ARTICLE IN PRESS
Atmospheric Environment 40 (2006) 3574–3587
www.elsevier.com/locate/atmosenv
Climate-relevant properties of primary particulate emissions
from oil and natural gas combustion
Tami C. Bonda,, Birgit Wehnerb, Antje Plewkab, Alfred Wiedensohlerb,
Jost Heintzenbergb, Robert J. Charlsonc
a
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
b
Institute for Tropospheric Research, 15 Permoserstrasse, Leipzig, Germany
c
Department of Atmospheric Sciences, University of Washington, Seattle, Washington 98195, USA
Received 18 August 2005; received in revised form 22 December 2005; accepted 27 December 2005
Abstract
We report emissions of mass, light absorption, particle number, chemical composition and size-resolved organic species
from an industrial boiler that burned natural gas and residual oil. Organic compounds detected from oil combustion are
mainly alkanes; it is not a major source of identifiable polyaromatic hydrocarbons. Elemental carbon (EC) and organic
carbon (OC) make up approximately 38% and 15% of the particles from oil burning, respectively. Mass emissions from
natural gas were below detection limits. A number peak of ultrafine aerosol (diameters lower than 10 nm) was always
associated with oil burning. Burning at full power produced the greatest number of particles in the accumulation mode.
Natural gas also produced fine particles, but at a much lower rate. The emission rate of light-absorbing particles from this
relatively new boiler is lower than that in current emission inventories. However, real-time measurements show a large
contribution to emitted light absorption from boiler warm-up and transients, even those with very short durations. The
measured absorption is best explained with a constant absorption cross-section for EC, rather than predictions based on
size distribution or mixed aerosol; this finding is consistent with EC in fractal-aggregate form. We compare the emissions
with those of a lignite stoker, which this boiler replaced during environmental cleanup in the mid-1990s. Emissions of mass,
light absorption and particles are lowest from natural gas, but the oil boiler is also a substantial improvement: emissions of
particulate matter are 100 times lower, and emitted absorption is three times lower. However, the oil-burning emissions
have a greater net warming effect per mass than those of the lignite plant.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Particle size distributions; Light absorption; Elemental carbon; Organic speciation; Technology change
1. Introduction
Anthropogenic aerosols from the burning of
fossil fuels affect the solar input to the earth–atmoCorresponding author. Tel.: +1 217 244 5277;
fax: +1 217 333 6968.
E-mail address: [email protected] (T.C. Bond).
1352-2310/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2005.12.030
sphere system by scattering and absorbing radiation
and by providing sites for the condensation of cloud
drops. Emission rates of climate-relevant properties,
such as number of particles and absorption crosssection, are used in simulations of net radiative and
climatic effects of these particles. Particles that do
not absorb light, such as sulfates, produce a cooling
effect, especially in industrial regions (Charlson
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
et al., 1991). Warming by light-absorbing aerosols
offsets this cooling; even small amounts of absorption may significantly alter the net radiative forcing
by particles (Haywood and Shine, 1995). (‘‘Radiative forcing’’, a measure of climatic impact, is the
net change in flux at the Earth’s tropopause.)
Black carbon (BC), produced from the incomplete combustion of carbon-based fuels, is thought
to be the largest component of light-absorbing
atmospheric particles (Rosen et al., 1978). Carbonaceous aerosols that do not absorb light, often
called ‘‘organic carbon’’ (OC), may also make up a
large fraction of anthropogenic particles (Novakov
et al., 1997; Quinn et al., 2004). The relative amount
of absorption versus scattering is one factor that
determines whether those particles warm or cool the
earth system (Jacobson, 2002; Penner et al., 2003).
Anthropogenic increases in cloud condensation
nuclei (CCN) may contribute to the ‘‘indirect
effect’’, or negative forcing due to increases in cloud
albedo (Twomey et al., 1984; Chuang et al., 2002).
Primary particles appear to have a large impact on
CCN (Adams and Seinfeld, 2003).
Aerosol emissions from combustion sources also
affect human health, and have been the subject of
several epidemiological studies (e.g. Pope and
Dockery, 1999). Although some researchers suggest
that respiratory diseases are linked to the number
concentration of particles below 100 nm (Pope,
2000; Oberdörster, 2001; Kreyling et al., 2004),
source-characterization measurements typically focus on aerosol mass, which is dominated by larger
particles.
Direct measurements of the climate- and healthrelevant properties of emissions are rare. In most
cases, mass emission measurements must be converted to the quantities of interest using assumptions about optical cross-sections or size
distributions. Lack of information on the emissions
translates directly to uncertainties in climate models. Measurements of climate-relevant properties at
the point of emission provide initial constraints for
model assumptions, even if those properties are
altered in the atmosphere. In this paper, we report
climate-relevant characteristics—particulate light
absorption and number size distribution—of particles emitted from an industrial boiler that burns oil
and natural gas. We provide size-dependent information on the chemical composition. While our
work focuses on identifying the properties needed to
estimate climatic impacts, the information may also
be useful for studies on human health.
3575
The modern, computer-controlled boiler measured in this study replaced a lignite-burning stoker
that was decommissioned in late 1996. The replacement occurred as part of the environmental cleanup
following German reunification. We reported the
properties of particulate matter emitted from the
lignite stoker in earlier work (Bond et al., 1999b;
Wehner et al., 1999). In this paper, we include a
comparison with the old stoker to assess how
emissions change due to the rapid changes in
technology associated with economic development.
