ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-14515-2016Morphology and mixing of black carbon particles collected in central
California during the CARES field studyMoffetRyan C.rmoffet@pacific.eduO'BrienRachel E.AlpertPeter A.https://orcid.org/0000-0002-7582-9206KellyStephen T.PhamDon Q.GillesMary K.KnopfDaniel A.https://orcid.org/0000-0001-7732-3922LaskinAlexanderhttps://orcid.org/0000-0002-7836-8417Department of Chemistry, University of the Pacific, Stockton, CA
95211, USAChemical Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, CA 94720, USAInstitute for Terrestrial and
Planetary Atmospheres, School of Marine and Atmospheric Sciences,
Stony Brook University, Stony Brook, NY 11794, USAPacific Northwest National Laboratory, W. R. Wiley Environmental
Molecular Sciences Laboratory, Richland, WA 99354, USApresent address: Department of Civil and Environmental Engineering,
Massachusetts Institute of Technology, Cambridge, MA 02139,
USApresent address: CNRS, UMR5256, IRCELYON, Institut de
Recherches sur la Catalyse et l'Environnement de Lyon,
Villeurbanne 69626, Francepresent address: Carl Zeiss X-ray
Microscopy Inc., Pleasanton, CA 94588, USARyan C. Moffet (rmoffet@pacific.edu)23November20161622145151452516July201620July201627October20162November2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/14515/2016/acp-16-14515-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/14515/2016/acp-16-14515-2016.pdf
Aerosol absorption is strongly dependent on the internal
heterogeneity (mixing state) and morphology of individual particles
containing black carbon (BC) and other non-absorbing species. Here, we
examine an extensive microscopic data set collected in the California Central
Valley during the CARES 2010 field campaign. During a period of high
photochemical activity and pollution buildup, the particle mixing state and
morphology were characterized using scanning transmission X-ray microscopy
(STXM) at the carbon K-edge. Observations of compacted BC core morphologies
and thick organic coatings at both urban and rural sites provide evidence of
the aged nature of particles, highlighting the importance of highly aged
particles at urban sites during periods of high photochemical activity. Based
on the observation of thick coatings and more convex BC inclusion morphology,
either the aging was rapid or the contribution of fresh BC emissions at the
urban site was relatively small compared to background concentrations. Most
particles were observed to have the BC inclusion close to the center of the
host. However, host particles containing inorganic rich inclusions had the BC
inclusion closer to the edge of the particle. These measurements of BC
morphology and mixing state provide important constraints for the
morphological effects on BC optical properties expected in aged urban plumes.
Introduction
Aerosols have a direct effect on climate by scattering and absorbing solar
radiation. Black carbon (BC), which results from the incomplete combustion of
hydrocarbons from a variety of fuels, absorbs solar radiation across the
visible spectrum, resulting in a warming effect (Bond et al., 2013; IPCC,
2013). BC is estimated to be the second most potent atmospheric warming
agent, with carbon dioxide being the most potent. Reducing BC emissions would
rapidly counteract the heating by greenhouse gases (Ramanathan and Xu, 2010;
Ramanathan and Feng, 2008; Rogelj et al., 2014). To predict the amount of
cooling by removing BC from the atmosphere, the direct effect due to BC must
be modeled using realistic assumptions.
(a–d) Single energy images at 278, 285.4, 288.6,
and 320 eV representing the pre-edge, C* = C sp2 carbon, C*OOH,
and total carbon. (e) Organic map produced by subtracting the image
at 278 eV from the image at 288.6 eV. (f) Inorganic map produced
by taking the ratio of the image at 278 eV to the image at 320 eV
(pre-edge: total carbon). (g) sp2 carbon map derived by
multiplying the ratio of 285.4 eV to 320 eV by a constant to give the
percentage of sp2 bonds as described in Hopkins et al. (2007).
(h) Combined maps derived from thresholding of maps;
(e)–(g) red areas contain
% sp2 > 35 %, green areas are organic
dominant, and blue areas are
non-carbonaceous inorganic dominant.
Because of the insufficient knowledge of particle morphology, mixing state,
and interactions with other atmospheric constituents, the radiative effect of
BC is uncertain. Radiative transfer models require knowledge about scattering
and absorption cross sections and the angular dependence (phase function) of
scattered light. Estimates of these parameters are obtained using Mie theory,
which assumes particles are homogenous spheres. However, aerosols containing
BC are frequently internally mixed. Hence, within the same particle, the BC
is heterogeneously mixed with non-absorbing species (Adachi and Buseck, 2008;
Moffet et al., 2013). To address the heterogeneous particle structure, the BC
has been modeled as a centrally located sphere evenly coated by non-absorbing
material (Ackerman and Toon, 1981). Implementing this type of core shell
theory in global modeling studies suggests a large warming due to the
internal mixing of BC (Jacobson, 2001). Numerous recent studies indicate that
assuming that the BC is located exactly in the center of the particle
overestimates BC absorption (Adachi et al., 2007; Cappa et al., 2012).
Several studies point out that a lower BC absorption is obtained by
offsetting the BC inclusion from the center towards the particle edge; recent
field studies confirm that the core-shell model may not be valid and that
other modeling approaches are needed (Cappa et al., 2012; China et al.,
2013). Alternate approaches include the Maxwell Garnett approximation as well
as the discrete dipole approximation (DDA; Scarnato et al., 2013). The
Maxwell Garnett is an “effective medium” approximation whereby an effective
dielectric constant is calculated using the dielectric constants of the host
and the inclusion. Effective medium approaches still use Mie theory to
generate cross sections and phase functions. Alternatively, DDA uses an array
of dipoles with prescribed optical properties to calculate cross sections and
phase functions. If enough dipoles are used with DDA, the calculation
theoretically becomes exact but is computationally expensive. To test the
validity of these theoretical approaches to calculating aerosol radiative
properties, detailed morphological and chemical measurements are required at
the individual particle level.
