https://doi.org/10.5194/amt-2021-166
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Estimates of mass absorption cross sections of black carbon for filterbased absorption photometers in the Arctic
Sho Ohata1,2,*, Tatsuhiro Mori3,4,*, Yutaka Kondo5,*, Sangeeta Sharma6, Antti Hyvärinen7, Elisabeth
5 Andrews8,9, Peter Tunved10, Eija Asmi7, John Backman7, Henri Servomaa7, Daniel Veber6,
Konstantinos Eleftheriadis11, Stergios Vratolis11, Makoto Koike3, Yugo Kanaya12,13, Atsushi Yoshida5,
Nobuhiro Moteki3, Yongjing Zhao14, Yutaka Tobo5,15, Junji Matsushita5, and Naga Oshima16
1

10

15

20

25

30

Institute for Space–Earth Environmental Research, Nagoya University, Nagoya, Aichi, Japan
Institute for Advanced Research, Nagoya University, Nagoya, Aichi, Japan3
Department of Earth and Planetary Science, Graduate School of Science, The University of Tokyo, Tokyo,
Japan
4
Department of Physics, Faculty of Science Division I, Tokyo University of Science, Tokyo, Japan
5
National Institute of Polar Research, Tachikawa, Tokyo, Japan
6
Climate Chemistry Measurements Research/Climate Research Division, Environment and Climate Change
Canada/Government of Canada
7
Finnish Meteorological Institute, Helsinki, Finland
8
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO,USA
9
NOAA Global Monitoring Laboratory, 325 Broadway, Boulder, CO, USA
10
Department of Environmental Science and Analytical Chemistry (ACES), Atmospheric Science Unit,
Stockholm University, Stockholm, Sweden
11
Environmental Radioactivity Laboratory (ERL), Institute of Nuclear and Radiological Science & Technology,
Energy & Safety, National Centre for Scientific Research ‘‘Demokritos’’, 15310 Attiki, Greece
12
Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology(JAMSTEC), Yokohama, Kanagawa, Japan
13
Graduate School of Maritime Sciences, Kobe University, Kobe, Japan
14
Air Quality Research Center, University of California, Davis, CA, USA
15
Department of Polar Science, School of Multidisciplinary Sciences, The Graduate University for Advanced
Studies, SOKENDAI, Tachikawa, Tokyo, Japan
16
Meteorological Research Institute, Tsukuba, Japan
2

*

35

These authors contributed equally to this work.

Correspondence to: Sho Ohata (sho.ohata@isee.nagoya-u.ac.jp)
Running title: Normalization of BC measurements by COSMOS1

https://doi.org/10.5194/amt-2021-166
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Abstract. Long-term measurements of atmospheric mass concentrations of black carbon (BC) are40

needed to investigate changes in its emission, transport, and deposition. However, depending on
instrumentation, parameters related to BC such as aerosol absorption coefficient (babs) have beenmeasured instead. Most ground-based measurements of babs in the Arctic have been made by filterbased absorption photometers, including particle soot absorption photometers (PSAP), continuous lightabsorption photometer (CLAP), Aethalometers, and multi-angle absorption photometers (MAAP). The

45

measured babs can be converted to mass concentrations of BC (MBC) by assuming the value of the mass
absorption cross section (MAC; MBC = babs/MAC). However, the accuracy of conversion of babs to MBC
has not been adequately assessed. Here, we introduce a systematic method for deriving MAC values
from babs measured by these instruments and independently measured MBC. In this method, MBC wasmeasured with a filter-based absorption photometer with a heated inlet (COSMOS). COSMOS-derived

50

MBC (MBC (COSMOS)) is traceable to a rigorously calibrated single particle soot photometer (SP2) andthe absolute accuracy of MBC (COSMOS) has been demonstrated previously to be about 15 % in Asiaand the Arctic. The necessary conditions for application of this method are a high correlation of themeasured babs with independently measured MBC, and long-term stability of the regression slope, which
is denoted as MACcor (MAC derived from the correlation). In general, babs–MBC (COSMOS)

55

correlations were high (r2 = 0.76–0.95 for hourly data) at Alert in Canada, Ny-Ålesund in Svalbard,
Barrow in Alaska, Pallastunturi in Finland, and Fukue in Japan, and stable for up to 10 years. We
successfully estimated MACcor values (10.6–15.2 m2 g–1 at a wavelength of 550 nm) for these
instruments and these MACcor values can be used to obtain error-constrained estimates of MBC from babs
measured at these sites even in the past, when COSMOS measurements were not made. Because the60

absolute values of MBC in these Arctic sites estimated by this method are consistent with each other,
they are applicable to the study of spatial and temporal variation of MBC in the Arctic and to evaluationof the performance of numerical model calculations.

2https://doi.org/10.5194/amt-2021-166
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65

1 Introduction
Black carbon (BC) aerosols strongly absorb solar radiation and thereby impact the radiation budget in
the Arctic (Bond et al., 2013; AMAP, 2015). In addition, BC deposited on snow decreases the snow
surface albedo and accelerates snowmelt (AMAP, 2015; Flanner et al., 2009). According to recent
climate model calculations in the sixth phase of the Coupled Model Intercomparison Project (CMIP6;

70

Eyring et al., 2016), BC contributes the second largest positive radiative forcing in the Arctic, after
carbon dioxide (CO2) (Oshima et al., 2020). BC is one of the short-lived climate forcers (SLCF) andreductions of BC emissions can decrease the positive Arctic radiative forcing over much shorter
timescales than can reductions of CO2 emissions (Sand et al., 2016). Long-term measurements of massconcentrations of BC in the atmosphere (MBC [µg m–3]) at various locations provide fundamental data75

for the detection of long-term trends in MBC in the Arctic that are associated with changes in BC
emissions. Such MBC data are also useful for validation and improvement of climate models. However,
because many long-term surface instruments measure aerosol light absorption coefficient (babs [Mm–1])
rather than MBC, there are large uncertainties in MBC estimated from the measurements of babs; these
uncertainties have not been critically evaluated.

80

A continuous soot monitoring system called COSMOS (Kanomax, Osaka, Japan) has been developed tomeasure MBC (Miyazaki et al., 2008; Kondo et al., 2009, 2011). This filter-based absorption photometeris equipped with an inlet that is heated to 300°C to remove non-refractory components from the aerosol
phase. COSMOS MBC values (MBC (COSMOS)) have been compared with those measured by a single
particle soot photometer (SP2; Droplet Measurement Technologies, Longmont, CO, USA; MBC (SP2)),

85

which is based on a laser-induced incandescence technique (Schwarz et al., 2006; Moteki and Kondo,
2010); simultaneous measurements in Asia and at Ny-Ålesund in Svalbard have shown that MBC (SP2)and MBC (COSMOS) agree to within about 10 % (Kondo et al., 2009, 2011; Ohata et al., 2019).
Long-term measurements of babs at various sites have been carried out by other types of filter-based
absorption photometers, including the particle absorption soot photometer (PSAP; Radiance Research,

90

Seattle, WA, USA), the continuous light absorption photometer (CLAP; NOAA, Boulder, CO, USA;
Ogren et al., 2017), the Aethalometer (Magee Scientific, Berkeley, CA, USA), and the multi-angle
absorption photometer (MAAP; Thermo Scientific, Waltham, MA, USA) (e.g., Schmeisser et al., 2018).
Measurements of light-absorption and light-scattering properties of aerosols are important for
constraining their interannual and seasonal variability, potential particle sources, and resulting aerosol-

95

radiation interactions in the Earth system (Schmeisser et al., 2018; Bellouin et al., 2020). However, theaccuracy and stability of conversion of babs obtained by these instruments to MBC have not yet been fully
evaluated, mainly because of a lack of simultaneous and reliable long-term MBC measurements. The3https://doi.org/10.5194/amt-2021-166
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relationship between babs obtained by these instruments and MBC are complicated by complex
contributions from mixing states of BC (i.e., lensing effect by BC-coating materials; Bond et al., 2006:
100

Lack et al., 2008), other co-existing light-absorbing aerosols such as brown carbon and mineral dust,
and measurement artifacts by light-scattering aerosols on filters (Bond et al., 1999). Evaluations thathave been completed to date include those of Kanaya et al. (2013, 2020), who compared MBC(COSMOS) with the babs measured by MAAP (babs (MAAP)) on Fukue Island, Japan, and Sinha et al.
(2017), who compared babs measured by PSAP (babs (PSAP)) at Barrow in Alaska and Ny-Ålesund

105(Zeppelin station), Svalbard. The results of these studies showed that babs (MAAP) and babs (PSAP)
were strongly correlated with MBC (COSMOS), making it possible to convert babs to MBC at these sites
with reasonable accuracy. Long-term observations of babs have been made also at Arctic sites Alert in
Canada by PSAP and Aethalometer (Sharma et al., 2004, 2006, 2017), Ny-Ålesund by Aethalometer(Eleftheriadis et al., 2009), and Pallastunturi in Finland by MAAP (Hyvärinen et al., 2011; Lihavainen

110

et al., 2015). To investigate the possibility of converting babs to MBC at each of these sites, it is importantto simultaneously measure MBC and babs by collocating a COSMOS (or SP2) at each site with each ofthese filter-based absorption photometer instruments.
The conversion of babs obtained by these instruments to MBC can be made by assuming a reasonable
conversion factor, i.e, the value of mass absorption cross section (MAC [m2 g–1]; MBC = babs/MAC). The

115

MAC values can depend on location because the spatiotemporal variations in microphysical properties
of BC (i.e., mixing states and size distributions) and properties of co-existing light-absorbing andscattering aerosols will affect babs measurements. The plausible MAC values for conversion can also
depend on the type of instrument because each instrument uses different wavelength and adopts various
correction methods for quantifying babs. Despite several intercomparisons and field experiments (Asmi120

et al., 2020) as well as thorough assessment of these techniques (Lack et al., 2008; Moosmüller et al.,2009) the simultaneous changes in aerosol source region, mixing state, concentration and particle
optical size are reflected in the instruments' response in a complex way and with a variable level of
uncertainty.
In general, the MAC of BC, here simply denoted as “MACBC” for both bare and internally-mixed BC, is125

a fundamental optical parameter that relates MBC with babs of BC (babs,BC) in climate models (i.e., babs,BC= MBC × MACBC). Bond and Bergstrom (2006) reported the MACBC value of 7.5 m2 g–1 at a wavelengthof 550 nm for combusted fresh BC. Cho et al., (2021) estimated MACBC values of 6–12 m2 g–1 at 550
nm in the Asian outflow using aircraft-based SP2 data and Mie theory. Yuan et al. (2021) showed that
the MACBC values at 870 nm at a rural site in Germany clearly increased as the coating thickness of BC

