JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 3709–3722, doi:10.1002/jgrd.50317, 2013
Seasonal variations of black carbon observed at the remote
mountain site Happo in Japan
X. Liu,1,2 Y. Kondo,1 K. Ram,1,3 H. Matsui,1 K. Nakagomi,4 T. Ikeda,4 N. Oshima,5
R. L. Verma,1,6 N. Takegawa,7 M. Koike,1 and M. Kajino5
Received 6 December 2012; revised 26 February 2013; accepted 5 March 2013; published 13 May 2013.
[1] The emission of black carbon (BC) from East Asia and its long-range transport
strongly influence the mass concentration of BC (MBC) over the western Pacific. However,
reliable and long-term BC data are still limited in this region, especially at elevated
altitudes. In this study, we present accurate measurements of MBC using a continuous soot
monitoring system at Happo, a remote mountain site at an altitude of about 1.8 km in Japan,
from August 2007 to August 2009. The annual average MBC at Happo was about
0.26 0.18 (1s) mg m3. The monthly average MBC values exhibited similar seasonal
variations during both years, with minimum values in winter. Around 40% of the air
sampled at the site was of free tropospheric (FT) origin, with about 10% originating in
North China (NC) origin, respectively. The MBC values for FT (0.24 mg m3) and NC
(0.23 mg m3) air were representative of the MBC values (0.26 mg m3) at 1.8 km height in
the western Pacific, which are strongly influenced by BC emissions in North China. The
MBC values calculated using a regional-scale model reproduced well the MBC observed at
Happo. The model predicted that BC transported from northern China alone contributed
~53% to the measured MBC, consistent with trajectory analysis. The comparison of
model-calculated and observed MBC values indicates that the minimum values of MBC
in winter were caused by the suppressed upward transport of BC over the Asian
continent. Biomass burning in Siberia substantially increased MBC in the spring of 2008.
Citation: Liu, X., Y. Kondo, K. Ram, H. Matsui, K. Nakagomi, T. Ikeda, N. Oshima, R. L. Verma, N. Takegawa,
M. Koike, and M. Kajino (2013), Seasonal variations of black carbon observed at the remote mountain site Happo in Japan,
J. Geophys. Res. Atmos., 118, 3709–3722, doi:10.1002/jgrd.50317.
1.
Introduction
[2] Black carbon (BC) is produced from the incomplete
combustion of fossil fuels and biofuels and from biomass
burning (BB) emissions [Horvath, 1993]. BC strongly absorbs
solar radiation at visible wavelengths and significantly contributes to radiative forcing [e.g., Hansen and Sato, 2001].
1
Department of Earth and Planetary Science, Graduate School of
Science, The University of Tokyo, Bunkyo, Tokyo, Japan.
2
Now at the School of Mathematics and Physics, Changzhou
University, Changzhou, China.
3
School of Earth, Ocean and Climate Sciences, Indian Institute of
Technology, Bhubaneswar, India.
4
Nagano Environmental Conservation Research Institute, Nagano,
Japan.
5
Meteorological Research Institute, Tsukuba, Japan.
6
Regional Resources Center for Asia and the Pacific, Asian Institute of
Technology, Klong Luang, Thailand.
7
Research Center for Advanced Science and Technology, The
University of Tokyo, Tokyo, Japan.
Corresponding author: Y. Kondo, Department of Earth and Planetary
Science, Graduate School of Science, The University of Tokyo, Hongo 7-3-1,
Bunkyo-ku, Tokyo 113-0033, Japan. ([email protected])
©2013. American Geophysical Union. All Rights Reserved.
2169-897X/13/10.1002/jgrd.50317
The Intergovernmental Panel on Climate Change (IPCC) has
estimated that the global mean clear-sky radiative forcing
of BC is 0.23 0.25 W m2 [IPCC, 2007]. However, the
estimate of radiative forcing by BC is highly uncertain partly
due to insufficient data on the spatial and vertical distributions
of BC mass concentrations (MBC), which can be used to
validate model calculations.
[3] East Asia is a major source region of BC aerosols
[Streets et al., 2003; Ohara et al., 2007; Zhang et al.,
2009] and contributes about 30% of the estimated global
BC emissions [Bond et al., 2004]. Long-term ground-based
measurements of MBC over the western Pacific have been
made at Hedo [26.87 N, 128.26 E, ~60 m above sea level
(asl)] on the Japanese island of Okinawa [Kondo et al.,
2011a; Verma et al., 2011]. Using this data set and model
calculations, Kondo et al. [2011a] evaluated the BC emission
rate from China and found it to be close to that estimated
by Zhang et al. [2009]. The MBC measured at Hedo was
found to be strongly influenced by BC transported from
China throughout the year, except for summer [Kondo et al.,
2011a; Verma et al., 2011].
[4] Measurements of MBC from remote and high-altitude
sites in the western Pacific are crucial to improving our
understanding of the long-range transport of BC from
continental Asia. Kondo et al. [2011a] discussed the
3709
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
2.
Measurement
2.1. Observational Site
[7] The BC measurements were made at the Happo observatory in Nagano prefecture in Japan, which is one of the
national acid deposition monitoring stations of the Japanese
Ministry of the Environment. The station is located in the
Hakuba Mountains (northern Japanese Alps), in the center
of the main island of Japan, about 200 km northwest of
Tokyo and 25 km south of the Sea of Japan (Figure 1). No
significant effects of BC emissions in the vicinity of the
sampling site were detected. The nearest city to the observational site, Shinano-omachi, with a population of about
30,000, is about 25 km away toward the south. The site
was often influenced by free tropospheric (FT) air parcels.
3
NC
40
Happo
2
-1
KR
JP
30
1
Hedo
20
BC (Gg year / grid)
50
Latitude (°N)
measurements and the reliability of BC mass concentrations
obtained during previous campaigns, including the Transport and Chemical Evolution over the Pacific (TRACE-P,
2001) mission [Jacob et al., 2003; Park et al., 2005] and
the Asian-Pacific Regional Aerosol Characterization Experiment (ACE-Asia, 2001) [Uno et al., 2003]. The period of
the measurement was too short for a quantitative understanding of the major sources and transport of BC in this
region. In addition, the accuracy of the BC measured during
ACE-Asia has not been fully quantified [e.g., Huebert
and Charlson, 2000]. Aircraft measurements of BC, with
improved accuracy, were recently made using a singleparticle soot photometer (SP2) instrument in spring 2009
during the Aerosol Radiative Forcing in East Asia (A-FORCE)
campaign [Kondo et al., 2011a; Oshima et al., 2012]. Over the
East China Sea, the average MBC values were about 0.5 mg
m3 up to an altitude of 1.8 km and decreased sharply by about
a factor of 10 at 3 km. The transport efficiency of BC (TEBC)
from the East Asian region was also derived from the
BC-carbon monoxide (CO) correlation, and it was found
that TEBC in the free troposphere was strongly influenced
by the precipitation amount that the sampled air masses
experienced [Oshima et al., 2012].
