Cold frontal passages usually promote quick removal of atmospheric pollutants over
North China (e.g. the Beijing–Tianjin–Hebei region). However, in the Yangtze River
Delta (YRD), cold fronts may bring air pollutants from the polluted North China Plain
(NCP), thereby deteriorating the air quality in the YRD. In this study, a cold frontal
passage and a subsequent stable weather event over YRD during 21–26 January 2015 was
investigated with in situ observations and Weather Research and Forecasting – Community
Multiscale Air Quality Modeling System simulations. Observations showed a burst of
PM2.5 pollution and an obvious southward motion of PM2.5 peaks on the afternoon
of 21 January, suggesting a strong inflow of highly polluted air masses to YRD by a cold
frontal passage. Model simulations revealed an existing warm and polluted air mass over
YRD ahead of the frontal zone, which climbed to the free troposphere along the frontal
surface as the cold front passed, increasing the PM2.5 concentration at high
altitudes. Strong north-westerly frontal airflow transported particles from the highly
polluted NCP to the YRD. As the frontal zone moved downstream of YRD, high pressure took
control over the YRD, which resulted in a synoptic subsidence that trapped PM2.5 in
the boundary layer. After the cold frontal episode, a uniform pressure field took control
over the YRD. Locally emitted PM2.5 started to accumulate under the weak winds and
stable atmosphere. Tagging of PM2.5 by geophysical regions showed that the
PM2.5 contribution from the YRD itself was 35 % and the contribution from the
NCP was 29 % during the cold frontal passage. However, under the subsequent stable
weather conditions, the PM2.5 contribution from the YRD increased to 61.5 % and
the contribution from the NCP decreased to 14.5 %. The results of this study indicate
that cold fronts are potential carriers of atmospheric pollutants when there are strong
air pollutant sources in upstream areas, which may deteriorate air quality in downstream
regions.
Introduction
Fast economic development and urbanization processes in China have led to an
increase in air pollution during the past few decades (Han et al., 2016; Chen
and Wang, 2015; Cao et al., 2015). Haze, which is formed by fine particulate
extinction, has been the most prevalent atmospheric pollution phenomenon over
China in recent years (Huang et al., 2014; Wang et al., 2017). The
fundamental cause of haze is an increase in particulate matter – especially
fine particles – with aerodynamic diameters equal to or less than
2.5 µm (PM2.5). Recently, fine particulate matter has caused
wide concern owing to its impacts on regional air quality (Z. Wang et al.,
2013), human health (Gao et al., 2017), and climate change (Rosenfeld et al.,
2014).
Densely populated city clusters in China (e.g. the Beijing–Tianjin–Hebei,
BTH, region; Yangtze River Delta, YRD; and Pearl River Delta, PRD) are
associated with heavy particle pollution (Z. Wang et al., 2013; Liao et al.,
2015; Wu et al., 2007). The two largest city clusters, BTH and YRD, are
geographically close to each other. Significant cross-border transport of
PM2.5 has occurred between BTH and YRD (Li et al., 2013). Cold fronts
promote the long-range transport of dust and anthropogenic air pollutants
(Liu, 2003; Mari, 2004) that are usually favourable for the quick removal of
atmospheric pollutants in BTH (Zhao et al., 2013; Gao et al., 2016).
Meanwhile, the YRD is located south of BTH, where cold fronts may transport
pollutants from BTH to YRD and exacerbate atmospheric pollution. This
indicates that the control of emissions in one city cluster is not sufficient
to reduce particulate pollution; joint efforts among city clusters are
crucial.
The formation mechanisms of PM2.5 pollution in China remain highly
uncertain owing to complex interactions among pollution sources, meteorology,
and atmospheric chemical processes (Guo et al., 2014). Generally, high
emission intensity, adverse meteorological conditions, secondary aerosol
formation, and the regional transport of particles are main factors
contributing to the formation of particulate pollution (Sun et al., 2013;
Wang et al., 2014; Y. Wang et al., 2013; Li et al., 2013). As anthropogenic
emissions do not vary much from day to day, particulate pollution episodes
are more often associated with adverse meteorological conditions, such as
weak surface winds, stable stratified conditions, low mixing layers, and
winds from particle source regions that transport large volumes of particles
(Tao et al., 2014; Y. Wang et al., 2013; J. Li et al., 2017). Under such
weather conditions, substantial amounts of secondary aerosols can be
generated and aggravate particulate pollution (Gao et al., 2015; Huang et
al., 2014).