130

increased.
However, in this paper we focus on the MAC values mainly from the viewpoint of a conversion factor
to obtain error-constrained MBC from the babs measurements by the filter-based absorption photometers4https://doi.org/10.5194/amt-2021-166
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because such MBC data will be the observational base for understanding long-term trends and spatial
distributions of BC in the Arctic. Detailed investigations of the accuracy of the absolute values of babs
135

measured at each site are beyond the scope of this study.
We critically re-examine the concepts underpinning the use of filter-based instruments to estimate MBC.
We derive MAC values for PSAP/CLAP, Aethalometer, and MAAP measurements based on theircomparison with COSMOS measurements at the four above-mentioned Arctic sites (Alert, Ny-Ålesund,Barrow, and Pallastunturi) and one East Asian site (Fukue). The variability of the derived MAC values

140

and their dependencies on observation site and instrument type are analyzed. We also compare MBC
values measured by COSMOS and SP2 at Alert and Fukue to confirm their agreement under different
environmental conditions.

2 Methods
2.1 Observation sites
145

Measurements of babs by the various types of filter-based absorption photometers were compared withmeasurements of MBC by COSMOS at Arctic sites Alert in Canada (82.5º N, 62.5º W; Sharma et al.,2017), Ny-Ålesund (Zeppelin station) in Svalbard (78.9º N, 11.9º E; Sinha et al., 2017), Barrow in
Alaska (71.3º N, 156.6º W; Sinha et al., 2017), and Pallastunturi (Pallas, hereafter) in Finland (68.0º N,
24.0º E; Hyvärinen et al., 2011), as summarized in Table 1 and Fig. 1. Along with these sites,

150

comparisons were also made at a remote site on Fukue Island (32.8º N, 128.7º E; Kanaya et al., 2020) inJapan, where air masses from the Asian continent are occasionally transported to the site and properties
of aerosols should be distinctly different from those at the Arctic sites. Instruments used at each site arelisted in Table 1 and described in the following section.
2.2 Instruments

155

2.2.1 SP2
In this study we used the SP2 and COSMOS as standard instruments to measure MBC. Detailed
descriptions of the SP2, including calibration methods, are given elsewhere (Schwarz et al., 2006;
Moteki and Kondo, 2010). Briefly, the SP2 uses the laser-induced incandescence technique and detects
BC on a single-particle basis. We used two SP2s in this study: the one installed at Fukue was160

maintained and calibrated by the University of Tokyo (UT-SP2, hereafter) and the other one at Alert
was maintained and calibrated by Environmental and Climate Change Canada (EC-SP2, hereafter). The
configuration of the UT-SP2 is identical to that described by Moteki and Kondo (2010). The model
designation of the EC-SP2 was “SP2-D” with eight channels. The UT-SP2 and EC-SP2 measured BC
size distributions in the mass-equivalent diameter (Dm) range 70–850 and 60–600 nm, respectively. The

165

void-free density of BC was assumed to be 1.8 g cm–3. These SP2s were calibrated using fullerene soot5https://doi.org/10.5194/amt-2021-166
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particles (Alfa Aeser, stock #40971, lot #FS12S011; Moteki and Kondo, 2010; Kondo et al., 2011). The
laser-induced incandescence signal intensity of the UT-SP2 for the specific mass of ambient BC
particles in Tokyo agree with that of fullerene soot particles to within about 10 % (Kondo et al., 2011).
Laborde et al. (2012) reported similar SP2 calibration curves for fullerene soot particles, diesel exhaust,
170

and ambient BC particles in Switzerland. The accuracy of MBC (SP2) estimated from the uncertainty of
the calibration and operational conditions of SP2 was about 10 %. No particle-size cut was used for the
inlet of the UT-SP2, whereas a PM1 cyclone was used for the EC-SP2.
2.2.2 COSMOS
2.2.2.1 Measurements of MBC by COSMOS175

The principles of operation of the COSMOS apparatus are detailed in previous papers (Miyazaki et al.,2008; Kondo et al., 2011; Kondo, 2015; Ohata et al., 2019). Briefly, the COSMOS measures theextinction coefficient (b0) of aerosols collected on a quartz-fiber filter at a given wavelength (λ = 565
nm). Most previous studies used filters from Pallflex (E70-2075W, Pall, Port Washington, NY, USA),
which are no longer available. Consequently, HEPA filters have been used for more recent observations

180(Irwin et al., 2015), including this study. An important difference between the COSMOS and the othertypes of filter-based absorption photometer is that the inlet of the COSMOS is heated to 300°C toremove volatile light scattering particles (LSPs) and coatings of BC from the aerosol phase. Therefore,
the effect on b0 of co-existing volatile components externally or internally mixed with BC particles canbe ignored. The COSMOS is equipped with a PM1 cyclone to minimize the effect in coarse mode of

185

refractory non-BC particles, such as dust and sea-salt particles. Consequently, the absorption coefficientfor the COSMOS is given as𝑏!"# (COSMOS) = 𝑓$%& 𝑏' .

(1)Here, ffil is a factor used to correct for the increase of absorption caused by multiple scattering in thefilter medium (Bond et al., 1999; Ogren, 2010; Ohata et al., 2019). The MAC for the COSMOS [m2 g–1]
190

is operationally defined as
MAC (COSMOS, SP2) ≡(!"# (+,-.,-)
0$% (-12),(2)

where the numerator and denominator, respectively, are simultaneous measurements of babs [Mm–1] by
COSMOS and MBC [µg m–3] by SP2 for ambient air. The MAC value for a Pallflex filter at λ = 565 nm
was previously set at 8.73 [m2 g–1] (Sinha et al., 2017). For a HEPA filter, the MAC is about 6 % higher
195(Irwin et al., 2015). Depending on the filters used (Pallflex or HEPA), the appropriate MAC value wasused in this study.
Once the MAC (COSMOS, SP2) is determined, MBC (COSMOS) [g m–3] at standard temperature andpressure (0°C, 1013 hPa) can be estimated as6https://doi.org/10.5194/amt-2021-166
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((+,-.,-)

𝑀3+ (COSMOS) = .4+!"#(+,-.,-,-12).
200

(3)

One particular purpose of the heating of sampled air to 300°C is to make the MAC (COSMOS, SP2)
stable and independent of original mixing states of BC particles. In other words, the heating treatment
makes babs (COSMOS) more proportional to BC mass concentrations, as compared to the other filterbased absorption photometers described in Sect. 2.2.3. As a consequence, unlike the other filter-based
absorption photometers, the absorption coefficient of unheated original aerosols is not provided by

205

COSMOS. Thus, the COSMOS has been developed to measure MBC, not babs. In this sense, MBC(COSMOS) is different from “equivalent” BC mass concentrations estimated from the unheated babs
measurements (Petzold et al., 2013).
We call the COSMOS that was calibrated by comparison with the SP2 in Tokyo the “standard
COSMOS”, described hereafter as Std-COSMOS. Because the MAC of the Std-COSMOS was

210

determined by comparison with SP2 (Eq. (2)), it acts as a transfer standard for the SP2. The babs
(COSMOS) of each COSMOS manufactured is compared with the Std-COSMOS by sampling ambient
BC particles in Osaka, Japan, typically for 1–2 weeks. The comparisons during these periods were
statistically reliable partly due to relatively high BC concentrations in Osaka. The babs (COSMOS) of 28
COSMOS instruments manufactured thus far agree with that of Std-COSMOS to within about ±7 %,215

indicating reliable quality control in manufacturing. The small differences originating from theuncertainty of the filter sampling spot size of each unit are corrected for in deriving MBC (COSMOS).
It is important to compare MBC (COSMOS) and MBC (SP2) outside Tokyo and Osaka, to confirm boththe strong correlation between MBC (COSMOS) and MBC (SP2) and the long-term stability of the MAC(COSMOS) value. Ohata et al. (2019) made these comparisons at two remote sites: at Cape Hedo

220

(26.9°N, 128.3°E), Japan, and at Ny-Ålesund. At each of these locations, the concentrations of BC and
LSP and the mixing states of BC were considerably different from those in Tokyo and Osaka. MBC(COSMOS) and MBC (SP2) agree to within about 10 % at these sites, thus demonstrating the validity ofusing the Std-COSMOS to calibrate each of the COSMOS instruments to be used for field observations.
Ohata et al. (2019) also showed that the dependencies of MAC (COSMOS) on the thickness of coatings

225

of BC particles, MBC, and volume concentrations of the co-existing LSPs were small. Although the
MAC (COSMOS) showed a slight dependence on the mass size distributions of BC, the sensitivity of
the MAC (COSMOS) to such variations in microphysical properties of BC was generally less than 10 %(Kondo et al., 2011; Ohata et al., 2019).
Previously estimated uncertainties of MBC (COSMOS) were about 10 % based on the range of230

agreement between MBC measurements by COSMOS and UT-SP2 (Kondo et al., 2011; Ohata et al.,2019). It may be more appropriate to estimate the absolute accuracy of MBC (COSMOS) to be about
15 %, including the above-mentioned 10 % uncertainty of MBC (SP2). This 15 % uncertainty also covers
7https://doi.org/10.5194/amt-2021-166
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the range of agreement between MBC (COSMOS) and MBC (SP2) previously reported by other groups at
Ny-Ålesund (Zannata et al., 2018) and at Fukue (Miyakawa et al., 2017).
235

