Introduction
Beijing (39∘56′ N, 116∘20′ E), the capital of China, is
one of the largest megacities in the world with more than 21 million
residents and 5.4 million vehicles in operation by the end of 2013 (Beijing
Municipal Bureau of Statistics, 2014). In the west, north, and northeast,
the city is surrounded by the Taihang and Yanshan mountains at approximately
1000–1500 m above sea level. The fan-shaped topography in addition to the
rapid urbanization has caused frequent severe haze pollution episodes in
Beijing. These conditions have received a significant amount of attention
from atmospheric scientists, the government, and the general public (Sun
et al., 2006, 2012a, 2013b, 2014; Guo et al., 2014).
For in-depth elucidation of severe urban haze formation and
particulate matter (PM) characteristics, extensive studies have been
conducted in Beijing including real-time online measurements and filter
sampling with subsequent offline analyses (Sun et al., 2006; Pope III. et
al., 2009; Zhao et al., 2013). Aerosol mass spectrometers (AMS), which are
capable of determining size-resolved aerosol compositions with high
sensitivity, have been widely deployed in Beijing and other cities in China
since 2006 (Huang, X.-F. et al., 2012; Zhang et al., 2014; Li et al., 2015).
Numerous conclusions and findings have been obtained since then, which have
greatly improved our understanding of aerosol composition, formation
mechanisms, and evolution processes (Sun et al., 2010; Xiao et al.,
2011; Zhang et al., 2012, 2014; Hu et al., 2013; Huang et al., 2013; Guo et al.,
2014; Li et al., 2015). However, most previous AMS studies
include short-term measurements of generally less than 2 months, because
of the high cost and maintenance of the instrument. The recently developed
Aerodyne Aerosol Chemical Speciation Monitor (ACSM) (Ng et al.,
2011) has been used in some studies for examining the chemical composition,
sources, and processes of atmospheric aerosols in China. The advantage of
the ACSM is its robustness for real-time long-term measurements of aerosol
particle composition with little attendance (Ng et al., 2011; Sun et al.,
2012a, 2013b, 2014; Budisulistiorini et al., 2014; Jiang
et al., 2015; Parworth et al., 2015; Petit et al., 2015). The first ACSM
measurements in Beijing highlighted the important role of nitrate in PM
pollution in summer, which was mainly attributed to the partitioning of
nitric acid into liquid ammonium nitrate particles (Sun et al.,
2012a). The PM pollution characteristics also dramatically differed between
summer and winter. Agricultural burning and photochemical production play
major roles in PM pollution in summer (Li et al., 2010; Huang, K. et al.,
2012; Sun et al., 2012a; Zhang et al., 2015), whereas coal combustion is the
dominant source of PM in winter (Sun et al., 2013b). A more detailed
analysis of a severe haze pollution episode that occurred in January 2013
suggested that stagnant meteorological conditions, source emissions,
secondary production, and regional transport are four major factors driving
the formation and evolution of haze pollution in Beijing during winter
(Sun et al., 2013b, 2014; Guo et al., 2014; Zhang et al., 2014).
Despite extensive efforts for the characterization of fine particle
pollution in Beijing, most studies are conducted at ground sites, which are
subject to significant influences of local emission sources such as traffic,
cooking, and biomass burning. In comparison, measurements obtained above the
urban canopy with much less influence of local source are more
representative for a large scale, which is of great importance for
characterizing regional transport. However, such studies in Beijing are rare
due to the absence of high platforms. The Beijing 325 m meteorological tower
(BMT) is a unique platform for measuring aerosol and gaseous species at
various heights in Beijing megacity. Moreover, this platform is beneficial
for studying the interactions of the lower boundary layer (< 300 m)
and air pollution, particularly during autumn and winter when the nocturnal
planetary boundary height is often below 300 m (Ting et al.,
2008; Zhang et al., 2013). Based on the BMT measurements, Sun et al. (2009, 2013)
reported that the SO2 concentration reached
its maximal value at 50 m during heating periods, whereas PM2.5 showed
a “higher top and lower bottom” vertical pattern due to the inversions of
temperature (T) and relative humidity (RH) during summer hazy days. Guinot et
al. (2006) and Meng et al. (2008) also determined that local
concentration peaks at 50 to 100 m were likely related to the urban
canopy. However, real-time characterization of aerosol particle composition
above the urban canopy has been performed only once (Sun et al.,
2015). The 2-week study found substantially different aerosol compositions
between ground level and 260 m. In addition, the compositional differences
at the two heights were found to be strongly associated with source
emissions, the vertical mixing mechanism, and RH/T-dependent secondary
production. Because these measurements only lasted 2 weeks, the aerosol
characteristics and sources above the urban canopy remain poorly understood.
The 2014 Asia–Pacific Economic Cooperation (APEC) summit was hosted in
Beijing during 5–11 November 2014, when strict emission control measures
were implemented in Beijing and surrounding regions to ensure good air
quality. During 3–12 November emission controls such as reducing the
number of vehicles in operation by approximately 50 %, shutting down
factories, stopping construction activities, and enhancing the cleanliness
of urban roads were gradually implemented (http://www.gov.cn/xinwen/2014-11/14/content_2778635.htm,
in Chinese). The neighboring provinces such as Hebei, Tianjin, and Shandong
implemented the same emission controls during APEC (http://www.bjepb.gov.cn/bjepb/324122/412670/index.html, in Chinese). As a
result, the PM levels in Beijing during the summit were significantly
reduced, leading to “APEC blue”, a phrase commonly used to refer to the
good air quality. However, the response of aerosol chemistry to emission
controls over a regional scale has not been investigated. Measurements above
the urban canopy are ideal for evaluating the roles of emission controls in
reducing PM levels under the condition of minimizing the influences of local
point sources.