Particulate concentrations have been decreasing since 2013 owing to implementation of the
Atmospheric Pollution Prevention and Control Action Plan (Wei et al., 2017). However,
particle pollution episodes remain frequent, especially in the wintertime. Under the
influence of the East Asia winter monsoon, the YRD is dominated by cold air activity in
the wintertime. If cold air activity intensified, cold fronts would intrude into the YRD.
In contrast, after a cold frontal passage, weakened winds and a stable atmosphere remain
over the YRD. A regional-scale stationary atmosphere is unfavourable for the diffusion of
pollutants and leads to haze events, a phenomenon that has been extensively studied over
East China (Yang et al., 2015; Z. Wang et al., 2013; Y. Wang et al., 2013; Leng et al.,
2016). Lin et al. (2007) suggested that long-range transport of Asian dust and upstream
air pollutants by cold fronts are important environmental issues of Taiwan during the
winter monsoon season. Liu (2003) pointed out that the major process driving Asian
pollution outflow in spring is frontal lifting ahead of south-eastward-moving cold fronts
and transport in the boundary layer behind the cold fronts. Therefore, cold fronts may
have a significant impact on air quality along its transport pathway.
In this study, we employed the Weather Research and Forecasting (WRF) mesoscale
meteorological model and the Community Multiscale Air Quality Modelling System (CMAQ) to
investigate the sources and formation processes of PM2.5 pollution during a cold
frontal passage and subsequent stable weather conditions in January 2015. We investigated
the formation processes, horizontal distributions, vertical structures, and contributions
from source regions to PM2.5 over the YRD in both synoptic patterns. Our results
highlight the reasons behind high PM2.5 episodes and source contributions to
PM2.5 over the YRD and will be helpful to policy-makers in this region.
Model description and verificationConfiguration of weather prediction model
The numerical model used in this study was the non-hydrostatic, compressible,
two-way interactive Advanced Research WRF (version 3.4; Skamarock et al.,
2008) coupled with a single-layer urban canopy model (Kusaka et al.,
2001; Chen et al.,
2004). The simulation domain includes geographical areas (e.g. East China and
the Korean Peninsula) with 10km×10 km horizontal
resolution and 220×220 grids, centred at 33.5∘ N and
118∘ E (Fig. 1). The vertical grid contains 30 full sigma levels
from the surface to 50 hPa, the lowest 20 levels of which are below 2 km to
better resolve processes within the boundary layer. The WRF interior
grid-nudging technique was used to improve meteorological fields simulation.
An 18-day simulation (from 00:00 UTC 10 January 2015 to 00:00 UTC
28 January 2015) was conducted with initial conditions (ICONs) and boundary
conditions (BCONs) from the National Centers for Environmental Prediction's
1∘ grid spacing operational Global Forecast System final analyses. To
represent a more realistic urban land type in the study area, fine-resolution
(30 s) 20-category MODIS land-use data were used.
Modelling domain and source regions. White stars denote the locations of
observation sites in Nanjing, Suzhou, and Linan.
Configuration of air quality model
The CMAQ (version 5.0.2) was applied to simulate gaseous and particulate air pollutants
using a 10 km horizontal grid spacing domain that covered East China and the Korean
Peninsula (Fig. 1), while the hourly meteorological field was provided by the mesoscale
meteorological model WRFv3.4. A period from 10 to 28 January 2015 was selected for the
simulation, with the first 9 days being the spin-up period to exclude the impacts of
uncertainties in ICONs. The ICONs and BCONs for the CMAQ simulation were obtained from
the modelling result of the Model for Ozone and Related Chemical Tracers (version 4), an
offline global chemical transport model for the troposphere (Emmons et al., 2010). The
anthropogenic emissions used in this study were provided by a mosaic Asian monthly
anthropogenic emission inventory, MIX (M. Li et al., 2017), with a horizontal resolution
of 0.25∘×0.25∘. Biogenic emissions were generated by the Model
for Emissions of Gases and Aerosols from Nature (version 2.1). The CB05 and AERO6
mechanisms were chosen for gas-phase chemistry and aerosols, respectively.