[5] Considering the large spatiotemporal variability in
MBC associated with emission and transport of BC from the
East Asian region, long-term BC measurements at highaltitude sites are important. We made measurements of
MBC at Happo (36.68 N and 137.80 E) in Japan at 1.8 km
asl for two consecutive years (August 2007–August 2009).
Earlier studies have suggested seasonal variability in the
CO concentration at this site and downstream of the Asian
continent. In fact, the site was strongly influenced by the
transport of anthropogenic emissions in China and Korea
and, occasionally, Siberian biomass burning events [Kato
et al., 2002; Narita et al., 1999]. However, reliable longterm measurements of MBC are still limited at Happo and
other locations in the western Pacific.
[6] For the first time, we present accurate measurements
of MBC for 2 years, i.e., 2007–2009, its seasonal and
interannual variability, and the transport of BC aerosols
from the Asian continent at this altitude in the western
Pacific. The data on seasonal and interannual variability of
MBC are interpreted using back trajectories. We quantify
the influence of transport from source regions in East Asia
and biomass burning on the MBC levels based on the model
calculations. We also derive TEBC using the model.
SC
0
10
100
120
140
Longitude (°E)
Figure 1. Map of anthropogenic BC emissions over East
Asia for the year 2006 with a spatial resolution of 0.5 0.5
[Zhang et al., 2009]. The regions of North China (NC), south
China (SC), Korea (KR), and Japan (JP) defined in this study
are shown with white boxes. The white circles are the
locations of the measurement sites at Happo (137.80 E,
36.68 N) and Hedo (26.87 N, 128.26 E) in the western
Pacific region. The gray lines show the flight tracks of the
Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft
campaign [Oshima et al., 2012], conducted over the East
China Sea in spring 2009.
The air masses arriving at the site, including FT air, were
under the influence of anthropogenic emissions in China
and Korea throughout the year and, occasionally, Siberian
biomass burning events in spring. Continuous measurements
of MBC were made from August 2007 to August 2009. We
analyzed the data for two springs (March–May), summers
(June–August), falls (September–November), and winters
(December–February).
2.2. Instrumentation
[8] MBC in the fine mode (PM2.5, i.e., particles with
aerodynamic diameter smaller than 2.5 mm) were measured
using a filter-based absorption photometer, namely, a
continuous soot monitoring system (COSMOS) [Miyazaki
et al., 2008; Kondo et al., 2009, 2011b, 2012]. The
instrument measures changes in the transmittance at
565 nm wavelength (l) across an automatically advancing
quartz fiber filter tape. The changes in the transmittance are
converted to MBC using the mass absorption cross section
(MAC) by the following equation.
MBC ¼ b0 ½ ffill =MAC
(1)
[9] Here b0 is the absorption coefficient directly measured
by COSMOS, and ffill is the correction of the magnification
of absorption by multiple scattering in the filter media.
Therefore, the ffill/MAC ratio is of upmost importance, not
the absolute value of MAC in determining MBC, because
the MAC value depends on the scheme used for ffill [Kondo
et al., 2011b]. We determined the ffill/MAC ratio and MAC
(by specifying ffill as a function of filter transmittance) by
comparison with a single-particle soot photometer (SP2)
3710
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
[12] Figure 2a shows the trajectories of the air masses
arriving at Happo for each day during the spring and
summer of 2008. The majority of the air masses passed over
the Asian continent, mostly over Mongolia and northwestern
China in spring, winter, and fall, driven by the Siberian high,
persistent during the winter monsoon period. In summer, the
North Pacific high-pressure system was much stronger, and
the Siberian high was reversed to a low-pressure system,
typical of the summer monsoon in East Asia. Associated with
the summer monsoon, cleaner Pacific air was transported to
Happo more frequently near the surface.
[13] We classified the air mass types based on the
residence time (RT) of an air mass in a given region as
predicted by the trajectories. These regions are defined
as North China (NC) (40 N–50 N, 100 E–130 E and
33 N–40 N, 100 E–123 E), south China (SC) (20 N–33 N,
100 E–123 E), Korea (KR) (33.5 N–40 N, 123 E–129.5 E),
Japan (JP) (30 N–46 N, 130 E–147 E), marine (MA), and
FT. We have used the same classifications as were used for
the analysis of the BC data at Hedo [Verma et al., 2011]. The
air masses were defined as NC, KR, SC, or JP if their back
trajectories originated in the boundary layer (BL) of NC, KR,
SC, or JP, respectively. In this study, we defined the top level
of the BL over the Asian continent as the 700 hPa atmospheric
pressure level (about 3.0 km). The air masses were classified
as MA if their back trajectories did not pass over the domain
areas of NC, KR, SC, or JP. Similarly, the air masses were
categorized as FT if their back trajectories traveled above the
BL over the domain areas of NC, KR, and SC. The residence
time has been calculated as the time spent by individual air
based on the laser-induced incandescence technique and
the thermal-optical transmittance (TOT) technique [Kondo
et al., 2009, 2011b]. The stability of MAC (or, more
correctly, the ffill/MAC ratio) is achieved by removing volatile aerosol components with the use of an inlet heated at
400 C, prior to the collection of BC particles on filters.
The MBC values are given in units of mass per unit volume
of air (mg m3) at standard temperature and pressure
(273.15 K and 1013 hPa).
[10] The accuracy of the MBC measured by COSMOS has
been fully estimated to be about 10%, by comparison with
that measured by SP2 and TOT instruments [Kondo et al.,
2009, 2011a; Kanaya et al., 2013]. We used 1 h average
BC data for the present analysis. In addition to the BC data
at Happo, we used the ground-based MBC data obtained
at Hedo [Verma et al., 2011] and those obtained by the
A-FORCE aircraft campaign conducted over the East China
Sea in spring 2009 [Kondo et al., 2011a; Oshima et al.,
2012]. The location of Hedo and the flight tracks of the
A-FORCE campaign are also shown in Figure 1.
3.
