JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, D12205, doi:10.1029/2005JD006257, 2006
Temporal variations of elemental carbon in Tokyo
Y. Kondo,1 Y. Komazaki,1 Y. Miyazaki,1 N. Moteki,1 N. Takegawa,1 D. Kodama,1
S. Deguchi,1 M. Nogami,1 M. Fukuda,1 T. Miyakawa,1 Y. Morino,1 M. Koike,2
H. Sakurai,3 and K. Ehara3
Received 23 May 2005; revised 6 January 2006; accepted 2 February 2006; published 17 June 2006.
[1] Mass concentrations of elemental carbon (EC) in fine mode and mixing ratios of
carbon monoxide (CO) were measured at the University of Tokyo campus in Tokyo in
different seasons in 2003–2005. Measurements of EC were made using a semicontinuous
thermal-optical analyzer. The mass concentrations of nonvolatile aerosol measured by
the calibrated scanning mobility particle sizer combined with a heated inlet agreed with the
independent EC measurements with a systematic difference of about 4%, demonstrating
that the mass concentrations of nonvolatile aerosol well represent those for EC. A
majority of the nonvolatile aerosol and therefore EC mass concentration was in volume
equivalent diameters between 50 and 200 nm, peaking at around 130 nm. The correlation
of EC and CO was generally compact throughout the measurement period because of
the similarity in sources. The slope of the EC-CO correlation (DEC/DCO) is
therefore a useful parameter in validating EC emission inventories. The EC concentration
and DEC/DCO showed distinct diurnal variation. On weekdays, EC and DEC/DCO
reached maximum values of about 3 mg m3 and 9 ng m3/parts per billion by volume,
respectively, in the early morning (0400–0800 local time), when the traffic density of
heavy-duty trucks with diesel engines was highest. In addition, these values were
lower by a factor of 2 on Sundays. The heavy truck traffic showed similar diurnal and
weekday/weekend variations, indicating that exhaust from diesel engines is an important
source of EC. Monthly mean DEC/DCO showed a seasonal variation, reaching broad
maximum values in spring-autumn and reaching minimum values in midwinter, following
the seasonal variation in temperature, as observed in Maryland, United States (Chen et al.,
2001). This temperature dependence is likely due to the temperature dependence of EC
emissions from diesel engines on intake air temperature. More stringent regulation of
emissions of particles from diesel cars started in the Tokyo Metropolitan Area in October
2003. The DEC/DCO values did not change, however, exceeding the natural variability
(10%) after 1 year from the start of the new regulations, when the temperature dependence
is taken into account. This indicates that the regulation of particle emissions in the
Tokyo Metropolitan Area was not effective in reducing the EC concentrations after 1 year.
Citation: Kondo, Y., et al. (2006), Temporal variations of elemental carbon in Tokyo, J. Geophys. Res., 111, D12205,
doi:10.1029/2005JD006257.
1. Introduction
[2] Elemental carbon (EC), sometimes referred to as
black carbon (BC), is produced by incomplete combustion
of carbon-based fuels, principally fossil fuels used in
transportation, heating, power generation, and industrial
processes; wood for residential heating; and agricultural
biomass. Natural wildfires at temperate and boreal latitudes
1
Research Center for Advanced Science and Technology, University of
Tokyo, Tokyo, Japan.
2
Department of Earth and Planetary Science, Graduate School of
Science, University of Tokyo, Tokyo, Japan.
3
National Institute of Advanced Industrial Science and Technology,
Tsukuba, Ibaraki, Japan.
Copyright 2006 by the American Geophysical Union.
0148-0227/06/2005JD006257$09.00
are also significant EC sources [e.g., Streets et al., 2003;
Bond et al., 2004]. Soot particles have been shown to be
agglomerates of spherical EC particles with diameters of
15– 50 nm coated with organic carbon (OC) [Seinfeld and
Pandis, 1998; Park et al., 2004a, 2004b; Slowik et
al., 2004]. A significant fraction of EC particles has OC
coatings.
[3] EC also comprises a significant portion of nanoparticles, which are harmful to human health at high concentrations in megacities. EC particles act as carriers of the
organic compounds, especially polycyclic aromatic hydrocarbons (PAHs), that can be allergens or carcinogens [Lighty
et al., 2000]. EC has also been identified as making
important contributions to the radiative heating of the
atmosphere [Haywood et al., 1997; Myhre et al., 1998;
Jacobson, 2001, 2002]. It can also contribute to climate
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ment Program for Aerosol and Oxidant Chemistry in Tokyo
(IMPACT) campaigns. The IMPACT campaigns were conducted within the framework of the International Global
Atmospheric Chemistry Project (IGAC), Mega-Cities: Asia.
Here we show that long-term, high-accuracy measurements
of EC and its tracers are useful in understanding emissions
and transport of EC in urban areas.
2. Measurements
Figure 1. (a) Configurations of the instruments used for
the ambient air measurements. A gas-phase organics
denuder is used to remove gas-phase organic carbon
species. Heaters are used to control the air temperature up
to 400C. (b) Test and calibration systems for nonvolatile
aerosol.
forcing by changing snow and ice albedos [Hansen and
Nazarenko, 2004]. Therefore reductions of EC are beneficial to air quality and global climate [Hansen and Sato,
2001].
[4] Emissions of EC inside megacities are important for
local air quality and that in the surrounding regions,
considering the magnitude of emissions. In addition, EC
transported from megacities can influence regional and
global climate. Emissions of EC in megacities are relatively
well known in that the major sources are general automotive
traffic and industrial fuel combustion, as compared with EC
emissions from less well characterized sources, such as
combustion of biofuels and biomass, which are much more
variable [e.g., Streets et al., 2003]. The behavior of EC has
not been fully characterized, however, even in urban areas,
including those in Japan, mainly because of a paucity of
sufficiently time-resolved EC data for extended time periods. Uncertainties in the estimates of EC emissions in these
areas, including those from road traffic, are still significant
[e.g., Schaap et al., 2004], partly because of the lack of
detailed EC information. Obtaining systematic and accurate
EC data is an important step in characterizing EC emissions
in urban regions. Measurements of EC were made in Tokyo
in 2003 –2004, through the series of Integrated Measure-
[5] EC concentrations were measured along with other
tracers, including CO and CO2 near the urban center of
Tokyo during periods from May 2003 to February 2005. Air
samples were taken about 20 m above ground level from a
building at the Research Center of Advanced Science and
Technology (RCAST) campus of the University of Tokyo
(35.66N, 139.66E) in Japan. The configurations of the
instruments used for the ambient measurements and calibration are shown in Figure 1. RCAST is located about
10 km west of the Tokyo Bay coastline and is near the
southeastern edge of the Kanto Plain, composed of prefectures labeled 1, 2, 3, 6, and, 7 and southern parts of
prefectures 4 and 5 in Figure 2. The population of Tokyo
(labeled 2 in Figure 2) is 12 million, and the population in
the whole Tokyo Metropolitan Area (TMA labeled 1, 2, 3,
and 7 in Figure 2) is 41 million. The 10-km-resolution CO
emission rates, estimated by the Japanese Ministry of
Environment (JMOE), are also shown in Figure 2. RCAST
is located in the highest-CO-emission regions in the TMA.
