer atmospheric
lifetime than boundary layer aerosol (Laing et al., 2016) allowing it to be
transported over greater distances.
Studies of transported biomass burning aerosol are typically performed using
instrumentation either on board aircraft (Capes et al., 2008) or located at
low altitude (Bougiatioti et al., 2014; Vakkari et al., 2014) and continental
mountain (Laing et al., 2016) sites. Aircraft measurements have the advantage
of sampling aerosol over wide spatial and altitudinal ranges, but they are
limited to short time periods, typically of a few days to a week (Capes et
al., 2008; Dunlea et al., 2009). Ground sites are less constricted by time,
but low-altitude sites are less often affected by pyro-convective wildfire
plumes due to the high injection heights of wildfires (Val Martin et al.,
2008a). Continental mountain sites typically have seasonally limited access
to the free troposphere, because high summer temperatures can lead to
convection of the planetary boundary layer (Collaud Coen et al., 2011). Thus,
many of the continental mountain sites have long-term access to the free
troposphere in the winter, but not in the summer when most wildfire activity
occurs. The Pico Mountain Observatory (PMO, see the Supplement for additional
information), is located 2225 m above sea level (a.s.l.) on the caldera
summit of Pico Mountain, on Pico Island in the Azores archipelago in the
North Atlantic. The marine boundary layer in the region has been measured and
is estimated to range from 500 to 2000 m a.s.l. in the summer months (Kleissl
et al., 2007; Remillard et al., 2012; Zhang et al., 2017), well below the
observatory. This permits access to free tropospheric long-range-transported
aerosol during the wildfire season. This, in conjunction with negligible
local emission sources, makes PMO an ideal site for the study of long-range-transported free tropospheric aerosol.
As described by Zhang et al. (2017), the Azores–Bermuda anticyclone causes
persistent downward mixing from the upper free troposphere and lower
stratosphere, and is the dominant meteorological pattern in this region, and
strengthens in the summer. The FLEXible PARTicle dispersion model (FLEXPART)
retroplumes discussed in Zhang et al. (2017) show that this site is most
commonly impacted by North American outflow (30 %–40 %). In the
summer months (June–August), 15 % of the intercepted air masses have a
North American anthropogenic influence, and 7.3 % have a wildfire
influence (Zhang et al., 2017). These factors make PMO an excellent site for
the study of North American outflow (Val Martin et al., 2008a). In many of
the previous studies at PMO, investigators focused on the North American
outflows of NOx, NOy, CH4,
non-methane hydrocarbons, and O3 gases (Val Martin et al., 2006,
2008a, b; Pfister et al., 2006; Helmig et al., 2015) as well as the physical
characteristics of black carbon and mineral dust aerosol and their ice
nucleation activity (Fialho et al., 2005; China et al., 2015, 2017). So far,
only Džepina et al. (2015) has looked at the aerosol chemical
and molecular characteristics of the organic aerosol collected at the site.
Recent environmental and laboratory studies have shown that under low
temperature and low relative humidity (conditions common in the free
troposphere), aerosol can be in a solid glassy phase (Zobrist et al., 2008;
Virtanen et al., 2010). This observation has been hypothesized to lead to
longer atmospheric lifetimes for organic species that are otherwise
susceptible to degradation through oxidative processes. As an example,
polycyclic aromatic hydrocarbons (PAHs) such as benzo[a]pyrene were observed
to have a much higher ambient concentration than what could be explained by
model simulations without considering the
aerosol phase state (Shrivastava et
al., 2017). Recently, PAHs have been shown to enhance the formation of a
viscous phase state in laboratory-generated secondary organic aerosol (SOA;
Zelenyuk et al., 2017). Since PAHs are common products of biomass burning and
anthropogenic emissions, the viscosity could be enhanced in ambient samples
as well, leading to a greater likelihood of the occurrence of solid-phase
aerosol. The solid phase can increase the resistance of aerosol to
photodegradation (Lignell et al., 2014; Hinks et al., 2015) and water
diffusivity (Berkemeier et al., 2014), and ozone reactions (Berkemeier et
al., 2016), which may lead to lower rates of oxidation. Shiraiwa and
colleagues developed a set of equations to predict the dry glass transition
temperature based on the mass and O/C ratio of organic aerosol
components (Shiraiwa et al., 2017; DeRieux et al., 2018). Thus, the phase
state of molecular species with respect to ambient conditions can be
predicted using the Gordon–Taylor equation (Shiraiwa et al., 2017; DeRieux
et al., 2018). Additionally, estimation methods to determine the volatility
of organic aerosol were reported by Donahue et al. (2011) and Li et
al. (2016). Both the phase state and volatility are important in
understanding the processes that affect aerosol during transport and aging.
The low oxidation observed by Džepina et al. (2015) was attributed to the
dominance of persistent aerosol that resisted removal mechanisms; however, it
is possible that the phase state of the aerosol during transport played a
significant role. The increased resistance to photodegradation (Lignell et
al., 2014; Hinks et al., 2015) and water diffusivity (Berkemeier et al.,
2014) of solid-phase organic aerosol provide a basis for this hypothesis.
Ultrahigh-resolution mass spectrometry (MS) is a necessary tool for
determining the molecular characteristics of complex mixtures such as organic
aerosol. It has been used to analyze dissolved organic matter (Kido-Soule et
al., 2010; Herzsprung et al., 2014), cloud water (Zhao et al., 2013; Cook et
al., 2017), fog water (Mazzoleni et al., 2010), sea spray (Schmitt-Kopplin et
al., 2012), and organic aerosol (Walser et al., 2007; Mazzoleni et al.,
2012; O'Brien et al., 2013; Wozniak et al., 2014; Džepina et al., 2015).
Ultrahigh-resolution MS techniques are typically paired with electrospray
ionization (ESI) because it is a soft ionization technique with little to no
fragmentation of the molecular species being analyzed. Negative mode ESI is
sensitive to molecules with acidic functional groups, which is ideal for the
analysis of long-range-transported organic aerosol due to its generally
acidic nature (Bougiatioti et al., 2016). The ultrahigh mass resolution
available from Fourier transform ion cyclotron resonance MS (FT-ICR MS) and
the high-field Orbitrap Elite MS instruments (R=240000) separates
sulfur-containing species from carbon-, hydrogen-, and oxygen-containing
species (Schmitt-Kopplin et al., 2010), which is important because
sulfur-containing species are common in atmospheric aerosol (Schmitt-Kopplin
et al., 2010; Mazzoleni et al., 2012; Džepina et al., 2015).
