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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article"><?xmltex \bartext{Measurement report}?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">ACP</journal-id><journal-title-group>
    <journal-title>Atmospheric Chemistry and Physics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1680-7324</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-23-3051-2023</article-id><title-group><article-title>Measurement report: Black carbon properties and concentrations in southern Sweden urban and rural air – the importance of long-range transport</article-title><alt-title>Measurement report: Black carbon properties and concentrations in southern Sweden</alt-title>
      </title-group><?xmltex \runningtitle{Measurement report: Black carbon properties and concentrations in southern Sweden}?><?xmltex \runningauthor{E. Ahlberg et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Ahlberg</surname><given-names>Erik</given-names></name>
          <email>erik.ahlberg@nuclear.lu.se</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff7">
          <name><surname>Ausmeel</surname><given-names>Stina</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Nilsson</surname><given-names>Lovisa</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Spanne</surname><given-names>Mårten</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Pauraite</surname><given-names>Julija</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4 aff8">
          <name><surname>Klenø Nøjgaard</surname><given-names>Jacob</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Bertò</surname><given-names>Michele</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-9182-6427</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Skov</surname><given-names>Henrik</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-1167-8696</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Roldin</surname><given-names>Pontus</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4223-4708</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Kristensson</surname><given-names>Adam</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Swietlicki</surname><given-names>Erik</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-2031-0404</ext-link></contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff6">
          <name><surname>Eriksson</surname><given-names>Axel</given-names></name>
          <email>axel.eriksson@design.lth.se</email>
        </contrib>
        <aff id="aff1"><label>1</label><institution>Division of Nuclear Physics, Lund University, Box 118, 221 00 Lund,
Sweden</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Environment Department, City of Malmö, 208 50 Malmö, Sweden</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Department of Environmental Research, Center for Physical Sciences and
Technology, <?xmltex \hack{\break}?>Savanorių ave. 231, 02300 Vilnius, Lithuania</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Department of Environmental Science, iClimate, Aarhus University,
Roskilde, Denmark</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI),
5232 Villigen PSI, Switzerland</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Ergonomics and Aerosol Technology, Lund University, Box 118, 221 00
Lund, Sweden</institution>
        </aff>
        <aff id="aff7"><label>a</label><institution>now at: Swedish Environmental Protection Agency, 10648 Stockholm,
Sweden</institution>
        </aff>
        <aff id="aff8"><label>b</label><institution>now at: National Research Centre for the Working Environment, 2100
Copenhagen, Denmark</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Erik Ahlberg (erik.ahlberg@nuclear.lu.se) and Axel Eriksson
(axel.eriksson@design.lth.se)</corresp></author-notes><pub-date><day>8</day><month>March</month><year>2023</year></pub-date>
      
      <volume>23</volume>
      <issue>5</issue>
      <fpage>3051</fpage><lpage>3064</lpage>
      <history>
        <date date-type="received"><day>28</day><month>February</month><year>2022</year></date>
           <date date-type="rev-request"><day>19</day><month>May</month><year>2022</year></date>
           <date date-type="rev-recd"><day>23</day><month>January</month><year>2023</year></date>
           <date date-type="accepted"><day>30</day><month>January</month><year>2023</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2023 </copyright-statement>
        <copyright-year>2023</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e235">Soot, or black carbon (BC), aerosol is a major climate
forcer with severe health effects. The impacts depend strongly on particle
number concentration, size and mixing state. This work reports on two field
campaigns at nearby urban and rural sites, 65 km apart, in southern Sweden
during late summer 2018. BC was measured using a single-particle soot
photometer (SP2) and Aethalometers (AE33). Differences in BC concentrations
between the sites are driven primarily by local traffic emissions.
Equivalent and refractory BC mass concentrations at the urban site were on
average a factor 2.2 and 2.5, with peaks during rush hour up to a factor
<inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula>, higher than the rural background levels. The number
fraction of particles containing a soot core was significantly higher in the
city. BC particles at the urban site were on average smaller by mass and had
less coating owing to fresh traffic emissions. The organic components of the
fresh traffic plumes were similar in mass spectral signature to
hydrocarbon-like organic aerosol (HOA), commonly associated with
traffic. Despite the intense local traffic (<inline-formula><mml:math id="M2" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 30 000 vehicles
passing per day), PM<inline-formula><mml:math id="M3" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>, including organic aerosol, was dominated by aged
continental air masses even at the curbside site. The fraction of thickly
coated particles at the urban site was highly correlated with the mass
concentrations of all measured chemical species of PM<inline-formula><mml:math id="M4" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>, consistent with
aged, internally mixed aerosol. Trajectory analysis for the whole year
showed that air masses arriving at the rural site from eastern Europe
contained approximately double the amount of BC compared to air masses from
western Europe. Furthermore, the largest regional emissions of BC transported to the rural site, from the Malmö–Copenhagen urban area, are discernible above background levels only when precipitation events are excluded. We show
that continental Europe and not the Malmö–Copenhagen region is the
major contributor to the background BC mass concentrations in southern
Sweden.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<?pagebreak page3052?><sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e282">Virtually everywhere in the world, a fraction of the ambient aerosol
consists of soot. Soot is formed by incomplete combustion of carbonaceous
fuels in hot air-starved conditions and commonly contains both highly
absorbing graphitic-like black carbon (BC) and organic carbon. It has severe
effects on climate and human health (e.g., Bond et al., 2013; WHO, 2021;
IARC, 2014; IPCC, 2021). Therefore, ambient measurements of soot
concentrations and properties are of great importance to constrain and model
its effects. Soot measurements are complicated by the fact that the ambient
aerosol is a dynamic mixture and that soot from different sources may not
possess the same properties in terms of chemical content and nano-structure
(Vander Wal et al., 2010; Malmborg et al., 2019), light absorption
(Sandradewi et al., 2008), size (Schwarz et al., 2008) and toxicity
(Hakkarainen et al., 2022).</p>
      <p id="d1e285">A soot particle survives in the atmosphere approximately 5–9 d (Textor et
al., 2006). During its lifetime several processes affect its properties.
Soot is formed in a chain of steps, starting with the inception of the first
condensed-phase particles from gas-phase hydrocarbon soot precursor species
(Michelsen et al., 2020). These then grow rapidly by coagulation and
gas-to-particle conversion and become more graphitic, also making them more
light-absorbing. These near-spherical 10–30 nm primary particles coagulate
to form agglomerates that are emitted from the source to the surrounding
air if not removed by oxidation already in the combustion process or by
exhaust after-treatment (e.g., particle filters). The properties of the
emitted soot particles depend on the combustion conditions and the fuel used.
