Introduction
Aerosols are relatively stable suspensions formed by
micro-liquid and micro-solid particles that are uniformly
distributed in the air (Seinfeld and Pandis,
1998). Atmospheric aerosols can directly change the balance
and distribution of global radiation by scattering or
absorbing sunlight, and they can also affect the formation of
clouds and fog (as condensation nuclei) and indirectly
affect the global climate (Shine and Forster, 1999; Myhre
et al., 2001; IPCC, 2007). Furthermore, atmospheric aerosols
are carriers of photochemical reactions and provide good
reaction beds for chemical reactions; therefore, they promote
the occurrence of atmospheric photochemical reactions
(Seinfeld and Pandis, 1998). Because of their small radii and
high specific areas, atmospheric aerosols can easily
accumulate as hazardous material and can be absorbed by human
bodies, where they are deposited in the lungs and threaten human
health (Englert, 2004; Campbell et al., 2005; Peters, 2005;
Auger et al., 2006).
Observation sites and topography over northern China.
With the rapid economic development of China, the amount of
industrial products and the number of vehicles
increase year by year, thus leading to an increase of energy
consumption (National Bureau of Statistics of China, 2014).
The North China Plain region has one of the highest global
aerosol concentrations (Lu et al., 2010). Beijing, the
economic, political and cultural center of China, is
adjacent to the Yanshan Mountains to the north and Taihang
Mountains to the west and is on the north boundary of the North
China Plain (Fig. 1). This special horseshoe-shaped geographical
region provides efficient southerly transport of
pollutants to Beijing, which affects air quality (Ding
et al., 2005; Xin et al., 2010). In 2012, China promulgated
the Air Pollution Prevention and Control Action Plan to
prevent and control air pollution, and the details were
disseminated in September 2012. The key control region
for air pollution is the North China Plain, which contains
Beijing, Tianjin and Hebei. The coordinated prevention and
control of pollution in this region have been proposed (State
council, 2013).
Although coordinated regional prevention and control have been
proposed for many years, it is difficult to obtain evidence and
quantify the intensity of regional transport solely based on
ground observations. Thus, reductions in regional emissions
have not been implemented. Previous studies attempted to use air
quality models to quantify the intensity and height of regional
transport (Wu et al., 2011). However, the vertical gradient of
air pollutants was not measured to test the model; therefore,
the results are not reliable. Thus, it is of great importance
to measure the vertical gradient of air pollutants to quantify
the intensity and height of the regional transport.
Studies of the vertical distribution characteristics of
atmospheric aerosols include layered observations from
meteorological observation towers, mooring boats, airplanes,
ground remote sensing and satellites, and such data can be
utilized for exploration and measurements of different spatial
regions from near the surface to the free atmosphere. Using
these observation methods to study the vertical gradient, the
effects of sand storms (Zhang et al., 2006; McAuliffe and Ruth,
2013), volcanic eruptions (Emeis et al., 2011), and
anthropogenic sources (Tesche et al., 2007; Kamp
et al., 2008; Zhang et al., 2009; Hänel et al., 2012; Sun
et al., 2013) on the atmospheric environment have been
evaluated in several countries. However, such studies in
northern China remain at the initial stages. Using the airplane
observation method, Zhang et al. (2006) classified the origin
of atmospheric aerosols in Beijing and showed that they are
primarily affected by sand storms, southerly transport and
local emissions. Their airplane data were used to determine
the concentration of aerosol particles and vertical
distribution characteristics of particle radii in the Beijing
area during the periods when atmospheric aerosols are mainly
affected by anthropogenic sources. Zhang et al. (2009) also analyzed
the causes of vertical aerosol distribution under different
meteorological conditions by considering meteorological
factors. Guinot et al. (2006) and Sun et al. (2013) used the
layered meteorological observation method to show variations
in the vertical gradient of air pollutants during periods of
heavy pollution. Although the aforementioned studies analyzed
the vertical variation of aerosols in the Beijing area, the
results are not ideal because they have low resolution,
small sample size and low observational height; they are
unrepresentative; and they lack evidence for regional transport. In
recent years, satellite observations have become increasingly
important in investigations of atmospheric aerosol
profiles. In addition, satellite observations provide reliable
results compared with ground remote sensing (Wu et al., 2014).
However, the resolution of the satellite observation method is
very low because of short passing time. Therefore, surface remote
sensing is the best method to acquire the continuous vertical
structure of atmospheric aerosols at high resolution.
