PUBLICATIONS
Journal of Geophysical Research: Atmospheres
RESEARCH ARTICLE
10.1002/2014JD021721
Key Points:
• Structures of aerosol plume have been
characterized by satellite observations
• Optical property variations due to
aerosol mixing have been identified
• Percentage of dust-soot mixtures is
significant in transpacific transport
Impact of pollution on the optical properties
of trans-Pacific East Asian dust from satellite
and ground-based measurements
Bingqi Yi1, Ping Yang1, and Bryan A. Baum2
1
Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA, 2Space Science and Engineering
Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
Abstract
Correspondence to:
B. Yi,
bingqi.yi@tamu.edu
Citation:
Yi, B., P. Yang, and B. A. Baum (2014),
Impact of pollution on the optical
properties of trans-Pacific East Asian
dust from satellite and ground-based
measurements, J. Geophys. Res. Atmos.,
119, 5397–5409, doi:10.1002/
2014JD021721.
Received 6 MAR 2014
Accepted 17 APR 2014
Accepted article online 23 APR 2014
Published online 9 MAY 2014
We investigate changes in the optical properties of a large dust plume originating from East
Asian deserts during its transport over the northwestern Pacific Ocean in March 2013. The study makes
use of observational products from two sensors in the NASA A-Train satellite constellation, the Moderate
Resolution Imaging Spectroradiometer and the Cloud-Aerosol Lidar with Orthogonal Polarization. Forward
trajectory clustering analysis and satellite observations show that dust initiating from the Taklimakan and
Gobi deserts experienced thorough mixing with industrial pollution aerosols shortly after leaving the source
region and were lofted by a strong midlatitude weather system to more than 4 km in height. The dust plume
accompanied the weather system and reached the east coast of the North American continent within 7–10
days. The dust aerosols became spectrally absorptive during transport due to mixing with other aerosol types
such as soot. Furthermore, a decrease in the depolarization ratio suggests that the complexities in aerosol
particle morphologies were reduced during transport over the ocean. More than half of the dust aerosol
layers surviving the trans-Pacific transport were polluted and exhibited different optical properties and
radiative effects from those of pure dust.
1. Introduction
Aerosols originating from East Asia affect not only local and regional areas but also remote locations
thousands of kilometers away [Uno et al., 2009], i.e., North America [Chin et al., 2007; Yu et al., 2008, 2012] and
the Arctic [Di Pierro et al., 2011]. The aerosols have a significant impact on radiation and precipitation [Li et al.,
2007, 2011]. Dust aerosol is one of the most important atmospheric components in the East Asian region.
Dust storms in China are often associated with frontal and midlatitude cyclonic systems [Sun et al., 2001]. Liu
et al. [2011] investigates the horizontal and vertical structures, transport behavior, and radiative effects of two
dust events that reached the Yangtze Delta region of China by observational and modeling studies. Wu et al.
[2013] investigates the characteristics of the East Asian aerosol transport and distribution, which is
modulated by wind divergence/convergence, from the GOCART (Goddard Chemistry Aerosol Radiation and
Transport) model results. Dust aerosols from the Taklimakan and Gobi deserts contribute differently to the
vertical structures of dust plumes in the downstream regions. Based on combined lidar observations and
modeling results, Itahashi et al. [2010] identifies two patterns of spring aerosol outflow related to different
meteorological systems over East Asia. From 5 years of spaceborne lidar layer products, Liu et al. [2013] finds
that East Asian dust exhibits decreased particulate depolarization ratios, which may be related to the mixing
of dust with pollutants or other aerosols from different source regions during the northward and eastward
trans-Pacific transport.
During the boreal spring, the predominant aerosols over East Asia are dust and industrial pollution aerosols.
With major dust sources located to the northwest and urban industrial areas located to the east of the
continent, there is a question as to what optical property changes might occur when such aerosols are
transported through pollution-laden areas and over the ocean. The optical properties are necessary for
simulating the spectral, narrowband, and broadband radiances of the dust aerosols in numerical models.