For example, it is well known that the wavelength dependence of light
absorption is stronger for biomass burning BC than for traffic emissions
(Sandradewi et al., 2008).</p>
      <p id="d1e288">Once in the atmosphere, the freshly formed soot particles evolve from their
initial agglomerated state, each consisting of large numbers of primary soot
particles, into compacted soot cores with significant coatings of inorganic
and organic material (Corbin et al., 2023). During such atmospheric aging,
the soot particles will not only increase their size and effective density,
but their ability to absorb light will also typically increase (Zhang et
al., 2018). Further, the particles change from being nearly hydrophobic into
hygroscopic particles that can act as CCN (cloud condensation nuclei;
Swietlicki et al., 2008), which increases the likelihood for wet removal, which is the main deposition process for BC in the atmosphere (Textor et
al., 2006). This transformation depends on atmospheric conditions and
constituents but can be on the order of hours under favorable conditions
(Eriksson et al., 2017).</p>
      <p id="d1e291">Already in 2012, the International Agency for Research on Cancer, which is
part of the World Health Organization (WHO), classified diesel engine
exhaust as carcinogenic. The WHO further concluded that there is sufficient
evidence for an association between short-term BC levels and all-cause and
cardiovascular mortality and cardiopulmonary hospital admissions (WHO,
2013). Drawing similar conclusions as the WHO, the US EPA (2019) summarizes
the associations between several health effects and BC concentrations in
its impact assessment (US EPA, 2019). In its latest update of the Air
Quality Guidelines, the WHO did not yet recommend air quality guidelines for BC
(WHO, 2021). Instead, it made a statement of good practice recommending systematic measurements, the production of emission inventories, exposure assessments and source apportionment of black and elemental carbon.</p>
      <p id="d1e295">A myriad of BC measurement techniques exist, and the terminology is based on
the measured property (Petzold et al., 2013). From light absorption
techniques, the equivalent black carbon (eBC) mass concentration is obtained
from the ratio of measured light absorption coefficients to the
corresponding mass absorption cross section (MAC). More recently, techniques
based on laser-induced incandescence (LII) have been developed for measuring
the refractory black carbon (rBC) mass concentration. For instance, the
single-particle soot photometer (SP2) (Schwarz et al., 2006; Stephens et
al., 2003) deploys LII to measure the single-particle rBC mass. In addition,
the SP2 can be used to retrieve the rBC core size, mass size distribution
and provide an estimation of the coating thickness of rBC particles
(Moteki and Kondo, 2007).</p>
      <p id="d1e298">Although BC mass concentrations are routinely estimated from optical
methods, BC number concentrations, size distributions and mixing state are
rarely measured. In a previous study it was shown that global aerosol
microphysics models underestimate the BC particle size, by a factor of
<inline-formula><mml:math id="M5" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 2–3, while overestimating the number concentrations, by more
than a factor of 3, compared to airborne measurements using the SP2
(Reddington et al., 2013). BC from different sources has different size
distributions (Schwarz et al., 2008; Laborde et al., 2013; Saarikoski et
al., 2021), which affects both transport (lifetime) and light interactions
(Hinds, 2012) as well as deposited dose (Alfoldy et al., 2009; Rissler et
al., 2012). Recent studies have pointed to the importance of BC mixing
state, governed by emission source and atmospheric aging, in understanding
the light-absorbing properties, and hence climatic impacts, of BC containing
particles (e.g., Liu et al., 2017, 2020; Fierce et al., 2020;
Yuan et al., 2021). These properties of BC that are crucial to understanding
both health and climate impacts are not measured by the BC measurement
techniques commonly used by monitoring networks.</p>
      <?pagebreak page3053?><p id="d1e308">The aim of this study was to compare BC particle properties in nearby urban
and rural settings and to investigate the influence of urban emissions on
the rural background air, utilizing both filter-based absorption
measurements and single-particle LII. We compare BC mass and number
concentrations, size distributions and mixing state. Furthermore, the
relation to total particle number concentrations and chemically resolved
PM<inline-formula><mml:math id="M6" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> is assessed. Trajectory analysis was used to assess the influence
of long- and short-range transport.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Measurement sites</title>
      <p id="d1e335">Consecutive aerosol measurement campaigns were performed at existing field
sites in a rural and an urban setting in southern Sweden, during the period
of late July to early October 2018. The weather did not change dramatically
between the two campaigns; hence seasonality is not expected to play a major
role in the results. Figure S1 shows that the BC concentrations at the
rural site during July–October did not change drastically between the times
of the two campaigns. The urban campaign (September–October) took place at a
curbside measurement site near a busy road junction surrounded by four- to seven-story
buildings (about 30 000 vehicles per day) in Malmö, which has about
300 000 inhabitants, situated about 30 km east of Copenhagen. Air was
sampled at 3 m above the pavement using <inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula>” stainless
steel tubing and a PM<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> cyclone. Total inlet length was 4–5 m and
the flow was 7–8 L min<inline-formula><mml:math id="M9" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The validity of the curbside site
measurements as an indicator of the BC concentrations in the city was
assessed by comparing simultaneously collected data at a rooftop urban
background site (20 m a.g.l., PM<inline-formula><mml:math id="M10" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> inlet). The rural measurements
(July–August) were performed at the Hyltemossa Research Station, about 65 km northeast of Malmö–Copenhagen. This station is part of both the ACTRIS
(Aerosol, Clouds, and Trace gases European Research Infrastructure) and ICOS
(Integrated Carbon Observation System) European environmental research
infrastructure networks. The field site is surrounded by a managed spruce
forest. Aerosols were sampled at a height of 30 m above ground through
a PM<inline-formula><mml:math id="M11" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">10</mml:mn></mml:msub></mml:math></inline-formula> inlet and 25 mm stainless steel tube, at a flow rate of 16.7 L min<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The single-particle soot measurements at the rural site
were conducted through a <inline-formula><mml:math id="M13" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula>” tube at 20 L min<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
(turbulent flow), due to simultaneous eddy covariance flux measurements (not
described here).</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Instrumentation and analysis</title>
<sec id="Ch1.S2.SS2.SSS1">
  <label>2.2.1</label><title>Overview</title>
      <p id="d1e441">Instrumentation to measure aerosols and gases was similar at both sites.
Figure 1 shows during which time the urban and rural campaigns took place
and which data were used. BC properties and concentrations were determined
using an SP2 that was moved between the sites and Aethalometers (AE33)
deployed permanently. Aethalometer data for the whole year were used from the
rural site to assess source regions. The particle size distribution was
measured using scanning (urban) and differential (rural) mobility particle
sizers (SMPS and DMPS). During the latter part of the urban campaign, chemically resolved
particle constituents were measured simultaneously at both sites with soot
particle aerosol mass spectrometers (SP-AMSs). An aerosol particle mass
analyzer (APM) was at a later stage deployed at the urban site together with
a differential mobility analyzer (DMA) to measure the size-resolved
effective density and particle mass.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e446">Overview of the data and instruments used. Not shown in
the figure are DMA–APM measurements of effective density during spring
2019.</p></caption>
            <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f01.png"/>

          </fig>

</sec>
<sec id="Ch1.S2.SS2.SSS2">
  <label>2.2.2</label><title>SP2</title>
      <p id="d1e463">The SP2 (Droplet Measurement Technologies) measures the refractory black
carbon (rBC) mass of individual particles using laser-induced incandescence
(LII) (Stephens et al., 2003; Schwarz et al., 2006). In the SP2, particles
are passed through a continuous 1064 nm Nd:YAG laser beam. Light-absorbing
particles (such as soot) are heated by the laser to temperatures where they
will start to incandesce if they are large enough. The incandescent light,
measured by optical detectors, is linearly proportional to the BC core mass
and independent of particle coating and fractal structure (Schwarz et al.,
2006; Slowik et al., 2007). The approximate range of the SP2 is 0.5–200 fg per particle, where the lower limit is due to energy dissipation, and the
particles in the upper limit may either saturate the detectors or not absorb
enough energy to incandesce. The overall relative uncertainty in mass
concentration by the SP2 was estimated by Sharma et al. (2017) to be within
25 %–38 %. To limit the data collected, not all particle peak signals were
saved (10 % and 1 %–5 % was saved in the rural and urban campaigns, respectively).</p>
      <p id="d1e466">The SP2 incandescence channels were calibrated using monodisperse Aquadag
(provided by Droplet Measurement Technologies) before, during and after the
field campaigns. Particle sizes were selected using a DMA, and mass was
calculated using the effective density recommended by Gysel et al. (2011).
Since the calibration during the rural campaign did not yield satisfactory
data, the calibration during the urban campaign was used to analyze both
datasets. Although this is not optimal, the incandescence detector
calibration is relatively stable in time. The response of the broadband
incandescence detector from typical ambient BC particle masses varied by
less than <inline-formula><mml:math id="M15" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> % for calibrations performed before and after the
rural campaign. The SP2 sensitivity to ambient BC has been shown to resemble
that of fullerene soot particles (Baumgardner et al., 2012). Following
Laborde et al. (2012b), the Aquadag calibration factors were therefore
translated into a fullerene soot equivalent calibration using a scaling
factor of 1.34 at 8.9 fg and an intercept of 0.</p>
      <p id="d1e479">The calibrations and campaign data were processed using the PSI SP2 toolkit
version 4.111. BC particles with mass equivalent diameters of between 64 and 580 nm (using a density of 1800 kg m<inline-formula><mml:math id="M16" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) were included in the result. The lower size
was selected from looking at the sharp decrease in the number–size
distribution when including very low peak heights. The mass and number
concentrations presented are not corrected for particles outside this range.
Pileci et al. (2021) found that the rBC mass outside the range of the SP2 is
on the order of 20 % for several European background<?pagebreak page3054?> stations, depending
on the size distribution. No particle detection efficiency calibration was
performed. Lognormal fits to averages of 2 and 24 h were used to calculate
geometric mean diameters.</p>
      <p id="d1e494">BC particle coatings can be estimated by the SP2 using a separate scattering
detector. The delay time method was used to estimate BC particle coatings in
a qualitative way (Moteki and Kondo, 2007; Subramanian et al., 2010). This
method separates BC particles as being either thinly or thickly coated
depending on the delay time between the maximum scattering and incandescence
peak heights. Coated BC particles generate two scattering peaks: one from
the evaporating coating and one from the BC core itself. The scattering
signal of the coating will be detected before the incandescence signal since
BC particles take some time to heat up to the point of incandescence, and
absorbed energy will dissipate through evaporation of the coating material.
For thickly coated particles, the scattering of the coating will exceed the
scattering of the BC core, while for thinly coated particles the opposite is
true. Moteki and Kondo (2007) and Laborde et al. (2012a) showed that a
coating volume fraction of 70 % is needed for a particle to be classified
as thickly coated by the SP2.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS3">
  <label>2.2.3</label><title>Aethalometer</title>
      <p id="d1e505">Aerosol light absorption was measured at both sites using a seven wavelength
Aethalometer (model AE33, Magee Scientific) (Drinovec et al., 2015).
