ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-17-12327-2017Aerosol surface area concentration: a governing factor in new particle
formation in BeijingCaiRunlongYangDongsenFuYueyunWangXingLiXiaoxiaoMaYanHaoJimingZhengJunzheng.jun@nuist.edu.cnhttps://orcid.org/0000-0001-6225-6130JiangJingkunjiangjk@tsinghua.edu.cnState Key Joint Laboratory of Environment Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing, 100084, ChinaCollaborative Innovation Center of Atmospheric Environment and
Equipment Technology, Nanjing University of Information Science &
Technology, Nanjing 210044, ChinaThese authors contributed equally to this work.Jingkun Jiang (jiangjk@tsinghua.edu.cn) and Jun Zheng (zheng.jun@nuist.edu.cn)17October20171720123271234017May201720May20175September20176September2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/17/12327/2017/acp-17-12327-2017.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/17/12327/2017/acp-17-12327-2017.pdf
The predominating role of aerosol Fuchs surface area,
AFuchs, in determining the occurrence of new particle formation
(NPF) events in Beijing was elucidated in this study. The analysis was based
on a field campaign from 12 March to 6 April 2016 in Beijing, during which
aerosol size distributions down to ∼ 1 nm and sulfuric acid
concentrations were simultaneously monitored. The 26 days were classified
into 11 typical NPF days, 2 undefined days, and 13 non-event days. A
dimensionless factor, LΓ, characterized by the relative ratio of
the coagulation scavenging rate over the condensational growth rate (Kuang et
al., 2010), was applied in this work to reveal the governing factors for NPF
events in Beijing. The three parameters determining LΓ are
sulfuric acid concentration, the growth enhancement factor characterized by
contribution of other gaseous precursors to particle growth, Γ, and
AFuchs. Different from other atmospheric environments, such as in
Boulder and Hyytiälä, the daily-maximum sulfuric acid concentration
and Γ in Beijing varied in a narrow range with geometric standard
deviations of 1.40 and 1.31, respectively. A positive correlation between the
estimated new particle formation rate, J1.5, and sulfuric acid
concentration was found with a mean fitted exponent of 2.4. However, the
maximum sulfuric acid concentrations on NPF days were not significantly
higher (even lower, sometimes) than those on non-event days, indicating that
the abundance of sulfuric acid in Beijing was high enough to initiate
nucleation, but may not necessarily lead to NPF events. Instead,
AFuchs in Beijing varied greatly among days with a geometric
standard deviation of 2.56, whereas the variabilities of AFuchs in
Tecamac, Atlanta, and Boulder were reported to be much smaller. In addition,
there was a good correlation between AFuchs and LΓ in
Beijing (R2=0.88). Therefore, it was AFuchs that
fundamentally determined the occurrence of NPF events. Among 11 observed NPF
events, 10 events occurred when AFuchs was smaller than
200 µm2 cm-3. NPF events were suppressed due to the
coagulation scavenging when AFuchs was greater than
200 µm2 cm-3. Measured AFuchs in Beijing had a
good correlation with its PM2.5 mass concentration (R2=0.85) since
AFuchs in Beijing was mainly determined by particles in the size
range of 50–500 nm that also contribute to the PM2.5 mass
concentration.
Introduction
New particle formation (NPF) is closely related to atmospheric
environment. It is a common atmospheric phenomenon, which has been observed
all over the world (Kulmala et al., 2004). High concentrations of ultrafine
particles are formed intensively during NPF events. It has been illustrated
through both theoretical modeling and field
observations that these ultrafine particles can grow and serve as cloud
condensation nuclei (Kuang et al., 2009; Spracklen et al., 2008) and thus
affect climate (IPCC, 2013). The increased number concentration of ultrafine
particles also raises concerns about human health (HEI, 2013).
New particles are formed by nucleation from gaseous precursors, such as
sulfuric acid, ammonia, and organics. Newly formed particles either grow by
condensation or are lost by coagulation with other particles (McMurry, 1983).
Aerosol Fuchs surface area, AFuchs, is a parameter that describes
the coagulation scavenging effect quantitatively. In addition to gaseous
precursors participating in nucleation and subsequent condensational growth,
there has been a consensus that the occurrence of a NPF event is also limited
by AFuchs, because the survival possibility of nucleated particles
is suppressed when the coagulation scavenging effect is significant (Weber et
al., 1997; Kerminen et al., 2001; Kuang et al., 2012). Reported average
AFuchs (or in the form of a condensation sink) on NPF days was
found to be lower than that on non-event days at several locations (Dal Maso
et al., 2005; Gong et al., 2010; Qi et al., 2015).