Numerous previous studies provide possible scenarios from observational and modeling perspectives. Clarke
et al. [2004] examines the size distributions and mixing states of aerosol outflow from East Asia and concludes
that optical properties and radiative forcing of aerosol mixtures cannot be simply derived by linearly adding
or scaling the individual sources. Anthropogenic soot dominates the small (i.e., submicron) particle size range
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and is transported with the dust as a mixture. Li et al. [2012] simulates a March 2010 super dust storm in which
the mixing of dust with pollution is evident and significantly affects the atmospheric chemistry cycle when
the storm passes over the Northern China plain. Strong radiative effects (i.e., heating) resulting from the
mixing state of black carbon together with other aerosol constituents (i.e., dust and sulfate) are shown in
other studies [Jacobson, 2000, 2001]. Lau et al. [2006] discusses the important heating effect of a dust and
soot mixture over the Tibetan Plateau. The chemical components of a dust and pollution mixture are reported
at the northern edge of the Loess Plateau [Wang et al., 2011]. The influence of pollution (especially soot) on
dust aerosol retrievals by satellite observations is found to be significant [Lin et al., 2013]. Yang et al. [2013]
combines modeling results and satellite observations for a study of African dust and smoke aerosol mixing.
While these studies provide a growing sense that the mixing of pollution with dust affects many remote
sensing aerosol and cloud products, there is little information available about the detailed structure and
components of an aerosol mixture plume, particularly in the vertical profile, and of the changes occurring
in the optical properties during transport over long distances. Since satellites cover large spatial areas at
high resolution, they provide a unique way to monitor and characterize the aerosol initialization and
transport. In this study, we combine the aerosol layer/profile products from the Moderate Resolution
Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP).
Ground-based aerosol measurements are employed to reveal the detailed horizontal and vertical
structures of a trans-Pacific aerosol plume.
Section 2 describes the data and model used for the study. Section 3 shows the results from the forward
trajectory model and observational data sets depicting the meteorological conditions, as well as the mixing and
transport of the aerosols from East Asia to North America. Section 4 summarizes and concludes this study.
2. Data and Trajectory Model
2.1. Data Sets Used in This Study
Multiple data sets are employed to analyze the mixing and transport processes of East Asian dust and
pollutants and the relationship with meteorological conditions.
Aerosol optical depth (AOD) is obtained at the 550 nm wavelength from the Aqua MODIS satellite Collection
5.1 Level-3 daily averaged retrievals (downloaded from http://ladsweb.nascom.nasa.gov/data/). MODIS AOD
is retrieved from different combinations of the solar channels over land and ocean. Higher uncertainties are
reported with a dark target background over land, ±(0.05 + 0.15τ), than ocean, ±(0.04 + 0.10τ), where τ is the
AOD [Levy et al., 2007, 2010; Remer et al., 2005]. Deep Blue algorithm products [Hsu et al., 2006] provide AOD
over bright surfaces such as deserts. The MODIS daily AOD retrievals provide total column aerosol
properties globally.
Vertical profiles of aerosol type, extinction coefficient, backscattering coefficient, and depolarization ratio are
provided in the Level-2 CALIOP aerosol layer/profile products at 532 nm and 1064 nm wavelengths [Liu et al.,
2009; Winker et al., 2009; Young and Vaughan, 2009] on the CALIPSO (Cloud-Aerosol Lidar and Infrared
Pathfinder Satellite Observation) satellite (available for download at https://eosweb.larc.nasa.gov/project/
calipso/calipso_table). Together with the Aqua MODIS in the A-Train satellite constellation, CALIOP aerosol
products reveal the vertical distributions of various aerosol types and their optical properties, although for
only a very narrow portion of the MODIS swath.
AERONET (Aerosol Robotic Network) aerosol inversion products (Version 2, Level 2.0, available for download
at http://aeronet.gsfc.nasa.gov) are used for selected sites within East Asia to illustrate and confirm the
aerosol optical property changes. Level 1.5 AERONET inversion data are used in place of Level 2.0 when Level
2.0 data are not available. The AERONET direct sun algorithm AOD is very accurate, with an uncertainty of
about ±0.01 [Holben et al., 2001], and is often regarded as the benchmark measurement. Inversion products
include aerosol single-scattering albedo, asymmetry factor, and refractive index, which provide additional
information about the aerosol characteristics [Dubovik and King, 2000].