Although we used the SP2 and COSMOS as standard instruments to measure MBC in this study,
thermal-optical analysis, which quantifies elemental carbon (EC) mass concentrations (MEC), also has
been a traditional standard method to measure BC. Measurements of MEC can depend on thetemperature protocol and optical charring correction method used (e.g., Bond et al., 2013). Agreements
within 10 % of MBC (SP2), MBC (COSMOS), and MEC were reported by Kondo et al. (2011), whereas

240

systematic differences between MBC (SP2) and MEC up to a factor of 2 were found by Pileci et al. (2021).
Although the difference between MBC (COSMOS) and MEC was generally lower than 5 ng m–3 at the
Arctic site Barrow (Sinha et al., 2017), this difference can be important for pristine summer Arctic
conditions (MBC (COSMOS) < 20 ng m–3). Considering these previously reported agreements anddiscrepancies between MBC (SP2 or COSMOS) and MEC, in some cases the MAC values determined by245

babs and MBC measurements (this study) can differ from those determined by babs and MEC measurements(Zanatta et al., 2016).
2.2.2.2 Effect of light-absorbing FeOx particles on MBC (COSMOS)
Light-absorbing iron oxide (FeOx) aerosols, which the SP2 can distinguish from BC (Yoshida et al.,2016; Lamb, 2019), can affect MBC measured by filter-based absorption photometers. FeOx aerosols are

250

emitted from both anthropogenic sources (e.g., motor vehicle exhaust) and natural sources (e.g., windblown mineral dust). Within the detectable diameter range of the UT-SP2 (Dm = 70–850 nm for BC and
Dm =170–2100 nm for FeOx), the mass concentration ratios of FeOx to BC were typically ~0.4 in East
Asia and ~0.2 in the Arctic; they were mainly of anthropogenic origin in both regions (Moteki et al.,2017; Ohata et al., 2018; Yoshida et al., 2018, 2020). FeOx aerosols contribute at least 4–7 % of the255

short-wave absorbing powers of BC in Asian continental outflows (Moteki et al., 2017) and their direct
radiative forcing has been estimated to be 0.22 W m–2 over East Asia (Matsui et al., 2018). Here, weestimate the effect of light absorption by FeOx on MBC measured by the COSMOS. The ratio of lightabsorbed by FeOx to that absorbed by BC at a wavelength l (e(l)) is given by
0 '(𝜀(𝜆) =)*+, .4+∫0 6 '-./023*_)*+, (75 ,8) 9&:;71
7
0

9

260

'(

1

$% .4+∫0 8 '-./0
23*_$% (75 ,8) 9&:;71

,

(4)

1

where Dm is mass equivalent diameter of bare BC or FeOx; DL and DU are the lower and upper limits,
respectively, of the diameter for the integral calculus; dMBC/dlogDm and dMFeOx/dlogDm are the mass
size distributions of BC and FeOx, respectively; and MACMie_BC (Dm, l) and MACMie_FeOx (Dm, l) are
the MAC values of bare BC and FeOx, respectively, for Dm and l calculated by Mie theory.
The mass size distributions of BC and FeOx at Fukue and Ny-Ålesund (Fig. 2) were obtained by fitting265

monomodal and bimodal lognormal functions to the average mass size distributions measured by the8https://doi.org/10.5194/amt-2021-166
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SP2 during each observation campaign (Yoshida et al., 2020). The measurements at Fukue were madein April 2019 and those at Ny-Ålesund in March 2017. The MACMie_BC (Dm, l) and MACMie_FeOx (Dm,l) data (Fig. 2) were calculated by Mie theory for l = 565 nm (wavelength used for COSMOS). For thiscalculation, we assumed BC and FeOx to be in the form of bare spheres with void-free densities of 1.80
270

g cm–3 and 5.17 g cm–3, respectively. The refractive index of BC we used was 1.99 + 0.64i, which is thevalue for BC at l = 600 nm (Bergstrom, 1972). The refractive index of FeOx we used was 2.56 + 0.57i,
which is the value for magnetite at l = 600 nm (Huffman and Stapp, 1973).
From Eq. (4), the e values at Fukue and Ny-Ålesund were calculated to be 3.6 % and 1.9 %,respectively, for (DL, DU) = (30, 1000 nm). These e values became 4.6 % and 2.6 % for (DL, DU) = (30,2752500 nm). Because COSMOS is equipped with a PM1 cyclone, we estimated the effect of lightabsorption by FeOx on MBC measured by COSMOS to be < 4 % in East Asia and < 2 % in the Arctic.
Note that these estimates are upper limits of the effect of FeOx because the PM1 cyclone is designed toremove particles of > 1 µm aerodynamic diameter (Da). Due to the fractal shape and high density of
FeOx particles (Moteki et al., 2017), Dm is considerably smaller than Da for FeOx particles and thus DU

280

in Eq. (4) should be less than 1 µm.
The effect of FeOx on MBC (COSMOS) should be even smaller considering that the mass concentrationof anthropogenic FeOx is correlated with MBC, as mentioned above. Even if babs (COSMOS) is enhanced
by FeOx by a few percent, this effect is already incorporated to some extent, by operationally defining
MAC (COSMOS, SP2) by Eq. (2).

285

The effect of FeOx on babs may be somewhat higher for the other filter-based absorption photometersthan for COSMOS if they are equipped with a larger particle size cut (PM2.5 or PM10). For accurate
measurements of MBC, the use of a PM1 cyclone or impactor is recommended to minimize the effects of
FeOx, as well as other refractory particles such as natural dust and sea-salt particles.

2.2.3 Filter-based absorption photometers other than COSMOS
290

2.2.3.1 PSAP and CLAP
The principle of operation of the PSAP is similar to those of COSMOS (Bond et al., 1999; Sinha et al.,2017). In this study, we also used babs data obtained with a continuous light absorption photometer(CLAP) (Ogren et al., 2017). The CLAP is conceptually similar to the PSAP but uses solenoid valves tocycle through eight sample filter spots. The PSAP and CLAP both utilize the Pallflex filters. The unit-

295

to-unit variations of the PSAP and CLAP were reported to be within 6 % (Bond et al.,1999) and 4 %(Ogren et al., 2017), respectively. The wavelengths of the light absorption measured by either PSAP or
CLAP at Barrow, Ny-Ålesund, and Alert were about 467, 530, and 660 nm. The major difference of the
PSAP and CLAP from the COSMOS is that the sample air inlets of the PSAP and CLAP are not heated9https://doi.org/10.5194/amt-2021-166
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to 300°C. Therefore, the effect of the attenuation of light by LSPs is corrected for by using the aerosol
300

light scattering coefficient simultaneously measured by an integrating nephelometer (Bond et al., 1999;
Ogren 2010). This correction adjusts for measurement artifacts but introduces uncertainties in theestimate of babs (PSAP or CLAP). At the above three sites, light scattering coefficients measured bynephelometers at wavelengths of 450, 550, and 700 nm were used for this correction. The babs for the
PSAP or CLAP (hereafter, babs (PSAP/CLAP)) at λ = 550 nm was obtained by adjusting measured

305

absorption at 530 to 550 nm by using the λ–1 relationship (Sinha et al., 2017; Sharma et al., 2017).
Schmeisser et al. (2017) reported that the median value of the absorption Ångström exponent at Arctic
sites was 1.04, which supports our assumption of the λ–1 relationship. The accuracy of the babs measured
by PSAP ranges between 20 and 30% (Bond et al., 2013).
2.2.3.2 Aethalometer

310

An AE-31 Aethalometer (Hansen et al., 1984) has been used for measurements of babs at Alert without
any particle size cut (Sharma et al., 2017). This Aethalometer measures the attenuation (ATN) of lighttransmitted through particles accumulating on a quartz fiber filter at seven wavelengths (370, 470, 520,
590, 660, 880, and 950 nm). In deriving babs (Aethalometer) from ATN data, the correction factor Cf =3.45 (Backman et al., 2017) was applied. This correction factor is very close to the correction factor C0315= 3.5 recommended by the World Meteorological Organization/Global Atmosphere Watch (2016).
Another AE-31 Aethalometer has also been used at Ny-Ålesund (Zeppelin station) (Eleftheriadis et al.,2009), where the sampling inlet was equipped with a calculated PM10 size cut. Data post-processing
included flagging based on Zeppelin station logs, Ny-Ålesund harbor logs and diagnostics reported by
the instrument (flowrate, raw attenuation, zero signal, etc). A correction factor C0 = 3.5 was used to320compensate for the multiple scattering effect.
The filter loading effect is not significant for Arctic aerosol, as reported by Backman et al. (2017). For
Alert, the slope of the correction factor Cf-1 to ATN is k = 0.00074, indicating a 5 % difference at an
ATN value of 80. For Zeppelin, the loading effect causes a 2 % difference in Cf at an attenuation valueof 80. These uncertainties are considered small compared to the overall babs uncertainty, which is 20–325

30 % (Bond et al., 2013). Therefore, the loading correction is not applied to the AE31 measurements.
Corrections for light scattering by using nephelometer data were also not applied.
2.2.3.3 MAAP
Detailed descriptions of the MAAP are given elsewhere (Petzold et al., 2002, 2005; Petzold andSchӧnlinner, 2004; Kanaya et al., 2013). In brief, the MAAP monitors the transmittance of light through a

330

glass-fiber tape and measures reflectance at two angles. To remove the influence of LSPs, babs (MAAP)
from particles deposited on the filter is derived by radiative transfer calculations. The uncertainty of babs
(MAAP) was estimated by Petzold and Schӧnlinner (2004) to be 12%. The unit-to-unit variation of the10https://doi.org/10.5194/amt-2021-166
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MAAP was reported to be within 5% (Müller et al., 2011). The MAC values for the MAAP (MAC
(MAAP)) for λ = 637 nm was determined by comparing babs (MAAP) and MBC measured at four sites in335

Germany by the German reference method VDI2465 Part 1 (GRM; Schmid et al., 2001), represented by(.441)(

MAC (MAAP, GRM) ≡ 0!"# (<=.) .