Origin of Air Masses
[11] We calculated 5 day backward trajectories using the
trajectory model of the National Institute of Polar Research
[Tomikawa and Sato, 2005] driven by the pressure and wind
field data from the National Center for Environmental
Prediction-Final Analyses to study the transport patterns of
air masses arriving at the observation site. Each trajectory
started from 800 hPa at 12:00 local time (LT).
(a)
(b)
FT
1000
900
50
800
40
700
Pressure(hPa)
Latitude(°N)
60
600
30
500
20
80
100
120
140
160
Longitude(°E)
Figure 2. Five day back trajectories of air masses for (a) spring and summer seasons of the year 2008
and (b) free tropospheric (FT) air masses during April 2008. Back trajectories were calculated starting
at 800 hPa pressure altitude and 12:00 local time. The regions of North China (NC), south China (SC),
Korea (KR), and Japan (JP) defined in this study are shown with red boxes (same as in Figure 1).
3711
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
masses in the respective regions. To ensure robustness in
the analysis, we have used only data with RT > 24 h in the
specified regions. Based on the criteria of RT (>24 h), SC air
rarely reached Happo.
[14] As can be seen in Figure 2a, air masses originating
from NC often passed over the Korean region before
reaching Happo. We calculated the Rf(NC) ratio of the
residence time in NC to the total residence time in NC + KR.
We defined KR for air masses with Rf(NC) < 0.2, Mixed
(NC + KR) for 0.2 < Rf(NC) < 0.8, and NC for Rf(NC)
0.8. We follow this classification for NC, KR, and mixed
(MX) type of air masses throughout this paper. The trajectories for FT air masses for April 2008 (Figure 2b), a typical
example, show that FT air passed predominantly over the
Asian continent, especially China.
[15] Figure 3 shows the percentage (%) contribution
of different air mass types during the observation period.
Generally, the FT air masses dominated the total air masses
reaching Happo, except for summer. The contribution of
NC air was 9%–14% during the study period and was a
minimum during summer and fall 2008 (Figure 3). If the
air masses from KR and MX are considered to have been
influenced by BC emissions in NC, the total fractions of
air masses of NC origin increase to 35%–55%. The fractions
of the Chinese air (NC + SC + MX + KR) are similar to the
values of 47%–55% observed at Hedo [Verma et al., 2011].
4.
Model Calculations
[16] We calculated MBC using the Community Multiscale
Air Quality (CMAQ) three-dimensional model (version 4.7)
[Byun and Ching, 1999; Binkowski and Roselle, 2003],
combined with the source and process apportionment
method (process, age, and source region chasing algorithm;
PASCAL) [Matsui and Koike, 2012]. The meteorological
inputs were calculated using the Weather Research and
Forecasting model (version 3.1.1) [Skamarock et al., 2008].
The model calculations and emission inventories used in
this study are the same as those described in detail by Matsui
et al. (submitted).
[17] The CMAQ-PASCAL calculation domain covers the
entire North and East Asian region (60 – 180 E, 5 – 70 N)
with a horizontal grid spacing of 81 km (140 90 grids)
and 20 vertical layers from the surface to 100 hPa [Matsui
and Koike, 2012; Matsui et al. (submitted)]. In this study,
PASCAL is used to trace source regions and types of
emissions in Asia to understand the observed variability of
MBC at Happo. Source regions and types are defined in this
study as anthropogenic sources in East Asia (5 N–50 N and
60 E–150 E), North China (>32 N), south China (<32 N),
Korea, and Japan and biomass burning sources in Siberia
and Kazakhstan (50 N–70 N and 60 E–180 E). However,
the latitudinal division between North China and south China
(32 N) was slightly different from that used for the trajectory
analysis (33 N).
[18] The CMAQ-PASCAL model was also used to
calculate TEBC at Happo. TEBC values are defined in this
study as the fraction of BC concentrations in the base
simulation relative to those assuming no removal processes
(i.e., sum of the base simulation and DDEP and WDEP tags:
DDEP and WDEP are the loss amounts by dry and wet
deposition processes, respectively, traced in PASCAL).
TEBC values can be also calculated using derived MBC-CO
correlations. These two definitions of TEBC are identical
provided the MBC-CO correlation that is not influenced by
wet deposition of BC is appropriately chosen.
[19] We used the Asian anthropogenic emission inventory
with a grid resolution of 0.5 0.5 in latitude and longitude
Figure 3. Fractions of the air masses of different categories arriving at Happo in different seasons
for the entire measurement period. For statistics, we included only air masses that spent at least
24 h (i.e., RT > 24 h) in a specified region. NC: North China, SC: south China, KR: Korea, MA:
marine, FT: free troposphere.
3712
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
developed by Zhang et al. [2009] for the year 2006. We have
also incorporated daily biomass burning (BB) emissions from
fire counts (MOD14A1 and MYD14A1) and land use
(MCD12Q1) data measured by Moderate Resolution Imaging
Spectroradiometer (MODIS) satellites with predetermined
values of combustion and emission factors [Reid et al.,
2009; Chang and Song, 2010]. These BB emissions were
evaluated in Matsui et al. (submitted) through comparison
with other inventories of biomass burning emissions.
[20] Figure 1 shows a map of the BC emission rate (Gg/yr/
grid) in East Asia using the emission estimates of Zhang
et al. [2009] for the year 2006. BC emissions in East Asia
(comprising China, Japan, and Korea) for the year 2006
were estimated to be about 1.90 Tg/yr, with most of the
contribution (~95% or 1.81 Tg) coming from China alone
[Zhang et al., 2009], as can be seen from Figure 1. The
relative contributions from Japan and Korea to the total BC
emissions over East Asia were about 3% and 2%, respectively. Most of the BC emissions in China are derived from
industrial, vehicular, and coal-based emissions [Zhang et al.,
2009]. However, a recent study has suggested that biomass
burning (BB) emissions contribute ~13% of total BC aerosols
in China [Kondo et al., 2011a].
5.
Results and Discussion
5.1. Temporal Variations of MBC
[21] Figure 4 shows the variations of the daily average
MBC at Happo during 2007–2009. On average, MBC was
generally stable throughout the year, with an annual mean
of 0.26 0.18 (1s; one standard deviation; SD) mg m3.
There were large variations, however, especially in spring.
The lower envelope of MBC underwent some seasonal variation, reaching a minimum in summer. Before further analysis of this data set, we assessed the possible effects of local
BC emission sources on the observed MBC.
