Introduction
Oil sands (OS), a type of unconventional petroleum deposit, are naturally
occurring mixtures of bitumen (a viscous form of crude oil), sand, water
and small amounts of other contaminants. The OS deposit in Alberta, Canada,
is estimated to contain about 1.7 trillion barrels of bitumen. This deposit
is distributed in the Athabasca, Cold Lake and Peace River regions, covering
a total area of ∼ 1.42 × 105 km2, of which
about 10 % can be recovered economically with existing technologies
(Government of Alberta, 2009). Bitumen can be recovered in two ways, i.e.,
surface mining for the shallow reserves (e.g., less than 75 m below the
surface) and using in situ technologies for the deeper deposits. Surface
mining can be applied to an area of only 4800 km2 area within the
Athabasca region, and by 2013, about 19 % of this surface minable area had
been disturbed (Alberta Energy, 2017). As demand for crude oil fluctuated,
oil production from the Alberta oil sands experienced periods of rapid
expansion and stabilized production over the last decade, with total OS
production doubling between 2004 (1.1 million barrels per day, with about
66 % from surface mining) and 2014 (2.2 million barrels per day, with
about 47 % from surface mining) (Alberta Energy, 2016).
The OS industry in Alberta has raised concerns of environmental impacts. For
example, measurement results from Kelly et al. (2009, 2010) and Kurek et
al. (2013) showed that the OS development contributed organic (e.g., polycyclic
aromatic hydrocarbons, PAHs) and inorganic (e.g., mercury, nickel and
thallium) pollutants to the Athabasca River watershed; model simulations by
Parajulee and Wania (2014) indicated that the Canadian National Pollutant
Release Inventory (NPRI) likely underestimated PAH emissions in the
Athabasca OS region. Despite these studies, both the emissions and
subsequent environmental impacts remain poorly understood for pollutants
from the Alberta OS industry. To help address this lack of understanding, an
aircraft campaign was conducted with measurements of an extensive set of air
pollutants over the Athabasca OS region in the summer of 2013. Using results
from the campaign, Shephard et al. (2015) validated profiles of ammonia,
carbon monoxide, formic acid and methanol retrieved from the Tropospheric
Emission Spectrometer (TES) satellite; Liggio et al. (2016, 2017)
demonstrated the large OS surface mining facilities in Athabasca as a
significant source of secondary organic aerosol (SOA) and gaseous organic
acids, and Li et al. (2017) identified the surface mining facilities as a
greater source of volatile organic compounds (VOCs) than previously
realized.
In addition to gaseous pollutants and SOA, another focus of the 2013
aircraft campaign was black carbon (BC) emissions from the surface mining
facilities and its transport downwind. BC is a distinct type of carbonaceous
material formed during incomplete combustion of fossil and biomass fuels,
which is strongly light-absorbing in the visible light spectral range,
refractory, insoluble and typically appears as chain-like aggregates
consisting of fewer than 10 to several hundred carbon spherules (Andreae and
Gelencsér, 2006; Bond et al., 2013; Petzold et al., 2013; Buseck et al.,
2014). BC plays a unique and important role in the Earth's climate system as
an effective absorber of solar radiation. It has relatively short
atmospheric residence times but can exert a strong warming effect on global
and regional climate (Ramanathan and Carmichael, 2008; Bond et al., 2013;
Myhre et al., 2013). Therefore, BC emission reduction has long been
considered as an important near-term climate mitigation target. However,
each step along the way between the source and environmental effect of BC is
complex. For example, anthropogenic BC emissions and the resulting temporal
and spatial variations of BC, which can be simulated by chemical transport
models, remain highly uncertain (Samset et al., 2014); parameterizations of
BC size and mixing state have not been well addressed in state-of-the-art
radiative transfer models (Morgenstern et al., 2017). Both factors are
recognized as important sources of uncertainties in the estimate of climate
forcing by BC (IPCC, 2013).
For large-scale industrial activities such as the OS surface mining
operations in Athabasca, key concerns regarding BC include (but are not
limited to) the quantities of BC emitted into the atmosphere, size
distribution and mixing state of the freshly emitted BC particles, evolution
of the BC particles including their size, mixing state and optical
properties as the OS plumes are transported downwind, and BC deposition. In
this study, a total of 17 flights conducted during the 2013 aircraft
campaign were investigated to characterize BC emissions from six major OS
surface mining facilities in the Athabasca region, with focuses on the
evolution of BC size distribution and mixing state. Airborne BC measurements
were performed by a single-particle soot photometer (SP2). BC mass and
number size distributions were determined and compared not only for
different facilities but also for different downwind distances. BC mixing
state was estimated by coating thickness retrieved from the SP2, based on
which the influences of photochemical aging were illustrated. Limitations of
using this coating thickness to represent BC mixing state were also
discussed. These results can provide insights into the evolution of BC
aerosol in the real atmosphere.