The process analysis technique introduced by Gipson (1999) was implemented in
the CMAQ modelling system to determine the contributions of both physical and
chemical processes to simulated species. The physical and chemical processes
discussed in this study include vertical advection (ZADV), horizontal
advection (HADV), vertical diffusion (VDIF), dry deposition (DDEP), cloud
processes and aqueous chemistry (CLDS), and aerosol (AERO) processes.
Observed and simulated 2 m air temperature (T), relative humidity (RH), 10 m
wind direction (Wdir), wind speed (Wspd), and surface PM2.5 concentrations from
00:00 LT 19 January 2015 to 00:00 LT 28 January 2015 at Nanjing, Suzhou, and Linan.
The integrated source apportionment method (ISAM) has been implemented in CMAQ (Kwok et
al., 2013). ISAM tracks contributions from ICONs, BCONs, and user-defined source regions
to ambient and deposited gases and aerosol particles. Currently, ISAM supports two kinds
of PM2.5 tags: a primary species tag, which tracks the primary emissions of
elemental carbon, organic carbon, sulfate, nitrate, ammonium, and other trace elements
(e.g. Cl, Na, K, Fe, Ca, Al, Si, Ti, and Mn); and a secondary species tag, which tracks
secondarily formed sulfate, nitrate, and ammonium, as well as all gaseous species
associated with secondary aerosol species formations (e.g. SO2, NO2,
NO, NO3, HNO3, HONO, N2O5, PAN, and NH3).
Model verification
The model-simulated surface meteorological parameters and PM2.5
concentrations were compared with observations obtained from Nanjing, Suzhou,
and Linan (Fig. 1). Figure 2 compares the surface temperature, relative
humidity, wind direction, wind speed, and PM2.5 concentrations between
the simulations and observations from 00:00 LT 19 January 2015 to 00:00 LT
28 January 2015. Simulations from the coupled WRF–CMAQ model appeared to
effectively reproduce the variations of meteorological parameters and
PM2.5 concentrations at the three observation sites.
Statistical comparisons between the observed and simulated
meteorological parameters and PM2.5 concentrations at Nanjing, Suzhou,
and Linan∗.
∗R is correlation coefficient, NMB is normalized mean bias, NME is
normalized mean error, T is air temperature, RH is relative humidity, Wdir is wind
direction, Wspd is wind speed, PM2.5 is PM2.5 concentration.
Some statistical metrics including the correlation coefficient (R),
normalized mean bias (NMB), and normalized mean error (NME) were calculated
to compare simulated results with observations. The NMB and NME were
calculated, respectively, by Eqs. (1) and (2):
NMB=∑i=1NMi-Oi∑i=1NOi×100%,NME=∑i=1NMi-Oi∑i=1NOi×100%,
where Mi represents the simulated value, Oi represents the
observational data, and N denotes the number of data pairs. Statistical
comparisons between the observed and simulated variables are shown in Table 1.
The correlation coefficients for meteorological parameters, except for wind direction and
wind speed at Suzhou and Linan, were found to be around 0.90. This discrepancy is likely
because the Suzhou station is located in an urban centre, and the Linan station is
located on a hill. The 10km×10 km model grid was unable to properly
represent the complicated urban canopy at Suzhou and the rolling terrain at Linan. The
correlation coefficients for PM2.5 concentrations at Nanjing, Suzhou, and Linan were
found to be 0.77, 0.68, and 0.74, respectively. This indicates that the time series
patterns of PM2.5 simulations agree well with observations. The NMB and NME for
meteorological parameters were found to be relatively small, except for wind speed and
wind direction at Suzhou and Linan. The model systematically underestimated PM2.5
concentrations by about 20 % for all three stations. This can probably be attributed
to the coarse model grid size and lower emission resolution. The NME for PM2.5 at
all three stations was found to be below 35 %, indicating that model performance was
acceptable.