NCEP-DOE (National Centers for Environmental Prediction - Department of Energy) reanalysis II data
[Kanamitsu et al., 2002] provide the meteorological information, i.e., horizontal/vertical wind fields during the
dust outbreak and transport processes (available from http://www.esrl.noaa.gov/psd/data/gridded/data.
ncep.reanalysis2.html).
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The primary focus period of our study is during March 2013 although we present findings from the entire
boreal spring season (March-April-May) to capture the numerous dust plume outbreaks that were initiated
from East Asian deserts.
2.2. HYSPLIT (Hybrid Single-Particle Lagrangian Trajectory) Model
The NOAA/ARL (National Oceanic and Atmospheric Administration/Air Resources Laboratory) HYSPLIT model
[Draxler and Hess, 1998] is used for the backward/forward trajectory analysis to characterize the aerosol
transport process. In this study, the HYSPLIT model is initiated with the NCEP reanalysis meteorological fields at
6 hourly intervals with a horizontal resolution of 2.5 × 2.5° (available for download at http://www.esrl.noaa.gov/
psd/data/gridded/data.ncep.reanalysis.html). Vertical motion information from the reanalysis model product is
used in the trajectory calculations. A clustering technique, in conjunction with the HYSPLIT model, is used to
classify different trajectory categories from various sources. The clustering technique is described in section 3.1.
3. Results and Discussion
In this section, we first present the forward trajectory clustering analysis results from the HYSPLIT model to
illustrate the general trends of aerosol transport paths. A typical dust emission and transport event lasting
about 10 days in late March 2013 is selected for in-depth study using a combination of satellite and groundbased measurements. Our statistical study is based on the analysis for March 2013 and then extended to the
boreal spring season in 2013.
3.1. HYSPLIT-Simulated Dust Transport Trajectories
The HYSPLIT model-simulated forward trajectories are used to identify the general trends of aerosol plume
propagation and evolution during March 2013. Three sets of 10 day forward aerosol trajectories, starting at
the boundary layer from 500 to 1000 m above ground level, are calculated four times daily for the entire
month of March 2013, for a total of 124 trajectories, for three selected aerosol source regions: the Taklimakan
desert (41°N, 88°E), Gobi desert (43°N, 108°E), and metropolitan east coast of China (31°N, 119°E). The
trajectory cluster analysis is performed to discriminate different aerosol transport trends/tendencies in the
horizontal and vertical directions. Similar trajectories are paired to form clusters in the clustering analysis,
from which maximized differences are found. More details of the clustering technique can be found in the
manual and references of the HYSPLIT model [Draxler and Hess, 1998].
Dust aerosols entrained from within the Taklimakan desert at 500 m above ground level (Figure 1a) result in
four major clusters of trajectories, of which approximately one third pass over the east coast of China and are
transported over the Pacific Ocean in two branches. One branch moves toward high latitudes, while the other
moves toward the central northern Pacific Ocean. Approximately 46% of the trajectories reach the east coast
of China where industrial pollution is dominant. The remaining 25% are confined in the planetary boundary
layer (< 1 km in height) and typically affect the local region. Comparatively, nearly half of the dust aerosols
from the Gobi desert (Figure 1b) are transported toward higher latitude regions, of which about 40% mix with
the pollution over the east China coast, and approximately 11% are transported off the continent but remain
at an altitude of 2 km. Our results are in general agreement with those of Sun et al. [2001] and Zhu et al. [2007].
Note that a significant amount of dust converges on the highly polluted east China coastal area where
aerosol mixing is possible.
