Introduction
Aerosol hygroscopicity describes the interaction between aerosol particles
and ambient water molecules at both sub-saturated and supersaturated conditions in the
atmosphere (Topping et al., 2005; McFiggans et al., 2006; Swietlicki et al.,
2008). A key property is its effect on the size distribution of ambient
aerosols, and it can indirectly give information on particle compositions
(Swietlicki et al., 2008; Zhang et al., 2011). It also plays an important
role in visibility degradation and multiphase chemistry due to an enlarged
cross-section area of aerosol particles after taking up water in a humid
environment (Tang et al., 1996; Malm et al., 2003; Cheng et al., 2008, 2016;
Liu et al., 2013; Li et al., 2014; Zheng et al., 2015). Moreover, it
determines the number concentration of cloud condensation nuclei and the
lifetime of the clouds, which in turn affects the regional and global climate
indirectly (Zhang et al., 2008; Reutter et al., 2009; Su et al., 2010; IPCC,
2013; Rosenfeld et al., 2014; Schmale et al., 2014; Seinfeld et al., 2016;
Zieger et al., 2017).
Hygroscopic measurements have been conducted in numerous laboratory and field
conditions around the world. Different observational findings related to the
hygroscopic properties of particles and their chemical composition were
obtained for aerosols from various environmental background conditions.
(Bougiatioti et al., 2009; Park et al., 2009; Swietlicki et al., 2008; Asmi
et al., 2010; Tritscher et al., 2011; Whitehead et al., 2014; Hong et al.,
2015; Chen et al., 2017). Recent studies have specifically focused on the
hygroscopicity of organic material, as atmospheric aerosols normally contain
a large number of organic species, which exhibit highly various water uptake
abilities. Previous works have extensively examined and reported the
hygroscopicity of the organic fraction in aerosols worldwide, including
boreal forest and rural and urban background areas (Chang et al., 2010; Wu et
al., 2013; Mei et al., 2013; Hong et al., 2015; Wu et al., 2016). They found
that the oxidation level or the oxygenation state of all organics, which
directly affects their corresponding solubility in water, is the major factor
that drives the water uptake ability of the organic fraction in aerosols.
However, knowledge on the hygroscopicity of organic material and its
dependency on the oxidation level of organics in urban background areas under
high aerosol mass loading conditions is limited, for instance in China, where
air pollution has become one of the top environmental concerns in recent
decades (Chan and Yao, 2008).
Due to the fast development of industrialization and urbanization, China has
experienced increasingly severe air pollution during the few past decades
(Zheng et al., 2015; Wang et al., 2017). High loadings of atmospheric
aerosols can reduce visibility and lead to adverse acute and chronic health
effects due to the penetration and deposition of submicron particles in the
human respiratory system (Dockery et al., 1993; Cabada et al., 2004; Tie et
al., 2009). In order to better understand the chemical composition, sources
and aging processes of atmospheric aerosols and in turn target the
atmospheric pollution problems in China, measurements of atmospheric
particles with various properties have increased during the recent years.
Hygroscopicity, an important physico-chemical property of atmospheric
particles (Cheng et al., 2008; Gunthe et al., 2011; Cheng et al., 2016), has
also been implemented into extensive campaigns in densely populated areas,
such as that of the North China Plain (Massling et al., 2009; Liu et al., 2011) and the
Yangtze River Delta (Ye et al., 2013). In the Pearl River Delta (PRD)
region, a metropolis in southeastern China with high aerosol loadings and
low visibility (probably due to anthropogenic emissions), Hygroscopic
measurements have also been initiated during the past few years (Tan et al.,
2013; Jiang et al., 2016; Cai et al., 2017). These previous studies have
mainly focused on the statistical analysis of the hygroscopic properties of
PRD aerosols and tried to give possible explanations for their temporal
variations. However, the relationship between the hygroscopic properties of
aerosols in the PRD region and the particle-phase chemical composition have not
yet been systematically constrained, especially the relation of hygroscopic
properties of the organic fraction in the particles to their oxidation level.
Particularly, a close look at the hygroscopicity and the chemical composition of
particles during high aerosol loadings is also scarce.
In this study, we measured the size-dependent hygroscopic properties and
non-size-resolved chemical composition by a self-assembled hygroscopic
tandem differential mobility analyzer (HTDMA) and an aerodyne quadruple
aerosol chemical speciation monitor (ACSM), respectively, in a suburban site in
the PRD region. We aim to find the link between the hygroscopicity of aerosols
and their chemical composition, with a focus on identifying the hygroscopic
properties of the organic material and their O:C dependency for these
suburban aerosols. Hygroscopic properties and the chemical composition of aerosol
particles under high and low aerosol loadings were particularly analyzed
separately.
Materials and methodology
Sampling site and air mass origins
The measurements were conducted from 12 September to 19 October 2016 at the
CAWNET (Chinese Meteorological Administration Atmospheric Watch Network)
station in Panyu, southern China. The site is located at the top of
Dazhengang Mountain, which is in the suburban
area of the megacity Guangzhou. A figure of the geographical location is
available in Tan et al. (2013) and Jiang et al. (2016). A detailed
description of the CAWNET station and the sampling inlet can be found in Tan
et al. (2013) and Cai et al. (2017).