The Asia-Pacific Economic Cooperation (APEC) summit was held
from 3 to 11 November 2014 in Beijing, and it was important to
ensure good air quality to provide for a successful
summit. Thus, the governments of Hebei province, Tianjin city,
Shanxi province, Inner Mongolia Autonomous Region, and Shandong
province cooperated with the government of Beijing to increase
the intensity of emission reductions for the entire region of
northern China during the APEC summit, and a series of emission
reduction methods were conducted. Consequently,
more than 460 businesses with high emissions in Beijing
were required to stop or limit their production during 3–12 November 2014.
The number of private vehicles in operation during the same
period was reduced by 50 % through an
odd/even-number-plate rule. Further, 9298 enterprises were suspended,
3900 enterprises were ordered to limit production, and
more than 40 000 construction sites were shut down in all six of the
provinces, cities and autonomous region. Additionally, when the heating supply
began to run extensively after 15 November, there was also
a slight difference in emissions in the time periods
before and after APEC. Therefore, the implementation of these
emission variability methods resulted in significant variations
in regional transport and local pollutant contributions.
In this study,
a lidar ceilometer was used to determine the mixing-layer height and
the attenuated backscattering coefficient before and after APEC
(15 October to 30 November 2014). The values for fine particulate matter
(PM2.5) and aerosol optical depth (AOD) were
combined, and the present study tested and compared the
attenuated backscattering coefficient measured by the lidar
ceilometer from 15 October to 30 November 2014. By applying
visibility as an index to classify the degrees of air pollution,
the vertical gradients of the attenuated backscattering coefficient
were analyzed during multiple pollution episodes to determine
the origin of atmospheric pollution for different degrees of air
pollution. Afterwards, changes in the attenuated backscattering
coefficient profiles before, during and after APEC (BAPEC, DAPEC
and AAPEC, respectively) reflect the causes of variation
under different pollution conditions and relative contribution
of regional transport and local emissions in DAPEC.
Finally, three typical pollution episodes were analyzed in
BAPEC, DAPEC and AAPEC to show the origin of
atmospheric pollution under different pollution conditions in
Beijing and the effects of the emission reduction methods in
DAPEC. The results strengthen our knowledge of
pollution formation and development in the Beijing area and
provide a scientific basis for the control of air pollution in
Beijing.
Methods
Measurements of attenuated backscattering coefficients
An observational station (BJT) was built in the Tieta courtyard of
the Institute of Atmospheric Physics of the Chinese Academy of
Science (west of Jiandemen, Haidian district,
Beijing) (Fig. 1). The station was between North Third Ring Road
and North Fourth Ring Road, and route G6 was on the east side. The
geographic location of the station was 39.97∘ N,
116.37∘ E, and the altitude was 60 m.
The equipment used in this study included an enhanced
single-lens lidar ceilometer (CL51, Vaisala). This equipment
adopted the strobe laser lidar (laser detection and distance
measurement) technique (910 nm) to measure the
atmospheric attenuated backscattering coefficient profiles.
The detection distance of the CL51 ceilometer was
15.4 km, and it had a temporal resolution of
6–120 s and vertical resolution of
10 m. Because the height of the atmospheric mixing
layer barely exceeded 4 km and the concentration of
aerosols in the free atmosphere above the mixing layer
is low in the Beijing area, high detection distance was not
necessary to study the air pollution in this area. To
strengthen the echo signals and reduce detection noise, the
detection height of the ceilometer was reduced by half to
7.7 km. Additional data were obtained to smooth the
noise of detection signals by setting the temporal resolution
of detection to 16 s. To filter the noise
of the observed data, 240 m vertical, 1200 s
time smoothly averaging was applied by BL-VIEW software before
analyses (Münkel et al., 2007).
Evaluation method of attenuated backscattering
coefficients
Although aerosol concentration cannot be measured directly by a ceilometer
(Wiegner et al., 2014), the attenuated backscattering
coefficient is a good indicator of the aerosol stratification.
However, uncertainties might occur in the attenuated backscattering
coefficients measured by the lidar ceilometer, especially
above the boundary layer, where the aerosol concentration is
low (Jin et al., 2015). In addition, the attenuated backscattering coefficients
measured in the spectral region of 910 nm are influenced
by water vapor absorption, and the strength of the influence can be
highly variable in time and space (Wiegner and Gasteiger, 2015).
Therefore, the representativeness of the attenuated backscattering
coefficient must be evaluated by comparison with other observations, and
a good relationship indicates that the influence of water vapor absorption
is negligible.
PM2.5
concentrations and mixing-layer heights vs. time
from 15 October to 30 November 2014.