The urban metropolitan region has not only local industrial pollution emissions from within the boundary
layer but also desert dust aerosols that are advected into the area at an altitude of approximately 1 km
(Figures 1a and 1b). Thus, trajectories are calculated for the east China coastal area with higher starting
altitudes of 1000 m (Figure 1c). A significant number of the trajectories (28%) remain in the boundary layer
within a short distance from the source region. The remaining trajectories show a similar trend of
northwestward movement before reaching 160°E. Approximately 13% of the trajectories diverge to higher
latitudes, another 30% are terminated during the journey, and 30% remain to complete the trans-Pacific
transport. The trajectory analysis indicates that aerosols generally need to be at heights of at least 3000 m in
height (Figure 1) to be transported to as far as 180°E. If the aerosol layer is lofted higher initially, the layer
tends to move over greater distances and the transport tends to occur more quickly.
From the analysis, we find that aerosols from various sources have the potential to travel long distances.
However, the key point for the long-range transport is the aerosol entrainment height, which is largely
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Figure 1. HYSPLIT model-simulated aerosol transport trajectory tendencies for March 2013 beginning from (a) Taklimakan
desert at 500 m, (b) Gobi desert at 500 m, and (c) East China coast at 1000 m.
determined by the meteorological conditions, especially pressure and wind. In the next section, we discuss
the meteorological conditions related to the aerosol transport process. We will focus on one typical 10 day
case from 22 March to 1 April 2013. We note that this particular month had a number of individual dust
outbreaks occurring nearly continuously, as this month had vigorous dust generation.
3.2. Aerosol Outbreaks and Mixing Process From Satellite Observations
Figure 2 shows the meteorological wind fields in the horizontal and vertical directions for a 4 day period that
encompasses the process from dust outbreak over the deserts in the west to aerosol mixing farther to the
east. Meteorological conditions are important for both aerosol entrainment and local air quality [Zhang et al.,
2012]. Before and during the aerosol outbreaks, low pressure systems associated with upward air current
motions are found around the two key dust sources: Taklimakan desert and Gobi desert and also the two
pollution sources: East China coast and south China region (Figure 2a). The meteorological pattern remained
favorable for aerosol entrainment and transport for several days throughout the process (Figures 2b–2d).
Figure 3 shows that MODIS aerosol products detect strong aerosol loading in the corresponding source
regions. The MODIS panels also provide the CALIPSO ground track in red. For example, Figure 3a shows the
CALIPSO ground track passing through the Taklimakan desert around 45°N and capturing the dust
entrainment height. The CALIOP-derived aerosol profiles are shown in Figure 4 for the ground tracks shown
in Figure 3. For the case shown in Figure 3a, the dust layers over the source region extend to a height of 4–5
km (Figure 4a). Note that the layers are mostly identified as pure dust in contrast to the polluted aerosols
located toward the south wing of the Tibetan Plateau. Trapped by the unique surrounding topography and
directed by the leading westerly wind fields in the lower troposphere (at around the 500 hPa level, figure not
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Figure 2. Horizontal (vectors) and vertical (shadings) wind fields at 850 hPa from the NCEP Reanalysis: (a) 22 March 18:00
UTC, (b) 23 March 18:00 UTC, (c) 24 March 18:00 UTC, and (d) 25 March 18:00 UTC.
shown), the dust aerosols follow a northwest-southeast pathway and then move toward the east coast
(Figure 3b). A portion of the dust aerosols travel northeastward and are regulated by the mesoscale
anticyclone near 40°N (hereafter, referred to as the northern dust transport branch). A vertical cross section
(Figure 4b) shows that the dust layer heights do not change significantly during short-range transport and
continue to occupy the lower troposphere. At the same time, aerosols originating from industrial pollution in
the southern part of China are accumulating along the central east coast (around 30°N) by southwesterly lowlevel transport. By 24 March 2013, a strong midlatitude baroclinic system is strengthening upon entering the
East China Sea (Figure 2c). Dust aerosols from the northwest, pollution aerosols from the south, and local
aerosol emission merge near the east coast behind the strong trough (Figure 3c). The northern dust transport
branch also experiences the pollution around 45°N. From Figure 4c, the dust aerosols near 40°N are mixed
thoroughly with the pollution aerosols while the mixing in the southern branch is just beginning to occur (i.e.,
smoke and dust aerosols converged near 20°–30°N).