[22] Figure 5 shows the diurnal variation of the average
MBC values at Happo for July 2008 and January 2009.
Unlike the prominent diurnal variability observed in MBC
within the source regions of BC emissions [Kondo et al.,
2006, 2012; Han et al., 2009; Verma et al., 2010], MBC
values showed small diurnal variations at Happo. The MBC
is anticipated to increase during the daytime after sunrise
Figure 4. Time series plot of daily averaged MBC during
the measurement period (August 2007–August 2009). The
vertical dashed line is used to distinguish different seasons
as defined in the text.
Figure 5. Diurnal variations of MBC observed at Happo in
(a) July 2008 and (b) January 2009. The vertical bars represent 1s of the measured MBC.
associated with the upslope wind from the foothills of the
mountains, transporting lower-latitude air with presumably
higher MBC. During the nighttime, radiative cooling of the
surface of the mountains acts to bring down FT air with
lower MBC, most prominently in the early morning prior to
sunrise. Thus, the MBC is anticipated to be lowest during
this period.
[23] The amplitude of the diurnal variation in MBC seems
to be larger in July 2008 than in January 2009 (Figure 5).
To be more quantitative, the MBC values were averaged for
daytime (extended to early evening) (07:00–20:00 local
time, LT) and nighttime (20:00–6:00 LT). The daytime/
nighttime ratios of MBC were 1.21 for July 2008 and 1.11
for January 2009. The ratios for other months were generally
in this range (not shown). The seasonal variation of the ratio
is mainly due to the variation of the heating rate of the
mountain slopes. The diurnal variation of MBC is not necessarily due to BC emitted locally. As discussed later in this
section, MBC generally decreased with the increase in
altitude from the BL to the FT over the western Pacific.
The vertical gradient in MBC can cause small diurnal variations in MBC at Happo, coupled with diurnal variations of
the upward and downward transport of ambient air. Because
of this, we used diurnally averaged values of MBC for the
quantitative analysis in this paper without discarding the
daytime data. The uncertainty in the interpretation of the
3713
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
[26] We calculated monthly averaged MBC values for NC,
FT, and MX air masses, as shown in Figure 7a. The mean
MBC values in FT air masses are close to those of NC air
masses, for which trajectories were located below 700 hPa.
The mean pressure level of FT air near the eastern boundaries
0.8
Happo NC (Obs)
Happo FT (Obs)
Happo MX (Obs)
(a)
0.6
BC (µg m-3)
MBC data associated with the 24 h averaging is estimated to
be about 5% for winter and 10% for summer.
[24] Figure 6 shows time series plots for monthly mean
values of MBC separately for 2007–2008 and 2008–2009 at
Happo. The statistics of the measured MBC (mean 1s)
values for each season are also summarized in Table 1.
The mean MBC was 0.26 0.18 mg m3 for the entire measurement period. The comparison of monthly mean and median
values of MBC shows that MBC underwent similar seasonal
variations in both years (Figure 6) with the mean MBC highest
in spring (~0.35 mg m3) for the 2 years.
[25] The important features of the seasonal variations
of MBC are better understood by extracting the seasonal
variations of the different types of air. The observational site
was under the influence of continental outflow from China
and Korea during the study period (Figure 3). In addition,
FT air masses constituted about 35%–59% of the total air
masses measured at Happo, except for summer (Figure 3).
By definition, these air masses were located above 700 hPa
(~3 km altitude) when they passed over the eastern borders
of the NC or SC regions. NC air constituted about
9%–14% of the sample air masses throughout the seasons.
0.4
0.2
0.0
Mar
May
Jul
Sep
Nov
Jan
2008
Mar
May
2009
1.6
(b)
Hedo NC
Hedo FT
BC (µg m-3)
1.2
0.8
0.4
0.0
Figure 6. Interannual variability of the monthly average
MBC during the 2 year measurement period (August 2007–
August 2009).
Spring 08 Summer 08
Fall 08
Winter 08 Spring 09
Figure 7. (a) Monthly mean ( 1s) of the observed MBC
values at Happo in FT, NC, and MX air masses during
2008–2009. (b) Seasonally averaged MBC values observed
at Hedo in NC and FT air masses. The 1s values are those
of the hourly MBC values.
Table 1. Seasonal Statistics of Observed and Model-Calculated (CMAQ-PASCAL) MBC at Happoa
CMAQ-PASCAL for East Asia
Observation
WWD
WWOD
(Base)
(Without Deposition)
Season
Av. SD
Median
Av. SD
Median
Av. SD
Median
Summer 07
Fall 07
Winter 07
Spring 08
Summer 08
Fall 08
Winter 08
Spring 09
Summer 09
All data
0.25 0.20
0.22 0.15
0.24 0.16
0.37 0.29
0.22 0.15
0.24 0.15
0.24 0.12
0.33 0.18
0.24 0.16
0.26 0.18
0.18
0.19
0.21
0.28
0.18
0.21
0.22
0.28
0.19
0.22
NA
NA
NA
0.36 0.29
0.16 0.13
0.20 0.17
0.17 0.20
0.32 0.26
0.18 0.17
0.23 0.23
NA
NA
NA
0.28
0.14
0.14
0.10
0.24
0.13
0.15
NA
NA
NA
0.61 0.37
0.57 0.28
0.39 0.27
0.37 0.40
0.52 0.32
0.56 0.30
0.49 0.35
NA
NA
NA
0.57
0.52
0.34
0.24
0.49
0.57
0.43
WWD: MBC calculated by CMAQ-PASCAL considering the effects of wet deposition. WOWD: MBC calculated by CMAQ-PASCAL without considering the effects of wet deposition. NA: Not available.
a
The average (Av.) standard deviation (SD) and median are given in units of mg m3.
3714
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
was about 570 hPa (about 4.5 km). This suggests that BL air
was well mixed up to at least about 700 hPa. It is also possible that FT air was mixed with NC air before reaching Happo
at 1.8 km (~750 hPa). In this regard, the MBC values in NC
and FT air are interpreted to be the most representative
MBC values at 1.8 km height in the western Pacific, strongly
influenced by BC emissions in North China.
[27] The MBC values in FT and NC air were the lowest in
the November–March period, and they were similar for the
other months. The MBC values showed rather sharp increases
from March to April. The lower MBC values in late fall/early
spring were also seen for MX air, although less pronounced,
suggesting some differences in the characteristics of MX air.