2. Method
2.1. Source description
The boiler measured in this study provided heat
and hot water for a research complex of about 20
buildings. The combustion was thought to be clean
enough that no particulate control devices are
needed, and none were installed. Natural gas was
the preferred fuel due to its lower cost, but the
heating plant received a discount on its gas prices in
exchange for agreeing to use oil during peak load
times. A large tank stored the oil for the boiler
outside the heating plant.
Table 1 contains analyses of the fuel used during
testing. The building complex was not heated at
night, so the boiler was either off or operating at
very low power in the evenings. Our measurements
each day began with the startup period and lasted
until sufficient steam for the daily operation of the
buildings was provided. The boiler typically operated for 7 h when burning natural gas, while the
demand was met after 3 h each day with oil fuel.
Table 1
Ultimate analysis of residual oil (DIN 51603), and composition
of natural gas
Residual Oil (DIN 51603)
Natural Gas
Element
Mass fraction (%) Compound Mole fraction (%)
Carbon
Hydrogen
Oxygen
Nitrogen
Sulfur
Other
86
13
0.50
0.24
0.20
0.06
CH4
C2H6
C3H8
C4H10
CO2
N2
Other
Data were provided by the City of Leipzig.
88.0
5.9
1.4
0.4
1.1
3.0
0.2
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
The oil boiler warmed up for about 1 h upon
startup each day. During that time, the boiler
operated at 100% power with 15–20% excess air,
and the exhaust gas temperature oscillated between
about 120 and 140 1C. After the warmup period, the
excess air increased to 40–50%, the power dropped
to 60–80% of maximum, and the exhaust temperature became more constant. When burning natural
gas, the power behavior was the same, but there was
no warmup period when higher excess air was used.
2.2. Measurement description
The emission characteristics we measured that are
directly relevant to climate modeling include the
emission factor of particulate matter [EFPM,
g (kg fuel) 1], the absorption cross-section of the
emitted particles (MAC, m2 g 1), and the number
size distribution of the particles. Values of EFPM
and MAC can be combined into a single, easily
measured parameter, the absorption emission index
[EIabs, (m2 absorption) (kg fuel) 1] (Bond et al.,
1998), bypassing the need to determine absorptive
properties from chemical composition. An analogous quantity for particle number is the particle
emission index [EIN, particles (kg fuel) 1]. Both
EIabs and EIN can be obtained from real-time
measurements of light absorption, number concentration, and CO2 in the exhaust gas.
We sampled the exhaust gas with a porous-tube
diluting probe, which reduced coagulation of particles, eliminated condensation of water, and simulated
dilution in the atmosphere. The sample was drawn
into the probe isoaxially, and was diluted with dried,
filtered air in less than 10 ms; dilution ratios ranged
from 10:1 to 30:1. Several studies have discussed the
influence of dilution on particle number size distributions (Abdul-Khalek et al., 1999; Shi and Harrison,
1999), especially in the ultrafine ‘‘nucleation’’ mode.
A recent study (Lyyrännen et al., 2004) suggested that
the porous-tube diluter leads to the fewest artifacts in
the nucleation mode, compared with other portable
dilution systems.
We measured particles with diameters below
1 mm, which interact most efficiently with visible
light, by removing larger particles with two preimpactors from the diluted gas. Simultaneous
measurements of light absorption by all particles
smaller than 10 mm and by all particles smaller than
1 mm were statistically identical, so very little coarseparticle light absorption was ignored by choosing a
1-mm cutpoint. Sampling rates were below or near
isokinetic. Submicrometer particles are little affected by variations from isokinetic sampling, and
biases due to these variations were calculated to be
less than 1% for these particles.
Continuous measurements in the diluted gas
included particulate light absorption, particle size
distributions and CO2. We measured the diluted-air
CO2 with an NDIR analyzer (Horiba MEXA GE534) and light absorption by particles with a Particle
Soot Absorption Photometer (PSAP, Radiance
Research, calibrated to a wavelength of 550 nm).
We made spot measurements of CO2, O2, CO, and
unburned hydrocarbons in the exhaust gas about
every 5 min. We obtained dilution ratios by
comparing CO2 measurements in the sample stream
and exhaust. The power-plant computer provided
charts of power and exhaust gas temperature.
Particle number size distributions from 3 to
800 nm (particle diameter) were measured using a
twin differential mobility particle size (TDMPS)system (Birmili et al., 1999). The TDMPS-system
consists of two subsystems measuring different size
ranges of dry particles at the same time. Very small
particles (3oDpo21 nm) were measured by an
ultrafine differential mobility analyzer (UDMA,
Hauke-type, center rod length 11 cm) in conjunction
with an ultrafine condensation particle counter
(UCPC, Model 3025, TSI Inc., St. Paul, MN,
USA). For larger particles (Dp421 nm), a differential mobility analyzer (DMA, Hauke-type, center
rod length 28 cm) and a CPC (Model 3010, TSI Inc.,
St. Paul, MN, USA) were used.
We collected samples on Nuclepores filters, which
were weighed to determine mass emissions and
analyzed with a four-wavelength integrating plate
for light absorption efficiency. Values of EFPM,
MAC, and wavelength dependence of absorption
come from these measurements, which necessarily
span larger time periods and are less numerous than
the real-time measurements. Both PSAP and integrating-plate measurements were corrected according
to the recommendations of Bond et al. (1999a).
Size-segregated particle samples were collected by
a five-stage low-pressure cascade Berner-impactor
with cut-off diameters of 0.14, 0.42, 1.2, and 3.5 mm.