Episode description
The YRD region was suffering from particle pollution in January 2015. The
field experiment was carried out from 00:00 LT 19 January 2015 to 00:00 LT
28 January 2015 at Nanjing, Suzhou, and Linan (Fig. 1). The Nanjing
observation site is located in a suburban area, the Suzhou station is located
in an urban area, and the Linan station represents the regional background
site. Observations revealed that 9-day mean PM2.5 concentrations reached
100 µg m-3 at the Nanjing and Suzhou sites. In some
high-pollution episodes, PM2.5 concentrations reached as high as
300 µg m-3 (Fig. 3).
A short-term burst of PM2.5 pollution accompanied by strong north-west winds
successively appeared in Nanjing, Suzhou, and Linan between 12:00 LT 21 January 2015 and
04:00 LT 22 January 2015 (Fig. 3). The peaks of PM2.5 concentrations reached
Nanjing, Suzhou, and Linan at 16:00, 19:00, and 21:00 LT, respectively, with a 5 h
delay from Nanjing to Linan. This process reveals that a strong north-westerly flow
brought a polluted air mass across the YRD. Synoptic maps show dense isobars at the head
of the cold front, which appeared over the north (upstream) of the YRD at 08:00 LT
21 January 2015 (Fig. 4a). At that moment, a south-westerly wind prevailed in the YRD.
Twelve hours later, the cold front moved to the East China Sea (downstream of YRD;
Fig. 4b). Meanwhile, the wind direction over the YRD shifted to the north-west, which was
favourable for the horizontal transport of air pollutants from the upstream area to the
YRD.
PM2.5 concentrations (green bars), wind speeds (Wspd, red
lines), and wind directions (Wdir, vectors) at (a) Nanjing,
(b) Suzhou, and (c) Linan.
Surface weather patterns over eastern Asia at (a) 08:00 LT 21 January,
(b) 20:00 LT 21 January, (c) 08:00 LT 23 January, and
(d) 08:00 LT 26 January.
In order to validate whether this finding was just a special case or not, further
investigations were conducted using three months (from December 2014 to February 2015) of
PM2.5 and meteorological observation data. The result showed that at least 13 cold
frontal processes transported atmospheric pollutants from the NCP to YRD in the three
months (see Fig. S1 in the Supplement). That means long-range transport of air pollutants
by cold frontal passage may be an important cause of air pollution over YRD in
wintertime; however, we did not notice it before. Note that the cold front generally
deteriorates air quality over the YRD in a short time period, but it will finally clean
the atmosphere.
After the cold frontal episode, YRD experienced a uniform pressure field for
about 3 days (Fig. 4c, d), creating conditions that were unfavourable for the
horizontal transport and vertical mixing of atmospheric pollutants (Zhu et
al., 2010). Aerosol particles gradually accumulated over the YRD under this
stable atmosphere. In order to exclude the impact of the cold front, this
study designated the stable period from 24 to 27 January 2015, when the wind
speed was relatively low but PM2.5 concentrations were extremely high
(Fig. 3), indicating that the pollution likely originated locally. On
27 January 2015, a strong cold front intruded into the YRD accompanied by
precipitation, resulting in the significant removal of PM2.5.
Results and discussion
Observations revealed that the cold front pushed polluted air masses over the NCP to YRD,
which increased PM2.5 concentration over YRD on 21 January. This finding is
reproduced by the well-evaluated WRF model. Based on this finding, we considered the
formation processes and source contributions of PM2.5 pollution over the YRD during
the cold frontal passage and the subsequent stable weather conditions.
Formation processes of high PM<inline-formula><mml:math id="M79" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> during cold frontal passage
A strong wind accompanied by high PM2.5 concentrations is favourable for the
long-range transport of aerosols. Time-averaged PM2.5 concentrations and fluxes at
the surface and 1.0 km altitude during the cold frontal passage are shown in Fig. 5.