[6] EC mass concentrations were measured every hour
with a semicontinuous EC and organic carbon (OC) ana-
Figure 2. Locations of the sampling points at RCAST
(diamond), Iogi tunnel (triangle), Ring Road 8 (thick line),
Tsukuba city (square), and Kisai city (circle). Prefectures
numbered 1 – 7 belong to the Tokyo metropolitan area
(Kanto area) by administrative definition. Shaded areas
represent the CO emission rates. Tokyo (2) and Kanagawa
(1) prefectures constitute major CO emission regions.
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lyzer manufactured by Sunset Laboratory Inc. (Beaverton,
Oregon, United States), using a thermal-optical method. The
inlet for air sampling was equipped with a PM1 (1-mmdiameter cutoff size) cyclone (Model URG-2000-30EHB,
URG Inc., United States) and a gas-phase organics denuder
(Sunset Laboratory Inc.) to remove gas-phase organic
carbon species. Ambient aerosol, including EC and OC
particles, was collected on a quartz fiber filter with an
effective collection area of 0.69 cm2 for 45 min at a flow
rate of 133 cm3 s1. Collected aerosols were analyzed on
the basis of the thermal-optical transmittance method in
15 min. The total number of days of these observations was
277.
[7] For this analysis, we used the temperature protocol
proposed by the National Institute for Occupational Safety
and Health (NIOSH) [Birch and Cary, 1996]. Part of the OC
is pyrolytically converted to EC during the heating of this
filter in an oxygen-free helium atmosphere in four temperature steps up to 870C. After completion of the oxygenfree heating stages, the filter is heated up to 900C in the
presence of 2% oxygen. During this phase, both the original
EC and that produced by pyrolysis of OC are converted to
CO2, which is measured by a nondispersive infrared (NDIR)
CO2 detector. The correction for the pyrolytic conversion of
OC to EC was performed by monitoring the transmittance
of a pulsed diode laser beam at 670 nm through a quartz
fiber filter during the sample analysis. More detailed
descriptions of this EC-OC analyzer are given elsewhere
[Birch and Cary, 1996; Bae et al. 2004]. The sensitivity of
the EC-OC analyzer was measured by a routine addition of
a known amount of CH4 every hour. Overall calibration was
made by adding a known amount of sucrose (86 mg) onto
the filters every week. The uncertainty of this calibration
was estimated to be 3% from the ratio of the sensitivities
determined from sucrose calibration and routine CH4 calibration. The zero level was determined by removing aerosol
in the sample air using a filter once per week. The detection
limit was determined to be 0.4 mg m3 from the variability
(2s) of the zero level.
[8] The uncertainties associated with the aerosol sampling by the semicontinuous instrument were assessed by
comparison with filter samples taken at RCAST during the
IMPACT campaign conducted in July – August 2004, followed by EC-OC analysis in the laboratory. The systematic
uncertainty and the detection limit of the semicontinuous
EC measurement were estimated to be 4% and 0.48 mg m3
(2s), respectively. A similar analysis was made by comparing semicontinuous and filter-based measurements in East
St. Louis, Illinois, United States [Bae et al., 2004]. The
systematic difference of the two EC measurements was
estimated to be 5% for an average EC concentration of
0.70 mg m3.
[9] In addition, a comparison with the temperature protocol proposed by the Interagency Monitoring of Protected
Visual Environments (IMPROVE) of the Desert Research
Institute was performed. The mass concentrations of EC
based on the NIOSH protocol were found to be lower by
approximately 21% than those based on the IMPROVE
protocol, under typical ambient conditions in Tokyo. This is
considered to be a measure of the uncertainty associated
with the separation of EC and OC. The overall accuracy of
the present EC measurement is estimated to be 22% from
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uncertainties associated with the sensitivity calibration,
aerosol sampling, and temperature protocol.
[10] Nonvolatile aerosol has been found to contain a
significant portion of EC in outflows from the Asian
continent [e.g., Clarke et al., 2004], although some contribution of dust was indicated, depending on the meteorological conditions. EC is expected to constitute a much
larger part of nonvolatile aerosol in Tokyo, where concentrations of dust should be much smaller than those of EC.
We have measured size distributions of PM1 nonvolatile
aerosol using a heated inlet system, which is described
below, and a scanning mobility particle sizer (SMPS; TSI
Inc., Model 3034, St. Paul, Minnesota, United States),
which is composed of a 1-mm diameter cut off size impactor,
differential mobility analyzer (DMA), and condensation
nuclei counter (CNC) (Figure 1a). About six sets of size
distributions at aerosol mobility diameters (Dm) between 10
and 487 nm were obtained every hour. Dm measured by the
SMPS was calibrated using standard polystyrene latex
(PSL) particles (Duke Scientific Corp., Palo Alto, California, United States) with diameters of 102, 199, and 404 nm.
The PSL particles were nebulized in purified water. The
uncertainty of the PSL particle diameter, traceable to the
National Institute of Standards and Technology (NIST), was
certified to be 1 – 3% by the manufacturer. The uncertainty
of the number size distribution (dN/dlogDm) measured by
this SMPS was estimated to be about 10%, from a comparison with two other SMPS systems (TSI Inc., Model 3936).
A 21-cm-long section of the inlet, made of 7-mm inner
diameter stainless steel tubing, was heated to 400C, using a
method similar to that used by Clarke et al. [2004]. The
residence time of sampled air in the heated section was 0.48
s. In order to confirm evaporation of volatile components,
the chemical composition of ambient aerosol was measured
using an Aerodyne aerosol mass spectrometer (AMS) [e.g.,
Takegawa et al., 2005] by varing inlet temperatures between
20 and 400C in 20C increments, when the ambient PM1
aerosol concentrations were stable at about 39 ± 3 mg m3.
At 400C, about 97 ± 5% of inorganic (SO2
4 , NO3 , Cl ,
+
and NH4 ) and organic components were estimated to have
evaporated (Y. Komazaki, unpublished data, 2004) from the
measured decreases in their mass concentrations by heating.
This result confirms high evaporation efficiency at this
temperature, although some of the organic compounds
might have pyrolized. The possible error in the estimate
of the EC mass concentration by the pyrolized organic
compounds is estimated to be less than about 10%, as
discussed in section 4.1. Loss of EC particles through the
heated inlet was measured by comparison with measurements at ambient temperature using glassy carbon particles.
The loss was measured to be 0, 2, and 5% with an
uncertainty of about ±5% for Dm = 100, 60, and 30 nm,
respectively. No detectable loss was observed at larger
diameters.
[11] A relationship between mass and Dm was calibrated
for nonvolatile particles in ambient air at the National
Institute of Advanced Industrial Science and Technology
(AIST), Tsukuba (Figure 2), Ibaraki, Japan, using an aerosol
particle mass analyzer (APM) [Ehara et al., 1996]. The
uncertainty of the aerosol mass measurement by the DMAAPM system is estimated to be about 5% [McMurry et al.,
2002]. The mass of ambient aerosol after being heated to
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the instrument sensitivity (i.e., stability of the calibration
signals) was about 1.5% (1s). The overall precision and
accuracy of the 1-min CO data were estimated to be 4 ppbv
and 20 ppbv, respectively, at a CO mixing ratio of 400 ppbv.