A dimensionless criterion, LΓ, was proposed to characterize the
ratio of particle scavenging loss rate over condensational growth rate, and
to predict the occurrence of NPF events in diverse atmospheric environments
(Kuang et al., 2010). By definition, LΓ is determined by three
factors, i.e., the sulfuric acid concentration, the growth enhancement factor
representing contributions of other gaseous precursors in addition to the
sulfuric acid concentration, Γ, and AFuchs. The diurnal
sulfuric acid concentration can vary drastically due to
the substantial change in radiation (e.g., from several thousand to
∼1.5×106# cm-3 in this campaign) and the increase in sulfuric acid concentration
after the sunrise can potentially lead to nucleation. The values of
AFuchs, however, were usually reported within a narrow range at
locations, such as Tecamac, Atlanta, and Boulder (Kuang et al., 2010). The
sulfuric acid concentration in Atlanta and Hyytiälä can differ
significantly among days (Eisele et al., 2006; Petäjä et al., 2009).
Therefore, the sulfuric acid concentration often governs nucleation and
subsequent growth in the sulfur-rich atmosphere, such as in Atlanta (McMurry
et al., 2005). The growth enhancement factor, Γ, at Hyytiälä
varied in a wide range, while those at Tecamac and Boulder were found in a
relatively narrow range.
Aerosol concentrations in Beijing are usually much higher than those in clean
environments. The annual average PM2.5 mass concentration in 2016 was
73 µg m-3 (reported by the Beijing Municipal Environmental
Protection Bureau), and the average AFuchs measured in Beijing by
this campaign was 381.5 µm2 cm-3, which is approximately
a magnitude higher than those measured in clean environments, such as in
Hyytiälä (Dal Maso et al., 2002). Differently from the comparatively
slow accumulation and depletion process of aerosol concentrations in clean
environments, AFuchs in Beijing may change rapidly because of
changes in air mass origins (Wehner et al., 2008) or accumulation of
pollutants.
The sulfuric acid concentration is needed to estimate LΓ and
direct measurement of particle size distribution down to ∼ 1 nm will
help to better quantify NPF events. Although sulfuric acid has been measured
around the world (Erupe et al., 2010) and analyses based on sub-3 nm size
distributions have been conducted sporadically since the development of
diethylene glycol scanning mobility particle spectrometers (DEG-SMPS, Jiang
et al., 2011a, b; Kuang et al., 2012) and particle size magnifiers (PSMs,
Vanhanen et al., 2011; Kulmala et al., 2013), there are limited data on
atmospheric sulfuric acid concentrations and directly measured sub-3 nm
particle size distributions in China. A campaign in Beijing during the 2008
Olympic Games (Yue et al., 2010; Zheng et al., 2011) characterized
atmospheric sulfuric acid concentration and its correlation with the new
particle formation rate. The exponent in the correlation of the formation
rate, J3, with the sulfuric acid concentration was found to be 2.3. The
exponent for correlating derived J1.5 with the sulfuric acid
concentration was 2.7 (Wang et al., 2011). They were different from the
exponents between 1 and 2 often reported in other places around the world
(Riipinen et al., 2007; Sihto et al., 2006; Kuang et al., 2008). The same
instrument used in the Beijing campaign was also deployed in Kaiping to
measure the sulfuric acid concentration during a 1-month campaign in 2008
(Wang et al., 2013a). Sub-3 nm particle size distributions have not been
reported previously in China, except for the 1–3 nm particle number
concentration in Shanghai in the winter of 2013 inferred by a PSM (Xiao et
al., 2015). Due to the limitation of observation data, although a good
correlation between the new particle formation rate and the sulfuric acid
concentration in Beijing was found and the ratio of the sulfuric acid
concentration over AFuchs was reported to positively correlate with
the number concentration of 3–6 nm particles (Wang et al., 2011), the roles
of the sulfuric acid concentration and AFuchs in determining the
occurrence of NPF events have not been quantitatively illustrated.
In this study, we aimed to examine the roles of AFuchs and the sulfuric
acid concentration in determining whether a NPF event will occur on a
particular day in Beijing. The data analysis was based on simultaneous
measurement of particle size distributions down to ∼ 1 nm and
sulfuric acid. The correlation between particle formation rate, J1.5,
and the sulfuric acid concentration was examined. LΓ was used to
predict the occurrence of NPF events. Daily variations of the three
parameters determining LΓ, i.e., the sulfuric acid concentration,
Γ, and AFuchs, were compared. A nominal value of AFuchs was
suggested to predict the occurrence of NPF events in Beijing. The
relationship between the PM2.5 mass concentration and NPF events was
also examined.
Experiments
A field campaign studying NPF in Beijing was carried out from 7 March 2016 to
7 April 2016. The campaign site was located on the campus of Tsinghua
University. Details of this site can be found elsewhere (Cai and Jiang, 2017;
He et al., 2001). A home-made DEG SMPS was used to measure sub-5 nm particle
size distributions and a particle size distribution system (including a TSI
aerodynamic particle sizer and two parallel SMPSs, equipped with a TSI
nanoDMA and a TSI long DMA, respectively) was used to measure size
distributions of particles from 3 nm (in electrical mobility diameter) to
10 µm (in aerodynamic diameter, Liu et al., 2016). A specially
designed miniature cylindrical differential mobility analyzer (mini-cyDMA)
for effective classification of sub-3 nm aerosol was equipped with the
DEG-SMPS (Cai et al., 2017). A cyclone was used at the sampling inlet to
remove particles larger than 10 µm. The sampled aerosol was
subsequently dried by a silica-gel diffusion drier. The diameter change due
to drying was neglected when calculating AFuchs since the mean
daytime relative humidity during the campaign period was ∼ 25 %.