Equivalent black carbon (eBC) mass concentrations were calculated using
absorption at 880 nm and the default mass absorption cross section (MAC)
value of 7.77 m<inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> g<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The absorption Ångström exponent
(AAE), a measure of the spectral dependence of light absorption and commonly
used in source apportionment of BC (Kirchstetter et al., 2004; Sandradewi et
al., 2008), was calculated between the wavelengths 370–950 nm. The
relative uncertainty of the absorption coefficient measured by the
Aethalometer increases with lower BC mass concentrations and has been shown
to converge around 30 % for an older version of the instrument (Backman
et al., 2017). The uncertainty of eBC also includes the uncertainty in the
MAC value, which was not estimated in the present study.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS4">
  <label>2.2.4</label><title>SP-AMS</title>
      <p id="d1e537">The chemical composition of refractory and non-refractory particulate mass
was measured in real time with two soot particle aerosol mass spectrometers
(SP-AMS, Aerodyne Research Inc.) (Onasch et al., 2012): one each at the urban and
rural measurement site. The measurements were performed in
parallel, and there are 15 d of overlap (25 September to 10 October). The SP-AMS
detects particles within the vacuum aerodynamic diameter size range of about
70 nm to 1 <inline-formula><mml:math id="M19" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m. The aerosol sample flow is focused through an
aerodynamic lens. The (non-refractory) components of particles in the air
beam are vaporized on a heated tungsten plate (600 <inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C), subjected
to 70 eV electron ionization, and the ions produced are detected and
categorized (organic, nitrate, sulfate, ammonium or chloride) by a
high-resolution time-of-flight mass spectrometer. In the SP-AMS setup a
laser is used to also vaporize the refractory BC (rBC). We operated both
SP-AMSs in the “dual vaporizer” configuration as further discussed in the
Supplement. Calibrations were performed in the field using 300 nm mobility diameter
particles from nebulizing ammonium nitrate as described in Onasch et al. (2012). The absolute concentrations of species at the urban site are not
shown due to uncertainties in the calibration and dissimilarities when
comparing to other instruments. For the rural data, PM<inline-formula><mml:math id="M21" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> derived from
the DMPS (using a density of 1.5 g cm<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and a Palas Fidas 200 at a
nearby site agreed well with that from the SP-AMS. All rBC data presented in
this work are derived from the SP2 measurements which are more accurate.
Data analysis was performed with IGOR Pro 7 (Wavemetrics, USA) and the AMS
analysis software package including SQUIRREL 1.61F and PIKA 1.21F.</p>
      <p id="d1e578">For the urban dataset, the fresh traffic aerosol was isolated through
the selection of distinct traffic plumes, i.e., short (seconds to minutes)
increase in concentration. Increases in rBC number concentration from the
SP2 and the concentration of the hydrocarbon-like organic aerosol (HOA) marker ion C<inline-formula><mml:math id="M23" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>H<inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">9</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> from
the AMS were used as indicators of fresh<?pagebreak page3055?> traffic plumes, and 90 such plumes
were selected. For each plume, the current urban background aerosol was
defined by selecting two windows, one before and one after the plume, of
about 2 min, i.e., a total of 4 min (see Figs. S2). The typical
plume duration was about 30–60 s. Organic aerosol (OA) mass spectra
from the AMS were calculated for the plume and for the background, respectively, and the background spectra were subtracted from the plume
spectra to obtain a net contribution to OA mass concentrations. The <inline-formula><mml:math id="M25" display="inline"><mml:mrow><mml:mi>m</mml:mi><mml:mo>/</mml:mo><mml:mi>z</mml:mi></mml:mrow></mml:math></inline-formula>
tracer method (Ng et al., 2011) was used to estimate the different OA
components.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS5">
  <label>2.2.5</label><title>DMPS and SMPS</title>
      <p id="d1e623">Particle size distributions were measured between electrical mobility
diameters of 3.2–900 nm at the rural site and 11.5–604 nm at the urban
site. At the rural site the DMPS consisted of two Hauke type DMAs and two
condensation particle counters (CPCs, TSI 3772 and TSI UCPC 3025)
(Wiedensohler et al., 2012). At the urban site the SMPS consisted of a TSI
DMA 3082 and a TSI CPC 3772. At both sites, the aerosol was dried before
sizing using Permapure driers with low-pressure sheath air. Size
distributions at both sites were averaged over 1 h.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS6">
  <label>2.2.6</label><title>DMA–APM</title>
      <p id="d1e634">Size-dependent particle mass and effective density were measured with a
DMA–APM. Pre-selection of particle size was done with a DMA (TSI 3082),
which selects particles based on electrical mobility diameter. The
quasi-monodisperse aerosol was then led through the APM (model 3600,
Kanomax), which measures the relationship between electrical mobility and
particle mass. In the APM, the aerosol passes a rotating cylinder with an
applied voltage, and the particle mass is determined based on the balance
equation between the centrifugal force and electrostatic force (McMurry et
al., 2002). The mass selected particles were counted after the DMA–APM with
a CPC (TSI 3772). The aerosol flow was 1 L min<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The effective
density is calculated based on the electrical mobility diameter and the
particle mass from the DMA–APM. For spherical particles, this is the bulk
density, but for non-spherical particles, the effective density depends on
the particle shape factor. Six different particle mobility diameters were
tested: 50, 75, 100, 150, 250 and 350 nm. The APM was operated in a
constant RPM (revolutions per minute) mode, where the angular rotation speed was constant and the APM
voltage was increased step-wise during a time period of 15 min per scan.
The rotational speed and voltage were selected so that the effective density
was measured in approximately the range 0.1–3.5 g cm<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The APM was run
during 5 d in spring 2019, after the intensive campaigns to verify the
bimodality, in terms of effective density, of the city aerosol.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S2.SS2.SSS7">
  <label>2.2.7</label><title>Particle inlet losses</title>
      <p id="d1e670">Particle losses in the inlets were assessed using the Particle Loss
Calculator (von der Weiden et al., 2009). The losses in the longest tube
sections of each inlet that was used are shown in Fig. S3. Losses in
additional tubing and the actual inlets are expected to be similar (and
small) in all cases. In the laminar flow inlets at both sites, PM<inline-formula><mml:math id="M28" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>
losses are negligible, while the turbulent flow inlet has losses of 20 %–30 % for spherical particles with a diameter between 100–1000 nm (density
1600 kg m<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). Based on these calculations and the measured rBC size
distribution (discussed below), the SP2 mass and number concentrations
measured at the rural site have been adjusted to correct for 25 % and 30 %
losses, respectively, since adjusting by size is not possible because the size
of rBC cores including coating was not measured.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS8">
  <label>2.2.8</label><title>Trajectory analysis</title>
      <p id="d1e702">Wind direction and speed data from the rural site at Hyltemossa were
downloaded from the ICOS Carbon portal (ICOS, 2019) and analyzed using the
Igor pro tool Zefir (Petit et al., 2017). To investigate how the air mass
origin influences the BC concentrations at the rural site, we used the Hybrid
Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with
meteorological data from the Global Data Assimilation System (GDAS) (Stein
et al., 2015; Rolph et al., 2017). Seven-day HYSPLIT backward trajectories,
arriving with 1 h intervals at 100 m a.g.l. at Hyltemossa, were
calculated for the year 2018. The air masses were then classified into four
different categories depending on which geographical region the air masses
spent most time over. For this classification we only considered the air
mass origin during the last 48 h upwind of Hyltemossa and the cumulative
time which the transported air parcels were below 1000 m a.g.l. Figure S4
in the Supplement illustrates how the air mass origin was
divided into northwesterly (NW), southwesterly (SW), southeasterly (SE)
and northeasterly (NE). In addition we separated the air mass origin
depending on if the air masses passed over the Malmö–Copenhagen region less than
12 h before they arrived at Hyltemossa.</p>
      <p id="d1e705">The long-distance transported BC source contributions during the rural and
urban measurement campaigns were estimated using the Lagrangian 1D-column
chemistry transport model ADCHEM (Roldin et al., 2011; Roldin et al., 2019).
