Air pollution is typically at its lowest in Taiwan during summer. The mean
concentrations of PM10, PM2.5, and daytime ozone (08:00–17:00 LST) during summer (June–August) over central Taiwan were 35–40 µg m-3, 18–22 µg m-3, and 30–42 ppb, respectively, between
2004 and 2019. Sampling analysis revealed that the contribution of organic
carbon (OC) to PM2.5 could have exceeded 30 % in urban and inland mountain
sites during July in 2017 and 2018. Frequent episodes of air quality
deterioration occur over the western plains of Taiwan when an easterly
typhoon circulation interacts with the complex topographic structure of the
island. We explored an episode of air quality deterioration that was
associated with a typhoon between 15 and 17 July 2018 using the Weather
Research Forecasting with Chemistry (WRF-Chem) model. The results indicated
that the continual formation of low-pressure systems or typhoons in the area
between Taiwan and Luzon island in the Philippines provided a strong
easterly ambient flow, which lasted for an extended period between 15 and 17
July. The interaction between the easterly flow and Taiwan's Central
Mountain Range (CMR) resulted in stable weather conditions and weak wind
speed in western Taiwan during the study period. Numerical modeling also
indicated that a lee side vortex easily formed, and the wind direction
could have changed from southwesterly to northwesterly over central Taiwan
because of the interaction between the typhoon circulation and the CMR. The
northwesterly wind coupled with a sea breeze was conducive to the transport
of air pollutants from the coastal upstream industrial and urban areas to
the inland area. The dynamic process for the wind direction changed given a
reasonable explanation for why the observed SO42- became the major
contributor to PM2.5 during the episode. SO42- contribution
proportions (%) to PM2.5 at the coastal, urban, and mountain sites
were 9.4 µg m-3 (30.5 %), 12.1 µg m-3 (29.9 %),
and 11.6 µg m-3 (29.7 %), respectively. Moreover, the
variation of the boundary layer height had a strong effect on the
concentration level of both PM2.5 and ozone. The lee
vortex and land–sea breeze, as well as the boundary layer development, were
the key mechanisms in air pollutant accumulation and transport. As typhoons
frequently occur around Taiwan during summer and fall, their effect on
the island's air quality merits further research attention.
Introduction
Tropical cyclones (also known as typhoons) are a frequent occurrence in East
Asia during summer and fall. Typhoons significantly affect not only
meteorological parameters but also air quality. That is because air
pollution is strongly related to atmospheric conditions, and typhoon
circulation typically alters atmospheric stability and air pollutant
diffusion in specific locations. For example, researchers revealed that
ozone episodes in Hong Kong and southeastern China are strongly related to
the passage of typhoons as they approach the area (Lee et al., 2002; Ding et
al., 2004; Huang et al., 2005, 2006; Yang et al., 2012; Zhang et al.,
2013, 2014; Wei et al., 2016; Yan et al., 2016; Luo et al.,
2018; Deng et al., 2019; Huang et al., 2021). The stagnant meteorological
conditions associated with strong subsidence and stable stratification in
the boundary layer result in pollutant accumulation before typhoons make
landfall. Huang et al. (2005) reported that approximately 30 % of total
ozone in Hong Kong was due to local chemical production in the lower
atmospheric boundary layer, and approximately 70 % was contributed by
long-range transport from southern China (i.e., the Pearl River Delta).
According to the dynamic process perspective, Chow et al. (2018) reported
frequent high-O3 days when typhoons were located between Hong Kong and
Taiwan (Fig. 1a) due to the influence of the typhoon position and associated
atmospheric circulations on air quality.
(a) Location of Taiwan and surrounding countries in East Asia. KM and
MG are the island stations of the Taiwan Environmental Protection
Administration (TEPA). (b) Topography over Taiwan and the locations of
Taichung city and Miaoli county. (c) Location of TEPA air quality monitoring
stations in central Taiwan in coastal (SL and XX), urban (FY, XT, ZM, CH,
and DL), and mountain (PL, NT, and ZS) areas. TPP, Taichung Power Plant;
THI, Taichung Harbor industrial area.
Taiwan also experiences air quality deterioration as typhoons approach (Fang
et al., 2009; Chang et al., 2011, Cheng et al., 2014; Hsu and Cheng, 2019).
However, not all typhoons are associated with poor air quality in Taiwan.