High PM2.5 concentrations (>100µg m-3) and high wind speeds can
be observed both at the surface (Fig. 5a) and at 1.0 km (Fig. 5b), resulting in strong
PM2.5 fluxes from polluted upstream regions to downstream regions. Mean PM2.5
fluxes at the surface and at 1.0 km were 619 and 1072 µg m-2 s-1,
respectively. PM2.5 fluxes were stronger at 1.0 km than at the surface because the
wind speed was higher, while the PM2.5 concentrations were comparable to those at
surface levels. We can conclude that high altitudes are important aerosol transport
pathways during cold frontal passage; they are probably more important than surface
transport pathways.
Mean wind vectors (arrow), PM2.5 flux (coloured arrow), and
mass concentration (black contours) at (a) the surface and
(b) 1.0 km altitude from 12:00 LT 21 January 2015 to 04:00 LT
22 January 2015. The dashed red line (A–B–C) in Fig. 5b denotes the
location of the vertical cross section shown in Fig. 6. Points E and F
indicate the YRD locations shown in Fig. 6.
Vertical cross sections of PM2.5 concentration (colour-filled
contours), and equivalent potential temperature (EPT, dashed black lines),
in-plane wind vectors (arrow) where the vertical speed is multiplied by 100,
and PM2.5 flux (arrow colour), at (a) 12:00 LT 21 January,
(b) 16:00 LT 21 January, (c) 22:00 LT 21 January, and
(d) 04:00 LT 22 January. The thicker red lines in
panels (a) and (b) denote the locations of the cold front.
Figure 6 shows a vertical cross section of PM2.5 concentration,
PM2.5 flux, and equivalent potential temperature (EPT) along the aerosol
transport pathway (indicated by the dashed red line in Fig. 5b) during the
cold frontal passage through the YRD from 12:00 LT 21 January to 04:00 LT
22 January. An obvious cold front can be identified over the northern YRD
from the densely spaced EPT contours near-surface and vertical wind shear
(Fig. 6a). The EPT contours reveal a stable layer over the YRD with
isentropic tilt toward the cold air and parallel to the cold front. Wind
vectors show clear downward (upward) movements in the north (south) of the
cold front (red lines in Fig. 6a and b).
At noon (12:00 LT) on 21 January, the cold front reached the northern
boundary of the YRD accompanied by high PM2.5 concentrations (>100µg m-3) and strong PM2.5 fluxes
(800–1600 µg m-2 s-1; Fig. 6a). At the southern end of
the cold front, the vertical extent of the high PM2.5 concentrations
(100 µg m-3) reached 2.0 km, significantly higher than the
boundary layer height (around 0.6–0.8 km, not shown in Fig. 6a). Therefore,
the vertical transport of PM2.5 is inferred to be caused by systematic
prefrontal upward movements rather than boundary layer turbulent mixing.
Surface PM2.5 concentrations exceeded 100 µg m-3 over
the YRD before the cold front's arrival. When the cold front moved into the
YRD, it forced the warm and polluted YRD air mass ahead of the frontal zone
up along the frontal boundary, lifting PM2.5 into the upper air (Ding et
al., 2009). Liu (2003) suggested that this kind of frontal lifting promotes
the transport of pollution to the free troposphere.
Vertical profiles of PM2.5 concentrations and the contributions of
physical/chemical processes over the centre of the YRD (from 30 to 33∘ N) to
PM2.5 concentrations (a) at the beginning and (b) at the end of
the cold frontal period.
In the afternoon (16:00 LT) of 21 January, the cold front intruded into the YRD
(Fig. 6b). A deep neutral condition (see Fig. S2) appeared over the YRD because of the
strong wind. The high PM2.5 concentration zone moved south alongside the cold front.
Aerosols from the NCP were transported to the YRD by strong north-westerly frontal
airflow, and hence increased aerosol concentrations and fluxes over the YRD.