The observations of Džepina et al. (2015) raised interesting questions
regarding the nature of long-range-transported free tropospheric aerosol. To
further elucidate the detailed molecular characteristics of free tropospheric
aerosol, we analyzed three pollution events using ultrahigh-resolution FT-ICR
MS. We observed key molecular differences pertaining to the extent of
oxidation likely related to the combination of transport pathways and their
apparent emission sources. In this paper, we present the detailed molecular
characteristics of organic aerosol collected at PMO and use the aerosol
chemical composition, FLEXPART model simulations, and physical property
estimates to interpret those characteristics and infer implications for
long-range-transported organic aerosol.
Methods
Sample collection
PM2.5 samples were collected at PMO on 8.5×10 in. quartz fiber
filters using high-volume air samplers (EcoTech HiVol 3000, Warren, RI, USA)
operated at an average volumetric flow rate of 84 m3 h-1 for
24 h. Prior to sampling, the filters were wrapped in clean, heavy-duty
aluminum foil and baked at 500 ∘C for ∼8 h to remove organic
artifacts associated with the filters. Afterward, they were placed in
antistatic sealable bags until deployment. We deployed four air samplers at
the site, each was simultaneously set up with a filter and programmed to
start one day after another, allowing for continuous sample collection for up
to 4 consecutive days. This procedure was used to maximize the number of
filters collected. Daily visits and maintenance were limited by the
time-consuming and strenuous hike necessary to reach the site. The sampled filters
were removed and returned to the same aluminum wrapper and bag. The samples
were then brought down the mountain and stored in a freezer until cold
transport back to Michigan Technological University where they were stored in a freezer until
analysis. Three samples, collected in consecutive years at PMO, on
27–28 June 2013, 5–6 July 2014, and 20–21 June 2015 were analyzed in this
study. The sampling time for all samples was 24 h; on 27–28 June the
sampling began at 19:00 LT, on 5–6 July and on 20–21 June the sampling began
at 15:00 LT, all local times.
Chemical analyses
Organic carbon and elemental carbon (OC/EC) measurements were
performed using an OC/EC analyzer (Model 4, Sunset Laboratory Inc.
Tigard, OR, USA) following the NIOSH protocol. Major anions and cations were
analyzed using ion chromatography. Anion analysis was performed using a
Dionex ICS-2100 instrument (Thermo Scientific) with an AS-17-C analytical and
guard column set (Thermo Scientific) using a KOH generator for gradient
elution. Cation analysis was performed using a Dionex ICS-1100 instrument
with CS-12A analytical and guard column set (Thermo Scientific) and an
isocratic 20 mM methanesulfonic acid eluent. The instruments were operated
in parallel using split flow from the autosampler. Additional details can be
found in the Supplement.
Ultrahigh-resolution FT-ICR mass spectrometry analysis
The samples for FT-ICR MS analysis were selected based on the organic carbon
concentration. Selected samples typically had more than 1000 µg of
organic carbon per quartz filter. Sample preparation was described in detail
in previous studies from our group (Mazzoleni et al., 2010, 2012; Zhao et
al., 2013; Džepina et al., 2015). Briefly, one-quarter of the quartz
filter was cut into strips, placed in a pre-washed and baked 40 mL glass
vial, and then extracted using ultrasonic agitation in an Optima
with deionized water of LC/MS grade (Fisher Scientific, Waltham, MA, USA) for 30 min. The
extract was then filtered using a pre-baked quartz filter syringe to remove
undissolved material and quartz filter fragments. The sample filter was then
sonicated again in 10 mL of Optima LC/MS-grade deionized water for 30 min,
filtered, and then added to the original 30 mL of filtrate yielding a total
of 40 mL. Ice packs were used during the sonication to ensure the water
temperature stayed below 25 ∘C. The water-soluble organic carbon
(WSOC) compounds were then isolated using Strata-X (Phenomenex, Torrance, CA,
USA) reversed phase solid-phase extraction (SPE) cartridges to remove inorganic salts that can adduct with
organic compounds during electrospray ionization. During the reversed phase
SPE, losses of highly water soluble, low molecular weight (MW) organic
compounds, and hydrophobic, high-MW organic compounds are expected. Thus, the
resulting WSOC is the SPE-recovered fraction. The cartridges were
pre-conditioned with acetonitrile and water of LC/MS grade before the 40 mL
filtrate was applied to the cartridges at a rate of ∼1 mL min-1.
The cartridges were eluted with 2 mL of an aqueous acetonitrile solution
(90/10 acetonitrile/water by volume) and stored in the freezer until
analysis. The procedural loss of ionic low-MW compounds such as oxalate can
lead to an underprediction of the organic aerosol O/C ratio and
overprediction of the average glass transition temperatures (Tg).
To investigate this, we used the concentrations of the prominent organic
anions measured with ion chromatography to estimate the abundance of these
compound relative to the compounds detected by FT-ICR MS. The low-MW organic
anion-corrected average O/C values correlated with the trends of the
original O/C values; however, the significance of the impact varies
with the measured analyte concentrations and the assumptions associated with
the uncertain mass fraction of the molecular formula composition
(Supplement Table S4). When low-MW organic anions were included in the
estimated average dry Tg values, they dropped by ≤2.5 %,
which was deemed relatively insignificant (Table S5).
Ultrahigh-resolution mass spectrometric analysis was done using FT-ICR MS
with ESI at the Woods Hole Oceanographic Institution (Thermo Scientific LTQ
Ultra). The samples were analyzed using direct infusion ESI in the negative
ion mode. Negative polarity is effective for the deprotonation of polar
organic molecules (Mazzoleni et al., 2010), which are expected to dominate
the organic aerosol mass fraction and were the focus of this study. The spray
voltage ranged from 3.15 to 3.40 kV depending on the ionization stability
with a sample flow rate of 4 to 5 µL min-1. We used a scan
range of m/z 100–1000 with a mass resolving power of 400 000 (defined at
m/z 400) for all samples. The samples were run in duplicate and
200 transient scans were collected. The transients were co-added for each
replicate run using the MIDAS Coadd tool and molecular formula assignments
were made using the Composer software (Sierra Analytics), as described in
previous studies (Mazzoleni et al., 2012; Džepina et al., 2015). The
resulting molecular formula assignments underwent additional quality
assurance (QA) data filtering to remove chemically unreasonable formulas with
respect to O/C, hydrogen to carbon ratio (H/C), double bond
equivalent (DBE), and absolute ppm error as described in the supplemental information of Putman et al. (2012).
