A simulation of Aerosols in Asia with the use of ADAM2 and ... · A simulation of Aerosols in Asia...
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A simulation of Aerosols in Asia with the use of ADAM2 and CMAQ
Soon-Ung Park*, Joeng Hoon Cho, Moon-Soo Park
Center for Atmospheric and Environmental Modeling
Seoul National University Research Park RM 515
San 4-2, Bongcheon-dong, Gwanak-gu, Seoul, 151-919
REPUBLIC OF KOREA *[email protected] http://www.caem.re.kr
Abstract: The Aerosol Modeling System (AMS) has been developed to estimate aerosol concentrations of both
natural (dust) and anthropogenic aerosols and implemented to simulate the observed PM10 concentration for
the period from 10 to 17 March 2010 when a couple of Asian dust events are observed in South Korea. The
system is based on the Asian Dust Aerosol Model 2 (ADAM2) for the dust aerosol and the Community
Multiscale Air Quality (CAMQ) modeling system of the US Environmental Protection Agency (EPA) for the
anthropogenic aerosol. The AMS has been employed to simulate aerosol concentrations in the Asian domain at
27 km horizontal grid spacing with the Intercontinental Chemical Transport Experiment – Phase B (INTEX-B)
pollutant emission data in Asia and in the nested East Asian domain at 9 km horizontal grid spacing with
emission data from the INTEX-B in Asia and the Clear Air Policy Supporting System (CAPSS) of Korea
Ministry of Environment in the South Korean region. It is found that the AMS model with the 27 km horizontal
grid scheme (Model 1) tends to underestimate the concentrations of both the dust (natural) and the
anthropogenic aerosols, whereas the model with the 9 km horizontal grid scheme (Model 2) quite successfully
simulates the observed Asian dust and anthropogenic aerosol concentrations. This suggests that AMS has a
great potential for the use of Asian aerosol forecast model in Asia.
Key-Words: Aerosol Modeling System (AMS), ADAM2, Anthropogenic aerosol, Asian dust aerosol, CMAQ
1 Introduction In recent years, atmospheric aerosols have become
an emerging issue due to their important role in
atmospheric processes, including their number
concentration, their mass, size, chemical
composition, and aerodynamic and optical
properties. Of these, size is the most important; it
not only reflects the nature of the source of the
aerosols but also relates to their health effects (Bates
et al., 1966; Pope et al., 1992; Dockery et al., 1992,
1993; Balásházy et al., 2003) and to their aesthetic
and climate effects via their light scattering
properties (Chang and Park, 2004; Park et al., 2005;
IPCC, 1996; Jacobson, 2001; Kanfman et al., 2002;
Penner et al., 2004; Crutzen, 2004).
Current estimates suggest that anthropogenic
aerosols and biomass burning have climate forcing
enough to offset warming caused by greenhouse
gases such as carbon dioxide (Kiehl and Briegle,
1993). However, a large uncertainty of key
properties of aerosols makes it difficult to correctly
quantify the radiative forcing (Chang and Park,
2004). The uncertainties are due to in part to the
limited data on aerosol climatology, and in part to
the lack of our understanding on the processes
responsible for the production, transport, physical
and chemical evolution and the removal of aerosols
at various spatial and time scales that are largely
dependent on the aerosol size distribution (Clarke et
al., 2004).
East Asia is a major source of natural (Asian
dust) and anthropogenic aerosols over the Northern
Hemisphere due to rapid economic expansion in
many Asian countries. Asian dust (Hwangsa in
Korean) which is a typical example of mineral
aerosol occurs in the Sand desert, Gobi desert and
Loess plateau in northern China and Mongolia more
frequently during the spring season (Park and In,
2003; In and Park, 2003; Park and Lee, 2004).
Tropospheric aerosols that originate in China are the
complex mixture of various aerosols such as Asian
dust and anthropogenic particles from a variety of
sources. The dust particles raised in the source
regions of inland China will experience pollutants
emitted from the industrialized regions that are
heavily concentrated in the eastern part of China
during long-range transport of dust. Consequently, a
significant transformation of chemical composition
of the dust is expected as indicated by observations
(Saxena and Seigneur, 1983; Gao et al., 1991; Kang
and Sang, 1991; Park et al., 2005).