To investigate the relationship between atmospheric aerosol hygroscopicity
and the transport paths or source regions of air masses, 72 h back
trajectories of air parcels arriving at CAWNET were calculated at 6 h
intervals using the Hybrid Single-Particle Lagrangian Integrated Trajectory
(HYSPLIT) model for this study. The arrival height of the trajectories was
chosen to be at 700 m above ground level, which is the mean height of the
boundary layer in Guangzhou during the entire experimental period according
to the data obtained from European Center for Medium-Range Weather Forecasts
(ERA Interim). Trajectories with similar spatial distributions or patterns
were grouped together to generate clusters, representing their mean
trajectories and the predominant air mass origins during the campaign.
Measurements and data analysis
A self-assembled HTDMA was deployed to measure the hygroscopic growth factor
(HGF), the mixing state and the particle number size distribution
(10–1000 nm) of ambient aerosols during this study. A detailed
characterization of the HTDMA system and its operating principles are
available in Tan et al. (2013b). Briefly, after passing through a PM1
impactor inlet, ambient aerosols were first brought through a Nafion dryer
(Model PD-70T- 24ss, Perma Pure Inc.) to be dried to a relative humidity (RH)
lower than 10 % and were subsequently charged by a neutralizer
(Kr85, TSI Inc.). These dry particles of four specific mobility
diameters (D0; 30, 60, 100 and 145 nm) were selected by the first
Differential Mobility Analyzer (DMA1, Model 3081L, TSI Inc.) in the HTDMA
system and were then introduced into a membrane permeation humidifier (Model
PD-70T-24ss, Perma Pure Inc.) to reach a 90 % RH. With a second DMA
(DMA2, Model 3081L, TSI Inc.) and a condensation particle counter (CPC, Model
3772, TSI Inc.), the growth factor distributions (GFDs) or the mobility
diameter (Dp) of these conditioned particles at the 90 % RH
were measured at room temperature. The
hygroscopic growth factor (HGF, RH = 90 %) is then defined as the
following;
HGF(90%)=DpRH=90%D0.
In practice, the growth factor probability density function (GF-PDF) was
fitted from the measured GFDs with bimodal lognormal distributions using a
TDMAfit algorithm (Stolzenburg, 1988; Stolzenburg and McMurry, 2008). After
obtaining the GF-PDF and the ensemble average HGF, number fractions of
particles at each mode and the spread of each mode were calculated.
An Aerodyne Quadruple Aerosol Chemical Speciation Monitor (ACSM; Aerodyne
Research Inc.) was employed to determine the non-refractory PM1 chemical
composition and O:C of submicron aerosol particles with a 50 %
collection efficiency during the experimental period (Ng et al., 2011). The
ratios of oxygen to carbon (O:C) were then estimated by their
relationship to the mass fractions of m/z 44 (f44) to the total organic
mass (Canagaratna et al., 2015). The mass concentration of black carbon was
measured by an aethalometer using a PM2.5 inlet (Hansen et al., 1982).
Wu et al. (2009) compared the BC concentration in PM1 and PM2.5 and found that BC aerosols mainly exist in the fine
particles, with roughly 80 % of the BC mass in PM1. Due to the limited
literature data on BC size distributions in the PRD region, we used this
simplified assumption by Wu et al. (2009) to estimate the BC concentration in
PM1 for this study. It is necessary to note that the chemical
composition of PM1 can be different from those of size-segregated
aerosols, and the ACSM measures the chemical composition of PM1, which
may be significantly different from those of Aitken mode particles. In
addition, complimentary measurements for ambient meteorological conditions
(e.g., relative humidity, wind direction and wind speed) as well as the
particulate matter (PM2.5) mass concentration measurements by an
Environmental Dust Monitor (EDM, Grimm Model 180) were conducted concurrently
during the experimental period.
Closure study
Ambient aerosol particles are mixtures of a vast number and variety of
species. In order to estimate the averaged hygroscopicity of ambient
particles, the Zdanovskii–Stokes–Robinson (ZSR) mixing rule (Zdanovskii,
1948; Stokes and Robinson, 1966) was assumed and the hygroscopic growth
factor (HGFm) of a mixed particle was calculated by summarizing the
volume-weighted HGF of the major chemical components of aerosol particles;
HGFm=∑iεi⋅HGFi31/3,
where εi is the volume fraction of each species and HGFi
is the growth factor of each species present in the mixed particle. The
volume fraction of each species was calculated from their individual dry
densities and mass fractions from ACSM data (Gysel et al., 2007; Meyer et
al., 2009) by neglecting the interactions between different species. Since
ACSM measures the concentration of ions, the molecular composition can be
reconstructed from the ion pairing based on the principles of aerosol
neutralization and molecular thermodynamics (McMurry et al., 1983;
Kortelainen et al., 2017). Several neutral molecules such as
(NH4)2SO4, NH4HSO4, NH4NO3,
H2SO4 and other possible species were therefore obtained. The
related properties of each species necessary for the calculation in Eq. (2)
are listed in Table 1. Ensemble values of the HGF of organic compounds
(HGForg) were suggested as the best-fit values of
the closure analysis were achieved, which is described in detail in
Sect. 3.4. As suggested in earlier studies, the hygroscopicity of organics in
the aerosol particles is dependent on their degree of oxygenation inferred
from the O:C ratio (Massoli et al., 2010; Duplissy et al., 2011; Hong
et al., 2015); hence, we further estimated HGForg according to
the degree of oxygenation presented by the O:C ratio. A similar
approach for approximating the hygroscopicity of organics in the particle
phase based on their O:C ratio is also proposed by Hong et al. (2015).