In this study, scanning transmission X-ray microscopy (STXM) is used to
quantify the morphology and mixing state of BC containing particles collected
from the Carbonaceous Aerosols and Radiative Effects Study (CARES). During
the June 2010 CARES study, a comprehensive set of aerosol, gas, and
meteorological parameters was measured (Moffet et al., 2013; Zaveri et al.,
2012; Fast et al., 2012). The CARES field study focused on the chemical and
physical properties of organic carbon and BC containing particles, and
several reports have examined the characteristics of BC particles (Cappa et
al., 2012; Cahill et al., 2012; Cazorla et al., 2013; Chakrabarty et al.,
2014). Thus far, none report direct measurements of the chemical and
morphological properties for a statistically significant number of BC
particles. This report presents a microscopic analysis for a large number of
BC particles (∼ 1900 BC containing particles out of a data set
containing ∼ 20 000 particles) collected during selected dates of the
CARES field campaign. This manuscript utilizes and builds upon the data
set presented in two earlier studies (Moffet et al., 2013; O'Brien et al.,
2015). Results presented here can be used to validate assumptions employed in
optical and radiative transfer models.
Experimental
Samples of atmospheric particles were collected during the CARES campaign
conducted in June 2010 in Central Valley, California. Field sites and
sampling procedures are described in previous publications (Moffet et al.,
2013; Zaveri et al., 2012) and are only briefly described here. Sampling
occurred at two primary field sites: the first site was in the Sacramento
urban area (T0 site) expected to have enhanced fresh emissions, and the
second site was located 40 km east of T0 in the Sierra Nevada foothills (T1
site) expected to have enhanced aged aerosol. Samples utilized here were
collected over 2 days (27 and 28 June) during a period of high temperatures
and increased aerosol loadings over T0 due to high photochemical activity. CO
tracer modeling indicated that significant transport from the San Francisco
Bay Area affected the Sacramento site in the morning while the boundary layer
was low. Later on in the day a larger fraction of emission at the T0 site was
from the Sacramento metropolitan area. Similar contributions from the San
Francisco Bay Area were modeled at T1; however, emissions from Sacramento
constituted the largest source of emissions during this time period (Moffet
et al., 2013; Fast et al., 2014). Aerosols were collected onto several
substrates, including Si wafers for ice nucleation studies (Knopf et al.,
2014), Si wafers containing Si3N4 membrane windows (Moffet et al.,
2013), and Formvar/carbon type B coated copper grids (Ted Pella, Redding, CA)
using a time resolved aerosol collector (TRAC) (Laskin et al., 2003, 2006).
After collection, the samples were sealed and stored at ambient temperature
(∼ 21 ∘C) and relative humidity (∼ 50 %). Sealing
the samples prevented additional exposure to light and moisture.
Cropped composition maps for all BC containing particles identified
in CARES samples collected at T0 (top) and T1 (bottom). The submicron (left
panels) particles are separated from the supermicron particles (right
panels).
Summary of all particles analyzed from the CARES STXM data set.
Green bars represent particles only containing the OC rich phase, black bars
indicate particles containing BC and OC, red indicates the fraction of
particles containing OC, BC, and IN, and blue bars indicate the fraction of
particles containing an inorganic dominant phase (IN). Orange dots indicate
the total number of BC particles analyzed from a particular sample. The total
number (N) of particles analyzed in each sample is indicated on the top of
the figure.
STXM analysis was performed continuously from 2010 to 2015 at Lawrence
Berkeley National Laboratory's (LBNL) Advanced Light Source (ALS) at beamline
5.3.2.2 described in detail elsewhere (Kilcoyne et al., 2003). The STXM
instrument provides raw images with photon counts representing pixel
intensities. The pixel intensities are converted to optical density (OD) by
the relation lnII0=-μρt where I0 and I are the
photon counts for particle-free and particle-containing regions of the image,
respectively, μ is the mass absorption coefficient, ρ is the
material density, and t is the particle thickness. MATLAB algorithms
described originally in an earlier publication (Moffet et al., 2010) were
used to identify the regions of an aerosol containing BC, organic carbon, and
inorganic species. However, the mapping algorithms implemented here utilized
only four images at different photon energies. Mapping with four images
decreases analysis time, allowing for higher throughput and, thus, analysis
of a larger population of particles. To generate a carbon based map, aerosol
particles were imaged at 278 eV (the carbon pre-edge), 285.4 eV
(sp2 C* = C), 288.6 eV (C*OOH), and 320 eV (the carbon
post-edge). Characteristic single energy images at these energies are shown
in Fig. 1a–d. Typically, at each energy, a
15 × 15 µm2 image was acquired with
0.035 µm pixel size and 1 ms dwell time. Occasionally, ∼ 120
different constant energy images were utilized in this study to obtain a
high-resolution carbon spectrum. For consistency, the same set of four
constant energy images was used to classify particles in spectral images
acquired containing both 120 and 4 energy points.
Maps derived from these four images are shown in Fig. 1e–g. To map
“organic” regions, the difference between the carboxylic transition (C*OOH, 288.6 eV)
and the pre-edge of carbon is used and the resulting map is shown in Fig. 1e.
The inorganic map, representing non-carbonaceous inorganic dominant regions,
is derived from the ratio of the pre-edge (278 eV) to the post-edge
(320 eV) ratio (ODpre/ ODpost) and is shown in
Fig. 1f. Non-carbonaceous, inorganic inclusions of (NH4)2SO4 and
NaCl were confirmed using energy dispersive X-ray spectroscopy for these
CARES samples (Moffet et al., 2013). BC is mapped by normalizing the
C* = C sp2 hybridized carbon peak at 285.4 eV to the post-edge
absorbance at 320 eV. This ratio is then scaled with respect to highly
oriented pyrolitic graphite (HOPG) enabling calculation of the sp2
hybridization fraction (Hopkins et al., 2007):
%sp2=OD(285.4eV)OD(320)×OD(320)HOPGOD(285.4)HOPG.
BC particles, which mostly consist of elemental carbon, are expected to have
a high % sp2 and appear as bright areas in Fig. 1g. This paper
focuses on quantifying the morphology of particles containing these high
% sp2 regions which are defined as BC.