In this study, we conduct real-time measurements of non-refractory submicron
aerosol (NR-PM1) composition including organics (Org), sulfate
(SO42-), nitrate (NO3-), ammonium (NH4+), and
chloride (Cl-) at 260 m at the BMT before and during APEC, 10 October–2 November
and 3–12 November 2014, respectively, by using an ACSM. The
aerosol composition, diurnal variation, and sources above the urban canopy
are investigated in detail. The responses of aerosol composition, particle
acidity, and sources of organic aerosol (OA) to emission controls are
elucidated by comparing the changes before and during APEC, and the roles of
meteorological conditions in PM reduction during APEC are discussed. In
addition, the vertical differences of aerosol composition and its
interactions with boundary-layer dynamics are also examined.
Experimental methods
Sampling site and measurements
All of the measurements in this study were conducted at the same site as
that reported by Sun et al. (2013b), which is an urban site at the
Institute of Atmospheric Physics, Chinese Academy of Sciences, between North
3rd and 4th Ring Road from 10 October to 12 November 2014. The
ACSM and gas measurement instruments were mounted inside a container at 260 m
on the BMT. The ACSM sampling setup used in this study is similar to that
described by Sun et al. (2012a). Briefly, aerosol particles were
first sampled into the container with a PM2.5 cyclone to remove coarse
particles larger than 2.5 µm. After passing through a diffusion
silica-gel dryer, aerosol particles were sampled into the ACSM at a flow
rate of ∼0.1 L min-1. The ACSM was operated by alternating
ambient air and filtered air with a mass spectrometer at a scanning rate of
500 ms amu-1 from m/z 10 to 150. The data were saved every two cycles,
leading to a time resolution of approximately 5 min. The detailed principles
of the ACSM can be found elsewhere (Ng et al., 2011; Sun et al., 2012a).
An Aerodyne high-resolution time-of-flight AMS (HR-ToF-AMS) was
simultaneously deployed near ground level at the same location to
measure the size-resolved NR-PM1 aerosol composition. Details of the
sampling and operation procedures of the HR-ToF-AMS are given in Xu et al. (2015).
Meteorological variables including wind speed (WS), wind direction (WD), RH,
and T at 15 heights of 8, 15, 32, 47, 65, 100, 120, 140, 160, 180, 200, 280,
and 320 m were obtained from the BMT. In addition, a Doppler wind lidar
(Windcube 200, Leosphere, Orsay, France) was deployed at the same location
to obtain the wind profiles from 100 to 5000 m with a spatial resolution
of 50 m and a time resolution of 10 min. All of the data in this study are
reported in Beijing Standard Time (BST), which is equal to Coordinated Universal
Time (UTC) plus 8 h.
Data analysis
The ACSM data were analyzed for the mass concentration and chemical
composition of NR-PM1 species including organics, sulfate, nitrate,
ammonium, and chloride by using ACSM standard data analysis software (v.
1.5.3.0). Detailed analytical procedures have been reported by Ng et al. (2011)
and Sun et al. (2012a). Similar to that of previous
studies in Beijing (Sun et al., 2011, 2012a, 2013b, 2014), an empirical and constant collection efficiency
(CE) of 0.5 was applied during the entire campaign to compensate for the
particle loss due mainly to particle bounce at the vaporizer (Matthew
et al., 2008). The CE of 0.5 is rational for this study because aerosol
particles were dried, and the mass fraction of ammonium nitrate was overall
below the threshold value (40 %) that affects CE (Middlebrook et
al., 2012). The average ratio of measured NH4+
(NH4+meas) versus predicted NH4+
(NH4+pred) was 0.56, suggesting that the aerosol particles
were acidic. Although the particle acidity would have a slightly higher CE
than 0.5 (∼0.59) if the equation CEdry= max (0.45,
1.0–0.73 × (NH4+meas/NH4+pred))
recommended by Middlebrook et al. (2012) were used, no effect
on CE is present if using the parameterization reported by Quinn et al. (2006).
For consistency with our previous studies and with
the HR-ToF-AMS measurements at the ground site, we maintained CE = 0.5 in
this study. The default relative ionization efficiency (RIE) values were 1.4 for
organics, 1.1 for nitrate, 1.2 for sulfate, and 1.3 for chloride, except
ammonium (6.5) which was determined from pure ammonium nitrate particles.
Note that the ACSM measurements were compared with those of HR-AMS at the
same location before the campaign. All submicron aerosol species measured by
the ACSM were highly correlated with those by the HR-AMS (r2 > 0.97).
Although the total NR-PM1 mass measured by the ACSM
agreed well with that by HR-AMS (r2=0.99, slope = 0.99), the
regression slopes of ACSM against HR-AMS varied from 0.61 to 1.24 for
different aerosol species. Because ACSM was found to have a larger
uncertainty in the quantification of submicron aerosol species, particularly
in the determination of relative ionization efficiency, the mass concentrations of
aerosol species measured by the ACSM at 260 m were further corrected using
the regression slopes of ACSM/HR-AMS obtained from the intercomparison
study.
Positive matrix factorization (PMF) with the PMF2.exe algorithm (Paatero
and Tapper, 1994) was performed on the ACSM OA mass spectra to resolve
potential OA components with different sources and processes. Only m/zs < 125
were included in the PMF analysis due to the large
interferences of naphthalene signals on several larger m/zs (e.g., m/z 127–129)
(Sun et al., 2012a, 2013b, 2014). The PMF results
were then evaluated using an Igor Pro-based PMF Evaluation Tool (PET, v. 2.06)
(Ulbrich et al., 2009) following procedures detailed by
Zhang et al. (2011). After careful evaluation of the mass spectra
and time series of OA factors, a 2-factor solution, i.e., an oxygenated OA
(OOA) and a hydrocarbon-like OA (HOA) with fpeak = 0.4, was chosen. More
detailed PMF diagnostics are presented in Figs. S1, S2, and Table S1 in the Supplement. While
the 3-factor solution resolved an unrealistic factor with unexpectedly high
m/z 12 and m/z 15, the 2-factor solution at fpeak = 0 showed much higher m/z 44
in the HOA spectrum, which is generally a characteristic of OOA (Fig. S3).