A density value of 1250 kg m-3 was used for the organics to calculate
their volume fraction, which was suggested by Yeung et al. (2014) in their
closure analysis for aerosols from a similar environment.
Hygroscopic growth factors of all compounds and their individual
density used in the ZSR calculation.
HGF (90 %)
Compounds
Density
Aitken mode
Accumulation mode
(kg m-3)
(30 nm, 60 nm)
(100 nm, 145 nm)
(NH4)2SO4a
1769
1.66
1.70
NH4HSO4
1780
1.74
1.78
NH4NO3
1720
1.74
1.80
H2SO4
1830
2.02
2.05
Organics
1250b
1.0–1.3c
a Hygroscopic growth factor and
density values of all inorganic materials were chosen from Gysel et al. (2007);
b density of organic materials was chosen from Yeung et
al. (2014); c hygroscopic growth factor for organic materials
was varied from 1 to 1.3 according to literature values (Gysel et al., 2004;
Carrico et al., 2005; Aklilu et al., 2006; Good et al., 2010; Hong et al.,
2015; Chen et al., 2017).
Results and discussions
Overview of measurements
Figure 1 shows the temporal variations of meteorological conditions (e.g.,
relative humidity, wind direction, average wind speed) and PM2.5 as well
as BC mass concentration in PM1. In general, the RH showed a clear diurnal
cycle and a northern wind was frequently experienced during this study. The
PM2.5 mass concentration varied from 20 to 180 µg m-3,
with relatively low values (roughly below 50 µg m-3) most of the time. Previous PM2.5 mass concentration measurements at this
site have yielded quite similar results (Jiang et al., 2016) in this season.
During the period of 22–27 September, the PRD region experienced stagnant
weather conditions, with low wind speeds and fluctuating wind directions near
the surface. The stagnant weather leads to the observed increase in the mass
concentrations of PM2.5 and BC, with values up to about 2 times higher values
than in the rest of this study.
Figure 2 shows an overview GF-PDF for particles of four different diameters,
with the color code of probability density and the mass fractions of the ACSM
chemical components as well as the particle number size distributions
(10–400 nm) over the entire measurements period. The white gap in the mass
fraction data in the fifth panel is due to an instrument failure. Particles
of all sizes showed apparent bimodal growth factor distributions with a mode
of more- hygroscopic particles and a mode of less-hygroscopic particles,
indicating that the particle population was mainly externally mixed. A
similar feature was also observed in the PRD region previously (Eichler et
al., 2008; Tan et al., 2013b; Jiang et al., 2016; Cai et al., 2017) as well
as in other urban environments around the world (Massling et al., 2005; Fors
et al., 2011; Liu et al., 2011; Ye et al., 2013).
Time series for relative humidity, wind speeds, wind directions and
concentrations of PM2.5 as well as BC concentration (bottom panel).
Time series of hygroscopic growth factor distribution for 30, 60,
100 and 145 nm particles using HTDMA in the upper four panels and with the color
code indicating probability density. Time series of mass fractions of
chemical species in submicron particles and particle number size distribution
within 10–400 nm using ACSM and DMPS, respectively, in the lower two
panels.
In our study, the bimodal distributions had a dominant more-hygroscopic (MH)
mode for larger particles (100 nm, 145 nm), whereas for smaller particles
(30 nm, 60 nm), these number fractions of two modes were approximately of a
similar magnitude. From the fifth panel in Fig. 1, we can see that the total
inorganic and organic material had roughly equivalent contributions to the
mass fractions in PM1 at the PRD region. This is not a surprise due to
the stronger anthropogenic influence of our measurement site. Particle number
size distributions below 10 nm were not measured by our setup, so new
particle formation events could not be systematically classified for this
study. However, a subsequent particle growth from 10 nm to the accumulation
mode was periodically observed. In this study, two distinguished types of
days (e.g., “relative clean days” on 12–19 September and 9–15 October and
“polluted days” from 22 September at 18:00 LT to 27 September, 09:00 LT)
were characterized by their corresponding differences in meteorological
conditions, the mass concentration of PM2.5 or BC and the occurrence of
clear particle growth above 10 nm. A distinct analysis of aerosol
hygroscopicity, chemical composition and the air mass origins for these two
periods will be further discussed in Sect. 3.3.
Hygroscopicity and mixing state
The diurnal variations of the average HGF of particles of four different
sizes are illustrated in Fig. S1. In general, larger particles were more
hygroscopic than smaller particles. No strong diurnal pattern of the mean HGF
can be concluded from the current results after taking the
uncertainties associated with the mean values into account. This suggests complex sources
and aging processes of aerosols at this suburban site.
Diurnal variation of the HGF of less-hygroscopic (LH) and more-hygroscopic (MH) mode particles and their respective number fractions.
In the upper panels of Fig. 3, we compared the diurnal variation of the HGFs
of particles in the LH and MH mode. The HGFs of LH mode of particles of all
sizes started to increase after 10:00 LT and decrease at about 15:00 LT until
reaching their lowest levels at about 20:00 LT. A possible candidate for
these LH mode particles could be carbonaceous material emitted from local
automobile exhaust during rush hours, with soot and water-insoluble organics
as the major components. These freshly less-hygroscopic particles started to
age in the atmosphere through the condensation of different vapors or
multiphase reactions in the daytime, leading to an obvious increase in HGFs
of LH mode particles without reaching that of MH mode particles. The HGFs of
MH mode particles of larger sizes (100 nm, 145 nm) started a slight
decrease after about 10:00 LT and then increased again between around noon
and late evening. Particles of this mode are supposed to be more aged than
particles in the LH mode, having a substantial fraction of inorganic
components such as sulfate and nitrate. However, during the daytime, when the
photochemical activity is stronger, the MH mode particles are expected to
experience the condensation of different species, especially organics, which
are less hygroscopic. Hence, a slightly lower HGF of these particles was
observed in the afternoon than in the morning. In case of smaller particles
(30 nm, 60 nm), the HGFs of MH group particles appeared to decrease during
the afternoon until about 20:00 LT, suggesting that the transport of these
particles was not long-range, but were rather secondary formed, either
locally or from nearby emissions.