Molecular formulas in common with the instrument blanks with signal intensity
ratios < 3 were removed; meanwhile, analytes in common with the
field blanks with signal intensity ratios < 3 were flagged.
Specifically, two formulas (C17H34O4 and
C19H38O4) observed in PMO-1 could not be classified as
pertaining only to the field blank and so they were not removed. Further
discussion about the blank subtraction is provided in the Supplement. To
produce the final data set for each sample, the replicates were aligned and
only the molecular formulas found in both replicates after QA were retained.
FLEXPART numerical simulations
FLEXPART was used to determine the sources, ages, and transport pathways of
the aerosol samples collected at PMO. FLEXPART backward simulations (also
called retroplumes) were driven by meteorology fields from the Global
Forecast System (GFS) and its “Final Analysis” with 3 h temporal
resolution, 1∘ horizontal resolution, and 26 vertical levels. The
output was saved in a grid with a horizontal resolution of 1∘
latitude by 1∘ longitude, and 11 vertical levels from the surface to
15 000 m a.s.l. For each simulation, Eighty thousand air parcels were
released from the receptor and transported backwards for 20 days to calculate
a source–receptor relationship (in units of s kg-1; Seibert and Frank,
2004). FLEXPART retroplumes were then multiplied with CO emission inventories
(kg s-1) from the Emissions Database for Global Atmospheric Research
(EDGAR version 3.2; Olivier and Berdowski, 2001) and the Global Fire
Assimilation System (Kaiser et al., 2012) to estimate the influence from
anthropogenic and wildfire sources, respectively. The FLEXPART CO tracer
calculated with this approach indicates the relative contributions from
anthropogenic and biomass burning emissions. Since CO chemistry and dry
deposition are not considered in the FLEXPART setup, the absolute FLEXPART CO
value does not reproduce the actual CO concentrations at Pico. FLEXPART does
not consider the background CO accumulated in the atmosphere. The difference
between FLEXPART CO and the actual CO largely depends on these factors. In
previous applications of this approach, FLEXPART CO was able to estimate the
episodes of CO enhancement due to transport of emissions (e.g., Brown et al.,
2009; Stohl et al., 2007; Warneke et al., 2009). This approach has been used
in several PMO studies and successfully captured elevated CO periods (e.g.,
Džepina et al., 2015; Zhang et al., 2014, 2017) and it is used here to
assist in the interpretation of the chemical composition in this work.
FLEXPART retroplumes for 28 June 2013 06:00 LT (PMO-1, a, d), 6 July 2014 03:00 LT (PMO-2, b, e), and 21 June 2015 03:00 LT (PMO-3, c, f): column-integrated residence time over the 20-day transport time (a–c) and
vertical distribution of the retroplume residence time at given upwind times
(d–f). The labels indicate the approximate locations of the center of the
plume for each of the transport days. Residence time is color coded by
logarithmic grades representing its ratio to the location of maximal
integrated residence time (100 %). The black lines in (d)–(f) indicate the mean
height of the plume during transport.
In addition to the typical FLEXPART simulations done for the site (e.g.,
retroplume, CO source apportionment), we extracted the ambient temperature
and relative humidity (RH) from the GFS analysis data for model grids along
the FLEXPART simulated transport pathways. These parameters were then used to
estimate the glass transition temperatures (Tg) of the organic
aerosol components during transport, based on its molecular composition from
ultrahigh-resolution MS, using estimation methods recently developed by
Shiraiwa et al. (2017) and extended to higher masses by DeRieux et
al. (2018). DeRieux et al. (2018) reported an uncertainty of ±21 K for
the prediction of any single compound, but the uncertainty is expected to
decrease when a mixture of compounds is considered. Nonetheless, we assumed
an uncertainty range of ±21 K on Tg and found that it did
not significantly change the Tg trends presented in Sect. 3.5.
Further discussion on the uncertainty in Tg is provided in the
Supplement. The distributions of the estimated organic aerosol component
Tg values provides new insight for the interpretation of
long-range-transported aerosol.
Average concentrations (µg m-3) of major ions and
organic carbon.
Component
PMO-1
PMO-2
PMO-3
Acetate
0.0519±0.0001
0.004587±0.000005
0.0071±0.0002
Formate
0.0289±0.0003
0.00438±0.00007
0.0119±0.0001
MSA
0
0.00439±0.00006
0.00232±0.00002
Chloride
0.0104±0.0003
0
0.0310±0.0001
Nitrate
0.189±0.002
0.0173±0.0004
0.3010±0.00028
Sulfate
0.338±0.004
1.07±0.01
0.421±0.003
Oxalate
0.0938±0.00070
0.0897±0.00181
0.05222±0.00002
Sodium
0.2101±0.0004a
0.2560±0.0001a
0.548±0.005a
Ammonium
0.1364±0.0004
0.2394±0.00001
0.1193±0.00062
Potassium
0.0791±0.0020b
0.0126±0.0002
0.0197±0.0003
OC
2.07±0.02
0.478±0.026
0.87±0.10
a Sodium concentrations were not background subtracted due to inconsistent
and high blank levels, they are included to provide an upper limit on the
approximate sodium concentrations.
b Replicate measurements of potassium were inconsistent. The sample could
not be re-analyzed because there was no remaining sample. Standard deviation
was determined by looking at the average standard deviation of 36 potassium
measurements in other samples. This sample should only be considered as
elevated potassium and only minimal importance placed on the actual measured
value.
Results and discussion
Overview of the aerosol chemistry: OC/EC and IC
In this study, we present the detailed composition of three individual
samples collected for 24 h on 27–28 June 2013, 5–6 July 2014, and
20–21 June 2015 at the PMO. These samples, referred to as PMO-1, PMO-2, and
PMO-3, respectively, hereafter, were selected after analysis of organic and elemental carbon
(OC/EC) were performed for all 127 aerosol samples collected in this
study. The three selected samples all had elevated organic carbon (OC)
concentrations (Table 1) representing the capture of a pollution plume. After
blank subtraction, the median OC of the samples collected over the summers of
2013–2015 was 0.16±0.018 µg m-3. The minimum OC level
measured was below the average blank concentration and the maximum was 2.07±0.017 µg m-3 (PMO-1). The most abundant anions and
cations in these samples are also shown in Table 1. The presence of these
ions is consistent with the results of other studies (Yu et al., 2005;
Aggarwal and Kawamura, 2009). Further discussion of the bulk chemical trends
will be presented in a future manuscript.