To define organic carbon rich (OC), inorganic non-carbonaceous rich (IN), and
black carbon (BC) regions, thresholds for each of the three maps in
Fig. 1e–g were set using the following criteria: (1) pixels at 288.6 eV
with intensities 3 times below the signal to noise ratio were set to zero;
(2) pixels having ODpre/ ODpost < 0.5 were
set to zero as discussed in Moffet et al. (2010); and (3) the % sp2
was set to zero below a value of 35 %. The empirical determination of the
threshold value of 35 % is discussed elsewhere (Moffet et al., 2011).
Areas of each of the maps with fewer than 7 conjoined pixels were excluded.
Thresholds for maps in Fig. 1e–g were applied to produce binary images. In
Fig. 1h, to highlight the BC mixing state, these three binary images are
overlaid in the following order: organic, inorganic, sp2.
Morphological information for the compositional regions of interest
(inclusion center of mass, convexity, area) was
obtained using the MATLAB image processing toolbox and other custom-written
algorithms. Particles not completely captured by the image were not included
in the analysis. Individual particle maps were cropped and stored for
interactive and query based plotting. Interactive single particle maps were
utilized for quality control of the data and to exclude particles that were
misidentified as BC. For the interactive visualization, all of the particles
within a user-defined subset are displayed. Individual particles are selected
via a graphical user interface. Upon selection, the raw data for that
particular data set are activated to allow further scrutiny of the data.
Occasionally, visual inspection indicated particles may have been
misclassified. These particles were omitted from the analysis. Specific
biological particle types were identified erroneously as BC and were excluded
from the data set based on their morphology and/or spectral characteristics.
Additionally, small nominally pure BC particles were occasionally
unidentified due to the specifics of the initial particle detection methods.
Another problem area for the identification of BC particles is regions close
to inorganic inclusions due to high background levels caused by
non-carbonaceous species. MATLAB routines packaged as an application are
available at
https://www.mathworks.com/matlabcentral/fileexchange/58259-stxm-particleanalysis2-gui.
ResultsBC mixing state
X-ray spectromicroscopy is one of the few techniques that use chemical
markers for imaging the internal structures of BC containing particles.
Figure 1 shows a typical field of view for samples collected during the CARES
campaign. The BC map in Fig. 1g and h demonstrates a variety of BC morphology
including large, fractal particles, large compact particles, and small
compact particles. BC particles were internally mixed with inorganic and
organic material. For example, the large fractal BC particle (particle 1,
Fig. 1g and h) has a small compact inorganic inclusion on its upper extremity
and is surrounded by organic carbon. Other BC containing particles have small
compact BC inclusions located towards the center of the particle (particles 3
and 4). Some of the small BC inclusions are surrounded by mostly organic
material (particle 4), whereas other small compact BC particles are
surrounded by inorganic materials (particles 5 and 6). The organic map shown
in Fig. 1e demonstrates that there are organic coatings surrounding most of
the particles. Furthermore, the branched BC particle shows considerable
intensity in the organic (C*OOH). The magnitude of the ratio of the pre-edge to the post-edge is
proportional to the total mass of non-carbonaceous inorganic species.
Inorganic inclusions appear as regions of high intensity in Fig. 1f or blue
areas in Fig. 1h. Sea salt particles are common in the region and, based on
their cubic morphology, the larger particles containing inorganic regions are
likely sea salt. Smaller particles having inorganic dominant regions likely
contain sulfate (Moffet et al., 2013).
Based on these maps, the mixing state of the particles was stored in a
database for the subsequent analysis of BC morphology. The label based mixing
state is defined from particles having OC, BC, or IN regions defined by the
binary maps shown in Fig. 1h. For example, if a particle contains both
organic and black carbon regions it is labeled OCBC and so on. Figure 2 shows
cropped single particle maps for all BC particles utilized in this study
separated by the sampling site and size (submicron and supermicron). The most
striking difference between BC particles from T0 and T1 is the high number of
inorganic dominant regions for T0 particles. T0 was impacted by sea spray and
sulfates from petroleum refineries located in the San Francisco Bay Area
(Laskin et al., 2012). The large inorganic dominant particles can be
attributed to sea spray particles that have coagulated with BC emissions from
the Bay Area. Many of the smaller inorganic dominant particles are likely
agglomerates of BC and sulfates. Indeed, many of the inorganic regions for
submicron particles have elongated inorganic regions which are consistent
with the crystalline structure of ammonium sulfate (Li et al., 2003).
Frequently, BC inclusions were seen on the outside edge of an inorganic
dominant region; this arrangement may have occurred upon efflorescence, when
a salt excludes the aqueous phase (Liu et al., 2008). At T1, the majority of
the BC containing particles included a larger fraction of organic dominant
regions as a result of the increased photochemical age and large availability
of secondary organic aerosol precursors in the foothills of the Sierra Nevada
(Moffet et al., 2013).
(a) Size distribution of BC containing particles at T0
(blue) and T1 (green). (b) Size distribution of BC inclusions at T0
(blue) and T1 (green).
A small portion of particles contained more than a single BC inclusion. In
some cases, the identification of more than one BC inclusion was determined
to be an artifact of the automated analysis used in the identification of the
BC inclusions. However, in many cases, larger particles tend to be associated
with more than one BC inclusion per particle, as confirmed manually with an
interactive version of Fig. 2. Few studies have examined the radiative
effects of particles containing multiple BC inclusions. Others (Jacobson,
2006) have commented that as hydrometeors (cloud and precipitation particles)
evaporate, the non-volatile BC inclusions coalesce. While submicron aerosol
may not be necessarily identical to hydrometers discussed in that study, it
is expected that the behavior upon evaporation will be similar. Here, some
particle images show that the BC inclusions are separated by inorganic
(presumably crystalline) dominant regions.