This sample stream operated separately from the
other measurements and therefore was not subjected to the pre-impactors. This sample was also
diluted 1:10 by a dilution system similar to that used
for the submicrometer particle measurements. Aluminum foils were used to collect the particles and to
determine organic and elemental carbon. For
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
3. Results and discussion
3.1. Particle number size distributions
3.1.1. Natural gas
Fig. 1 shows representative size distributions
measured during natural gas combustion, with
full power
decreasing power
60% of full power
107
102
106
100
105
10-2
104
103
ambientair
1
10
100
Dp in nm
1000
dV/ dlog Dp (µm3 cm-3)
108
dN/ dlog Dp (cm-3)
analysis of single organic compounds, two pieces of
ferromagnetic foils (Fe–Ni alloy, Curie point
590 1C) were placed on each of the four smallest
stages. The mass of these samples was determined
by weighing the foils before and after exposure
(Mettler Toledo UMT 2, 50% RH). The absolute
precision of this balance is in the range of 1–2 mg.
The fraction of OC and elemental carbon (EC) was
determined with a thermographic method (C-mat
5500, Ströhlein). A detailed description of the
thermographic method is given by Neusüss et al.
(2002). The aluminum foil was placed in a quartz tube
and heated rapidly to a specific temperature. In a first
step the sample is heated under nitrogen to 500 1C,
and compounds which evaporate under these conditions are referred to as OC. In a second step, the
sample is heated under oxygen to 650 1C, where all
elemental carbon is oxidized to CO2 which is analyzed
with an IR detector. No adjustment to account for
the associated hydrogen and oxygen is reported here,
so the total associated organic matter is expected to
be higher than the OC reported by about 40%.
For analysis of single organic compounds, we used
the Curie-point pyrolysis gas chromatography mass
spectrometry apparatus described by Neusüss et al.
(2000). In this method, the ferromagnetic foil with the
particles is heated very rapidly (about 20 ms) to the
Curie point temperature by eddy currents in the foil
stimulated by a high-frequency magnetic field. When
the alloy reaches its Curie-point temperature the foil
becomes non-magnetic and the heating effect ceases.
Because the heating is rapid, the organic compounds
are evaporated, not pyrolyzed, and introduced by a
helium carrier into the GC/MS. Identification is
carried out by matching the mass spectra and
retention data with those of reference compounds.
Deuterated polycyclic aromatic hydrocarbons and
aliphatic hydrocarbons were used as reference materials. Only compounds which evaporate easily can be
measured; thus, the identified mass is a small fraction
of the organics. This method has the advantage that
only small sample amounts (a few nanograms) are
necessary for analysis, which allows size-segregated
measurements of particle composition.
3577
10-4
Fig. 1. Number size distributions measured at the heating plant
fired with natural gas (filled symbols) and at ambient air and the
corresponding volume size distributions (open symbols) during
varying operating conditions.
concentration adjusted to the undiluted exhaust.
These number size distributions were taken during
full-power combustion, which always occurred
during the first hour of operation; during 60%
power after the warmup period; and during the
transition between the two. With decreasing power,
the number concentration of ultrafine particles
(3oDpo20 nm) strongly decreases. The particle
number in the size range 20–100 nm also decreases
with decreasing power, but the concentration of
particles larger than 100 nm is nearly constant
during the entire measurement period. The number
size distribution measured during the same time on
the top of a building located next to the heating
plant is included as the solid line. The concentration
of particles larger than 20 nm is relatively low and
similar to those values measured in surrounding the
urban area. Number concentrations in the ultrafine
regions at full-power operation are several orders of
magnitude higher than the background concentration, and examination of all size distributions (not
shown) suggests that the number concentration in
the nuclei mode decreases approximately linearly
with burning rate.
3.1.2. Fuel oil
Size distributions with fuel oil performed at the
same boiler differ significantly from those taken
with natural gas, as shown in Fig. 2. Volume size
distributions calculated using the assumption of
spherical particles are shown as dotted lines with the
same symbols. Fig. 2 shows three size distributions:
one at full power, one at power decreasing between
100% and 60%, and one at 60% of full power. Like
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number concentration
volume concentration
108
104
103
107
102
106
101
105
full power
decreasing power
approx. 60% of full power
104
1
10
100
100
10-1
1000
Dp in nm
Fig. 2. Selected number size distributions measured at the
heating plant fired with heating oil (filled symbols) and the
corresponding volume size distributions (open symbols).
those of Linak et al. (2000) for residual fuel oil, the
volume mode peaks around 100 nm. The full-power
scan differs from the others because it has higher
concentrations in the accumulation mode range
(80–200 nm). At lower power, the ultrafine mode
increases slightly and the accumulation mode
decreases significantly. During full-power conditions, the higher available surface area associated
with the larger accumulation mode may remove
some of the ultrafine particles by coagulation.
Because the accumulation mode decreases as power
decreases, the volume size distributions also depend
significantly on the boiler power.
3.1.3. Comparison of three fuels
The size distributions measured from residual oil
combustion differ in both concentration and shape
from those measured with natural gas. For oil, the
number concentration maximum (3 108 cm 3) is
about a factor of 30 greater than the highest value
for natural gas. The maxima in the ultrafine region
exceed those from full-power natural gas burning by
an order of magnitude, and do not show the
dependence on power that appears in the naturalgas combustion. The size distributions from oil also
exhibit a much higher accumulation mode, by two
to three orders of magnitude, than those from
natural gas.