Diffusion losses, charging efficiency, penetration efficiencies through the
DMAs, detection efficiencies of particle counters, and multi-charging effect
were considered during data inversion. The particle density was assumed to be
1.6 g cm-3 according to local observation results (Hu et al., 2012).
Sulfuric acid was measured by a modified high-resolution time-of-flight
chemical ionization mass spectrometer (HR-ToF-CIMS, Aerodyne Research Inc.).
Instead of using a radioactive ion source, a home-made corona discharge (CD)
ion source was utilized with the HR-TOF-CIMS. The CD ion source was designed
to be able to operate from a few Torr up to near atmospheric pressure and has
been successfully implemented in measuring ambient amine (Zheng et al.,
2015a) and formaldehyde (Ma et al., 2016). In this study, nitrate reagent
ions were used to measure gaseous sulfuric acid (Zheng et al., 2010). The
detailed ion chemistry to generate nitrate ions and the calibration procedure
for sulfuric acid measurement have been reported in Zheng et al. (2015b).
Ambient sulfuric acid concentration in Beijing has been reported only once in
a field campaign conducted in 2008 (Zheng et al., 2011; Wang et al., 2011).
Compared to that campaign, the sulfuric acid concentration measured in this
study displayed similar diurnal variations, but with lower daily-maximum
values. This might be caused by the relatively weak solar radiation intensity
encountered in this springtime observation compared with the previous
summertime campaign. To verify the precision of sulfuric acid measurement,
the instrument was calibrated daily at night and background checks were
performed for ∼ 3 min each hour during daytime.
A meteorological station (Davis 6250) measuring temperature, relative
humidity, wind speed, wind direction, and precipitation was located
∼ 10 m away from the sampling inlet. The PM2.5 mass concentration
measured in the nearest national monitoring station (Wanliu station,
∼ 5 km away to the southwest of our campaign site) was also used for
analysis. Backward trajectories were obtained from the online HYSPLIT server
of the National Oceanic and Atmospheric Administration (NOAA).
Theory
Nucleation is only the first step of new particle formation. The random collisions of gaseous precursor molecules can form clusters together by Van der Waals forces and/or chemical
bonds. These clusters become particles if they are more likely to grow by
condensation rather than evaporate. However, particles formed by nucleation
may be scavenged through coagulation with larger particles before they grow
large enough to be detected (McMurry, 1983; Zhang et al., 2012). Nucleation
only refers to the process where stable molecular clusters formed
spontaneously from gaseous precursors. New particle formation also requires
subsequent condensational growth of freshly nucleated particles. That is, the
occurrence of nucleation is mainly determined by gaseous precursors (e.g.,
sulfuric acid and organics) in atmospheric environments, while new particle
formation is also influenced by the coagulation scavenging effect of
pre-existing aerosols. A possibility exists that nucleation occurs while NPF
events are not observed because of the short lifetime of nucleated particles
due to a strong coagulation scavenging (Kerminen et al., 2001). In fact,
nucleation can also be suppressed when the aerosol concentration is high
since vapors and clusters may
also be scavenged by aerosol surfaces.
Aerosol Fuchs surface area, AFuchs, is a representative parameter
of coagulation scavenging based on kinetic theory. It is corrected for
particles whose size falls in the transition regime (Davis et al., 1980;
McMurry, 1983). The formula assuming a unity mass accommodation coefficient
(sticking probability) is shown in Eq. (1),
AFuchs=4π3∫dmin∞dp2×Kn+Kn21+1.71Kn+1.33Kn2×n×ddp,
where dp is the particle diameter, dmin is the smallest
particle diameter in theory and the smallest detected one in practice, Kn
is the Knudsen number, and n is the particle size distribution function,
dN/ddp. The condensation sink and coagulation sink can also
describe how rapidly gaseous precursors and particles are scavenged by
pre-existing aerosols, respectively (Kerminen et al., 2001; Kulmala et al.,
2001). Since the condensation sink is proportional to AFuchs
(McMurry et al., 2005) and the coagulation sink can be approximately
converted to the condensation sink using a simple formula (Lehtinen et al.,
2007), only AFuchs is used in this study to describe the
coagulation scavenging effect. Condensation sink values reported in previous
studies are referred to in the form of AFuchs. The diffusion
coefficient of sulfuric acid was assumed to be 0.117 cm-2 s-1
(Gong et al., 2010) when converting the condensation sink into AFuchs.