Air mass trajectory analyses
The 3-day (72 h) back trajectories were calculated every hour at 500 m
height using the Hybrid Single-Particle Lagrangian Integrated Trajectory
(HYSPLIT, NOAA) 4.9 model (Draxler and Hess, 1997; Li et al.,
2015). The trajectories were then grouped into four clusters before and
during APEC using the algorithm of cluster analysis. The clustering of
trajectories is based on the total spatial variance (TSV) method (Draxler et
al., 2012). This method minimizes the inter-cluster differences among
trajectories while maximizing the inter-cluster differences, which has been
widely used in previous studies (Sun et al., 2014; Zhang et al., 2014; Li
et al., 2015).
Evolution of vertical profiles of (a) wind speed (WS) and
(b) wind direction (WD) from the measurements of the Doppler wind lidar. The
time series of NR-PM1 (i.e., Org + SO42-+ NO3-+
NH4++ Cl-) is shown as the black line in (a). The
shaded area refers to the APEC period (same for following figures).
Results and discussion
General description
Submicron aerosol and meteorology
The NR-PM1 mass concentration varied significantly from 0.7 to 254 µgm-3,
with an average of 53.5 µgm-3. As indicated in Fig. 1,
the variations of NR-PM1 were strongly associated with WD and WS.
The formation of severe haze episodes was generally initiated by a WD change
from northerly to southerly and a decrease of WS to less than 5 m s-1
below 1 km. The southern air flow and low WS were then dominant most of the
time during the evolution of the haze episode; subsequently, the air masses
changed from the south to the north/northwest, leading to a rapid decrease
of PM level in a few hours. Haze episodes with such life cycle driven by
meteorological conditions have also been observed many times in Beijing
(Jia et al., 2008; Sun et al., 2013b, 2014; Guo et al., 2014).
Note that a mountain–valley breeze lasting approximately half a day was
frequently observed throughout the study, which reduced the daytime PM
levels to a certain degree. As shown in Fig. 1, most of the cleaning
processes were similar, all driven by the switch of air masses from
south/southwest to north/northwest associated with high WS across the entire
vertical layer (> 5 m s-1). However, the cleaning process
that occurred on 20–21 October was different. As the WD changed from the south
to the northwest/northeast, the NR-PM1 concentration remained high.
This phenomenon can be explained by the low WS (< 4 m s-1)
below 500 m and the high RH (Figs. 2, S4). The NR-PM1 began to decrease
at ∼ 20:00 as WD shifted to the south associated with a
decrease in RH. This result indicates that a cleaner and drier air mass was
located to the south of Beijing during this stage. Such a cleaning process
by southern air flow is not common and is generally weaker than that by
northern/northwestern flow. This observation is supported by the higher
NR-PM1 concentration of ∼ 20 µgm-3 on 21 October
compared to during other cleaning periods at ∼ < 5 µgm-3.
The average mass concentration of NR-PM1 during APEC was 24.1 µgm-3,
which is significantly lower than the 65.1 µgm-3 recorded before APEC, indicating a large reduction of PM during
APEC. In addition, the southern air mass occurred less frequently and had a
shorter duration during APEC. These results manifest that meteorology, in
addition to emission controls, might have played an important role in
reducing PM levels during APEC.
Time series of (a) T, (b) RH, (c) WS and
WD, and (d) concentrations of NR-PM1 species (Org, SO42-, NO3-, NH4+,
and Cl-), and (e) mass fraction of each species in NR-PM1. Two
clean periods and five haze episodes are marked in (d) for further
discussions. The meteorological parameters in this figure were all from the
tower measurements.
The NR-PM1 species showed similar and dramatic variations to the total
NR-PM1 mass (Fig. 2). In particular, three haze episodes before APEC
(Ep1, Ep2, and Ep3 in Fig. 2d) and two episodes during the summit (APEC1 and
APEC2 in Fig. 2d) were observed in this study. The three episodes before
APEC were all characterized by high RH at 48–70 % and low WS at 2.3–3.4 m s-1,
elucidating the important roles of stagnant meteorological
conditions in severe haze formation. In comparison, the RH in the two
episodes during APEC was lower at 34–38 %, and the WS was comparably
higher at 3.1–3.8 m s-1 (Table 1). These results suggest that the
meteorological conditions during APEC appeared to be more favorable for the
dispersion of pollutants. Indeed, clear accumulation processes of aerosol
species were observed for three episodes before APEC, yet they were much
weaker during the summit. However, the two episodes during APEC showed
obvious temperature inversions, which inhibited the vertical convection of
pollutants. The meteorological conditions during haze episodes differed
substantially from those during clean periods, which were characterized by
high WS at > 5 m s-1 and low RH at < 20 %.
Summary of average meteorological variables for different periods
and the mass differences of aerosol species between the ground site and 260 m
(i.e., ground – 260 m).
Before APEC
During APEC
Entire
Ep1
Ep2
Ep3
Entire
APEC1
APEC2
Meteorological variables
RH (%)
47.1
48.4
69.7
56.7
29.8
34.2
38.5
T (∘C)
13.3
16.7
12.5
10.9
9.0
11.5
8.1
WS (m s-1)
4.0
3.4
2.3
2.3
4.9
3.8
3.1
Mass differences (µg m-3)
Org
0.7
0.3
4.5
-5.2
9.6
14.6
13.6
SO42-
3.4
3.0
8.8
1.3
1.3
1.6
1.9
NO3-
4.3
4.5
10.9
0.8
0.7
1.0
1.0
NH4+
3.9
4.2
9.0
2.3
1.6
2.9
2.3
Cl-
-0.1
0.0
-0.4
-0.2
1.0
1.7
1.5
NR-PM1
12.1
12.0
32.8
-1.1
14.1
21.8
20.2
Time series of (a) sulfur oxidation ratio (SOR),
(b) ratio of NO3-/SO42-, and (c) NR-PM1. The SOR and
NO3- / SO42- were color-coded by RH.