The particle number size distributions measured
during combustion of natural gas and heating oil
show significant differences with respect to operating conditions. Fig. 3 shows how the total number
concentration of particles varies with the boiler
operating power for both fuels. The number
concentration was calculated by integration over
Particle number concentration [cm-3]
dN/ dlog Dp (cm-3)
109
dV/ dlog Dp (µm3cm-3)
T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
3578
109
100% power
108
Natural Gas
Heating Oil
107
106
105
60 - 70% power
104
0.0
0.5
1.0
1.5
2.0
2.5
time since start of operation [h]
3.0
Fig. 3. Change in total number of emitted particles (o800 nm)
with decreasing boiler power during combustion of natural gas
(dotted lines) and heating oil (solid lines). Boiler power trace is
marked with filled squares.
the measurement size range (3–800 nm), and is
dominated by the ultrafine mode because of the
high concentration in that size range.
As expected from Fig. 1, the emitted particle
number concentration decreases with decreasing
power when the boiler is fired with natural gas,
although the trend is not linear with power. During
the warmup period, the particle number concentration decreases, while power values are constant. For
the heating oil measurements, the number concentration remains nearly constant. Because of the
slight increase in the ultrafine mode, the number
concentration actually increases as the power drops.
Fig. 4 shows the time series of the total volume
concentration of the emitted particles (o800 nm).
The particle volume was calculated from the
number size distributions with the assumption of
spherical particles. The solid curve (natural gas)
decreases very slightly during the 2 h of measurement. The particle volume emitted at heating oil
combustion decreases strongly after 1 h of operation
when the power decreases and the excess air
supplied to the combustion increases.
Table 2 summarizes the characteristics of the
lognormal modes for the two fuels, and also
compares them with our previous study on a
lignite-burning heating plant (Wehner et al., 1999).
The measured number size distributions from
different combustion processes were approximated
by three lognormal modes, using an iterative
moment-preserving least-squares fitting algorithm
(Birmili, 2001). During this procedure, not only
the number size distributions were fitted but
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
12500
60
Natural Gas (left scale)
Heating Oil (right scale)
10000
40
7500
5000
20
2500
0.0
0.5 1.0 1.5 2.0 2.5
time since start of operation [h]
3.0
Particle volume concentration
[µm3 cm-3]
Particle volume concentration
[µm3 cm-3]
simultaneously the distributions of the moments +2
and +4. This improved the convergence of the
least-squares algorithm, and also ensured that the
lognormal modes represented upper moments of the
distribution, such as the condensational sink, and
particle volume concentration at a similar accuracy
as particle number concentration.
Table 2 shows parameters of the approximated
number size distributions at the different combustion stages, averaged over the entire test period.
Each individual size distribution was taken over a
period of 6–8 min. During the experiment at the old
coal-fired heating plant, neither the boiler power
nor the size distributions remained as constant as
those in the new boiler. Therefore, three different
size distributions, representative of most of the
combustion, were selected and approximated by the
lognormal modes.
Fig. 4. Variation of particle volume concentration as a function
of operation time for natural gas and oil combustion. The
warmup period, with lower excess air, ends after 1 h of operation.
3579
The number concentration from the brown coal
plant was nearly constant, about 2 107 cm 3. Oil
combustion emits more particles than natural gas,
with the number concentration varying between
5 107 and 2 108 cm 3. The emissions of the
brown-coal heating plant have number maxima at
particle diameters between 50 and 100 nm. The
largest number concentration of natural gas and oil
particle emissions occurs in the ultrafine range,
especially during operation at full power. For oil
combustion, the difference between full and halfpower emissions occurs in all modes, but most
markedly in the accumulation mode. The number
concentration drops and the peak diameter shifts to
larger particles as the power decreases. For natural
gas, the number concentration of the two modes
that are significantly above ambient concentration
decreases between full and half-power, but the
ultrafine mode (around 10 nm) decreases most
markedly. The particles are apparently larger at
low power, but the difference is less noticeable than
that exhibited by oil combustion.
3.2. Bulk emission properties
Measured emission properties are summarized in
Table 3. The uncertainties reflect both measurement
error and one standard deviation in the observed
variability; the latter contributed most of the
uncertainty. Particulate emissions from the natural
gas burner were quite low. The mass on the
Nuclepores filters was below the detection limit,
Table 2
Parameters of lognormal modes describing the measured number size distributions measured in the exhaust of different combustion
processes at different fuels and different loads
Source
Ultrafine mode
Aitken mode
Accumulation mode
Nt3
s3
Dm3
Nt2
s2
Dm2
Nt1
s1
Dm1
Natural gas
Full power
Decrease
Steady state
1.7 107
1.1 105
8.4 103
1.3
1.6
1.6
5
8
13
2.5 104
1.7 104
1.4 104
1.8
1.8
1.8
40
52
59
1.5 103
1.4 103
1.3 103
1.7
1.6
1.7
206
206
198
Fuel oil
Full power
Decrease
Steady state
1.7 108
3.4 108
1.2 108
1.3
1.4
1.7
5
6
7
1.5 107
9.5 105
4.1 106
1.8
1.6
1.8
36
60
35
1.2 107
1.2 105
2.6 105
1.6
1.4
1.6
89
200
150
Brown coal
Scan1
Scan2
Scan3
1.6 105
1.0 104
2.5 105
1.4
1.4
1.4
3
5
3
6.8 107
4.9 107
7.5 107
1.5
1.5
1.4
48
51
52
1.5 105
4.5 104
1.2 105
1.6
1.6
1.6
400
300
280
Nt means the total particle number concentration in the current mode in part cm 3, s the geometric standard deviation, and Dm the mean
diameter in nm.