[14] CO2 was measured using an NDIR-based instrument
with an integration time of 10 s (Model LI7000, Li-Cor,
Inc., United States). The sample line for the CO2 instrument
was the same as that for the CO instrument, so as to reduce
the interference from H2O. A detailed description of the
calibration of the CO2 instrument is given by Takegawa et
al. [2006]. The precision and accuracy of the 10-s CO2 data
were estimated to be 0.3 ppmv and 2 ppmv, respectively, at
the CO2 mixing ratio of 400 ppmv.
3. Meteorological Fields
Figure 3. Average mass of nonvolatile aerosol versus the
mobility diameter (Dm) measured by the heater-DMA-APM
system shown in Figure 1b.
400C was measured by the APM mounted downstream of
the DMA, as shown in Figure 1b. This aerosol mass
calibration system is similar to that used for diesel exhaust
particles by Park et al. [2003]. The difference is that we
used ambient air instead of direct diesel exhaust. The
average mass (M) of the nonvolatile aerosol measured by
this system is shown as a function of Dm in Figure 3. We
define the volume equivalent diameter Dve as
M =r ¼ pD3ve =6
ð1Þ
[12] Here, r is the density of EC. Park et al. [2004b]
showed that the density of diesel soot particles was
1.77 g cm3, after they were heated to 300C to remove
volatile organic compounds. Using this reported density and
equation (1), the relationship between Dm and Dve can be
derived from the Dm-M calibration data. Once dN/dlogDm
is measured, it can be converted to mass size distribution
dM/dlogDm using the Dm-Dve relationship.
[13] CO concentration was measured by an NDIR gas
analyzer (Thermo Electron Inc., Model 48C, United States)
with an integration time of 1 min. In order to reduce the
interference from water vapor, the sample air for the CO
instrument was dried (dew point < 0C) using a Nafion
dryer (Perma-Pure, Inc., United States). The background
(zero) signals were routinely measured every 1 or 2 hours
by supplying purified (dry) air into the sample line. The
zero signals measured using the purified air agreed well
with those measured using a Hopcalite scrubber (CO
removal catalyst) after passing the sample air through the
Nafion dryer. The uncertainty in determining the zero levels
was estimated to be about 30 ppbv (2s). Calibrations were
performed once every 3 weeks by supplying a CO standard
(5 parts per million by volume (ppmv) CO in air) manufactured by the Nissan-Tanaka Corp., Japan. The stability of
[15] Meteorological conditions for the measurements are
described briefly. From late spring to midsummer, a sealand breeze circulation was often driven by the heating and
cooling of the Kanto Plain during daytime and nighttime,
respectively. On clear, calm days, southerlies typically
dominated during the daytime, and air over the ocean was
brought to the observational site and further transported
northward. From midnight to early morning, weak
northerlies dominated and air was transported from northern
Kanto Plain. The typical altitude of the top of the boundary
layer was about 1200 – 1800 m during midday and 300–
500 m during midnight in July 2004, according to lowpowered laser radar (Ceilometer TXK-6, Meisei Electric.
Co. Ltd.) observations at the National Institute of Information and Communications Technology (NICT) in Koganei
city, 20 km west of RCAST (M. Yasui, unpublished data,
2004). In winter, the sea-land breeze circulation did not
develop. Instead, the northwesterlies associated with the
strong Siberian high-pressure system generally dominated
over the Japanese islands. As a result, air was transported to
the observational site primarily from the northwest, after
passing over the northern part of the Kanto Plain.
4. Results and Discussion
4.1. Size Distribution
[16] Size distributions of nonvolatile aerosols measured
by the SMPS with a heated inlet were measured between 24
July and 15 August 2004. The average mass size distributions for 0700, 1400, and 2200 local time (LT) are shown in
Figure 4 as a function of Dm and Dve. Nonvolatile aerosol
had a unimodal size distribution, and a majority of the mass
concentration was in the size range of Dve = 50– 200 nm
(Dm = 50– 480 nm), peaking at around Dve = 130 nm.
Changes in the peak Dve were small, ranging over 130 ±
20 nm during the whole of the observational period. These
mass size distributions were integrated to derive total mass
concentrations of nonvolatile aerosol (SMPS mass), assuming smooth extrapolation beyond 480 nm. For this estimation, lognormal size distributions were derived by fitting to
the observed values. The error associated with this extrapolation is estimated to be about 1%. Loss of EC through the
heated inlet for Dm < 100 nm introduces errors less than 1%.
The nonvolatile SMPS mass concentrations are compared
with the PM1 EC concentrations measured simultaneously
with the EC-OC analyzer in Figures 5a (time series) and 5b
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with the present measurements. However, it should be noted
that the diameters of particles collected by impaction in the
United States and Finland are those for internally mixed
aerosols, which contain volatile species in addition to the
EC component. By contrast, the present data provide mass
size distributions of the EC component in internally mixed
aerosols. In addition, the present size distributions were
obtained at higher size and time resolutions than the
previous studies. Therefore the mass size distribution is
not smeared out by integration, and a more accurate
distribution was obtained in this study.
Figure 4. Average mass (M) size distribution of nonvolatile aerosol measured as a function of Dm and volume
equivalent diameter (Dve) at 0700, 1400, and 2200 LT in
July – August 2004. Bars indicate the 1s values.
(scatterplot). The SMPS mass concentrations agree very
well with the EC concentrations with a slope of 0.96 and r2 =
0.88. The systematic difference of about 4% between the
two measurements is within the combined accuracy of the
EC (22%) and SMPS (about 10%) measurements discussed
in section 2, demonstrating that the mass concentrations of
nonvolatile aerosol are representative of those for EC. From
this result, we can conclude that size distributions of
nonvolatile aerosols (Figure 4) represent those for EC
particles. Particles with 50 < Dve < 200 nm constituted a
majority of the total EC mass in Tokyo. Mass size distributions of EC particles in urban air were measured previously by using impactors in the Los Angeles basin, United
States [Venkataraman and Friedlander, 1994], Pittsburgh,
United States [Cabada et al., 2004], and Helsinki, Finland
[Viidanoja et al., 2002]. In most cases, a majority of EC
mass was in the submicron range, basically in agreement
4.2. EC-CO Correlation
[17 ] The EC concentrations observed during July –
August 2004 are plotted versus CO concentration in
Figure 6. EC was generally correlated well with CO during
this and other periods (r2 = 0.62). Correlation coefficients
improve to r2 = 0.70 when the data sets are selected by local
time because of a diurnal variation of the slope, as discussed
in section 4.3. EC is known to be correlated with CO in
other urban areas as well [Chen et al., 2001; Baumgardner
et al., 2002; Park et al., 2005], because both species are
released by incomplete combustion of carbon-based fuels,
especially fossil fuel in the case of the present study.