The vertical cross section over the East China Sea from north to south (Figure 4d) illustrates several interesting
features. One is that polluted dust aerosols generally reach a higher altitude (usually around 4–6 km but can
be up to 10 km), while pure/clean dust tends to concentrate at lower levels. Larger amount of dust aerosols is
found at lower heights. Figure 5 shows profiles of the aerosol extinction coefficient corresponding to the
CALIOP tracks shown in Figure 3. Although dust could be entrained to higher altitudes, the largest dust
extinction occurs at 1–2 km above ground level in the source region (Figures 5a and 5b). Large palls of smoke
and dust move toward the east coast near 30°N and mix at an altitude of 3–4 km (Figures 5c and 5d).
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Figure 3. AQUA MODIS daily aerosol optical depth at 550 nm with the CALIOP ground track (red line): (a) 22 March, (b) 23
March, (c) 24 March, and (d) 25 March.
Figure 4. The CALIOP aerosol type as a function of height showing the dust aerosol outbreak and mixing process corresponding to the ground tracks shown in Figure 3.
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1
Figure 5. Aerosol extinction coefficients (km
ing to the ground tracks shown in Figure 3.
) at the 532 nm wavelength from CALIOP aerosol profile products correspond-
3.3. Evidence From Ground-Based AERONET Inversion Products
The previous analysis provides a large-scale context. Supportive evidence is obtained for aerosol mixing and
its induced effects on optical properties from the inversion products of selected AERONET sites within the
East Asian region. Figure 6 shows the variations in the daily averaged aerosol single-scattering albedo (SSA) at
Figure 6. Aerosol single-scattering albedo at the 441 nm wavelength from selected AERONET sites in the East Asia: (a)
Dalanzadgad, (b) Mt_WLG, (c) Beijing_RADI, (d) Taihu, (e) Gangneung_WNU, and (f) NAM_CO.
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Figure 7. Same as Figure 6, but for the Ångström exponent calculated at the 440 and 870 nm wavelengths.
a wavelength of 441 nm during March 2013 at the Dalanzadgad (43.58°N, 104.42°E), Mt_WLG (36.28°N, 100.90°E),
Beijing_RADI (40.0°N, 116.38°E), Taihu (31.42°N, 120.22°E), Gangneung_WNU (37.77°N, 128.87°E), and
NAM_CO (30.77°N, 90.96°E) sites. Figure 7 shows the Ångström exponent (440–870 nm), which provides particle
h i h i
size information, for the corresponding sites. The Ångström exponent is defined as α ¼ ln ττððλλ12 ÞÞ = ln λλ12 ,
where τ and λ are the aerosol optical depth and wavelength, respectively.
The Dalanzadgad and Mt_WLG sites are located on the northern and southern branch of the dust transport
pathways from the Taklimakan source region. The Beijing_RADI and Taihu sites are on the northern (45°–50°N)
and southern (30°N) aerosol plume outlets at the rim of the continent. The Gangneung_WNU site is
downstream of the Beijing_RADI site, and the NAM_CO site represents conditions in the central southwest of
China. The SSA is the most important parameter modulating the radiative forcing and heating rate of aerosols
[Zhu et al., 2007]. A trend in the SSA variability is not found at the Dalanzadgad site, although the SSA has
day-to-day changes from ~0.8 to ~1.0. In contrast, the Mt_WLG site shows a strong decreasing SSA trend with
time. The Beijing_RADI, Taihu, and Gangneung_WNU sites all exhibit a slight increasing trend in SSA with
time; however, the NAM_CO site displays the strongest increasing trend.
Based on the locations of the AERONET sites and the temporal evolution of aerosol transport, some of the
observed variability in the aerosol SSA may be attributed partially to the aerosol mixing process. When aerosols
of different types mix, the optical properties of the aerosol mixture will change, depending on the particle type,
size, shape, and the type of mixing (e.g., internal or external mixture). Generally, the AERONET sites (i.e.,
Dalanzadgad) in northern China are not severely affected by the mixing process, where nonabsorbing/weakly
absorbing aerosols (i.e., dust) are dominant and show minor changes in the aerosol optical properties.