Methods
Aircraft campaign
The aircraft campaign was conducted over the Athabasca OS region in northern
Alberta between 13 August and 7 September 2013 in support of the Joint
Canada-Alberta Implementation Plan for Oil Sands Monitoring (JOSM). Using
instruments installed aboard the National Research Council Institute for
Aerospace Research Convair-580 research aircraft, an extensive set of air
pollutants (including both gaseous and particulate species) were determined
with high time resolutions (Gordon et al., 2015; Liggio et al., 2016; Li et
al., 2017). During this campaign, 22 flights were made for a total of about
84 h, without the influences of wet removal and cloud processing. These
flights were designed (1) to quantify emissions of air pollutants from six
major OS surface mining facilities including Syncrude Mildred Lake (SML),
Suncor Energy OSG (SUN), Canadian Natural Resources Limited Horizon (CNRL),
Shell Albian and Jackpine (SAJ), Syncrude Aurora (SAU) and Imperial's Kearl
oil sands mine (IKL), and (2) to determine atmospheric evolution of the
primary pollutants. The details of the measurements, flight patterns
and objectives of the flights were described in detail by Liggio et al. (2016)
and Li et al. (2017). In 14 flights for emission quantitation, the
aircraft was typically flown in a four- or five-sided polygon pattern encircling
an OS surface mining facility, with level flight tracks at 8–10 altitudes
increasing from 150 to 1370 m above ground and reaching above the mixed
layer; these level flight tracks were stacked along the sides of the polygon
to form a virtual box encasing the facility (Figs. 1a and S1a in the Supplement). Repeated
emission flights were made over SML, SUN, CNRL and SAJ, whereas single
flights were made over SAU and IKL.
Examples of flight tracks for (a) emission and
(b) transformation flights, which were flown on 28 August (F_8/28)
and September 4 (F_9/4), 2013, respectively. F_8/28 was flown in a
five-sided polygon pattern, encircling the SUN facility. F_9/4 was conducted
in a Lagrangian pattern, involving five virtual screens (S1 to
S5). A virtual screen corresponds to a specific downwind distance from the
OS source area and consists of level flight tracks perpendicular to the wind
direction at multiple altitudes. Distances between the successive flight
screens during F_9/4 were approximately 30 km, whereas distance between the
OS center (shown approximately by the open star) and the first screen (i.e.,
S1, which was located at the downwind edge of the OS source region)
was also about 30 km. Composite Google Earth images showing flight tracks
are presented in Fig. S1 for F_8/28 and F_9/4. Altitude shown here
indicates the ellipsoid height.
Three flights were designed to study transformation of air pollutants
emitted from the OS surface mining facilities. They were conducted in a
Lagrangian pattern such that the same OS plume was sampled at different time
intervals (approximately 1 h apart) as it was transported downwind from
the source area (Figs. 1b and S1b). Real-time wind speed and direction
measurements were used to guide the intercepting locations. The first
intercepting locations were chosen at about 1 h downwind of the majority
of the OS facilities so that the emitted air pollutants were well mixed and
merged into large plumes. At each intercepting position, the aircraft was
flown along level flight tracks perpendicular to the wind direction at
multiple altitudes; then these level flight tracks were stacked vertically
to create a virtual screen downwind of the OS source area. At least three
screens were created for each transformation flight, without industrial
emissions in between.
Aerosol sampling
Aerosols were sampled through an isokinetic, shrouded solid diffuser inlet
(Droplet Measurement Technologies Inc., Boulder, CO, USA) with a NASA design
as described in Huebert et al. (2004). The inlet was shared by all aerosol
instruments inboard the aircraft, including a high-resolution time-of-flight
aerosol mass spectrometer (HR-ToF-AMS; Aerodyne Research Inc., Billerica,
MA, USA), a condensation particle counter (CPC, Model 3775; TSI Inc.,
Shoreview, MN, USA), an ultra-high-sensitivity aerosol spectrometer (UHSAS) and a
single-particle soot photometer (Droplet Measurement
Technologies Inc., Boulder, CO, USA). The UHSAS measures particle number
size distribution in the 0.06 to 1.0 µm diameter range. Aerosol number
size distributions were also measured using a forward scattering
spectrometer probe (FSSP, Model 300; Particle Measuring Systems Inc.,
Boulder, CO, USA) housed in a pod and mounted under the right wing of the
aircraft. The FSSP has a nonintrusive inletless design and measures
particle number size distribution in the 0.3 to 20 µm diameter range. A
comparison of the measurement results from the UHSAS and FSSP in the
overlapping size range of 0.3 to 1.0 µm showed an agreement in terms of
both particle numbers and their size distributions (Fig. S2). This
comparison suggests that in the inlet and sampling line, both the particle
loss and the evaporation loss from the particles were minimal for the
< 1.0 µm size range.
BC measurements by the SP2
From the common inlet and sampling line, a SP2 was used to measure the
refractory black carbon (rBC) cores on a particle-by-particle basis based on
incandescent light emitted from heated rBC cores when they cross and absorb
energy from a laser beam (Stephens et al., 2003; Baumgardner et al., 2004;
Schwarz et al., 2006; Moteki and Kondo, 2010; Laborde et al., 2012a). The
SP2 used in this study detected single-particle rBC cores in the mass range
of ∼ 0.3–16 fg, based on the calibration using regal black
particles (Cappa et al., 2012). To account for the rBC cores outside this
detection range, a lognormal fit was applied to the measured rBC size
distribution and then extrapolated over 10–1000 nm (Schwarz et al., 2006).
Here the rBC size refers to the mass equivalent diameter (DMEV)
calculated as 6×m/ρ×π1/3, where m and ρ are the mass and density
of the rBC core, respectively. The value of ρ was assumed to be 1.8 g cm-3,
which is the median ρ value recommended by Bond and
Bergstrom (2006). Based on this ρ value, the SP2's detection range for
single-particle rBC core mass (∼ 0.3–16 fg) corresponded to
an rBC size detection range of ∼ 70–260 nm in terms of
DMEV. For either rBC mass or number concentration, a scaling factor
(FrBC) was calculated as Iwhole/Idetected, where Iwhole
indicates the integral of the lognormal fitting curve from 10 to 1000 nm,
and Idetected indicates the integral of the curve from 70 to 260 nm.