The effect of typhoons on air quality is highly related to the location of
the typhoon and its circulation's interaction with Taiwan's Central Mountain
Range (CMR; Fig. 1b). Thus, the mechanism of the formation of poor air
quality may differ between Taiwan and Hong Kong. Air quality deterioration
frequently occurs over the western plains of Taiwan when typhoons pass
between Taiwan and Luzon island in the Philippines; the distance of the
typhoons from Taiwan is typically several hundred kilometers but may even be
greater than 1000 km. Under such conditions, the weather is
typically stable, with clear skies, strong solar intensity, and weak wind
speeds over Taiwan's western plains because of the interactions of the
typhoon's easterly circulations with the CMR. Furthermore, such typhoons are
usually associated with a Pacific high-pressure system during summer; thus,
the air temperature may be high. For example, researchers have noted that
typhoon's secondary circulation may enhance subsidence and result in a heat
wave, clear skies, and weak wind speed over Taiwan or southern China (e.g.,
Ding et al., 2004; Huang et al., 2005; Jiang et al., 2015; Shu et al., 2016;
Lam, et al., 2018), thus adversely affecting air quality as well. In Taiwan,
this phenomenon is particularly attributed to the blocking effect of the
CMR. The CMR occupies approximately two-thirds of Taiwan's landmass (300 km × 100 km) and lies NNE–SSW (Fig. 1b), with an average terrain
height of approximately 2000 m (Lin and Chen, 2002; Lin et al., 2011) and
some peaks of nearly 4000 m. The CMR has a major effect on local circulation
and frequently interferes with the easterly or northeasterly prevailing
winds such as long-range transport dust storms and air pollution events (Lin
et al., 2004, 2005, 2012a, b) during the winter monsoon. When a typhoon is located
between Taiwan and Luzon, the low-level easterly airflow easily splits
northern and southern Taiwan and moves around the island, forming a vortex
at the lee side of the mountain (Hunt and Synder, 1980; Smolarkiewicz and
Rotunno, 1989; Y. L. Lin, 1993; Lin et al., 2007). On the lee side of the CMR,
wind speeds are weak (Lin et al., 2007) and the atmospheric conditions are
more stable than on the windward side of eastern Taiwan. Under these
favorable conditions, air pollutants readily accumulate and result in high
ozone and aerosol concentrations over western Taiwan. Actually, the
interactions between ambient flow and topography result in stable weather
conditions, and air pollutant accumulation in the low boundary is common
all over the world. According to the obstacle's scale, it could
occur on plateaus (Ning et al., 2019), mountains (Lai and Lin et al., 2020), and
even among buildings (W. Theurer, 1999) as the airflow interacts with
them. For example, Wallace et al. (2010) investigated the spatial and
topographic effects of temperature inversions on air quality in the
industrial city of Hamilton, located at the western tip of Lake Ontario,
Canada. Topographically constrained wind flows and frequent temperature
inversions occurred in Los Angeles, California (Lu and Turco, 1995), the
Highveld Plateau industrial region in South Africa (Jury and Tosen, 2004),
and Perth, Australia (Pitts and Lyons, 1988). Valverde et al. (2016) studied
air pollution in Europe and found that the dispersion and transfer of air
pollutants are affected by topographic features and weather patterns. Ning
et al. (2019) presented synergistic effects of synoptic weather patterns of a low
trough, low vortex, and topography on air quality over the Sichuan Basin of
China.
Summer and fall are regarded as the “typhoon season” over Taiwan and
throughout East Asia. Statistically, more than 20 typhoons form in the
western Pacific Ocean per year, and approximately 3–4 typhoons directly
strike Taiwan (Lin et al., 2011; Tu and Chen 2019). Records from Taiwan's
Central Weather Bureau (CWB) indicate that 18 % of typhoons (Type 5;
https://www.cwb.gov.tw/V8/C/K/Encyclopedia/typhoon/typhoon.pdf, last access: 18 March 2021) between 1911
and 2019 did not make landfall but passed between Taiwan and Luzon. The wind
circulations of this type of typhoon were easterly or southeasterly
depending on the location of the typhoons. Thus, it is not uncommon for more
than 10 typhoons per year to pass near Taiwan and affect the island's air
quality. The impact of the interaction between the typhoon's circulation and
the CMR on the air quality on the lee side of the mountain is more serious
than in other areas.
To date, air pollution episodes with a formation mechanism associated with
the interactions between typhoon circulation and the CMR have not been
thoroughly documented in Taiwan. In this study, we investigated a major air
quality event that occurred on 17 July 2018, with a maximum O3
concentration of 134 ppb and a daily maximum aerosol concentration for
PM10 (PM2.5) reaching 152 µg m-3 (70 µg m-3)
in inland rural areas of central Taiwan. We used the Weather Research
Forecasting with Chemistry model (WRF-Chem version 3.9; Grell et al., 2005)
to study the processes and mechanisms of formation of the air pollution
episode. The remainder of this paper is organized as follows: Sect. 2
describes the data sources and sampling measurement during the study period;
Sect. 3 presents the model and settings used in this study; Sect. 4 presents
the air quality characteristics and measurements recorded over the western
plains of Taiwan; Sect. 5 describes and discusses the simulation results of
air quality associated with the typhoon event using WRF-Chem; and, finally,
Sect. 6 provides the conclusions.
Data sources and measurement
We collected measurements of hourly PM10, PM2.5, and other
pollutants (O3, NOx, CO, and SO2) as well as meteorological
parameters (air temperature, wind field, and rainfall) from Taiwan
Environmental Protection Administration (TEPA) air quality monitoring
stations. To elucidate the spatial distribution of air pollutants, we
classified the observed stations over central Taiwan into “coast,”
“urban,” and “mountain.” Each of these categories represents the mean
concentration of the numbers derived from stations of the same type. The
coast category included two stations: Shalu (SL) and Xianxi (XX; Fig. 1c).
The urban category included five stations: Fengyuan (FY), Xitun (XT),
Zhongming (ZM), Changhua (CH), and Dali (DL; Fig. 1c). The mountain category
included three stations: Nantou (NT), Zhushan (ZS), and Puli (PL), which
were located nearby or in basins surrounded by high mountains (Fig. 1c). Two
stations on small islands were also considered in the analysis. One was in
Kinmen (KM), which is located close to Xiamen city in southeastern China, and
the other was Magong (MG) station located in the Taiwan Strait (Fig. 1a).