The concentrations of common anions and cations can offer important insight
regarding cloud processing and emission sources (Table 1). Specifically, the
elevated level of sulfate observed in the PMO-2 sample can be an indicator of
anthropogenic influence, cloud processing, or marine influence (Yu et al.,
2005). We also observed elevated oxalate concentrations in PMO-1 and PMO-2.
Oxalate is known to co-vary with sulfate concentrations in the atmosphere
when they are formed by aerosol–cloud processing (Yu et al., 2005; Sorooshian
et al., 2007). Thus, the oxalate to sulfate ratio can be an indication of
cloud processing (Sorooshian et al., 2007); in general, a higher ratio is the
result of increased cloud processing. As described in Sorooshian et
al. (2007), the oxalate concentrations increase with cloud processing because
there is more time for it to be produced, leading to an increased ratio.
PMO-1 had the highest oxalate to sulfate ratio (0.278), followed by PMO-3
(0.124), and PMO-2 (0.084). The observed oxalate to sulfate ratios for these
samples are all much higher than what was reported in Sorooshian et
al. (2007) suggesting other factors may have impacted the ion concentrations.
Specifically, an enrichment of oxalate from biomass combustion plumes (Cao et
al., 2017) likely contributed to the observed concentrations of these ions in
PMO-1 and PMO-3. The bulk concentration of oxalate in PMO-2 is similar to
PMO-1, but the sulfate in PMO-2 is much higher, leading to a low oxalate to
sulfate ratio. Based on FLEXPART simulations it is likely that PMO-2
underwent aqueous-phase processing (see Sect. 3.5), but the high
concentration of sulfate from possible anthropogenic and marine sources
appears to have obscured the oxalate–sulfate relationship (Yu et al., 2005;
Sorooshian et al., 2007).
Reconstructed negative ion mass spectra (a–c) and
O/C histograms (d–f) for the three PMO samples. The color in the mass
spectra indicates the O/C value for the molecular formula it
represents. The tallest peaks in the mass spectra in (b) and (c) exceed the range, this was
done to improve the visibility of the lower abundance species (see also
Fig. S6).
Despite inconsistencies in the replicate potassium measurements for PMO-1,
elevated potassium levels were observed, indicating contributions from
biomass combustion (Duan et al., 2004). PMO-3 had slightly elevated
potassium relative to PMO-2, but not as high as PMO-1. Chloride was also
present in PMO-1 and PMO-3, which has been shown in some studies to be a
minor product of biomass burning, depending on the fuel burned (Levin et
al., 2010; Liu et al., 2017).
The nitrate levels in PMO-2 were significantly lower than what was observed
in PMO-1 and PMO-3, which is consistent with the observation that the marine
boundary layer promotes the rapid removal of HNO3 (Val Martin et
al., 2008b). This is also consistent with removal due to cloud scavenging
(Dunlea et al., 2009). The elevated nitrate in PMO-1 and PMO-3 is consistent
with the observation of elevated NOy and
NOx in the plumes of wildfire emissions made in previous
studies at PMO (Val Martin et al., 2008a) and a lack of recent cloud
scavenging (Dunlea et al., 2009).
Despite the low-altitude transport, the major ion concentrations in PMO-2 do
not strongly support a major influence from marine sources (Quinn et al.,
2015; Kirpes et al., 2018). However, the increased concentration of methane
sulfonic acid (MSA) in PMO-2 relative to PMO-1 and PMO-3 suggests some degree
of marine influence. To estimate this, we used the non-background subtracted
sodium concentration as an upper limit to estimate sea salt sulfate according
to the method described in Chow et al. (2015), this led to a maximum sea salt
sulfate contribution of 25 %. The influence of marine sources supports
boundary layer transport. However, the results indicate that marine aerosol
is not likely a major component of PMO-2, perhaps because the rate of PMO-2
transport was very fast.
FLEXPART retroplume simulation results
Representative FLEXPART retroplumes for the three samples are shown in
Fig. 1, additional time periods are in the Supplement (Figs. S1–S3). PMO-1 was largely influenced by North American outflow
transported relatively high in the free troposphere. Based on the FLEXPART
carbon monoxide (CO) modeling (Fig. S4 in the Supplement), PMO-1 was impacted by wildfire
emissions from Canada. The transport time for PMO-1 air masses from North
America to PMO was about 7 days. The free tropospheric transport is likely
due to the high injection heights (Val Martin et al., 2008a, 2010) of organic
aerosol from wildfire events in northwestern Quebec (see Figs. S4, S5).
Similar events at PMO have been previously identified by (Val Martin et al.,
2006, 2008a). The air masses intercepted during PMO-3 were North American
outflows that traveled in the lower free troposphere across the Northern
Atlantic Ocean to western Europe before circling back to PMO. The transport
time for the PMO-3 air masses from North America to PMO was roughly 10 days.
After a northward transport to western Europe in the jet stream during the
first 4–5 days, the simulated plume turned to the south and west, arriving
at PMO from Europe in about 2–4 days. This air mass was most likely
influenced by wildfire emissions in western and central Canada (US Air
Quality, Smog Blog, http://alg.umbc.edu; last access: 9 January 2018). Similar to PMO-1, FLEXPART CO source
apportionment (Fig. S4) suggests this sample was influenced by fire, although
considering the OC concentration and transport time, it was much more diluted
than what was observed in PMO-1. In contrast, the PMO-2 air masses traveled
relatively low (≤2 km) over the “Rust Belt” (Illinois, Indiana,
Michigan, Ohio, Pennsylvania, and New York) of the United States and stayed
at approximately the same altitude until it reached the observatory 2–4 days
later. This transport pattern suggests that the aerosol was predominantly
transported in the boundary layer on its way to the PMO and was primarily
influenced by a mixture of continental US anthropogenic and biogenic
emissions. This was supported by the FLEXPART CO simulations as well
(Fig. S4). The height of the boundary layer over the continent generally
ranges from 500 to 2500 m and is strongly affected by diurnal cycles, seasonal
effects, and topography (Liu and Liang, 2010); overall, the continental
boundary layer height generally increases during the day and during the
summer months. This suggests that PMO-2 was within the boundary layer over
the United States.
Van Krevelen plots for the CHNO species with all
identified CHNO species (gray) and unique species (colored). The color
represents the number of double bond equivalents (DBEs) in the corresponding
molecular formula. The diagonal line is an oxidation line (OSC=0 for C, H, O elements; Tu et al., 2016), where the more oxidized
formulas are on the right side and less oxidized are on the left.