Subsequently, the final rBC concentration could be determined as FrBC × Cdetected,
where Cdetected is the detected rBC
concentration (either mass or number) derived from the SP2. All the rBC
concentrations involved in this paper have been scaled by flight-specific
FrBC.
In addition to emitting incandescent radiation, rBC-containing particles
also scatter light when passing through the laser beam of the SP2. Coating
thicknesses on rBC cores (Tcoating, in nanometers, nm) can be retrieved from the
scattering signals on a particle-by-particle basis, using Mie theory
calculation with a series of assumptions (Schwarz et al., 2008a, b; Laborde
et al., 2012b). To calculate Tcoating for an rBC-containing particle,
the internally mixed particle needs to be idealized as a two-component
sphere with a concentric core-shell morphology. In this study, the rBC core
was assumed to have a complex refractive index of 2.26–1.26i, which was
initially suggested by Moteki et al. (2010) and subsequently confirmed by
Taylor et al. (2015). The coating material on a rBC core was assumed to have
a complex refractive index of 1.5–0i, which is representative of the
corresponding values determined for inorganic salts (e.g., ammonium sulfate)
and secondary organic aerosol (Schnaiter et al., 2005; Lambe et al., 2013).
The core size was held fixed at DMEV of the rBC core, whereas the
diameter of the whole particle was varied in the Mie calculation until the
modeled scattering cross section matched the measurement. The measured
scattering cross section was determined by a leading-edge-only (LEO) fit to
the recorded scattering signal (Gao et al., 2007). Finally, Tcoating was
calculated as the difference between the radii of the whole particle and the
rBC core.
A key step in retrieving Tcoating of an rBC-containing particle from its
scattering signal (S) is the LEO fit, which requires at least S can be
properly measured (Schwarz et al., 2008a, b; Laborde et al., 2012b; Liu et
al., 2014). The LEO fit cannot be performed when S is outside the SP2's
detection range of scattering intensity. Thus, Tcoating cannot be
calculated for relatively small rBC cores with thin coatings (i.e., rBC-containing particles with S below the lower detection limit of scattering
intensity) or relatively large rBC cores with thick coatings (i.e., rBC-containing particles with S above the upper detection limit of scattering
intensity) (Metcalf et al., 2012; Dahlkötter et al., 2014). This
limitation prohibits a direct comparison of Tcoating across all rBC
cores with different sizes.
Moreover, the retrieved Tcoating could be considerably influenced by
uncertainties introduced by the LEO fit. These uncertainties can be
evaluated using non-rBC-containing particles. The scattering signals of
non-rBC-containing particles always have the shape of a full Gaussian curve,
since they will not evaporate or change in size when passing through the
SP2's laser beam. Thus, for non-rBC-containing particles, the LEO fit should
in principle lead to the same scattering amplitude or the same optical size
(Doptical) as that retrieved from a fit to the full scattering signal
(i.e., the full-Gaussian fit) (Gao et al., 2007). In this study, the LEO and
full-Gaussian fits agreed within approximately ±15 % in determining
Doptical for non-rBC-containing particles (Fig. 2). Here
Doptical were calculated from the fitted scattering amplitudes, by
assuming a complex refractive index of 1.5–0i for non-rBC-containing
particles. Doptical was used in Fig. 2 to evaluate the agreement
between the LEO and full-Gaussian fits because it was more directly related
to Tcoating compared to the scattering amplitude.
Relationships between optical sizes (Doptical) retrieved
from the LEO and full-Gaussian fits for non-rBC-containing particles observed
during the three transformation flights conducted on 4 September (F_9/4),
19 August (F_8/19) and 5 September (F_9/5), 2013.
Mass and number size distributions of rBC for the 14 emission
flights conducted over the OS facilities. For each flight, measured masses of
individual rBC cores are first grouped into different size bins and then fitted by a lognormal curve; rBC counts
are processed similarly. Results from flight tracks between the airport and
OS facilities are not involved in the analysis. Measurement dates and the
targeted OS facilities (1–3) are also shown for each flight. MMD, NMD, mass
and number distribution widths, which are determined by lognormal fits to the
measurement results, are summarized in Supplement Table S1 for these emission
flights.
Additional data sets used
Organic aerosol (OA) mass was measured with a time resolution of 10 s by the
HR-ToF-AMS. Photochemical age was calculated as
-log10(NOx / NOy), where NOx is the sum of nitrogen
monoxide and nitrogen dioxide (i.e., NO + NO2) and NOy refers to
the total reactive oxidized nitrogen compounds (Kleinman et al., 2008).
Measurements of OA, NOx and NOy during the aircraft campaign have
been described elsewhere (Liggio et al., 2016).
Results and discussion
rBC size distributions over the OS source region: facility-integrated
results
For each flight, the measured masses of the individual rBC cores over the
entire flight were first grouped into different size bins and then fitted by
a lognormal curve:
dmdlogDMEV=Amass×exp0-lnDMEV/X1,massX2,mass2,
where Amass, X1,mass and X2,mass are the fitting
parameters. The fitting parameter X1,mass will be termed the mass
median diameter (MMD), and the fitting parameter X2,mass will be
loosely referred to as the mass distribution width (Widthmass) which
can be converted to the standard deviation of the distribution (σmass) by σmass=expWidthmass/2. As can be seen from
Eq. (1), Amass is proportional to the absolute value of rBC mass
concentration and thus it is unimportant for describing the shape of a
lognormal curve. This is particularly the case for comparison of rBC size
distributions among different OS facilities. It should also be noted that
the mass-based scaling factor (FrBC,mass), which accounts for the rBC
masses outside the SP2's detection range, is independent of Amass.