ADCHEM was set up and run forward in time along pre-computed 14 d backward
HYSPLIT air mass trajectories arriving 100 m a.g.l. at Hyltemossa, with one new
trajectory every hour. Source-specific anthropogenic BC emissions along the
trajectories were taken from the CAMS-GLOB-ANT v4.2 global emission
inventory, which has a spatial resolution of <inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.1</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:mn mathvariant="normal">0.1</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>
(Granier et al., 2019). BC emissions from wildfires were estimated using the
GFED4 emission inventory (Randerson et al., 2018).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e730">Diurnal cycles of rBC mass concentrations (<inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>)
from the urban and rural sites as measured by the SP2. Values are averages
of data collected during 34 (rural) and 41 (urban) days of sampling.</p></caption>
            <?xmltex \igopts{width=184.942913pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f02.png"/>

          </fig>

<?xmltex \hack{\newpage}?>
</sec>
</sec>
</sec>
<?pagebreak page3056?><sec id="Ch1.S3">
  <label>3</label><title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>BC concentrations</title>
      <p id="d1e770">An overview of the BC measurement results is shown in Table 1. As expected,
the curbside site has higher concentrations than the rural site, with
campaign average factors of 2.5 for rBC mass, 2.2 for eBC mass and 3.2 for
rBC number concentration. The differences in concentrations are due to local
emissions, clearly shown in the diurnal pattern (Fig. 2), which follows
traffic intensity. The comparison between the urban street level and urban
background eBC levels are very similar in time series but with a lower daily
maximum for the rooftop measurements (Fig. S5). This suggests that the
curbside measurements are indicative of the city. The average eBC mass
concentration at the rooftop site during the campaign was 15 % lower than
at the curbside site. The largest difference between the urban and rural
sites occur during morning rush hour when rBC mass concentrations are up to
a factor 3.7 higher in the city. The mass concentrations are still higher in
the city during nighttime, before the first rush hour peaks, but only by a
factor of 1.2–1.3. The weekends have lower rBC mass concentration (<inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">rBC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
of <inline-formula><mml:math id="M33" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.11</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.06</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M34" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) compared to weekdays in the city,
but it is still a factor of 1.8 higher than the average for the rural
background station. The AAE is slightly higher at the urban site, which
could be due to the differences in BC size distribution and coating
(Virkkula, 2021).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e819">Averages <inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula> (original averaging time in
parentheses) for the urban and rural campaigns. rBC mass (<inline-formula><mml:math id="M37" display="inline"><mml:mi>M</mml:mi></mml:math></inline-formula>) and number (<inline-formula><mml:math id="M38" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula>)
concentrations are from SP2 measurements, and eBC mass concentrations are
from absorption at 880 nm using a MAC of 7.77 m<inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> g<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Mass-based
geometric mean diameter (GMD<inline-formula><mml:math id="M41" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">M</mml:mi></mml:msub></mml:math></inline-formula>) and geometric standard deviation
(GSD<inline-formula><mml:math id="M42" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">M</mml:mi></mml:msub></mml:math></inline-formula>) are from the rBC mass equivalent size distribution. rBC
concentrations are not corrected for particles outside the range of the
instrument. Rural rBC concentrations are corrected for inlet losses.
Absorption Ångström exponents (AAE) are calculated between
absorption at 370 and 950 nm.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Rural</oasis:entry>
         <oasis:entry colname="col3">Urban</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">rBC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (1 h), <inline-formula><mml:math id="M44" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.06</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.15</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.11</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:msub><mml:mi>M</mml:mi><mml:mi mathvariant="normal">eBC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (1 h), <inline-formula><mml:math id="M49" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M50" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.22</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.16</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.49</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.45</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">rBC</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (1 h), cm<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:mn mathvariant="normal">31</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">21</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M56" display="inline"><mml:mrow><mml:mn mathvariant="normal">100</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">80</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GMD<inline-formula><mml:math id="M57" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">M</mml:mi></mml:msub></mml:math></inline-formula> (24 h), nm</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:mn mathvariant="normal">168</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">12</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mn mathvariant="normal">141</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">11</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GSD<inline-formula><mml:math id="M60" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">M</mml:mi></mml:msub></mml:math></inline-formula> (24 h), nm</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M61" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.74</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.08</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.77</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AAE<inline-formula><mml:math id="M63" display="inline"><mml:msub><mml:mi/><mml:mtext>370–950 nm</mml:mtext></mml:msub></mml:math></inline-formula> (1 h)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.13</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.12</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.24</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.26</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Estimation of BC particle number fractions</title>
      <p id="d1e1223">The number fraction of particles containing a BC core was estimated by
comparing the daily average of BC number concentration from the SP2 to the
number concentration of particles larger than 64 nm as measured by the
mobility particle sizers. At the rural site this fraction was <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.7</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.6</mml:mn></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>) %, while for the urban site the fraction was <inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mn mathvariant="normal">13.4</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">5.5</mml:mn></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>) %. These estimates are biased low because the BC
size distribution (as measured by a mobility particle sizer) is shifted to
larger sizes if shape factors and coating are added. If the cutoff
size for total particle number measured by the SMPS is increased to <inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:msub><mml:mi>D</mml:mi><mml:mi mathvariant="normal">P</mml:mi></mml:msub><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">130</mml:mn></mml:mrow></mml:math></inline-formula> nm (assuming a coating thickness of similar magnitude as the rBC core
mass equivalent diameter), the fractions are increased to 6 % in the rural
campaign and 45 % in the urban campaign. In a study outside Paris
(Laborde et al., 2013), the number of BC particles counted by the SP2 (with
no correction for particles outside the measurement range) was 0 %–15 % of
the total particle number concentration (above 20 nm) measured by an SMPS.
In airborne measurements over Europe (using an SP2 and a passive cavity
aerosol spectrometer probe), Reddington et al. (2013) found that the number
fraction of approximately 14 % of particles with dry diameters above 260 nm contained a BC core. In an older study, Rose et al. (2006), using a
volatility tandem-DMA setup, measured summertime BC particle number
fractions of 2 %–7 % at a rural site and 20 %–60 % in a street canyon,
depending on the selected size (30–150 nm in mobility diameter).</p>
</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>rBC vs. eBC</title>
      <p id="d1e1293">The difference between rBC and eBC is significant at both sites (Fig. S6).
For the full campaign averages, eBC is more than 3 times higher than rBC at
both sites, with median ratios (eBC <inline-formula><mml:math id="M71" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> rBC) of 3.04 and 3.65 at the urban and
rural sites, respectively. Several studies have found similar discrepancies
between rBC and eBC (Holder et al., 2014; Raatikainen et al., 2015; Sharma
et al., 2017; Tasoglou et al., 2018; Li et al., 2019). The rBC mass in this
study is biased low because of<?pagebreak page3057?> the limited range of the SP2, but given the
size distributions measured (example shown in Fig. S7), this mass bias
should be on the order of 10 %–20 %, which would still only lower the ratio
between eBC and rBC to 2.4–2.7. One reason for biased high eBC values is
that the measured absorption can be amplified by non-absorbing coatings of
BC cores (Kalbermatter et al., 2022). It is well known that site-specific
MAC can differ from the default values from the manufacturer of the AE33
(e.g., Cui et al., 2016). At a site nearby the rural site of this study, a
MAC of 12.64 m<inline-formula><mml:math id="M72" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> g<inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at 880 nm has previously been derived using
Aethalometer (AE33) absorption coefficients and elemental carbon (EC)
measurements (Martinsson et al., 2017). This value is 1.6 times higher than
the default, and if it is used, the ratio between eBC and rBC of the rural campaign
would be <inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e1336">Average mass size distribution of BC cores for the urban (black)
and rural (orange) campaigns. Filled areas show <inline-formula><mml:math id="M75" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>. Insert
shows the normalized distribution for comparison of the modes. Dip at 270 nm is due to erroneous stitching of high and low gain detector channels.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f03.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS4">
  <label>3.4</label><title>BC core size and coating</title>
      <p id="d1e1365">The average geometric mean diameter (GMD) of the rBC mass size distribution,
from lognormal fits of 24 h data, was highest in the rural setting (Table 1). The average mass size distributions for the full campaigns are shown in
Fig. 3. Mass equivalent diameters of 168 and 148 nm for the rural and urban
sites, respectively, correspond to BC particle masses of 4.5 and 3.1 fg. The
number size distribution generally peaked close to the SP2 detection limit
(64 nm, corresponding to 0.25 fg, for both campaigns), and the GMD of this
distribution is therefore more uncertain and not presented here. An example
of 24 h number and mass size distributions are shown in Fig. S7. The
difference in mass GMD is statistically significant (<inline-formula><mml:math id="M76" display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>) and
can be explained by different BC particle sources, air masses and
coagulation. Figure S1 shows that while BC concentrations at the rural site
were similar during the two campaigns, the source sectors changed slightly.