(5)

$%

For the measurements of MBC (GRM), organic carbon was removed by solvent extraction and the residualBC particles on the filters were oxidized to CO2 and quantified by coulometric titration. The measurement
uncertainty of MBC (GRM) was about 25 % (Petzold and Schӧnlinner, 2004). The MAC of 6.6 m2 g–1 is the340

default setting by the manufacturer based on their study. In determining MAC (MAAP, GRM), an SP2 was
not used to measure MBC, and this is a potential source of discrepancy in this value of MAC, as discussed
in Sect. 3.4.1 and 3.5.2.

3 Results and discussion
3.1 Alert
345

3.1.1 COSMOS-SP2 comparison
Long-term measurements of BC using different manufacturer’s model versions of SP2s have been
conducted at Alert since 2011 (Sharma et al., 2017). In this study, we used the data obtained by an ECSP2 (model “SP2-D” with eight channels; see Sect. 2.2.1) from January to May 2018 for comparison
with the COSMOS data. The EC-SP2 and COSMOS aspired sample air from a common inlet with a

350

PM1 size cut. Fig. 3a shows the number and mass size distributions of BC averaged over theobservation period. The mode diameter of the average mass size distribution of BC was ~210 nm,
which is similar to that previously reported at Alert (Sharma et al., 2017) and that observed by aircraftbased measurements over Alert (Schulz et al., 2019). Because the upper limit of the detectable diameter
range of BC was ~600 nm for the EC-SP2, we have estimated MBC (SP2) over the range up to 1000 nm

355

by fitting lognormal functions to the measured mass size distributions. The time series of hourly valuesof MBC (COSMOS) and MBC (SP2) (Fig. 3b) were strongly correlated (r2 = 0.92; r2 is the square of thecorrelation coefficient) and the slope of the regression forced through the origin was 1.02 (Fig. 3c).
These results show that on average, the agreement between MBC (COSMOS) and MBC (SP2) at Alertwas within 10 %.

360

Although this agreement was consistent with those reported in previous studies using UT-SP2 (Kondo
et al., 2011; Ohata et. al., 2019), note that there were some differences between MBC (SP2) measured by
the EC-SP2 and that by the UT-SP2. The EC-SP2 was calibrated by Aquadag samples at Alert during
the observation period and also calibrated by fullerene soot samples at the Paul Scherrer Institute in
Switzerland after the observation period. Because the sensitivity of the incandescence signals of the SP2

365

to Aquadag is higher than that to fullerene soot, the calibration curve for Aquadag needs correction to11https://doi.org/10.5194/amt-2021-166
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obtain the fullerene-soot equivalent calibration curve (Baumgardner et al., 2012). Additionally, to makethis correction, assumptions of the effective density (reff) values of Aquadag (Moteki and Kondo, 2010;
Gysel et al., 2011), which depend on the mobility diameter of Aquadag, are needed since a differential
mobility analyzer (DMA) is used for the on-site calibration at Alert instead of an aerosol particle mass
370

analyzer (APM) or a centrifugal particle mass analyzer. The reff values of Aquadag samples can dependon their batches (Gysel et al., 2011). In the previous study by Sharma et al. (2017), the constant value ofreff (= 0.7 g cm–3) for Aquadag was assumed to derive MBC (SP2) at Alert. However, we have foundthat MBC (SP2) at Alert highly depended on the assumed reff values of Aquadag used for the on-site
calibration with a DMA. Because of this, we used the calibration curve obtained by fullerene soot with375

an APM at the Paul Scherrer Institute after the observation period for this study. The conditions of the
EC-SP2 might have differed slightly between during and after the observation period, which may leadto additional uncertainties for MBC (SP2) at Alert, although the difference of Aquadag calibrations madebefore and after the campaign was less than about 10 %. In addition, the upper limit of the detectable
diameter of BC for the EC-SP2 (Dm ~600 nm) was lower than that for the UT-SP2 (Dm ~850 nm),380

although the above-mentioned extrapolation up to 1000 nm was made to derive MBC (SP2) at Alert.
Despite these differences between EC-SP2 and UT-SP2, MBC (COSMOS) and MBC (SP2) agree towithin 10 % at Alert, consistent with previous studies that reported the stability of the relationshipbetween MBC (COSMOS) and MBC (SP2) at various sites (Kondo et al., 2011; Ohata et. al., 2019).
3.1.2 COSMOS-PSAP comparison

385

Measurements of MBC (COSMOS) at Alert began in January 2018. A PM1 cyclone was used for the
COSMOS and a PM1 impactor for the PSAP and two CLAP instruments (CLAP1, CLAP2). The timeseries of 1-h and 24-h averaged MBC (COSMOS) were strongly correlated with babs (PSAP; λ = 550 nm)
for 2018–2019 (r2 ~0.96; Fig. 4a–d). In this study, we define the MAC value, MACcor, as the slope ofthe least squares regression forced through the origin in the correlation plot. The values of MACcor

390(PSAP; λ= 550 nm) for the whole period were 13.9 m2 g–1 and 14.0 m2 g–1 for the 1-h and 24-h
averaged data, respectively, as summarized in Table 2. The results of the same analyses for otherwavelengths of the PSAP and the two CLAPs show that the strength of the correlation depended little
on wavelength (Table 2). The babs, and therefore the MAC, for the PSAP and the two CLAP instruments(CLAP1, CLAP2) agree to within 8%, indicating little difference in the performance of these395

instruments.
Along with the correlation analysis, variability of the babs (PSAP) / MBC (COSMOS) ratio was also
analyzed for the 1-h and 24-h data (Fig. 4e and f). This ratio can be interpreted as an hourly or daily
MAC value at each time. Because this ratio tends to be unstable when the MBC (COSMOS) values arevery low, we set a threshold MBC (COSMOS) value of 2 ng m–3 in this analysis, as shown in these400

figures. The median ratio, defined as median MAC and denoted as MACmed, was 13.5 m2 g–1 for both 112

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h and 24-h data, which is very close to MACcor (13.9 m2 g–1 and 14.0 m2 g–1 for the 1-h and 24-h data,
respectively) (Table 3). The difference between MACcor and MACmed was about 4 %, leading to thesame difference between the estimated MBC values if these MAC values are used for conversion of babs
(PSAP) to MBC. Based on the interquartile ranges of the babs (PSAP) / MBC (COSMOS) ratios (Fig. 4e405

and f), variations of the ratios (with an MBC threshold of 2 ng m–3), denoted as VMAC, were within 19 %and 18 % of the MACmed values for the 1-h and 24-h data, respectively (Table 3). Therefore, conversionof 1-h and 24-h averaged babs (PSAP; λ = 550 nm) data to MBC by assuming a constant MACmed leads touncertainty of about 19 % at Alert. We used the same method in estimating MACcor, MACmed, and VMAC
for other instruments and other locations, as summarized in Table 3. Note that this estimated uncertainty

410

can depend on the threshold value of MBC (COSMOS) assumed in the analysis. The relative uncertainty
becomes higher (lower) in summer (winter/spring) when the MBC values tend to be low (high) (Fig. 4a
and b).
3.1.3 COSMOS–Aethalometer comparison
Measurements of babs at Alert were made by an Aethalometer at wavelengths of 370, 470, 520, 590, 660,

415

880, and 950 nm without any particle size cut. Time series of babs (Aethalometer; λ = 590 nm) and MBC(COSMOS) in 2018–2019 are shown in Fig. S1 in the Supplement. babs (Aethalometer; λ = 590 nm) was
highly correlated (r2 > 0.90) with MBC (COSMOS) (Fig 5a and b). The MACcor (Aethalometer; λ = 590nm) values were 12.5 and 12.7 m2 g–1 for the 1-h and 24-h data, respectively. The MACmed values of thebabs (Aethalometer) / MBC (COSMOS) ratios were 13.5 m2 g–1 and 13.8 m2 g–1 for the 1-h and 24-h data,

420

respectively (Fig. 5c and d), which agree with the MACcor values to within 8 %. Therefore, dependingon the MAC values used, the estimated MBC values can differ by about 8 %. Because the interquartile
ranges of the babs (Aethalometer) / MBC (COSMOS) ratios were 11.4–16.5 m2 g–1 (1-h data) and 12.1–
15.7 m2 g–1 (24-h data), the VMAC was about 22% (with an MBC threshold of 2 ng m–3) for babs
(Aethalometer; λ = 590 nm) at Alert (Table 3).

425

The MACcor (Aethalometer) values for each wavelength are summarized in Table 4. Note that thesewavelength-dependent MACcor values should be interpreted as the simple conversion factors to obtainaverage MBC from babs (Aethalometer), which might have been contributed to by BC and also otherlight-absorbing aerosols. In other words, these MACcor values differ from MACBC, as discussed in Sect.
1. The r2 values were generally high for all wavelengths examined. This weak dependence on

430wavelength indicates that the contribution of other light-absorbing aerosols such as brown carbon (BrC)
to babs (Aethalometer) is small or the BrC/BC concentration ratio was rather stable at Alert during
2018–2019, because BrC should enhance light absorption in near ultraviolet wavelengths.
The MACcor (Aethalometer) and MACcor (PSAP) are compared in Table 5. They agree within 10 % at
three wavelengths, despite the different particle size cuts of the inlets for Aethalometer (total suspended435

particle) and PSAP (PM1). This agreement is consistent with the results by Backman et al. (2017), who
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showed that the correction factor Cf of 3.45 for Aethalometer harmonizes babs (Aethalometer) with babs
(PSAP), babs (CLAP), and babs (MAAP) at Arctic sites.
3.2 Ny-Ålesund
3.2.1 COSMOS-PSAP comparison
440

Simultaneous measurements of MBC (COSMOS) for PM1 and babs (PSAP) for PM10 began at NyÅlesund in 2012 (Sinha et al., 2017; Fig. S2 in the Supplement). The 1-h and 24-h averaged babs (PSAP;
λ = 550 nm) were well correlated (r2 = 0.76–0.82) with MBC (COSMOS), and the MACcor (PSAP) value
for the whole period was 14.4–15.2 m2 g–1 (Fig. 6a and b). Year-to-year variations of MACcor (PSAP)
are also shown in Fig. 7a and Table 6. The correlation between babs (PSAP) and MBC (COSMOS) during

445

April–December 2012 was weak for unknown reasons. Excluding this period, average MACcor (PSAP)
during 2013–2016 was 15.2 ± 2.2 (1σ) and 16.6 ± 1.4 m2 g–1 for the 1-h and 24-h data, respectively.
Although the reason for the relatively large change in MACcor (PSAP) values during 2014–2015 (Fig.
7a and Table 6) is not clear, this may be partly because babs (PSAP) data from December 2014 to April
2015 (during an “Arctic haze” period) were not available (Fig. S2).

