Introduction
Observations of dust deposition in desertification
regions.
Continent
Location
Period
Dust deposition
Citation
t km-2 yr-1
N. America
Kansas, USA
1964–1966
53.5–62.1
USDA (1968)
New Mexico, USA
1962–1972
9.3–125.8
Gile and Grossman (1979)
Arizona, USA
1972–1973
54
Péwé (1981)
Europe
Spain
2002–2003
17–79
Menéndez et al. (2007)
Africa
Nigeria
1976–1979
137–181
McTainsh and Walker (1982)
Niger
1985
164–212
Drees et al. (1993)
Libya
2000–2001
420
O'Hara et al. (2006)
Oceania
Australia
2000–2001
5–100
Cattle et al. (2009)
Asia
Israel
1968–1973
57–217
Yaalon and Ganor (1975)
Kuwait
1982
2600
Khalaf and Al-Hashash (1983)
Saudi Arabia
1991–1992
4704
Modaihash (1997)
Lanzhou, China
1988–1991
108
Derbyshire et al. (1998)
Loess Plateau, China
2003–2004
133
Liu et al. (2004)
Urumqi, China
1981–2004
284.5
Zhang et al. (2010)
Iran
2008-2009
72–120
Saeid et al. (2012)
Uzbekistan
2003–2010
8365
Groll et al. (2013)
Dust deposition and PM10 concentrations at 14
stations in Xinjiang.
No.
Station
Region1
Latitude
Longitude
Population2
Annual dust
Annual PM10
(million)
deposition
concentration
(t km-2)
(µg m-3)
1
Urumqi
NJ
43.832∘ N
87.616∘ E
2.26
229.4
141
2
Changji
NJ
44.017∘ N
87.308∘ E
0.36
295.7
76
3
Shihezi
NJ
44.306∘ N
86.080∘ E
0.62
107.7
61
4
Bole
NJ
44.900∘ N
82.071∘ E
0.27
133
48
5
Karamay
NJ
45.580∘ N
84.889∘ E
0.29
81.1
54
6
Tacheng
NJ
46.691∘ N
82.952∘ E
0.17
84.9
39
7
Yining
NJ
43.912∘ N
81.329∘ E
0.53
142.7
78
8
Kuytun
NJ
44.426∘ N
84.903∘ E
0.30
108.1
66
9
Hami
EJ
42.818∘ N
93.514∘ E
0.48
209.8
84
10
Turpan
EJ
42.957∘ N
89.179∘ E
0.28
180.1
145
11
Korla
SJ
41.727∘ N
86.174∘ E
0.57
231.8
131
12
Hotan
SJ
37.113∘ N
79.922∘ E
0.33
1394.1
352
13
Kashgar
SJ
39.471∘ N
75.989∘ E
0.57
516.9
236
14
Aksu
SJ
41.170∘ N
80.230∘ E
0.51
511.5
238
1 Xinjiang Province was classified into three regions: northern Xinjiang
(NJ), eastern Xinjiang (EJ) and southern Xinjiang (SJ). 2 Population in 2013 as reported by the Xinjiang Statistical Bureau.
Airborne dust generated by eolian activity is an environmental concern in
central and east Asia (Huang et al., 2011; Chen et al., 2014). Historically,
eolian activity and airborne dust influenced civilization along the ancient
Silk Road which connected Asia and Europe (Zhang, 1984; Dong et al., 2012;
Groll et al., 2013). Today, airborne dust is recognized as a factor
affecting global radiation and warming (Stanhill, 2005; Carslaw et al.,
2013; IPCC, 2013; Huang et al., 2009; Chen et al., 2013; Huang et al.,
2014) and air quality in distant lands (Tsoar and Pye, 1987; Xu et al.,
2007; Uno et al., 2009; Li et al., 2012). Deposition of airborne dust also
plays a significant role in soil formation and biological diversity in arid
and semi-arid regions (Simonson, 1995; Lin and Feng, 2015; Varga et al.,
2016). An understanding of atmospheric dust sources, emissions and
deposition is therefore essential to improve our knowledge of dust impact on
regional air quality.
Location of Xinjiang Province in China (gray area
outlined on inset map). Dust deposition and concentrations were measured at
stations signified by small triangles. Land use types are identified across
the province according to Wang et al. (2005).