At the end of the cold frontal period (Fig. 6c, d), when the frontal zone moved
downstream of the YRD, the YRD was under a high-pressure system that resulted in
divergence (e.g. the vertical PM2.5 flux at 1.0 km was about
-0.9µg m-2 s-1, and at 0.5 km was about
-0.5µg m-2 s-1). Synoptic subsidence behind the frontal zone
would suppress the upward transport of PM2.5, increasing the surface particle
concentration (Mari, 2004). Up until the next morning (04:00 LT 22 January), high
PM2.5 concentrations were primarily restricted to below 1.0 km over the YRD
(Fig. 6d), because the downward motion behind the frontal zone trapped air pollutants in
the boundary layer. Additionally, an extremely strong southward PM2.5 flux (>1800µg m-2 s-1) can be identified over the YRD, indicating the
transport pathway of PM2.5 (Fig. 6c). The high concentration of PM2.5 that
appeared over both the YRD and its downstream regions was probably due to the mixing of
locally emitted particles with those brought by the cold front from the NCP.
A process analysis technique was introduced to evaluate the effects of
physical and chemical processes on aerosol vertical distributions over the
YRD. Figure 7 shows the profiles of the averaged PM2.5 concentrations
and the contributions of VDIF, AERO, ZADV, and HADV processes over the centre
of the YRD (from 30 to 33∘ N, including Shanghai, south of Jiangsu,
and north of Zhejiang, since the whole YRD is larger than the frontal zone)
to PM2.5 concentrations during the cold frontal passage. At the
beginning of the cold front period (12:00 to 16:00 LT 21 January), the
centre of the YRD was located ahead of the frontal zone, and the
contributions of vertical advection processes to PM2.5 concentrations
were negative (decreased aerosol concentrations) below 1.0 km, but positive
(increased aerosol concentrations) between 1.0 and 2.5 km (Fig. 7a). This
supports the previous conclusion that vertical motions ahead of the frontal
zone lifted particles from the boundary layer to the free troposphere.
The horizontal advection process increased PM2.5 concentrations below
1.0 km but decreased PM2.5 concentrations above 1.0 km. Through the
horizontal advection process, the cold air mass brought aerosols from the NCP
to the YRD, increasing the surface aerosol concentration over the YRD. The
negative contribution of horizontal advection above 1.0 km was probably due
to aerosol concentrations being increased by strong prefrontal lifting that
transported aerosols from the surface to the free troposphere, thus
strengthening the outflow of free-tropospheric aerosols from the YRD. The
vertical diffusion process has a relatively small effect on aerosol vertical
distributions except for in the first layer, where most of the emissions
exist. Vertical aerosol concentrations were slightly increased through
secondary aerosol formation.
Averaged PM2.5 flux (coloured arrows) and mass concentrations
(black contour) at (a) the surface and (b) 1.0 km altitude
from 00:00 LT 24 January 2015 to 00:00 LT 27 January 2015.
The profiles of averaged PM2.5 concentrations and the contributions of
physical and chemical processes to PM2.5 concentrations over the centre
of the YRD at the end of the cold frontal period (22:00 LT 21 January to
04:00 LT 22 January) are shown in Fig. 7b. The vertical advection process
made positive contributions to PM2.5 concentrations in the lower
atmosphere but negative contributions in the upper atmosphere – the opposite
of the result obtained at the beginning of cold frontal passage. This result
indicates that divergence behind the frontal zone (Fig. 6c, d) transports
particles from the lower free troposphere to the boundary layer. The
contributions of the horizontal advection process were negative between the
surface and the free troposphere, implying a net horizontal outflow of
aerosols from the YRD. At this time, the region upstream of the YRD was
cleaner than the YRD itself.
Formation processes of high PM<inline-formula><mml:math id="M146" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> concentrations under stable
weather
After the cold frontal episode, aerosol particles started to accumulate under a stable
atmosphere that resulted in high PM2.5 concentrations in the near-surface layer over
east China (Fig. 8a). In the centre of the YRD, the mean PM2.5 concentration was
more than 200 µg m-3 higher than that of the cold frontal period, but the
PM2.5 concentrations at 1.0 km (Fig. 8b) were significantly lower. The PM2.5
fluxes in the stable atmosphere were lower than those in the cold frontal passage at both
the surface and 1.0 km, reflecting the lower mean wind velocity under stable weather.
This indicates that atmospheric conditions were not favourable for the horizontal
transport of PM2.5.