The NR-PM1 was dominated by organics, accounting for on average 46 %
of the total mass, followed by nitrate at 27 %, sulfate at 13 %,
ammonium at 9 %, and chloride at 5 %. The nitrate contribution ranged
from 27 to 28 % during the three episodes before APEC and from 29
to 31 % in the two episodes during APEC, which is significantly higher
than the sulfate contribution of 10–15 and 8–11 %, respectively
(Fig. 6). Although the dominance of organics in PM1 was consistent with
that in previous studies in Beijing (Sun et al., 2012a,
2013b, 2014; Guo et al., 2014; Zhang et al., 2014), the nitrate
contribution in this study was approximately twice that of sulfate and
significantly higher than previously reported values of 16 % in 2011
(Sun et al., 2013b) and 13–14 % in 2013 (Sun et
al., 2014; Zhang et al., 2014). The mass ratio of
NO3- / SO42- can be used to indicate the relative
importance of mobile and stationary sources (Arimoto et al., 1996).
Therefore, higher NO3- / SO42- in this study likely
indicates the predominance of mobile sources rather than stationary sources.
Because of the continuous increase of NOx emissions associated with a
decrease in SO2 (Wang et al., 2013), nitrate is
expected to play a more important role in PM pollution in the future. Our
results highlight that NOx emission control should be a priority in
mitigating air pollution, particularly in non-heating seasons with low
SO2 precursors.
Figure 3 further shows the time series of NO3- / SO42- mass
ratio and sulfur oxidation ratio (SOR) calculated as the molar fraction of
sulfate in total sulfur (i.e., sulfate and SO2) (Sun et
al., 2014). The NO3- / SO42- was ubiquitously greater
than 1 during five haze episodes, indicating the importance of nitrate in
the formation of severe haze pollution. Interestingly, we observed a rapid
increase in NO3- / SO42- during the formation stage of a
pollution episode, followed by a decrease in NO3- / SO42-
during the subsequent evolution stage. The variations of
NO3- / SO42- illustrates that two different formation
mechanisms might drive the formation and evolution of haze episodes. During
the early stage of haze formation, the RH was relatively low and the
formation rate of sulfate was correspondingly low, which is supported by the
low SOR values. Consequently, the nitrate formation played a dominant role
during this stage. The SO42- concentration remained consistently
low when the nitrate began to increase (Fig. 2d). As the RH continued to
increase, the SOR showed a corresponding increase, indicating that more
SO2 was oxidized to form sulfate, most likely via aqueous-phase
processing (Zhang and Tie, 2011; Sun et al., 2013a). The SO42-
concentration then showed a substantial increase, and the
NO3- / SO42- ratio decreased as a result. For example,
during Ep2, the hourly NO3- / SO42- increased from
∼ 1.1 to 4.0 during the formation stage and then decreased to
∼ 1.8 during the evolution stage. These results indicate that
SO42- played an enhanced role in PM pollution during the
evolution stage of haze episodes with high RH. Moreover, the
NO3- / SO42- ratios during clean periods
(∼ 0.3) were much lower than those during haze episodes. One
explanation is that the nitrate in clean air masses from the north/northwest is
significantly lower than that of sulfate.
(a) Mass spectra of HOA and OOA, (b) diurnal variations
of the mass concentration and mass fraction of HOA and OOA, (c) time series
of HOA, OOA, and inorganic species (SO42-, NO3-,
Cl-). The correlations of HOA and OOA with inorganic species are also
shown in the figure.
Sources and composition of OA
Two OA factors, HOA and OOA, were identified in this study. The HOA spectrum
was similar to those determined at other urban sites (Huang, K. et al.,
2012; Sun et al., 2012a, b), which is characterized by
prominent hydrocarbon ion peaks of m/z 27, 29, 41, 43, 55, and 57 (Fig. 4a). The
HOA spectrum showed a higher m/z 55/57 ratio compared with that of exhaust
aerosols from diesel trucks and gasoline vehicles (Mohr et al.,
2009), yet it had characteristics similar to those resolved in urban Beijing
(Sun et al., 2010, 2012a). The high m/z 55/57 ratio and the two
visible peaks at meal times in diurnal variations (Fig. 4b) indicate the
impact of local cooking activities (Sun et al., 2011,
2012a, 2013b). However, the two HOA peaks were much smaller than
those observed at the ground site (Xu et al., 2015), indicating a
significantly smaller impact of local cooking emissions on OA at 260 m.
Moreover, the HOA spectrum showed a considerable m/z 60 peak, a marker m/z for
biomass burning (Aiken et al., 2009; Huang et al., 2011; Zhang et al.,
2015). The fraction of m/z 60 was 0.9 %, which is much higher than
∼ 0.3 % in the absence of biomass burning. All these
results suggest that HOA was a primary OA factor combined with traffic,
cooking, and biomass burning emissions. Limited by the ACSM spectra and PMF
analysis, we were not able to separate the different primary OA factors in
this study. HOA correlated well with chloride (r2=0.61) and
moderately well with secondary inorganic species (r2=0.42–0.65),
indicating that a major fraction of HOA shared similar sources to secondary
species at 260 m, which likely came from regional transport. HOA on average
contributed 39 % of total organics, which is less than the 57 % observed
at the ground site during the same study period (Xu et al., 2015). This
result indicates a smaller impact of primary sources above the urban canopy.
The diurnal cycle of HOA was relatively flat, with two visible peaks
occurring at noon and night. The HOA contribution to OA was relatively
constant throughout the day, ranging from 36 to 43 %. This result
further supports the theory that HOA above the urban canopy came dominantly
from regional transport and was well mixed with regional secondary OA (SOA).