A dimensionless criterion, LΓ, was proposed to predict the
occurrence of NPF events (Kuang et al., 2010). It is defined as
LΓ=c‾×AFuchs4β11N1×1Γ,
where c‾ is the mean thermal speed of sulfuric acid that can be
calculated from molecular kinetic theory; β11 is the coagulation
coefficient between sulfuric acid monomers that can be calculated using
Eq. (13.56) in Seinfeld and Pandis (2006); N1 is the number
concentration of sulfuric acid; Γ is a growth enhancement factor and
is defined as
Γ=2GRv1Nmc‾,
where GR is the observed mean growth rate; v1 is the corresponding
volume of sulfuric acid monomer and was estimated to be 1.7×10-28 m3 (the volume of a hydrated sulfuric acid molecule, Kuang et
al., 2010); and Nm is the maximum number of sulfuric acid
concentration during a whole NPF event period. Since other gaseous precursors
in addition to sulfuric acid might also contribute to the condensational
growth of particles formed by nucleation (O'Dowd et al., 2002; Ristovski et
al., 2010) and only sulfuric acid concentration is used in Eq. (2), the ratio
of measured growth rate over the sulfuric acid condensational growth rate
(Weber et al., 1997), i.e., Γ, was used for correction. It should be
clarified that LΓ in Eq. (2) is defined similarly to that in
McMurry et al. (2005) but slightly differently from that in Kuang et
al. (2010), since LΓ in this study presents time-resolved values
rather than event-specific ones. Theoretically, Γ can also be time-
and size-resolved when using time- and size-resolved GR and time-resolved
sulfuric acid (Kuang et al., 2012). However, Γ during each NPF event
is assumed to be constant in Eq. (3) because further evaluations are needed
for this time- and size-resolved model. Note that in Eq. (2) the absolute
sulfuric acid concentrations were effectively normalized by the corresponding
daily-maximum sulfuric acid concentrations and thus have no influence on
LΓ values and conclusions based on LΓ reported in this
study.
A new balance formula to estimate the new particle formation rate was
proposed recently (Cai and Jiang, 2017) and is given below:
Jk=dN[dk,du)dt+∑dg=dkdu-1∑di=dmin+∞βi,gN[di,di+1)N[dg,dg+1)-12∑dg=dmindu-1∑di3=max(dmin3,dk3-dmin3)di+13+dg+13≤du3β(i,j)N[di,di+1)N[dg,dg+1)+nu×GRu,
where Jk is the formation rate of particles at the size of dk,
N[dk,du) is the total number concentration of particles
from dk to du (not included), du is the upper bound of
the size range for calculation (25 nm in this study), du-1 is the lower bound of the last size bin, and dmin is
the size of the smallest cluster in theory and the smallest detected size in
practice (1.3 nm in this study). The second and third terms on the
right-hand side of Eq. (4) are the coagulation sink term (CoagSnk)
and the coagulation source term (CoagSrc), respectively. The
difference between CoagSnk and CoagSrc is the net
CoagSnk representing the net rate of particles from dk to
du, i.e., lost by coagulation scavenging. The last term is often
negligible according to the determination criteria for du. dN / dt
is the balance result of Jk and net CoagSnk.
Contour of measured particle size distributions during 12 March to 6
April. The identified 13 non-event days and 2 undefined days are shadowed by
grey and yellow background, respectively.
Results and discussion
A total of 26 days from 12 March to 6 April was classified by the occurrence
of a daytime NPF event. A typical NPF day is featured with distinct and
persisting increases in the sub-3 nm particle number concentration and
subsequent growth of these nucleated particles. A non-event day means that
neither of these two features was observed. As shown in Fig. 1, there are 11
typical NPF days and 13 non-event days. The other 2 days, i.e., 19 and
30 March, were classified as undefined days. On these days, the increase in
the sub-3 nm particle number concentration and subsequent growth were both
observed. However, the sub-3 nm particle number concentration was relatively
low and the evolution of particle size distributions was not continuous. NPF
events mainly occurred when wind came from northwest of Beijing and non-event
days were associated with air masses from the southwest (as summarized in
Table 1). Air masses coming from the north usually experience less influence
from urban pollution (Wehner et al., 2008; Wang et al., 2013b); i.e., the
AFuchs values on days dominated by the northerly wind are usually
lower than those on days dominated by the southwesterly wind (Wu et al.,
2007).
a Indicated by 12 h backward trajectory (starting at noon, 500 m in
altitude).b Difficult to estimate.
The occurrence of NPF events on most days can be predicted by LΓ
if unity was empirically chosen as the threshold value. Greater LΓ
indicates higher possibilities of nucleated particles being scavenged by
coagulation before they can continue to grow. Growth rates on non-event days
were assumed to be 2.4 nm h-1, the mean value of observed growth rates
on NPF days (the range is 1.2 to 3.3 nm h-1). A threshold value of
LΓ can not be theoretically predicted but can be empirically
estimated; 0.7 was suggested as the threshold value by Kuang et al. (2010).
However, unity suggested by McMurry et al. (2005) appeared to work better for
results from this campaign in Beijing. As shown in Table 1, the median and
mean values of LΓ on NPF days observed in this campaign were 0.55
and 0.71 (with a standard deviation of 0.40), respectively, compared to 3.05
and 3.45 on non-event days (with a standard deviation of 1.79), respectively.