Molecular formula oxidation metrics: O/C and OSC
In this section, we describe the detailed molecular formula composition of
the three individual samples: PMO-1, PMO-2, and PMO-3. Overall, nearly 80%
of the observed mass spectral peaks in the ultrahigh-resolution mass spectra
were assigned molecular formulas, which is comparable to previous studies
(Zhao et al., 2013; Džepina et al., 2015). After removing the duplicate
molecular formulas containing 13C or 34S, a total of 3168
(PMO-1), 2121 (PMO-2), and 1820 (PMO-3) monoisotopic molecular formulas
remained. Groups of molecular formulas were assigned based on their elemental
composition CcHhNnOoSs, including: carbon, hydrogen,
and oxygen (CHO); carbon, hydrogen, nitrogen, and oxygen (CHNO); and carbon,
hydrogen, oxygen, and sulfur (CHOS). The most frequently observed
compositions were CHO and CHNO. The reconstructed negative ion mass spectra
of the monoisotopic molecular formulas for each of the samples are provided
in Fig. 2. Visual comparisons of the mass spectra indicate that PMO-2, which
was likely transported through the North American continental and North
Atlantic marine boundary layer, has an increased prevalence of higher
O/C ratio formulas compared to the two samples transported through the
free troposphere. Considering the ion distribution and normalized relative
abundances, PMO-1 and PMO-3 mass spectra look quite similar with a high
frequency of individual O/C values < 0.5. This may suggest
similar emission sources or aerosol processing. In contrast, PMO-2 has a
stronger relative influence of molecular compositions with higher O/C
ratios. The O/C histogram plots in Fig. 2 provide additional evidence
for the O/C differences between the two types of samples (free
troposphere and boundary layer) due to the difference in the O/C
distribution.
Molecular formula composition with abundance-weighted
average values and the numbers of formulas for each elemental group.
Sample
Group
O/Cw
H/Cw
DBEw
OSCw
Number
PMO-1
All
0.48±0.13
1.30±0.28
7.74±3.38
-0.42±0.43
3168
PMO-2
All
0.57±0.17
1.36±0.22
6.42±2.54
-0.30±0.46
2121
PMO-3
All
0.45±0.11
1.34±0.41
7.45±3.15
-0.50±0.41
1820
PMO-1
CHO
0.47±0.14
1.31±0.29
7.43±3.68
-0.37±0.44
1848
PMO-2
CHO
0.55±0.17
1.35±0.25
6.43±3.66
-0.26±0.45
1281
PMO-3
CHO
0.44±0.14
1.37±0.31
6.93±3.82
-0.48±0.48
1183
PMO-1
CHNO
0.49±0.15
1.2±0.26
9.44±3.09
-0.50±0.3
1120
PMO-2
CHNO
0.59±0.14
1.25±0.19
8.20±2.19
-0.38±0.29
561
PMO-3
CHNO
0.49±0.14
1.23±0.21
9.25±2.41
-0.52±0.25
608
PMO-1
CHOS
0.48±0.14
1.78±0.35
2.87±3.28
-1.20±0.42
200
PMO-2
CHOS
0.74±0.34
1.57±0.23
4.05±2.45
-0.54±0.51
274
PMO-3
CHOS
0.40±14
1.90±0.47
1.60±4.29
-1.50±0.20
29
The North American boundary layer outflow of organic aerosol captured in
PMO-2 was likely influenced by SOA (Zhang et al., 2007) and thus is expected
to have a higher initial O/C value compared to pyro-convected wildfire
emissions of organic aerosol (e.g., Aiken et al., 2008; Jimenez et al., 2009;
Bougiatioti et al., 2014). Although the initial compositions are unknown, we
anticipated that the samples with longer transport times (∼1 week for
PMO-1 and PMO-3) would be at least similar or perhaps more oxidized than
PMO-2, which had a much shorter transport time (∼3 days). This
expectation was based on literature describing SOA formation and aging
(Volkamer et al., 2006; Jimenez et al., 2009) and the reported molecular
composition of continental boundary layer aerosol (Mazzoleni et al., 2012;
Huang et al., 2014). The lower oxidation observed in the free tropospheric
samples transported for 7–10 days is consistent with our previous study at
this site reported in Džepina et al. (2015). In fact, when we compared
the molecular formula composition of the free tropospheric aerosol sample
“9/24” from Džepina et al. (2015) to the free tropospheric samples in
this study (PMO-1 and PMO-3), we observed that 86 % and 91 % of the
molecular formulas are in common. FLEXPART simulations from both studies
indicated these samples were all affected by wildfire emissions, contributing
to their similarity. In contrast, only 75 % of the formulas found in the
boundary layer sample (PMO-2) were common with those in Džepina et
al. (2015). These comparisons are provided in Table S2.
As observed in the mass spectra and histograms presented in Fig. 2, the
samples have noticeable differences in the distribution of O/C values.
This is also reflected in the abundance-weighted mean O/C values for
the samples: 0.48±0.13 (PMO-1), 0.57±0.17 (PMO-2), and 0.45±0.11 (PMO-3). Note that these O/C values are averages of thousands of
individual measurements, as such the standard deviation represents the range
of values and not uncertainties (see Figs. S7–S8 for violin plots of the
distributions). We also note that the relative abundance of compounds in ESI
mass spectra is not directly proportional to their solution concentration,
other factors including surface activity and polarity impact the ionization
efficiency (Cech and Enke, 2001). Nonetheless, the abundance does
differentiate trends between the samples and the assigned molecular formulas
which likely represent a collection of multifunctional isomers (e.g., LeClair et al.,
2012). For completeness, both the abundance-weighted average values for
various metrics of aerosol oxidation and saturation (Table 2) and the
unweighted average values (Table S3) are reported. Additional O/C
distribution insight was derived from separating the species into CHO, CHNO,
and CHOS elemental groups. For example, the comparison of the species with CHO
formulas in each sample indicates a smaller relative difference between PMO-2
aerosol compared to PMO-1 and PMO-3, with the PMO-2 aerosol having a higher
average O/C value (0.55±0.17, PMO-2, compared to 0.47±0.14, PMO-1, and 0.44±0.14, PMO-3).
Meanwhile 85 %–98 % of the CHO
species in each sample are present in at least one other sample, with 848
(42 –78 %) of the formulas being found in all three samples, as shown
in Fig. S9. This suggests that the CHO composition may be fairly uniform
throughout the atmosphere, without a significant abundance of clear marker
species after long-range transport, regardless of the source region and
transport time. This observation is consistent with other studies which have
observed the decay of marker species after ∼24 h (Bougiatioti et al.,
2014; Forrister et al., 2015).