Notably, more industrial emissions and less shipping emissions affected the
concentrations during the urban campaign. Figure 4 shows the diurnal
variation in GMD from mass size distributions averaged over 2 h. The urban
site has a higher fraction of particles coming from local traffic, which
have been shown to be smaller than particles from, e.g., biomass burning
(Schwarz et al., 2008; Laborde et al., 2013; Saarikoski et al., 2021). This
shifts the size distribution during daytime to slightly lower sizes,
although the measurement uncertainties, including calibrations, of the SP2
are close to the difference in average GMD between the sites.</p>
      <p id="d1e1380">The BC particles at the rural site were characterized by a thicker coating
than at the urban location, as measured by the SP2 delay time method (a
typical example is shown in Fig. S8). The fraction of “thickly coated” BC
particles with an incandescence peak height corresponding to a BC core
diameter of mass 2.4 fg (<inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">136</mml:mn></mml:mrow></mml:math></inline-formula> nm mass equivalent diameter)
was on average <inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:mn mathvariant="normal">71</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">8</mml:mn></mml:mrow></mml:math></inline-formula> % (<inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>) at the rural site and <inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mn mathvariant="normal">38</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">7</mml:mn></mml:mrow></mml:math></inline-formula> % (<inline-formula><mml:math id="M81" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>) at the urban site, with no big difference during
weekends. The short-term APM measurements verified the bimodal structure in
effective density of the urban aerosol. The mass distribution of 150 nm particles is shown in Fig. 5. The two modes suggest that the aerosol is
externally mixed, with more and less dense particles present. The two
lognormal curve fittings have a mean mass of <inline-formula><mml:math id="M82" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.86</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula> fg and <inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.49</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula> fg, respectively. These masses correspond to effective
densities of <inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.49</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.41</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> g cm<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, respectively, which is very similar to the effective densities
presented by Rissler et al. (2014), who reported two effective densities for 150 nm particles sampled in downtown Copenhagen of <inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.53</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.36</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.15</mml:mn></mml:mrow></mml:math></inline-formula> g cm<inline-formula><mml:math id="M89" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. For 50 and 75 nm particles, the average mass distribution was unimodal with a mean mass of
<inline-formula><mml:math id="M90" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.062</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.001</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M91" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.26</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> fg, respectively, corresponding
to effective densities of <inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.95</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M93" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.19</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula> g cm<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The average mass distribution of 100 nm particles was bimodal with
mean masses of <inline-formula><mml:math id="M95" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.33</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.68</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> fg, corresponding
to effective densities of <inline-formula><mml:math id="M97" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.63</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M98" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.29</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> g cm<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. These values are also similar to the densities in Rissler et al. (2014), but we did not observe an additional mode at higher masses for 50
and 75 nm particles but only the less dense, fresh soot mode. However, in
single APM spectra, the mean mass mode was sometimes different from the
average, and on a couple of occasions, a bimodal distribution was observed
also for the smaller particles. No mass mode could be extracted for APM
measurements of larger particle sizes (250 and 350 nm) due to low particle
concentrations and consequently poor counting statistics.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><?xmltex \currentcnt{4}?><?xmltex \def\figurename{Figure}?><label>Figure 4</label><caption><p id="d1e1658">Box plot showing the daily pattern of rBC GMD (2 h averages) as
measured by the SP2, at the urban and rural sites. Boxes show the median and the 25th and 75th percentiles, with values more than 1.5 below or
above those considered outliers (<inline-formula><mml:math id="M100" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>).</p></caption>
          <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f04.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><?xmltex \currentcnt{5}?><?xmltex \def\figurename{Figure}?><label>Figure 5</label><caption><p id="d1e1677">Measured DMA–APM spectrum for urban particles with a diameter of
150 nm (black markers). The spectrum is the average number concentration
(arbitrary units) of 11 samples from all sampling days. Two lognormal
fits are shown in black.</p></caption>
          <?xmltex \igopts{width=184.942913pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f05.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><?xmltex \currentcnt{6}?><?xmltex \def\figurename{Figure}?><label>Figure 6</label><caption><p id="d1e1688">Wind rose showing the frequency of different wind directions
(30<inline-formula><mml:math id="M101" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> resolution) during the rural campaign and corresponding
concentrations of eBC.</p></caption>
          <?xmltex \igopts{width=199.169291pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f06.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><?xmltex \currentcnt{7}?><?xmltex \def\figurename{Figure}?><label>Figure 7</label><caption><p id="d1e1708">Trajectory analysis of different air mass origins, with
corresponding median eBC mass concentrations in the legend. Panel <bold>(a)</bold> shows
histograms with the observed eBC from the Aethalometer at Hyltemossa from
the year 2018 for air masses originating from the southeast, northeast, northwest and southwest as defined in
Fig. S4. Panel <bold>(b)</bold> shows the eBC histogram from all SW air masses with or
without influence from the Copenhagen (CPH) and Malmö region.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f07.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS5">
  <label>3.5</label><title>Origins of BC in the rural background air</title>
      <p id="d1e1732">Figure 6 shows the wind direction probability together with eBC from the 5-week rural campaign. The Malmö–Copenhagen area is in the direction
200–230<inline-formula><mml:math id="M102" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> as seen from the rural site. Based on the HYSPLIT
trajectory analysis (Sect. 2.2.8), some peaks in eBC, non-refractory PM<inline-formula><mml:math id="M103" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and total particle number concentrations at the rural site coincide with air
masses originating over Malmö–Copenhagen. These urban plumes were
discernible when the air mass was relatively clean (typically of western or
northwestern origin). However, no conclusive results on the influence of
the urban site on rural levels could be derived from analysis of the limited
field campaign data. Also, when analyzing the complete eBC dataset from 2018, there is no significant difference in the median eBC concentration for air
masses with and without influence from Copenhagen and/or Malmö,
according to the trajectory analysis. However, if we only consider air
masses with insignificant precipitation within 48 h upwind of the rural
site (i.e., less than <inline-formula><mml:math id="M104" display="inline"><mml:mrow><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> mm precipitation according the HYSPLIT
model), the measured eBC median concentration is significantly higher in the
air masses that have moved over Copenhagen–Malmö, 354.7 ng m<inline-formula><mml:math id="M105" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> compared
to 226.9 ng m<inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> without influence from Copenhagen–Malmö. Similar results
are also found when only the air masses originating from the southwest are considered
(see Fig. 7 and Tables S2–S4). Most likely the contribution from the BC
emissions from Copenhagen–Malmö is not apparent when analyzing the whole
eBC dataset from 2018 because the SW air masses are generally influenced by
more precipitation (more BC wet scavenging) compared to other air masses.
The HYSPLIT trajectory simulations for the complete year show that 66 %
of all air masses that passed over Malmö–Copenhagen were influenced by
<inline-formula><mml:math id="M107" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> mm precipitation within 48 h upwind of the rural site,
compared to 39 % for all other air masses. The lowest median eBC
concentration is found in air masses from the northwest (101 ng m<inline-formula><mml:math id="M108" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) followed by NE air
masses (149.9 ng m<inline-formula><mml:math id="M109" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and SW air masses (192.0 ng m<inline-formula><mml:math id="M110" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). SE air masses
clearly stand out from any other air masses, with a median eBC concentration
of 563 ng m<inline-formula><mml:math id="M111" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. This can be partly explained by the low probability of
precipitation in SE air<?pagebreak page3059?> masses. Only 23 % of these air masses are
influenced by <inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> mm precipitation within 48 h upwind of the
rural site. However, when also considering the effect of precipitation
upwind of Hyltemossa, the SE air masses have a median eBC concentration that is
<inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> times larger than the SW air masses.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><?xmltex \currentcnt{8}?><?xmltex \def\figurename{Figure}?><label>Figure 8</label><caption><p id="d1e1869">Concentrations of eBC and PM<inline-formula><mml:math id="M114" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> chemical species at both sites
during overlapping urban and rural measurement periods. One-hour averages for
eBC; 20 min for PM<inline-formula><mml:math id="M115" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> chemical species. It was not possible to extract absolute concentrations of
PM<inline-formula><mml:math id="M116" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> at the urban site to uncertainties
in the calibration.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f08.png"/>

        </fig>

      <p id="d1e1905">A comparison of the 15 d of simultaneous urban and rural measurements is
shown in Fig. 8. It is clear that non-refractory PM<inline-formula><mml:math id="M117" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> concentration and
composition are driven by long-range pollution at both sites, while black
carbon is more influenced by local emissions. The organic aerosol at the
urban site was clearly dominated by oxygenated organic aerosol (OOA, 78 %)
with only a minor contribution of HOA (9 %), suggesting that aged
long-range sources dominate even the organic aerosol, for which one could
expect a larger difference between the sites owing to the high urban traffic
density (Glasius et al., 2011). However, in the original time resolution of
20 s (not shown), the urban AMS data feature transient plumes of
traffic exhaust. Yet, as shown in Fig. 8, these plumes have little impact on
average concentration. The OA mass spectrum from traffic plumes at the
curbside site is shown in Fig. S9. The plume spectra are similar in mass
spectral profiles to hydrocarbon-like organic aerosol (HOA), commonly
associated with traffic emissions. This OA is likely present in thin
coatings on the freshly emitted traffic BC and possibly also externally
mixed with the BC and hence is not detected by the SP2 time delay method.</p>
      <p id="d1e1918">With regards to eBC, Fig. 8 shows that approximately half of the mass at the
urban site is due to long-range transport, despite the high traffic
intensity (about 30 000 vehicles per day). This can be deduced from the
temporal variability and absolute concentrations at both sites. The result
is corroborated by the rBC results shown in Fig. 2. Firstly, rBC
concentrations are roughly doubled at the urban site compared to the rural
site. Secondly, the diurnal pattern observed at the urban site (see Fig. 2) shows that levels between 1:00 and 5:00 LT, during which local
traffic density is low, are about half of the average concentration.</p>
      <p id="d1e1921">Consistent with the high abundance of BC from long-range transport at the
urban site, on average 40 % of urban BC particles with a diameter close
to the mass GMD were found to be thickly coated based on the SP2 data. We
did not directly measure the chemical composition of the thick coatings.