The number fractions of differently sized particles in each mode are illustrated
in the lower panels of Fig. 3. For larger particles (100 nm, 145 nm), MH
mode particles dominated over the LH mode particles. For smaller particles
(30 nm, 60 nm), the number fraction of LH mode particles decreased
dramatically after 00:00 LT and increased back to the same level after
18:00 LT. A similar yet less obvious pattern was also observed for larger
particles. This feature directly suggests that small particles have a lower
degree of external mixing during the afternoon compared with the rest of the
day, providing further evidence that local traffic emissions may be the major
sources of those LH mode particles, especially the ones of smaller sizes.
The correlation between the mean
HGF of accumulation mode particles (100 nm, 145 nm in size) and the
contribution of different species in the particle phase as well as the
O:C of the organic materials.
The hygroscopicity of aerosol particles is ultimately driven by the relative
abundances of compounds with a different water uptake ability in the particle
phase. Hence, we also looked at HGFs of aerosol particles in terms of their
direct composition information. Our ACSM measured the non-size-resolved
chemical composition of particles, which may deviate considerably from that
of Aitken mode particles but may be close to that of accumulation mode
particles. This requires us to choose the HGF of larger particles (100 nm,
145 nm) for the analysis. In Fig. 4, the HGFs of the accumulation mode particles
correlate with the mass fraction ratio between inorganics and
organics + BC (R2=0.38–0.47) better than with the oxidation level of
the organic fraction with R2 values of around 0.23. A detailed
comparison between the HTDMA-measured HGFs and the predicted HGFs using
size-dependent chemical composition will be given below in Sect. 3.4. Gysel
et al. (2007) suggested that, compared with the HGFs of pure organic particles
affected strongly by their oxidation level (Duplissy et al., 2011), the HGFs of
mixed particles are less sensitive to the properties relating to uncertainties
in the growth factor of less-hygroscopic compounds in the aerosol phase. This
feature might explain why the HGFs of our suburban aerosol were influenced to
a lesser extent by the oxidation level of organic compounds than the aerosol
particles typically studied in smog chamber measurements or measured in a
boreal forest environment (Massoli et al., 2010; Tritscher et al., 2011; Hong
et al., 2015).
Diurnal variation of mass concentration of SO42-,
organics, NO3-, BC in particle phase, and the O:C ratio of
organics and their relative contributions in particle-phase composition during
clean days and polluted days.
The major clusters for the 72 h backward trajectory simulation for
air masses arriving at the CAWNET Panyu site with an arrival height of
700 m. (a) shows the results throughout the whole observational
period, while (b) shows the one during polluted days and
(c) is for clean days. All trajectories that are near each other
were merged to a mean trajectory to represent the entire groups by cluster
analysis. The percentage number beside the labeled cluster indicates how many
back trajectories can be represented by this cluster.
Comparison between polluted and clean days
In order to understand the influence of primary sources and secondary
formation on the aerosol loading during different synoptic conditions (e.g.,
relatively clean days and polluted days), we studied the chemical
characteristics and physico-chemical properties of aerosols as
well as individual air mass origins during the two distinguished periods,
respectively. Figure 5 shows the diurnal variation in the major species in
the particle phase during the polluted and relatively clean days.
Concentrations of all of the displayed species were higher during the
polluted period compared with the clean days. This was particularly obvious
for NO3-, whose concentration was almost 10 times higher during the
polluted days. Wind speeds shown in Fig. 1 were the lowest during the
polluted period, enabling local emitted air pollutants such as those from
traffic and cooking to accumulate. Moreover, a substantial fraction
(53 %) of the air mass trajectories (shown in Fig. 6) were passing along
the coastal areas in the southeast of China, which is heavily populated.
These coastal air masses, together with a considerable fraction (16 %) of
air masses circulating within the PRD region, may potentially transport
significant amounts of pollutants, presumably from anthropogenic emissions,
to the site. Contrary to this, air masses on the clean days were mainly from
the inland areas in the north. These regions are covered with vegetation and
are less influenced by anthropogenic emissions, so air masses coming from
there may promote the dilution and clearance of the local pollutants at the
observational site.
During the polluted days, SO42-, NO3- and organics had
clear diurnal patterns. Concentrations of SO42- and organics
peaked during the late afternoon, probably due to gas-phase condensation or
multiphase reactions associated with high levels of SO2 or gaseous
organics after long-range transport, as previously discussed. Nitrate had higher
concentrations in the early morning than in the afternoon. Pathak et
al. (2009) suggested that high concentrations of particulate nitrate could be
explained by the heterogeneous hydrolysis of N2O5 under high
relative humidity conditions. Morino et al. (2006) concluded through using both
observation and thermodynamic modeling that lower temperatures and a higher RH
cause an enhanced condensation of HNO3 in the particle phase.