Average OSC vs. carbon number plots for
molecular formula identified in each of PMO samples (a–c). The size of the
symbols is scaled to the analyte relative abundance and the color represents
the elemental group: CHO (green), CHNO (blue), and CHOS (red). The right
panels (d–f) contain average OSC histograms based on the sum of
normalized abundance.
In contrast, the CHNO molecular formulas demonstrate stronger differences
that correlate with the overall O/C ratio. The average O/C
value for the CHNO formulas in PMO-2 was 0.59±0.14 compared to 0.49±0.15 in PMO-1 and 0.49±0.14 in PMO-3 (Table 2). Differences in the
elemental ratios are often visualized using the van Krevelen plot, which
shows the correlation of H/C vs. O/C. The van Krevelen plots
for the three samples with the unique CHNO formulas present in each sample
are shown in Fig. 3. Most of the unique CHNO species in PMO-2 (68 %) fall
in the more oxidized region of the plot (Tu et al., 2016) with high overall
O/C values. This differs from the PMO-1 unique species that are
predominantly on the less oxidized, low O/C side of the plot, or the
oxidized aromatic region. Another observation from the CHNO species is more
identified species in both PMO-1 (1120) and PMO-3 (608) than in PMO-2 (561),
despite the higher total number of molecular species in PMO-2 compared to
PMO-3. This is potentially due to the enrichment of NOx and
NOy species as previously observed in wildfire pollution
events (Val Martin et al., 2008a), which may in turn lead to an increased
nitrogen content in the organic aerosol species. The nitrogen-containing
species show a distinct difference in terms of the total oxidation between
the two sets of samples, more so than the CHO compounds. This implies that
much of the distinction between aerosol sources may come from heteroatom-containing species.
The difference in O/C is even more evident in the sulfur-containing formulas (CHOS). The PMO-2 CHOS species have a much higher average O/C
ratio (0.74±0.34) than what is observed in PMO-1 (0.48±0.14).
Consistent with the CHNO formulas, the PMO-2 unique CHOS formulas (55 %
of unique formulas) are present in the oxidized region of the plot, whereas
those in PMO-1 are nearly completely in the less oxidized region of the van
Krevelen plot (Fig. S10). The Kendrick plot (Fig. S10c) also demonstrates a
clear difference between the two samples. Most of the unique CHOS compounds
in PMO-2 are located on the lower mass, higher defect side of the plot, while
the PMO-1 formulas are on the higher mass, lower defect side. This difference
is due to the larger amount of oxygen present in the PMO-2 formulas, which
would lead to a greater mass defect than the more reduced CHOS formulas
present in PMO-1. Higher oxygen content of PMO-2 aerosol is supported by its
higher O/C ratio when compared to PMO-1 as shown in box plots
(Fig. S10d). Very few CHOS molecular formulas (N=29) were identified in
PMO-3 and most of them (N = 26 of 29 total) were also present in PMO-1. Due
to the small number of identified CHOS formulas in PMO-3, we did not consider
it in the comparison between CHOS formulas in the samples. The increased
number of sulfur species observed in PMO-2 are likely associated with the
anthropogenic emission sources in the North American boundary layer. Overall,
the observed differences in the O/C ratios between the boundary layer
transported aerosol (PMO-2) compared to the free troposphere transported
aerosol (PMO-1 and PMO-3) highlight differences in the aging and lifetime of
aerosol relative to its transport pathway and emission source.
Another commonly used metric of aerosol oxidation is the average oxidation
state of carbon (OSC) described by Kroll et al. (2011). The
average OSC includes both hydrogen and oxygen for the average
oxidation of carbon in each molecular formula. Additionally, we assumed all
nitrogen and sulfur were present as nitrate and sulfate functional groups and
calculated the OSC with the appropriate corrections (Eq. S1 in
the Supplement). The average OSC values (Table 2) for the three
samples show again that PMO-2 is more oxidized than the other two samples.
The average OSC values for the CHO formulas in PMO-1 and PMO-2
are very similar (Table 2), but as shown in the histograms in Fig. 4, their
relative abundance distributions are quite different. The OSC vs.
carbon number plots in Fig. 4 show slight differences between PMO-1 and
PMO-2, mostly in the distribution of the sulfur-containing formulas. However,
the similarity of the PMO-1 and PMO-3 samples and their difference from the
PMO-2 sample is quite clear in the visual comparisons of the histograms of
the OSC values with their normalized relative abundances. The
observation of an overall lower oxidation in PMO-1 and PMO-3 may support the
findings of Aiken et al. (2008) and Bougiatioti et al. (2014), who reported
that biomass burning aerosol is less oxidized than other types of aerosol,
even after some aging. Conversely, the overall higher oxidation of PMO-2
implies that the sampled aerosol was likely more hygroscopic, included more
efficient cloud condensation nuclei (Massoli et al., 2010), or had components
of a less volatile nature (Ng et al., 2011) than PMO-1 and PMO-3.
Normalized bar charts for the aromaticity of the three PMO
samples, calculated using the Koch and Dittmar (2006, 2016) modified
aromaticity index (AImod).
Molecular formula aromaticity and brown carbon
The aromaticity of the samples is also different between the two groups of
aerosol samples. Based on the aromaticity index (AI, Eq. S2;
AImod, Eq. S3; Koch and Dittmar, 2006, 2016), the free
tropospheric aerosol samples (PMO-1 and PMO-3) are more aromatic than the
convected boundary layer aerosol (PMO-2; Fig. 5). The presence of more
aromatic species in the long-range-transported wildfire-influenced aerosol
may lead to increased light absorption (Bao et al., 2017) and perhaps an
increased resistance to oxidation (Perraudin et al., 2006). Aromatic species
can also be associated with the presence of brown carbon (BrC; Desyaterik et
al., 2013). Aromaticity is heavily dependent on the H/C ratio and the
DBE (Eq. S4), where low H/C and high DBE indicate aromatic structure.
Histograms depicting the distribution of H/C and DBE values for the
three samples are shown in Fig. S11. As observed previously, PMO-1 and PMO-3
are more similar to each other than compared to PMO-2. Likewise, PMO-1 and
PMO-3 exhibit an increase in the number frequency of higher DBE species,
which is not observed in PMO-2, supporting the observation of an increased
overall aromaticity for these free tropospheric aerosol samples. Many
aromatic compounds, such as PAHs are known to be carcinogens, and are a
product of incomplete combustion biomass burning and anthropogenic emissions
(Perraudin et al., 2006; Bignal et al., 2008).
OSC vs. volatility estimated using the Li et
al. (2016) method for the CHO species in the three samples. The size is
determined by the normalized relative abundance (RA) and the color is determined
by the logarithm of the normalized relative abundance multiplied by 1000.