Dust in the atmosphere and its subsequent deposition are vital indicators of
eolian activity and environmental quality. Deposition has been measured
directly at only a few sites; therefore, reliable dust deposition data are
lacking around the world (Pye, 1987; Mahowald et al., 1999, 2009; Prospero, 1999;
Zhang et al., 2010; Huneeus et al., 2011; Shao et
al., 2011). Annual dust deposition ranges from 10 to 200 t km-2 on
continents and 1–2 orders of magnitude lower over oceans (Pye, 1987;
Duce et al., 1991; Ginoux et al., 2001, 2012). It is
estimated that the annual average dust deposition rate in desert areas ranged
between 14 and 2100 t km-2 (Zhang et al., 1997). Observations of dust
deposition have been made over deserts with an enhanced awareness of its
significance. Table 1 lists observations of dust deposition in desert
regions and other regions of the world prone to eolian activity. According
to these observations (Table 1), dust deposition is high in Asia with an
annual deposition of 8365 t km-2 in the Aral Sea Basin (Wake and
Mayewski, 1994; Groll et al., 2013). Recent investigations suggest that the
intensity of dust deposition is closely related to weather. For example,
dust deposition during extreme highly winds can be 10 to 25 times higher than
the annual average (Liu et al., 2004; Zhang et al., 2010; Goudie, 2014). The
observations on dust deposition are ordinarily scattered and discontinuous.
The limited observational data restricted our understanding of dust fluxes
between the atmosphere and land surface; thus numerical simulations are
needed to evaluate dust fluxes and the rate of global dust deposition.
Ginoux et al. (2001) simulated dust deposition at 16 sites around the world
and predicted the annual global dust deposition was approximately 1842
megatons. Shao et al. (2011) estimated that over 2000 megatons of dust is
emitted from the Earth's surface into the atmosphere annually. Zheng et
al. (2016) estimated that annual average global dust deposition was
approximately 1161 megatons. However, uncertainties remain in estimating the
dust deposition budget of the Earth system because of the lack of
observational data and inaccuracies of parameters in numerical simulations
(Ginoux et al., 2001, 2012; Huneeus et al., 2011; Shao et al., 2011; J. Zhang et al., 2014). Observation of worldwide dust deposition
is urgently needed to assess biogeochemical cycle of dust on Earth.
Located in east Asia and at the boundary of central Asia, Xinjiang Province
of northwestern China has long played a strategic role in cultural and
economic trade between Asia and Europe. Xinjiang Province experiences severe
sand and dust storms and is highly susceptible to desertification (Chen,
2010). Xinjiang Province is one of two major source regions of atmospheric
dust in China, the other region being western Inner Mongolia (Xuan, 1999;
Xuan et al., 2000). Long-range transport of dust from the region strongly
affects air quality in east Asia (Derbyshire et al., 1998; Uno et al.,
2009). In fact, dust from the region can be transported across the Pacific
Ocean and thus impact air quality in North America (Husar et al., 2001;
Osada et al., 2014). Indeed, particulate matter associated with dust
transport can severely deteriorate air quality (Sharratt and Lauer, 2006;
Shoemaker et al., 2013). Over the past decades, many observations have been
made of processes that govern dust emissions, transport and deposition in
Asia (Shao et al., 2011; Groll et al., 2013). Little is known, however,
concerning dust deposition and concentrations in Xinjiang Province. In fact,
temporal and spatial variations in dust deposition and concentration have
not been characterized despite the importance of dust transport from the
region. To improve our understanding of the fate and transport of airborne
dust in central and east Asia, there is a need for continuous and long-term
records of dust deposition and concentration. The purpose of this study is
to characterize the spatiotemporal distribution of dust deposition and
particulate matter concentration in Xinjiang Province. This characterization
will strengthen our comprehension of aerosol transport in east Asia and
provide aerosol data for modeling dust transport in global desertification
regions.
Annual average dust deposition reported at 14 stations in
Xinjiang Province from 2000 to 2013. Land use types across the province are
identified according to Wang et al. (2005).
Methods
Study area
Xinjiang Province is located in northwest China and is the largest inland
province which covers an area of more than 1.6 million km2 (Fig. 1).