To evaluate the atmospheric attenuated
backscattering coefficients measured by the lidar ceilometer,
two methods based on the near-surface PM2.5
concentration and AOD column data were adopted in this
study. The reliability of measured results based on
calibration of the near-surface attenuated backscattering
coefficients was evaluated by comparing the near-surface
PM2.5 concentrations and near-surface atmospheric
attenuated backscattering coefficients. Observational
PM2.5 data were downloaded from the Chinese
Environmental Protection Administration website
(http://www.zhb.gov.cn/), and observational data at the
Olympic center (OLY), which was the closest landmark to the
observational station, were chosen for comparison (Fig. 1). The AOD
data were measured using the MICROTOPS II heliograph at BJT station (Fig. 1) when the
weather conditions were sunny and partly cloudy. Each
measurement was repeated three to five times, and the average
value was used as the mean value at each time step. Because
the waveband of the heliograph is different from the
observational range of the lidar ceilometer, the AOD at
910 nm, which is consistent with the wavelength of the
lidar ceilometer, was derived from the measured AOD at
1020 nm using the heliograph and wavelength indices of
four wave bands. The derivation method was based on Eq. (1),
where α is the wavelength index between 340 and
675 nm, and τ is the AOD:
lnα=lnτ(1020nm)-lnτ(910nm)ln1020-ln910.
Calculation of mixing-layer height
Because the particle lifetimes are long and range from several
days to tens of days, the distribution of particle
concentrations in the atmospheric mixing layer is more uniform
than that of gas-phase pollutants (Seinfeld, and Pandis,
1998). In addition, huge differences in the
concentrations of particles are observed between the mixing layer and free
atmosphere. The profile of attenuated backscattering
coefficients in the atmosphere can be analyzed to determine
the location of sudden changes caused by variations in the
attenuated backscattering coefficients, which is at the top of
the atmospheric mixing layer. The lidar ceilometer is inexpensive
and convenient and has been widely applied in observations of
the mixing-layer height (Sicard et al., 2006; Münkel
et al., 2007; McKendry et al., 2009; Emeis et al., 2012; Yang
et al., 2013; Pandolfi et al., 2013; Schween et al., 2014;
Scarino et al., 2014). In this study, the gradient method was
used to identify the mixing-layer height, and maximum negative
gradient value (-dβ/dx) of the
attenuated backscattering coefficient profile was
at the top of the mixing layer (Michael et al., 2006; Emeis
et al., 2012). Because the data are easily affected by noise
and interference from the aerosol layering structure, time or
space must be smoothly averaged before the gradient
method can be used to calculate the mixing-layer height from the
profile data (Münkel et al., 2007).
Other data
Because Beijing has a low concentration of industry and
a large amount of vehicle traffic, the emissions of
SO2 are low, while the emissions of CO are high. Thus,
the ratio of CO to SO2 may provide a partial
indication of the origin of atmospheric pollutants. The CO and
SO2 data at OLY station published by the
Chinese Environment Protection Administration were also used
to help analyze the origin of atmospheric pollutants (Fig. 1). The
observational data were downloaded from the live-updated
website published by the Chinese Environment Protection
Administration (http://www.zhb.gov.cn/).
Visibility was measured at BJT station using a Belfort Model 6000 visibility
sensor to characterize the degree of atmospheric pollution during this period.
In addition, to understand the transport characteristics of different
degrees of atmospheric pollution, wind speed and direction vertical profile data
were obtained from the international standard weather station at
Beijing Capital International Airport (ID: ZBAA) (Fig. 1). The meteorological sounding profile data were measured
twice a day at 08:00 and 20:00 LT at the ZBAA station.
Results and discussion
Overview of air pollution
During the summit, a number of controls were adopted to
guarantee good air quality in Beijing. To understand the
pollution variation tendency during this period, the
PM2.5 concentration was plotted against time using
the hourly PM2.5 concentration data from 15 October to
30 November (Fig. 2). The observation period lasted for 47 days, and
nine poor-air-quality episodes were observed, which lasted for
5.2 days on average. During each pollution episode, the
PM2.5 concentration was characterized as “slowly
accumulating and rapidly disappearing”. At the transition stage
during each pollution episode, the
pollutant concentration increased. After reaching the maximum
value, the pollutant concentration plateaued for 1–2 days and
then rapidly decreased, which
usually lasted for 4 to 6 days from the beginning of the
pollution episode to the end. This result is consistent with
previous studies (Jia et al., 2008).
PM2.5
concentrations and CO / SO2 ratios of the mixing layer at
different heights.