[28] Figure 7b shows seasonally averaged MBC values for
NC and FT air masses at Hedo. The observed MBC values for
NC and FT air masses at Hedo are very different from those
at Happo. In contrast to the relatively similar MBC values for
NC and FT air masses at Happo, MBC values were a factor of
2–3 higher for NC air mass at Hedo. However, the level of
MBC in FT air masses at Hedo is more or less similar to that
at Happo. This suggests that the mixing and transport
pathways of the NC air masses were somewhat different
between Happo and Hedo. The measurements of MBC at
Hedo represent values near the surface, whereas those at
Happo were at an altitude of ~1.8 km. In the case of Hedo,
the NC air masses were transported at lower altitude, well
within the BL. The high MBC in winter at Hedo, is consistent
with the low MBC at Happo in the same season. The higher
BL/FT MBC ratio in winter is interpreted to be due to the
weakened upward transport of BC from the mixed layer.
[29] The MBC values for MX air in April and May 2008
were considerably higher than those for FT and NC air. They
were also higher than those for MX air in 2009. This
suggests additional sources of BC aerosols in Asia, especially
in spring 2008. The possible cause of the high MBC in MX air
in spring is discussed in detail in section 5.4.
[30] We have also compared MBC values of ground-based
observations at Hedo and Happo to understand the observed
vertical distribution of MBC over the western Pacific Ocean.
The vertical profile of MBC (between altitudes of 0.5 and
8 km) was obtained during the A-FORCE aircraft campaign
[Kondo et al., 2011a; Oshima et al., 2012]. The mean MBC
values were between 0.3 and 0.5 mg m3 at altitudes below
2 km, strongly influenced by the transport of BC from
China and decreasing sharply above 2 km altitude (Figure 8).
The mean MBC values at Happo are similar to the MBC
values obtained during the A-FORCE campaign, within the
variability of MBC shown as horizontal bars in Figure 8.
The small vertical gradient of MBC from the surface up to
1.8 km is consistent with the similarity in the MBC for FT
and NC air at Happo, as discussed above.
were used for quantitative interpretation of the observed MBC
data.
[32] Figure 10a shows the time series of comparison of the
monthly mean MBC (1s) observed (MBC-obs) and modeled
(MBC-model) during the 2 year measurement period. The
model calculations for anthropogenic + biomass burning
(AN + BN) and anthropogenic alone (AN) are shown separately. Table 1 summarizes the seasonal average MBC-model
(AN + BB) for a quantitative comparison. The average
MBC-model/MBC-obs ratio was 0.96 for all the data, indicating
that the CMAQ-PASCAL model (base case data)
reproduced well the yearly averaged MBC at Happo. The
model generally reproduced the seasonal variations of
MBC, although it overestimated MBC by 11%–15% for
spring 2008 and 2009.
[33] The MBC-model calculation for anthropogenic only (AN)
showed a small spring maximum, and the inclusion of BB
emissions further increased MBC-model values (Figure 10a).
Therefore, it is likely that the spring maximum of MBC was
due to increased efficiency of transport of anthropogenic BC
from the Asian continent and BB emissions in Siberia. These
effects are discussed more quantitatively using statistical data
of FT, NC, and MX air in section 5.4.
5.2. Comparison of Observed and
Model-Calculated MBC
[31] Figures 9a and 9b show the horizontal distributions of
MBC at about 990 hPa (0.2 km), 810 hPa (1.8 km), and
720 hPa (2.8 km) calculated by CMAQ-PASCAL (MBC-model)
for April 2008 and January 2009, respectively. The calculations were made including anthropogenic and BB emissions
(AN + BB), and excluding BB sources (i.e., AN only). The
model calculations were made with and without wet deposition (base) using AN + BB emissions. These model results
5.3. Transport from the Asian Continent
and Its Efficiency
[34] The relative contributions of anthropogenic BC emissions from different countries in Asia (China, Japan, Korea,
Southeast Asia (SEA), and others) to the MBC values observed
at Happo were calculated by the CMAQ-PASCAL model and
are shown in Figure 10b (source regions are defined in section
4). Table 2 summarizes the relative contributions of BC emitted from China (fChina), NC (fN-China), SC (fS-China), and the
other countries (e.g., Japan and Korea; fOthers) to the observed
Aircraft (Latitude: 26-33°N)
Observation
8
Ground-based at Happo
Mean and SD
Altitude (km)
6
Ground-based at Hedo
Mean
Median
4
2
0
0
500
1000
BC (ng
1500
m-3)
Figure 8. Comparison of MBC values from ground-based
observations at Hedo (~60 m asl) and Happo (~1800 m asl)
in the western Pacific. The vertical profile of MBC obtained
during the Aerosol Radiative Forcing in East Asia (A-FORCE)
[Oshima et al., 2012] aircraft campaign over the western
Pacific is also shown for comparison.
3715
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
Figure 9. (a) Distributions of the model-calculated (CMAQ-PASCAL) MBC at about 2.8 km (720 hPa),
1.8 km (810 hPa), and 0.2 km (990 hPa) for April 2008. The calculations were made including anthropogenic and BB emissions (AN + BB) and excluding BB sources (i.e., AN only). (b) Same as Figure 9 (a) but
for January 2009. The locations of Happo and Hedo are marked as circles.
MBC. The model estimate indicates that China was the largest
contributor to the total MBC at Happo, with an fChina of about
67% for the entire period. It was also observed that, on
average, northern China alone contributed ~61% of the MBC
at Happo, whereas only 6% was from south China. According
to this model, the average contributions of BC emitted from
3716
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
Figure 9. (Continued)
Japan and Korea are estimated to be about 14% and 6%,
respectively, during the whole period.
[35] The transport efficiencies of BC (TEBC) calculated
by the CMAQ-PASCAL model for different seasons are
shown in Figure 11, together with fChina. The TEBC was
relatively stable throughout the year except for summer,
when it fell to 0.27. We have also calculated TEBC values
for different types of air masses reaching Happo (not shown).
The TEBC values for the MX type of air masses were
similar to those of NC air masses. TEBC values were
lowest in summer when the fraction of MA air was as
high as ~35% (Figure 3).
3717
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
(a)
(b)
(c)
Figure 10. (a) Time series plots of the monthly mean ( 1s) values of the observed and modelcalculated (CMAQ-PASCAL) MBC at Happo. The calculations including anthropogenic and BB
emissions (AN + BB) and excluding BB sources (AN) are shown separately. The 1s values represent
the hourly MBC values. (b) Fraction of MBC at Happo originating from anthropogenic sources (AN) in
Asian countries (China, Japan, Korea, Southeast Asia (SEA), and others). (c) Fractions of MBC at Happo
originating from biomass burning (BB) in Asian countries and Siberia.