Generally, BrC is considered to be aromatic or olefinic in nature (Bao et
al., 2017). In our observations, the two samples influenced by wildfire show
the greatest amount of olefinic and aromatic species, which is likely
associated with the presence of BrC compounds. Additional evidence for the
presence of BrC in PMO-1 comes from Aethalometer measurements using the
seven-wavelength Aethalometer (Magee Scientific, Berkeley, California, USA)
located at the site, which detected a wavelength-dependent peak with an
Ångström exponent of 1.3 during the sampling period. Ångström
exponents above 1 suggest the presence of BrC or iron oxides. Based on the
retroplume analysis and comparison to similar samples (Džepina et al.,
2015), the detected peak is most likely the result of BrC. Figure S12
contains the Aethalometer observations for this event. Difficulties with the
instrument prevented similar data from being collected for PMO-3; although
based on the retroplumes, ambient conditions, and molecular characteristics,
similar results seem likely. In addition to the Aethalometer response, PMO-1
contained species that were related to BrC in studies by Iinuma et al. (2010)
and Lin et al. (2016) (Table S4). This observation provides evidence for the
persistence of BrC species, which is contrary to the observations by
Forrister et al. (2015) who concluded that BrC is mostly removed within 24
hours. Additionally, the high concentration of OC for this sample makes it
seem unlikely that we observed just a minor residual fraction. Perhaps, the
lifetime of BrC is dependent on additional ambient conditions that influence
aerosol oxidation and phase state.
Phase state, volatility, and cloud processing: implications for
the observed aerosol oxidation
Atmospheric aging processes are influenced by ambient conditions, such as
temperature and water vapor, and the concentrations of reactive species.
Recently, Shrivastava et al. (2017) reported observations of long-range-transported
PAHs from Asia to North America and suggested an enhanced lifetime
due to a probable glassy aerosol phase state during transport. Additionally,
model simulations reported by Shiraiwa et al. (2017) indicated that model SOA
is predicted to be semisolid or glassy at altitudes above 2000 m in the
Northern Hemisphere. Since the PMO aerosol was sampled at 2225 m above sea
level, we examined the estimated glass transition temperature
(Tg) of the studied WSOC species in addition to the markers of
aqueous-phase processing for the three PMO samples. Increased aerosol
viscosity has been shown to decrease the rate of photodegradation (Lignell et
al., 2014; Hinks et al., 2015) and water diffusivity (Berkemeier et al.,
2014). Both photodegradation and water diffusion are expected to strongly
affect the oxidation and aging of aerosol species during transport.
In general, lower volatility typically inversely correlates with
Tg (Shiraiwa et al., 2017) and viscosity. As such it was
important to estimate the volatility of the PMO aerosol. Using the parameters
reported by Donahue et al. (2011) and Li et al. (2016), we estimated the
volatility of the FT-ICR MS identified organic aerosol molecular compositions
(Figs. S13 and S14, respectively). As expected based on the length of
transport for the samples, the majority of formulas show extremely low
volatility. Interestingly, PMO-2 has a larger number of higher abundance
molecular formulas with extremely low volatility and elevated oxidation
relative to PMO-1 and PMO-3 (Fig. 6). This highlights the relationship
between O/C and volatility, where volatility is expected to decrease
as O/C increases when the mass range is constant (Ng et al., 2011);
the relationship between oxygen and carbon and its effect on volatility is
used by both Donahue et al. (2011) and Li et al. (2016) to estimate
volatility. Similarly, lower volatility is expected to lead to lower
diffusivity in aerosol even at elevated RH as demonstrated by Ye et
al. (2016).
Panels (a)–(c) contain the ambient conditions extracted from
the GFS analysis along the FLEXPART modeled path weighted by the residence
time for PMO-1, PMO-2, and PMO-3, respectively. The line represents the mean
value and the shading represents 1 standard deviation of the values. Panels (d)–(f)
contain the box plot distributions of the RH-dependent
Tg values for molecular formulas using the maximum, mean, and
minimum RH for PMO-1, PMO-2, and PMO-3, respectively. The Tg
values for the full composition of each sample were calculated using the
maximum, mean, and minimum RH and then all three sets of data are combined
and plotted as a single distribution for each time period. The open circles
represent the abundance and Boyer–Kauzmann estimated Tg for the
acid forms of the three most abundant low-MW organic ions, the bars around
the circles represent the range of possible Tg values for those
compounds when the range of RH is considered. The red line demonstrates the
ambient temperature at each time point, as extracted from GFS. The centerline
of the box plot represents the median, and the top and bottom of the box
represent the third and first quartiles, respectively. The whiskers
represent Q3 + 1.5* interquartile
range (IQR, Q3–Q1, maximum), and
Q1 - 1.5* (IQR, minimum).
As predicted in earlier studies (Shrivastava et al., 2017; Shiraiwa et al.,
2017), particles transported in the free troposphere are likely semisolid to
solid, where the actual particle viscosity depends on the ambient conditions
and the composition of the particles. Thus, to better understand the
potential phase state associated with the PMO organic aerosol, we first
estimated the dry Tg for the identified CHO molecular formulas in
each of the PMO aerosol using the estimation method by DeRieux et al. (2018,
Eq. S5). We then converted the dry Tg to the RH-dependent
Tg (below). Currently Tg can only be estimated for
CHO species; however, the CHO species were the most frequently observed and
constituted a major fraction of the total relative abundance in the PMO
negative ion mass spectra. Assuming the identified CHO compositions are
fairly representative of the total organic aerosol composition, a comparison
of the Tg values to the ambient temperature (Tamb)
provides an indication of the likely phase state of the organic aerosol
particles. Generally, if Tg exceeds Tamb, a glassy
solid state is predicted, likewise, if Tg is less than
Tamb then either a semisolid or liquid state is predicted
depending on the ratio magnitude (Shiraiwa et al., 2017; DeRieux et al.,
2018). Although the exact composition of the total organic aerosol is yet
unknown, the identified water-soluble organic compounds provide a reasonable
upper limit for the estimated Tg values. Under this assumption,
the CHO molecular formulas in PMO-1 and PMO-3 had higher average dry
Tg values than PMO-2 (Table S5, Fig. S16), which implies that
they would be more viscous than PMO-2, given similar atmospheric conditions.