Therefore, Amass will not be further discussed in rBC size distribution.
Similarly, rBC number size distribution could be expressed as follows:
dNdlogDMEV=Anumber×exp0-lnDMEV/X1,numberX2,number2,
where Anumber, X1,number and X2,number are the fitting
parameters. X1,number and X2,number will be termed the number
median diameter (NMD) and the number distribution width (Widthnumber),
respectively. Widthnumber can be converted to the standard deviation of
the rBC number size distribution (σnumber) by σnumber=expWidthnumber/2.
Mass and number size distributions of rBC are summarized in Fig. 3 for the
14 emission flights. As shown in Fig. 3, the rBC MMD and NMD were
typically in the range of 135–145 and 60–70 nm, respectively, while
both the mass and number distribution widths were approximately 0.7 (the
corresponding σmass and σnumber were about 1.6).
Most of the rBC from the surface mining facilities were from the heavy
diesel trucks used to transport the mined oil sands ores to centralized
locations in each facility for bitumen separation from the sands. In most
cases, rBC emissions from the six major OS surface mining facilities
exhibited similar size distributions. These rBC size distributions are
comparable with those observed for urban emissions and source (or
near-source) samples representing different types of engine exhausts (Table 1).
For example, (1) during an airborne measurement conducted as part of the
CalNex 2010 campaign, rBC MMD was estimated to be 122 nm over the Los
Angeles Basin (Metcalf et al., 2012); (2) rBC MMD observed in urban
outflows were typically in the range of 140–180 nm, as evidenced by
ground-based measurement downwind of Tokyo (Shiraiwa et al., 2007), and by
aircraft-based observations over Texas (Schwarz et al., 2008a), California
(Sahu et al., 2012), and western and northern Europe (McMeeking et al.,
2010); (3) when mainly impacted by traffic emissions, rBC MMDs were about 100
and 120 nm for a suburban site in Paris (Laborde et al., 2013) and an urban
site in London (Liu et al., 2014), respectively; (4) rBC MMD measured at
urban sites in Tokyo, Japan (Kondo et al., 2011b), and Sacramento, CA (Cappa
et al., 2012), were between 140 and 150 nm; (5) a laboratory study showed
that the MMD was about 125 nm for rBC cores emitted from a diesel car
(Laborde et al., 2012b); (6) a MMD of 126 nm was observed for rBC at
Cranfield Airport in the UK, attributable to aircraft engine exhausts (McMeeking
et al., 2010). Although not all of these studies determined rBC MMD and NMD
simultaneously, rBC NMD were typically in the range of ∼ 60 to
80 nm for urban emissions dominated by contributions from fossil fuel
combustion (e.g., Schwarz et al., 2008a; Kondo et al., 2011b; Metcalf et
al., 2012).
A summary of rBC MMDs representative of different types of
emission sources. The calibration material and assumed density of rBC are
also shown. The corresponding rBC NMDs are presented in parentheses when available.
Campaign information
Calibration material
Density
MMD (nm)
Reference
(g cm-3)
Urban emissions dominated by contributions from fossil fuel combustion
Airborne measurement over California, USA, in May 2010
Aquadag
1.8
122 over the Los Angeles basin (NMD ≈ 60 nm)
Metcalf et al. (2012)
Ground-based measurement downwind of Tokyo, Japan, in the summer of 2004
thermally denuded ambient soot
1.77
between 145 and 150
Shiraiwa et al. (2007)
Airborne measurement over Texas, USA, in September 2006
glassy carbon spheres
2.0
∼ 170 for urban emissions (NMD ≈ 70 nm)
Schwarz et al. (2008a)
Airborne measurement over California, USA, in June 2008
thermally denuded ambient soot
2.0
averaging 175 for urban emissions
Sahu et al. (2012)
Airborne measurement over western and northern Europe in April and May 2008
Aquadag
1.8
173 and 178 for urban outflows from Liverpool, UK, and Cabauw, Netherlands, respectively (NMD ≈ 80 nm for both cases)
McMeeking et al. (2010)
Ground-based measurement in Paris, France, during the winter of 2010
fullerene soot
1.8
∼ 100 when impacted by fresh traffic emissions
Laborde et al. (2013)
Ground-based measurement in London, UK, during the winter and summer of 2008
Aquadag
1.8
between 119 and 124 during summer when mainly impacted by traffic emissions
Liu et al. (2014)
Ground-based measurement in Tokyo, Japan, from late August to early September 2009
thermally denuded ambient soot
1.72
averaging 146, typically in the range of 130–170 (NMD averaging 64 nm)
Kondo et al. (2011b)
Ground-based measurement in Sacramento, USA, in June 2010
Aquadag
1.8
∼ 145
Cappa et al. (2012)
Near-source measurement at Cranfield Airport, UK, in September 2008
Aquadag
1.8
126
McMeeking et al. (2010)
Laboratory study for source emissions from a diesel car
fullerene soot
1.8
∼ 125
Laborde et al. (2012b)
Biomass burning emissions
Airborne measurement over Texas, USA, in September 2006
glassy carbon spheres
2.0
∼ 210 for biomass burning plumes (NMD ≈ 140 nm)
Schwarz et al. (2008a)
Airborne measurement over California, USA, in June 2008
thermally denuded ambient soot
2.0
averaging 193 for biomass burning plumes (NMD averaging 141 nm)
Sahu et al. (2012)
Airborne measurements over Canada between June and July 2008, and over the Arctic in April 2008