To explore the air pollution episodes during summer, we recorded data in
central Taiwan in July 2017 and 2018. For the summer campaigns, we employed
three sampling sites (the squares in Fig. 1c): Shalu (SL, 24.23∘ N, 120.57∘ E; the same location as the TEPA station), Zhushan
(ZS, 23.76∘ N, 120.68∘ E; the same location as the
TEPA station), and Chung Shan Medical University (CSM) (24.12∘ N,
120.65∘ E; Fig. 1c). ZS is a suburban site located in a complex
valley surrounded by hills (300–500 m) and high mountains (CMR; elevation >2000 m) to the east and south, respectively. The remaining two
sampling sites, SL and CSM, are located in a coastal suburban and urban
area (Fig. 1c), respectively. The sampling period of each sample was 11 h;
daytime samples were collected from 08:00 to 19:00 LST, whereas nighttime
sampling was conducted from 20:00 to 07:00 LST. We determined mass
concentrations of the aerosols using a gravimetric measurement of the
samples collected on polytetrafluoroethylene membrane filters (Chou et al.,
2008; Lee et al., 2019). The filter samples were analyzed for water-soluble
ions (Ca2+, Mg2+, Na+, NH4+, K+,
SO42-, NO3-, and Cl-) via ion chromatography (Dionex
ICS 1000, Thermo Scientific). Organic carbon (OC) and elemental carbon (EC)
were measured by a thermal–optical carbon analyzer (DRI, 2001A, Atmoslytic
Inc.), following the IMPROVE thermo-optical reflectance (TOR) protocol (Chow
et al., 2001). The instruments for the hourly measurement of PM10 and
PM2.5 from TEPA are METONE_BAM1020 (https://airtw.epa.gov.tw/CHT/EnvMonitoring/Central/Tools.aspx, last access: 18 March 2021). Two
reactive gases, ozone (O3) and sulfur dioxide (SO2), were measured
in parallel with the aerosol measurements. A non-dispersive ultraviolet
photometer (ML9810, Ecotech, Australia) and an ultraviolet fluorescence
spectrometer (ML9850, Ecotech, Australia) were used to measure O3 and
SO2 concentrations, respectively. Sounding data were obtained from
the CWB; the site on Penghu island (the World Meteorological Organization
– WMO – station number code is 46734) was close to the MG TEPA station (Fig. 1a).
During summer, the land–sea breeze easily combines with the mountain upslope and downslope wind during daytime and nighttime. As the sea breeze develops, airflows
are typically transported from coastal areas and pass over the Taichung
metropolitan region (Fig. 1c) coupled with mountain slope flow to the inland
area. The Taichung metropolis is a large urban environment comprising
residential, industrial, and agricultural lands (Cheng et al., 2009). In
particular, Taichung Power Plant (TPP, Fig. 1c), which is coal-fired, and
the Taichung Harbor industrial area (THI, Fig. 1c) are both located on the
coast and are responsible for substantial emissions in central Taiwan. Thus,
severe emission sources contribute to and affect the air quality in the
Taichung metropolitan area under favorable weather conditions.
Meteorological parameters, including wind speed and wind direction,
temperature, and relative humidity, were acquired from a meteorological
station in the same location where data were collected for this study.
Model configurations
In this study, we used the Weather Research and Forecasting (WRF) model
coupled with the WRF-Chem version 3.9 to study air pollutant transport
during the episode. We obtained the meteorological initial and boundary
conditions for WRF-Chem from the National Center for Environmental
Prediction (NCEP) Operational Global Forecast System (GFS) 0.25∘×0.25∘ data sets at 6 h intervals. We selected the
Yonsei University (YSU) planetary boundary layer (PBL) scheme for this
study. The coarse and fine domains had 259×370 and 301×301 grid nets with resolutions of 9 and 3 km, respectively. The vertical
had 41 levels, with the lowest level approximately 40 m above the surface.
To ensure that the meteorological fields were well simulated, we employed
the four-dimensional data assimilation scheme according to the NCEP GFS
data. Transport processes included advection by winds, convection by clouds,
and diffusion by turbulent mixing. Removal processes included gravitational
settling, surface deposition, and wet deposition (scavenging in convective
updrafts and rainout or washout in large-scale precipitation). The kinetic
preprocessor (KPP) interface was used in both the chemistry scheme of the
Regional Atmospheric Chemistry Mechanism (Stockwell et al., 1990). The
secondary organic aerosol formation module, the Modal Aerosol Dynamics Model
for Europe (MADE) (Ackermann et al., 1998) volatility basis set (VBS)
(Ahmadov et al., 2012), was employed in the WRF-Chem model. The anthropogenic
emissions in Taiwan were obtained from the air pollutant monitoring database
of the TEPA. Its emission inventory system is called the Taiwan Emission Data
System (TEDS). The TEDS version in this study is V9.0 (2013) and contains
data on eight primary atmospheric pollutants: CO, NO, NO2, NOx,
O3, PM10, PM2.5, and SO2.
Results and discussionCharacteristics of air quality over central Taiwan
Figure 2a–c indicate the monthly mean concentration for PM10,
PM2.5, and daytime (08:00–17:00 LST) ozone between 2004 and 2019.
Clear seasonal variations were noted for aerosol and ozone over central
Taiwan. The lowest PM10, PM2.5, and daytime ozone concentrations
were observed during summer (June–August) at 32–40 µg m-3,
16–23 µg m-3, and 35–42 ppb, respectively. The concentration
of daytime ozone peaked in October, whereas PM10 and PM2.5 peaked
in March. In general, the highest concentrations were observed in spring
(March–May) and fall (September–November). The daytime ozone peaked at 56 and 48 ppb in October and April, respectively (Fig. 2c). For PM10
and PM2.5, the peak concentrations were 70–75 and
40–45 µg m-3 over the western plains in March (Fig. 2a, b).
Regarding the characteristics of ozone distribution, the concentration at
the mountain site was typically higher than that in urban areas and the
coast. For PM10 and PM2.5, the mountain site also typically had
higher concentrations than the urban and coastal areas, except during
summer (Fig. 2a, b). The monsoon dominates the prevailing wind over East
Asia. During summer, a southwesterly wind prevails, whereas a northeasterly
wind prevails during fall, winter, and spring. The characteristics of the
seasonal variations might be due to the summer having a cleaner background
and higher boundary layer height than in other seasons. As mentioned
earlier, the major emission sources such as industry and traffic are located
in coastal and urban areas. The mean highest concentration of ozone
typically occurs over rural mountain areas during summer; thus, the dominant
land–sea breeze might play a critical role in the air quality in western
Taiwan.
Average monthly concentrations of (a) PM10, (b) PM2.5, and
(c) daytime (08:00–17:00 LST) ozone for coastal, urban, and mountain areas
between 2004 and 2019.