The averaged PM2.5 profile over the YRD shows significant vertical gradients under
stable weather (Fig. 9). The process analysis showed that the vertical advection process
transported PM2.5 from the surface to the upper air. However, this vertical
transport only reached 1.0 km altitude – much lower than it did during the cold frontal
passage (∼2.0 km). Horizontal advection shows a small negative contribution to
PM2.5 concentrations over the YRD from the surface to 1.0 km. This indicates that
there was a weak outflow of PM2.5 from the YRD to its surroundings, because the YRD
is an important aerosol source region. Vertical diffusion mixed PM2.5 between the
surface and the upper air, but its contribution to PM2.5 was relatively small.
Secondary aerosol formation slightly increased the aerosol concentration from the surface
to 1.0 km.
Vertical profiles of PM2.5 concentrations and the contributions
of physical/chemical processes to PM2.5 concentrations during the period
of stable weather.
Time series of PM2.5 concentrations and contributions of source regions to
the PM2.5 concentrations over the Yangtze River Delta (YRD) from 19 to 28 January
2015. SYRD is south-west of YRD, AH is Anhui, and OTHR is other.
Contributions of PM<inline-formula><mml:math id="M165" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> from source regions to the YRD
Anthropogenic emissions are the fundamental source of PM2.5. Knowing
the source regions of aerosols and their contributions to the YRD is
critical in controlling PM2.5 pollution. Our results revealed a
significant transport of aerosol particles from the NCP to the YRD during
the cold frontal passage and a remarkable local PM2.5 contribution
during stable weather conditions. Based on these results, we derived the
contributions of PM2.5 from source regions to the YRD using ISAM, which
was incorporated in the CMAQ model.
Mass contributions from each of the geographical source regions, BCONs, and
ICONs to PM2.5 concentrations over the YRD from 19 to 28 January 2015
are shown in Fig. 10. The YRD is a quickly developing and densely populated
region where anthropogenic activities such as industrial production, vehicle
usage, power plant operation, and residential activities release huge volumes
of atmospheric pollutants. Therefore, in the YRD, the most significant source
of PM2.5 is local emissions (Fig. 10). The NCP is another heavily
polluted region in east China (Cao et al., 2015; Chen and Wang, 2015; J. Li
et al., 2017), located adjacent to YRD to the south. On 21 January, a cold
front brought polluted air mass from the NCP to the YRD resulting in a high
contribution of PM2.5. PM2.5 from regions outside of the modelling
domain (BCONs) also impacted on the PM2.5 concentration over the YRD
through long-range transport. However, contributions from other source
regions were relatively small.
Contribution rate of each source region to PM2.5 over the
Yangtze River Delta (YRD) during (a) the whole simulation period,
(b) the cold frontal passage, and (c) under the stable
weather conditions. JS is Jiangsu, SH is Shanghai, and
ZJ is Zhejiang.
Mean contributions from each source region from 19 to 28 January 2015 are shown in
Fig. 11a. Local contributions (from the YRD itself) accounted for 56.5 % of the
PM2.5 concentration, in which Jiangsu, Shanghai, and Zhejiang accounted for
32.5 %, 3.5 %, and 20.5 %, respectively. PM2.5 from the NCP and BCONs
contributed 18.5 % and 10.5 %, respectively. The YRD, NCP, and BCONs contributed
85.5 % in total. During the cold frontal passage, a strong north-west wind prevailed
over the YRD; locally originated aerosols only accounted for 35 % of the PM2.5
contribution, with Jiangsu, Shanghai, and Zhejiang accounting for 22 %, 2 %, and
11 %, respectively (Fig. 11b). These contributions are much lower than those in the
total average because the strong wind in the cold frontal period was unfavourable for the
accumulation of locally emitted pollutants. PM2.5 from the NCP contributed 29 %
to the PM2.5 concentrations over YRD, a significantly higher amount than in the
average contribution. Contributions from other geographical source regions were also
increased during the cold frontal passage because of the long-range transport of aerosol.
In general, the cold front decreased local contributions in the YRD, but increased
long-range transport contributions from the NCP region.