450

The MACmed values of the babs (PSAP) / MBC (COSMOS) ratios were 16.7 and 17.2 m2 g–1 for the 1-h
and 24-h data, respectively, when the MBC threshold of 2 ng m–3 was applied in the analysis (Fig. 6c andd). The MACmed values were by 16 % and 13 % higher than MACcor for 1-h and 24-h data, respectively(Table 3). Therefore, conversion of babs (PSAP; λ = 550 nm) to MBC using a constant MACcor may resultin a slightly biased MBC, especially for lower babs data. This is partly because the correlation of babs

455

(PSAP) with MBC (COSMOS) is not very high and scatter of the data, especially those with lower MBC
values, contributes to large variations of the babs (PSAP) / MBC (COSMOS) ratios (Fig. 6). Theinterquartile range of the ratios were 10.6–21.7 m2 g–1 and 11.9–21.4 m2 g–1 for the 1-h and 24-h data,
respectively. Although these large variations might be partly attributed to actual variations in mixing
states of BC, artifacts of babs measurements by PSAP at Ny-Ålesund may be a contributing factor,

460

considering the higher correlations of babs (Aethalometer) at Ny-Ålesund with MBC (COSMOS) (Sect.
3.2.2.). Based on the interquartile ranges of the babs (PSAP) / MBC (COSMOS) ratios, VMAC was about
35 % for babs (PSAP; λ = 550 nm) at Ny-Ålesund (Table 3). The above-mentioned bias leads to an
additional uncertainty of about 15 % for the estimates of MBC, if the constant MACcor value is used.
3.2.2 COSMOS-Aethalometer comparison

465

Measurements of babs (Aethalometer; λ = 590 nm) for PM10 were compared with measurements of MBC(COSMOS) for PM1 during 2012–2019. The time series data of babs (Aethalometer; λ = 590 nm) werehighly correlated with those for MBC (COSMOS) (Fig. S3 in the Supplement) (r2 = 0.90 for both the 1-h
and 24-h data; Fig. 8a and b). The MACcor (Aethalometer; λ = 590 nm) values were 10.2 and 10.1 m2 g–
1

for the 1-h and 24-h data, respectively. Year-to-year variations of MACcor (Aethalometer) are also
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470

shown in Fig. 7a and Table 7. The r2 values were generally high for each year and the average MACcor(Aethalometer) during 2012–2019 was 10.2 ± 1.6 (1σ) and 10.0 ± 1.3 m2 g–1 for the 1-h and 24-h data,
respectively. The MACcor (Aethalometer) value for 2012 was 8.7 m2 g–1 at 590 nm (i.e., 9.3 m2 g–1 at
550 nm assuming the λ–1 relationship) for 24-h data, which is consistent with the MACcor of 9.8 m2 g–1
at 550 nm inferred from the SP2 and Aethalometer measurements in the spring of 2012 (Zanatta et al.,4752018). At Ny-Ålesund, the MACcor (Aethalometer) values (10.2 and 10.1 m2 g–1 for the 1-h and 24-hdata, respectively) were systematically lower than the MACcor (PSAP) values (14.4 m2 g–1 and 15.2 m2
g–1). This discrepancy is different from that at Alert (Sect. 3.1.3) and the reason is unclear, but could be
partly due to uncertainty in the absolute values of babs, as discussed in Sect. 1 and Sect. 2.2.3.
The MACmed values of the babs (Aethalometer) / MBC (COSMOS) ratios were 11.2 and 12.3 m2 g–1 for480

the 1-h and 24-h data, respectively (Fig. 8c and d). While the MACmed for the 1-h data agree with
MACcor to within 10%, there is a 22 % discrepancy for the 24-h data under the assumed thresholdsetting (2 ng m–3) of MBC (COSMOS) (Table 3). Therefore, conversion of 24-h averaged babs
(Aethalometer; λ = 590 nm) to MBC using a constant MACcor may be somewhat biased, especially forlower babs values. At Ny-Ålesund, the VMAC was about 25 % for babs (Aethalometer; λ = 590 nm). The

485

above-mentioned bias leads to an additional uncertainty of about 20 % for conversion of 24-averaged
low babs data to MBC, if the constant MACcor value is assumed.
3.3 Barrow
3.3.1 COSMOS-PSAP/CLAP comparison
Simultaneous measurements of PM1 for MBC (COSMOS) and babs (PSAP/CLAP) began at Barrow in490

2012 (Sinha et al., 2017). At Barrow, both the PSAP and CLAP aspired ambient air using PM1 andPM10 impactors alternately for 30 min of each hour. Here we used the data from the PSAP/CLAP
equipped with the PM1 impactor and data from the PSAP in 2012–2015 and the CLAP in 2016–2019(Fig. S4 in the Supplement). Because the 24-h averaged babs (PSAP) and babs (CLAP) values agreed towithin 2 % during 2012–2015 (Sinha et al., 2017) when the PSAP and CLAP overlapped, we consider

495

the two instruments to be equivalent. The MBC (COSMOS) data from June 2018 to May 2019 were
unavailable due to problems with the COSMOS instrument.
The babs (PSAP/CLAP; λ = 550 nm) data were strongly correlated with those for MBC (COSMOS) (r2 =0.88 and r2 = 0.86; Fig. 9a and b) and the MACcor (PSAP/CLAP) derived from 1-h and 24-h averaged
data for the whole period were 10.8 and 10.6 m2 g–1, respectively. Average MACcor (PSAP/CLAP)

500

during 2012–2018 was stable at 11.0 ± 0.9 (1σ) m2 g–1 (Fig. 7b and Table 8). Yearly MBC (COSMOS)
values did not exhibit large changes during this period (Fig. 7b). The babs (CLAP) data was weakly
correlated with MBC (COSMOS) data during June–December 2019 (Table 8), indicating that either the
CLAP or COSMOS results might not have been accurate during this period. Therefore, in Table 8 we
15

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calculated the average MACcor (PSAP/CLAP) by excluding the MAC value for 2019.
505

The MACmed values of the babs (PSAP/CLAP) / MBC (COSMOS) ratios were 11.2 and 11.0 m2 g–1 for 1h and 24-h data (Fig. 9c and d), which are very close to the MACcor values of 10.8 and 10.6 m2 g–1,
respectively (Table 3). Therefore, when either MACcor or MACmed is used for conversion of babs
(PSAP/CLAP; λ = 550 nm) to MBC, the resulting MBC values differ by only about 4 %. The VMAC wasabout 25 % for babs (PSAP /CLAP; λ = 550 nm) at Barrow (Table 3).

510

3.4 Pallas
3.4.1 COSMOS-MAAP comparison
Measurements of babs (MAAP; λ = 637 nm) have been made since 2007 at the Global Atmospheric
Watch (GAW) station at Pallas (Hyvärinen et al., 2011). PM10 and PM1 inlets were used for MAAP and
COSMOS, respectively. MBC (COSMOS) measurements began in July 2019; we used the data collected

515

up to July 2020 in this study. The MBC (COSMOS) data for about 3 months (February to April 2020)
were unavailable due to an air sampling problem.
The babs (MAAP) 1-h and 24-h values (Fig. S5 in the Supplement) were strongly correlated with thosefor MBC (COSMOS) with r2 = 0.93 and r2 = 0.95, respectively (Fig. 10a and b). MACcor (MAAP) was
13.0 m2 g–1 for both the 1-h and 24-h data. This MACcor value is about twice the manufacturer’s default

520

setting (= 6.6 m2 g–1) of MAC (MAAP). One possible reason is the difference of the methods of MBC
measurements to determine MACcor (MAAP) values, as mentioned in Sect. 2.2.3.3. Another reason
could be that the difference in microphysical properties of BC (mixing states and size distribution) andproperties of co-existing LSPs lead to the different MACcor (MAAP) values.
The MACmed values of the babs (MAAP) / MBC (COSMOS) ratios for the 1-h and 24-h data were 12.4

525

and 13.1 m2 g–1, respectively (Fig. 10c and d), which are very close to that for MACcor (13.0 m2 g–1 forboth 1-h and 24-h data, Table 3). Therefore, the difference between the estimated MBC values is lessthan 5 % when these MACcor or MACmed values are used for conversion of babs (MAAP) to MBC. The
VMAC was about 25 % for babs (MAAP) at Pallas (Table 3).
3.5 Fukue Island

530

3.5.1 COSMOS-SP2 comparison
The UT-SP2 was operated at Fukue for 3 weeks in April 2019 (Yoshida et al., 2020), as mentioned in
Sect. 2.2.1. Fig. 11a shows the number and mass size distributions of BC measured by the UT-SP2
averaged over the observation period. In addition to the MBC (SP2) derived by integrating the mass size
distributions over the detectable diameter range (Dm = 70–850 nm), we also estimated MBC (SP2) in the535

Dm = 30–1000 nm range by fitting a lognormal function to the data. As the two sets of MBC (SP2) values
deviated by less than 2 %, we used the former MBC (SP2) for comparison with MBC (COSMOS). The16https://doi.org/10.5194/amt-2021-166
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time series of hourly values of MBC (COSMOS) were strongly correlated (r2 = 0.97) with MBC (SP2)(Fig. 11b) and the slope of the regression was 0.92 (Fig. 11c). This relationship agrees with thoseobserved by Ohata et al. (2019) at Tokyo, Hedo, and Ny-Ålesund and those observed at Alert (Sect.
540

3.1.1), thus confirming the clear and consistent relationship between MBC (COSMOS) and MBC (SP2).
Miyakawa et al. (2017) also reported a strong correlation (r2 = 0.92; regression slope 1.14) between
MBC (COSMOS) and MBC (SP2) at Fukue in spring 2015 by using an SP2 maintained and calibrated by
the Japan Agency for Marine-Earth Science and Technology.
3.5.2 COSMOS-MAAP comparison