During summer (July only in this study) in 2017 and 2018, we conducted
sampling campaigns in central Taiwan. Table 1 presents the mean
concentration of the elements in PM2.5 at sampling stations SL, CSM,
and ZS during July in 2017 and 2018. The mean concentrations of PM2.5
for stations SL, CSM, and ZS were 15.7, 16.9, and 21.4 µg m-3.
The inland rural mountain site, ZS, clearly had the highest total PM2.5
concentration. Organic carbon (OC) and SO42- had the highest
concentrations of the species in PM2.5, and both increased from the
coast to the inland mountain area (Table 1). Because the major emissions
were from coastal industry or urban areas, sea breeze transport played a
role in PM2.5 concentration in the western plains. The major
contributing species in PM2.5 were OC, SO42-, NO3-,
NH4+, and elemental carbon (EC; Table 1). At the coastal station
SL, the concentrations of OC and SO42-were comparable at 4.3 and 4.5 µg m-3, accounting for 27.5 % and
28.6 % of PM2.5, respectively. At the city site CSM and the inland
rural mountain station ZS, OC had concentrations of 5.6 (33.1 % of
PM2.5) and 6.6 µg m-3 (30.9 % of PM2.5),
respectively. The results indicated that the contribution of OC to
PM2.5 could exceed 30 % at the urban and inland mountain sites. The
concentration of OC increased from the coast (4.3 µg m-3;
27.5 % of PM2.5) to the mountain station (6.6 µg m-3;
30.9 % of PM2.5), and the urban site had the highest proportion (5.6 µg m-3; 33.1 % of PM2.5) in PM2.5 among these
stations (Table 1). SO42- also exhibited an increased
concentration from coastal areas to the inland mountain area, but the
changes were minor (4.5–4.8 µg m-3). Notably, the proportion of
SO42-in PM2.5 decreased from the coast to the mountain area
because the major sources, TPP and THI (Fig. 1c), are located on the coast.
The other species, namely NO3-, NH4+, and EC, at SL,
CSM, and ZS had comparable concentrations between stations (1.0–1.4,
1.7–2.0, and 1.1–1.4 µg m-3, respectively; Table 1). The
inland rural station ZS is located in a foothill valley of the CMR and
surrounded by mountains. Thus, the high concentration at ZS might be due to
sea breeze transport.
Concentrations of PM2.5 and its major components
(SO42-, OC, NO3-, NH4+, and EC) as well as daytime
ozone and meteorological parameters at the SL (coast), CSM (urban),
and ZS (mountain) sampling sites in July 2017 and 2018.
In general, OC and SO42- were the major species over western
Taiwan, especially in inland areas. These results suggest that local
contributions, such as traffic, industry, and even agricultural emissions,
might play critical roles in the composition of PM2.5. Furthermore, the
spatial distributions of the highest PM2.5 and daytime ozone concentration
were not always in urban areas; instead, concentrations accumulated in
inland rural areas (Fig. 2 and Table 1). The roles that the land–sea breeze,
boundary layer development, and interaction of typhoon circulation with
complex geographic structures play in air quality require clarification. The
mechanisms of these complex processes and local circulation variations are
demonstrated through a case study using numerical model simulation in Sect. 4.2.2.
Air quality deterioration case from 15–17 July 2018Weather condition and observation
To explore air quality deterioration processes and formation mechanisms, we
employed a severe air pollution episode between 15 and 17 July 2018. Weather
maps obtained from the NCEP Global Forecast System (GFS) revealed that a
tropical depression formed to the east of the Philippines and moved
northwestward on 15 July 2018 (Fig. 3a). Another low-pressure system
followed, located to the south of this tropical depression on 16 July (Fig. 3b). On 17 July, this tropical depression strengthened and formed a weak
typhoon named Son-Tinh, located between Taiwan and Luzon island in the
Philippines (Fig. 3c); the original low-pressure system also strengthened
into a tropical depression on 17 July. The continual formation of
low-pressure systems or typhoons to the east of Luzon shifted the ambient
wind flow of Taiwan to an easterly direction for an extended period between
15 and 17 July (Fig. 3a–c). The easterly ambient flow was easily blocked by
Taiwan's CMR, resulting in a lee vortex formation associated with stable
atmospheric conditions and weak wind speed in western Taiwan. The mechanism
of lee vortex formation on the lee side of a high mountain has been
described through a laboratory experiment (Hunt and Synder, 1980) and
numerical modeling (e.g., Smolarkiewicz and Rotunno, 1989). Li and Chen
(1998) employed wind flow with a low Froude number (<0.5) (Fr≡U/NH, where U is the far upstream flow speed; N is the
Brunt–Vaisala frequency, a measure of stratification; and H is the height
of an obstacle), and the low-level airflow easily split off the northern
coast and moved around the island of Taiwan. The current study is an example
of a low-Fr case (<0.5; assumed average wind speed, U=10 ms-1; Brunt–Vaisala frequency, N=10-2 s-1; and average
mountain height, H=2.5 km). Thus, we expected wind speeds to be weak and
atmospheric conditions to be more stable on the lee side of the CMR compared
with the windward side of eastern Taiwan.
Near-surface weather charts obtained from NCEP GFS data. The gray area
represents clouds according to a Himawari satellite infrared image. (a):
00:00 UTC on 15 July; (b) 00:00 UTC on 16 July, and (c) 00:00 UTC on 17 July.
Sounding data (Fig. 4) recorded at the CWB station on Penghu island (WMO station number code is 46734, close to MG in
Fig. 1a) indicated a relatively weak wind speed (<5 m s-1) in
the low boundary (below 850 hPa) during the study period from 15 to 17 July
2018 (Fig. 4a–c). Above 700 hPa (3000 m), a strong easterly wind
(>10 m s-1) prevailed due to the typhoon circulations.