Recently Park et al. (2010a) have developed the
Asian Dust Aerosol Model 2 (ADAM2) and used to
Advances in Fluid Mechanics and Heat & Mass Transfer
ISBN: 978-1-61804-114-2 258
simulate successfully the Asian dust events (Park et
al., 2010b, Park et al., 2010 c). However, this model
cannot be used to simulate the anthropogenic
aerosols. Therefore, the Community Multiscale Air
Quality (CAMQ) model (Otte et al., 2005; Byun and
Schere, 2006) has been coupled with ADAM2 to
simulate all kinds of aerosols including natural and
anthropogenic aerosols.
The purpose of this study is to simulate aerosols
in Asia using the Aerosol Modeling System (AMS)
that entails coupling the ADAM2 model with the
CAMQ model for the period of 10 to 17 March
2010 when Asian dust events occurred in Asia and
to test the performance of the AMS model.
2 Model description
2.1 Meteorological Model The meteorological model used in this study is the
fifth generation mesoscale model of non-hydrostatic
version (MM5, Pennsylvania State University/
National Center for Atmospheric Research) defined
in the x, y, and σ coordinate (Grell et al., 1994;
Dudhia et al., 1998).
The model domain (Fig. 1) has horizontal
resolution of 27 x 27 km2 for the Asian domain (Fig.
1a) with nested domains of 9 x 9 km2 for the East
Asia domain (Fig. 1b). Each domain has 25 vertical
layers. For our convenience the model with the
Asian domain is referred to “Model 1” and that of
the East Asian domain to “Model 2”.
Fig. 1 Model domains and the Asian dust source
region with surface soil types (Gobi , Sand ,
Loess and Mixed ) in (a) Model 1 (Asian
domain) and (b) Model 2 (East Asian domain).
2.2 Aerosol Modeling System (AMS) The Aerosol Modeling System (AMS) is consisted
of the Asian Dust Aerosol Model 2 (ADAM2, Park
et al., 2010a), the Community Multiscale Air
Quality (CMAQ) modeling system (http://www.
cmaq-model.org) with pollutants emission data.
2.2.1 ADAM2 model The ADAM2 model is an Eulerian dust transport
model that includes the specifications of the dust
source regions, delineated by the statistical analysis
of the World Meteorological Organization (WMO)
dust reporting data and statistically derived dust
emission conditions in Sand, Gobi, Loess and mixed
soil surface in the domain in Fig. 1a. The model
uses the suspended particle-size distribution
parameterized by the several log-normal
distributions in the source regions, based on the
concept of the minimally and fully dispersed
particle-size distribution. It has 11-size of bins with
near the same logarithm interval for particles of
0.15-37 µm in radius (Park and In, 2003; Park and
Lee, 2004). The model can be run for a whole year
round with a temporally varying emission reduction
factors derived statistically using the normalized
difference vegetation index (NDVI) in the different
surface soil types in the Asian dust source region.
The detailed description is given in Park et al.
(2010a).
2.2.2 CMAQ model
The EPA Community Multiscale Air Quality
(CMAQ) modeling system (http://www.cmaq-
model. org) is a three-dimensional Eulerian
atmospheric chemistry and transport modeling
system that simulates ozone, particulate matter,
toxic airborne pollutants, visibility, and acidic and
nutrient pollutant species throughout the
troposphere (University of North Carolina, 2010).
The aerosol component of the CMAQ model has
the particle size distribution as the superposition of
three lognormal subdistributions, called modes. Fine
particles with diameters less than 2.5 µm (PM2.5) are
represented by two subdistributions called the
Aitken and accumulation modes. The Aitken mode
includes particles with diameters up to
approximately 0.1 µm for mass distribution and the
accumulation mode covers the mass distribution in
the range from 0.1 to 2.5 µm. The coarse mode
covers the mass distribution in the range from 2.5
µm to 10 µm. The model includes the processes of
coagulation, particle growth by the addition of mass
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and new particle formation (Binkowski and Roselle
2003).