545

Kanaya et al. (2013, 2016, 2020) made simultaneous measurements of MBC (COSMOS) and babs
(MAAP; λ = 639 nm) at Fukue for about 10 years (April 2009–May 2019; Fig. S6 in the Supplement).
The air inlet for the MAAP and COSMOS was equipped with a PM1 cyclone after November 2011.
Before that a PM2.5 cyclone was used instead. babs (MAAP) was highly correlated (r2 = 0.94) with MBC(COSMOS) and the MACcor (MAAP) for the entire period was found to be 10.8 m2 g–1 and 10.9 m2 g–1

550

for the 1-h and 24-h data (Fig. 12a and b), respectively. Because the correlation of babs (MAAP) with
MBC (COSMOS) was also strong for individual years, MACcor (MAAP) for each year was also derived(Fig. 7c and Table 9). MBC (COSMOS) decreased by about 50 % during this period, owing to a large
decrease of BC emissions in China (Kanaya et al., 2020). However, the yearly average MACcor(MAAP) values were stable at 11.1 ± 1.0 (1σ) m2 g–1 for both the 1-h and 24-h data, despite the large

555change in MBC (COSMOS). This MACcor value is considerably higher than the manufacturer’s default
setting (= 6.6 m2 g–1), possibly for the same reasons discussed in Sect. 3.4.1.
Because the number of data with MBC less than 2 ng m–3 was very small at Fukue, the MACmed values
and the interquartile ranges of the babs (MAAP) / MBC (COSMOS) ratios were obtained for all data
without applying any threshold of MBC. The MACmed was 11.4 m2 g–1 for both 1-h and 24-h data (Fig.

560

12c and d), which agrees well (within 6 %) with the MACcor values derived from correlation plots (10.8
and 10.9 m2 g–1 for 1-h and 24-h data, respectively) (Table 3). Therefore, using either MACcor or
MACmed for conversion of babs (MAAP) to MBC affects the resulting MBC values by less than 6 %. The
VMAC was about 15 %, which is lower than those at Arctic sites (Table 3) partly because the higher MBC(COSMOS) values at Fukue make the calculated ratios more stable. Also, aerosol properties including

565

mixing states of BC might be more stable at Fukue than those at the Arctic sites examined in this study.

3.6 Spatial variability of MACcor and r2
In previous sections, we showed that the MACcor values depended on instrument and observation site.
The values of MACcor (λ = 550 nm) and r2 are summarized in Table 10. Here, the MACcor (MAAP; λ~637 nm) and MACcor (Aethalometer; λ = 590 nm) values were adjusted to those at λ = 550 nm by17https://doi.org/10.5194/amt-2021-166
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570

assuming an absorption Ångstrom exponent of 1.0 (i.e., a λ–1 relationship). The unit-to-unit variations ofbabs measurements were reported to be within 5 % for MAAP (Müller et al., 2011), 6 % for PSAP (Bondet al.,1999), and 4 % for CLAP (Ogren et al., 2017), if the careful calibration of flows and filter
sampling spot sizes of these instruments are made for individual units. Therefore, the spatial variationsof MACcor values observed in this study likely reflects differences of aerosol properties at the575

observation sites.
The values of MACcor (PSAP) at Alert and MACcor (PSAP/CLAP) at Barrow were both determinedwith a PM1 size cut and they differed by about 22 % for 1-h data. Differences in aerosol properties
including mixing states of BC at these sites could contribute to the different MAC values, although thiseffect cannot be assessed quantitatively with only this dataset. The correlations of babs (PSAP) with MBC

580(COSMOS) at Alert were somewhat higher (r2 = 0.96) than those of babs (PSAP/CLAP) at Barrow (r2 =0.84–0.87). The stronger correlation of babs (PSAP) with MBC (COSMOS) at Alert suggests thatenvironmental conditions including LSP/BC ratios and mixing states of BC were more stable at Alert.
We found that at Alert babs (PSAP) data with loading and scattering corrections were strongly correlatedwith the uncorrected babs (PSAP) data and the contribution of the loading and scattering corrections was

585

about 35 %, on average. In contrast at Barrow, the contribution of these corrections was about 63 %.
This indicates that at Alert, the LSP/BC ratio was small and stable at Alert, and the influence of LSPs
on derived babs (PSAP) was small. The greater distance from continental sources of aerosols at Alert
than at Barrow (Fig. 1), which may contribute to these observed differences.
At Ny-Ålesund, where a PM10 inlet was used, the MACcor (PSAP) values were higher than those at

590

Alert and Barrow. Also, the r2 values at Ny-Ålesund (r2 = 0.84–0.89) were lower than those at Alert.
Effects of particles larger than 1 µm including dust and sea salt may partly contribute to the larger MAC
and lower r2 values at Ny-Ålesund.
The MACcor (PSAP) and MACcor (Aethalometer) agree to within 4 % for 1-h data at Alert, in spite ofthe different particle size cut of the inlets. However, they differed by about 24% for 1-h data at Ny-

595Ålesund. Although the agreements were somewhat better for 2015–2016 at Ny-Ålesund (Fig. 7a), thereason for the overall discrepancy is unknown. Furthermore, while the MACcor (PSAP) at Ny-Ålesund
was higher than that at Alert, the opposite result was obtained by Aethalometers, which is not easilyinterpreted.
The values of MACcor (MAAP) determined at Pallas and Fukue differ by about 17%. This difference

600

may be attributed to the difference of average mixing states of BC and properties of other co-existing
aerosols, which were affected by environmental conditions and also by the different particle size cuts
used at these sites (i.e., PM1 for Fukue and PM10 for Pallas). Because these are the only available
MACcor (MAAP) data sets derived from MBC (COSMOS), it is difficult to further evaluate spatial
variability.
18

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605

We have shown that in general, babs values obtained by PSAP, CLAP, Aethalometer, and MAAP werestrongly correlated with MBC (COSMOS) at all four Arctic sites, although the strength of thecorrelations differed somewhat among the sites. Based on the analysis of babs/MBC variations among
these sites, the MACcor and MACmed were most stable for PSAP with a PM1 inlet at Alert and mostvariable for PSAP with a PM10 inlet at Ny-Ålesund (Table 3). The average MACcor (λ = 550 nm) values

610

at these four Arctic sites were 13.1 ± 1.7 (1s; 13 % of the average) and 13.2 ± 1.9 (1s; 14 %) m2 g–1 for
1-h and 24-h data, respectively (Table 10). However, these correlations and resulting MACcor values
may not hold outside the Arctic, where environmental conditions can be very different, especially themixing states of BC and amount of interference by LSPs.
Zanatta et al. (2016), using MEC measured by the thermal-optical transmittance method with the615

EUSAAR-2 protocol instead of MBC (COSMOS), reported the average MACcor value at λ = 637 nm fornine European background sites to be 10.0 m2 g–1. From this MACcor (λ = 637 nm) value, the value of
MACcor at λ = 550 nm is calculated to be 11.6 m2 g–1 by assuming an absorption Ångstrom exponent of
1.0. Although their MACcor values were generally obtained using PM10 inlets or without particle sizecuts, their average MACcor value (= 11.6 m2 g–1) is about 15 % lower than our average MACcor value

620(13.1–13.2 m2 g–1) at 4 Arctic sites determined in this study. This discrepancy may be partly due to thedifferent methods used to determine absolute mass concentrations of BC.
Mason et al. (2018) derived the values of MACcor (PSAP) and MACcor (CLAP) for PM1 size range inbiomass burning and agriculture fire plumes during the SEAC4RS aircraft observation campaign byusing MBC (SP2) data. They reported the MACcor (PSAP; λ = 532 nm) and MACcor (CLAP; λ = 532 nm)

625

values to be 21.0 and 26.5 m2 g–1, respectively, which are about 60 % larger than the average MACcor
value (13.1–13.2 m2 g–1) determined in this study. Although the causes for their very high MACcor
values are not clear, one possible explanation given by Mason et al. (2018) is the considerable amountof additional absorbers other than BC, including tar balls, that might have existed in their samples. Also,
strong lensing effects by BC coatings could contribute to the high MACcor values. Thus, the MACcor

630

values can be highly dependent on environmental conditions and those reported in the present study are
considered to be site-specific values, although the variability (1s) of our MACcor values in the 4 Arctic
sites was within 14% of the average MACcor value for these 4 sites.

4 Summary and conclusions
Long-term measurements of MBC by ground-based instruments are needed to investigate changes in the635

emission, transport, and deposition of BC. Various types of filter-based absorption photometers,
including the particle absorption soot photometer (PSAP), the continuous light absorption photometer(CLAP), the Aethalometer, and the multi-angle absorption photometer (MAAP) have been used in the
Arctic. To date, the accuracy of MBC estimated from absorption coefficients (babs) measured by these19https://doi.org/10.5194/amt-2021-166
Preprint. Discussion started: 29 June 2021
c Author(s) 2021. CC BY 4.0 License.

instruments have not been adequately assessed, mainly because of a lack of simultaneous and reliable640

MBC measurements.
In this paper, we introduced a systematic methodology to derive MBC from babs measured by these
instruments. To obtain accurate values of MBC, we used a filter-based absorption photometer with aheated inlet (COSMOS), which we calibrated to within 10 % uncertainty with an SP2 deployed inTokyo. Individual COSMOS instruments used for field observations were calibrated against the645

standard COSMOS to within about 10 %. The accuracy of MBC (COSMOS) has previously been
demonstrated to be about 15 % by comparison with MBC (SP2) in Asia and the Arctic. The effect on
MBC (COSMOS) of interference by light-absorbing FeOx particles was estimated to be only a few
percent, owing partly to the particle-size cut off of 1 μm by the PM1 cyclone used. This effect may besomewhat higher for the other filter-based absorption photometers equipped with larger particle-size