thermally denuded ambient soot
2.0
187 for fresh biomass burning plumes in Canada (NMD = 136 nm); 207 for aged biomass burning plumes transported from Asia to the Arctic (NMD = 141 nm)
Kondo et al. (2011a)
Airborne measurement over eastern Canada in July 2011
Aquadag
1.8
194 and 196 for two biomass burning plumes not impacted by wet deposition (NMD = 137 and 128 nm, respectively); 152 for a biomass burning plume impacted by wet deposition (NMD = 100 nm)
Taylor et al. (2014)
Aged air masses in remote areas
Ground-based measurement at a remote island in Japan during the spring of 2007
thermally denuded ambient soot
1.77
between 200 and 220 (NMD between 120 and 140 nm)
Shiraiwa et al. (2008)
Ground-based measurement at a tropospheric site in Switzerland from February to March 2007
glassy carbon spheres
1.9
∼ 200
Liu et al. (2010)
Airborne measurement over western and northern Europe in April and May 2008
Aquadag
1.8
199 over the Atlantic Ocean (NMD ≈ 90 nm)
McMeeking et al. (2010)
Airborne measurement over the remote Pacific in January 2009
fullerene soot
2.0
∼ 180 for remote atmosphere and ∼ 225 for the Arctic
Schwarz et al. (2010)
A comparison of rBC size distributions between this study and previous ones
confirms the finding that rBC cores emitted from fossil fuel combustion were
smaller in size compared to those from biomass burning (e.g., Schwarz et
al., 2008a). The rBC MMDs and NMDs measured in biomass burning plumes were
typically around 200 and 140 nm (Table 1), respectively, as
supported by airborne measurements over Texas (Schwarz et al., 2008a),
California (Sahu et al., 2012), Canada (Kondo et al., 2011a; Taylor et al.,
2014) and the Arctic (Kondo et al., 2011a). However, wet deposition could
lead to a large decrease (e.g., as much as 50 nm) in the MMD of rBC cores in
biomass burning plumes (Taylor et al., 2014), suggesting that an rBC MMD
substantially smaller than 200 nm does not exclude the possibility of
biomass burning contributions.
Different assumptions have been made by aerosol–climate models for the size
distribution of black carbon. For example, the NMD of black carbon emitted
by fossil fuel combustion were assumed to be 30, 40 and 60 nm by Dentener et al. (2006;
for AeroCom Phase I models), Heald et al. (2014; for a radiative
transfer model coupled with GEOS-Chem) and Stier et al. (2005; for the
aerosol–climate modeling system ECHAM5-HAM), respectively. According to the
SP2 measurement results on rBC, including results from the present study, a
NMD of 60 nm would be a more appropriate input parameter in the models for
black carbon emissions from fossil fuel combustion. However, there is also a
need to evaluate the unimodal assumption for black carbon size distribution
(Liggio et al., 2012; Buffaloe et al., 2014), given the SP2's limited
detection range of rBC core size.
rBC size distributions over the OS source region: time-resolved results
In addition to the facility-integrated results (Fig. 3), lognormal fits
were also applied to 2 min intervals of rBC data derived from the SP2.
Figures 4 and 5 show results from the emission flights conducted for CNRL on
26 August 2013 (i.e., F_8/26) and for SUN on 28 August 2013
(i.e., F_8/28), respectively. In both cases, the rBC mass and
number size distributions did not exhibit major temporal variations, despite
the minor fluctuations observed during F_8/28. The stable rBC
size distribution within a flight can be more readily seen from Fig. 6a,
which indicates that the rBC MMD, mass distribution width and therefore the
mass-based scaling factor (FrBC,mass) were independent of rBC
concentration. As shown in Fig. 6a and Table 2, the variations of rBC MMD,
mass distribution width and FrBC,mass were within 5 % for
F_8/26. Larger variations in rBC size distribution were
observed for F_8/28, but the variations in these three
parameters were still within 10 %. The variations of rBC NMD, number
distribution width and number-based scaling factor (FrBC,number)
were also within 10 % for both F_8/26 and F_8/28 (Table 2).
Time-resolved rBC (a) mass size distribution,
(b) number size distribution and (c) concentrations
observed over the CNRL facility during F_8/26. Solid lines in
(a) and (c) indicate MMD and NMD, respectively. The
horizontal axis shows UTC time.
Time-resolved rBC (a) mass size distribution,
(b) number size distribution and (c) concentrations
observed over the SUN facility during F_8/28. Solid lines in
(a) and (c) indicate MMD and NMD, respectively. The
horizontal axis shows UTC time. The flight track of F_8/28 is shown in
Fig. 1a.
Variations of the parameters derived from time-resolved
lognormal fits to single-particle rBC data measured during F_8/26 and F_8/28. Variations are determined as relative
standard deviations (RSDs, in percentage).
MMD
Widthmass
FrBC,mass
NMD
Widthnumber
FrBC,number
F_8/26
1.46
4.42
2.82
4.48
5.30
4.07
F_8/28
6.85
8.46
9.47
7.94
7.18
8.07
The temporal variations of rBC concentration shown in Figs. 4 and 5 were
mainly driven by the in- vs. out-of-plume differences. There was a sharp
increase in rBC concentration when the aircraft flew into a plume, whereas
the rBC concentration deceased rapidly when the aircraft left the plume.