Furthermore, clear subsidence and multiple inversion layers were revealed in
the sounding between 16 and 17 July (Fig. 4b, c). On 17 July, the inversion
layer was even lower than 950 hPa (Fig. 4c); that is, only a few hundred
meters over Penghu island in the Taiwan Strait. The sounding data revealed
stable atmospheric conditions, high relative humidity, and weak wind speed
on the lee side of the mountains over western Taiwan.
Morning sounding launched at 00:00 UTC at station 46734 (located at
MG in Fig. 1a): (a) 15 July, (b) 16 July, and (c) 17 July. The red line
represents the vertical profile of air temperature, and blue is dew-point
temperature.
Concentrations of PM2.5 and its major components (SO42-,
OC, NO3-, NH4+, and EC) as well as daytime ozone and
meteorological parameters at the SL (coast), CSM (urban), and ZS (mountain)
sampling sites between 15 and 17 July 2018.
Figure 5 displays the variations in wind field and air pollutants (both
PM2.5 and ozone) at the TEPA stations on two small islands, KM and MG
(locations marked in Fig. 1a), and results over the western plains from 12 to
18 July 2018. The wind direction and wind speed were quite different between
these two stations and over the western plains (Fig. 5a). The wind speed was
relatively strong at KM, especially between 16 and 17 July because the
typhoon circulation had already reached the coastal area of China and the
Taiwan Strait. The wind direction was originally southerly on 12 July,
becoming northeasterly after 12:00 LST on 14 July 2018. During periods of
strong wind speed at KM, the concentrations of PM2.5 and O3
revealed no diurnal variation and a steady low, with PM2.5< 15 µg m-3 and daytime O3<40 ppb after 12:00 LST
on 14 July. The wind speed at MG was weaker than that at KM because MG is
close to Taiwan and was likely affected by the mountain blocking effect
mentioned earlier. Because the wind speed did not change considerably, the
PM2.5 and O3 concentration levels did not fluctuate obviously at
MG during the study period.
Hourly variation of observed (red) and simulated (blue) values for
(a) wind, (b) PM 2.5, and (c) daytime (08:00–17:00 LST) ozone between
12 and 18 July 2018 for the coastal, urban, and mountain stations as well
as for the two island stations, Kinmen (KM) and Magong (MG).
By contrast, the wind field time series indicated clear land–sea breeze
variations over western Taiwan. At the inland mountain site, wind speed was
relatively weak compared with the coastal and urban sites (Fig. 5a). The
PM2.5 and ozone time series for the coastal, urban, mountain sites are
presented in Fig. 5b and c. The PM2.5 concentrations at the urban and
mountain sites ranged from 30 to 60 µg m-3 between 16 and 17
July 2018. Notably, the timing of the peak PM2.5 concentration differed
between the coastal, urban, and mountain sites. Peak PM2.5 at the
coastal and urban sites was observed around noon, whereas peak PM2.5 at
the inland mountain site occurred at 18:00 LST on 17 July 2018 (Fig. 5b).
The differences in the timing of the peak PM2.5 concentrations between
the coastal and urban sites and the inland mountain site could be attributed
to the transport of the sea breeze. No clear diurnal variation in PM2.5
concentration was observed between the urban and mountain sites between 16
and 17 July. That is, even at night and in the early morning, the
concentration remained as high as 40 µg m-3 (Fig. 5b) because
atmospheric conditions were favorable for air pollutant accumulation. The
peak ozone concentration occurred around noon at the coast and urban sites,
whereas the peak at the mountain site occurred later at 16:00 LST (Fig. 5c).
We estimated that the concentrations of PM2.5 and ozone on the episode
day on 17 July (Fig. 5b, c) were 3 times higher than the mean
concentration during summer (Fig. 2) in central Taiwan. As mentioned
earlier, the major emissions were generated by coastal industry and the
Taichung city metropolitan area, but the peak ozone concentration occurred
at the inland mountain station (120 ppb at PL) because of sea breeze
transport from upstream to downstream sites.
The spatial distribution of the wind field and PM2.5 concentration (Fig. 6)
from TEPA stations in Taiwan revealed a strong easterly wind in northern and
southern Taiwan as well as weak wind speed and clear sea breeze development during
daytime in central Taiwan. PM2.5 concentrations remained low (<15µg m-3) at the northern, eastern, and southern tips of Taiwan
on 17 July 2018 (Fig. 6a–f). Over western Taiwan, a sea breeze developed
after 10:00 LST, and a strong onshore flow blew air pollutants to the inland
area (Fig. 6b–d). A high PM2.5 concentration (>50µg m-3) extended from the coast to the urban area at noon (Fig. 6b, c),
which was subsequently transported to the inland mountain area in the
afternoon and nighttime (Fig. 6d–f). The high PM2.5 concentration
accumulated in Miaoli county (located north of Taichung city) at midnight
owing to the convergence of southerly and land breezes (Fig. 6f). Actually,
the spatial variation of PM2.5 could also be observed on the previous
day (16 July; Fig. 5b), which contributed approximately 30 µg m-3 in the early morning on 17 July in central Taiwan.
Observed PM2.5 concentration (µg m-3) and wind
recorded in Taiwan (a) at 08:00 LST, (b) 12:00 LST, (c) 14:00 LST, (d) 16:00 LST, and (e) 20:00 LST on 17 July as well as (f) 00:00 LST on 18 July 2018.
The location of the high-pollution ozone was also strongly associated with
the land–sea breeze during the daytime (Fig. 7b–e). A high concentration of
ozone was observed at the urban station at noontime (Fig. 7c); the ozone was
transported to the inland mountain station, resulting in peak concentrations
higher than 120 ppb between 16:00 and 18:00 LST (Fig. 7d–f). By 22:00 LST,
the ozone concentration had declined more rapidly in the city than in the
mountain area because of the dilution effect (Fig. 7g, h). The detailed
pollution process and mechanism are demonstrated and discussed in the model
simulation in Sect. 4.2.2.