Water is known to be a strong plasticizer relative to typical aerosol species
(Koop et al., 2011; Shiraiwa et al., 2017; Reid et al., 2018), thus it can
decrease Tg and the overall aerosol viscosity. Therefore, it's
important to consider the ambient RH when estimating the
Tg. Using the extracted ambient temperature and RH from the GFS
along the FLEXPART retroplumes and the Gordon–Taylor equation (Eqs. S6–S7),
the calculated dry Tg were modified to RH-dependent
Tg for the CHO molecular species. The distributions of the
Tg values for the three PMO samples based on 1 standard
deviation of the ambient conditions are shown as box plots in Fig. 7. The
range of ambient temperature and RH extracted from the GFS along the FLEXPART
simulated path yields a wide range of Tg values (Figs. 7, S17).
The estimates were taken back only 5 days due to the increasing range of
possible meteorological conditions associated with the spread in the air
masses as shown in Figs. 1 and S1–S3. Overall, the distributions of
Tg values in PMO-1 and PMO-3 generally exceed the ambient
temperature (Fig. 7), implying that particles containing a majority of these
compounds would likely be solid. To account for the low-MW
organic anions not observed in the FT-ICR mass spectra, their mass
concentrations and Tg values (estimated using the Boyer–Kauzmann
rule; Koop et al., 2011; Shiraiwa et al., 2017; and DeRieux et al., 2018) are
also shown in Fig. 7. The three most prevalent low-MW organic
acids indicate the potential impact of those compounds on the overall
Tg value of a particle that contains them. Oxalic acid was
estimated to have a similar Tg value to a majority of the higher
MW species identified in PMO-2, but it is slightly lower than the majority of
species in PMO-1 and PMO-3. However, the organic mass fraction of oxalate is 3 times
lower in PMO-1 and PMO-3 (2.3 % and 3.0 %) compared to PMO-2 (9.4 %).
PMO-2 van Krevelen plots for unique molecular formulas
separated by group. Symbols are scaled to indicate the normalized relative
abundance (Norm. RA). The DBE is indicated for each group of unique molecular formulas using
colored symbols. Formulas common with other samples are provided in gray for
context.
The results suggest that aerosol in PMO-1 and PMO-3 was overall less
susceptible to atmospheric oxidation due to the aerosol phase state during
free tropospheric long-range transport than it may have been in the boundary
layer with higher ambient RH and temperature. A more viscous phase state
during transport may also explain the presence of persistent BrC species in
PMO-1, where the BrC species are protected from oxidation similarly to the
long-lived PAHs observed by Shrivastava et al. (2017). In contrast to the
observations from PMO-1 and PMO-3, much of the PMO-2 Tg
distribution falls below the ambient temperature implying a semisolid or
liquid state during the final 5 days of transport. This indicates an
increased susceptibility to oxidation processes in the atmosphere (Shiraiwa
et al., 2011), such as aqueous-phase processing. The possibility of aqueous-phase
processing is also supported by the extracted GFS RH in Fig. 7, which
is above 50 % for the last 5 days of PMO-2 transport. The potential for
liquid and/or semisolid aerosol in the boundary layer is consistent with other
studies (Shiraiwa et al., 2017; Maclean et al., 2017) due to the increased RH
in the boundary layer and the plasticizing effect of water. Although, we note
the PMO-2 average dry Tg values were 4–5∘ lower than
those of PMO-1 and PMO-3. Overall, the estimates of dry Tg and
RH-dependent Tg provide an otherwise unattainable upper limit
estimate of the aerosol phase state of the sampled free tropospheric aerosol
in this study.
As described above, the most obvious difference in the molecular composition
of PMO-2 vs. PMO-1 and PMO-3 is the increased extent of oxidation. In fact,
most of the unique species observed in PMO-2 are in the highly oxidized
region of the van Krevelen plot (Fig. 8). However, the exact oxidation
pathways that led to the increased oxidation observed for PMO-2 and its
initial composition are unclear. Both gas-phase and aqueous-phase reactions
lead to SOA, where aqueous SOA components can have higher O/C values
than gas-phase SOA components (Lim et al., 2010; Ervens et al., 2011). The
high numbers of CHNO and CHOS molecular formulas observed here are consistent
with secondary components associated with an emission plume likely enriched
in SO2, NOx, and O3 pertaining to its expected
anthropogenic influence. All three of these reactive species have been shown
to lead to production and oxidation of SOA in the atmosphere (Hoyle et al.,
2016; Bertrand et al., 2018). Cloud and aqueous processing have also been
shown to increase the oxidation of atmospheric organic matter (e.g., Ervens
et al., 2008; Zhao et al., 2013; Cook et al., 2017; Brege et al., 2018).
Comparisons of the detailed molecular composition of the PMO samples with
studies of cloud (Zhao et al., 2013; Cook et al., 2017) and fog (Mazzoleni et
al., 2010) organic matter indicate that the formulas uniquely common to only
PMO-2 have a higher O/C, which supports aqueous-phase processing during
transport. These results are provided in Fig. S19 and Table S6. Studies have
shown that the reactive species emitted from anthropogenic plumes
(SO2, NOx, O3) can play a role in the oxidation of the
organic species that are dissolved in water (Blando and Turpin, 2000; Chen et
al., 2008; Ervens et al., 2011); furthermore, studies have shown aerosol
liquid water content contributes to aqueous production of SOA (Volkamer et
al., 2009; Lim et al., 2010). The elevated RH extracted from the GFS for this
plume (Fig. 7) indicates the presence of aerosol liquid water and is
consistent with its ubiquitous nature (Nguyen et al., 2016). Additionally,
PMO-2 had a strongly elevated non-sea-salt sulfate concentration relative to
PMO-1 and PMO-3, which also indicates aqueous-phase processing (Crahan et
al., 2004; Yu et al., 2005; Sorooshian et al., 2007; Hoyle et al., 2016).
Oxalate, another well-known marker of potential aqueous-phase processing
(Warneck 2003; Crahan et al., 2004; Yu et al., 2005; Sorooshian et al., 2007;
Carlton et al., 2007), was also elevated in PMO-2. The organic mass fraction
of oxalate was 9.4 % in PMO-2 compared to 2.3 % and 3.0 % in
PMO-1 and PMO-3. The nitrate concentration in PMO-2 was very low compared to
PMO-1 or PMO-3 (Table 1), supporting aqueous-phase processed aerosol in
PMO-2. While clearly gas-phase SOA cannot be excluded, several lines of
evidence suggest that aqueous-phase oxidation likely influenced the chemical
and physical characteristics of the PMO-2 aerosol to a larger extent than
those of PMO-1 and PMO-3 based on the observed molecular characteristics,
major ion concentrations (Fig. S20), and the model simulated transport
pathways and GFS meteorology.