Table 2. Fractions of MBC ( f ) Originating From China, North
China, and Others (Korea and Japan), Along With the Transport Efficiency of BC (TEBC) for Different Seasons
Season
fChina
fN-China
fS-China
fOthers
fN-China/fChina
TEBC
Spring 2008
Summer 2008
Fall 2008
Winter 2009
Spring 2009
All data
0.59
0.57
0.66
0.82
0.66
0.67
0.53
0.48
0.64
0.70
0.60
0.61
0.06
0.09
0.02
0.11
0.06
0.06
0.41
0.43
0.34
0.18
0.35
0.33
0.90
0.85
0.97
0.86
0.91
0.91
0.58
0.27
0.50
0.46
0.61
0.49
5.4. Upward Transport and Biomass Burning
[36] It is estimated that BC emissions and surface BC
concentrations in China are relatively higher during winter
compared to those during spring months [Streets et al.,
2003; Zhang et al., 2009]. However, the MBC levels were
significantly higher during the spring of both years than
those in winter at Happo (Figure 6). The MBC at
Happo increased to 0.37 mg m3 from an average value of
0.22 mg m3, in particular during the month of April of both
years. There could be two reasons for the enhancement in
Figure 11. Fractional contribution of China to MBC ( fChina)
and TEBC for different seasons.
the levels of MBC at Happo during spring. First, the ambient
temperature over North China is usually lower during winter
than that in the spring season, resulting in shallower mixing
layer heights over North China during winter as compared to
that in spring. Therefore, upward transport of BC enriched
air masses from the surface to the regions above the mixed
3718
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
layer could be lower during winter than those in spring.
Second, BC emissions from biomass burning during the spring
season could be the cause of the winter-spring difference.
[37] For quantitative investigations of the dynamical effect,
we extracted the MBC values for FT, NC, and MX air,
separately. MBC-model (AN) values for these air masses are
compared with the observed MBC values in Figure 12. The
model calculations reproduced well the winter minimum for
FT and NC air. Excellent agreement was obtained for FT air,
which was least impacted by BB. This agreement indicates
that the changes in the upward transport mainly caused the
seasonal variations of the MBC in FT air.
[38] The MBC-model (AN) values at 1.8 and 2.8 km at 130 –
140 E were higher in April than in January (Figures 9a and
9b). In contrast, the MBC-model (AN) in the BL (~0.2 km) over
the Asian continent was much higher in January than in April.
These results also support that the increase in the upward
transport followed by northeastward horizontal transport was
the main cause of the rapid increase in the MBC values in April.
Figure 12. Comparison of the model calculated monthly
mean MBC (AN + BB) values with those observed for (a)
FT, (b) NC, and (c) MX air masses.
[39] Second, there could be additional BC emissions other
than AN, such as those from biomass or agricultural waste
burning in the Asian continent during the spring season.
Earlier studies have suggested that the spring maximum of
CO concentration at Happo results from biomass burning
events in East Asia, particularly from Siberia [Kato et al.,
2002; Narita et al., 1999]. Because BC and CO are produced
simultaneously, as indicated by a strong correlation between
their mass concentrations near source regions [Kondo et al.,
2006; Limon–Sanchez et al., 2011; Pan et al., 2011], it is
likely that Siberian biomass burning events had a strong
influence on the MBC at Happo during spring as well.
[40] The distribution of active fire detections during 2008
and 2009 was produced by the MODIS rapid response
system and is shown in Figure 13a. The map of fire counts
was plotted online using the NASA-Northern Eurasia Earth
Science Partnership Initiative (NASA-NEESPI). The time
series plot of fire counts (Overpass-Corrected Fire Pixel
Counts) for the period of 2007–2009 is shown in Figure 13b.
A number of biomass burning events were detected in
northeast China, Mongolia, and Siberia during spring of the years
2008 (peaking in April) and 2009 (peaking in April–May).
However, the fire counts of the Siberian biomass burning were
relatively lower during April 2009 (Figure 13b).
[41] We also investigated the effect of BB over Eurasia
and East Asia in April 2008 on measured MBC based on
the trajectories shown in Figure 2b. About 18% of the trajectories of the FT air passed over the BB region in Siberia
(40 N–60 N, 60 E–80 E) and 49% over Northeast China
(40 N–60 N, 100 E–135 E) in April 2008. The same analysis
was also applied to the spring of 2009.
[42] The observed MBC for FT and NC air in April and
May in 2008 were similar to those in 2009, despite large
differences in the BB activities in Siberia during those
2 years. The substantial difference is seen for MX air, and
thus, it is possible that the BB in Siberia influenced the
MBC in this air in the spring of 2008.
[43] For more quantitative estimates of the effect of the
BB, we calculated horizontal distribution of MBC at about
2.8 km (720 hPa), 1.8 km (810 hPa), and 0.2 km (990 hPa),
originating from anthropogenic and BB emissions (AN + BB),
and excluding BB sources using the CMAQ-PASCAL
model. Figures 9a and 9b present the horizontal distribution
of the effect of BB emissions for April 2008 and January
2009, respectively. The calculations were made separately
for anthropogenic and BB emissions (AN + BB) and excluding BB sources. The average MBC values with AN + BB emissions for April 2008 and 2009 were 0.44 and 0.45 mg m3,
respectively. In contrast, MBC values for AN emission were
significantly lower: 0.21 and 0.27 mg m3, respectively. The
observed MBC values at Happo during April 2008 also were
much higher than the average nonspring MBC values (about
0.25 mg m3), and Figure 9a suggests that MBC values were
highly influenced by the Siberian biomass burning in spring.
The average contribution of the BB in Siberia to the MBC is
estimated to be as high as 50% for April 2008 (Figure 10c).