2.2.3 Emission data
Air pollutant emissions in Asia (Fig. 2) in the year
2006 are obtained from the Intercontinental
Chemical Transport Experiment – Phase B (INTEX
B, Zhang et al., 2009) that include
anthropogenic sources, excluding biomass burning.
The estimated total Asian (China
genic emissions in the year 2006 are 47.1 Tg (31.0
Tg) SO2, 36.7 Tg (20.8 Tg) NOX, 54.6 Tg (23.2 Tg)
VOC, 298.2 Tg (166.9 Tg) CO, 29.2 Tg
PM10, 22.2 Tg (13.3 Tg) PM2.5, suggesting more
than 60 % of the total anthropogenic emissions
being contributed by China.
Fig. 2 Horizontal distributions of emission rate (t
day-1 grid
-1) of (a) SO2, (b) NOx, (c) NH
PM10 (1 grid: 27x27 km2) on March 2006.
Air pollutant emissions in South Korea (Fig. 3) in
the year 2007 are obtained from the Clean Air
Policy Supporting System (CAPSS, Korean
Ministry of Environment) in a 1 x 1 km
scheme. These emission data over South Korea are
used for the simulation of aerosols in
3 A simulation of aerosols for the
period of 10 to 17 March 2010An aerosol simulation has been done with the use of
AMS for the period of 10 to 17 March 2010 in the
Asian domain (Fig. 1a) with the use of emission
data in Fig. 2 and the nested East Asia domain (Fig.
1b) with emission data in Figs. 2 and 3.
Binkowski and Roselle,
Air pollutant emissions in Asia (Fig. 2) in the year
2006 are obtained from the Intercontinental
hase B (INTEX-
ncludes all major
anthropogenic sources, excluding biomass burning.
The estimated total Asian (China’s) anthropo-
genic emissions in the year 2006 are 47.1 Tg (31.0
, 54.6 Tg (23.2 Tg)
VOC, 298.2 Tg (166.9 Tg) CO, 29.2 Tg (18.2 Tg)
, suggesting more
than 60 % of the total anthropogenic emissions
Horizontal distributions of emission rate (t
, (b) NOx, (c) NH3, and (d)
) on March 2006.
Air pollutant emissions in South Korea (Fig. 3) in
the year 2007 are obtained from the Clean Air
Policy Supporting System (CAPSS, Korean
Ministry of Environment) in a 1 x 1 km2 grid
scheme. These emission data over South Korea are
used for the simulation of aerosols in Model 2.
A simulation of aerosols for the
period of 10 to 17 March 2010 has been done with the use of
AMS for the period of 10 to 17 March 2010 in the
Asian domain (Fig. 1a) with the use of emission
data in Fig. 2 and the nested East Asia domain (Fig.
1b) with emission data in Figs. 2 and 3.
Fig. 3 Horizontal distributions
day-1 grid
-1) of (a) SO2, (b) NOx, (c) NH
PM10 (1 grid: 3x3 km2) on March 2006.
Fig. 4 shows the spatial distributions of the near
surface total PM10 concentration (Fig. 4a) and the
anthropogenic aerosol (PM
4b) simulated by Model 1
2010.
(a) Total PM10
(b) Anthropogenic PM 10
Fig. 4 Horizontal distribution of near surface (a)
total PM10 concentration and (b) anthropogenic
aerosol (PM10) concentration simulated by Model 1
at 00 UTC 16 March 2010.
Horizontal distributions of emission rate (t
, (b) NOx, (c) NH3, and (d)
) on March 2006.
Fig. 4 shows the spatial distributions of the near
concentration (Fig. 4a) and the
anthropogenic aerosol (PM10) concentration (Fig.
simulated by Model 1 at 00 UTC 16 March
Horizontal distribution of near surface (a)
concentration and (b) anthropogenic
) concentration simulated by Model 1
UTC 16 March 2010.