For the entire particle population, particle mixing states and the fraction
of BC particles were characterized for each sampling time as indicated in
Fig. 3. Figure 3 shows the number of particles analyzed and the fraction of
those particles with a particular mixing state. Based on the individual
particle maps, OCBC and OCBCIN particles were distinguished from OC and INOC
particle types. Overall, the major difference between T0 and T1 is the larger
abundance of nominally pure homogenous organic particles at T1. As seen in
Fig. 2, BC particles at T1 are more frequently mixed with the OC phase rather
than with the IN phase. Generally, as the number of nominally pure OC
particles increased, the OCBC particle type increased (r=+0.50,
r2= 0.25). Additionally, as the IN particle type increased, the OCBCIN
particle type increased (r=+ 0.79, r2= 0.62). As can be
qualitatively seen in Fig. 2, most of the carbon mass likely comes from the
particle BC component. This observation is supported by the mass based
carbonaceous mixing state of a smaller subset of these data parameterized
using mass based entropy metrics (O'Brien et al., 2015; Riemer and West,
2013). In O'Brien et al. (2015), entropy metrics were used to calculate a
diversity that represents the effective number of species per particle or in
the bulk population. In this case diversities were specified using the OC,
BC, and IN components such that a particle or population can have a maximum
diversity of 3. Generally, due to the dense nature of the BC, emission of BC
particles controls trends in the overall mass based carbonaceous mixing
state. Given that the average individual particle diversity did not increase
with the bulk population diversity, the BC containing particles are
considered to be externally mixed with respect to the carbonaceous mixing
state defined using STXM measurements (O'Brien et al., 2015). Nevertheless,
the majority of BC containing particles are associated with other species.
Because the size and morphological characteristics of the OC and IN phases
within the BC particles are expected to impact the optical properties of the
particles, those properties are quantified here.
Histograms of BC inclusion convexity for the T0 and T1 sites.
(a) Distributions of the ratio of the BC inclusion diameter
to the total particle diameter (DBC/Dtotal) after
transmission efficiency correction. Images shown above the plot are examples
of particles having (from left to right)
0.1 < DBC/Dtotal < 0.25,
0.4 < DBC/Dtotal < 0.6, and
0.8 < DBC/Dtotal < 1.0.
(b, c) Two-dimensional histograms showing the number of
particles having a total diameter Dtotal and a BC core diameter
DBC for T0 (c) and T1 (b). White lines indicate
1:1 ratios.
Size and shape characteristics
For internally mixed BC particles, both the size of the BC inclusion and the
overall size of particle have the greatest influence on the light extinction
(Moffet and Prather, 2009). Most importantly, the absorption cross
section is driven largely by the size of the BC inclusion. To provide a best
estimate of the BC inclusion size distribution and overall particle size
distributions, the identified BC areas were used to calculate a circular
equivalent diameter (Deqiv=2Aroiπ), where
Aroi is the area of the region of interest (ROI) identified by the
mapping described above. Figure 4a shows the total host particle size
characteristics of BC containing particles sampled at T0 and T1 scaled by
the transmission efficiency of the impactor (see Supplement).
These characteristics are similar, but there are small differences that may
be due to particle aging. Compared to T0, the total particle distribution
for T1 shows a significantly higher population of larger particles. This
result is expected considering that the T0 site is located in a source
region for freshly emitted BC particles. Due to growth by condensation of
organic material, larger particle sizes are also expected at T1.
Distributions from both sites show enhanced numbers in the droplet mode
(∼ 200–1000 nm). The transmission efficiency curve shown in
Fig. S1 in the Supplement systematically overestimates the transmission for particles below
300 nm. Size distributions obtained using a scanning mobility particle sizer
show much higher populations below ∼ 100 nm, falling off more
sharply than the total particle size distributions obtained here (Zaveri
et al., 2012). Nevertheless, the influence of coating on the particles is
apparent; we attribute the coating to the condensation of organic material
on BC particles at the T1 site where particles are expected to be more aged.
The single scattering albedo of BC particles is highly sensitive to the size
of the BC inclusion (Moffet and Prather, 2009). The fact that BC inclusion
sizes at T0 and T1 are similar with only minor differences (Fig. 4b) suggests
that restructuring of the particles to more compact shapes upon transport is
negligible. Previous studies have implied that as BC particles age, the
morphology changes from a branched, fractal morphology to a more compact
morphology (Mikhailov et al., 2006; Huang et al., 1994; Ramachandran and
Reist, 1995; Weingartner et al., 1997; Martins et al., 1998). As the freshly
emitted fractal particles absorb liquid water due to the presence of
hygroscopic species and become coated with organic material, capillary forces
act to collapse the chain-like fractal particles. It is probable that most of
the particles sampled during CARES are substantially aged and/or that the
aging time (and subsequent collapse into compact shapes) is rapid. To
quantify the extent of particle compaction between T0 and T1, particle
convexity (convexity =AACvxHull, where ACvxHull
is the area of the convex hull around the particle area A) was calculated for
the BC inclusions and is shown in Fig. 5. Convexity distributions for
inclusions from T0 and T1 are similar, with the exception of a slightly
higher number of inclusions with lower convexities at T0. Inclusions that are
more branched have lower values of convexity (Coz and Leck, 2011); hence, the
presence of more particles with lower convexities is consistent with the
presence of fresh emissions at T0. It is possible that the resolution of the
STXM instrument limits the ability to identify small (< 100 nm)
branched/fractal inclusions. However, even freshly emitted diesel soot
particles become more compact at smaller sizes (Park et al., 2004). Moreover,
monomer size tends to be around 40 nm, which should be detectable by the
STXM instrument. The monomers of BC aggregates are typically connected in
order to form a branched, fractal particle, resulting in the observation that
only larger particles have a high fractal dimension. Nevertheless, comparison
of the convexity distributions between T0 and T1 indicates a small
statistically significant population of less compact particles at T0
consistent with fresh emissions. However, it should be emphasized that the
majority of particles at both sites have compact shapes and are likely due to
the prevalence of aged BC containing particles.