Observed ozone concentration (ppb) and wind recorded in Taiwan at (a)
08:00 LST, (b) 10:00 LST, (c) 12:00 LST, (d) 14:00 LST, (e) 16:00 LST, (f) 18:00
LST, (g) 20:00 LST, and (h) 22:00 LST on 17 July 2018.
Simulation results
The hourly comparison between observed (red solid) and simulated (blue
dashed) PM2.5 and ozone between 12 and 18 July 2018 is presented in
Fig. 5b and c. In general, our simulation reasonably captured the variation of
PM2.5 and ozone in western Taiwan and the small island sites MG and KM
(Table 2). For PM2.5, the root mean square error (RMSE) at all sites
was less than 1.0 µg m-3, and the correlation between observed
and simulated values was 0.72 and 0.81 at the urban and mountain sites,
respectively. Regarding the mean bias of PM2.5, it was slightly
overestimated at coastal and urban sites and underestimated at the mountain
site and sites on the two islands. In the ozone simulation, the correlation
between observed and simulated values was as high as 0.73–0.9, except for
MG. The RMSE of ozone for all areas was less than 1.45 ppb. For the mean
bias of ozone, the maximum underestimation (-10 ppb) occurred at the
coastal site, and the maximum overestimation (13.8 ppb) occurred over the
mountain area because of the simulation of the spatial distribution
difference.
Figure 8 indicates the simulated wind field (streamline) and spatial
distribution of PM2.5 on 17 July 2018. The ambient wind flow was
easterly and blocked by the CMR; the wind flow went around the CMR during
the study period. The strongest wind speeds were recorded at the northern
and southern tips of Taiwan and the coastal area of southeastern China (Fig. 8). By contrast, the wind speed was relatively weak on the lee side of the
CMR from the middle of the Taiwan Strait to western Taiwan. This finding is
consistent with the observed wind speed being stronger at KM (Fig. 5a) than
in the area over western Taiwan. Figure 8a–f reveal that the highest
PM2.5 concentration (>60µg m-3) occurred on
the lee side of the CMR in central Taiwan during the daytime (08:00–16:00 LST) on 17 July 2018. After 08:00 LST, the sea breeze gradually developed
and the onshore wind speed increased (Fig. 8a–c); thus, the
high-concentration PM2.5 plume was transported from the coast to the
inland mountain area. Even though the area has high emissions, the
PM2.5 concentration along the coastal area of China was low because of
the strong wind speed (Fig. 8a–c). As a sea breeze developed after 08:00 LST,
the vortex circulation was coupled with the onshore flow (Fig. 8a–d).
The lee vortex circulation was not clear because it combined with the sea
breeze and enhanced the air pollutant transport to the inland area during
the daytime. However, the lee vortex circulation was clearly formed in the
area from 23.5 to 24.5∘ N in the afternoon until early morning
the next day because the land breeze interacted with the mountain lee side
flows (Fig. 8e–f). After the lee vortex circulation formed, the southerly
flow in the western plains was enhanced (Fig. 8e, f). These processes resulted
in trapped air pollutants over the plains area because of the interaction
between the lee vortex southerly component wind and the offshore flow in the
nighttime and early morning. This also explains the absence of diurnal
PM2.5 variation, and high concentrations (>35µg m-3) accumulated during nighttime and early morning on 16 and 17 July
over central Taiwan (Figs. 5a, b, and 6f). Thus, the lee vortex formation was
adverse to the development of the offshore flow (land breeze) and prolonged
the air pollutant accumulation in western central Taiwan (Figs. 6 and 8).
These critical processes explain why air pollutants tended to accumulate in
central Taiwan during the episode days. Notably, the wind speed was strong
and the concentration of PM2.5 was low in the Taiwan Strait close to
coastal areas of China in the simulation (Fig. 8a–f) and according to
observations at KM (Fig. 5a). According to the spatial distribution, a
strong wind speed can limit the number of air pollutants transported
southward from mainland China to Taiwan (Fig. 8b–f). That is, the pollution
type was locally dominated during the event days.
Simulated near-surface (30 m) streamline and PM2.5 concentration
(µg m-3) in Taiwan (a) at 08:00 LST, (b) 12:00 LST, (c) 14:00 LST, (d)
16:00 LST, and (e) 20:00 LST on 17 July as well as (f) 00:00 LST on 18 July 2018.
Similar to the observed ozone (Fig. 7), the simulated ozone (Fig. 9) was also
dominated by circulations associated with the land–sea breeze and the
interaction of the easterly flow with the CMR. Most of the area had steady
low concentrations in the early morning on 17 July (Fig. 9a) because of the
dilution effect of the ozone formation in the nighttime and early morning
(Fig. 9a and h–i). A high concentration already existed over the mountain
area in Miaoli county (Fig. 1b) in the early morning at 04:00 LST (Fig. 9a),
with a steady low concentration over the coastal and urban areas. During the
daytime, the background ozone concentration was 25–35 ppb over the ocean.
The ozone concentration promptly increased around noon and extended over
almost the entire western plains in the afternoon (Fig. 9c–f) on 17 July.
The area of high ozone concentration extended over the western plains when
the sea breeze developed after 10:00 LST on 17 July (Fig. 9c). Following
increases in wind speed, the high ozone concentration extended to the inland
area and was transported further south of Taichung city (Fig. 9d, e). The
peak ozone concentration at the inland rural site occurred at 16:00 LST,
whereas it occurred in the city center at the urban site at 12:00–14:00 LST
(Figs. 5c, 7c, d, 9d, e). Because the major emission sources were coastal
industry and the urban area, the high ozone concentration at the inland site
was the result of ozone being transported by the sea breeze. The simulated
peak ozone concentration occurred between 14:00 and 16:00 LST at the inland
site because of the sea breeze coupled with the mountain upslope wind (Fig. 9
c–f). Moreover, the high-ozone plume was associated with the lee vortex
circulation over the Taiwan Strait and existed during the nighttime and
early morning. It provided a southerly flow component during the nighttime
and early morning (Figs. 9a and g–i).