Indeed, the correlation of HOA with OOA in this study was quite high
(r2=0.76), supporting that HOA and OOA might have some common
sources (e.g., regional transport) at 260 m.
The mass spectrum of OOA resembles that identified in 2012 in summer in
Beijing (Sun et al., 2012a) in addition to the spectra resolved at other
urban sites (Ulbrich et al., 2009), in that it is characterized by a
prominent m/z 44 peak (mainly CO2+). OOA dominated the OA composition
throughout the day, ranging from 57 to 64 %. The average OOA
contribution to OA was 61 %, which is close to that previously reported
in Beijing (Huang et al., 2010; Sun et al., 2012a, 2013b). The
diurnal cycle of OOA was relatively flat, yet a gradual increase during the
day was also observed despite the rising planetary boundary layer,
suggesting daytime photochemical processing. OOA is often considered as a
good surrogate of SOA (Zhang et al., 2005; Jimenez et al., 2009; Ng et al.,
2011). In this study, OOA correlated well with secondary inorganic species such
as NO3- and SO42- (r2=0.72–0.90), which is
consistent with previous conclusions that OOA is a secondary species in
nature (Zhang et al., 2005; Sun et al., 2012a).
Submicron aerosol composition as a function of
NR-PM1 mass loadings (a) before APEC and (b) during APEC. The solid
line shows the probability of NR-PM1 mass.
Response of aerosol chemistry to emission controls
Aerosol composition
Figure 5 shows the variations of aerosol composition as a function of
NR-PM1 mass loading before and during APEC. The organics contribution
showed a notable decrease from 62 to 32 % as the NR-PM1 mass
concentration increased from < 10 to > 200 µgm-3
before APEC. In contrast, the sulfate contribution
showed a corresponding increase from 8 to 22 %. Except for low values
at NR-PM1 < 10 µgm-3, nitrate and ammonium
constituted relatively constant fractions of NR-PM1 across different
NR-PM1 loadings and varied at 21–31 and 8–12 %, respectively.
These results highlighted the enhanced roles of secondary inorganic species
in severe PM pollution before APEC. This observation is further supported by
a comparison of average chemical composition between three pollution
episodes and a clean event (Fig. 6). The secondary inorganic aerosol (SIA; SO42-+ NO3-+ NH4+) on average
contributed 46–51 % of the total NR-PM1 mass during the three
episodes before APEC, which is significantly higher than the 40 % reported
during the clean event (Fig. 6). The NR-PM1 mass-loading-dependent
aerosol composition showed different behavior during APEC. As shown in
Fig. 5b, all aerosol species had relatively constant contributions to
NR-PM1 at 10–100 µgm-3. The contribution of organics
ranged from 43 to 58 %, which is higher overall than before
APEC. This result indicates an enhanced role of organics during APEC,
particularly during severe PM pollution periods. Similarly, nitrate
contributed the largest fraction of NR-PM1, varying from 23 to
32 %. Figure 5 also shows a very broad range of NR-PM1 mass
concentration with the maximum concentration over 200 µg m-3
before APEC. In contrast, the range of NR-PM1 was much narrower during
APEC, suggesting a significantly lower amount of severe haze pollution
during APEC. Indeed, 93 % of the time during APEC, the NR-PM1 level
was lower than 60 µg m-3, whereas 49 % of the time before
APEC, it exceeded such a concentration level. These results indicate that the air
pollution was substantially more severe before APEC. The average mass
concentration of NR-PM1 was 24.1 µg m-3 during APEC, which
is 63 % lower than the 65.1 µg m-3 recorded before APEC (Fig. 6).
This result demonstrates a significant reduction of PM during APEC due
to emission controls and better weather conditions, including higher WS and
lower RH. However, the bulk NR-PM1 composition was rather similar
before and during APEC, both of which were dominated by organics, 46 %
versus 47 %, followed by nitrate at 27 % versus 29 %, and sulfate at
14 % versus 10 % (Fig. 6). The lower sulfate contribution during APEC
might be due to the lower RH associated with lower liquid water content,
leading to less production of sulfate. These results highlight that the
emission controls during APEC did not significantly affect the regional
aerosol bulk composition, although the mass concentrations of precursors and
aerosol species were reduced substantially. One possible explanation is the
synergetic control of various precursors such as SO2, NOx, and
volatile organic compounds (VOCs) over a regional scale during APEC. Our
results clearly imply that synergetic controls of the emissions of
precursors over a regional scale are efficient for mitigating air pollution
in north China.
Average chemical composition of NR-PM1 before and
during APEC, and also that of five haze episodes and two clean events marked
in Fig. 2.
Diurnal variations of meteorological variables (T, RH, WS,
and WD), NR-PM1 species, and OA factors before and during APEC. The
change rates during APEC (i.e., (before APEC–APEC)/before APEC × 100)
are also marked as light gray in the figure.
Diurnal variations
The diurnal variations of meteorological variables, NR-PM1 species, and
OA components before and during APEC are presented in Fig. 7. The diurnal
cycles of meteorological conditions were overall similar before and during
APEC except for lower temperatures and RH during APEC. The WS during APEC
was consistently higher than that before APEC, particularly in the morning
(04:00–12:00) and evening (18:00–22:00). Although the WD during APEC came
dominantly from the northwest at night and shifted to the south during the
day, it came mainly from the south before APEC (Fig. 2c).
The total NR-PM1 showed pronounced diurnal variation with two peaks in
the early afternoon (12:00–14:00) and late evening (20:00–22:00) that were
dominantly influenced by organics. By checking the diurnal cycles of the OA
factors, we concluded that the two peaks occurring at meal times are mainly
attributed to primary emissions such as cooking-related activities and
traffic emissions (Allan et al., 2010; Sun et al., 2011,
2012a). Compared with the diurnal cycles of OA previously observed at the
ground site in Beijing (Sun et al., 2012a), the two peaks of
organics were considerably smaller. This result indicates that local source
emissions can be vertically mixed above the urban canopy but at
substantially reduced concentrations. Our results also demonstrate that
sampling above the urban canopy is less influenced by local source emissions
and can be more representative over a regional scale.