Figure S1 shows that RH values were higher in the early morning than other
times of the day under polluted conditions. We also looked at gaseous
HNO3 concentrations obtained from MARGA measurements and found them
to be less than 2 times higher in polluted conditions than on clean
days. The partition of HNO3 to the particle phase due to condensation
might not be able to fully explain the nitrate
concentrations that are one order of magnitude higher in the particle phase in polluted days than clean days. Hence, we
speculate that the heterogeneous hydrolysis of N2O5 could be the
alternative reason for the production of the observed high concentrations of
nitrate in the early morning under polluted conditions. During clean days,
both inorganic and organic species have lower concentrations with no strong
diurnal pattern, which indirectly indicates that the influence of the
elevated boundary height on the daily variation of chemical composition was
minor. The concentration of BC peaked at around rush hours, suggesting
that traffic emissions could be one of the major sources of BC.
Sources of uncertainties associated within
hygroscopicity-composition closure, given in terms of three standard
deviations and their corresponding contribution to the overall uncertainty in
hygroscopicity-composition closure.
Parameter
Uncertainty
Uncertainty in
HGForg
(3 standard deviations)
measurements
(relative to 1.26)
RH (DMA2)
1 %
2.3 % in measured HGF
3.2 %
Organic density
18 %
2.6 % in ACSM-derived HGF
3.2 %
BC density
33 %
1.0 % in ACSM-derived HGF
2.0 %
NH4, NO3 mass concentration
20 %
0.6 %, 0.5 %
0.8 %, 1.6 %
SO4 mass concentration
20 %
1.8 %
4.0 %
Organics mass concentration
20 %
1.4 %
3.2 %
BC mass concentration
5 %
0.1 %
0.8 %
Considering all examined species together, the difference in the
inorganics / (organic + BC) ratio between early
morning and late afternoon was more obvious during the polluted conditions
than during the clean days (lower panels of Fig. 5). The average O:C
ratio during the polluted days was a little bit lower than during the clean
days, suggesting that the organic fraction was less oxidized during the
pollution episode.
The HGFs correlate much better with the contribution of different species to
the mass fractions during the polluted days than during the clean days
(Fig. 7). However, the oxidation level had a relatively stronger influence on
the HGFs during the clean days compared with the polluted days. Taken
together, these observations suggest that despite the variability in its
oxidation level, the hygroscopicity of the organic aerosol fraction did not
vary much during the polluted days.
The correlation between the mean HGFs of accumulation mode particles
(100 nm, 145 nm in size) and the contribution of different species in the
particle phase as well as the O:C of the organic materials during
polluted days and clean days.
Hygroscopicity-composition closure
Approximations of the HGForg
The hygroscopic growth factors of organic compounds in the ambient aerosols
(HGForg) cannot be determined from direct observations. However,
by conducting a closure analysis using different approximation approaches,
HGForg was estimated to range widely for various ambient aerosols
in other studies, from about 1.0 to 1.3 (Gysel et al., 2004; Carrico et al.,
2005; Aklilu et al., 2006; Good et al., 2010; Hong et al., 2015; Chen et al.,
2017). In this section, we performed a closure study between the measured and
predicted HGF using a PM1 bulk chemical composition from the ACSM. An
ensemble-mean HGForg (value of 1.1) was determined when the sum
of all residuals (RMSE; root-mean-square error) between the measured growth
factors and corresponding ZSR predictions reached a minimum by varying
HGForgs between 1.0 and 1.3.
By applying this constant HGForg, Fig. 8 compares the
ACSM-derived HGF with the HTDMA-measured ones for four differently sized
particles, with the color code indicating the O:C ratio. It is obvious
that the degree of agreement increased with increasing particle size.
However, the bulk aerosols mainly represent the chemical composition of
aerosol particles near the mass median diameter of the mass size distribution
of ambient aerosol particles (Wu et al., 2013). The question then arises as
to what extent the size-resolved chemical composition of aerosols (for
instance, 100 and 145 nm particles) is comparable with that of the bulk
aerosol. Previous studies (Cai et al., 2017, 2018) reported that the average
organic mass fraction of PM1 was about 25 % and 16 % lower than those
of the 100 and 145 nm particles, respectively, measured by a high-resolution
aerosol mass spectrometer (HR-AMS) during the same season in 2014 at the same
measurement site. Correspondingly, the average inorganic mass fraction of
PM1 was about 25 % and 16 % higher than those of the 100 and
145 nm particles obtained in their results. Due to insufficient information
on the size-resolved chemical composition of ambient aerosols, we hence made
an arbitrary assumption by applying the results from Cai et al. (2017). In
this section, we considered the mass fraction of organic being 25 % and
16 % higher and corresponding lower inorganic mass fractions (ammonium
sulfate mass fraction is decreased) as having smaller sizes (100 and 145 nm)
compared to the bulk aerosol. In addition, we assumed a 20 % uncertainty
in theses suggested values, thus resulting in 25%±3% and
16±3% elevations in organic mass fractions in the 100 nm and
145 nm particles in the current study. This would lead to larger
HGForg values of 1.23±0.02 (100 nm particles) and 1.26±0.03 (145 nm particles) when assuming different chemical compositions of
size-resolved particles and comparing them to the bulk aerosols (see Fig. 9).
In contrast to the results from bulk chemical composition, the closure for
the 100 nm particles considerably improved, as the RMSE value between the
HTDMA_HGF and ACSM_HGF decreased from 1.61 to 0.87, with more than 90 %
of the data within 10 % closure. The closure for 145 nm particles did
not show any significant improvement, with no reduction in the RMSE value.