However, some exceptions were also observed. On the 2 undefined days,
LΓ were 1.40 and 0.64, respectively, and weak nucleation was
observed. Although the estimated LΓ value on 18 March was 1.75, a
comparatively weak but still distinct NPF event was observed. Despite these
few exceptions, LΓ works well on most days in this campaign and
was verified in other places (Kuang et al., 2010). The following discussion
is focused on the contribution of different factors, i.e., the sulfuric acid
concentration, Γ, and AFuchs.
Time series for Fuchs surface area (AFuchs), the sulfuric acid
concentration, and number concentration of 1–3 nm particles. Typical NPF
days and undefined days are shadowed by light blue and light green
background, respectively.
The role of gaseous precursors
There was a positive correlation between the estimated new particle formation
rate, J1.5, and the sulfuric acid concentration during most NPF periods
(typically 08:00–16:00 when the estimated J1.5 was greater than zero).
On NPF days, an increase in the sub-3 nm particle number concentration was
often accompanied by an increase in the sulfuric acid concentration (as shown
in Fig. 2). Considering the possible sensitivity of the fitted parameters to
the fitting time period (Kuang et al., 2008), the correlation between
J1.5 and the sulfuric acid concentration was only examined for NPF
periods. We found that the mean coefficient of determination (R2) in
this campaign was 0.53. The exponents for correlating the J1.5 and the
sulfuric acid concentration ranged from 1.5 to 4.0 in the 10 days, with a
mean value of 2.4 (29 March was not included because of insignificant
correlation). This is in agreement with the previously reported mean exponent
of 2.3 using J3 in Beijing (Wang et al., 2011). However, the exponent is
quite different from the exponents no greater than 2 observed in North
America and Europe (Kuang et al., 2008; Riipinen et al., 2007; Sihto et al.,
2006), indicating that activation or kinetic nucleation alone can not explain
all NPF events observed in this campaign.
The correlations between the estimated new particle formation rate,
J1.5, and the sulfuric acid concentration during the NPF event period on
each NPF day. The regression line of J1.5 versus the sulfuric acid
concentration was exponentially fitted. n is the exponent. Data on 29 March
were not included because the correlation was not significant (p=0.34).
Although the correlation between the sulfuric acid concentration and the
particle formation rate was significant, sulfuric acid appeared not to be the
determining factor for whether a NPF event would occur in Beijing. As
illustrated by the temporal trend of the sulfuric acid concentration in
Fig. 2, a significant diurnal variation was observed every day. However, the
differences among the daily-maximum sulfuric acid concentrations were small.
The variations of daily-maximum sulfuric acid concentration were
significantly less than those of AFuchs. The geometrical standard
deviation and relative standard deviation of maximum sulfuric acid
concentration on each day were 1.40 and 0.34, respectively, while those of
the daily-averaged AFuchs values were 2.56 and 0.82, respectively.
The sulfuric acid concentrations during NPF periods were not significantly
higher than those between 08:00 and 16:00 on non-event days (significant
value, p=1). In addition, comparatively high sulfuric acid concentrations,
e.g., on 4–6 April, did not necessarily lead to NPF events.
Normalized growth enhancement factor, Γ, in this campaign
in comparison to those reported for other campaigns. Γ was
normalized by the geometric mean value in each campaign.
The influence of the growth enhancement factor, Γ, on the occurrence
of NPF events also needs to be addressed because sulfuric acid alone may not
explain the observed growth rates. The estimated Γ value for each
event was normalized by the geometric mean Γ value for the whole
campaign to make it comparable with those obtained from previous studies
(Kuang et al., 2010): MILAGRO in Tecamac (Iida et al., 2008); ANARChE
(McMurry et al., 2005) in Atlanta; Boulder (Iida et al., 2006); and QUEST II
(Sihto et al., 2006), QUEST IV (Riipinen, et al., 2007), and EUCAARI
(Manninen et al., 2009) at the SMEAR II station in Hyytiälä. It
should be clarified that the relative value of Γ can improve the
comparability by overcoming some uncertainties in the measured sulfuric acid
concentrations in different studies. Figure 4 indicates that Γ values
observed in this study are distributed in a relatively narrow range, similar
to those observed in Tecamac, Atlanta, and Boulder, while being different
from the widely spreading characteristics of
Γ values in Hyytiälä. Geometric standard deviations of
Γ values were 1.31, 1.75, 2.23, 1.87, 1.62, 2.77, and 2.87 in this
campaign, MILAGRO, ANARChE, Boulder, QUEST II, QUEST IV, and EUCAARI,
respectively. The daily variations of Γ values in Beijing were less
than those observed in other places. They were also less than the daily
variations of AFuchs values measured in this campaign. Considering
the small daily variations of both the sulfuric acid concentration and
Γ values, it is reasonable to conclude that the abundance of gaseous
precursors, such as sulfuric acid, in Beijing during the campaign period was
sufficiently high for nucleation to occur, but the occurrence of NPF events
appeared to be governed by AFuchs.