Variations of NR-PM1 species and OA factors as a
function of (a) RH and (b) WS before and during APEC. The RH and WS were
from the tower measurements at 280 m.
SIA and OOA showed similar diurnal patterns before and during APEC, all of
which were characterized by gradual increases during the day. These results
indicate that their diurnal cycles were driven by similar formation
mechanisms before and during APEC, such as photochemical processing and
daytime vertical mixing. Higher concentrations of secondary species were
also observed at night, which might have been associated with a more shallow
boundary-layer height (Sun et al., 2012a). It should be noted that
all secondary species showed relatively constant background concentrations,
indicating that a major fraction was likely from regional transport. SIA and
OOA during APEC showed substantial reductions (45–74 %) throughout the
day compared with those before APEC, indicating that regional emission
controls played a significant role in reducing secondary species during
APEC, although the lower RH and higher WS were also important. Moreover, a
higher reduction percentage was observed between 04:00 and 12:00, when
higher mountain–valley breezes occurring routinely during APEC cleaned the
air pollutants more efficiently.
The diurnal cycles of chloride showed some differences before and during
APEC. Although it was relatively flat during APEC, chloride showed a clear
decrease in the afternoon before APEC, likely due to the evaporative loss
and dilution effects associated with higher T and the elevated boundary layer
(Sun et al., 2012a). The diurnal cycle of HOA showed a lower overall
concentration during the day except for a pronounced noon peak before and
during APEC. Considering that the peak time corresponds to lunchtime, we
concluded that it was attributed mainly to local cooking sources. In
addition, a more significant reduction in the evening peak of HOA was observed
during APEC. One explanation is that controls of heavy-duty vehicles (HDV)
and heavy-duty diesel trucks (HDDT) decreased the HOA emissions at night
during APEC.
Meteorological effects
Meteorological parameters contribute the largest uncertainties to the
evaluation of the effects of emission controls on PM reduction. Here we compared the
variations of aerosol species as a function of RH and WS before and during
APEC (Fig. 8). At low RH levels (< 40 %), all aerosol species appeared to
increase linearly as a function of RH in both periods at similar rates of
increase. Moreover, the mass concentrations of aerosol species were slightly
lower during APEC than before the summit, indicating small reductions
in aerosol species during APEC. By checking the air mass trajectories (Fig. S5),
we determined that the low RH periods were mainly associated with the
air masses from the north/northwest where fewer emission controls were
implemented during APEC. This finding explains the small reductions in
aerosol species (∼ 22 %) during APEC under the same RH
conditions. However, the variations in aerosol species showed substantially
different behaviors as a function of RH at high RH levels (> 40 %)
before and during APEC. Whereas most aerosol species continued to
linearly increase as a function of RH before APEC, they remained relatively
constant and even showed decreases during APEC. As a result, significant
reductions in aerosol species at high RH levels were observed during APEC.
The air masses during high RH periods were found to be dominantly from the
south/southeast where strict emission controls were implemented such as in
Hebei, Tianjin, and Shandong provinces. These results clearly indicate that
emission controls played a major role in PM reduction during APEC and that
the control effects tended to be more efficient under higher RH periods. The
primary HOA and chloride showed decreases when the RH was > 60 %,
indicating that humidity has a significantly lower impact on primary
aerosols than secondary components at high RH levels.
The mass concentrations of aerosol species showed a strong dependence on WS
before and during APEC. For example, the total NR-PM1 mass was
decreased by ∼ 80 % from ∼ 100
to < 20 µg m-3 as WS increased to 7 m s-1
before APEC. These results indicate that wind is efficient in cleaning air
pollutants in Beijing, which is consistent with previous conclusions
(Han et al., 2009; Sun et al., 2013b). In comparison, the
decreasing rates of aerosol species as a function of WS were lower during
APEC. As a result, aerosol species showed the largest concentration
differences before and during APEC in periods with low WS. As indicated by
the wind increase plots in Fig. 9, low and high WS levels were mainly associated
with southern/southeastern and northern/northwestern winds, respectively.
These results further indicate that larger reductions of aerosol species
occurred in Beijing when air masses were from the south.
Wind rose plots (a) before APEC and (b) during APEC.
Back trajectory analysis
Figure 10 presents the average chemical composition of NR-PM1,
corresponding to four clusters before and during APEC, determined from the
cluster analysis of back trajectories (Draxler and Hess, 1997). The air
masses before APEC were predominantly from the south/southeast at 54 % of
the time (C1 in Fig. 10a), and the aerosol loading was the highest (96.7 µg m-3)
among the clusters. Comparatively, the northwesterly
clusters (C3 and C4 in Fig. 10a) presented significantly lower aerosol
loadings at 8.3 and 3.5 µg m-3, respectively,
with fewer frequencies of 14 and 11 %, respectively. Such large
differences in aerosol loadings between the northerly and southerly air
masses are consistent with the spatial distributions of anthropogenic
emissions such as SO2, NOx, and BC (Zhang et al., 2007; Lu et
al., 2011). Although the areas to the north/northwest of Beijing are
relatively clean with low emissions of anthropogenic primary pollutants, the
south/southeast regions are characterized by substantially higher emissions.