Simulated near-surface (30 m) streamline and ozone concentration
(ppb) in Taiwan at (a) 04:00 LST, (b) 08:00 LST, (c) 10:00 LST, (d) 12:00 LST, (e)
14:00 LST, (f) 16:00 LST, (g) 18:00 LST (h) 20:00 LST, and (i) 22:00 LST on 17 July 2018.
As mentioned earlier, sounding data indicated multiple inversion layers on
the event days. To further investigate the boundary layer development and
air pollutant distribution in the vertical, a northwest–southeast
cross section AA' (Fig. 10a) was superimposed over the high-concentration
area, as illustrated in Fig. 10. In the early morning at 05:00 LST (Fig. 10b), a
separate high-concentration plume was observed at ground level, and another
remained at an elevation of 1000 m on 17 July. It is a typical boundary
layer structure due to ground surface radiation cooling under stable
atmospheric conditions during nighttime and early morning. These two layers'
plumes coupled together due to a boundary layer gradually developing in the
morning after 07:00 LST (Fig. 10b–d). Because the emissions increased during
rush hour, the concentration promptly increased as the PM2.5 plumes of
these two layers coupled well in the vertical below 1000 m at 10:00 LST (Fig. 10d). The wind speed was weak at elevations below 1500 m but strong
and offshore in a southeast–northwest direction above 2000 m due to easterly
tropical cyclone circulation. The high-PM2.5 plume (concentration >50µg m-3) was pushed by the sea breeze coupled
with the upslope wind and accumulated in the inland rural area during
daytime (12:00–16:00 LST) (Fig. 10e–g). The highest concentration was not
at ground level but heights between 500 and 1000 m at noontime (Fig. 10e) and
1000–1500 m in the afternoon (Fig. 10f, g). The boundary layer structure as well as
the coupling between the sea breeze and mountain upslope wind played important
roles for the PM2.5 concentration distribution in the vertical along
the cross section (Fig. 10d–g). As offshore wind developed, which pushed the
air pollutants from the mountain area to the plains and coastal area (Fig. 10g–i), the elevation of the plume was predominantly between 500 and 1500 m after 20:00 LST. The discussion above indicates that the PM2.5
concentration was not only strongly related to the interaction of ambient
flow with the CMR but also the diurnal variations in boundary layer
development.
(a) The geographic location of the study area in central Taiwan and the
location of NW–SE cross section AA'. Wind field distribution and PM2.5
concentration (unit: µg m-3) along the northwest–southeast
cross section at (b) 05:00 LST, (c) 07:00 LST, (d) 10:00 LST, (e) 12:00 LST, (f)
14:00 LST, (g) 16:00 LST, (h) 18:00 LST, and (i) 20:00 LST on 17 July 2018.
Wind field distribution and ozone concentration (unit: ppb) along
the northwest–southeast cross section AA' in Fig. 10a at (a) 04:00 LST, (b) 08:00 LST, (c) 10:00 LST, (d) 12:00 LST, (e) 14:00 LST, (f) 16:00 LST, (g)
18:00 LST, (h) 20:00 LST, and (i) 23:00 LST.
Figure 11 indicates the ozone cross section in a northwest–southeast
direction in Fig. 10a. A low ozone concentration (<25 ppb) was
observed near ground level because of the dilution effect in the early
morning at 04:00 LST (Fig. 11a) on 17 July. However, a high-ozone layer was
observed between 500 and 1500 m because of the previous day's contribution.
After 08:00 LST, the mixing layer developed, and emissions from traffic and
industry also increased. Concurrently, both the onshore sea breeze over the
plains and the upslope wind over the mountain developed; thus, wind speed
was also enhanced in the low boundary (Fig. 11b–e). The sea breeze and weak wind
speed also exacerbated the high-concentration ozone in the inland area
during the daytime (Fig. 11c–f). At nighttime, the ozone concentration
gradually decreased because of the dilution effect below 500 m (Fig. 11h, i).
However, TEPA measurements revealed that a layer with a high ozone
concentration remained between 1000 and 1500 m (Fig. 7g, h) because low
NOx was emitted over the mountain area in Taichung and Miaoli county.
This also explains why the high ozone concentration first occurred over the
mountain slope area as a result of the concurrent sea breeze and upslope
wind in the morning (Figs. 9a and 11a). That is, the area of high
concentration occurred earlier in the low-emission mountain area than on the
plains, a major emission area. The simulated ozone concentration indicated
that the high concentration did not occur near ground level but at 800–1000 m. This phenomenon was closely related to the development of the boundary
layer structure and its interaction with the upper residual layer formation
on the previous day.
Schematic of the processes of air quality deterioration during an episode
associated with a typhoon over Taiwan's western plains.
Discussion
The wind direction over Taiwan during summer is mostly southerly to
southwesterly (Table 1). However, the wind direction during the episode was
westerly to northwesterly (Table 2). The wind direction changed because of
the critical interaction between typhoon circulations and the CMR. Moreover,
the concentration of PM2.5 and its composition during the episode also
differed significantly from the monthly mean, as revealed in Table 2. A
substantial increase in daily mean PM2.5 was observed at all sites,
especially at the CSM site (urban), where the concentration increased from 16.9
to 40.5 µg m-3 (Table 2). Furthermore, SO42- became the
dominant species in PM2.5. Its concentration increased from the coast
(9.4 µg m-3; 30.5 % of PM2.5) to the mountain station (11.6 µg m-3; 29.7 % of PM2.5), and the urban site had the highest
concentration (12.1 µgm-3; 29.9 % of PM2.5) in PM2.5
among these stations. The SO42- concentration during the episode
(Table 2) was more than twice that of the monthly mean (Table 1) in the
Taichung area. This variation was due to the wind direction changing from
southwesterly to northwesterly, resulting in a contribution increase from
the upstream TPP and THI (Fig. 1c), which are the major sources in central
Taiwan.