However, the Mt_WLG and NAM_CO sites are near industrial emission sources of absorbing aerosols (i.e.,
smoke/soot) and are located on the northern and southern dust aerosol transport pathway. These two sites
can be influenced by the advected dust as well as pollution. At the NAM_CO site in particular, studies
have shown the influence of dust from the Taklimakan desert to the north [Xia et al., 2008] and pollution
from the Ganges Plain to the south [Xia et al., 2011; Zhao et al., 2013]. However, opposing trends (one
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Figure 8. Same as Figure 3, but during the transport process over the Pacific Ocean: (a) 26 March, (b) 28 March, (c) 30
March, and (d) 1 April.
increasing and one decreasing) are found at the two sites for the period of study that indicates the temporal
evolution of the aerosol mixing. For example, the NAM_CO site was initially influenced by industrial
absorbing aerosols and first exhibited a low SSA. After dust aerosols advect into the pollution layer and the
mixing process begins, the aerosol mixture SSA shows a gradual increase as the fraction of dust increases.
The Ångström exponent at the NAM_CO site (Figure 7f) has a corresponding decreasing trend from
approximately 2 to 0.5, indicating the aerosol particle size shifts from the fine mode (i.e., smoke) to the coarse
mode (i.e., dust), which in part supports the analysis. The same trends, as those of the SSA, are reflected in
the aerosol radiative forcing efficiency products from the AERONET sites (figures not shown). The opposite
aerosol mixing process can be deduced for the Mt_WLG site. The other sites did not show dramatic changes in
the Ångström exponent (Figure 7). At the Beijing_RADI, Taihu, and Gangneung_WNU sites, the averaged
Ångström exponents are around 1 (with moderate fluctuations), which implies mixing of coarse and fine mode
aerosols. The analysis indicates the importance of determining whether dust aerosols are mixed with pollution
aerosols and if the optical property changes influences the radiative energy balance. Other factors, such as
the aerosol (dust, soot, and other) particle habits in the aerosol mixture [Colarco et al., 2014; Li et al., 2010; Yi et al.,
2011] and the type of mixing [Jacobson, 2000, 2001], are related but outside of the scope of this study. A follow-up
study is planned to investigate the optical properties and radiative effects of aerosol mixing more fully.
3.4. Transport of Aerosols Across the Pacific and Into North America
The aerosols that advect over the East coast of the Asian continent are influenced by the midlevel “steering
wind” (the jet stream) and large-scale meteorological systems. Typically, approximately 7–10 days are
necessary for the aerosols to complete a trans-Pacific transport. Figures 8 and 9 provide snapshots, in the
horizontal and vertical directions, of the aerosol transport process over the ocean. Over the ocean, the
satellite-based aerosol detection is frequently hindered by clouds and is also hindered in the sun glint
regions. The transport paths cover a wide range in the meridional direction from ~30°N to ~60°N. From the
vertical cross section observations by CALIPSO, we find that the dust has not yet fully mixed with smoke near
20°–30°N prior to leaving East Asia (Figure 9a). With the propagation of the aerosol plume, the mixing process
continues to mix the pure dust with the pollution aerosols as the plume approaches the western coast of
North America (Figures 9b and 9c). The scavenging process is also a factor that affects a large portion of the
aerosol plume. By the time the aerosol plume reaches the North American coast, some aerosol layers are
reduced to < 3km above the surface. However, polluted dust aerosols are proven to be a dominant
component of the aerosol plume surviving the long-range transport (see section 3.5).
3.5. Frequency and Optical Properties of the Polluted Dust
An interesting and important problem is the frequency for which polluted dust is found instead of pure dust.