In addition, 21 % of the air masses originated from the west and showed
moderately high NR-PM1 mass at 55.4 µg m-3. It should be
noted that the air masses from the south were often stagnant, as indicated
by their shorter trajectories that played an important role in
facilitating the accumulation of pollutants. The aerosol composition varied
significantly among four clusters, reflecting the variety in chemical
characteristics of aerosol particles from different source regions. The
aerosol particle composition from the southeastern and western clusters (C1
and C2) were dominated by nitrate at 27 and 30 % and by OOA at 26 and
32 %, respectively, with considerable contribution from sulfate at 14
and 10 %, respectively. These results elucidate the dominant roles of
nitrate and OOA in severe PM pollution before APEC, which differs
significantly from previous studies that reported that sulfate was generally
more prevalent than nitrate (Huang et al., 2014; Sun et al., 2014). These
results also highlight very different pollution characteristics during the
late fall season compared to winter. In comparison, the nitrate
contributions were significantly lower, at 17 and 8 %, in the two
northwestern clusters (C3 and C4), associated with an enhanced contribution
of sulfate at 19 and 21 %, respectively. Moreover, the cleanest
cluster (C4) showed a dominant contribution of organics at 64 %,
indicating the important role of organics during clean periods (Sun et
al., 2010, 2013b).
The average NR-PM1 composition for each cluster (a) before and
(b) during APEC. The numbers on the pie charts refer to the
average total NR-PM1 mass for each cluster. In addition, the number of
trajectories and corresponding percentages of the total trajectories are also shown in
the legends.
Comparisons of time series of total NR-PM1 mass and
NR-PM1 species between 260 m and ground level.
The air masses during APEC showed changes, particularly the increases in
frequency of two northwestern clusters (C1 and C4), which was 40 % of the
time compared with 25 % before APEC (Fig. 10b). These two clusters showed
similar bulk aerosol compositions to those before APEC yet with reductions
of the total NR-PM1 mass loading at nearly 40–50 %. The air masses
during APEC were dominated by cluster 3 (C3 in Fig. 10b). Although C3
originated from the north of Beijing, it circulated around the south of
Beijing including Baoding, a polluted city in the Hebei province, before
arriving at the sampling site. As a result, C3 presented the highest aerosol
mass loading, at 44.0 µg m-3, composed primarily of nitrate and
OOA at 30 and 29 %, respectively. Moreover, cluster 2 (C2 in Fig. 10b),
originating from the northwest, showed a similar aerosol composition,
yet had a ∼ 50 % decrease in total mass compared to C3. One
explanation is that air masses in C2 passed through western Beijing,
which is relatively clean compared to the southeastern regions. As shown in Fig. 10,
similar clusters before and during APEC showed ubiquitous reductions in
NR-PM1 mass during APEC, indicating that emission controls played an
important role in PM reduction. Moreover, the decreases in frequency of
southern/southeastern air masses during APEC also helped to alleviate the PM
level for the entire period, thus achieving the “APEC blue” effect.
Emission controls in surrounding regions south of Beijing should be taken as
a priority for the mitigation of air pollution in Beijing.
Vertical differences: insights into emission controls and
boundary-layer dynamics
Figure 11 shows a comparison of the time series of NR-PM1 species
between 260 m and the ground level for the entire study. All submicron
species showed overall similar variations at the two different heights,
indicating their relatively similar sources and evolution processes.
However, large vertical differences in aerosol composition were also
frequently observed, illustrating complex vertical gradients of aerosol
species caused by multiple factors such as local emissions, regional
transport, and boundary-layer dynamics. The average compositional
differences before and during APEC are shown in Fig. 12. Although the
concentration difference in NR-PM1 was similar before and during APEC, at
12.1 and 14.1 µg m-3, respectively, the
composition differed significantly. SIA dominated the compositional
difference before APEC, together accounting for 95 % of the total
NR-PM1 mass. In comparison, organics and chloride showed minor vertical
differences (< 5 %). These results indicate different sources and
formation mechanisms between SIA and organic aerosol. During APEC, the
compositional difference was dominated by organics, accounting for 68 % on
average, and the contribution of SIA was largely reduced to 25 %. These
results suggest that emission controls over regional scales affect the
composition differences between ground level and the urban canopy. As
discussed in Sect. 3.2 and by Xu et al. (2015), secondary species
including SIA and SOA showed significant reductions at both ground level and
260 m during APEC as a result of emission controls. Although primary OA
showed similar reductions as those of SOA above the urban canopy, the
changes remained small near ground level. Thus, the largest organic
difference during APEC was mainly caused by local primary source emissions.
Average chemical composition of the difference between
ground level and 260 m (a) before APEC and (b) during APEC. The “1 %” in
the box indicates a lower concentration of chloride at the ground site compared to at 260 m.
Evolution of vertical profiles of meteorological
variables (WD, WS, RH, and T) and NR-PM1 concentration at 260 m and
at the ground site during two pollution episodes (a) Ep2 and (b) APEC2. The
vertical profiles of wind speed and wind direction were from the
measurements of the Doppler wind lidar, and those of RH and T were from the
tower measurements. The white areas in the figure indicate that the data
were not available.
The vertical differences in aerosol composition also varied largely among
different haze episodes. As indicated in Fig. 11 and Table 1, Ep3 presented
the smallest vertical differences for all aerosol species, indicating a
well-mixed layer below 260 m. The WS was consistently low at < 2.5 m s-1
across the different heights, and the WD was predominantly from the
south during Ep3. Moreover, the vertical profiles of extinction showed an
evident reduction in pollution from ∼ 2 km to the ground on
28 October, leading to the formation of Ep3 (Fig. S6). Such boundary-layer
dynamics would produce a well-mixed layer in the lower atmosphere, leading
to minor chemical differences between the ground level and 260 m.
Comparatively, the vertical evolution of Ep2 differed significantly (Fig. 13a).