(a) The relationship between Fuchs surface area and number
concentration of 1–3 nm particles, N1-3. The relative concentration of
measured sulfuric acid is represented by symbol size; i.e., the higher the
relative concentration, the bigger the symbol size. Data points are 5 min
resolved. (b) Frequencies of observed NPF days, undefined days, and
non-event days in comparison to the daily-average AFuchs. On
typical NPF days and undefined days, AFuchs was averaged during
NPF event periods. On non-event days, it was averaged between 08:00 and
16:00. AFuchs values were binned in a logarithmic scale ranging
from 45 to 1150.
Relationship between AFuchs and NPF events
Comparatively lower AFuchs values were found during most of the
NPF days, whereas the sulfuric acid concentrations on NPF days were not
significantly higher than those on non-event days. NPF events mainly occurred
when AFuchs was smaller than 200 µm2 cm-3 (the
corresponding condensation sink is 0.027 s-1). Non-event days mainly
corresponded to a real-time AFuchs value greater than
200 µm2 cm-3 and an average AFuchs value
greater than 350 µm2 cm-3 (Fig. 5). The value of
200 µm2 cm-3 appeared to be an empirical division
between NPF days and non-event days. If AFuchs was lower than this
value, a NPF event tended to occur. Otherwise, the occurrence of NPF events
was suppressed because of the predominant coagulation scavenging effect. A
similar threshold (the condensation sink of 0.02 s-1) was found in
Budapest, Hungary (Salma et al., 2017).
The variation of LΓ in Beijing was governed by AFuchs.
The measured LΓ and AFuchs values had a good correlation
with the coefficient of determination (R2) of 0.88. The mean relative
error of fitted LΓ using AFuchs was 11.4 % compared
to the measured ones (Fig. 6a). It should be clarified that GR on non-event
days in this campaign was assumed to be the same (2.4 nm h-1, an
average of the fitted values on NPF days). The correlation between LΓ and AFuchs on NPF days alone had an R2 of 0.89. The
AFuchs of 200 µm2 cm-3 corresponds to an
LΓ of approximately unity in this campaign. Since LΓ
has been verified as a proper nucleation criterion in diverse atmospheric
environments, it is reasonable to conclude that AFuchs was the
governing factor of the occurrence of NPF events observed in this campaign.
(a) The correlation between LΓ and AFuchs (data from
Table 1) in this campaign. NPF days, non-event days, and undefined days are
shown as different symbols. The regression was based on all campaign days.
(b) The correlation between LΓ and AFuchs estimated for this
study in comparison to other campaigns.
The characteristics of AFuchs dominated NPF events in Beijing are
different from those at other locations. As shown in Fig. 6b, LΓ
and AFuchs in most other places do not correlate well, indicating
that AFuchs alone can not predict the occurrence of NPF events at
these locations. The variations of these parameters at various locations are
illustrated in Fig. 7. In Atlanta and Boulder, AFuchs values
fluctuated within relatively narrow ranges, while the concentrations of
gaseous precursors participating in nucleation differed significantly. The
variations of LΓ at these locations were mainly caused by the
relatively large variations in the concentrations of gaseous precursors.
However, the contribution of gaseous precursors to LΓ in Beijing
was relatively stable and the variations of LΓ were mainly caused
by the variations in AFuchs values.
The schematic of governing factors for LΓ at different
locations. Concentration of growth relevant gaseous precursors is represented
by Γ×N1, where Γ is the growth enhancement factor
and N1 is the sulfuric acid number concentration. Background color
represents the magnitude of LΓ. Data for each location are shown
as different symbols (circle: Beijing; square: Atlanta; diamond: Boulder;
triangle: Hyytiälä). The ellipse and the boxes were artificially
drawn to illustrate the variations. Tecamac was not included due to the lack
of data on non-event days. Both axes are in log scale.
The predominant role of AFuchs in Beijing can also be explained
using the balance formula shown as Eq. (4). It is dN / dt rather than
the formation rate, J, that directly reflects whether a NPF event has
occurred or not. dN / dt is the balanced result of the formation rate
and the net CoagSnk. Differently from LΓ, that is, the
ratio of the particle loss rate over the growth rate, the ratio of the net
CoagSnk over J represents how many nucleated particles are lost
due to the coagulation scavenging. The surviving particles are accounted for
by the increment in the number concentration of particles in the nucleation
mode (1–25 nm). The nucleation mode was used in this study to estimate
dN / dt caused by nucleation because newly formed particles seldom grew
beyond 25 nm in the evaluated time period. Surviving possibilities of
nucleated particles can also be inferred using the growth rate and
AFuchs (Weber et al., 1997; Kerminen and Kulmala, 2002; Kuang et
al., 2012). However, the ratio of the net CoagSnk over J was used
because it is based on measured particle size distributions. Note that
theoretically the ratio of the net CoagSnk over J can be greater
than unity. This would correspond to a negative dN / dt value. For a
better description of the occurrence of NPF events rather than the whole
process including termination, only NPF periods when dN / dt was
positive were considered here. On average, 70 % of particles formed by
nucleation were lost due to coagulation scavenging on NPF days (as shown in
Fig. 8), indicating high coagulation losses in Beijing even on NPF days. When
the AFuchs value was much greater, most nucleated particles were
lost due to the coagulation scavenging rather than were grown into larger
sizes, such that NPF events were less likely to be observed.