However, the newly determined HGForg is expected to be more
accurate than the one reported in the previous section, as assumptions of
size-dependent chemical composition were considered, though with some
uncertainties. In addition, the newly obtained HGForg was close
that (1.18) of Yeung et al. (2014), who studied the hygroscopicity of ambient
aerosols in September 2011 at the Hong Kong University of Science and
Technology (HKUST) Supersite, less than 120 km away from our
measurement site.
Closure study between the HTDMA-measured HGFs and the ACSM-derived
HGFs. The dashed lines indicate the 1 : 1 line, while the red lines are those
fitted to the data points. The color bar indicates the O:C ratio
of the organic aerosol fraction. The black solid lines indicate the 1 : 1
line and the black dashed lines represent ±10 % deviation, while the
red lines are those fitted to the data points. The color bar indicates
the O:C ratio of the organic aerosol fraction.
Previous studies suggest that a single ensemble HGForg
approximation might not be capable of evaluating the hygroscopicity of
ambient aerosols from different sources with various characteristics. Hence,
the HGForg approximation according to the O:C ratio was
tested using the chemical composition of both bulk aerosols and size-resolved
particles based on previous assumptions. To facilitate our comparison, the
closure analysis was only conducted for the 145 nm particles. The relation
between the HGForg and the O:C ratio based on the chemical
composition of bulk aerosols was obtained as follows:
HGForg=0.31⋅O:C+0.88.
This closure was no better than the one shown in Fig. 8 using a constant
HGForg, both being based on the chemical composition of bulk
aerosols, and there was little change in the RMSE value (from 0.63 to 0.62).
By taking into account the variation of the O:C ratio,
HGForg ranged from 0.9 to 1.2 when using Eq. (3), with around
80 % of the data having values larger than 1. This finding implies that
the approximation in Eq. (3) may introduce huge errors, as 20 % of the
values of HGForg were not physically correct. The closure
considering size-dependent chemical composition of aerosols from previous
assumptions is shown in Fig. 10, with a new relation between
HGForg and the O:C ratio as the following;
HGForg=0.32±0.01⋅O:C+1.10±0.04.
The closure was somewhat better than in Fig. 8 due to the slightly lower RMSE
value (0.58 vs. 0.63). In addition, the HGForg
ranged from 1.1 to 1.4 with the varying O:C ratio, and there were no
HGForg values smaller than unity, indicating that the new
relation in Eq. (4) seems more widely applicable than the one in Eq. (3). In
general, when considering the fitted slopes being much less than unity and
with consideration to the entire discussion above, we are concerned that
other potential uncertainties may remain in the closure analysis between the
measurements and predictions. This motivates us to make a comprehensive
uncertainty analysis of the hygroscopic-composition closure. It is important
to note that the uncertainty analysis below takes into account the
aforementioned assumption regarding the size-dependent chemical composition
of aerosols.
Closure study between the HTDMA-measured HGFs and the ACSM-derived
HGFs, assuming that the average inorganic mass fractions of PM1 were about
25%±3% and 16%±3% higher and the average
ammonium sulfate mass fractions of PM1 were about 25%±3%
and 16%±3% lower than those of 100 and 145 nm particles. The
black solid lines indicate the 1 : 1 line and the black dashed lines
represent ±10 % deviation, while the red lines are those fitted
to the data points. The color bar indicates the O:C ratio of the
organic aerosol fraction.
Closure analysis with the best fitting between the measured HGFs and
the ACSM-derived ones, using the O:C-dependent HGForg for
145 nm particles. The assumption of size-dependent chemical composition of
aerosols was considered to determine the ACSM-derived HGFs. The equation is
the achieved approximation for HGForg as a function of the
O:C ratio of organic aerosol fraction.
Closure analysis for polluted and clean days
A similar analysis to the hygroscopicity-composition closure similar to that
in Sect. 3.4.1 was performed separately for the polluted and clean days. We
kept adopting the previous assumption in Sect. 3.4.1 considering the
size-dependent chemical composition of aerosols in the current section. The
ensemble-mean HGForg values were quite close to each other between
the polluted and clean days (HGForg=1.30 and 1.28, respectively),
and each closure is shown in Fig. S3. These values are similar to those previously determined (HGForg of 1.26) for the entire
experimental period. A good closure was achieved during the polluted days
with a substantially high R2 value (0.82), whereas during the clean
days, the ACSM-derived HGF did not correlate well with the one measured by
the HTDMA, indicating that other factors, such as the O:C ratio of organic
material, might have affected the achievement of the closure.
Closure analysis with the best fitting between the measured HGFs and
the ACSM-derived ones using the O:C-dependent HGForg for
145 nm particles during the polluted and clean days. The
equation is the achieved approximation for HGForg as a function
of the O:C of organic aerosol fraction. During the polluted days,
HGForg is less sensitive to the changes in the O:C ratio
of organic material compared with the ones during the clean days, indicating
different organic species during these two distinct periods.
Comparison with earlier studies on the hygroscopicity of organic
material with the atomic O:C ratio (or f44 from chemical
composition data) obtained from different environmental background areas. In
this figure, HGForg in this study was converted to
κorg for comparison.