650

cuts. The two necessary conditions for application of our method are a high correlation of babs withindependently measured MBC and long-term stability of the slope of the regression, which represents
MACcor.
We compared babs (PSAP/CLAP) with MBC (COSMOS) at Alert (PM1) for 2 years, Ny-Ålesund (PM10)
for 4 years, and Barrow (PM1) for 7 years. The babs (PSAP/CLAP) was highly correlated with MBC

655(COSMOS) at these sites. For 1-h data, the MACcor (PSAP/CLAP) at λ = 550 nm was 13.9 m2 g–1 at
Alert, 14.4 m2 g–1 at Ny-Ålesund, and 10.8 m2 g–1 at Barrow. The VMAC was 19 % at Alert, 37 % at NyÅlesund, and 22 % at Barrow (Table 3).
We also compared babs (Aethalometer) with MBC (COSMOS) at Alert (total suspended particles) for 2
years and at Ny-Ålesund (PM10) for 8 years. They were highly correlated and the MACcor

660(Aethalometer) at λ = 590 nm for 1-h data was 12.5 m2 g–1 at Alert and 10.2 m2 g–1 at Ny-Ålesund. The
VMAC was 22 % at Alert and 25 % at Ny-Ålesund (Table 3).
The babs (MAAP) and MBC (COSMOS) were also compared at Pallas (PM10) for about 1 year and at
Fukue (PM1) for about 10 years. babs (MAAP) was highly correlated with MBC (COSMOS) at these sites.
The MACcor (MAAP) at λ = 637 nm was 13.0 m2 g–1 at Pallas for both 1-h and 24-h data. The MACmed

665(MAAP) at λ = 639 nm at Fukue was stable at 11.1 ± 1.0 m2 g–1, despite a 50 % decrease in MBC(COSMOS) during this period (Table 3). The default setting of MACcor (MAAP) by the manufacturer(6.6 m2 g–1) is about half the present values, indicating a similar overestimation of MBC if the default
value is used to convert babs (MAAP) to MBC at these sites. The VMAC was 25 % at Pallas and 15 % at
Fukue.

670

Our results show that MBC can be derived from babs obtained from PSAP, CLAP, Aethalometer, and
MAAP measurements with reasonable accuracy by using the MACcor obtained from the regression
slope of the babs–MBC correlation, especially for long data-averaging times. However, scatter in babs–
20https://doi.org/10.5194/amt-2021-166
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c Author(s) 2021. CC BY 4.0 License.

MBC (COSMOS) correlations indicate that the accuracy of this method will be somewhat lower than that
achieved by direct measurement of MBC (COSMOS). We also caution that the reliability of the use of675

babs data to derive MBC at other locations, especially those outside the Arctic, is unknown. Rigorouscomparisons with COSMOS or SP2 data, such as those of this study, are required if use of our method
is to expand beyond the Arctic region. Moreover, long-term comparisons are desirable for accurate
determination of the MACcor. Short-term comparisons will be of limited value for understanding thevariability of MAC for each instrument and location.

680

Data availability
The

observational

data

set

used

in

this

publicationisavailable

online(https://ads.nipr.ac.jp/dataset/A20201120-001).

Author contributions
SO, TM, and YKo designed the study, conducted the analyses, and wrote the paper. SS and DV
685

contributed to the field observations and data analysis of SP2, PSAP, CLAP, and Aethalometer at Alert.
AH, EAs, JB, and HS contributed to the field observations and data analysis of MAAP at Pallas. EAncontributed to the field observations and data analysis of PSAP and CLAP at Barrow. PT obtained andanalyzed PSAP data at Ny-Ålesund. KE and SV obtained and analyzed Aethalometer data at NyÅlesund. YKa contributed to the field observations and data analysis of MAAP and COSMOS at Fukue.

690

AY and NM obtained and analyzed SP2 data at Fukue. SO, TM, YKo, MK, YZ, YT, JM, and NO
contributed to instrument maintenance and data analysis of COSMOS.

Competing interests
The authors declare that they have no conflicts of interest.

Acknowledgements
695

We thank Kevin Rawlings and Melody Fraser of Environment and Climate Change (Canada) and CFS
Alert for operations and maintenance of the Alert site. We thank Bryan Thomas, Peter Detwiler, andRoss Peterson for supporting the measurements at Barrow. We thank the staff of the Norwegian Polar
Institute for supporting the measurements at Ny-Ålesund (Zeppelin). This research was performed by
the

700

Environment

ResearchandTechnology

Development

Fund(JPMEERF20142003,

JPMEERF20172003, JPMEERF20202003, and JPMEERF20205001) of the Environmental Restoration
and Conservation Agency of Japan; the Japanese Ministry of Education, Culture, Sports, Science, andTechnology; the Japan Society for the Promotion of Science KAKENHI Grants (JP12J06736,
21https://doi.org/10.5194/amt-2021-166
Preprint. Discussion started: 29 June 2021
c Author(s) 2021. CC BY 4.0 License.

JP1604452, JP23221001, JP26241003, JP26701004, JP16H01770, JP17H04709, JP18H03363,
JP19K20437, JP19K20441, and JP20H00638); the Arctic Challenge for Sustainability (ArCS) project
705(JPMXD1300000000);

theArcticChallengeforSustainability

II

(ArCS

II)

project(JPMXD1420318865); and a grant for the Global Environmental Research Coordination System from
the Ministry of the Environment, Japan (MLIT1753). Pallas and Zeppelin measurements and/or analysis
were conducted under the financial support of the ACTRIS by the European Union’s Horizon 2020
research and innovation programme under grant agreement no. 654109, partly under the European
710

Union’s Horizon 2020 research and innovation program under grant agreement no. 689443 via projectiCUPE (Integrative and Comprehensive Understanding on Polar Environments) and the 16ENV02
Black Carbon project of the European Union through the European Metrology Programme forInnovation and Research (EMPIR). The research was also supported by Academy of Finland via project
NABCEA (grant no. 29664) and Academy of Finland Flagship funding (grant no. 337552). E. Andrews

715

contribution to this effort was supported in part by the Atmospheric Radiation Measurement (ARM)
user facility, a US Department of Energy (DOE) Office of Science user facility managed by the
Biological and Environmental Research program.

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FiguresFigure 1. Locations of the Arctic sites where BC was measured for this study.
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Figure 2. Mass size distributions of BC (black line) and FeOx (red line) and mass absorption crosssections calculated by Mie theory for bare BC (black dashed line) and bare FeOx (red dashed line) at (a)Fukue in April 2019 and (b) Ny-Ålesund in March 2017. Assumptions for the Mie calculations are970

given in Sect. 2.

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975

Figure 3. (a) Number and mass size distributions of BC averaged over the observation period at Alertfrom January to May 2018. The dashed (solid) red line is the lognormal fit to the number (mass) size
distribution. (b) Time series (1-h data) and (c) correlation of MBC measured by COSMOS and SP2. The
solid line in the correlation plot is the least squares regression forced through the origin.

980

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Figure 4. Time series of MBC (COSMOS) and babs (PSAP; λ = 550 nm) from January 2018 to December
2019 at Alert for (a) 1-h averaged and (b) 24-h averaged data. (c) and (d) Corresponding correlations of
MBC (COSMOS) and babs (PSAP). The solid lines are the least squares regressions forced through the985

origin. (e) and (f) Corresponding histograms of babs (PSAP) / MBC (COSMOS) ratios for all data anddata with MBC (COSMOS) > 2 ng m–3. The interquartile ranges are shown in parentheses.
33

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Figure 5. Correlations of MBC (COSMOS) and babs (Aethalometer; λ = 590 nm) from January 2018 to
December 2019 at Alert for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are the least990

squares regressions forced through the origin. (c) and (d) Corresponding histograms of babs
(Aethalometer) / MBC (COSMOS) ratios for all data and data with MBC (COSMOS) > 2 ng m–3.

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995

Figure 6. Correlations of MBC (COSMOS) and babs (PSAP; λ = 550 nm) from April 2012 to September
2016 at Ny-Ålesund for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are the leastsquares regressions forced through the origin. (c) and (d) Corresponding histograms of babs (PSAP) /MBC (COSMOS) ratios for all data and data with MBC (COSMOS) > 2 ng m–3.
1000

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Figure 7. (a) Time series of yearly MACcor (PSAP; λ = 550 nm), MACcor (Aethalometer; λ = 590 nm),and MBC (COSMOS) at Ny-Ålesund. (b) Time series of yearly MACcor (PSAP/CLAP; λ = 550 nm) and1005

MBC (COSMOS) at Barrow. (c) Time series of yearly MACcor (MAAP; λ = 639 nm) and MBC(COSMOS) at Fukue. In each panel, yearly MACcor and MBC (COSMOS) are calculated from 1-h data.
The dashed lines show the averages of yearly MACcor for the entire time series.

36https://doi.org/10.5194/amt-2021-166
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1010

Figure 8. Correlations of MBC (COSMOS) and babs (Aethalometer; λ = 590 nm) from April 2012 toAugust 2019 at Ny-Ålesund for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are theleast squares regressions forced through the origin. (c) and (d) Corresponding histograms of babs
(Aethalometer) / MBC (COSMOS) ratios for all data and data with MBC (COSMOS) > 2 ng m–3.
1015

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Figure 9. Correlations of MBC (COSMOS) and babs (PSAP/CLAP; λ = 550 nm) from August 2012 to
December 2019 at Barrow for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are the least1020

squares regressions forced through the origin. (c) and (d) Corresponding histograms of babs
(PSAP/CLAP) / MBC (COSMOS) ratios for all data and data with MBC (COSMOS) > 2 ng m–3.

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1025

Figure 10. Correlations of MBC (COSMOS) and babs (MAAP; λ = 637 nm) from July 2019 to July 2020
at Pallas for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are the least squares
regressions forced through the origin. (c) and (d) Corresponding histograms of babs (MAAP) / MBC(COSMOS) ratios for all data and data with MBC (COSMOS) > 2 ng m–3.

1030

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Figure 11. (a) Number and mass size distributions of BC averaged over the observation period at Fukue
in April 2019. The dashed (solid) red line is the lognormal fit to the number (mass) size distribution. (b)Time series (1-h data) and (c) correlation of MBC measured by COSMOS and SP2. The solid line in the1035

correlation plot is the least squares regression forced through the origin.