[44] The effect of BB on MBC is more clearly seen in the
comparison of the model and observed MBC with higher
time resolution. The MBC calculated by CMAQ-PASCAL
incorporating these BB events in April are compared with
the measured MBC in Figure 14. It can be seen that the timing
and magnitudes of MBC calculated, including anthropogenic
3719
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
(a)
Fire Counts/ Month
70000
60000
Eurasia (40-60 °N, 60-140 °E)
East Eurasia (45-55 °N, 100-135 °E)
(b)
50000
40000
30000
20000
10000
0
09/07
12/07
03/08
06/08
09/08
12/08
03/09
06/09
Time
Figure 13. (a) Maps of fire counts (Overpass-Corrected Fire Pixel Counts) in the months of April 2008
and 2009, plotted online using the Northern Eurasia Earth Science Partnership Initiative (NASA-NEESPI;
website (http://gdata1.sci.gsfc.nasa.gov/daac-bin/G3/gui.cgi?instance_id=neespi). The distribution of
active fire detections is during a 5 day period from April 20 to April 24, 2008, produced by the MODIS
rapid response system, where red dots represent single 1 km MODIS active fire pixels (developed by the
University of Maryland with funds from NASA; website (http://maps.geog.umd.edu). (b) Time series
plots of monthly averaged fire counts over Eurasia and East Eurasia during the measurement period
(August 2007–August 2009).
Figure 14. Time series plots of the observed MBC and that calculated separately including emissions
from Siberian biomass burning (BB), all BB emissions, and total emissions (anthropogenic (AN) + BB)
during April 2008.
and all BB sources (AN + all BB), agree reasonably well with
the observations. More detailed studies of the effect of BB are
given in Matsui et al. (submitted).
[45] These results suggest that BB events in Siberia
substantially contributed to the spring maximum of MBC at
Happo. However, the estimates of BC emissions from BB
are still highly uncertain. The model overestimated MBC in
MX and NC air for May in 2008. In addition, an even larger
overestimate is seen for May in 2009, when the Siberian BB
was much less active. It is likely that the emissions of BC
from BB in China and Siberia were overestimated. Quantifying the effect of the BB on MBC in spring requires further
3720
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
improvements in the estimates of the BC emissions from
BB and simultaneous measurements of MBC at this site for
a longer time period.
6.
Conclusions
[46] We made accurate and long-term measurements of
MBC using a COSMOS at Happo, a remote mountain site
at about 1.8 km altitude in Japan, from August 2007 to
August 2009. The annual average MBC at Happo was about
0.26 mg m3. The MBC values exhibited similar seasonal
variations in both years, with a maximum value of ~0.35 mg m3
in spring. About 40% and 10% the air masses sampled were
classified as free tropospheric (FT) and North China (NC) air.
The MBC values in these air masses represent the values most
strongly influenced by BC emitted from China. The MBC values
calculated using the CMAQ-PASCAL model reproduced well
the MBC for these air masses. The best agreement was obtained
for FT air.
[47] The MBC values in FT and NC air reached minimum
values from late fall to early spring. The comparisons with
the CMAQ-PASCAL model results indicate that the lowest
values in winter were caused by the suppressed upward
transport over China. In the other seasons, the more active
convective activities increased the levels of MBC values.
[48] The model predicted that BC transported from China
contributed ~67% to the measured MBC, consistent with the
trajectory analysis. The contribution of MBC from NC was
much higher (~61%) than that from SC (only 6%), reflecting
the transport pathways. The average transport efficiency of
BC (TEBC) for all the source regions was about 0.50 for
the spring, winter, and fall seasons and 0.27 for summer.
[49] In addition to the anthropogenic emissions in East
Asia, it is likely that BB also contributed to MBC values at
Happo, particularly in the spring season. An increase in
observed MBC values in April and May in 2008, especially
in MX air, suggest the substantial effects of very active BB
in Siberia. These observations are supported by the MODIS
fire counts maps of BB emissions over Siberian regions.
More quantitative analyses of the effect of the BB are
required to improve the estimates of BC emissions from
BB in East Asia.
[50] Acknowledgments. This work was supported by the Ministry of
Education, Culture, Sports, Science, and Technology (MEXT), the strategic
international cooperative program of the Japan Science and Technology
Agency (JST), the global environment research fund of the Japanese
Ministry of the Environment (A-0803 and A-1101), and the GRENE Arctic
Climate Change Research Project. X. Liu was supported by Research
Fellowships of the Japan Society for the Promotion of Science (JSPS) for
Foreign Researchers. The trajectory calculation program used in this paper
was developed by Y. Tomikawa of the National Institute of Polar Research
and K. Sato of The University of Tokyo, Japan.
References
Binkowski, F. S., and S. J. Roselle (2003), Models-3 Community Multiscale
Air Quality (CMAQ) model aerosol component: 1. Model description,
J. Geophys. Res., 108(D6), 4183, doi:10.1029/2001JD001409.
Bond, T. C., D. G. Streets, K. F. Yarber, S. M. Nelson, J.-H. Woo, and
Z. Klimont (2004), A technology-based global inventory of black and
organic carbon emissions from combustion, J. Geophys. Res., 109,
D14203, doi:10.1029/2003JD003697.
Byun, D. W., and J. K. S. Ching (1999), Science algorithms of the EPA
Models-3 Community Multiscale Air Quality (CMAQ) modeling system,
Rep. EPA/600/R-99/030, U.S. Environ. Prot. Agency, Washington, D. C.
Chang, D., and Y. Song (2010), Estimates of biomass burning emissions in
tropical Asia based on satellite-derived data, Atmos. Chem. Phys., 10,
2335–2351, doi:10.5194/acp-10-2335-2010.
Han, S., et al. (2009), Temporal variations of elemental carbon in Beijing,
J. Geophys. Res., 114, D23202, doi:10.1029/2009JD012027.
Hansen, J. E., and M. Sato (2001), Trends of measured climate forcing
agents, Proc. Natl. Acad. Sci. U. S. A., 98, 14778–14783.
Huebert, B., and R. J. Charlson (2000), Uncertainties in data on organic
aerosols, Tellus, 52B, 1249–1255.
Horvath, H. (1993), Atmospheric light absorption-a review, Atmos. Environ.,
27A, 293–317.
IPCC (2007), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the 4th Assessment Report of the IPCC,
Cambridge Univ. Press, Cambridge, U. K., 996 pp.
Jacob, D. J., J. H. Crawford, M. M. Kleb, V. S. Connors, R. J. Bendura, J. L.
Raper, G. W. Sachse, J. C. Gille, L. Emmons, and C. L. Heald (2003),
Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft
mission: Design, execution, and first results, J. Geophys. Res., 108(D20),
9000, doi:10.1029/2002JD003276.
Kanaya, Y., F. Taketani, Y. Komazaki, X. Liu, Y. Kondo, L. K. Sahu,
H. Irie, and H. Takashima (2013), Comparison of black carbon mass concentrations observed by multi-angle absorption photometer (MAAP) and
continuous soot-monitoring system (COSMOS) on Fukue Island and
in Tokyo, Japan, Aerosol Sci. Technol., 47, 1–10, doi:10.1080/
02786826.2012.716551.