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
Table 3
Characteristics of submicrometer emissions from industrial combustion of natural gas and residual oil
Natural gas
EFPM (g kg 1)
0.00470.004
MAC(m2 g 1)
435 nm
525 nm
660 nm
800 nm
Åap (absorption spectral dependence)
n.d.
n.d.
n.d.
n.d.
n.d.
EIabso1 mm (m2 kg 1)
Integratedb, 525 nm
Continuousb (Average)
(excluding high event)
(high event only)
EINo1 mm (1015 kg 1)
n.d.
0.002 7 0.002
n/a
n/a
0.00370.001
Residual oil
Warmup
Normal
Overall
pa
0.0670.05
0.0370.02
0.0570.04
0.28
1.471.7
1.171.2
1.071.1
0.870.8
0.870.2
0.970.6
0.770.4
0.670.4
0.470.2
1.170.1
1.271.3
1.071.0
0.970.9
0.770.7
0.970.2
0.76
0.66
0.68
0.62
0.12
0.0470.03
0.2670.29
0.0570.05
0.6170.18
1.270.6
0.0270.01
0.0470.04
0.0370.05
0.0570.01
1.770.3
0.0370.03
0.1270.15
0.0470.05
0.2070.26
1.570.5
0.36
0.00
0.18
0.00
0.00
a
The p-statistic is the result of an analysis of variance and represents the probability that the oil-combustion ‘‘warmup’’ and ‘‘normal’’
measurements do not differ.
b
Integrated values are from particles collected on Nuclepore filters and post-analyzed; continuous values are made with real-time PSAP
measurements.
and our estimated values of EFPM come from the
Berner impactor measurements, which had a higher
flow rate and a correspondingly higher mass.
The emission of submicrometer particulate matter
from natural-gas burning (0.003 g kg 1) is an order
of magnitude lower than that for oil burning
(0.05 g kg 1). For comparison, values published by
the US Environmental Protection Agency (EPA)
are 0.21 g kg 1 for natural gas and 0.5 g kg 1 for
No. 5 oil (US Environmental Protection Agency
(US EPA), 1996); the present measurements are
substantially lower, possibly because of the recent
installation.
The value of MAC for oil emissions, 1.0 m2 g 1, is
nearly an order of magnitude lower than that of
pure BC (approximately 7.5 m2 g 1). Of course, the
emitted particles are not wholly black carbon.
Particle size and shape also affect absorption
cross-section, and spherical particles that are large
relative to the wavelength of light have lower
absorption cross-sections. These particles cannot
be considered small, but they are probably fractal
aggregates rather than spherical; such particles
would have absorption cross-sections similar to
those of small particles. Thus, chemical composition
and not morphology is probably the reason for the
low value of MAC. This value is also highly
variable, as shown in the table, implying wide
variability in chemical composition. The absorption
is nearly inversely proportional to the wavelength of
light, as one would expect from black particles that
are small relative to the wavelength of light (Bohren
and Huffman, 1983) or fractal aggregates composed
of small spherules.
Values of the absorption emission index (EIabs)
and particle number emission index (EIN) are
calculated from 15-min averages of absorption,
CO2, and DMPS measurements. These real-time
data are more numerous and span more time than
the filter measurements. For natural gas, the value
of EIabs (0.002 m2 kg 1) was statistically different
from that of filtered air, but not from the background air in the heating plant. For the oil boiler,
the average value of EIabs is 0.12 m2 kg 1. As
discussed previously, emitted absorption cross-section (EIabs) should be equivalent to the product of
EFPM and MAC. Table 3 shows that this is not the
case. The continuous measurements that yielded
EIabs spanned one event with anomalously high
absorption, while the filter measurements used to
calculate EFPM and MAC did not include that
period. The average value of EIabs in Table 3 is
strongly affected by that period, and is not
comparable to the product of EFPM and MAC for
that reason. This anomalous event will be discussed
later.
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500
[µg/m3]
400
300
200
100
(a)
3.5-10
1.2-3.5
0.42-1.2
0.42
0.14-
0.14
0.05-
0
particle diameter [µm]
5.0
[µg/m3]
4.0
3.0
2.0
1.0
3.5-10
1.2-3.5
0.42-1.2
0.42
0.14-
0.05-
0.140
0.0
particle diameter [µm]
(b)
Fig. 5. Particle mass concentration emitted during: (a) oil
burning and (b) natural gas burning.
in % of particle mass
For comparison purposes, emission factors used
in recent emission inventories of BC can be
translated to values of EIabs by assuming a value
of MAC. The value of MAC (7.5 m2 g 1) for pure
BC can be used since we are comparing the emission
factors for BC alone. EFBC for natural gas was
given by Cooke et al. (1999) and Bond et al. (2004)
as 0.011 and 0.002 g kg 1, respectively; these translate to EIabs of 0.08 and 0.015 m2 kg 1. Both are
higher than our measured value by an order of
magnitude or more. However, emissions from
natural gas do not have a large impact on global
inventories of absorbing aerosols because even the
previous emission estimates were very low.
For oil burning with no emission controls,
0.07 g kg 1 is given by Cooke et al. (1999) and
0.02 g kg 1 by Bond et al. (2004), equivalent to 0.52
and 0.15 m2 kg 1, respectively. The value in Table 3
lies between the two estimates, but only when the
average includes the short period of anomalously
high absorption. Excluding that period, the average
lies even below the lower estimate. The newness of
the boiler may be a cause of these low emissions.