The Taklamakan and Gurbantunggut deserts are located in the province. The
Taklamakan Desert, located in the southern region, is the world's largest
shifting-sand-dune desert. The Gurbantunggut Desert, located in the northern
region, is the largest fixed-dune desert in China. The province is in part
characterized by extreme aridity and eolian desertification. The average
annual precipitation varies from more than 700 mm in high-altitude forests
and mountains to less than 50 mm in the deserts. Annual potential
evaporation can exceed 2000 mm in desert regions (Chen, 2010). Sand and dust
storms occur throughout the year but are most common in spring. In this
study, the province was divided by latitude and longitude into three
regions, those being northern Xinjiang, eastern Xinjiang and southern
Xinjiang (Table 2).
Experimental data
Dust deposition and PM10 concentration were measured at environmental
monitoring stations maintained by the Xinjiang Environmental Protection
Administration, a division of the Ministry of Environmental Protection (MEP)
in China. Data collected at 14 stations (Fig. 1 and Table 2) were used in
this study and represent a spatial distribution within this region.
Dust deposition was determined by the gravimetric method and documented at
monthly intervals. Glass cylinders were used to monitor dust deposition.
Three cylinders (replicates) were installed to monitor dust deposition at
each station. The cylinders (0.15 m in diameter, 0.3 m tall and open at the
top) were partly filled with an ethylene glycol (C2H6O2)–water
solution prior to deployment. The solution enabled trapping of dust in
a liquid medium at temperatures below 0 ∘C and also minimized
evaporation from the cylinder. Cylinders were mounted vertically on a tower
at approximate 10 m above ground. The mass of dust collected by the
cylinders was determined after washing the contents out of the cylinders and
oven-drying the contents at 105∘. Dust deposition rate was
calculated as the mass of dust per unit area per unit time and expressed in
units of t km-2 month-1 (MEP, 1994). Monthly and yearly dust
deposition data were available through the MEP for the 14 stations from
2000 to 2013.
Annual average dust deposition in Xinjiang Province from
2000 to 2013. Dust deposition in northern, eastern and southern Xinjiang is
the average deposition at 8, 2 and 4 stations, respectively.
Ambient PM10 concentration was measured with high-volume samplers
designed to collect particulate matter by filtration. The samplers were
installed at 1.5 m above the ground and equipped with fiberglass filters for
trapping PM10. PM10 concentration was determined based upon
gravimetric filter analysis and flow rate of each sampler. Daily PM10
concentration data were obtained by the arithmetic mean of four samplers,
with the sampling time being > 18 h for each sampler. PM10
was expressed in units of µg m-3 (MEP, 2011). Annual PM10 data were
available through the MEP for the 14 stations (Xinjiang Statistical Bureau,
2014).
Daily meteorological data – including dust days, surface wind speed and
precipitation – were collected from the China Meteorological Administration.
A dust day was defined by visibility according to World Meteorological
Organization (WMO) protocol; days on which visibility was < 10 km at any
observation time throughout the day constituted a dust day. The WMO further
classifies dust days as dust in suspension, blowing dust and dust storms
(http://www.wmo.int/pages/prog/www/WMOCodes.html; Shao and Dong, 2006).
Dust in suspension constitutes days on which dust is emitted at the station
at the time of observation and visibility is < 10 km, blowing dust
constitutes days on which dust or sand is emitted at the station and
visibility is 1–10 km, and dust storms constitutes days on which dust or
sand is emitted at the station and visibility is < 1 km.
Observations of visibility and wind characteristics at each station were
taken at 3 h intervals throughout the day.
Monthly average dust deposition in Xinjiang Province from
2000 to 2013. Dust deposition in northern, eastern and southern Xinjiang is the
average deposition at 8, 2 and 4 stations, respectively.
Daily air pollution index (API) data were obtained from air quality
monitoring statistics published by the MEP (http://datacenter.mep.gov.cn).
These data were used to illustrate the impact of airborne dust versus other
air pollutants on air quality. The API is calculated according to the daily
concentration of three main air pollutants (USEPA, 2006; Wang et al., 2013),
namely PM10, SO2 and NO2. The API is calculated as
API=max(APIi),APIi=APIu-APILCu-CL×Ci-CL+APIL,
where APIi is the index for pollutant i (i.e., PM10, SO2 and
NO2), APIu and APIL are the upper and lower limits of the
index for a specific category of air quality (i.e., excellent, slight,
moderate, moderately severe and severe), Ci is the observed
concentration of pollutant, and Cu and CL are the upper and lower
limits of the pollutant for a specific category of air quality.