According to the emission inventory by JMOE shown in
Figure 2, 80% of CO is emitted from vehicles (cars and
trucks) and the rest from industry and commercial facilities
in the TMA, suggesting that EC is also largely emitted from
vehicles. It should be noted that emission ratios of EC/CO
are very different depending on the types of emission
sources, even in the same region [Bond et al., 2004]. For
example, EC/CO emission ratios are known to be much
higher for diesel engines as compared with those for
gasoline engines. Considering the high traffic densities of
both diesel and gasoline vehicles, the slope of the EC-CO
correlation (DEC/DCO) in this study is considered to have
resulted from the mixing of air impacted by emissions with
different EC/CO emission ratios in the TMA. The uniformity of air impacted by these sources is evaluated by hourly
mean CO concentrations observed at monitoring stations in
the TMA in May 2003, as shown in Figure 7. The recordings of the CO data at the monitoring sites were made with a
resolution of 100 ppbv. CO concentrations measured at 7
locations 3 – 22 km distant from RCAST were rather uniform and showed highly correlated variations, with r2 =
0.44 – 0.88 and an average r2 = 0.77. Although the EC
measurement was made only at RCAST, CO and EC values
measured here represent those for mixtures of air impacted by
different sources, rather than those strongly influenced by a
few individual sources in highly localized areas. DEC/DCO
is better suited for detecting average changes in EC
emissions in the TMA than the absolute value of EC alone,
because changes in DEC/DCO through mixing with background air were much less than those in EC, as discussed in
section 4.3.1. In order to derive DEC/DCO, we determined
background values of EC and CO (EC0, CO0), defined as
the median of the values below the 3-s range, namely the
1.25th percentile of the EC and CO values for each month.
DEC/DCO was calculated in three different ways: (1) the
slope of the least squares fitting of the EC-CO scatterplots;
(2) the slope of the least squares fitting of the (EC EC0) (CO CO0) scatterplots, assuming a zero offset; and
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Figure 5. (a) Time series plot of PM1 EC mass concentration measured by the Sunset EC-OC
analyzer and the mass concentration of nonvolatile aerosol (SMPS mass concentration) for the data
obtained in July – August 2004. (b) Correlation between the EC and SMPS mass concentrations shown
in Figure 5a.
(3) median values of the slope of each data point, i.e., (EC EC0)/(CO CO0). For this calculation, data with CO CO0 < 100 ppbv were excluded. The three DEC/DCO
values generally agree well, and the median values within
these three estimates were used for the present study. In
most cases DEC/DCO derived by the method 2 became the
median values. EC0 and CO0 are the values for air masses
flowing into the TMA and thus can depend on various
factors, including season and day of week. They are
generally lower in the summer because of the southerly
flow of relatively clean air from the Pacific Ocean and
higher in the other seasons, especially winter, influenced by
the outflows from the Asian continent. The seasonal variations of EC0 and CO0 are largely taken into account by
using their monthly mean values. Variability with timescales
shorter than a month can lead to uncertainty in DEC/DCO.
[18] Emission ratios of trace species, including EC and
CO, versus CO2 are often used to relate them to fuels
burned [e.g., Andreae and Merlet, 2001; Streets et al.,
2003]. At RCAST, it has been found that CO2 was tightly
correlated with CO in autumn and winter (r2 = 0.91 – 0.92)
[Takegawa et al., 2006] and CO2 is a useful parameter for
comparison with the emission inventories discussed in
section 4.5.1. The slopes of the CO 2-CO correlation
(DCO/DCO2 values) in autumn and winter were 11.6 and
10.7 ppbv/ppmv, respectively.
4.3. Diurnal Variation of EC and DEC/DCO
4.3.1. Dynamical Effects
[19] Figure 8 shows the diurnal variations of the median
values of EC, CO, DEC/DCO, and wind speed for four
seasons. For winter, the values for two periods (February
2004; December 2004 to February 2005) are shown separately. The EC – wind speed correlation is also shown. The
diurnal variations of the median values of EC, CO, and
DEC/DCO for the entire observational period are shown in
Figure 9, for weekdays (Monday – Friday), Saturday, and
Sunday, for the consideration of possible differences in EC
emissions, depending on the day of the week. The EC
concentration did not show a significant dependence on the
day of the week Monday – Saturday, with an average value
of 1.9 mg m3, and it was about 40% lower than this value
on Sunday, similar to that observed in Atlanta, Georgia,
United States [Lim and Turpin, 2002]. These variations are
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Figure 6. EC-CO correlation using all the data obtained in July – August 2004. The correlations
obtained at 0400 – 0800 LT and 2200 – 0200 LT are also shown. The least squares fit is shown for
reference.
Figure 7. CO temporal variations measured at RCAST and two monitoring stations at Setagaya (3 km
from RCAST) and Arakawa (14 km from RCAST) in Tokyo in May 2003. The recordings of the CO data
at the monitoring sites were made with a resolution of 100 ppbv.
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Figure 8. Diurnal variations of the median values of EC, CO, DEC/DCO, and wind speed for each
season. The blue open and solid circles represent the values for February 2004 and for December 2004 to
February 2005, respectively. Bars for EC, CO, and wind speed, representing the 1s values, are shown
only for spring for the sake of clarity of the figures. The ranges of the bars are similar for the other
seasons. Bars for DEC/DCO indicate the range of the values derived by three methods (see text). The
correlations of EC and CO with wind speed are also shown.
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Figure 9. Diurnal variations of median values of DEC/
DCO for weekdays, Saturdays, and Sundays. Bars indicate
the range of the values derived by the three methods.
interpreted in terms of diurnal patterns of EC emissions and
transport below.
[20] As seen in Figure 8, EC started to increase rapidly
around 0400 LT, reaching maximum values of about 2 –
3 mg m3 around 0700 LT, because of increases in traffic,
especially diesel trucks, as discussed in more detail below. It
then decreased throughout the day, in summer and to a
lesser degree in spring. The decrease is less pronounced in
autumn and winter. The average nighttime EC values were
about 1.5 mg m3, half of the early morning peak values.
The decrease during the daytime was also seen for CO in
summer and spring. During these seasons, southerly wind
speed increased from morning to afternoon, associated with
the development of the sea breeze. The period of EC
decrease corresponds to that of the increase in wind speed,
as shown in Figure 8. Increases in the horizontal wind speed
allow for a shorter time for air to accumulate emitted EC
before reaching RCAST. In addition, the boundary layer
height increased in the early morning in summer, as
described earlier, indicating that vertical mixing became
more effective during daytime. Active venting of air during
daytime also dilutes higher EC and CO concentrations
near the surface by mixing with overlying air with lower
concentrations.
[21] In autumn and winter, the sea-land breeze circulation
did not develop and the wind speed did not show a
systematic diurnal variation similar to that for summer
and spring, although the wind speeds were generally higher
during daytime than nighttime. As a result, the diurnal
variation of EC between 0600 and 1800 LT was less
pronounced, especially in winter. Despite the seasonal
difference in the diurnal pattern of the local winds, EC
decreased with wind speeds similarly to spring and summer
(Figure 8). It should be noted that, in summertime, the
timing of the increases in the wind speed in the late morning
coincides with the decrease in EC emissions, as discussed in
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section 4.3.2. Therefore the EC – wind speed relationship in
summer might naturally have been more pronounced than
that for other seasons. Similar dynamical effects (wind
speed and boundary layer height) on EC concentrations
were observed also in the close vicinity of a high-traffic
road around Paris, leading to a continued decrease in EC
throughout the daytime in summer, after reaching maximum
values in the early morning [Ruellan and Cachier, 2001].
[22] As seen in Figure 9, DEC/DCO reached maximum
values of about 8 – 9 ng m3/ppbv on weekdays around
0700 LT similarly to EC. However, in summer and spring,
DEC/DCO values did not show a subsequent decrease
during the daytime, in contrast to EC, as seen from
Figure 8. The decrease in EC in the afternoon is associated
with the decrease in CO to a large degree, resulting in the
reduced decrease in DEC/DCO. After 1800 LT, DEC/DCO
started to decrease, reaching minimum values of about
5 ng m3/ppbv around midnight, irrespective of the season.