To compare the distribution of coating thicknesses at T0 and T1, the ratio of
the BC core diameter (DBC) to the total particle diameter
(DTotal) was binned, scaled by the transmission efficiency, and
displayed in Fig. 6a. Particles with thin coatings have
DBC/DTotal approaching 1, whereas particles with
thick coatings have DBC/DTotal approaching 0. The
T0 site shows a slightly enhanced mode of thinly coated particles compared to
T1, indicating the presence of fresh BC emissions at the T0 site. This mode
of thinly coated particles follows the 1:1 line in the two-dimensional
histogram in Fig. 6c. In a separate study, Bond et al. analyzed the various
regions of the Dtotal vs. DBC space (shown in Fig. 6b–c)
and found that particles that follow the 1:1 line are expected to have
lower absorption amplifications compared to particles having thicker coatings
(Bond et al., 2006). The majority of particles at both sites have thicker
coatings; based on previous modeling studies these particles are expected to
have larger absorption cross sections (Scarnato et al., 2013). As observed in
other studies with stagnant regional air masses (Moffet and Prather, 2009;
Moffet et al., 2008), these results highlight the predominance of particles
with thick coatings in urban areas with similar meteorological conditions.
For the CARES study, the source of these particles may be background
transport from the neighboring industrial areas such as the San Francisco Bay
Area.
Location of BC inclusions within host particles
The location of BC inclusions within the particle affects the optical
properties of the particle (Fuller et al., 1999). A previous investigation
associated with the CARES study found lower than expected absorption
enhancements, possibly due to the location of the BC inclusions on the edge
of the particles (Cappa et al., 2012). Figure 7 shows the distribution of
locations of the BC inclusions within their host particle for T0 and T1. To
enable comparison of particles between all sizes, the distance
(Rinc) of the BC inclusion center from the host particle center was
normalized by the the longest distance (Rmax) between the host
particle center and the host particle edge (see the graphic illustration in
Fig. 7). In this case, a ratio of Rinc/Rmax= 1
corresponds to the longest distance of the BC inclusion from the particle
center. Analysis of particles from two sampling sites showed minor
differences in the locations of the BC inclusions within host particles,
suggesting that the distribution of BC inclusions does not vary substantially
between the urban (T0) and rural (T1) sampling sites. Slightly more BC
inclusions are found closer to the edge of the host at T0. This is likely due
to the higher frequency of inorganic inclusions at T0; the crystalline
inorganic phase is thought to push the BC inclusions away from the center
upon efflorescence. Moreover, BC particles may more easily mix with the OC
phase when the particle is in the dry state. The bottom panel of Fig. 7
demonstrates that particles containing inorganic rich phases (OCBCIN
particles) have an enhanced number of particles with the BC inclusion near
the edge of the host; this trend is enhanced when particles with large
(500 nm) inorganic inclusions are considered. These results demonstrate that
the majority of the BC inclusions were found in the center of their impacted
host particle at both sites and that the presence of inorganic dominant
inclusions acts to push the BC inclusion farther from the center of the host.
(Top) Distance of the BC inclusions from the center to the host
particle for the CARES field study at the T0 (black) or T1 (green) sites. The
distance of the BC inclusion (Rinc) is normalized to the distance
from the particle center of mass to the farthest edge (Rmax) (see
illustration above plot). Modeled locations of BC inclusions are shown
assuming the inclusion was on the surface (blue) or randomly within the host
particle (magenta) before impaction. (Bottom) Distance of BC inclusion from
the host center for all BC containing particles (black), OCBCIN particles,
and particles containing inorganic inclusions (IN) having a geometric
diameter larger than 500 nm.
Of note, interpreting Fig. 7 may be biased because the distribution depends
on the orientation of the BC inclusion shortly before impaction. For example,
a BC inclusion can be attached to the outside of the host particle at its
lowest vertical coordinate (the bottom of the host). When impacted, the
two-dimensional image of the particle with the BC inclusion would appear to
be at the center even though it was attached to the outside of the host
particle. To explain the distributions in Fig. 7 with respect to BC inclusion
orientation, a model was constructed where the BC inclusion is positioned on
or within spherical host (see the supplementary section). From this model,
calculated distributions of the BC inclusion location were derived assuming
the particle was randomly distributed either on the surface or within the
volume of the host. Figure 7 demonstrates that the BC inclusions are
preferentially located at the host center compared to the modeled
distributions. Figure S3 demonstrates that if we change Rmax to be
the radius of the largest circle inscribing the host particle, the BC
inclusions measured near the center are still enhanced compared to the
modeled distributions in Fig. 7. The modeled distributions may underpredict
the number of BC inclusions in the center of the impacted host particle
because (1) the BC inclusion is “pinned” to the surface, while the host
particle material spreads away from it, or (2) the BC inclusion is
preferentially located at the host particle center due to the condensation of
organic and inorganic material around the host particle in the atmosphere. To
address point 1, a more detailed model of the particle impaction process is
required. Specifically, the phase of the organic and inorganic material must
be considered. If the inorganic/organic phase of the particles is liquid, it
is possible that the impaction process can be modeled using computational
fluid dynamics. However, there has recently been a body of research
indicating that the organic material that frequently hosts BC inclusions may
have a high viscosity and thus resist spreading (Booth et al., 2014; O'Brien
et al., 2014). Based on the analysis presented here, overall our data support
a coating model where the centrally located BC inclusion is covered by
non-absorbing material. Such coated BC inclusions will have higher absorption
than particles that are on the surface of the non-absorbing host.
Conclusions
The statistical analysis presented here represents the state of BC containing
particles at source (T0) and receptor (T1) sites in the California Central
Valley during a period of high photochemical activity and pollution buildup.
During this period, the overall particle size at the receptor site was
significantly larger due to the condensation of organic and inorganic
species. The BC inclusion sizes between the T0 and T1 sites showed no
detectable differences. The absorption efficiency of BC containing particles
is strongly dependent on the size of the BC inclusions. Hence, measurements
such as these in other geographical locations are important to understand the
radiative impact of particles.
The extent of coating on individual particles was quantified by calculating
the ratios of the BC inclusion area equivalent diameter to the host area
equivalent diameter. The T0 site had a small population of thinly coated
particles compared to the T1 site. This is consistent with slightly smaller
overall particle sizes at T0 and the assumption that BC at the source site
(T0) should have thinner coatings due to the presence of fresh BC emissions.