Annual average PM10 concentration reported for 14
stations in Xinjiang Province from 2000 to 2013. Land use types are identified
across the province according to Wang et al. (2005).
Information regarding the determination of the API index can be obtained
from the MEP (MEP, 2012a, b). Based on the API, air quality was
classified as excellent with an API of 0 to 50, slight pollution with an
API of 50 to 100, moderate pollution with an API of 100 to 200, moderately
severe pollution with an API of 200 to 300 and severe pollution with an API
of 300 to 500. For the purpose of this study, we used only API data
collected in 2010 since annual deposition and PM10 concentration
appeared to typify that which occurred between 2000 and 2013 in eastern,
northern and southern Xinjiang Province.
Temporal trends in dust deposition, PM10 concentration and dust days
were evaluated by testing the significance of the slope estimate using a t
test at a probability level (P value) of 0.05.
Results and discussion
Dust deposition
Detailed information on dust deposition during 2000–2013 was obtained from
14 environmental monitoring stations (Table 2). Annual average dust
deposition across all stations in Xinjiang Province was 301.9 t km-2.
The highest annual deposition occurred in Hotan and Kashgar in southern
Xinjiang, while the lowest deposition occurred in Karamay in northern
Xinjiang. Based upon spatial characteristics in annual dust deposition,
deposition increased from north to south across the province (Fig. 2). The
annual average dust deposition was 147.8, 194.9 and 663.6 t km-2 in
northern, eastern and southern Xinjiang, respectively. Generally, the origin
of mineral dust could be attributed to both natural and anthropogenic
sources (Miller-Schulze et al., 2015). Although dust deposition was
relatively low (< 150 t km-2) for the majority of stations in
northern Xinjiang Province, dust deposition was at least 50 % higher for
stations within the industrial belt on the northern slope of the Tianshan
Mountains. This industrial belt includes Changji and Urumqi. High dust
deposition in the industrial belt was due to local industry, coal burning
and vehicle exhaust (Matinmin and Meixner, 2011; X. X. Zhang et al., 2014).
Therefore, the mixing of the anthropogenic aerosol with transported desert
dust contributed to deposition in Changji and Urumqi (Li, et al., 2008).
Figures 3 and 4 depict the temporal variation in dust deposition from
2000 to 2013. The highest annual deposition occurred in 2012 in southern
Xinjiang, 2002 and 2012 in eastern Xinjiang, and 2001 in northern Xinjiang.
Over the 14-year period, dust deposition varied with time across Xinjiang
Province. The slope estimate of the relation between average dust deposition
and year (-6.4 ± 0.1 t km-2 yr-1) was significant at
P= 0.05. This trend was most apparent in northern Xinjiang (slope estimate
was -5.6 ± 0.1 t km-2 yr-1) and least apparent in southern
Xinjiang (slope estimate was -1.9 ± 0.1 t km-2 yr-1). High
dust deposition occurred in spring in eastern and northern Xinjiang and in
spring and summer in southern Xinjiang (Fig. 4). Dust deposition peaked in
April in eastern and northern Xinjiang and in May in southern Xinjiang. This
corresponds to the onset of wind erosion caused by intensifying zonal flow
and rising air temperatures before the arrival of the summer monsoon (Song
et al., 2016). The maximum monthly average dust deposition was 97.5 t km-2 in southern Xinjiang, which was 6.9 and 8 times more than the
deposition in northern and eastern Xinjiang, respectively. These results
suggest that dust deposition in south Xinjiang is of similar magnitude to
deposition that occurs in the Middle East and Sahel regions (Khalaf and
Al-Hashash, 1983; McTainsh and Walker, 1982; O'Hara et al., 2006).
Annual average PM10 concentration in Xinjiang
Province from 2000 to 2013.