We attempt to gain insight to this issue by a statistical survey of the CALIPSO-detected aerosol layers within
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Figure 9. Same as Figure 4, but during the transport process over the Pacific Ocean, corresponding to the ground tracks
shown in Figure 8.
the aerosol export region in East Asia and the aerosol import region in North America by investigating 1
month (March 2013) of CALIPSO Level 2 5-km resolution aerosol layer products. We extend the survey to the
entire March-April-May season and find March to be a good representative month of spring. The division of
export/import geographical regions is similar to that defined in Yu et al. [2012]. The export region is from 30°N
to 60°N and 135°E to 145°E, and the import region is from 30°N to 60°N and 125°W to 135°W. The survey
philosophy is to examine the percentage of polluted dust layers in relation to the total dust aerosol layers.
The percentage is defined as the number of polluted dust layers divided by the total number of dust (pure
and polluted) layers found in the investigated regions during the period.
The statistical results are summarized in Table 1, together with the March-April-May seasonal scenario with
the numbers shown in parentheses. The seasonal results only show marginal differences from the monthly
(March only) results. Not surprisingly for the spring season, dust occupies a significant portion of the total
aerosols in both the export and import regions with a little more than half (~55%) of the dust layers polluted.
We use a 3 km altitude as a threshold to discriminate between the upper (> 3 km) and lower (< 3 km) level
aerosol layers. The dust layer height is defined as the middle of the layer. In the import region, a significantly
higher percentage of dust layers are found in the upper level (82%) than in the lower level (31%). However, in
the export region, the upper-lower level difference in dust layer percentage is marginal (~10%). This suggests
that dust aerosols are mostly imported from the higher altitudes, and the dust layers in the lower levels
attenuate more quickly than those in the upper levels. Polluted dust layers are found slightly more frequently
in the lower levels than in the upper levels. However, regardless of the height level or region, approximately
half of the total dust aerosol layers contain polluted dust.
Table 1. Statistics of the Dust Layers Found Over the Export and Import Regions Using CALIPSO/CALIOP Aerosol Layer
a
Products From March 2013
Percentage of dust layers among all aerosol layers
Percentage of polluted dust layers among all dust layers
a
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All levels
Upper levels
Lower levels
All levels
Upper levels
Lower levels
Export Region
Import Region
64% (66%)
69% (73%)
59% (59%)
55% (58%)
49% (52%)
61% (65%)
50% (51%)
82% (84%)
31% (34%)
56% (55%)
48% (51%)
69% (60%)
Numbers in parentheses indicate the March-April-May seasonal scenario.
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Table 2. Statistics of the Dust Layer Integrated Optical Properties for the Export and Import Regions During March 2013
Export Region
Integrated attenuated backscatter at 532 nm
wavelength
Integrated volume depolarization ratio
Integrated particulate depolarization ratio
Integrated particulate color ratio
Feature optical depth at 532 nm wavelength
a
a
Import Region
Pure Dust
Polluted Dust
Pure Dust
Polluted Dust
0.00187
(0.00158)
0.137 (0.124)
0.293 (0.283)
0.815 (0.783)
0.109 (0.090)
0.00179
(0.00168)
0.061 (0.056)
0.128 (0.127)
0.693 (0.689)
0.146 (0.130)
0.000974
(0.000934)
0.102 (0.096)
0.278 (0.278)
0.715 (0.684)
0.049 (0.046)
0.00186
(0.0016)
0.058 (0.054)
0.134 (0.139)
0.718 (0.673)
0.097 (0.087)
Numbers in parentheses indicate the March-April-May seasonal averages rather than the averages for March.