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The anthropogenic aerosols include SO42-, NO3
-,
NH4+, OC, BC, sea salt, emitted PM10. It is quite
clear that the contribution of the anthropogenic
aerosols to the total aerosols is quite significant
especially in the south eastern part of China were
the pollutant emission rate is large. The enhanced
anthropogenic aerosol in this region may cause the
frequent occurrence of the haze.
Fig. 5 shows the spatial distributions of the near
surface total PM10 concentration (Fig. 5a) simulated
by Model 2 at the same time in Fig. 4.
The total PM10 concentration in the nested
domain is enhanced compared with that in the Asian
domain (Figs. 4 and 5) toward the downwind region
due to the enhanced wind speed in the lower level
that results in the enhancement of dust rise in the
source regions in northeastern China.
Fig. 5 The same as in Fig. 4 except for by Model 2.
To examine more closely the impact of the nested
grid domain on the aerosol concentration, the time
series of observed and modeled PM10 concentrations
estimated by Model 1 and Model 2 are compared at
several sites located in the downwind region of
South Korea.
Fig. 6 shows the time series of the observed total
PM10 concentration, the modeled total PM10
concentration and the anthropogenic aerosol
concentration estimated by Model 1 and Model 2 at
Seoul, Jeonju, Ulsan and Busan in Korea (Fig. 1b).
Fig. 6 Time series of observed (solid-dot line), total
(solid line), anthropogenic (dotted line) PM10
concentration simulated by Model 1 and Model 2 at
(a) Seoul, (b) Jeonju, (c) Ulsan, and (d) Busan.
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It is quite clear that the observed aerosol
concentrations more than 100 µg m-3 are mainly
contributed by the Asian dust aerosol and the Model
2 simulates much better peak aerosol contribution
during the dust event period and the anthropogenic
aerosol concentration during the non-dust event
period than those by the Model 1 at all sites (Fig. 6),
suggesting the importance of the nested grid model
for the simulation of the total aerosols.
Fig. 7 shows the time series of modeled total
aerosol concentration and the anthropogenic aerosol
concentration simulated by Model 1 and Model 2 at
Beijing in China. Although the direct comparison of
aerosol concentrations simulated by Model 1 and
Model 2 is difficult without the observed data, the
time series of wind speed (not shown) implies better
result of Model 2 than that of Model 1. The
anthropogenic aerosol concentration can be more
than 200 µg m-3 during the non-dust event period
causing a haze problem. The dust event occurred in
the later afternoon on 15 March (Fig. 7) may be
associated with the dust event observed in the
morning on 16 March in Korea (Fig. 6).
Fig. 7. Time series of total PM10 concentration
(solid line) and anthropogenic PM10 concentration
(dotted line) simulated by (a) Model 1 and (b)
Model 2.
4 Conclusion The presently developed Aerosol Modeling System
(AMS) on the basis of the ADAM2 model for the
Asian dust aerosols and the CMAQ model for the
anthropogenic aerosols has been employed to
estimate the total aerosol concentration (natural +
anthropogenic aerosols) in Asia for the period from
10 to 17 March 2010 when a couple of dust events
are observed in Korea.
It is found that the AMS model has demonstrated
its ability to simulate quite reasonably the observed
PM10 concentration and to distinguish the
contribution of anthropogenic aerosol concentration
from the total observed PM10 concentration. The
observed high PM10 concentrations exceeding 100
µg m-3 in Korea are found to be mainly contributed
by the Asian dust aerosol whereas the anthropogenic
aerosol concentrations exceeding 200 µg m-3 are
often found in the southeastern part of China where
the pollutant emissions are highest. This may cause
frequent occurrences of haze events in this region.
It is also found that Model 2 (horizontal grid
distance of 9 km) simulates much better total
aerosol concentration by simulating better
meteorological fields than Model 1 (horizontal grid
distance of 27 km).
The present study mainly pertains to the
performance test of the AMS model for a short time
period. More accurate prediction of the aerosol
concentration requires a proper parameterization of
interaction processes between the aerosol and
gaseous pollutants and among different aerosols.
This is now on hand.
Acknowledgments: This work was funded by the Korea Meteorological
Administration Research and Development Program
under grant CATER 2012-2050.
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