Fig. 5 shows the particle mass concentrations
from natural gas and oil burning from the impactor
measurements. As expected, the concentrations
from oil combustion are much higher. For these
emissions, most of the mass is found in the smallest
particles, although there are still significant concentrations in larger particles. Eighty percent of the
mass has diameters below one micrometer, and 90%
has diameters below 3.5 mm. Emissions from burning natural gas exhibit very low mass concentrations, as shown in Fig. 5(b). Most of the emitted
mass is found in the coarse particles.
Fig. 6 shows the fraction of OC and EC in the
particle mass from oil burning (natural gas emissions were below the detection limit). EC and OC
represent about 40% and 5%, respectively, of the
submicron particles. EC forms a substantial component of the fine particle mass. In contrast, the
larger particles contain only small amounts of EC,
confirming the observation that there was very little
absorption by particles above 1 mm. The preferential
concentration of EC in small particles agrees with
the results of Kleeman et al. (1999). The high
burning temperature contributes to the very low OC
percentage for all particle sizes. For particles with
diameters below 2.5 mm, both EC and OC fractions
(0.38 and 0.08, respectively) are similar to those
measured in an earlier study (0.29 and 0.13,
respectively; Hildemann et al., 1991). Both studies
3581
70
60
50
40
30
20
10
0
OC
EC
0.05-0.14
0.14-0.42 0.42-1.2
1.2-3.5
particle diameter [µm]
3.5-10
Fig. 6. OC and EC as percentages of particle mass in each size
bin during oil burning.
confirm that the particles are not purely carbonaceous. The remaining 54% of the particles probably
includes water, mineral matter, ionic compounds,
and some hydrogen and oxygen associated with
the OC.
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
Table 4
Speciation of organic single compounds for the four impactor stages
Substance
Biphenyle
Dibenzofurane
Methylphenanthrene
or -anthracene
Methylphenanthrene
Methylphenanthrene
Methylphenanthrene
Cyclopenta[c,d]-pyrene
oxygenated PAH
9H-Fluorenone
Phenalen-1-one
9.10-Anthracendion
4H-Cyclopenta[def]phenanthrenone
EPA-PAH
Phenanthrene
Anthracene
Fluoranthene
Pyrene
Chrysene
Benz[a]anthracene
Benzo[b]+Benzo[k]fluoranthene
Benzo[a]pyrene
Total EPA-PAHs
Alkanes
n-Octadecane (C18)
n-Nonadecane (C19)
n-Eicosane (C20)
n-Heneeicosane (C21)
n-Docosane (C22)
n-Tricosane (C23)
n-Tetracosane (C24)
n-Pentacosane (C25)
n-Hexacosane (C26)
n-Heptacosane (C27)
n-Octacosane (C28)
n-Nonacosane (C29)
n-Triacontane (C30)
n-Hentriacontane (C31)
Total alkanes
CPIodd
Alkan-2-ones
C14
C15
C16
Total Alkan-2-ones
0.05–0.14 mm
0.14-0.42 mm
0.42-1.2 mm
1.2–3.5 mm
ng/mg
ng/m3
ng/mg
ng/m3
ng/mg
ng/m3
3.4
5.2
1.5
1.6
2.4
0.7
0.7
2.3
22.1
0.1
0.4
0.1
n.d.
1.6
n.d.
n.d.
0.2
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
2.2
1.3
2.0
14.2
1.0
0.6
0.9
6.6
0.3
1.3
0.3
0.3
0.2
0.1
0.1
1.1
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
7.7
0.5
2.1
6.0
3.6
0.2
1.0
2.8
3.2
1.2
n.d.
n.d.
0.5
0.2
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
8.0
1.5
5.9
15.4
1.7
2.3
2.0
3.4
40.3
3.7
0.7
2.7
7.2
0.8
1.1
0.9
1.6
18.7
7.0
1.0
4.9
22.1
0.7
1.5
1.0
2.5
40.7
1.2
0.2
0.9
3.8
0.1
0.3
0.2
0.4
7.0
2.1
n.d.
n.d.
1.8
n.d.
n.d.
n.d.
n.d.
3.9
0.3
n.d.
n.d.
0.3
n.d.
n.d.
n.d.
n.d.
0.6
5.2
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
5.2
0.5
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
0.5
3.8
3.8
8.6
10.5
18.6
23.0
32.5
24.7
16.2
8.8
5.5
5.5
1.5
0.3
163.2
1.7
1.8
4.0
4.9
8.6
10.7
15.1
11.5
7.5
4.1
2.6
2.5
0.7
0.1
75.9
0.9
3.4
3.7
9.1
10.7
17.0
23.8
21.8
21.8
17.0
6.8
3.8
3.6
1.6
1.0
145.0
0.6
0.6
1.6
1.8
2.9
4.1
3.8
3.8
2.9
1.2
0.7
0.6
0.3
0.2
25.0
1.0
0.9
0.9
0.4
2.1
0.3
0.3
0.1
0.7
n.d.
n.d.
n.d.
n.d.
n.d.
n.d.
5.4
5.7
14.5
9.4
11.1
15.4
11.0
11.0
8.1
2.8
1.5
1.6
0.7
0.2
98.4
n.d.
n.d.
n.d.