Therefore, the stable rBC size distributions observed for the emission
flights, which were clearly independent of rBC concentration (e.g., Fig. 6a),
signify negligible difference in the rBC size distribution between the in-
and out-of-plume conditions over the OS source region. The size distribution
consistency for rBC is observed regardless of the threshold rBC
concentration used to distinguish the in- and out-of-plume conditions, which
is flight-dependent (e.g., ∼ 0.1 µg m-3 in terms of
2 min averaged rBC mass concentration for F_8/26 as shown in
Fig. S3). The implications of consistent size distributions for rBC near
the sources are further discussed in Sect. 3.3 together with results from
the transformation flights.
Dependences of (a) rBC MMD, mass distribution width
(Widthmass) and mass-based scaling factor
(FrBC,mass), and (b) photochemical age on rBC
concentration during F_8/26. Time resolution is 2 min for all the
parameters shown here. Based on the temporal variation of 2 min averaged rBC
mass concentration (Fig. S3), rBC ≤ 0.1 µg m-3 can be
used as an indicator for typical out-of-plume conditions during F_8/26.
Uncertainties introduced by lognormal fitting are within ±5 nm and
±0.06 for the time-resolved MMD and Widthmass, respectively.
(a) Time-resolved rBC mass size distribution observed
during the transformation flight F_9/4, (b) comparison of rBC mass
size distributions between typical in- and out-of-plume conditions,
(c) comparison of in-plume rBC mass size distributions among
successive flight screens, and evolutions of (d) average rBC mass
concentration and (e) photochemical age from screen 1 (S1) to screen
4 (S4). Scaling of out-of-plume rBC size distribution in (b),
scaling of rBC size distributions for screens 2 to 4 in (c), and
reason for excluding results from screen 5 in (c) to (e)
are explained in the text.
In addition to rBC concentration, the in- and out-of-plume air masses had
different photochemical ages as indicated by their values of
-log10(NOx / NOy), determined from concurrent measurements of
NOx and NOy. As shown in Fig. 6b, there was a robust negative
correlation between the rBC mass concentration and photochemical age.
Compared to the in-plume segments of a flight, the out-of-plume ones were
characterized by not only lower rBC concentrations but also older
photochemical ages. Given the clear dependence of rBC concentration on
photochemical age (Fig. 6b) and the stable rBC size distribution across
the whole rBC concentration range observed within an emission flight (Fig. 6a
and Table 2), it could be inferred that rBC size distribution was
independent of photochemical age over the OS source region.
rBC size distributions downwind of the OS source region
Mass and number size distributions of rBC are shown in Figs. 7 and 8,
respectively, for the transformation flight conducted on 4 September 2013
(i.e., F_9/4) which reached a downwind distance of
approximately 120 km (relative to the downwind edge of the OS source area;
Fig. 1b). As can be seen from the time-resolved lognormal fitting results
(Figs. 7a and 8a), both the rBC mass and number size distributions were
fairly stable during F_9/4, without major temporal change
patterns. For the typical in- and out-of-plume conditions of
F_9/4, the rBC MMDs were 143 and 142 nm with mass distribution
widths of 0.72 and 0.71, respectively (Fig. 7b); the rBC NMDs were 71 and
69 nm with number distribution widths of 0.68 and 0.69, respectively (Fig. 8b). These rBC size distributions (Figs. 7b and 8b) were derived from the
SP2 measurements performed on the various virtual screens, where the
aircraft was flown along level flight tracks (primarily at ∼ 450
and 600 m) perpendicular to the wind direction. For the level flight
tracks, the typical in- and out-of-plume conditions (i.e., segments) were
distinguished by rBC concentration (Fig. 9), i.e., the typical
out-of-plume conditions were identified by relatively low and constant rBC
concentrations whereas the typical in-plume conditions were characterized by
sharp increases in rBC concentration above the out-of-plume level. In Fig. 7b,
the rBC mass size distribution was scaled for the out-of-plume
conditions to reveal their lower rBC concentrations compared to the in-plume
conditions (Fig. 7d). When performing the scaling, the in-plume rBC size
distribution was used as a reference (i.e., kept unchanged). The
out-of-plume rBC size distribution was scaled to make the
Iout-of-plume, scaled to Iin-plume ratio equal the
rBCout-of-plume to rBCin-plume ratio, where the individual terms,
in sequence, represent the integral of the scaled out-of-plume rBC size
distribution curve, the integral of the reference in-plume rBC size
distribution curve, the average out-of-plume rBC mass concentration (54 ng m-3,
derived from Fig. 7d) and the average in-plume rBC
concentration (208 ng m-3, derived from Fig. 7d). In Fig. 8b, the
out-of-plume rBC number size distribution was scaled similarly. As can be
seen from Figs. 7b and 8b, the in- vs. out-of-plume difference was
negligible for rBC size distribution downwind of the OS region.
(a) Time-resolved rBC number size distribution observed
during the transformation flight F_9/4, (b) comparison of rBC
number size distributions between typical in- and
out-of-plume conditions, and (c) comparison of in-plume rBC number
size distributions among successive flight screens. Scaling of out-of-plume
rBC size distribution in (b) and scaling of rBC size distributions for
screens 2 to 4 in (c) are explained in the text.