Differences in the dust layer integrated optical properties over the export and import regions during March
2013 (as well as March-April-May season) are summarized in Table 2. CALIOP observations provide additional
information about the backscattering and polarization properties of aerosol layers compared with the
conventional passive remote sensing measurements from MODIS. For example, the depolarization ratio,
which is defined as the ratio of the perpendicular to the parallel components of polarization, is related to the
size and nonsphericity of the scattering particles, and is generally higher for pure dust. The color ratio,
which is the ratio of backscattering signals at 1064 nm and 532 nm, can be used to infer information about
aerosol particle size [Liu et al., 2013]. Again, good agreement is found between the monthly and seasonal
results. Pure dust and polluted dust show the most distinguishable differences in the integrated volume
and particulate depolarization ratios, with the pure dust ratio approximately 2 times larger than the polluted
dust ratio. A slight decrease in the depolarization ratios for pure dust is found between the export region
and the import region, but the difference is not evident in the polluted dust case. Pure dust layers in the
export region have a noticeably larger particulate color ratio in comparison with polluted layers, but the
value is decreased after reaching the import region. Generally, a larger color ratio is related to a larger particle
size if the particle shape is not considered [Bi et al., 2009]. The implication is that during transport, pure
dust may undergo changes in size more easily than polluted dust. Changes in humidity along the transport
path may play a role in this process. The AOD at a 532 nm wavelength for pure dust decreases by half during
transport, while it decreases by approximately one third for polluted dust.
While there are apparent differences between pure and polluted dust, the polluted dust is generally treated
as pure dust in recent studies because of a lack of knowledge about its properties. Large uncertainties in the
dust radiative effects may result from this assumption, leading to further uncertainties with regards to a
potential climate impact. Another study is underway to develop a model to provide a better representation of
pure and polluted dust optical properties.
4. Conclusions
In this study, we use aerosol property products from two instruments (CALIOP and MODIS) in the NASA
A-Train constellation and from AERONET ground-based observations to capture and characterize East Asian
dust outbreak, mixing, and transport processes. Forward trajectories of aerosols originating from different
source regions and heights are calculated with the HYSPLIT model and analyzed with a clustering method. A
large percentage of dust aerosols originating from the Taklimakan and Gobi deserts and smoke aerosols from
the south of China are transported to the central East Asian coast where thorough aerosol mixing occurs. As a
result of large-scale weather systems, the aerosols travel over the Pacific Ocean to the North American
continent within 7–10 days. MODIS and CALIOP observations capture the horizontal and vertical structures of
the aerosol plume and confirm that mixing occurs. Throughout the process, the optical properties of dust
aerosols experience significant changes in both the MODIS and CALIOP products. Inversion products from
selected AERONET sites over East Asia also show the variation of aerosol single-scattering albedo and particle
size during the mixing period. If treated as pure dust, polluted dust may cause significant uncertainties in
radiative transfer simulations and modeling studies.
A statistical survey, using CALIOP aerosol layer products during March/Spring 2013 over aerosol export (in
East Asia) and import (in North America) regions, shows that more than half of the detected dust layers are
YI ET AL.
©2014. American Geophysical Union. All Rights Reserved.
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Journal of Geophysical Research: Atmospheres
10.1002/2014JD021721
mixed with pollution. Although dust is generally advected at higher levels (> 3 km), polluted dust aerosol
layers occur slightly more frequently in the lower levels. Pure dust has a depolarization ratio that is
approximately 2 times larger than polluted dust. Larger color ratios are also found for pure dust than for
polluted dust being transported off the East Asian coast. Polluted dust aerosols tend to conserve their
properties during transport and to attenuate more slowly than pure dust layers. Note that we do not consider
the possible impact of aerosol-cloud interactions here, although a previous study does show its importance
[Yi et al., 2012]. The omission is due to the limited availability of suitable analysis methods and does not
necessarily mean the impact can be neglected. Future studies using numerical models have the potential to
provide further insight into this issue.
Acknowledgments
This study was partly supported by
NASA grants (NNX11AK37G,
NNX11AK39G, and NNX10AM27G) and
the endowment funds associated with
the David Bullock Harris Chair in
Geosciences at the College of
Geosciences, Texas A&M University. The
availability of the data used for this
study is fully described in section 2 of
this paper. The MODIS data were
downloaded from the NASA Goddard
Space Flight Center. The CALIPSO data
were obtained from the NASA Langley
Research Center Atmospheric Science
Data Center. We thank the PIs for their
effort in establishing and maintaining
the AERONET sites (Dalanzadgad,
Mt_WLG, Beijing_RADI, Taihu,
Gangneung_WNU, and NAM_CO) used
in this study.
YI ET AL.
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