0.8
0.8
2.2
1.4
1.6
2.3
1.6
1.6
1.2
0.4
0.2
0.2
0.1
0.0
14.6
0.9
n.d.
n.d.
n.d.
ng/mg
6.2
6.8
16.1
9.4
10.8
14.5
10.1
10.7
10.4
4.4
3.2
2.9
1.5
1.6
108.8
n.d.
n.d.
n.d.
ng/m3
0.6
0.6
1.5
0.9
1.0
1.3
0.9
1.0
1.0
0.4
0.3
0.3
0.1
0.1
10.1
0.9
n.d.
n.d.
n.d.
n.d.: not detected.
Values are per particle mass and per m3 of sampled air.
Table 4 shows the mass size distribution for the
identified polyaromatic hydrocarbons, alkanes and
ketones for oil combustion. Less than 1% of the OC
was identified for each size fraction, which is typical
for this method. The highest concentrations (in
ng mg 1and ng m 3 for all identified substances were
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
found for the fine particles. At the high temperatures present in the boiler, the semi-volatile organic
substances are primarily in the gas phase. During
cooling of the hot exhaust, the substances condense
mainly on the fine particles that provide the highest
surface area. Identified compounds with the highest
concentrations include pyrene, cyclopenta[c,d]pyrene, and several alkanes. Oil combustion is not a
major source of identifiable polyaromatic hydrocarbons.
The alkanes form the main part of the identified
compounds. They result mainly from unburned
fuel, and possibly from thermocracking of compounds during combustion (Kissin, 1990; Garrett et
al., 2000). The concentration ratio of odd to even
numbered n-alkanes, or the Carbon Preference
Index (CPIodd), should be close to 1.0 for the
combustion of fossil fuels (Simoneit and Mazurek,
1982; Simoneit, 1989). Our results agree with this
prediction at all particle sizes.
We are not aware of other organic speciation
measurements for external-combustion oil boilers.
The closest comparable measurements might be
those of diesel trucks reported by Schauer et al.
(1999). However, diesel engines burn a lighter
distillate fraction of the fuel than reported here,
and one which contains less mineral matter;
additionally, the internal-combustion process in
engines is unsteady and greatly differs from the
external combustion in boilers. Nevertheless, we
compare our speciation results with this study. The
ratio between alkane mass and OC is 0.004 in our
study, compared with 0.01 for diesel engines. Given
the disparity in combustion and fuel, the agreement
is fairly good. However, n-alkanes from oil burning
are 0.02% of the total mass below 3.5 mm, compared
3583
with 0.2% for diesel engines. The greater disparity
for the total mass comparison results because of the
much smaller fraction of OC in our work (5%
versus 19%).
3.3. Effect of operating conditions
Table 5 separates averages for warmup and nonwarmup periods for the oil boiler. Average values of
all characteristics were different under the two types
of operation. In particular, the emission of light
absorption was about six times higher during
warmup. For values of EFPM and MAC, the
difference is not statistically significant because of
the small number of measurements relative to the
high variability.
Conventional wisdom states that an increase in
excess air or equivalence ratio reduces the emission
of ‘‘soot’’ or light-absorbing material; Goldstein
and Siegmund (1976) observed this relationship in
boilers burning heavy fuel oil. Our observations
agree, although the correlation is not very significant. Increasing the burning rate has a slightly
negative effect on the emission of absorption,
probably because the higher temperatures result in
better burnout of the carbon particles. This relationship appears valid on an instantaneous basis only,
as the correlation is better for 1-s observations
(correlation coefficient 0.44) and much worse for
1-min averages (correlation coefficient 0.10).
Transient operation causes large increases in
absorption emission. The most marked difference
is that between absorption emission on the anomalous day (1 April) and on two other days. Fig. 7
shows a period of 10 min when the power was
sharply decreased and then increased. The graph
Table 5
Predicted light absorption at 550 nm based on chemical and physical properties, compared with measured light absorption
Bap (M m 1)
Error (%)
All times
Measured average
Constant absorption cross-section
Predicted from EC mass on impactor stages
Mie theory applied to DMPS measurement (external mixture)
Mie theory applied to DMPS measurement (internal mixture)
2200
1900
1400
3000
3800
16
57
+27
+42
Excluding high absorption period
Measured average
Mie theory applied to DMPS measurement (external mixture)
Mie theory applied to DMPS measurement (internal mixture)
1200
1300
1700
+8
+29
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
3584
100
80
40000
60
40
20000
20
0
8.2
8.3
8.4 8.5 8.6
Hour of Day
8.7
Power Potentiometer (%)
Bap (exhaust, Mm-1)
60000
0
8.8
Fig. 7. Behavior of absorption (Bap) during power turndown. Bap
is a commonly used atmospheric measurement, given in units
of meters squared absorption per cubic meter of air, multipled
by 106.
shows the setting of the power controller from the
plant charts; the event is also reflected in the exhaust
CO2 concentration. The absorption efficiency,
MAC, of the particles from that test is higher than
that from other tests, and the accumulation mode is
larger. If that result were excluded, the average
MAC from all oil-boiler tests would be about 30%
lower, and the variability would be reduced by
about 50%.
An additional unknown factor caused the difference between the anomalous period on 1 April,
when EIabs during warmup was 12 times higher
than during the other days. The pre-warmup
conditions were the same: natural gas burned the
day before, with the boiler cooled for 1–2 h prior to
initiating oil combustion. Power outputs, exhaust
temperatures, and excess air matched closely,
although the exhaust temperature on 1 April was
cooler by about 5 1C. We also discount errors in our
measurement system as a possible explanation,
because emissions after the warmup period were
comparable to other days. US EPA reports cite
poor fuel/air mixing, decreases in combustion
intensity or temperature, or wall quenching as
causes of incomplete combustion (US Environmental Protection Agency (US EPA), 1996). Our
measurements also concur with previous findings
of within-source variability, implying that a number
of tests, or continuous monitoring, are needed to
adequately represent emissions (US Environmental
Protection Agency (US EPA), 1997). Extensive realtime monitoring on a few sources may assist
in understanding the variability of combustion
sources and in identifying the number and type of
measurements required to adequately characterize
each source.