PM10 concentration
The annual average PM10 concentration in Xinjiang was 125 µg m-3 based upon data collected at 14 stations from 2000 to 2013. Ten
stations (71 %) in our study had an annual average PM10
concentration above the People's Republic of China Class II residential
standard of 70 µg m-3. The highest annual average PM10
concentration (352 µg m-3) occurred in Hotan in southern
Xinjiang, while the lowest average PM10 concentration (46 µg m-3) occurred in Tacheng in northern Xinjiang. The annual average
PM10 concentration appeared to increase from northern to southern
regions (Fig. 5). Annual average PM10 concentration in Xinjiang ranged
from 100 to 196 µg m-3 (Fig. 6) across years. The annual average
PM10 concentration was 70, 115 and 239 µg m-3 in northern,
eastern and southern Xinjiang, respectively. The high annual concentration
in southern Xinjiang is of the same magnitude as found in other
desertification regions of the world such as south Asia, the Middle East and
the western Sahel (WHO, 2016a). These high concentrations of suspended
particulates, especially finer particulate, may influence the health of
sensitive populations who are susceptible to respiratory illness (Goudie,
2014).
Relationship between annual dust deposition and PM10
concentration in Xinjiang Province. Each point represents data averaged
across 2000 to 2013 at one station.
Over the period of record (2000–2013), there was a trend of decreasing
PM10 concentration in Xinjiang Province. The slope estimate of the
relation between annual PM10 concentration and year (-4.2 ± 0.1 µg m-3 yr-1)
was significant at P= 0.05. This trend was most apparent in southern Xinjiang
(slope estimate was -11.8 ± 0.1 µg m-3 yr-1). However, PM10 concentration
appeared to increase with time in eastern and northern Xinjiang (slope
estimates were 1.3 ± 0.1 and 3 ± 0.1 µg m-3 yr-1, respectively). The slope estimate, however,
was not statistically different from zero and indicated no apparent trend in
PM10 concentration with time in northern Xinjiang. A decrease in both
dust deposition and PM10 concentration over 2000 to 2013 suggests a
positive relationship between dust deposition and PM10 concentration.
This relationship is supported by data in Fig. 7. Dust particles are
delivered back to the surface by both dry and wet deposition (Shao, 2000).
In arid and semi-arid regions of central Asia, the deposition process is
mainly dominated by dry deposition because of less precipitation, which is
comprised of gravitational settling, turbulent diffusion and molecular
diffusion (Zhang and Shao, 2014; Xi and Sokolik, 2015). Those physical
processes from the air to surface are complex and dependent on dust
concentration: the higher the dust concentration,
the higher the dust deposition (Slinn and Slinn, 1980; Wesely and Hicks, 2000;
Petroff, et al., 2008; J. Zhang et al., 2014). Figure 7 showed that dust
deposition significantly increased with high PM10 concentration above
200 µg m-3. A logarithmic function fit the data better than a
linear function, suggesting that changes in atmospheric PM10
concentration are smaller at higher rates of deposition with a correlation
coefficient R2≥ 0.81. This trend could be due to deposition of
larger or more massive particles under more severe dust or sand storms.
While PM10 concentration may rise under more severe wind erosion
events, the limited supply of PM10 in sand (major soil type in the
province) will likely suppress a rise in PM10 concentration in the
atmosphere under more severe erosion events. Nevertheless, from 2000 to
2013, the decline in both dust deposition and PM10 concentration across
Xinjiang could be due to less frequent or intense dust storms because dust
deposition in major cities of northern China was found to be closely related
to the frequency of sand and dust storms (Zhang et al., 2010).
Daily air pollution index for Kuytun and Urumqi in
northern Xinjiang, Hami and Turpan in eastern Xinjiang, and Kashgar and
Hotan in southern Xinjiang in 2010. The main air pollutant contributing to
the daily API is identified for each station. “Not detected” indicates
excellent air quality (API < 50).