PM2.5
concentrations and attenuated backscattering coefficients vs. time (a)
and their correlations (b) from 15 October to 30 November 2014.
A statistical analysis of the ground concentrations of
PM2.5 and heights of the mixing layers at the same
time showed that the average PM2.5 concentration
decreased from 158.9 to 67.9 µgm-3, with
mixing-layer heights rising from 0 to 1000 m. When
mixing-layer heights rose above 1200 m, the
PM2.5 concentration suddenly decreased (lower than
35 µgm-3) and did not vary with increasing
height of the mixing layer (Fig. 3). Thus, when the mixing
layer was lower than 1000 m, the PM2.5
concentration was negatively correlated with the mixing-layer
height; when the mixing layer was above 1000 m,
the air was of good quality and the negative correlation
between the PM2.5 concentration and mixing-layer
height disappeared. Therefore, increased pollution during each
pollution episode gradually led to the accumulation of
PM2.5 above 60 µgm-3, and the
corresponding mixing-layer heights were all below
1000 m. This result indicates that the vertical
diffusion capability of the atmosphere is weak, and
atmospheric pollution in Beijing may be enhanced by local
emissions. Because the level of industry and coal pollution is
low and the number of vehicles is high in Beijing, the ratio
of CO / SO2 can reflect the contribution of local
emissions to air pollution, with higher ratios indicating
higher local contributions. The ratios of CO / SO2
show that, with decreasing mixing-layer height, the ratio of CO / SO2 gradually
increased (Fig. 3). This result also suggests that the amount of pollutants transported from other
regions gradually decreases while the local contribution
gradually increases with increasing pollution.
Characteristics of attenuated backscattering coefficients
Evaluation of attenuated backscattering
coefficients
Because the vertical distribution of atmospheric pollutants in
the convective layer can better represent the evolution
characteristics of pollution, the PM2.5 and AOD data
observed during this time period were used to compare the
near-surface atmospheric attenuated backscattering coefficient
and 0–4500 m column attenuated backscattering
coefficient, and the results could be used to evaluate the
attenuated backscattering coefficient profile measured by
the lidar ceilometer, helping us to better understand the
vertical structure of atmospheric pollution.
The overlap of the laser beam of the ceilometer and its receiver
field of view is smaller than 1 in the near range. Therefore,
the attenuated backscattering coefficient values
at a height of 100 m were chosen for comparison
with the near-surface PM2.5 concentration. The
correlation showed that the variations were generally consistent besides differences during
several peak periods (Fig. 4a), which indicates that the attenuated backscattering
coefficients at 100 m and corresponding
PM2.5 concentrations were significantly positively
correlated (R=0.89) (Fig. 4b). For the column concentration,
4500 m can generally cover the entire mixing layer;
therefore, the interference of cloud layers from 0 to
4500 m was manually removed, the atmospheric attenuated
backscattering coefficients were integrated in this region, and
the values were compared with AOD. The results showed that AOD
varied directly with the integrated attenuated backscattering
coefficient of the atmospheric column (Fig. 5a), and the
positive correlation coefficient was as high as 0.86 (Fig. 5b).
AOD values and 0–4500 m column attenuated
backscattering coefficient vs. time (a) and their correlations (b).
It is noteworthy that any comparison with other parameters
(PM or AOD) cannot lead to full agreement
as long as we cannot quantify the water vapor effect
(Wiegner and Gasteiger, 2015). Even so, the significant
correlations between the attenuated backscattering coefficients
and concentrations of PM2.5 and the AOD showed that
the vertical attenuated backscattering coefficient profile
measured by the lidar ceilometer could accurately represent
the vertical distribution of atmospheric aerosols in Beijing.
Vertical distribution of attenuated backscattering coefficients
The vertical attenuated backscattering coefficient profile and the lapse rate.
According to the average vertical gradient of the attenuated
backscattering coefficients during the period of observation, we found
clear differences between the attenuated backscattering coefficients, with
the highest values near the surface and average
values reaching 4.5 Mm-1sr-1 (Fig. 6). The vertical
lapse rate of the attenuated backscattering coefficients for
layers from 0 to 200 m was small, and the attenuated
backscattering coefficients showed limited variation; however,
the vertical lapse rate above 200 m increased and the
attenuated backscattering coefficients significantly
decreased. After reaching the maximum value at the height of
400 to 800 m, the vertical lapse rate began to decrease
gradually. Above 1000 m, the attenuated backscattering
coefficient was below 0.65 Mm-1sr-1;
at approximately 2000 m, the coefficient was lower
than 0.1 Mm-1sr-1. A vertical gradient with
high values below and low values above is consistent with the
characteristics of vertical gradient in other
cities and regions (Tesche et al., 2007; Zhang et al., 2009;
Liu et al., 2012; Cao et al., 2013; McAuliffe and Ruth, 2013),
although it is different from those regions that are
severely affected by regional transport (Noh et al., 2007).