Photochemical ages were older for the out-of-plume conditions compared to
the in-plume ones, by ∼ 0.3–0.5 in terms of
-log10(NOx / NOy) for different screens of F_
9/4 (Fig. 7e). Therefore, the consistent rBC size distributions between
the in- and out-of-plume conditions indicated that photochemical age had
little influence on rBC size distribution downwind of the OS region. This
conclusion was also strongly supported by the comparison of in-plume rBC
size distributions among different downwind distances. As the OS plume was
transported downwind, the in-plume rBC concentration decreased due to
dilution (Fig. 7d), from ∼ 310 ng m-3 for the first
screen (screen 1) to ∼ 110 ng m-3 for the fourth
screen (screen 4); meanwhile, the in-plume photochemical age
-log10(NOx / NOy) increased (Fig. 7e), from ∼ 0.1
for screen 1 to ∼ 0.5 for screen 4. The last
screen (screen 5) did not differ largely from screen 4 with respect
to either in-plume rBC concentration or photochemical age, appearing to
indicate that the dilution and aging processes had slowed down or even
stopped since screen 4. However, it should be noted that, unlike the
first four screens, screen 5 did not captured the full OS plume, i.e.,
the plume edges were missed. Compared to the central portion of the plume,
the plume edges had lower rBC concentrations and older photochemical ages.
Therefore, the average rBC concentration and
-log10(NOx / NOy) could not be compared directly between
screen 5 and the first four screens, and consequently, results from
screen 5 were not involved in Fig. 7d and e. Nonetheless, for all
successive screens of F_9/4, the in-plume rBC MMDs and NMDs
were found to fall into a narrow range of 140–145 and 69–72 nm,
respectively, while both the mass and number distribution widths were about
0.7 (Figs. 7c, 8c and 10). In Figs. 7c and 8c, rBC size distributions
derived from successive screens were scaled to reveal the decrease in rBC
concentration caused by dilution, using the same approach as that described
in detail for Fig. 7b. The scaling requires rBC concentration
representative for the full plume and thus was not performed for screen
5. A direct comparison of rBC size distributions between screen 5
and the first four screens is provided by Fig. 10. Figure 10 also
demonstrates consistent in-plume rBC size distributions among successive
screens for the other two transformation flights that were conducted on
19 August and 5 September 2013, respectively (i.e., F_8/19
and F_9/5), providing further solid evidence for the
negligible influence of atmospheric aging on rBC size distribution downwind
of the OS source region.
Identification of typical in- and out-of-plume conditions for two
level flight tracks at ∼ 450 and 600 m (in terms of ellipsoid height,
equivalent to ∼ 150 and 300 m above ground) on the first virtual
screen of the transformation flight F_9/4.
As shown in Table 1, previous studies conducted in remote areas (either
ground- or aircraft-based) typically showed rBC MMD between 200 and 220 nm
(Shiraiwa et al., 2008; Liu et al., 2010; McMeeking et al., 2010; Schwarz et
al., 2010), substantially higher than those observed over urban areas (e.g.,
122 nm over the Los Angeles basin; Metcalf et al., 2012) or at urban
locations (e.g., 146 nm in Tokyo, Japan; Kondo et al., 2011b). Moreover, the
rBC MMD was found to be 20 nm larger for aged urban plumes from Nagoya,
Japan, compared to fresh emissions from the same urban area (Moteki et al.,
2007). Therefore, it has been argued that rBC size distribution tends to
shift toward larger sizes during aging (e.g., McMeeking et al., 2010).
Results from the present study, especially the comparison of rBC size
distributions among successive flight screens (Fig. 10), indicate that
this is not necessarily the case. It is inferred that not all aging
processes will change rBC size distribution and instead, influences of aging
on rBC size distribution may partially depend on the presence of atmospheric
processes that can lead to increased rBC core mass and size in a single
particle (e.g., rBC coagulation and evaporation of cloud droplets containing
multiple rBC particles). In this study, it appears that no such processes
were at play, and within the photochemical ages encountered, rBC core masses
and sizes did not change.
In-plume rBC MMD and NMD (a), and mass and number
distribution widths (Widthmass and Widthnumber;
b) derived from successive flight screens of the three
transformation flights. The results are also available in Table S2.
Dependence of coating thickness (Tcoating) on rBC core
size (DMEV) for successive flight screens of the transformation
flight F_9/4. To derive the dependence, rBC-containing particles detected by
the SP2 are divided into four equal-width bins according to their core sizes
(DMEV), the centers of which are 85, 115, 145 and 175 nm,
respectively. The lower edge of the first DMEV bin is 70 nm,
corresponding to the SP2's lower detection limit of DMEV; the
upper edge of the last DMEV bin is 190 nm. The DMEV
range of 70 to 190 nm accounts for approximately 95 % of the detected
rBC cores. For each DMEV bin, the fraction of rBC cores that can
be assigned a coating thickness (Fassigned, in percentage) is
also shown.
In addition to the evolution of in-plume rBC concentration, Fig. 7d shows
that the out-of-plume rBC concentration decreased until screen 3. This
decrease was associated with an increase in -log10(NOx / NOy)
for the out-of-plume conditions (Fig. 7e). For screen 4, both the
out-of-plume rBC concentration and photochemical age were nearly the same as
the respective values observed for screen 3. Therefore, the out-of-plume
conditions identified for screens 3 and 4 should be more
representative of the background. For screens 3 and 4, rBC size
distributions agreed well between the in- and out-of-plume conditions,
within ±3 nm in terms of MMD or NMD, indicating that the background
did not differ significantly from the OS emissions with respect to rBC size
distribution. Consistent in- and out-of-plume rBC size distributions
observed at smaller downwind distances (i.e., for screens 1 and 2)
and over the OS source area (i.e., for the emission flights) pointed to the
same conclusion, although the out-of-plume conditions in these cases were
less representative of the background. The rBC cores in the background could be
from the OS emissions and/or long-range transported urban emissions that had
not been influenced by atmospheric processes that can change single-particle
rBC core size. These two kinds of emissions did not differ largely in rBC
size distribution (as discussed in Sect. 3.1) and therefore they were
difficult to further distinguish by rBC size only.