However, as shown in Fig. 9, non-refractory PM<inline-formula><mml:math id="M118" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> concentration is highly
correlated with thickly coated BC fraction (<inline-formula><mml:math id="M119" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.87</mml:mn></mml:mrow></mml:math></inline-formula>). Indeed, all
major chemical species in non-refractory PM<inline-formula><mml:math id="M120" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> correlate well with the
thickly coated BC fraction (<inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 0.82–0.88). This suggests that
the BC coatings are similar in composition to non-refractory PM<inline-formula><mml:math id="M122" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>
(dominated by secondary material), despite the fact that only a minor
fraction of the particles in PM<inline-formula><mml:math id="M123" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> contains rBC as discussed above. As non-refractory PM<inline-formula><mml:math id="M124" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> is more widely and accurately measured than BC coating
composition, such homogeneity simplifies the assessment of BC properties and
impacts, for example concerning cloud formation and lung deposition.
However, direct measurements of BC coating composition, ideally on a single-particle basis, are needed to support this conjecture.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{9}?><?xmltex \def\figurename{Figure}?><label>Figure 9</label><caption><p id="d1e2000">Comparison of chemically resolved non-refractory PM<inline-formula><mml:math id="M125" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>
concentration and the fraction of thickly coated BC cores, with a mass
equivalent diameter corresponding to <inline-formula><mml:math id="M126" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">136</mml:mn></mml:mrow></mml:math></inline-formula> nm, in the urban
setting. Left: time series. Right: scatterplots of thickly coated BC
particle fraction vs. non-refractory PM<inline-formula><mml:math id="M127" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and subcategories thereof; 24 h averages.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/23/3051/2023/acp-23-3051-2023-f09.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Summary and conclusions</title>
      <p id="d1e2046">During 11 weeks in 2018, BC particles were sampled at two nearby sites in
southern Sweden. Campaign average mass<?pagebreak page3060?> concentrations of BC, measured with
two different methods, were a factor of 2.2–2.5 higher at the urban site,
compared to the rural background site. Hourly averages during rush hour
peaks were up to a factor 4 higher in the city. Despite good correlation
between rBC and eBC, a factor of 3 higher concentrations was consistently
measured with the optical method. The number fraction of particles
containing BC, compared to total particle concentration above 64 nm in
mobility diameter, was 2.4 % and 13.4 % at the rural and urban sites,
respectively. However, these numbers depend strongly on the sizes that are
integrated and would ideally be measured and reported in a size-segregated
manner using pre-selection of particles. The BC particle size distributions
were similar, with peak mode diameters slightly smaller in the city, which
can be expected since a larger fraction of the particles are from fresh
traffic emissions. This was also seen in the BC particle coating, which was
assessed in a qualitative manner. The rural site had approximately double
the amount of thickly coated particles compared to the street measurements.</p>
      <?pagebreak page3061?><p id="d1e2049"><?xmltex \hack{\newpage}?>Simultaneous measurements using SP-AMS at both sites showed similarities in
both time series and mass spectra of the organic aerosol, verifying the
impact of long-range aerosol and secondary aerosol production. Primary
organic aerosol mass spectra were investigated based on transient plumes
from local traffic at the urban site but composed a small fraction of the
total organic aerosol. The fraction of thickly coated particles at the urban
site was highly correlated to all measured species of the AMS, again showing
the importance of long-range transport.</p>
      <p id="d1e2053">Plumes from the nearby urban site to the rural site were not clearly
distinguishable during the field campaigns. Trajectory analysis of the full
year of 2018 shows that significant increases in eBC concentrations at the
rural site for air masses passing over the Malmö–Copenhagen area are
only clearly seen during days with low precipitation. This increase,
however, is small in comparison with the influence of long-range-transported
BC. Transport of BC from continental, and especially eastern, Europe is what
governs the BC concentrations in southern Sweden's background air when
looking at eBC from the full year of 2018.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e2061">Processed data for main results are available at
<ext-link xlink:href="https://doi.org/10.5281/zenodo.6559236" ext-link-type="DOI">10.5281/zenodo.6559236</ext-link> (Ahlberg, 2022).
Raw or specific
datasets are available from the authors upon request.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e2067">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-23-3051-2023-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-23-3051-2023-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e2076">EA: conceptualization, methodology, validation, formal analysis,
investigation, data curation, writing (original draft), visualization,
project administration. SA: validation, formal analysis, investigation, data
curation, writing (original draft), writing (review and editing). LN: formal
analysis, writing (review and editing), visualization. MS: investigation,
resources, data curation, writing (review and editing). JP: formal analysis,
writing (review and editing), visualization. JKN: resources, writing (review and editing). MB: writing (review and editing). HS: writing (review and editing). PR: methodology, software, formal analysis, resources, data
curation, writing (original draft), writing (review and editing),
visualization, funding acquisition. AK: formal analysis, data curation,
writing (review and editing). ES: conceptualization, methodology, resources,
writing (review and editing), supervision, project administration, funding
acquisition. AE: conceptualization, methodology, validation, formal
analysis, investigation, data curation, writing (original draft), writing (review and editing), visualization.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e2082">The contact author has declared that none of the authors has any competing interests.</p>
  </notes><?xmltex \hack{\newpage}?><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e2089">Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e2095">The authors would like to thank ICOS Sweden, especially Tobias Biermann,
Michal Heliasz, Jutta Holst and Thomas Holst, for meteorological data and
Hyltemossa station management and Paul Hansson at Malmö Environment
Department for help with setting up the urban station measurements and
Dalaplan station technical assistance.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e2100">This research has been supported by the Svenska Forskningsrådet Formas (grant nos. 2015-00994 and 2018-01745) and the Vetenskapsrådet (grant nos. 2019-05062, 2019-05006 and 2021-00177).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e2106">This paper was edited by Luis A. Ladino and reviewed by five anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><?label 1?><mixed-citation>Ahlberg, E.: ISSA figure data, <ext-link xlink:href="https://doi.org/10.5281/zenodo.6559236" ext-link-type="DOI">10.5281/zenodo.6559236</ext-link>, Zenodo [data set], 2022.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><?label 1?><mixed-citation>Alfoldy, B., Giechaskiel, B., Hofmann, W., and Drossinos, Y.:
Size-distribution dependent lung deposition of diesel exhaust particles, J.