Average contribution of the net CoagSnk, dN / dt, and the
condensational growth term (GR term) to the estimated new particle formation
rate, J1.5, on identified typical NPF days. The percentage presented in
each column is the relative ratio of the net CoagSnk compared to J1.5 of
that NPF event. Note that only the time period when dN / dt was
positive during a NPF event was taken into account when calculating the
average contribution.
It should be clarified that although with much less possibility, NPF events
may also occur in Beijing when AFuchs was greater than
200 µm2 cm-3. In this campaign, a distinct NPF event was
observed with a comparatively high AFuchs value of
329 µm2 cm-3 (on 18 March). It was significantly higher
than the suggested threshold value of 200 µm2 cm-3. As
indicated by Table 1, this exception was caused by the failure of LΓ rather than AFuchs alone; i.e., NPF events occurred when
estimated LΓ was greater than unity (the empirical threshold
value). The comparatively low number concentration of sub-3 nm particles
together with the moderate particle formation rate indicated that the NPF
event was suppressed. In addition, previous studies in Beijing also observed
some NPF events when AFuchs values were relatively high (Wu et al.,
2007; Wang et al., 2013c, 2017), e.g., an AFuchs value of
∼ 555 µm2 cm-3 (Kulmala et al., 2016). These
reported AFuchs values might be overestimated since the
daily-average value rather than the average only over NPF event periods was
used. AFuchs in Beijing during non-event periods can be
significantly higher. Nevertheless, AFuchs can be considered the
major determining factor of the occurrence of NPF events in Beijing while
admitting that exceptions can occasionally occur at a medium LΓ
value greater than unity (corresponding to the AFuchs value of
200 µm2 cm-3).
(a) Contour of measured particle size distributions on 2,
3, and 4 April. (b) Representative parameters on these 3 NPF days.
Time periods when LΓ was lower than 1.0 are shadowed by light blue
background. When wind speed was close to zero, the corresponding wind
direction data were not included in the plot.
A case study of 3 days
Three continuous days, including 2 NPF days and 1 non-event day, are shown in
Fig. 9 to further illustrate the roles of AFuchs and sulfuric acid
(together with other gaseous precursors) in affecting the occurrence of NPF
events in Beijing. On 2 April, AFuchs remained at a relatively low
level. A NPF event occurred after sunrise (together with an increase in the
sulfuric acid concentration) and ended in the afternoon when the sulfuric
acid concentration decreased to a low level. The whole NPF event began at
approximately 07:30 and ended at approximately 14:30, which was also the
typical time period for other NPF events observed in this campaign. However,
when wind direction changed from northwest to southwest at noon on 3 April,
the sulfuric acid concentration decreased and AFuchs increased
rapidly because of particles transported from the south. This led to an
increase in LΓ. The ongoing NPF event was interrupted and no newly
nucleated particles were detected even when the sulfuric acid concentration
increased again later. On 4 April, AFuchs stayed at a high level.
LΓ was always greater than unity. The maximum sulfuric acid
concentrations on 4 April were even higher than those on 2 and 3 April.
However, no NPF event was observed. It supports the argument that the
abundance of gaseous precursors in Beijing is often high enough for
nucleation to happen; however, whether or not a NPF event occurs is mainly
governed by AFuchs.
Normalized distribution of cumulative Fuchs surface area,
AFuchs‾, as a function of the particle diameter,
dp, on 2 NPF days (red circle) and 2 non-event days (blue diamond).
AFuchs‾ is equal to AFuchs when dp
approaches positive infinity.
dAFuchs‾/dlogdp is normalized
by AFuchs.
Predicting NPF days using PM2.5 mass concentration
The PM2.5 mass concentration in Beijing serves as a rough but simple
parameter to predict whether a NPF event can happen. The value of
AFuchs is affected by particle size distributions. Accumulation
mode particles ranging from 50 to 500 nm in Beijing were the major
contribution to AFuchs. Normalized size distributions of
accumulation mode particles were relatively stable at various
AFuchs levels (as shown in Fig. 10). On NPF days when
AFuchs was relatively low, particles smaller than 30 nm in
diameter formed by nucleation and subsequent growth also contributed to
AFuchs, although AFuchs was still governed by
accumulation mode particles. Thus, AFuchs should show better
correlation with the particle mass concentration rather than the particle
number concentration. Figure 11 indicates that there was a good correlation
between AFuchs and the PM2.5 mass concentration in Beijing,
with R2 of 0.85, although the correlation at a high AFuchs
level was generally better than that at a low AFuchs level because
particles formed by nucleation significantly changed the shape of particle
size distribution functions on NPF days. Measured PM2.5 mass
concentrations in the 26 days ranged from 3 to 420 µg m-3,
wide enough to represent both relatively clean days and severely polluted
days in Beijing. The PM2.5 mass concentrations during NPF event periods
were mostly lower than 30 µg m-3, except for the event on 18
March. On non-event days, the PM2.5 mass concentrations between 08:00
and 16:00 were typically greater than 30 µg m-3. Note that
this threshold PM2.5 value of 30 µg m-3 may not be valid
for the whole year. This campaign was in March and early April. Emissions and
radiation intensity are different in different seasons, such that the
concentrations of gaseous precursors can vary with seasons as well.