The mass concentrations of all aerosol species between the ground
level and 260 m were similar during the formation stage of Ep2, from 23 October
to 09:00 24 October. However, although aerosol species near ground
level showed large increases after 09:00 on 24 October, they remained
relatively constant at 260 m, leading to the largest vertical concentration
gradients among five episodes. The average NR-PM1 at 260 m was 143.4 µg m-3,
which is 38 % lower than that at the ground site. By
checking the vertical profiles of meteorological variables, we observed a
clear temperature inversion between 120 and 160 m that formed during
00:00–09:00 on 24 October. Such a temperature inversion formed a stable layer
below ∼ 200 m and inhibited the vertical mixing of air
pollutants between the ground and 260 m. In addition, the stagnant
meteorological conditions as indicated by low WS and high RH further
facilitated the accumulation of ground pollution. It should be noted that
the aqueous-phase processing, most likely fog processing under the high RH
conditions (often > 90 %) during this stage, also played an
important role in the increase of SIA, particularly sulfate. This finding is
also supported by the significant increase of SOR during this stage (Fig. 3).
The evolution of the severe Ep2 was terminated at approximately 00:00 on
26 October when the WD changed from south to northwest. Although the mass
concentrations of aerosol species at 260 m began to show rapid decreases at
that time, the concentration at the ground site decreased significantly
after 4 h. The different cleaning processes between 260 m and the ground
level are closely linked to the vertical profiles of meteorological
variables. As indicated in Fig. 13a, a strong temperature inversion below
320 m was observed during the cleaning period, which resulted in a
significantly higher WS and lower RH at 260 m than those at ground level.
Indeed, both WS and RH showed clear shears during the cleaning period,
suggesting a gradual interaction between the northern air mass and boundary
pollution from top to bottom. Such an interacting mechanism resulted in a
time lag of approximately 4 h in cleaning the pollutants at ground level
compared to that at 260 m. Similar interactions between boundary-layer dynamics and
aerosol pollution were also observed on 1, 5, and 11 November.
The evolution of vertical differences during APEC differed from those in
three episodes before APEC. As shown in Fig. 13b, frequent mountain–valley
breezes were observed during 8–11 November (APEC2). The northwest
mountain–valley breeze began routinely at approximately midnight and
dissipated at approximately noon. The NR-PM1 aerosol species showed
direct responses to the mountain–valley breeze, which was characterized by
similar routine diurnal cycles. All aerosol species began to decrease at
midnight because the cleaning effects of mountain–valley breeze reached
minimum concentrations at noon, then increased continuously when the WD
changed to south. The mountain–valley breeze also caused a unique diurnal
cycle of vertical differences. As shown in Fig. 13b, aerosol species were
well mixed within the lower boundary layer between 12:00 and 16:00, and the
concentrations between 260 m and the ground level were similar. However, the
differences in concentration began to increase when the boundary-layer
height decreased after sunset at ∼ 18:00, and the differences
were maximum at midnight when the NR-PM1 mass approached
100 µg m-3. A detailed investigation of the evolution of aerosol species showed that
such vertical differences in NR-PM1 were caused mainly by organics from
local primary sources (Xu et al., 2015; Fig. 11). These results indicate
that local source emissions played a more important role in PM pollution
near ground level during APEC. The concentration differences in NR-PM1
began to decrease with the occurrence of the mountain–valley breeze and
reached a minimum at noon. Our results revealed the important role of
mountain–valley breeze in affecting the boundary-layer structure and
reducing the daytime PM levels during APEC. It was estimated that the
mountain–valley breeze caused a reduction in NR-PM1 concentration of
approximately 50 µg m-3 at the ground site during the day on
10–11 November (Fig. 13b). Therefore, our results illustrated that the
achievement of “APEC blue” was also due partly to meteorological effects,
particularly the mountain–valley breeze, in addition to emission controls.
Conclusions
We have presented a detailed characterization of aerosol particle
composition and sources above the urban canopy in Beijing from 10 October to
12 November 2014. This study is unique because it examines strict emission
controls implemented during the 2014 APEC summit and synchronous real-time
measurements of aerosol particle composition at 260 m and near
ground level obtained by two aerosol mass spectrometers. The NR-PM1
composition above the urban canopy was dominated by organics at 46 %,
followed by nitrate at 27 %, and sulfate at 13 %. The high contribution
of nitrate and high NO3- / SO42- mass ratios illustrates
the important role of nitrate in PM pollution during the study period. This
result has significant implications, namely, that NOx emission controls should
be prioritized for the mitigation of air pollution in Beijing, particularly
in non-heating seasons with low SO2 precursors. The OA above the urban
canopy was dominated by OOA at 61 % and included HOA at 39 %. Different
from that at the ground site, HOA correlated moderately with OOA above the
urban canopy, indicating similar sources, likely through regional transport.
With the implementation of emission controls, the mass concentrations of
aerosol species were shown to have decreased significantly by 40–80 %
during APEC, whereas the bulk aerosol composition was relatively similar
before and during APEC. Organics were dominant before and during the summit,
at 46 % versus 47 %, respectively, followed by nitrate at 27 % versus
29 %, and sulfate at 14 % versus 10 %, respectively. Our results
suggest that synergetic controls of various precursors such as SO2,
NOx, and VOCs over a regional scale would not significantly affect
regional aerosol bulk composition, although the mass concentrations would be
reduced substantially. By linking aerosol compositions and sources to
meteorological conditions, we determined that meteorological parameters,
particularly mountain–valley breezes, played an important role in
suppressing PM growth and hence reducing PM levels during APEC. Our results
elucidated that the good air quality in Beijing during APEC was the combined
result of emission controls and meteorological effects, with the former
playing the dominant role. We further investigated the vertical evolution of
aerosol particle composition by comparing the aerosol chemistry between the
ground level and 260 m. We observed very complex vertical differences during
the formation and evolution of severe haze episodes which were closely
related to aerosol sources (local versus regional) and boundary-layer
dynamics. Although a stable T inversion layer between 120 and 160 m
associated with stagnant meteorology caused higher concentrations of aerosol
species at the ground site, the interaction of boundary-layer dynamics and
aerosol chemistry during the cleaning processes resulted in a lag time of
approximately 4 h in cleaning pollutants near ground level compared to
processes that occurr above the urban canopy.