Although the diurnal wind pattern was different for autumn,
the diurnal patterns of DEC/DCO became similar. In winter,
DEC/DCO was generally lower than the other seasons,
especially in the early to late morning. The average temperature in the early morning (0400 – 0800 LT) in midwinter
was about 3C, which was more than 10C lower than the
other seasons. EC/CO emission ratios for vehicles are lower
under the cold conditions in winter, as discussed in more
detail in section 4.4.
4.3.2. EC Emissions
[23] According to the estimates of EC emissions by
Streets et al. [2003], transportation and power generation
constitute 42 and 27%, respectively, of EC emissions in
Japan as a whole, with uncertainties of about 83%. Uncertainties in EC emission inventories with finer spatial resolutions are even larger (D. Streets, private communication,
2005). Attempts to estimate contributions of traffic EC
emissions to background EC levels in Tokyo were made
Figure 10. Average diurnal variations of the traffic density
of total vehicles measured in March 2001 and November
2003 for weekdays, Saturdays, and Sundays. Bars indicate
the range of values.
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Figure 11. Average diurnal variations of the fractions of all vehicles, comprising cars, light-duty trucks,
heavy-duty trucks, and all trucks, for March 2001 and November 2003 for weekdays, Saturday, and
Sunday.
by the Tokyo Metropolitan Research Institute for Environmental Protection (TMRIEP) and an outline of these studies
are summarized below. PM2.5 (particles smaller than 2.5 mm
in diameter) and PM10 aerosols were collected from filter
samples at 10 monitoring sites (5 residential and 5 roadside
sites) in Tokyo between April 2001 and February 2002 and
were also collected intensively at 4 monitoring sites (2
residential and 2 roadside sites) in Tokyo in March 2002
to measure concentrations of total aerosol mass, metallic
elements, water-soluble ions, EC, and OC. In addition,
chemical source profiles consisting of the same particulate
components were obtained for steel engineering, waste
incineration, heavy oil burning, vehicles, sea salt, as well
as for paved road dust. The derived data on relative
emissions of 7 elements (Na, K, Ca, V, Al, Mn, and EC)
from the above sources were combined with the observed
concentrations of these elements in a chemical mass balance
(CMB) receptor model [e.g., Zheng et al., 2002] for source
apportionment of EC. The results of the CMB modeling
showed that the major sources of EC at general/residential
sites were emissions from diesel vehicles (59 – 97% by
mass, 86% on average). Larger contributions from diesel
vehicles to the observed EC (87 –95%, 95% on average)
were derived for roadside areas. It should be noted, however, if EC emissions from sources other than those considered here are significant, the contributions of diesel
vehicles are overestimated.
[24] We now investigate how temporal variations in
traffic are reflected in the variations in DEC/DCO, considering the significant contributions of traffic. Figures 10
and 11 show one-way traffic density of different types of
vehicles (passenger cars, light trucks, and heavy-duty diesel
trucks) monitored in the Iogi tunnel on Ring Road 8 (marked
as triangle in Figure 2) in Tokyo on Saturday, Sunday,
Monday, and Tuesday during the periods 10 – 13 March
2001 and 8 – 11 November 2003 by TMRIEP (K. Ishii,
unpublished data, 2001 and 2003). Ring Road 8 is one of
the busiest roads in Tokyo, and the tunnel is located 8 km
north-northwest of RCAST. Although the monitoring was
made only for 8 days in total, the fluctuation in the traffic
density was very small, indicating that these data are
representative for ordinary conditions in spring and autumn.
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Table 1. Emission Factors of EC and CO for Gasoline Cars and
Heavy-Duty Diesel Trucksa
EC
CO
Cars
Trucks
0.001
10
0.01 – 0.16
6.8 – 10.0
Units are g km1. From Streets et al. [2003].
a
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[26] Considering that fd(EC) fg(EC), the EC/CO emission ratio for vehicles is expressed as
EC=CO ¼ f d ðECÞNd = f g ðCOÞNg þ f d ðCOÞNd ;
ð2Þ
where Ng and Nd are the traffic density of gasoline and
diesel vehicles, respectively.
[27] Assuming that fg(CO) = fd(CO), equation (2) is
approximated as
The diurnal pattern of the measured ratios of diesel trucks to
total vehicles will probably be similar to those averaged for
the TMA, considering the intensity of the traffic. However,
because of the lack of traffic data for other roads in the TMA,
our interpretation of the diurnal variation of EC in terms of
the diurnal variation of diesel trucks is qualitative.
[25] We have roughly estimated the CO and EC emissions
from gasoline cars and diesel trucks from existing data.
Emission factors of EC (fg(EC) and fd(EC)) and CO (fg(CO)
and fd(CO)) for gasoline and diesel vehicles respectively, in
g km1, estimated by Streets et al. [2003], are summarized
in Table 1, which show that fd(EC) is much greater than
fg(EC) (fd(EC)/fg(EC) = 10 – 160), although fg(CO) and
fd(CO) are similar. From the CO measurements in the Iogi
tunnel (K. Ishii, unpublished data, 2004), fg(CO)/fd(CO)
was derived to be close to unity. K. Miyamoto (unpublished
results, 2001) reported fg(CO)/fd(CO) = 0.5– 0.9 for Tokyo.
The similarity in fg(CO) and fd(CO) was also observed from
measurements in the a tunnel in Osaka, Japan, where
fg(CO)/fd(CO) = 0.86 [Funasaka et al., 1998] and in the
tunnels in Maryland and Pennsylvania, United States, where
fg(CO)/fd(CO) = 0.65 – 0.81 [Pierson et al., 1996]. A
significantly lower ratio of fg(CO)/fd(CO) = 0.32 was
reported by tests in Hong Kong [Tong et al., 2000].
Although values of fg(CO) and fd(CO) vary greatly, depending on various factors (types of cars, periods used, etc.), it is
very likely that fg(CO) is comparable to fd(CO) on average
in Japan. fd(EC) was observed to be much higher than
fg(EC) in the tunnel in Japan [Funasaka et al., 1998] and in
California, United States [Miguel et al., 1998], consistent
with Streets et al. [2003].
EC=CO ¼ ½f d ðECÞ=f d ðCOÞ Nd =Nt ;
ð3Þ
where Nt = Ng + Nd is the total traffic. If DEC/DCO reflects
EC/CO emission ratios, it should vary depending on Nd/Nt.
The total traffic densities of cars, light-duty trucks, and
heavy-duty trucks, are shown in Figure 10. The traffic of
different types of vehicles relative to total traffic is shown in
Figure 11. Light-duty trucks are considered to include both
diesel and gasoline vehicles. The total traffic showed rapid
increases in the early morning and a decrease in the early
evening. For weekdays, the relative car traffic during
nighttime was comparable or higher than that during
daytime and does not agree with the diurnal variation of
DEC/DCO. The fraction of heavy-duty trucks peaked at
around 0400 LT, 2 hours prior to the morning peak of the
total traffic. A significant portion of these trucks arrive in
the TMA by this time to complete freight shipments from
outside the TMA undisturbed by the morning high traffic
density. Only the diurnal pattern of traffic densities of
heavy-duty trucks or total trucks agrees with that of DEC/
DCO. These traffic densities increased by 60– 100% from
midnight to the early morning, in agreement with the
corresponding change in DEC/DCO.