Under stable weather conditions, local contributions (61.5 %) were increased,
especially for Zhejiang province (Fig. 11c). Lower wind speeds during the stable period
were unfavourable for the transport of pollutants, resulting in high PM2.5
concentrations and significant local contributions. NCP contributed 14.5 % to
PM2.5 concentrations over the YRD, accounting for only half that in the cold frontal
period. In general, PM2.5 contributions in the stable period were similar to those
in the total average, but with higher local contributions and lower NCP contributions.
Conclusions
Cold fronts are favourable to the outflow of PM2.5 in the BTH region, decreasing
aerosol concentrations as soon as they reach the area. However, in the YRD, cold fronts
remove local aerosol particles and can also introduce upstream air pollutants.
Understanding the processes of PM2.5 transport during the cold frontal passage is of
great significance for the understanding of haze formation mechanisms over the YRD in
wintertime. In this study, the coupled WRF–CMAQ model was employed to investigate the
processes and mechanisms of PM2.5 pollution over the YRD under a cold frontal
intrusion period and subsequent stable weather conditions in January 2015.
Observations at three sites show that high PM2.5 concentrations and strong
north-westerly winds appeared simultaneously as the locations of the peak PM2.5
concentration moved from north to south, indicating that the cold front transported
aerosol particles across the YRD. At the beginning of the cold frontal passage, when the
cold front first reached the YRD, it forced the warm and polluted YRD air mass ahead of
the frontal zone to move up along the frontal boundary, lifting PM2.5 into the free
troposphere. As the cold front intruded deep into the YRD, aerosols from upstream areas
(NCP) were transported to the YRD by strong north-westerly frontal airflow. At the end of
the cold frontal period, when the frontal zone had moved downstream of YRD (East China
Sea), high pressure took control over the YRD, resulting in divergence over the region.
The synoptic subsidence motions trapped PM2.5 in the boundary layer. The atmospheric
stratification became stable after the cold front from 24 to 27 January 2015. Aerosol
particles over the YRD then began to reaccumulate until the next cold front.
The contributions of PM2.5 from each of the defined source regions were
calculated by ISAM. For the entire 9-day simulation (19–28 January),
PM2.5 contributions from the local area (YRD), NCP, and BCONs accounted
for 56.5 %, 18.5 %, and 10.5 %, respectively. During the cold
frontal passage (12:00 LT 21 January to 04:00 LT 22 January), local
PM2.5 contributions decreased to 35 %, while contributions from the
NCP increased to 29 %. During the stable weather conditions (00:00 LT
24 January to 00:00 LT 27 January), local PM2.5 contributions increased
to 61.5 % while NCP contributions decreased to 14.5 %. This result
indicates that cold fronts intensify the long-range transport of air
pollutants in the NCP to the YRD.
Data availability
All observations and model outputs used in this study are available.
Readers can access the data directly or by contacting Bin Zhu via binzhu@nuist.edu.cn.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-3673-2019-supplement.
Author contributions
HK was responsible for paper writing, model simulation, and data analysis.
BZ proposed the idea and did the paper revision. JG performed model result processing and
plotting. YH performed observation data processing and plotting. HW performed observation
data collection. JS was responsible for weather map analysis. CP provided scripts for
data processing. TZ contributed to the paper revision and language editing. BY provided
meteorological observations at Linan.
Competing interests
The authors declare that they have no conflict of
interest.
Special issue statement
This article is part of the special issue “Regional transport
and transformation of air pollution in eastern China”. It is not associated
with a conference.
Acknowledgements
This work was supported by the National Natural Science Foundation of China (grant
nos. 91544229, 41605091, and 41605096), the National Key Research and Development Program
(grant no. 2016YFA0602003), The Startup Foundation for Introducing Talent of NUIST (grant
no. 2243141501035), the Hangzhou Scientific Research Project in Agriculture and Social
Development (grant no. 20170533B16), SUSTC Presidential Postdoctoral Fellowship, and the
open fund by the Key Laboratory for Aerosol-Cloud-Precipitation of CMA-NUIST (grant
no. KDW1701). We acknowledge the free use of MIX emission from Tsinghua
University. Edited by: Tong Zhu Reviewed
by: two anonymous referees
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