Relationship between hourly averaged AFuchs and the
PM2.5 mass concentration in Beijing. Data when AFuchs changed
rapidly were not included to avoid potential influence caused by the distance
between Wanliu station and our campaign site. NPF period, daytime
(08:00–16:00) on non-event days and undefined days, and other time are shown
as different symbols. The regression of AFuchs versus the
PM2.5 mass concentration was based on all the data. The proposed
criterion for the occurrence of NPF events, i.e., AFuchs is lower
than 200 µm2 cm-3 (the PM2.5 mass concentration is
lower than 30 µg cm3), is shadowed by light green
background.
The criterion of PM2.5 mass concentration was applied to predict NPF
events measured at the same site in Beijing in April and May 2014. Among 38
days in that campaign, 11 typical NPF events were identified. For 9 NPF
events, average PM2.5 mass concentrations during event periods were
lower than 30 µg m-3. For the other 2 events, it was 49.8 and
40.5 µg m-3, respectively. In another campaign in Beijing
during January 2016 (Jayaratne et al., 2017), 14 NPF events were observed.
Among them, 12 events occurred when the daily-average PM2.5 mass
concentration was lower than 30 µg m-3. The daily-average
PM2.5 mass concentrations on 16 non-event days were all greater than
40 µg m-3.
Conclusions
Factors governing the occurrence of NPF events in Beijing were examined using
data from a field campaign during 12 March 2016 to 6 April 2016. In these 26
days, 11 typical NPF events were observed. The rest were 2 undefined days and
13 non-event days. The new particle formation rate, J1.5, had a positive
correlation with the sulfuric acid concentration, with a fitted mean exponent
of 2.4. However, the sulfuric acid concentrations on NPF days were not
significantly higher than those on non-event days. A dimensionless criterion
proposed by Kuang et al. (2010), LΓ, was found to be applicable to
predict NPF events in most days. Theoretically, LΓ is determined
by the sulfuric acid concentration, the enhancement factor, Γ, and
the aerosol Fuchs surface area, AFuchs, together. In Beijing,
however, AFuchs alone was found to be in a good correlation with
LΓ (R2=0.88). Differently from NPF events observed at other
locations, such as Hyytiälä, the daily-maximum sulfuric acid
concentration and the enhancement factor in Beijing only varied in a narrow
range with geometric standard deviations of 1.40 and 1.31, respectively,
while AFuchs varied significantly among days with a geometric
standard deviation of 2.56. It was inferred that the concentrations of
gaseous precursors, such as sulfuric acid, in Beijing were high enough to
initiate nucleation, while it was AFuchs that determined whether a
NPF event would occur or not. An AFuchs value of
200 µm2 cm-3 was proposed as the empirical threshold in
Beijing below which NPF events are highly likely to occur. NPF events will be
suppressed when AFuchs is higher than this threshold value. The
AFuchs dominated characteristics in Beijing are different from
those at other locations, such as Atlanta, Boulder, and Hyytiälä.
Since AFuchs in Beijing was mainly governed by accumulation mode
particles (50 to 500 nm) and the normalized
dAFuchs‾/dlogdp in this size
range was relatively stable at different AFuchs levels in Beijing,
measured AFuchs had a good correlation with the PM2.5 mass
concentration (R2=0.85). Accordingly, the PM2.5 mass
concentration may also serve as a rough and simple parameter to predict the
occurrence of NPF events in Beijing. An empirical PM2.5 threshold value
of 30 µg m-3 was proposed based on data from this field
campaign and was found to also work well for other field campaigns in
Beijing.
The annual average PM2.5 mass concentration in Beijing, 2016, was obtained from the published “Bulletin of the environmental situation of Beijing in
2016” (http://www.bjepb.gov.cn/bjhrb/xxgk/jgzn/jgsz/jjgjgszjzz/xcjyc/xwfb/815044/index.html). The back trajectories were calculated using NOAA ARL HYSPLIT model
4.0 (http://ready.arl.noaa.gov/HYSPLIT.php). The other data used are listed in the tables and references.
The authors declare that they have no conflict of interest.
Acknowledgements
Financial supports from the National Science Foundation of China (21422703,
41227805, 21521064, 21377059 and 41575122) and the National Key R&D
Program of China (2014BAC22B00, 2016YFC0200102 and 2016YFC0202402) are
acknowledged. Edited by: Veli-Matti
Kerminen
Reviewed by: two anonymous referees
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