Kato, S., P. Pochanart, J. Hirokawa, Y. Kajii, H. Akimoto, Y. Ozaki,
K. Obi, T. Katsuno, D. G. Streets, and N. P. Minko (2002), The influence
of Siberian forest fires on carbon monoxide concentrations at Happo,
Japan, Atmos. Environ., 36(2), 385–390, doi:10.1016/s1352-2310(01)
00158-3.
Kondo, Y., et al. (2006), Temporal variations of elemental carbon in Tokyo,
J. Geophys. Res., 111, D12205, doi:10.1029/2005JD006257.
Kondo, Y., et al. (2009), Stabilization of the mass absorption cross section
of black carbon for filter-based absorption photometry by the use of a
heated inlet, Aerosol Sci. Technol., 43, 741–756, doi:10.1080/
02786820902889879.
Kondo, Y., N. Oshima, M. Kajino, R. Mikami, N. Moteki, N. Takegawa,
R. L. Verma, Y. Kajii, S. Kato, and A. A. Takami (2011a), Emissions
of black carbon in East Asia estimated from observations at remote site
in the East China Sea, J. Geophys. Res., 116, D16201, doi:10.1029/
2011JD015637.
Kondo, Y., L. Sahu, N. Moteki, F. Khan, N. Takegawa, X. Liu, M. Koike,
and T. Miyakawa (2011b), Consistency and traceability of black carbon
measurements made by laser-induced incandescence, thermal optical
transmittance, and filter-based photo-absorption technique, Aerosol Sci.
Technol., 45, 2, 295–312, doi:10.1080/02786826.2010.533215.
Kondo Y., K. Ram, N. Takegawa, L. Sahu, Y. Morino, X. Liu, and T. Ohara
(2012), Reduction of black carbon aerosols in Tokyo: Comparison of realtime observations with emission estimates, Atmos. Environ., 54, 242–249,
doi:10.1016/j.atmosenv.2012.02.003.
Limon-Sanchez, M. T., P. Carbajal-Romero, L. Hernandez-Mena,
H. Saldarriaga-Norena, A. Lopez-Lopez, R. Cosio-Ramirez, J. L.
Arriaga-Colina, and W. Smith (2011), Black carbon in PM2.5, data from
two urban sites in Guadalajara, Mexico during 2008, Atmos. Pollution
Res., 2, 358–365, doi:10.5094/APR.2011.040.
Matsui H., and M. Koike (2012), New source and process apportionment
method using a three-dimensional chemical transport model: Process,
age, and source region chasing algorithm (PASCAL), Atmos. Environ.,
55, 399–409, doi:10.1016/j.atmosenv.2012.02.080.
Miyazaki, Y., Y. Kondo, L. K. Sahu, J. Imaru, N. Fukushima, and A. Kanno
(2008), Performance of a Newly Designed Continuous Soot Monitoring System (COSMOS), J. Environ. Monit., 10, 1195–1201, doi:10.1039/b806957c.
Narita D., et al. (1999), Seasonal Variation of Carbon Monoxide at Remote
Sites in Japan, Chemosphere Global Change Sci., 1, 137–144.
Ohara, T., H. Akimoto, J. Kurokawa, N. Horii, K. Yamaji, X. Yan, and
T. Hayasaka (2007), An Asian emission inventory of anthropogenic
emission sources for the period 1980–2020, Atmos. Chem. Phys., 7,
4419–4444, doi:10.5194/acp-7-4419-2007.
Oshima, N., et al. (2012), Wet removal of black carbon in Asian outflow:
Aerosol Radiative Forcing in East Asia (A-FORCE) aircraft campaign,
J. Geophys. Res., 117, D03204, doi:10.1029/2011JD016552.
Pan, X. L., et al. (2011), Correlation of black carbon aerosol and carbon monoxide
in the high-altitude environment of Mt. Huang in Eastern China, Atmos. Chem.
Phys., 11(18), 9735–9747, doi:10.5194/acp-11-9735-2011.
Park, R. J., et al. (2005), Export efficiency of black carbon aerosol in continental outflow: Global implications, J. Geophys. Res., 110, D11205,
doi:10.1029/2004JD005432.
Reid, J. S., et al. (2009), Global monitoring and forecasting of biomassburning smoke; Description of and lessons from the fire locating and
modeling of burning emissions (FLAMBE) program, IEEE J. Select.
3721
LIU ET AL.: SEASONAL VARIATIONS OF BC AT HAPPO
Topics Appl. Earth Obs. Remote Sens., 2(3), 144–162, doi:10.1109/
JSTARS.2009.2027443.
Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang,
and J. G. Powers (2008), A description of the advanced research WRF version
3, NCAR Tech. Note, NCAR/TN-475 + STR, Natl. Cent. for Atmos. Res.,
Boulder, Colo. (www.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf).
Streets, D. G., et al. (2003), An inventory of gaseous and primary aerosol
emissions in Asia in the year 2000, J. Geophys. Res., 108(D21), 8809,
doi:10.1029/2002JD003093.
Tomikawa, Y., and K. Sato (2005), Design of the NIPR trajectory model,
Polar Meteorol. Glaciol., 19, 120–137.
Uno, I., G. R. Carmichael, D. Streets, S. Satake, T. Takemura, J.-H. Woo,
M. Uematsu, and S. Ohta (2003), Analysis of surface black carbon
distributions during ACE-Asia using a regional-scale aerosol model,
J. Geophys. Res., 108(D23), 8636, doi:10.1029/2002JD003252.
Verma, R. L., et al. (2010), Temporal variations of black carbon in Guangzhou, China, in summer 2006, Atmos. Chem. Phys., 10, 6471–6485,
doi:10.5194/acp-10-6471-2010.
Verma, R. L., Y. Kondo, N. Oshima, H. Matsui, K. Kita, L. K. Sahu,
S. Kato, Y. Kajii A. Takami, and T. Miyakawa (2011), Seasonal variations
of the transport of black carbon and carbon monoxide from the Asian
continent to the western Pacific in the boundary layer, J. Geophys. Res.,
116, D21307, doi:10.1029/2011JD015830.
Zhang, Q., et al. (2009), Asian emissions in 2006 for the NASA
INTEX-B mission, Atmos. Chem. Phys., 9, 5131–5153, doi:10.5194/
acp-9-5131-2009.
3722