Influence of atmospheric dust deposition on local air quality
Daily ambient air quality has been reported by the MEP since 2000. Airborne dust
is one of three pollutants influencing the API; thus the relative
contribution of dust to the API was of interest. Accordingly, we made a
comparative analysis to identify the impact of airborne dust on air quality
in Urumqi and Kuytun in northern Xinjiang, Turpan and Hami in eastern
Xinjiang, and Kashgar and Hotan in southern Xinjiang (Fig. 8). In 2010,
there were 178, 286, 351, 334, 363 and 360 days on which PM10 was
the main constituent of the API in Kuytun, Urumqi, Turpan, Hami, Kashgar and
Hotan, respectively (Fig. 8). The PM10 constituent accounted for
48.7, 78.4, 96.2, 91.5, 99.5 and 99.6 % of the API in
the respective above cities. These data suggest that particulate matter is
the main air pollutant in Xinjiang. Severe PM10 pollution (API > 300) occurred mainly in spring, which was closely associated
with the seasonality of strong winds and dust storm activity (Li et al.,
2004). Stations in southern Xinjiang (Kashgar and Hotan) had higher APIs
caused by elevated PM10 concentrations throughout the year. This can be
attributed to the violent and persistent eolian activity around the
Taklamakan Desert (Pi et al., 2014). Consequently, PM10 is an important
pollutant which dominates ambient air quality in Xinjiang.
Dust day frequency in Xinjiang Province from 2000 to
2013.
Factors influencing dust deposition and PM10 concentration
Many factors influence ambient particulate concentration and dust
deposition, but weather appears to be a dominate factor in arid regions
(Zhang et al., 1996, 2010). In fact, dust activity is highly
correlated with variability in global climate and atmospheric circulation
(Gong, et al, 2006; Mao et al., 2011; Shao et al., 2013). The Eurasian
atmospheric circulation greatly affects weather in central and east Asia
(Zhang et al., 1997; Kang et al., 2013; Xi and Sokolik, 2015). Dust
activities are primarily driven by the strength of cyclones and the Siberian
High affecting the study region (Park et al., 2011; Shao et al., 2013).
Strong winds associated with this atmospheric circulation cause large
amounts of dust to be emitted into the atmosphere. Deserts in central Asia
are an important source of atmospheric mineral dust (Miller-Schulze et al.,
2015). Under the strong westerly circulation, atmospheric dust can be
transported a few hundred kilometers to the east and be deposited through
wet scavenging and dry settling (Shao, 2000; Chen et al., 2014). Despite the
Taklimakan and Gurbantunggut deserts being local sources of dust in Xinjiang
Province, long-range transport of dust from the central Asian Aralkum,
Karakum, Caspian and Kyzylkum deserts (Indoitu et al., 2012) could also
contribute to the dust deposition and ambient PM10 concentration in
neighboring Xinjiang Province. Since the 1980s, the Aralkum Desert in
Uzbekistan and Kazakhstan has become one of world's youngest deserts and a
potential source of salt dust in east Asia (Indoitu et al., 2012; Groll et
al., 2013; Opp et al., 2016).
Relationship between annual dust deposition and dust day
frequency in Xinjiang Province. Each point represents data averaged across
2000 to 2013 at one station.
Climate also directly influences the atmospheric environment of arid and
semi-arid areas (Wei et al., 2004; Zu et al., 2008; Huang et al., 2014). The
annual average precipitation in north, east and south Xinjiang is 237, 94
and 87 mm, respectively. Dust emission was negatively correlated with
precipitation (Gong et al., 2006). Therefore, the lack of precipitation
contributes to dust emissions. In fact, regions with lower precipitation
have higher PM10 concentrations and dust deposition in Xinjiang
Province. Daily average wind speed in north, east and south Xinjiang is 2.5,
2.2 and 1.8 m s-1, respectively. In contrast to precipitation,
regional differences in wind speed fail to account for differences in
PM10 concentrations and dust deposition. Dust distribution in south
Xinjiang (including the Tarim Basin and Taklamakan Desert), however, is
strongly affected by wind flow patterns. Eolian transport in the Taklamakan
Desert is predominantly from the northeast toward the south (Wang et al.,
2014; Rittner et al., 2016). Huang et al. (2014) reported that the
Taklamakan Desert is a source of fine dust particles (≤ 3 µm in
aerodynamic diameter) which significantly influences East Asia. Strong
northeast winds dominate the prevailing wind regime in the eastern
Taklamakan Desert; these winds influence air quality in both the eastern and
the southeastern parts of the desert. The western and northern parts of the
Taklamakan Desert and Tarim Basin are highly affected by west, northwest and
north winds (Sun and Liu, 2006; Zan et al., 2014; Li et al., 2015). Under
prevailing winds, dust aerosols are transported from the northern to the
southern Taklamakan Desert (e.g., Hotan city) and thereby cause high ambient
PM10 concentration and dust deposition.