Thus, the gradual declining trend in the attenuated
backscattering coefficient from near the surface to the upper
boundary layer also indicates that the main sources of
atmospheric aerosols are from the near-surface layers in Beijing.
Attenuated backscattering coefficients
under different pollution conditions
The vertical gradient of attenuated
backscattering coefficients under different visibility conditions.
Although the main sources of atmospheric aerosols occur in the
near-surface layers, fine particles may originate from different
locations for the different degrees of pollution of each pollution
episode. To analyze the origin of air pollution,
visibility was used as an index to indicate the
degree of air pollution and applied in the analysis of the
vertical gradient profile of the attenuated backscattering
coefficients under different visibility conditions
(Fig. 7). When the visibility was above 40 km, small
differences occurred in the vertical gradients of the
attenuated backscattering coefficients from the ground to
1.5 km, and the corresponding attenuated
backscattering coefficients were all below
2 Mm-1sr-1. With decreasing visibility, the
attenuated backscattering coefficients increased to varying degrees
from the ground to 1.0 km. The near-surface layer presented a 2.1-fold
increase from 2.4 to 7.4 Mm-1sr-1 when the visibility
decreased from 20 to 4 km, and the mean attenuated backscattering
coefficient from 0 to 1500 m presented a 1.4-fold increase from 1 to
2.4 Mm-1sr-1. In addition, the highly
polluted region shifted from 0–300 to 0–900 m,
indicating that transport in the upper boundary layer
played an important role from the clear period to the
transition period with medium haze. When the visibility
decreased from 4 to 1 km, the attenuated backscatter
coefficient near the surface varied from 7.4 to
14 Mm-1sr-1. However,
the mean attenuated backscattering coefficient from
0 to 1500 m significantly decreased from 2.4 to
1.9 Mm-1sr-1 (approximately 20 %). The
attenuated backscattering coefficient from 300 to
900 m significantly decreased, and the variation at
approximately 450 m reached the maximum value
(decreasing approximately 4 Mm-1sr-1),
resulting in a sudden shift of the near-surface high-concentration
region from 0–900 m to 0–300 m. The significant decrease in the mean column
concentration differed from the rapid increase of the near-surface
concentration. Such a phenomenon is primarily caused by the
weakened transport capability of the atmosphere during heavy
haze, which results in decreased concentrations in
the space from 300 to 900 m, and the increased contributions of
local pollutants lead to a sudden increase of pollutant
concentrations. Thus, during the transition period of air
pollution, regional transport plays an important role, and
within 0 to 600 m it is characterized by strong
regional transport. During the polluted period, local
emissions are the most important factor and determine the
accumulation rate of pollutants and pollution episode intensity.
Impact of emission controls during APEC
Meteorological conditions and atmospheric particle concentrations during BAPEC, DAPEC and AAPEC.
WS
MLH
Ventilation
Visibility
PM2.5
(ms-1)
(m)
coefficient (m2s-1)
(km)
(µgm-3)
BAPEC
2.4
502.3
1208.3
17.5
126.8
DAPEC
3.1
452.8
1400.0
29.8
51.5
AAPEC
2.6
423.9
1085.9
19.1
125.2
Attenuated backscattering profiles under different air pollution
conditions during BAPEC, DAPEC and AAPEC: (a) PM <50 µgm-3, (b) 50µgm-3<PM<100µgm-3, (c) PM>100µgm-3.