Aerosol. Sci., 40, 652–663, <ext-link xlink:href="https://doi.org/10.1016/j.jaerosci.2009.04.009" ext-link-type="DOI">10.1016/j.jaerosci.2009.04.009</ext-link>, 2009.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><?label 1?><mixed-citation>Backman, J., Schmeisser, L., Virkkula, A., Ogren, J. A., Asmi, E., Starkweather, S., Sharma, S., Eleftheriadis, K., Uttal, T., Jefferson, A., Bergin, M., Makshtas, A., Tunved, P., and Fiebig, M.: On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic, Atmos. Meas. Tech., 10, 5039–5062, <ext-link xlink:href="https://doi.org/10.5194/amt-10-5039-2017" ext-link-type="DOI">10.5194/amt-10-5039-2017</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><?label 1?><mixed-citation>Baumgardner, D., Popovicheva, O., Allan, J., Bernardoni, V., Cao, J., Cavalli, F., Cozic, J., Diapouli, E., Eleftheriadis, K., Genberg, P. J., Gonzalez, C., Gysel, M., John, A., Kirchstetter, T. W., Kuhlbusch, T. A. J., Laborde, M., Lack, D., Müller, T., Niessner, R., Petzold, A., Piazzalunga, A., Putaud, J. P., Schwarz, J., Sheridan, P., Subramanian, R., Swietlicki, E., Valli, G., Vecchi, R., and Viana, M.: Soot reference materials for instrument calibration and intercomparisons: a workshop summary with recommendations, Atmos. Meas. Tech., 5, 1869–1887, <ext-link xlink:href="https://doi.org/10.5194/amt-5-1869-2012" ext-link-type="DOI">10.5194/amt-5-1869-2012</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><?label 1?><mixed-citation>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, <ext-link xlink:href="https://doi.org/10.1002/jgrd.50171" ext-link-type="DOI">10.1002/jgrd.50171</ext-link>, 2013.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib6"><label>6</label><?label 1?><mixed-citation>Corbin, J. C., Modini, R. L., and Gysel-Beer, M.: Mechanisms of
soot-aggregate restructuring and compaction, Aerosol. Sci. Tech.,
57, 89–111, <ext-link xlink:href="https://doi.org/10.1080/02786826.2022.2137385" ext-link-type="DOI">10.1080/02786826.2022.2137385</ext-link>, 2023.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><?label 1?><mixed-citation>Cui, X. J., Wang, X. F., Yang, L. X., Chen, B., Chen, J. M., Andersson, A.,
and Gustafsson, O.: Radiative absorption enhancement from coatings on black
carbon aerosols, Sci. Total Environ., 551, 51–56,
<ext-link xlink:href="https://doi.org/10.1016/j.scitotenv.2016.02.026" ext-link-type="DOI">10.1016/j.scitotenv.2016.02.026</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><?label 1?><mixed-citation>Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The ”dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, <ext-link xlink:href="https://doi.org/10.5194/amt-8-1965-2015" ext-link-type="DOI">10.5194/amt-8-1965-2015</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib9"><label>9</label><?label 1?><mixed-citation>
Eriksson, A., Wittbom, C., Roldin, P., Sporre, M., Öström, E.,
Nilsson, P., Martinsson, J., Rissler, J., Nordin, E., and Svenningsson, B.:
Diesel soot aging in urban plumes within hours under cold dark and humid
conditions, Sci. Rep., 7, 1–10, 2017.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><?label 1?><mixed-citation>Fierce, L., Onasch, T. B., Cappa, C. D., Mazzoleni, C., China, S., Bhandari,
J., Davidovits, P., Fischer, D. A., Helgestad, T., Lambe, A. T., Sedlacek,
A. J., Smith, G. D., and Wolff, L.: Radiative absorption enhancements by
black carbon controlled by particle-to-particle heterogeneity in
composition, P. Natl. Acad. Sci. USA,  117, 201919723,
<ext-link xlink:href="https://doi.org/10.1073/pnas.1919723117" ext-link-type="DOI">10.1073/pnas.1919723117</ext-link>, 2020.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><?label 1?><mixed-citation>Glasius, M., la Cour, A., and Lohse, C.: Fossil and nonfossil carbon in fine
particulate matter: A study of five European cities, J. Geophys. Res., 116, D11302, <ext-link xlink:href="https://doi.org/10.1029/2011JD015646" ext-link-type="DOI">10.1029/2011JD015646</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><?label 1?><mixed-citation>Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi,
N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse,
C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere
Monitoring Service global and regional emissions (April 2019 version),
Copernicus Atmosphere Monitoring Service (CAMS) report,
<ext-link xlink:href="https://doi.org/10.24380/d0bn-kx16" ext-link-type="DOI">10.24380/d0bn-kx16</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><?label 1?><mixed-citation>Gysel, M., Laborde, M., Olfert, J. S., Subramanian, R., and Gröhn, A. J.: Effective density of Aquadag and fullerene soot black carbon reference materials used for SP2 calibration, Atmos. Meas. Tech., 4, 2851–2858, <ext-link xlink:href="https://doi.org/10.5194/amt-4-2851-2011" ext-link-type="DOI">10.5194/amt-4-2851-2011</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><?label 1?><mixed-citation>Hakkarainen, H., Salo, L., Mikkonen, S., Saarikoski, S., Aurela, M.,
Teinilä, K., Ihalainen, M., Martikainen, S., Marjanen, P., and
Lepistö, T.: Black carbon toxicity dependence on particle coating:
Measurements with a novel cell exposure method, Sci. Total Environ., 834, 156543, <ext-link xlink:href="https://doi.org/10.1016/j.scitotenv.2022.156543" ext-link-type="DOI">10.1016/j.scitotenv.2022.156543</ext-link>, 2022.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><?label 1?><mixed-citation>
Hinds, W. C.: Aerosol technology: properties, behavior, and measurement of
airborne particles, John Wiley &amp; Sons,  ISBN 1118591976, 2012.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><?label 1?><mixed-citation>Holder, A. L., Hagler, G. S. W., Yelverton, T. L. B., and Hays, M. D.:
On-road black carbon instrument intercomparison and aerosol characteristics
by driving environment, Atmos. Environ., 88, 183–191,
<ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2014.01.021" ext-link-type="DOI">10.1016/j.atmosenv.2014.01.021</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><?label 1?><mixed-citation>
IARC: Diesel and gasoline engine exhausts and some nitroarenes, IARC
monographs on the evaluation of carcinogenic risks to humans,   105,  PubMedID 26442290, ISBN 978 92 832 01434, 2014.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><?label 1?><mixed-citation>ICOS, R. I.: ICOS ATC MTO Release, Hyltemossa (150.0 m),
26 September 2017–30 April 2019,
<uri>https://hdl.handle.net/11676/DbbmB-ppi1ZsmQzHfuQ9y_oY</uri> (last access: 18 January 2022), 2019.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><?label 1?><mixed-citation>IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P.,  Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA,  <uri>https://report.ipcc.ch/ar6/wg1/IPCC_AR6_WGI_FullReport.pdf</uri> (last access: 1 March 2023), 2021.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><?label 1?><mixed-citation>Kalbermatter, D. M., Močnik, G., Drinovec, L., Visser, B., Röhrbein, J., Oscity, M., Weingartner, E., Hyvärinen, A.-P., and Vasilatou, K.: Comparing black-carbon- and aerosol-absorption-measuring instruments – a new system using lab-generated soot coated with controlled amounts of secondary organic matter, Atmos. Meas. Tech., 15, 561–572, <ext-link xlink:href="https://doi.org/10.5194/amt-15-561-2022" ext-link-type="DOI">10.5194/amt-15-561-2022</ext-link>, 2022.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><?label 1?><mixed-citation>Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the
spectral dependence of light absorption by aerosols is affected by organic
carbon, J. Geophys. Res.-Atmos., 109, D21208, <ext-link xlink:href="https://doi.org/10.1029/2004jd004999" ext-link-type="DOI">10.1029/2004jd004999</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><?label 1?><mixed-citation>Laborde, M., Mertes, P., Zieger, P., Dommen, J., Baltensperger, U., and Gysel, M.: Sensitivity of the Single Particle Soot Photometer to different black carbon types, Atmos. Meas. Tech., 5, 1031–1043, <ext-link xlink:href="https://doi.org/10.5194/amt-5-1031-2012" ext-link-type="DOI">10.5194/amt-5-1031-2012</ext-link>, 2012a.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><?label 1?><mixed-citation>Laborde, M., Schnaiter, M., Linke, C., Saathoff, H., Naumann, K.-H., Möhler, O., Berlenz, S., Wagner, U., Taylor, J. W., Liu, D., Flynn, M., Allan, J. D., Coe, H., Heimerl, K., Dahlkötter, F., Weinzierl, B., Wollny, A. G., Zanatta, M., Cozic, J., Laj, P., Hitzenberger, R., Schwarz, J. P., and Gysel, M.: Single Particle Soot Photometer intercomparison at the AIDA chamber, Atmos. Meas. Tech., 5, 3077–3097, <ext-link xlink:href="https://doi.org/10.5194/amt-5-3077-2012" ext-link-type="DOI">10.5194/amt-5-3077-2012</ext-link>, 2012b.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><?label 1?><mixed-citation>Laborde, M., Crippa, M., Tritscher, T., Jurányi, Z., Decarlo, P. F., Temime-Roussel, B., Marchand, N., Eckhardt, S., Stohl, A., Baltensperger, U., Prévôt, A. S. H., Weingartner, E., and Gysel, M.: Black carbon physical properties and mixing state in the European megacity Paris, Atmos. Chem. Phys., 13, 5831–5856, <ext-link xlink:href="https://doi.org/10.5194/acp-13-5831-2013" ext-link-type="DOI">10.5194/acp-13-5831-2013</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib25"><label>25</label><?label 1?><mixed-citation>Li, H. Y., Lamb, K. D., Schwarz, J. P., Selimovic, V., Yokelson, R. J.,
McMeeking, G. R., and May, A. A.: Inter-comparison of black carbon
measurement methods for simulated open biomass burning emissions, Atmos.