[28] In addition to the diurnal pattern on weekdays, the
changes in relative traffic densities on Saturday and Sunday
from those on weekdays can be compared with the
corresponding changes in DEC/DCO. Again, only the traffic
densities of heavy-duty trucks or total trucks were lowest on
Sundays. To be more precise, the truck fraction for Saturday
and Sunday were normalized to those for weekdays and are
Figure 12. (left) Truck fraction ratios for Saturday and Sunday, normalized to those for weekdays.
(right) Ratios of DEC/DCO for Saturday and Sunday normalized to those for weekdays.
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Figure 13. Monthly median values of EC (solid circles) and CO (open circles) for all the data obtained.
compared with the corresponding ratios of DEC/DCO in
Figure 12. Diurnally averaged Saturday/weekday and Sunday/weekday ratios for all tucks were 0.80 and 0.63, which
are in reasonable agreement with the ratios of 0.92 and 0.69
for DEC/DCO, respectively. If the traffic of heavy-duty
trucks is used for this comparison, the Saturday/weekday
and Sunday/weekday ratios are significantly lower, 0.56 and
0.31, respectively. Therefore, for Sundays at least, considering some contribution of light-duty trucks to EC emissions in addition to the heavy-duty trucks improves
agreement. However, precise data of emission factors and
traffic density of diesel light-duty trucks are necessary to
assess their contributions more quantitatively.
[29] A shift of 1 – 2 hours between the peaks of the traffic
of heavy-duty trucks and DEC/DCO reflect delocalized
sources of EC. EC emitted at different locations are accumulated and mixed during transport prior to sampling at
RCAST. A delay in the DEC/DCO peak is reasonable
considering the time required to accumulate emitted EC.
In addition, the diurnal pattern of the traffic of heavy-duty
trucks shown in Figure 11 may be somewhat different at
different locations in Tokyo, although similar in general.
These factors can lead to a shift in the peak times of DEC/
DCO and the traffic on Ring Road 8. Despite this shift,
DEC/DCO generally followed the diurnal pattern of the
traffic both for weekdays and Sunday. Off-road vehicles
equipped with diesel engines are unlikely to be important
sources of EC in the early morning, because they are
generally operational from 0800 LT or later hours throughout the daytime (working hours) in Tokyo. In addition, an
increase in EC should occur at even later hours, considering
the time required for accumulation. From these analyses, it
is concluded that emissions from heavy-duty diesel trucks
are likely the major sources of EC in Tokyo. Some contributions from light-duty trucks are also likely.
4.3.3. Scavenging of EC by Rain (Rainout)
[30] While EC is hydrophobic immediately after emission, it gradually becomes hydrophilic after being coated by
inorganic and organic compounds. The time constant for
aging by sulfate under daytime conditions during summer is
estimated to be about 8 hours in regions close to sources, for
example, by mesoscale model calculations, although the
model predicts a significant variability [Riemer et al., 2004].
Aged EC is removed by uptake by clouds, followed by
precipitation. However, cloud formation was not frequent in
the boundary layer. Therefore removal of EC by cloud
processing should not be important for EC near the surface
in Tokyo. EC is also scavenged by collisions with and
adsorption onto raindrops (rainout). However, the time
constant for removal of submicron aerosol by falling raindrops is estimated to be longer than 4 days [Seinfeld and
Pandis, 1998], suggesting that precipitation scavenging of
EC is not important. Therefore it is likely that DEC/DCO
observed at RCAST is considered to be mainly controlled
by emissions, mixing, and transport out of Tokyo. In order
to confirm this, the diurnal variation of DEC/DCO on rainy
days was compared with the average values. Rainy days
were defined here as days when the amount of precipitation
exceeded 8 mm. In total, 14 rainy days were identified
between May and October in 2003 and 2004. The diurnal
variation of DEC/DCO on rainy days agreed well with the
average values, to within the range of the variability (bars in
Figure 9). The median value during 24 hours on rainy days
differed by only 0.1 ng m3/ppbv (2%) from the value for
the entire data set, confirming that scavenging of EC by
falling raindrops had little effect on the average EC diurnal
variation.
4.4. Seasonal Variation of EC and DEC/DCO
[31] We now investigate possible seasonal variations of
EC and DEC/DCO. Figure 13 shows monthly median
values of the EC and CO 24-hour average concentrations
in 2003 – 2005. It is clearly seen that changes in EC
corresponded well to those in CO, indicating that transport
processes are important factors in controlling median EC
concentrations, as discussed in section 4.3.1. Again, DEC/
DCO is more appropriate in detecting possible seasonal
variations in EC emissions than EC itself. The median EC
and CO values during the entire 2003 – 2005 period were
1.8 ± 1.8 mg m3 and 368 ± 274 ppbv, respectively.
[32] The DEC/DCO values for the data obtained during
0400– 0800 LT are shown in Figure 14. In Figure 14, the
median temperatures during this local time are also plotted
for comparison. These values represent the highest values
during the course of the day, which are most strongly
influenced by EC emissions from traffic in Tokyo, as
discussed in section 4.3.2. The lowest DEC/DCO values
at 2200 – 0200 LT and the diurnal average for the whole
period are also summarized in Table 2 for comparison. The
DEC/DCO ratio in the early morning ranged over 4.6–
9.3 ng m3/ppbv, with an average of 7.2 ng m3/ppbv
during this period. It reached broad maximum values
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Figure 14. Monthly median values of DEC/DCO for the early morning (0400 – 0800 LT). Bars indicate
the range of values derived from three different methods (see text). The r2 values are also shown for
reference.
between spring and autumn and minimum values in midwinter. The median temperature showed a similar seasonal
pattern. To be more quantitative, the median DEC/DCO
values in the early morning observed in Tokyo are plotted
versus median temperature (T) in Figure 15. The August
2004 data (open circle) deviated significantly from the other
data points. This data was persistently influenced by southerly maritime air associated with a high-pressure system
located east of Tokyo during this period. The DEC/DCO
value showed a systematic increase with temperature
between 2 and 25C, and the linear regression line,
excluding the August 2004 data, is expressed as
DEC=DCO ng m3 =ppbv ¼ 0:17 Tð
CÞ þ 4:85
ð4Þ
The DCO/DCO2 values in autumn and winter showed little
temperature dependence (11.6 and 10.7 ppbv/ppmv, respectively), as discussed in section 4.2., indicating that the
temperature dependence of the CO emission factor is small.
This in turn indicates that changes in EC emission factor
caused the changes in DEC/DCO.
[33] The temperature dependence of DEC/DCO was also
observed at a suburban site in Maryland, United States from
observations between July 1999 and July 2000 by Chen et
al. [2001]. This temperature dependence has been ascribed
to corresponding changes in intake air density for diesel
vehicles. In Maryland, DEC/DCO showed a strong increase
above 15C. By contrast, the increase in DEC/DCO was
more uniform in Tokyo over the range of 2 –25C. The
dependence of DEC/DCO on temperature was lower in
Tokyo: 0.17 ng m3/ppbv/C for 2– 25C in Tokyo versus
0.4 ng m3/ppbv/C for 15– 25C in Maryland. Despite
these differences, the temperature dependence of the EC
emissions from heavy-duty diesel engines is very likely a
common feature. The differences in the DEC/DCO – temperature relation can depend on various factors, including
differences in the design and performance of diesel engines,
the quality of fuels used, and the driving conditions in the
two countries.