To evaluate the effectiveness of the emission reduction
strategies during APEC, the observation period was divided
into three parts: BAPEC (15 October to 2 November), DAPEC
(3 to 12 November) and AAPEC (13 to 30 November). A statistical
analysis of the PM2.5 concentration during these three
time periods (Table 1) showed that the PM2.5 concentrations
in BAPEC, DAPEC and AAPEC were 126.8, 51.5 and
125.2 µgm-3, respectively. Compared with
BAPEC and AAPEC, the PM2.5
concentration in DAPEC was decreased by
approximately 60 %. Correspondingly, the visibility was
increased from 17.5 km in BAPEC and
19.1 km in AAPEC to 29.8 km in
DAPEC, which is an increase of approximately
60 %. To evaluate the diffusion capability of the
atmosphere during these three periods of time, the
corresponding wind speeds and mixing-layer heights were
calculated. The wind speeds in BAPEC, DAPEC, and AAPEC
were 2.4, 3.1 and 2.6 ms-1, respectively, and the
mixing-layer heights were 502.3, 452.8 and 423.9 m,
respectively. Because wind speeds and mixing-layer heights can represent
atmospheric diffusion capacity in the horizontal and vertical directions,
respectively, the ventilation coefficient (wind speed multiplied by the
mixing-layer height) was used as an index to evaluate the total diffusion
capacity of the atmosphere. The ventilation coefficients in
BAPEC, DAPEC, and AAPEC were 1208.3, 1400.0 and
1085.9 m2s-1, respectively. Thus, the diffusion capability
of the atmosphere was best in DAPEC, but the
variation magnitude was far below the decreased magnitude of
the PM2.5, which indicates that coordinated regional
emission reductions might have caused the significant decrease
in PM2.5 concentration because of the similar meteorological
conditions during these three periods.
The results in Sect. 3.1 and 3.2 show that PM2.5
originates from different sources when the degree of pollution
differs. To identify the vertical gradient variations
under different pollution conditions in BAPEC, DAPEC and
AAPEC, the PM2.5 concentration was divided
as follows: 50, 50–100 and >100 µgm-3,
which represented the clean period, transition period and polluted period,
respectively. The vertical gradient variations of the
atmospheric attenuated backscattering coefficients under the
three different pollution concentrations were statistically
analyzed to obtain the attenuated backscattering coefficient
profile plots for the three periods (Fig. 8).
During the clean period, the attenuated backscattering
coefficients for BAPEC, DAPEC, and AAPEC from 0 to
2000 m were similar, and the coefficients for near
the surface were all below
1.5 Mm-1sr-1 (Fig. 8a). The near-surface attenuated
backscattering coefficients in AAPEC were
0.3 Mm-1sr-1 higher than those during other periods
because of widespread
heating after 15 November. The variation magnitude was approximately 20 %.
Because of the important effect of regional transport from 0
to 1000 m, the attenuated backscattering coefficients
were all higher during the transition period
compared with the clean period for BAPEC, DAPEC, and AAPEC,
with 1.2- to 3-fold changes at different
heights (Fig. 8b). Interestingly, compared with BAPEC and AAPEC,
greater decreases in the coefficients occurred in DAPEC
with increasing height, and at 1000 m the
value was approximately 35 and 25 % lower compared with
that of BAPEC and AAPEC, respectively. The smallest decrease
of the attenuated backscattering coefficients occurred near the
surface at only 10 %. The decreased pollutant
concentration in the upper boundary layer relative to
near the surface showed that regional
transport was an important contributor to air pollution in Beijing during the transition period.
Considering the dominant effect of regional transport during this
period and southerly flow transport in
the lower atmosphere within 300 to 900 m, the mean
attenuated backscattering coefficients in DAPEC, BAPEC,
and AAPEC were calculated to eliminate
the effect of local emission. The results showed that the
attenuated backscattering coefficient for DAPEC
decreased by 36 and 25 % relative to BAPEC and AAPEC,
respectively, which indicate that the contribution of regional transport to
atmospheric aerosols in Beijing decreased by approximately 36
and 25 %, respectively.
Attenuated backscattering
coefficients at different heights and near-surface
CO / SO2 ratios from 21 to 26 October.
Attenuated backscattering coefficients
and wind vectors for the period
21–26 October at (a) 08:00 LT on
21 October, (b) 08:00 LT on
22 October, and (c) 08:00 LT on
25 October.
Attenuated backscattering coefficients at
different heights and near-surface CO / SO2 ratios from
6 to 11 November.
Attenuated backscattering coefficients
and wind vectors for
6–11 November at (a) 20:00 LT on
7 November, (b) 20:00 LT on
8 November, and (c) 20:00 LT on
10 November.
Attenuated backscattering coefficients at
different heights and near-surface CO / SO2 ratios from
17 to 21 November.
Attenuated backscattering coefficients
and wind vectors for
17–21 November at (a) 20:00 LT on
17 November, (b) 20:00 LT on
18 November, and (c) 20:00 LT on
21 November.
Compared with the transition period, the near-surface
attenuated backscattering coefficients for DAPEC, AAPEC
and BAPEC were all greatly enhanced during the heavy-pollution
stage and began to decrease at 600 to
1000 m. The near-surface attenuated backscattering
coefficients in BAPEC and AAPEC exceeded
8 Mm-1sr-1, which was approximately twice
the variation that occurred in the transition period.