The majority of the BC containing particles at both sites had thick coatings
indicative of aged background particles. The high abundance of aged
particles is consistent with the stagnant pollution plume present over the
sampling site during this period. To model radiative transfer in aged urban
pollution, particle-resolved measurements, such as those presented in this
study, are valuable for characterization of the morphological properties and
relative populations of aged vs. fresh emissions.
Previous particle resolved measurements of BC containing particles from the
CARES campaign have highlighted the effects of BC inclusion/host geometry on
absorption. Here, the location of the BC inclusions within the particles
attached to the substrate was characterized. Using a model of particle
impaction, it was shown that the BC inclusions were not all located at the
center, nor were they all likely to be located on the surface of the
particle prior to impaction. Particles containing inorganic rich inclusions
were more likely to have the BC inclusion pushed towards the edge of the
host. To improve our understanding of the location of the BC inclusion
within the impacted particle, more accurate models of particle impaction and
spreading are needed in future studies.
Data availability
The data for this article are available upon request to the corresponding author.
The Supplement related to this article is available online at doi:10.5194/acp-16-14515-2016-supplement.
Acknowledgements
Funding for sample collection during the CARES study was provided by the
Atmospheric Radiation Measurement Program sponsored by the US Department of
Energy (DOE), Office of Science, Office of Biological and Environmental
Research (OBER), Climate and Environmental Sciences Division (CESD). Funding
for the data analysis was provided by the US DOE's Atmospheric System
Research Program, BER under grants DE-SC0008643 and DE-SC0008613. The STXM/NEXAFS particle
analysis was performed at beamlines 11.0.2 and 5.3.2 at the Advanced Light
Source (ALS) at Lawrence Berkeley National Laboratory. The work at the ALS
was supported by the Director, Office of Science, Office of Basic Energy
Sciences, of the US DOE under contract DE-AC02-05CH11231. We thank
A. L. D. Kilcoyne and T. Tyliszczak for their assistance with STXM
experiments. Edited by: R.
Sullivan Reviewed by: two anonymous referees
References
Ackerman, T. P. and Toon, O. B.: Absorption of Visible Radiation in
Atmosphere Containing Mixtures of Absorbing and Non-Absorbing Particles,
Appl. Opt., 20, 3661–3668, 1981.Adachi, K., Chung, S. H., Friedrich, H., and Buseck, P. R.: Fractal
parameters of individual soot particles determined using electron
tomography: Implications for optical properties, J. Geophys. Res.-Atmos., 112,
D14202, 10.1029/2006jd008296, 2007.Adachi, K. and Buseck, P. R.: Internally mixed soot, sulfates, and organic matter in aerosol particles from Mexico City,
Atmos. Chem. Phys., 8, 6469–6481, 10.5194/acp-8-6469-2008, 2008.Bond, T. C., Habib, G., and Bergstrom, R. W.: Limitations in the enhancement
of visible light absorption due to mixing state, J. Geophys. Res.-Atmos., 111,
D20211, 10.1029/2006JD007315, 2006.Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T.,
DeAngelo, B. J., Flanner, M. G., Ghan, S., Karcher, B., Koch, D., Kinne, S.,
Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M.,
Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K.,
Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U.,
Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C.
S.: Bounding the role of black carbon in the climate system: A scientific
assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, 10.1002/Jgrd.50171,
2013.Booth, A. M., Murphy, B., Riipinen, I., Percival, C. J., and Topping, D. O.:
Connecting Bulk Viscosity Measurements to Kinetic Limitations on Attaining
Equilibrium for a Model Aerosol Composition, Environ. Sci. Technol., 48,
9298–9305, 10.1021/Es501705c, 2014.Cahill, J. F., Suski, K., Seinfeld, J. H., Zaveri, R. A., and Prather, K. A.: The mixing state of
carbonaceous aerosol particles in northern and southern California measured during CARES and CalNex 2010,
Atmos. Chem. Phys., 12, 10989–11002, 10.5194/acp-12-10989-2012, 2012.Cappa, C. D., Onasch, T. B., Massoli, P., Worsnop, D. R., Bates, T. S.,
Cross, E. S., Davidovits, P., Hakala, J., Hayden, K. L., Jobson, B. T.,
Kolesar, K. R., Lack, D. A., Lerner, B. M., Li, S. M., Mellon, D., Nuaaman,
I., Olfert, J. S., Petaja, T., Quinn, P. K., Song, C., Subramanian, R.,
Williams, E. J., and Zaveri, R. A.: Radiative Absorption Enhancements Due to
the Mixing State of Atmospheric Black Carbon, Science, 337, 1078–1081,
10.1126/science.1223447, 2012.Cazorla, A., Bahadur, R., Suski, K. J., Cahill, J. F., Chand, D., Schmid, B., Ramanathan, V., and Prather, K. A.:
Relating aerosol absorption due to soot, organic carbon, and dust to emission sources determined from in-situ chemical
measurements, Atmos. Chem. Phys., 13, 9337–9350, 10.5194/acp-13-9337-2013, 2013.Chakrabarty, R. K., Beres, N. D., Moosmuller, H., China, S., Mazzoleni, C.,
Dubey, M. K., Liu, L., and Mishchenko, M. I.: Soot superaggregates from
flaming wildfires and their direct radiative forcing, Sci. Rep.-UK, 4, 5508,
10.1038/Srep05508, 2014.China, S., Mazzoleni, C., Gorkowski, K., Aiken, A. C., and Dubey, M. K.:
Morphology and mixing state of individual freshly emitted wildfire
carbonaceous particles, Nat. Commun., 4, 2122, 10.1038/Ncomms3122, 2013.Coz, E. and Leck, C.: Morphology and state of mixture of atmospheric soot
aggregates during the winter season over Southern Asia-a quantitative
approach, Tellus B, 63, 107–116, 10.1111/j.1600-0889.2010.00513.x, 2011.Fast, J. D., Gustafson Jr., W. I., Berg, L. K., Shaw, W. J., Pekour, M., Shrivastava, M., Barnard, J. C.,
Ferrare, R. A., Hostetler, C. A., Hair, J. A., Erickson, M., Jobson, B. T., Flowers, B., Dubey, M. K.,
Springston, S., Pierce, R. B., Dolislager, L., Pederson, J., and Zaveri, R. A.: Transport and mixing
patterns over Central California during the carbonaceous aerosol and radiative effects study (CARES),
Atmos. Chem. Phys., 12, 1759–1783, 10.5194/acp-12-1759-2012, 2012.Fast, J. D., Allan, J., Bahreini, R., Craven, J., Emmons, L., Ferrare, R., Hayes, P. L., Hodzic, A., Holloway, J.,
Hostetler, C., Jimenez, J. L., Jonsson, H., Liu, S., Liu, Y., Metcalf, A., Middlebrook, A., Nowak, J., Pekour, M.,
Perring, A., Russell, L., Sedlacek, A., Seinfeld, J., Setyan, A., Shilling, J., Shrivastava, M., Springston, S., Song, C.,
Subramanian, R., Taylor, J. W., Vinoj, V., Yang, Q., Zaveri, R. A., and Zhang, Q.: Modeling regional aerosol and aerosol
precursor variability over California and its sensitivity to emissions and long-range transport during the 2010
CalNex and CARES campaigns, Atmos. Chem. Phys., 14, 10013–10060, 10.5194/acp-14-10013-2014, 2014.