We adopted a hygroscopicity dependent on the O:C of organic material
in the closure analysis separately for the polluted and clean days. The
resulting closure is illustrated in Fig. 11. Compared with the clean days,
the hygroscopicity of organic material was found to be less dependent on the
O:C ratio during the polluted days. This finding is consistent with
the previous discussion in Fig. 7, stating that the oxidation level had a
relatively stronger influence on the HGFs during the clean days compared with
the polluted days. This indicates that the organic compound, even with
similar hygroscopicity, may contain varying chemical species resulting from
different sources or atmospheric processes during these two distinct periods.
As previously stated in the paper, the aerosol particles appeared to have
been from the long-range transport during the polluted days, having a longer
aging history. The organic material in these aerosol particles were fully
oxygenated with a similar hygroscopicity, even for different O:C
ratios. However, during the clean days, the aerosol particles were mainly
from local emissions or formed locally without complex aging histories. The
changes in HGForg revealed the oxidation state of this locally
formed organic material.
Uncertainties of hygroscopicity-composition closure
Swietlicki et al. (2008) discussed the sources of error associated with HTDMA
measurements and concluded that the stability and accuracy of DMA2 RH should
be controlled well to maintain the nominal RH (for instance 90 %). The
accuracy of DMA2 RH in our system was controlled to be 90%±1 %.
This will result in a variability in the measured HGF of ±0.04 when
compared to the reported HGF. The bias uncertainty
(2.3 %) associated with RH accuracy is generally smaller than the
estimated uncertainty (10 %) reported in HTDMA measurements (Yeung et
al., 2014). For the hygroscopicity-composition closure, this biased HGF will
lead to a change of 2.1 % in the HGForg with respect to the
previously determined value of 1.26.
Other uncertainties pertain to the densities used for organic materials and
black carbon. The density value is estimated to range between 1000 and
1500 kg m-3 for organic materials (Kuwata et al., 2012) and 1000 and
2000 kg m-3 for black carbon (Sloane et al., 1983; Ouimette and
Flagan, 1982; Ma et al., 2011). The calculated uncertainty in the
ACSM-derived HGF using the density value at each extreme for organic
materials and black carbon is less than 3.2 % and 2.0 %,
respectively, both having a relatively small effect on the determination of the
constant value of HGForg.
Another source of uncertainty comes from the measurement of aerosol mass
concentration performed by the ACSM and aethalometer. Bahreini et al. (2009)
did a comprehensive uncertainty analysis on aerosol mass concentration
measurements using an aerosol mass spectrometer (AMS) having similar
operating principle as the ACSM, of which systematic biases are not
available. Their study reported an overall uncertainty of 30 % for AMS
measurements and concluded that they might be better for ground-based
studies. Jimenez et al. (2018) gave accuracies of 5 %–10 % from
other AMS practitioners and claimed that these estimated accuracies might be
too small. Hence, we used an overall uncertainty of 20 % for the mass
concentration measurements in this study. The uncertainty in the BC
measurements given by the manufacturer of the aethalometer is
within 5 % (Hansen et al., 2005; Zhang et al., 2017). The effect of the
perturbation in aerosol mass concentration of each species on the
ACSM-derived HGF as well as the determination of the HGForg are
summarized in Table 2. The change in the mass concentration of sulfate exerts
the largest effect on the ACSM-derived HGF as well as the corresponding
HGForg, which is not surprising, since sulfate contributes the
highest fraction in the more-hygroscopic component in aerosols.
In general, uncertainties were relatively low for each individual case
discussed above. It is possible that the contribution from multiple factors
could reduce the overall uncertainties. The greatest aforesaid uncertainty may still arise from the chemical composition of size-segregated aerosols,
since the performance of the closure and the approximations of
the HGForg were most sensitive to changes in the mass concentration
of sulfate and organic materials in aerosols. Except for the reasons
discussed previously, other factors may also cause potential effects on the
hygroscopicity closure. Pajunoja et al. (2015) showed that the phase state of
organic aerosols, which varies with ambient conditions, might have an effect
on the determination of hygroscopicity of organic fraction in aerosols.
Previous studies (Suda et al., 2014) suggested that the interaction between
inorganic and organic materials within the particle phase might alter the
hygroscopicity of organics in mixtures and speculated that the ZSR mixing rule
may not hold for inorganic dominated aerosols (Hong et al., 2015).
Nevertheless, the interpretation of the hygroscopicity-composition closure
and different approximations of the HGForg above reveals that in order
to estimate accurately the properties of ambient aerosols, we might need to
have precise measurements of their chemistry, including the size-dependent chemical
composition of the aerosols, as well as a better prediction model for HGF.
Comparison to other ambient measurements
A number of field studies have examined the relationship between the
hygroscopicity of organic compounds and their oxidation level for ambient
aerosols from various representative organic aerosol sources (Chang et al.,
2010; Chen et al., 2017; Duplissy et al., 2011; Hong et al., 2015a; Mei et
al., 2013; Wu et al., 2013, 2016). The empirical relationship obtained from
our results and these earlier studies are compared and described below in
Fig. 12. It is important to note two aspects before our discussion. First,
Eq. (4), which considers a size-dependent chemical composition of aerosols,
is used here for comparison, as it has a wider application than Eq. (3).
Secondly, the results from other studies shown in Fig. 12 were obtained using
the Hygroscopic parameter (κorg) (the left y axis), while
in this study we obtained the values of HGForg. Both parameters
represent a quantitative measure of the hygroscopicity of organic material.