[34] New regulations that restrict the use of diesel
vehicles (buses, trucks, and special category vehicles) with
high aerosol emissions were adopted in the TMA (prefectures labeled as 1, 2, 3, and 7) on 1 October 2003.
Limitations on the maximum allowable particulate emissions became more stringent, depending on the weight and
registration dates of vehicles. Vehicles that did not meet the
limitations were required to mount diesel particulate filters
(DPFs) to remove particles. We have used the DEC/DCO
ratio to detect the possible effect of this regulation on
ambient EC. The DEC/DCO for 0400– 0800 LT and the
24-hour average during May and June 2003 are 8.8 ± 0.8
and 6.5 ± 0.7 ng m3/ppbv, respectively. For comparison
with these data, we have chosen data obtained at similar
temperatures to minimize the effect of the temperature
dependence of DEC/DCO. The corresponding DEC/DCO
values in May – June 2004 are 8.0 ± 1.2 and 6.6 ±
1.2 ng m3/ppbv, respectively. If the data during May–
October 2004 (excluding August) are used, these values are
7.9 ± 0.9 and 6.4 ± 1.1 ng m3/ppbv. These values are only
0– 10% lower than the preregulation values. This means that
the possible decrease in DEC/DCO caused by the additional
regulation is within the 10% variability of the data. After
these regulations were adopted, about 10% of the diesel
vehicles in the TMA were equipped with passive regeneration-type DPFs, which are composed of a catalyst to
remove particles by oxidation and a particulate filter. This
Table 2. DEC/DCO for Tokyo at Different Local Times for the
Whole Period
Local Time
DEC/DCOa
Tb
nb
0400 – 0800
2200 – 0200
0000 – 2300
7.2 (±2.6)
4.3 (±1.7)
5.7 (±1.4)
16.7 (±9.6)
17.6 (±9.0)
18.6 (±9.0)
800
840
3860
Units are ng m3/ppbv.
T and n represent the median temperature and number of data points,
respectively.
a
b
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Figure 15. Monthly median values of DEC/DCO for the
early morning plotted versus temperature (T). The August
2004 data are shown as an open circle. The linear regression
line was derived excluding the August 2004 data, which
was persistently influenced by southerly maritime air
associated with a high-pressure system located east of
Tokyo during this period.
type of DPF removes particles emitted from diesel vehicles
with high efficiencies [Yokota et al., 2003]. However, about
90% of diesel vehicles in the TMA were equipped with
DPFs that use only catalysts. It is likely that this type of
DPF does not remove EC efficiently. In addition, the EC
Figure 16. Flight tracks for PEACE-C aircraft measurements made near Nagoya city, shown as thick and dashed
lines. The data obtained in the region north of 34.5N (thick
lines) were used for the present analysis.
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Figure 17. EC-CO correlation obtained in the boundary
layer over the region shown in Figure 16 (north of 34.5N).
The number of the data points (n) is 101. The least squares
fitting is shown for reference.
removal efficiency of any type of DPF might depend on the
condition of vehicles using the roadways. These possibilities need to be validated by further tests or measurements of
emissions directly from vehicles on the roads. The present
study demonstrates the importance of accurately measuring
ambient EC and its tracer CO on a long-term basis in
detecting the effects of EC emission changes on ambient
EC concentrations. There are no other systematic data sets
of EC and CO comparable to those obtained by the present
study in the TMA. In this regard, the continuation of the EC
and CO measurements will be useful in detecting the effects
regulations of EC emissions.
4.5. #EC/#CO at Other Locations
4.5.1. Nagoya City
[35] Here we make comparisons of the DEC/DCO values
in Tokyo with those obtained over Nagoya city and its
vicinity by aircraft in March 2003. The population of
Nagoya city (including surrounding major cities) is 2.20
(3.37) million and the locations of aircraft sampling in this
region are shown in Figure 16. In situ measurements of CO,
CO2, and EC were made onboard the Gulfstream-II aircraft
during the Pacific Exploration of Asian Continental Emission (PEACE) –C campaign, conducted between 22 and
27 March 2004, within the framework of the atmospheric
chemistry project of the Earth Observation Research Center
(EORC) of Japan Aerospace Exploration Agency (JAXA).
CO and CO2 were measured using a vacuum ultraviolet
(VUV) resonance fluorescence instrument [Takegawa et al.,
2001] and an NDIR instrument [Machida et al., 2002],
respectively, with a time resolution of 1 s.
[36] EC was measured using a particle soot absorption
photometer (PSAP) manufactured by Radiance Research
Inc. (Seattle, Washington, United States) and used for
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Table 3. Comparison of the Average DEC/DCO, DCO/DCO2, and
DEC/DCO2 Measured in Tokyo and Nagoyaa
Tokyo
Nagoya
Streets et al. [2003]
DEC/DCO
DCO/DCO2
DEC/DCO2
5.7 (±0.9)
6.3 (±0.5)
9.3 (±4.2)
11.2 (±0.4)
12.6 (±0.7)
8.8 (±1.5)
64 (±13)
79 (±11)
82 (±35)
a
DEC/DCO is given in ng m3/ppbv, DCO/DCO2 is given in ppbv/ppmv,
and DEC/DCO2 is given in ng m3/ppmv. Emission ratios derived from
emission inventories by Streets et al. [2003] are also shown for comparison.
previous aircraft missions [Liley et al., 2002]. The PSAP
measures optical extinction of light at 565 nm by absorbing
aerosols accumulated on a filter. For PEACE-C, sampled air
was heated to 400C to remove volatile aerosol components, in a way similar to that described in section 2. The
specific absorption coefficient sae (m2 g1) is defined as the
ratio of the optical absorption coefficient (m1) to the EC
mass concentration (g m3). Previous studies have shown
significant variability in sae values [e.g., Liousse et al.,
1993; Martins et al., 1998; Sharma et al., 2002], due partly
to differences in the mixing state of EC particles. However,
by heating the sampled air, the specific absorption coefficient sae has been found to become much more stable under
different conditions and not influenced by changes in the
mixing state of EC. The average sae, after correction
following the procedures described by Bond et al. [1999],
has been determined to be 8.9 m2 g1 by comparison with
the simultaneous EC measurements in Tokyo in July –
August 2004. In addition, during the same period, sae was
derived to be 8.7 m2 g1, by similar measurements in Kisai
city (Figure 2), 50 km north of Tokyo, where the degree of
EC mixing with volatile aerosols was greater (Y. Kondo,
unpublished data, 2004). From these comparisons in Tokyo
and Kisai, the uncertainty in sae is estimated to be smaller
than 10%. The precision of the EC measurements by PSAP
is estimated to be 0.3 mg m3 for an integration time of 10 s.
[37] The sample air for the PSAP was aspirated via a
forward facing inlet system. The flow velocity in this
system was slowed to 4– 5 m s1 from an air speed (aircraft
speed relative to wind speed) ranging over 100– 150 m s1
below 1 km. The flow velocity of 4 – 5 m s1 was comparable to the sampling velocity of the PSAP. This enabled
isokinetic air sampling by the PSAP for submicron aerosols.
In this analysis we used the data obtained below 1 km in the
region north of 34.5N (Figure 16), within distances of
about 50 km from Nagoya. In total, 8 profiles obtained on 4
different flight days were used.