Fuller, K. A., Malm, W. C., and Kreidenweis, S. M.: Effects of mixing on
extinction by carbonaceous particles, J. Geophys. Res.-Atmos., 104, 15941–15954,
1999.Hopkins, R. J., Tivanski, A. V., Marten, B. D., and Gilles, M. K.: Chemical
bonding and structure of black carbon reference materials and individual
carbonaceous atmospheric aerosols, J. Aerosol. Sci., 38, 573–591,
10.1016/j.jaerosci.2007.03.009, 2007.Huang, P. F., Turpin, B. J., Pipho, M. J., Kittelson, D. B., and Mcmurry, P.
H.: Effects of Water Condensation and Evaporation on Diesel
Chain-Agglomerate Morphology, J. Aerosol. Sci., 25, 447–459,
10.1016/0021-8502(94)90063-9, 1994.
IPCC: Climate Change 2013: The Physical Science Basis, Cambridge, United
Kingdom and New York, NY, USA, 996, 2013.
Jacobson, M. Z.: Strong radiative heating due to the mixing state of black
carbon in atmospheric aerosols, Nature, 409, 695–697, 2001.Jacobson, M. Z.: Effects of externally-through-internally-mixed soot
inclusions within clouds and precipitation on global climate, J. Phys. Chem. A,
110, 6860–6873, 10.1021/jp056391r, 2006.
Kilcoyne, A. L. D., Tyliszczak, T., Steele, W. F., Fakra, S., Hitchcock, P.,
Franck, K., Anderson, E., Harteneck, B., Rightor, E. G., Mitchell, G. E.,
Hitchcock, A. P., Yang, L., Warwick, T., and Ade, H.:
Interferometer-controlled scanning transmission X-ray microscopes at the
Advanced Light Source, J. Synchrotron Radiat., 10, 125–136, 2003.Knopf, D. A., Alpert, P. A., Wang, B., O'Brien, R. E., Kelly, S. T., Laskin,
A., Gilles, M. K., and Moffet, R.: Microspectroscopic imaging and
characterization of individually identified ice nucleating particles from a
case field study, J. Geophys. Res.-Atmos., 119, 10365–10381, 10.1002/2014JD021866, 2014.
Laskin, A., Iedema, M. J., and Cowin, J. P.: Time-resolved aerosol collector
for CCSEM/EDX single-particle analysis, Aerosol Sci. Technol., 37, 246–260, 2003.
Laskin, A., Cowin, J. P., and Iedema, M. J.: Analysis of individual
environmental particles using modern methods of electron microscopy and
X-ray microanalysis, J. Electron. Spectrosc., 150, 260–274, 2006.Laskin, A., Moffet, R. C., Gilles, M. K., Fast, J. D., Zaveri, R. A., Wang,
B. B., Nigge, P., and Shutthanandan, J.: Tropospheric chemistry of
internally mixed sea salt and organic particles: Surprising reactivity of
NaCl with weak organic acids, J. Geophys. Res.-Atmos., 117, D15302,
10.1029/2012jd017743, 2012.Li, J., Posfai, M., Hobbs, P. V., and Buseck, P. R.: Individual aerosol
particles from biomass burning in southern Africa: 2, Compositions and aging
of inorganic particles, J. Geophys. Res.-Atmos., 108, 8484, 10.1029/2002jd002310,
2003.Liu, Y., Yang, Z., Desyaterik, Y., Gassman, P. L., Wang, H., and Laskin, A.:
Hygroscopic behavior of substrate-deposited particles studied by micro-FT-IR
spectroscopy and complementary methods of particle analysis, Anal. Chem., 80,
633–642, 10.1021/ac701638r, 2008.Martins, J. V., Hobbs, P. V., Weiss, R. E., and Artaxo, P.: Sphericity and
morphology of smoke particles from biomass burning in Brazil, J. Geophys. Res.-Atmos., 103, 32051–32057, 10.1029/98jd01153, 1998.Mikhailov, E. F., Vlasenko, S. S., Podgorny, I. A., Ramanathan, V., and
Corrigan, C. E.: Optical properties of soot-water drop agglomerates: An
experimental study, J. Geophys. Res.-Atmos., 111, D07209, 10.1029/2005JD006389, 2006.Moffet, R. C., Qin, X. Y., Rebotier, T., Furutani, H., and Prather, K. A.:
Chemically segregated optical and microphysical properties of ambient
aerosols measured in a single-particle mass spectrometer, J. Geophys. Res.-Atmos., 113, D12213, 10.1029/2007jd009393, 2008.Moffet, R. C. and Prather, K. A.: In-situ measurements of the mixing state
and optical properties of soot with implications for radiative forcing
estimates, P. Natl. Acad. Sci. USA, 106, 11872–11877,
10.1073/pnas.0900040106, 2009.