Relationship between PM10 concentration and dust
day frequency in Xinjiang Province. Each point represents data averaged
across 2000 to 2013 at one station.
Spatial differences in dust deposition and PM10 concentration across
Xinjiang Province may also be due in part to differences in frequency of
dust days in the region. Dust storms normally occurred in all seasons in
southern Xinjiang. The magnitude of wind erosion and dust day frequency in
southern Xinjiang is nearly twice as large as in northern and eastern
Xinjiang (Wang et al., 2006). Figure 9 displays the variation in dust day
frequency in Xinjiang Province from 2000 to 2013. The data indicate that the
annual average frequency of dust days fluctuated from 15 to 52 days. The
frequency of dust days in the southern region ranged from 41 to 133 days,
while the frequency of dust days in eastern and northern regions ranged from
2 to 45 days and from 0 to 3 days, respectively, across years. The slope estimate of
the relationship between dust days and years (0.11 day yr-1) indicated
no apparent trend for an increase or decrease in dust days from 2000 to
2013. Thus, despite no temporal trend in dust days, we observed a decline in
dust deposition and PM10 concentration across years. This decline in
dust deposition or PM10 concentration could be due to a decrease in
frequency of severe dust days versus frequency of dust days from 2000 to
2013 in the region. We are unaware of any previous study which has examined
dust day severity in Xinjiang Province; thus we used data available through
the China Meteorological Administration to assess trends in dust day
severity. Dust days were characterized according to dust-in-suspension,
blowing dust and dust storm events. Although there was no trend in the
frequency of blowing dust and dust storm events from 2000 to 2013, there was
a trend for fewer dust-in-suspension events from 2000 to 2013 (Fig. S1 in
the Supplement). Thus, there appeared to be a close association between
frequency of dust-in-suspension events and PM10 concentration and dust
deposition. Nevertheless, in examining the relationship between average
annual dust days and dust deposition or PM10 concentration across
stations, the frequency of dust days was closely related to dust deposition
(R2= 0.93; Fig. 10) and ambient PM10 concentration
(R2= 0.89; Fig. 11). There was a significant increase in dust
deposition (7.91 t km-2 day-1) and PM10 concentration (2.06 µg m-3 day-1) associated with an increase in dust days.
Conclusions
The atmospheric environment of central and east Asia is severely affected by
the airborne dust; thus this study was undertaken to quantify dust
deposition and ambient PM10 concentration in east Asia. Data collected
at 14 environmental monitoring stations from 2000 to 2013 in Xinjiang Province,
China, confirmed that annual average dust deposition ranged from 255.7 to
421.4 t km-2. Annual average PM10 concentration varied from 100 to
196 µg m-3. The highest dust deposition was observed in Hotan in
the southern Taklamakan Desert with 1394.1 t km-2, which is 10 times
that in China's Loess Plateau (Liu et al., 2004). The highest ambient
PM10 concentration was also observed in Hotan with 352 µg m-3, which far exceeds the World Health Organization's long-term
exposure standard (WHO, 2016b). These observation results provide concrete
evidence on the study area as “dust region” described by Shao et al. (2011)
and Ginoux et al. (2012), and they suggest that dust sources in east Asia
affect regional air quality and is a potential contributor of global dust.
The spatial distribution and temporal variability in dust deposition and
ambient PM10 concentration showed significant variation and a trend for
lower deposition and concentration with time. The interannual dynamic of
dust deposition varied significantly with seasonality. Spring and summer had
the highest dust deposition (1.3 times the average), followed by autumn and
winter. The highest intensity of dust deposition was observed in May,
followed by April, June and July.
In dust source areas such as Xinjiang, China, windblown sand and dust affect
air quality, especially during the spring season. The analysis of the data
indicated no trend in frequency of dust days from 2000 to 2013. A positive
relationship existed, however, between dust days and dust deposition as well
as airborne PM10 concentration across stations. The effect of weather
on dust deposition and ambient air quality cannot be expressed by a simple
correlation and should not be extrapolated based on the currently limited
evidence. This study provides information on the potential spatiotemporal
dust deposition and ambient dust aerosol variation in east Asia. Although
longer-term datasets are needed to address trends over longer time periods,
this work can aid in adjusting model parameters in simulating dry dust
deposition or PM10 concentration in desertification regions of east
Asia.