Evolution of rBC mixing state
Coating thickness (Tcoating) was found to exhibit a decreasing trend
with the increase in rBC DMEV for both the transformation (Fig. 11)
and emission flights (Fig. S4). This trend was primarily attributed to the
limitation that the detection range of Tcoating is rBC DMEV
dependent (as explained in Sect. 2.3), rather than indicating that
relatively small rBC cores were more thickly coated than larger ones.
Besides Tcoating, the fraction of rBC cores that can be assigned a
coating thickness (Fassigned, in percentage) was also rBC DMEV dependent
such that Fassigned was found to be the highest (between ∼ 35–45 %)
for rBC cores in the DMEV range of 130–160 nm (Figs. 11
and S4). The rBC-containing particles in this DMEV range were selected
for further discussions on Tcoating (their Tcoating will be
specified as T*), with a focus on the evolution of rBC mixing state as the OS
plumes were transported downwind.
As shown in Fig. 12a for the transformation flight F_9/4,
the in-plume T* exhibited an increasing trend with the increase in downwind
distance or transport time, e.g., from ∼ 22 nm for screen 1 to ∼ 41 nm for screen 4. This trend is not
surprising given the continuous formation of SOA during transport of the OS
plumes (Liggio et al., 2016). For rBC near the sources, T* was close to zero
as observed from the emission flights over the OS facilities. For example,
T* was derived at ∼ 3 nm for F_9/3 (Fig. S4).
These freshly emitted rBC cores grew a coating of ∼ 20 nm
thickness in the first hour after emission, when the OS plume was
transported from the sources in the OS facilities to the downwind edge of
the OS region.
Evolutions of (a) coating thickness for rBC cores in the
DMEV range of 130–160 nm (T*) and (b) OA-to-rBC
mass ratio (OA / rBC) during the transformation flight F_9/4. Only
median values are shown for T* and OA / rBC. Quantitative
discussions on OA / rBC have been presented elsewhere (Liggio et al.,
2016), whereas statistical results are shown in Fig. S5 for T* measured
during F_9/4 (together with T* measured during the other two
transformation flights). Evolution of coating thickness for rBC cores in the
DMEV range of 160–190 nm (Fig. S6) exhibits the same pattern as
that shown in (a). It should also be noted that the out-of-plume OA
are dominated by preexisting secondary organic aerosols formed from biogenic
precursors (Liggio et al., 2016), which do not contribute to the formation of
coating materials on rBC cores. This explains why the out-of-plume conditions
have higher OA / rBC ratios but in general lower T* compared to in
plumes.
T* were found to be comparable between the in- and out-of-plume conditions
for screen 1, which were ∼ 22 and 23 nm, respectively
(Fig. 12a). It is unlikely that the out-of-plume T* could be as low as
∼ 23 nm, if the majority of the out-of-plume rBC cores were
from long-range transport. Therefore, the rBC cores observed in the out-of-plume conditions should
also be influenced by emissions in the oil sands region, albeit at much lower
air concentrations compared to the plumes, such as from on-road traffic that
was not part of any oil sands surface mining facility.
Compared to in plumes, the increase in T* was smaller for the out-of-plume
conditions as the OS plume was further transported from screen 1 (Fig. 12a)
and moreover, the out-of-plume T* stopped increasing after screen 3
such that it was ∼ 32 nm for both screens 3 and 4. One
explanation for the different evolution patterns of the in- and out-of-plume
T*, which had comparable initial values (i.e., those for screen 1), is
the less effective formation of coating materials (e.g., SOA and sulfate)
for the out-of-plume conditions than in plumes. Coating precursors (volatile
organic compounds and sulfur dioxide) were much more abundant in the plumes,
from which fast formation of SOA was observed (Liggio et al., 2016). As
shown in Fig. 12b, the in-plume OA-to-rBC mass ratio exhibited a robust
increasing trend with the increase in downwind distance (e.g., by
∼ 150 % for screen 4 relative to screen 1), whereas
the increase in OA-to-rBC ratio was less significant for the out-of-plume
conditions (e.g., by only ∼ 45 % for screen 4 compared
to screen 1) which was negligible between screens 3 and 4.
We did not compare Tcoating measured in this study with results from
previous ones due to the following reasons. (1) The detection range of
Tcoating and therefore the estimated Tcoating depend on the SP2's
detection range of scattering intensity, which could differ among different
SP2 instruments. This dependency indicates that different SP2 instruments
might lead to different Tcoating estimates even for the same ensemble of
rBC-containing particles. (2) The detection range of Tcoating and
therefore the estimated Tcoating also depend on the rBC core size (i.e.,
DMEV). Quite different DMEV ranges have been used by previous
studies to estimate Tcoating, e.g., 190–210 nm by Schwarz et al. (2008a, b)
vs. 162–185 nm by Langridge et al. (2012), indicating that
these Tcoating estimates are not directly comparable. (3) Comparison of
the LEO and full-Gaussian fits for the determination of Doptical or
scattering amplitude, which should be done using non-rBC-containing
particles, was not presented in many previous publications reporting
Tcoating. This is a concern because the LEO fit has been considered
reliable as long as the LEO-to-full-Gaussian ratios are relatively constant
(not necessarily around 1.0) for the fitted scattering amplitudes (e.g.,
Metcalf et al., 2012). Since an agreement between the LEO and full-Gaussian
fits was not always required, previously reported Tcoating might be
biased by the LEO-induced uncertainty to different extents, adding to the
difficulties in comparing Tcoating across studies.