Moffet, R. C., Henn, T., Laskin, A., and Gilles, M. K.: Automated Chemical
Analysis of Internally Mixed Aerosol Particles Using X-ray Spectromicroscopy
at the Carbon K-Edge, Anal. Chem., 82, 7906–7914, 2010.
Moffet, R. C., Tivanski, A. V., and Gilles, M. K.: Scanning Transmission
X-ray Microscopy: Applications in Atmosheric Aerosol Research, in:
Fundamentals and Applications in Aerosol Spectroscopy, edited by: Signorell,
R. and Reid, J. P., CRC Press, Boca Raton, 419 pp., 2011.Moffet, R. C., Rödel, T. C., Kelly, S. T., Yu, X. Y., Carroll, G. T., Fast, J., Zaveri, R. A., Laskin, A.,
and Gilles, M. K.: Spectro-microscopic measurements of carbonaceous aerosol aging in Central California,
Atmos. Chem. Phys., 13, 10445–10459, 10.5194/acp-13-10445-2013, 2013.O'Brien, R. E., Neu, A., Epstein, S. A., MacMillan, A. C., Wang, B. B.,
Kelly, S. T., Nizkorodov, S. A., Laskin, A., Moffet, R. C., and Gilles, M.
K.: Physical properties of ambient and laboratory-generated secondary
organic aerosol, Geophys. Res. Lett., 41, 4347–4353, 10.1002/2014gl060219,
2014.O'Brien, R. E., Wang, B. B., Laskin, A., Riemer, N., West, M., Zhang, Q.,
Sun, Y. L., Yu, X. Y., Alpert, P., Knopf, D. A., Gilles, M. K., and Moffet,
R. C.: Chemical imaging of ambient aerosol particles: Observational
constraints on mixing state parameterization, J. Geophys. Res.-Atmos., 120,
9591–9605, 10.1002/2015JD023480, 2015.Park, K., Kittelson, D. B., and McMurry, P. H.: Structural properties of
diesel exhaust particles measured by transmission electron microscopy (TEM):
Relationships to particle mass and mobility, Aerosol Sci. Technol., 38, 881–889,
10.1080/027868290505189, 2004.Ramachandran, G. and Reist, P. C.: Characterization of
Morphological-Changes in Agglomerates Subject to Condensation and
Evaporation Using Multiple Fractal Dimensions, Aerosol Sci. Technol., 23,
431–442, 10.1080/02786829508965326, 1995.Ramanathan, V. and Feng, Y.: On avoiding dangerous anthropogenic
interference with the climate system: Formidable challenges ahead, P. Natl.
Acad. Sci. USA, 105, 14245–14250, 10.1073/pnas.0803838105, 2008.Ramanathan, V. and Xu, Y. Y.: The Copenhagen Accord for limiting global
warming: Criteria, constraints, and available avenues, P. Natl. Acad. Sci. USA,
107, 8055–8062, 10.1073/pnas.1002293107, 2010.Riemer, N. and West, M.: Quantifying aerosol mixing state with entropy and diversity measures,
Atmos. Chem. Phys., 13, 11423–11439, 10.5194/acp-13-11423-2013, 2013.Rogelj, J., Schaeffer, M., Meinshausen, M., Shindell, D. T., Hare, W.,
Klimont, Z., Velders, G. J. M., Amann, M., and Schellnhuber, H. J.:
Disentangling the effects of CO2 and short-lived climate forcer mitigation,
P. Natl. Acad. Sci. USA, 111, 16325–16330, 10.1073/pnas.1415631111, 2014.Scarnato, B. V., Vahidinia, S., Richard, D. T., and Kirchstetter, T. W.: Effects of internal mixing and
aggregate morphology on optical properties of black carbon using a discrete dipole approximation model,
Atmos. Chem. Phys., 13, 5089–5101, 10.5194/acp-13-5089-2013, 2013.Weingartner, E., Burtscher, H., and Baltensperger, U.: Hygroscopic
properties of carbon and diesel soot particles, Atmos. Environ., 31,
2311–2327, 10.1016/S1352-2310(97)00023-X, 1997.Zaveri, R. A., Shaw, W. J., Cziczo, D. J., Schmid, B., Ferrare, R. A.,
Alexander, M. L., Alexandrov, M., Alvarez, R. J., Arnott, W. P., Atkinson, D.
B., Baidar, S., Banta, R. M., Barnard, J. C., Beranek, J., Berg, L. K.,
Brechtel, F., Brewer, W. A., Cahill, J. F., Cairns, B., Cappa, C. D., Chand,
D., China, S., Comstock, J. M., Dubey, M. K., Easter, R. C., Erickson, M. H.,
Fast, J. D., Floerchinger, C., Flowers, B. A., Fortner, E., Gaffney, J. S.,
Gilles, M. K., Gorkowski, K., Gustafson, W. I., Gyawali, M., Hair, J.,
Hardesty, R. M., Harworth, J. W., Herndon, S., Hiranuma, N., Hostetler, C.,
Hubbe, J. M., Jayne, J. T., Jeong, H., Jobson, B. T., Kassianov, E. I.,
Kleinman, L. I., Kluzek, C., Knighton, B., Kolesar, K. R., Kuang, C.,
Kubátová, A., Langford, A. O., Laskin, A., Laulainen, N., Marchbanks, R. D.,
Mazzoleni, C., Mei, F., Moffet, R. C., Nelson, D., Obland, M. D., Oetjen, H.,
Onasch, T. B., Ortega, I., Ottaviani, M., Pekour, M., Prather, K. A., Radney,
J. G., Rogers, R. R., Sandberg, S. P., Sedlacek, A., Senff, C. J., Senum, G.,
Setyan, A., Shilling, J. E., Shrivastava, M., Song, C., Springston, S. R.,
Subramanian, R., Suski, K., Tomlinson, J., Volkamer, R., Wallace, H. W.,
Wang, J., Weickmann, A. M., Worsnop, D. R., Yu, X.-Y., Zelenyuk, A., and
Zhang, Q.: Overview of the 2010 Carbonaceous Aerosols and Radiative Effects
Study (CARES), Atmos. Chem. Phys., 12, 7647–7687,
10.5194/acp-12-7647-2012, 2012.