40

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Figure 12. Correlations of MBC (COSMOS) and babs (MAAP; λ = 639 nm) from April 2009 to May
1040

2019 at Fukue for (a) 1-h averaged and (b) 24-h averaged data. The solid lines are the least squares
regression forced through the origin. (c) and (d) Corresponding histograms of babs (MAAP) / MBC(COSMOS) ratios.

1045

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TablesTable 1. Observation sites, periods, and instruments used in this study.
1050

Location
Alert
Ny-Ålesund

1055

1060

1065

1070

Barrow
PallasFukue (Japan)

PeriodJan – May 2018
Jan 2018 – Dec 2019
Apr 2012 – Sep 2016
Apr 2012 – Aug 2019
Aug 2012 – Dec 2019
Jul 2019 – Jul 2020
Apr 2019
Apr 2009 – May 2019

Instruments
COSMOS, EC-SP2COSMOS, PSAP, Aethalometer
COSMOS, PSAPCOSMOS, Aethalometer
COSMOS, PSAP, CLAPCOSMOS, MAAP
COSMOS, UT-SP2
COSMOS, MAAP

Table 2. MACcor (PSAP/CLAP; λ) values at Alert during 2018–2019. r2 is the square of the correlation
coefficient.

Instrument
CLAP1
CLAP2
PSAP
CLAP1
CLAP2
PSAP
CLAP1
CLAP2
PSAP

λ (nm)
450
450
450
550
550
550
700
700
700

MACcor (1-h)[m2 g–1]
r2(1-h)
13.6
0.93
15.4
0.96
15.7
0.95
12.1
0.93
13.6
0.96
13.9
0.96
9.7
0.93
10.8
0.95
11.5
0.94

1075

42

MACcor (24-h)[m2 g–1]
r2 (24-h)
13.6
0.95
15.4
0.96
15.4
0.96
12.1
0.95
13.8
0.95
14.0
0.95
9.7
0.95
10.9
0.95
11.6
0.95

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1080

Table 3. MAC, r2, and variability of MAC of MAAP, PSAP/CLAP, and Aethalometer at observationsites in this study.

Loca
tion

Instrument

Wavelength
[nm]

Inlet

Alert

PSAP

550

PM1

Alert

Aethalo
meter

590

TSP*

NyÅlesundNyÅlesund

PSAP

550

PM10

Aethalo
meter

590

PM10

Barrow

PSAP/CLAP

550

PM1

Pallas

MAAP

637

PM10

Fukue

MAAP

639

PM1**

*

Period
2018–
2019
2018–
2019
2012–
2016
2012–
2019
2012–
2019
2019–
2020
2009–
2019

(1-h)
MACcor[m2 g–
1]

r2

MACmed[m2 g–1]

VMAC[%](24-h)
MACcor[m2 g–
1]

r2

MACmed[m2 g–1]

VMAC
[%]

13.9

0.95

13.5

19

14.0

0.96

13.5

18

12.5

0.90

13.5

22

12.7

0.94

13.8

22

14.4

0.76

16.7

37

15.2

0.82

17.2

31

10.2

0.90

11.2

25

10.1

0.90

12.3

28

10.8

0.88

11.2

22

10.6

0.86

11.0

26

13.0

0.93

12.4

27

13.0

0.95

13.1

21

10.8

0.95

11.4

15

10.9

0.94

11.4

15

Total suspended particle.
A PM2.5 cyclone was used before November 2011.

1085

**

1090

Table 4. MACcor (Aethalometer; λ) and r2 values at Alert during 2018–2019.

1095

1100

λ (nm)
370
470
520
590
660
880
950

MACcor (1-h)[m2 g–1]
r2(1-h)
18.6
0.86
15.4
0.89
13.9
0.90
12.5
0.90
11.4
0.89
8.8
0.82
8.1
0.79

MACcor (24-h)[m2 g–1]
r2 (24-h)
18.7
0.90
15.6
0.93
14.1
0.94
12.7
0.94
11.6
0.94
8.9
0.94
8.1
0.94

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Table 5. MACcor (PSAP) and MACcor (Aethalometer) values derived from 24-h averaged data at Alertduring 2018–2019.
1110

λ (nm)
PSAP/Aeth
450/470550/590700/660

MACcor (PSAP) MACcor (Aeth)[m2 g–1][m2 g–1]
15.4
15.6
14.0
12.7
11.6
11.6

MACcor (Aeth)/ MACcor (PSAP)
1.01 (1.06)*
1.01 (1.03)*
1.00 (0.94)*1115*

MACcor (Aethalometer) values measured at λ = 470, 590, and 660 nm were adjusted to those at λ =450, 550, and 700 nm (wavelengths used for PSAP) by assuming an absorption Ångstrom exponentof 1.0.
1120

Table 6. Year-to-year variability of MACcor (PSAP; λ = 550 nm) and r2 at Ny-Ålesund.
1125

1130

Year
2012 (Apr–Dec)
2013
2014
2015
2016 (Jan–Sep)
Average (2013–2016)*
All**
*

1135

MACcor (1-h)[m2 g–1]
r2 (1-h)
5.7
0.30
17.0
0.81
17.4
0.80
12.0
0.84
14.5
0.90
15.2 ± 2.2
0.84 ± 0.04
14.4
0.76

MACcor (24-h)[m2 g–1]
r2 (24-h)
5.8
0.44
17.2
0.85
18.5
0.81
15.9
0.94
14.8
0.95
16.6 ± 1.4
0.89 ± 0.06
15.2
0.82

Average and standard deviation for individual years
Derived by regression slope for all data points**

Table 7. Year-to-year variability of MACcor (Aethalometer; λ = 590 nm) and r2 at Ny-Ålesund.
1140

1145

1150

Year
2012 (Apr–Dec)
2013
2014
2015
2016
2017
2018
2019 (Jan–Aug)
Average*
All**
*

1155

MACcor (1-h)[m2 g–1]
r2 (1-h)
8.67
0.80
9.65
0.87
9.77
0.92
9.82
0.96
12.4
0.92
13.0
0.86
10.3
0.92
8.07
0.91
10.2 ± 1.6
0.90 ± 0.05
10.2
0.90

Average and standard deviation for individual years
Derived by regression slope for of all data points**

44

MACcor (24-h)[m2 g–1]
r2 (24-h)
8.75
0.85
8.89
0.75
10.0
0.95
9.87
0.98
12.2
0.95
11.5
0.87
10.6
0.94
8.37
0.92
10.0 ± 1.3
0.90 ± 0.07
10.1
0.90

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Table 8. Year-to-year variability of MACcor (PSAP/CLAP; λ = 550 nm) and r2 at Barrow.
1160

1165

1170

Year
2012 (Aug–Dec)
2013
2014
2015
2016
2017
2018 (Jan–May)
2019 (Jun–Dec)
Average (2012–2018)*
All**
*

1175

MACcor (1-h)[m2 g–1]
r2 (1-h)
9.00
0.65
10.5
0.91
11.0
0.96
11.7
0.91
11.3
0.89
11.5
0.91
12.0
0.86
4.6
0.28
11.0 ± 0.9
0.87 ± 0.09
10.8
0.88

MACcor (24-h)[m2 g–1]
r2 (24-h)
8.80
0.67
10.5
0.91
10.8
0.91
11.5
0.91
11.2
0.88
11.3
0.93
10.9
0.69
5.1
0.41
10.7 ± 0.8
0.84 ± 0.10
10.6
0.86

Average and standard deviation for individual years
Derived by regression slope for all data points**

Table 9. Year-to-year variability of MACcor (MAAP; λ = 639 nm) and r2 at Fukue.
1180

1185

1190

1195

Year
2009 (Apr–Dec)
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019 (Jan–May)
Average*
All***

MACcor (1-h)[m2 g–1]
r2 (1-h)
10.4
0.98
9.62
0.95
11.2
0.95
12.6
0.96
12.8
0.94
10.7
0.98
10.0
0.96
9.90
0.95
10.9
0.93
11.4
0.96
12.1
0.95
11.1 ± 1.0
0.96 ± 0.01
10.8
0.95

MACcor (24-h)[m2 g–1]
r2 (24-h)
10.5
0.99
9.74
0.95
11.3
0.96
12.7
0.96
12.7
0.94
10.8
0.98
9.96
0.95
9.97
0.95
11.1
0.90
11.5
0.96
12.2
0.95
11.1 ± 1.0
0.95 ± 0.02
10.9
0.94

Average and standard deviation for individual years
Derived by regression slope for all data points

**

1200

45

https://doi.org/10.5194/amt-2021-166
Preprint. Discussion started: 29 June 2021
c Author(s) 2021. CC BY 4.0 License.

Table 10. MACcor and r2 for MAAP, PSAP/CLAP, and Aethalometer at λ = 550 nm at observation sites
in this study.
1205

Location

Instrument

Alert
PSAP
Alert
Aethalometer
Ny-Ålesund
PSAP
Ny-Ålesund Aethalometer
Barrow
PSAP/CLAP
Pallas
MAAP
Fukue
MAAP
Average in the 4 Arctic sites****

Inlet

Period

PM1
TSP*
PM10
PM10
PM1
PM10
PM1**

2018–20192018–20192013–2016
2012–20192012–20182019–2020
2009–2019(1-h)
MACcor[m2 g–1]
13.9
13.4***
14.4
10.9***
10.8
15.1***
12.5***
13.1±1.7

*

1210

r2
0.95
0.89
0.76
0.90
0.88
0.93
0.95
0.89±0.06(24-h)
MACcor[m2 g–1]
14.0
13.6***
15.2
10.8***
10.6
15.1***
12.7***
13.2±1.9

r2
0.96
0.92
0.82
0.90
0.86
0.95
0.95
0.91±0.05

Total suspended particles.
A PM2.5 cyclone was used before November 2011.
***
MACcor (MAAP; λ ~637 nm) and MACcor (Aethalometer; λ = 590 nm) values were adjusted to those at λ = 550 nm
by assuming an absorption Ångstrom exponent of 1.0.
****
Average and standard deviation values were calculated excluding MAAP data at Fukue.
**

1215

46