On 17 July 2018, Taichung city not only experienced high air pollutant
concentrations but also a maximum air temperature as high as 35.4 ∘C. That is, a heat wave (Lin et al., 2017; Kueh et al., 2017)
occurred on 17 July because of the subsidence of the typhoon circulation on
the lee side of the mountain. The daily mean temperatures for the sampling
sites between 15 and 17 July for SL, CSM, and ZS were 29.9, 30, and 29.4 ∘C, respectively. However, the monthly
mean temperatures (July in 2017 and 2018) during the sampling period for SL,
CSM, and ZS were 28.9, 28.8, and 26.5 ∘C, respectively. Thus, the daily mean temperature during the episode
was 1–2 ∘C higher than is typical for days in July. In general,
the mean wind speed on the episode days at these three sites was weaker
(<1 m s-1) than the monthly mean (Tables 1 and 2). Such stable
weather conditions, weak wind speed, and high air temperature were conducive
to the generation and formation of a secondary aerosol. This is exemplified
by the concentrations of other species, such as OC, NO3-, and
NH4+, being considerably higher during the episode days (Table 2)
compared with the monthly mean in Table 1. Notably, EC increased to a lesser
extent than the other species. These results suggest that secondary
aerosol plays a critical role under such stable weather conditions and wind
direction. Because ambient wind changes during typhoon formation between
Taiwan and Luzon island in the Philippines are not uncommon, the air quality
impacts in such weather conditions merit further research. A detailed
discussion of variations in aerosol chemical composition transformation will
be presented in a separate paper.
Summary
Summer was the season with the lowest air pollution levels in Taiwan during
2004–2019. The monthly mean concentrations of PM10, PM2.5, and
daytime ozone (08:00–17:00 LST) in summer (June–August) over central
Taiwan are 35–40 µg m-3, 18–22 µg m-3, and 30–42 ppb,
respectively. The contribution of OC to PM2.5 can exceed 30 % in
urban and inland mountain sites. However, episodes of poor air quality
frequently occur over the western plains when an easterly typhoon
circulation interacts with the complex topographic structure in Taiwan.
Under such a weather condition, concentrations of PM2.5 and ozone could
be 2 times higher than the monthly mean. During the episode in this
study, SO42- became the major contributor to PM2.5, and its
concentrations and contribution proportions (%) in PM2.5 at coastal,
urban, and mountain sites were 9.4 µg m-3 (30.5 %), 12.1 µg m-3 (29.9 %), and 11.6 µgm-3 (29.7 %), respectively.
To explore the mechanism of air pollution formation, we conducted a detailed
data analysis and WRF-Chem model simulation of an episode of poor air
quality associated with a typhoon event between 15 and 17 July 2018.
Numerical modeling indicated that not only wind direction changes due to lee
vortex but also land–sea breeze and boundary layer development were the key
mechanisms in the transport of air pollutants. We summarize the key
mechanisms and processes of the interaction between typhoon circulation,
lee vortex, land–sea breeze, boundary layer development, and topography as well as
their effects on air quality in Fig. 12.
First, typhoon circulations provided a strong easterly ambient flow. This
easterly flow interacted with the CMR, resulting in a lee vortex formation
over western Taiwan (Fig. 12, left panel).
During the nighttime, the offshore wind (land breeze) pushed the air
pollutants from the mountain area to the plains and coastal areas.
Concurrently, a clear lee vortex formation could be observed near Taiwan's
coastal area in the Taiwan Strait, and thus a southerly flow in the western
plains was enhanced. These processes resulted in trapped air pollutants over
the Taichung area in western Taiwan. The boundary layer height was low
because of ground surface radiation cooling and inversion layer formation.
Therefore, the air pollution plumes remained separate at ground level
coupled with the boundary residual layer being at a higher elevation
(Fig. 12, top right panel).
In the morning, this residual layer with polluted air mass combined and
contributed to the ground surface air concentration level because the
boundary layer height increased. This also explains why the ozone and
PM2.5 concentrations dramatically increased after the boundary layer
development during the daytime. During the daytime, the lee vortex flow
coupled with a sea breeze and combined with a mountain upslope wind
resulted in the accumulation of air pollutants in the inland mountain area.
The peak concentration at the inland mountain site occurred approximately
4–6 h later than at the upstream coastal site because of the sea
breeze (Fig. 12, bottom right panel).
Code availability
Software for maps and plots produced using the HYPERLINK http://cola.gmu.edu/grads/grads.php (Tsai and Doty, 1998) Graphic Analysis and Display System (GrADS) was developed at and supported by HYPERLINK http://cola.gmu.edu/ as well as COLA and George Mason U. (further information can be found at http://cola.gmu.edu/, last access: 18 March 2021).
Data availability
The hourly historical Taiwan EPA air quality monitoring data can be found at https://data.epa.gov.tw/dataset/aqx_p_15 (The Environmental Protection Administration's environmental open data platform, 2020). The sampling data used in this study can be obtained upon request from the corresponding author. The sounding observations can be found in the Data Bank for Atmospheric and Hydrologic Research at https://dbar.pccu.edu.tw/ (Ministry of Science and Technology and Chinese Culture University, 2018).
Author contributions
CYL conceived the idea, performed critical revision of the paper for important intellectual content, and supervised the study. YFS and WCC performed the model simulations. Data analysis and results discussion were contributed by CYL, YFS, WCC, CCKC, YYC, and WMC. CYL prepared the paper with the contributions from all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
The authors sincerely thank the National Center for High-Performance Computing (NCHC) for providing computational and storage resources.
Financial support
This research has been supported by the Ministry of Science and Technology, Taiwan (grant nos. 109-2111-M-001-004 and 108-2111-M-001-002).
Review statement
This paper was edited by Stefano Galmarini and reviewed by two anonymous referees.
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