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[38] The 1-min-averaged EC concentrations below 1 km
are plotted versus CO values in Figure 17. The DEC/DCO
derived from the slope of the least squares fitting is 6.3 ±
0.5 ng m3/ppbv. To check the variability in the CO source
types between the two regions, the slope of the observed
CO-CO2 correlation was compared. Over Nagoya, DCO/
DCO2 = 12.6 ± 0.7 ppbv/ppmv, which is similar to the value
of 16 ± 2 ppbv/ppmv obtained over Nagoya in January 2002
during PEACE-A [Takegawa et al., 2004]. These values,
together with DEC/DCO 2 , are compared with those
obtained in Tokyo in Table 3. In this table, EC/CO, CO/
CO2, and EC/CO2 emission ratios averaged over all of
Japan estimated by Streets et al. [2003] are also shown
for comparison. The observed ratios in Nagoya and Tokyo
are similar, indicating uniformity of the emission ratios
averaged over these areas. The average EC/CO and EC/
CO2 ratios given by Streets et al. [2003] agree with the
observed DEC/DCO and DEC/DCO2 values to within about
40 and 30%, respectively, providing a measure of the
overall uncertainty of the emission inventories averaged
over Japan. Further improvements in the estimate of the
CO/CO2 emission ratio could lead to a better understanding
of the difference between the observed DEC/DCO (DEC/
DCO2) ratios and the EC/CO (EC/CO2) emission inventory
ratios.
4.5.2. Other Urban Sites
[39] We have compared the median EC and DEC/DCO
values (24-hour averaged) obtained in Tokyo with those
measured in urban and suburban sites on the North American continent in Table 4. Generally, the DEC/DCO value in
the United States was lower than the values from the present
work. In Atlanta, Georgia, Fort Meade, Maryland, and
Baltimore, Maryland, United States, the DEC/DCO value
ranged between 2.9 and 4.1 ng m3/ppbv [Lim and Turpin,
2002; Chen et al., 2001; Park et al., 2005]. These values are
1.5– 2.1 times lower than those measured in Tokyo and
Nagoya. The DEC/DCO in Mexico City [Baumgardner et
al., 2002] is about 7 times lower than that in Tokyo. The
low value in Mexico City has been confirmed by observations during the Mexico City Metropolitan Area field
campaign in April 2004 [Jiang et al., 2005], although the
values were 80% higher than those in 2000. In Mexico City,
a majority of vehicles are equipped with gasoline engines,
leading to lower EC emissions than in Tokyo. CO concentrations in Mexico City were much higher than those in
Tokyo [Baumgardner et al., 2002], partly contributing to the
lower DEC/DCO. In summary, DEC/DCO in Tokyo was 2 –
3 times higher than or comparable to those measured in
Table 4. Comparison of DEC/DCO in Different Industrial/Urban Regions
Region
Period
Tokyo
Nagoya
Atlanta, Georgia, United States
Fort Meade, Maryland, United States
Baltimore, Maryland, United States
Mexico City
Mexico City
2003 – 2005
March 2003
Aug. – Sept. 1999
July 1999
March – Nov. 2002
Jan. – Feb. 2000
April 2004
DEC/DCOa
5.7 ±
6.3 ±
3.2
4.1 ±
2.5 ±
0.88
1.6
0.9
0.5
1.6
1.6
Method
Referenceb
thermal-optical
light absorption
thermal-optical
thermal-optical
thermal-optical
light absorption
light absorption
this work
this work
1
2
3
4
5
Units are ng m3/ppbv.
References: 1, Lim and Turpin [2002]; 2, Chen et al. [2001]; 3, Park et al. [2005]; 4, Baumgardner et al. [2002]; 5, Jiang et al. [2005].
a
b
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other urban or suburban areas in the United States and
Mexico.
DEC/DCO2 to within 60 and 20%, respectively, providing a
measure of the uncertainties in the emission inventories.
5. Summary and Conclusions
[45] Acknowledgments. This research was funded by the Japanese
Ministry of Education, Culture, Sports, Science and Technology (MEXT)
and the Japanese Science and Technology Agency (JST). We acknowledge
the ceilometer data provided by M. Yasui and the traffic and CO data in the
Iogi tunnel provided by K. Ishii. We are indebted to all of the PEACE-C
participants for their cooperation and support. Special thanks are due to the
flight and ground crews of the G-II aircraft of Mitsubishi Diamond Air
Service Co. CO2 data obtained during PEACE-C were provided by
T. Machida.
[40] PM1 EC concentrations and DEC/DCO were measured on an hourly basis in Tokyo between May 2003 and
February 2005. The mass concentrations of nonvolatile
aerosol measured by the calibrated SMPS combined with
a heated inlet agreed with the independent EC measurements, with a systematic difference of about 4%, demonstrating that the mass concentrations of nonvolatile aerosol
are representative of those for EC. A majority of the
nonvolatile aerosol and therefore EC mass concentration
was in the size range of Dve = 50– 200 nm (Dm = 50–
480 nm), peaking at around Dve = 130 nm.
[41] EC and CO were well correlated throughout the
measurement period because of a similarity in sources.
CO and CO2 were also well correlated in autumn and
winter, indicating that both CO and CO2 are good tracers
of EC. EC generally decreased with increasing wind speed,
indicating the importance of dilution by vertical mixing and
horizontal transport in controlling their near surface concentrations. Because the DEC/DCO ratio is not affected by
dilution, it is a more suitable parameter for detecting
changes in the strength of EC emissions than EC measurements alone. EC and DEC/DCO values showed diurnal
variation, peaking in the early morning (0400– 0800 LT)
and reaching minimum values around midnight. The peak
EC and DEC/DCO values were 2 times greater than the
minimum values at midnight. This diurnal pattern is similar
to that of the traffic density of diesel trucks. DEC/DCO for
Sundays was lower by about 50% than weekday values, in
reasonable agreement with changes in truck traffic density.
These results indicate that diesel trucks, especially heavyduty trucks, are the dominant sources of EC in Tokyo.
[42] The median EC and CO values of the whole data
set obtained in 2003– 2005 were 1.8 ± 1.8 mg m3 and
368 ± 274 ppbv, respectively. Because the variations of
monthly median EC and CO values were correlated,
the average monthly DEC/DCO ratio was stable at 7.2 ±
2.6 ng m3/ppbv for 0400 – 0800 LT. DEC/DCO showed a
seasonal variation, reaching broad maximum values in
spring-autumn and reaching minimum values in midwinter,
following the seasonal variation in temperature. The
overall dependence of DEC/DCO on temperature was
0.17 ng m3/ppbv/C for 2– 25C. The dependence of
DEC/DCO on temperature was also observed in Maryland,
United States [Chen et al., 2001], and is likely due to the
temperature dependence of EC emissions from diesel
engines on intake air temperature.
[43] More stringent regulation of emissions of particles
from diesel vehicles started in the Tokyo metropolitan area
in October 2003. Changes in the DEC/DCO values did not
exceed the natural variability (10%) after 1 year from the
start of the new regulations, when this temperature dependence is taken into account.
[44] DEC/DCO and DEC/DCO2 measured in the boundary layer over Nagoya in March 2004 were close to those
observed in Tokyo. EC/CO and EC/CO2 emission inventory
ratios averaged over Japan [Streets et al., 2003] agree with
the measured 24-hour average values of DEC/DCO and
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