Hence, we converted our obtained HGForg to Hygroscopic parameter
κ by the procedure given in Petters and Kreidenweis (2007) and
plotted the O:C dependent Hygroscopic parameter κ as a black
line in Fig. 12.
All listed studies show that the hygroscopicity of organic matters generally
increases with an increasing organic oxidation level, with significant
variance in the fitting slopes among all of the empirical relationships. For
aerosols from near-remote (Duplissy et al., 2011; Hong et al., 2015) or rural
background (Chang et al., 2010) areas under little or no influence from
anthropogenic activities, the value of O:C exhibits a stronger impact
on the water uptake ability of organic materials. This indicates that the
oxidation potential from photooxidation in the atmosphere of these
backgrounds is a critical factor in determining the characteristics of
organic materials. Similar to aerosols formed from biogenic precursors, the
apparent O:C dependency on the hygroscopicity of organics is obvious
for peat burning aerosols (Chen et al., 2017), mostly due to the complexity
in the types of biomasses.
In the suburban or urban atmosphere of megacities in China (e.g., Beijing and
Guangzhou), the hygroscopicity of organic material was almost constant, as
shown in this study and by Wu et al. (2016), being much less sensitive
towards the variation in their oxidation level. It is not surprising to
observe a similar O:C dependence on the hygroscopicity of organic
material in the rural background areas of Germany, as reported by Wu et
al. (2013). This might be explained by the fact that their measurement site
is located in central Germany, where anthropogenic activities cannot be
neglected. Wu et al. (2016) discussed that the addition of either an alcohol
or a carboxylic function could both elevate the O:C ratio of the
original organic aerosols. However, the corresponding hygroscopicity of these
organic products may not be increased to the same extent when compared with
the increase in the values of O:C. This could be a possible reason for
explaining that the variation of O:C of organic aerosols is not
necessarily responsible for the changes in hygroscopicity. In contrast, the
κorg of aerosols at an urban site in Pasadena, California,
US, exhibited a stronger increase, with an increasing O:C ratio (Mei
et al., 2013). They found that the relationship of their study is in line
with that obtained from HTDMA measurements of SOA formed from
1,3,5-trimethylbenzene (TMB), a surrogate for anthropogenic precursors
(Duplissy et al., 2011). They also deduced that the major components in SOA
from TMB photooxidation are mainly monoacids, which are quite water soluble.
It is also interesting to observe that the results by Lambe et al. (2011)
showed a quite similar parameterization of HGForg and O:C
dependence compared with that of the current study. They used a Potential
Aerosol Mass (PAM) flow reactor to study the hygroscopicity of organic
aerosols from the oxidation of alkanes and terpenoids, suggesting the
precursors of our organic aerosols in this study might have similar
properties or the same origins as these compounds in their study. The
comparisons of the κorg or HGForg as a function
of O:C within these aforementioned studies suggest that anthropogenic
precursors or the photooxidation mechanisms might differ significantly
between the suburban and urban atmosphere in China and those in the urban
background of the western US. This may lead to distinguished characteristics
of the oxidation products in SOA and therefore to a different relationship
between κorg/HGForg and O:C.
Summary and conclusions
The hygroscopic growth factor distribution obtained in the late summer of
2016 at the Panyu CAWNET station in the PRD region suggests that this suburban
aerosol population with a strong anthropogenic influence was almost always
externally mixed. The diurnal variation of the HGF in the LH and MH mode
particles of four sizes suggests that the LH mode particles were probably
from local emissions, whereas the MH mode particles had a longer aging
history. During the daytime, an external mixing of particles decreased due to
the condensation of different gaseous species onto them, which was
particularly obvious for Aitken mode particles. The contribution of
different species with various water affinities to the particle composition
determines the variation of the mean HGF in general. However, the oxidation
level of organics appeared to influence the hygroscopicity of the suburban
aerosols only slightly.
The stagnant meteorological conditions favored the accumulation of
pollutants originating from coastal areas in southeastern China during the
polluted days. During these days, the hygroscopicity of the organic aerosol
fraction was estimated to vary little despite the variability of its
oxidation level. The atmosphere was cleared by the air masses from the north
during clean days.
The ACSM-derived HGF correlated better with the HTDMA-measured ones for
larger particles (100, 145 nm particles) compared with smaller particles
(30, 60 nm particles). From the closure analysis, considering the assumption
of a size-dependent chemical composition of aerosols, a new relation between
the hygroscopic growth factor of organic compounds and their oxidation level
was obtained for the suburban aerosols over the PRD region during the
experimental periods; HGForg=(0.32±0.01)×O:C+(1.10±0.04). Clearly, a moderate hygroscopicity of organic materials,
with values of HGForg ranging between 1.1 and 1.3, was observed
and exhibited a weak dependence on the O:C ratio for the current
study. A comparison of this relation between polluted and clean days
indicates that even the organic material with similar hygroscopicity during these two
distinct periods may contain varying chemical species resulting from
different sources or atmospheric processes.
The PRD region, as one of the densely populated areas in China, represents a
geographical location in Asia under the subtropical marine monsoon climate
system. However, these issues that are obtained from the results above have been
discussed very little earlier, which thereby reflects the general value of our
contribution. The comparison with earlier studies regarding the relationship
between the HGForg and O:C ratio indicates that there are
substantial differences but also some similarities in the properties of
organic compounds in aerosols in different environments, especially in
urban areas. This motivates us to extend our measuring network in the
future to better understand the generality of the relationship between the
hygroscopicity and the oxygenation of the organic compounds.