The near-surface attenuated backscattering coefficient
during the DAPEC polluted period was only 4 Mm-1sr-1,
and the increase compared to the transition period was
25 %. Compared with BAPEC and AAPEC, the
attenuated backscattering coefficients in DAPEC in the
space from 0 to 2000 m were decreased by 0 to
48 % and 0 to 54 %, respectively, and
the near-surface attenuated backscattering coefficients showed
the greatest decrease at 48 and 54 %, respectively. With
increased height, the decreasing magnitude of the attenuated
backscattering coefficients decreased gradually. The higher
decreasing magnitude near the surface relative to
the upper boundary layer indicates that
local emission contributed significantly to
air pollution during the polluted period. Considering the dominant role of local
emissions during the polluted period and using the
near-surface attenuated backscattering coefficient as
a baseline, the significant decreases in DAPEC
relative to BAPEC and AAPEC indicate that the
contribution of local emissions decreased by 48 and 54 %,
respectively.
Although a number of air pollution controls were implemented
in DAPEC, the increased heat supply was the only
difference between BAPEC and AAPEC. To evaluate the effect of
heat supply on air pollution during the heavy-haze periods in
Beijing, the near-surface attenuated backscattering coefficients
in BAPEC and AAPEC were compared, and the result showed that they
were 1.1-fold higher in AAPEC than BAPEC, which indicates that
the contribution from the heat supply to atmospheric aerosols
in Beijing is approximately 10 % during the polluted period.
Based on the above discussion, three conclusions can be drawn:
(1) the regional transport in DAPEC decreased by 25
and 36 % compared with BAPEC and AAPEC, respectively; (2) the contribution of local emissions in DAPEC
decreased by 48 and 54 % compared with BAPEC and
AAPEC, respectively; and (3) the contribution of the local heat supply to
atmospheric aerosols in Beijing was approximately 10 % during
the polluted period. Although the quantitative contributions of local and
regional areas are given, these are still rough estimates for
different episodes. Detailed contributions of local and
regional sources over northern China still need further
investigation, and additional observational and modeling
studies (although beyond the scope of the present analysis)
are suggested for further work.
Characteristics of heavy-pollution episodes
To predict the occurrence and development of air pollution under
different pollution conditions in Beijing more precisely, the
atmospheric attenuated backscattering coefficients; mixing-layer
height; ratio of CO to SO2 during BAPEC, DAPEC, and AAPEC;
and backscattering profile with
wind vectors during typical periods (Figs. 9–14) were
evaluated in a time-series plot to investigate the
characteristics and the causes of the attenuated
backscattering coefficients under different pollution conditions at
different heights.
The heavy-pollution episodes in BAPEC
and AAPEC (Figs. 9, 10, 13 and 14) showed that during the
transition periods (21–23 October and 17–18 November)
southerly flow resulted in increased
mixing-layer height and a gradual increase of the atmospheric
attenuated backscattering coefficient from near the surface
(100 m) to the upper boundary layer (300 to
900 m). From 300 to 800 m, the effect of the
southerly flow was significant, and the
pollutant concentration rapidly increased. However, during the
polluted periods (23–25 October and 19–20 November),
the southerly flow disappeared. Thus, the
mixing-layer height decreased because of the westerly and
northerly flows, and the attenuated backscattering
coefficient of the upper boundary layer began to
decrease. The reduction in mixing-layer height and relatively
low wind speed promoted an increase in near-surface
pollutants, which quantitatively accumulated during the polluted
periods. When cold, dry air masses go through Beijing,
the attenuated backscattering coefficient and CO / SO2
ratio in the lower and upper air both rapidly decreased with
the rapidly increased mixing-layer height, and the
PM2.5 in the atmosphere was significantly
decreased. Subsequently, the evolution of a pollutant episode was completed.
Although the mixing-layer height gradually
decreased, the “slow accumulation and rapid disappearance”
characteristics of the PM2.5 concentration, which were
obvious in BAPEC and AAPEC, were not clear in the
pollution episode in DAPEC (6–11 October). In
addition, variations in the PM2.5 concentration and
atmospheric attenuated backscattering coefficient appeared as
zigzag shapes, and accumulation and disappearance alternated
(Fig. 12). During the transition stage in DAPEC, the variations
of air pollutants were similar to those
of BAPEC and AAPEC. Because of the effect of the southerly
flow, the simultaneous increase in the space
from 0 to 900 m that occurred in BAPEC and AAPEC
also occurred in DAPEC (Figs. 11 and 12). In
addition, the ratio of CO to SO2 was low, indicating
that regional transport was dominant during this period. During
the polluted period, the attenuated
backscattering coefficient of the upper boundary layer in DAPEC
significantly decreases because of the disappearance of
westerly jet flows, which is consistent with what occurred in
BAPEC and AAPEC. However, the near-surface
attenuated backscattering coefficient did not show a sharp
increase (up or down), and the CO / SO2 ratio did not
increase as expected. Instead, the near-surface attenuated
backscattering coefficient decreased. Thus, during the DAPEC
polluted period, the decreased local
contribution magnitude of pollutants was insufficient to
maintain the increases of pollutant concentrations near the
surface, which resulted in a zigzag distribution of
atmospheric attenuated backscattering coefficients during
the polluted period.