3.4. Light absorption and chemical composition
The chemical composition of submicrometer
particles is used to determine the climatic impacts
of those particles. We now determine the combination of particle size information and chemical
composition required to estimate particulate light
absorption. Table 5 shows several methods of
estimating light absorption and compares these
estimates with the submicrometer absorption that
is actually measured. We use the following methods:
(1) applying a constant absorption cross-section; (2)
applying Mie theory to the impactor measurements;
(3) applying Mie theory to the number size
distributions measured by the DMA, assuming an
external mixture; and (4) applying Mie theory to the
DMA measurements assuming an internal mixture.
More details and results of these comparisons are
given below. We used Matlab implementations of
BHMIE and BHCOAT for the Mie theory (Bohren
and Huffman, 1983; Mätzler, 2002).
(1) We apply a constant absorption cross-section
(7.5 m2 g 1, Bond and Bergstrom, 2006) to the
measured mass of elemental carbon. The predicted
absorption differs from the measurement by only
16%. (2) We apply Mie theory to the size distribution of EC on the submicrometer impactor stages.
These estimates of absorption are lower than
measurements, probably because the larger particles
are predicted to absorb less light but in fact are
fractal aggregates which have a constant absorption
per mass (Bond and Bergstrom, 2006). (3) We apply
Mie theory to the DMA size distributions, assuming
EC occurs as pure particles in isolation, and that the
EC fraction on the impactor stages represents the
fraction of particles composed of EC. Despite the
fact that the DMA misses the largest particles and
thus a substantial fraction of the mass, this
prediction is much greater (27%) than the measured
absorption. (4) We apply Mie theory to the DMA
size distributions, assuming that all particles of each
size are identical to each other and contain cores of
EC coated with non-absorbing material. Again, we
use the fraction of EC from the impactor stages.
This method predicts even higher absorption than
method 3, and thus there is a greater discrepancy
between prediction and measurement. This is true
even when the transient period is excluded, eliminating the possibility that the discrepancy could be
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T.C. Bond et al. / Atmospheric Environment 40 (2006) 3574–3587
attributed to changing size distributions. The DMA
is known to overestimate particle mass for combustion aerosol because fractal aggregates have greater
drag than spheres of equivalent mass. Thus, it
would also overestimate absorption. Incorporating
recent research that would define such a correction
will be the subject of future work.
3.5. Environmental impact of boiler replacement
Table 6 compares emission characteristics between the old, lignite-burning plant and the new
heating plant burning oil and gas fuel. Clearly,
natural gas is the preferred fuel for clean burning;
emissions of mass, light absorption and particles
are all orders of magnitude below the other two
fuels.
The oil boiler is also a substantial improvement
over the lignite plant. Compared with the brown
coal stoker, emissions of particulate matter per mass
of fuel burned are 100 times lower, and emitted
absorption is almost three times lower. More
particles per mass of fuel are emitted from oil than
from brown coal because of higher concentrations
in the ultrafine mode. Furthermore, the heating
value of the fuel is four times higher for oil than for
brown coal, and over six times higher for natural
gas. The net result is an improvement in all
measures when normalized to energy produced.
Compared with brown coal burning, oil burning has
12 times lower absorption cross-section per unit
energy, and slightly lower particle emissions. Natural gas improves over brown coal by three orders
of magnitude. These improved emissions result not
only from fuel-switching, but from the addition of
modern technology, such as computer control of the
fuel- and air-flow rates.
3585
The net climatic impact of particulate emissions is
determined not only by the amount of light
absorption, but also by the amount of light
scattering by these particles. We do not have
measurements of light scattering, but we can infer
that the submicrometer mass has similar scattering
properties for both oil and lignite emissions, because
the mass is dominated by the accumulation mode.
Compared with emissions from the lignite plant, the
oil-burning emissions have a higher mass absorption cross-section and thus a greater net warming
effect per mass. This presents a dilemma: the new
boiler has decreased the amount of emitted absorption, but increased the warming by the particles that
are emitted. We suggest that despite the net
warming per mass, the reduction in emission of all
climate-relevant properties is a positive step.
In this work, we have quantified the actual
change in health- and climate-relevant emissions
due to one instance of targeting a ‘‘dirty’’ boiler for
replacement. Continuing such replacement efforts
will lead to significant benefits for air quality and
health. The impact of these replacements will reduce
humans’ impact on climate, but may lead to net
warming.
Acknowledgements
We gratefully acknowledge the technical support
by Technoserv-Center Dr. Modes & Partner OHG,
Leipzig, in operating the heating plant. TCB
acknowledges travel support from a gift from
the Ford Motor Company to the University of
Washington.
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Table 6
Comparison of submicrometer emissions for old and new heating
plants
Lignite
EFPM
EIabs
EIN
g kg
g GJ
1
4.7
520
1
m2 kg
m2 GJ
1
0.32
36
1
1015 particles kg
particles GJ 1
1
0.4
44
Oil
Natural gas
0.05
1.2
0.003
0.05
0.12
2.9
0.0015
0.025
1.5
37
0.003
0.05
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