Based on the above discussion, southerly flow
occurred during the transition periods (21–22 October,
7–8 November, 17–18 November) in the upper boundary layer (300
to 900 m), and it transported large quantities of
pollutants from the south to Beijing. In turn, the attenuated
backscattering coefficients from near the surface to the upper
boundary layer increased, and the abundance of pollutants in the
mixing layer increased. Pollutants transported during the daytime are
mixed with pollutants released locally by convective mixing,
and pollutants transported at night remain above the mixing
layer overnight and then move to near the surface through upper boundary layer
convection after the development of the mixing
layer. Because of the transportation effect, the variation
rate of the entire profile was relatively small and resulted
in increased column concentrations of pollutants throughout
the mixing layer, which led to the air pollution. During the polluted periods
(24–26 October, 8–11 November, and 19–21 November),
southerly flow was not significant, and it was
replaced by near-surface static winds and westerly and
northerly winds in the high layers. Because of this effect,
the near-surface attenuated backscattering coefficient
continued to increase, whereas that of the upper boundary layer
continued to decrease, resulting in increased
variation rates of the entire profile with height. The
contribution of local emissions to pollution during the polluted period
increased, and its contribution to the upper boundary layer was reduced.
Conclusions
The APEC summit was held in Beijing from 3 to
11 November 2014. During this period, six areas – including provinces, cities
and an autonomous region – near Beijing
(Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia, and
Shandong) worked together to control the air pollution by emission
reduction, so this period provided the best experimental
platform for studying regional pollution and transport. The
following conclusions have been drawn based on the attenuated
backscattering coefficient and mixing-layer height in the Beijing area as measured by lidar
ceilometer for the period 15 October to 30 November 2014.
A comparison of PM2.5 concentrations and AOD values showed that the
near-surface and 0–4500 m attenuated backscattering coefficient measured
by the lidar ceilometer was well correlated with the near-surface
PM2.5 and AOD values, respectively, indicating that the lidar
ceilometer can be used to study air pollution and indicate regional transport
characteristics of atmospheric aerosols in the boundary layer.
Air pollutants under different conditions of pollution in Beijing were from
different sources. The transition period was primarily affected
by southerly flow, and pollutant transport in the space from
300 to 900 m was significant, which
resulted in the accumulation of pollutants and air pollution
in Beijing. However, during the polluted period, the
contribution of upper-air transport is decreased, and local
contributions played an important role.
PM2.5 concentrations in DAPEC in
Beijing were affected by coordinated regional emission
reductions and decreased by approximately 60 %, and the
visibility was enhanced by approximately 60 %. During the
transition period, the concentration was mainly affected by
regional transport, and the contribution of regional
transport to aerosols in the Beijing area was decreased by
36 and 25 % compared to BAPEC and AAPEC, respectively.
During the polluted period,
the concentration was dominated by local contributions, and
the local contribution in Beijing was significantly
decreased by 48 and 54 % relative to BAPEC and AAPEC, respectively.
A comparison of the near-surface attenuated
backscattering coefficients in BAPEC and AAPEC
showed that the contribution of coal burning for heating to air
pollution during the polluted period was approximately
10 %.
Therefore, local emissions are the key factors determining
the formation and development of air pollution in the Beijing
area, and a reduction in local emissions can greatly decrease
local pollution. However, regional transport can promote air
pollution, so such processes cannot be ignored,
particularly during the transition period, which results in
enhanced intensity and increased accumulation of local
pollution. Thus, during the transition period,
emissions in areas surrounding Beijing should be reduced to
effectively control regional transport and reduce the load of
regional pollution. During the polluted period, local
emissions should be reduced to control pollution. Our results
can provide a scientific basis for emission control and
management and air pollution forecasting and prevention, and they
have the potential for use in the design and implementation of
coordinated regional reduction strategies.