Environ., 206, 156–169, <ext-link xlink:href="https://doi.org/10.1016/j.atmosenv.2019.03.010" ext-link-type="DOI">10.1016/j.atmosenv.2019.03.010</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><?label 1?><mixed-citation>Liu, D. T., Whitehead, J., Alfarra, M. R., Reyes-Villegas, E., Spracklen, D.
V., Reddington, C. L., Kong, S. F., Williams, P. I., Ting, Y. C., Haslett,
S., Taylor, J. W., Flynn, M. J., Morgan, W. T., McFiggans, G., Coe, H., and
Allan, J. D.: Black-carbon absorption enhancement in the atmosphere
determined by particle mixing state, Nat. Geosci., 10, 184–188,
<ext-link xlink:href="https://doi.org/10.1038/Ngeo2901" ext-link-type="DOI">10.1038/Ngeo2901</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><?label 1?><mixed-citation>Liu, H., Pan, X., Liu, D., Liu, X., Chen, X., Tian, Y., Sun, Y., Fu, P., and Wang, Z.: Mixing characteristics of refractory black carbon aerosols at an urban site in Beijing, Atmos. Chem. Phys., 20, 5771–5785, <ext-link xlink:href="https://doi.org/10.5194/acp-20-5771-2020" ext-link-type="DOI">10.5194/acp-20-5771-2020</ext-link>, 2020.</mixed-citation></ref>
      <?pagebreak page3063?><ref id="bib1.bib28"><label>28</label><?label 1?><mixed-citation>Malmborg, V. B., Eriksson, A. C., Török, S., Zhang, Y., Kling, K.,
Martinsson, J., Fortner, E. C., Gren, L., Kook, S., Onasch, T. B.,
Bengtsson, P.-E., and Pagels, J.: Relating aerosol mass spectra to
composition and nanostructure of soot particles, Carbon, 142, 535–546,
<ext-link xlink:href="https://doi.org/10.1016/j.carbon.2018.10.072" ext-link-type="DOI">10.1016/j.carbon.2018.10.072</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><?label 1?><mixed-citation>Martinsson, J., Abdul Azeem, H., Sporre, M. K., Bergström, R., Ahlberg, E., Öström, E., Kristensson, A., Swietlicki, E., and Eriksson Stenström, K.: Carbonaceous aerosol source apportionment using the Aethalometer model – evaluation by radiocarbon and levoglucosan analysis at a rural background site in southern Sweden, Atmos. Chem. Phys., 17, 4265–4281, <ext-link xlink:href="https://doi.org/10.5194/acp-17-4265-2017" ext-link-type="DOI">10.5194/acp-17-4265-2017</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib30"><label>30</label><?label 1?><mixed-citation>McMurry, P. H., Wang, X., Park, K., and Ehara, K.: The relationship between
mass and mobility for atmospheric particles: A new technique for measuring
particle density, Aerosol. Sci. Tech., 36, 227–238, <ext-link xlink:href="https://doi.org/10.1080/027868202753504083" ext-link-type="DOI">10.1080/027868202753504083</ext-link>, 2002.</mixed-citation></ref>
      <ref id="bib1.bib31"><label>31</label><?label 1?><mixed-citation>Michelsen, H. A., Colket, M. B., Bengtsson, P. E., D'Anna, A., Desgroux, P.,
Haynes, B. S., Miller, J. H., Nathan, G. J., Pitsch, H., and Wang, H.: A
Review of Terminology Used to Describe Soot Formation and Evolution under
Combustion and Pyrolytic Conditions, Acs Nano, 14, 12470–12490,
<ext-link xlink:href="https://doi.org/10.1021/acsnano.0c06226" ext-link-type="DOI">10.1021/acsnano.0c06226</ext-link>, 2020.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><?label 1?><mixed-citation>Moteki, N. and Kondo, Y.: Effects of mixing state on black carbon
measurements by laser-induced incandescence, Aerosol. Sci. Tech.,
41, 398–417, <ext-link xlink:href="https://doi.org/10.1080/02786820701199728" ext-link-type="DOI">10.1080/02786820701199728</ext-link>, 2007.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><?label 1?><mixed-citation>Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Zhang, Q., Ulbrich, I. M.,
and Worsnop, D. R.: Real-Time Methods for Estimating Organic Component Mass
Concentrations from Aerosol Mass Spectrometer Data, Environ. Sci. Technol., 45, 910–916, <ext-link xlink:href="https://doi.org/10.1021/es102951k" ext-link-type="DOI">10.1021/es102951k</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><?label 1?><mixed-citation>Onasch, T. B., Trimborn, A., Fortner, E. C., Jayne, J. T., Kok, G. L.,
Williams, L. R., Davidovits, P., and Worsnop, D. R.: Soot Particle Aerosol
Mass Spectrometer: Development, Validation, and Initial Application, Aerosol. Sci. Tech., 46, 804–817, <ext-link xlink:href="https://doi.org/10.1080/02786826.2012.663948" ext-link-type="DOI">10.1080/02786826.2012.663948</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><?label 1?><mixed-citation>Petit, J. E., Favez, O., Albinet, A., and Canonaco, F.: A user-friendly tool
for comprehensive evaluation of the geographical origins of atmospheric
pollution: Wind and trajectory analyses, Environ. Modell. Softw., 88, 183–187, <ext-link xlink:href="https://doi.org/10.1016/j.envsoft.2016.11.022" ext-link-type="DOI">10.1016/j.envsoft.2016.11.022</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><?label 1?><mixed-citation>Petzold, A., Ogren, J. A., Fiebig, M., Laj, P., Li, S.-M., Baltensperger, U., Holzer-Popp, T., Kinne, S., Pappalardo, G., Sugimoto, N., Wehrli, C., Wiedensohler, A., and Zhang, X.-Y.: Recommendations for reporting ”black carbon” measurements, Atmos. Chem. Phys., 13, 8365–8379, <ext-link xlink:href="https://doi.org/10.5194/acp-13-8365-2013" ext-link-type="DOI">10.5194/acp-13-8365-2013</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><?label 1?><mixed-citation>Pileci, R. E., Modini, R. L., Bertò, M., Yuan, J., Corbin, J. C., Marinoni, A., Henzing, B., Moerman, M. M., Putaud, J. P., Spindler, G., Wehner, B., Müller, T., Tuch, T., Trentini, A., Zanatta, M., Baltensperger, U., and Gysel-Beer, M.: Comparison of co-located refractory black carbon (rBC) and elemental carbon (EC) mass concentration measurements during field campaigns at several European sites, Atmos. Meas. Tech., 14, 1379–1403, <ext-link xlink:href="https://doi.org/10.5194/amt-14-1379-2021" ext-link-type="DOI">10.5194/amt-14-1379-2021</ext-link>, 2021.</mixed-citation></ref>
      <ref id="bib1.bib38"><label>38</label><?label 1?><mixed-citation>Raatikainen, T., Brus, D., Hyvärinen, A.-P., Svensson, J., Asmi, E., and Lihavainen, H.: Black carbon concentrations and mixing state in the Finnish Arctic, Atmos. Chem. Phys., 15, 10057–10070, <ext-link xlink:href="https://doi.org/10.5194/acp-15-10057-2015" ext-link-type="DOI">10.5194/acp-15-10057-2015</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib39"><label>39</label><?label 1?><mixed-citation>Randerson, J. T., van der Werf, G. R., Giglio, L., Collatz, G. J., and
Kasibhatl, P. S.: Global Fire Emissions Database, Version 4.1 (GFEDv4), ORNL
DAAC, Oak Ridge, Tennessee, USA, <ext-link xlink:href="https://doi.org/10.3334/ORNLDAAC/1293" ext-link-type="DOI">10.3334/ORNLDAAC/1293</ext-link>,
2018.</mixed-citation></ref>
      <ref id="bib1.bib40"><label>40</label><?label 1?><mixed-citation>Reddington, C. L., McMeeking, G., Mann, G. W., Coe, H., Frontoso, M. G., Liu, D., Flynn, M., Spracklen, D. V., and Carslaw, K. S.: The mass and number size distributions of black carbon aerosol over Europe, Atmos. Chem. Phys., 13, 4917–4939, <ext-link xlink:href="https://doi.org/10.5194/acp-13-4917-2013" ext-link-type="DOI">10.5194/acp-13-4917-2013</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib41"><label>41</label><?label 1?><mixed-citation>
Rissler, J., Swietlicki, E., Bengtsson, A., Boman, C., Pagels, J.,
Sandström, T., Blomberg, A., and Löndahl, J.: Experimental
determination of deposition of diesel exhaust particles in the human
respiratory tract, J. Aerosol Sci., 48, 18–33, 2012.</mixed-citation></ref>
      <ref id="bib1.bib42"><label>42</label><?label 1?><mixed-citation>
Rissler, J., Nordin, E. Z., Eriksson, A. C., Nilsson, P. T., Frosch, M.,
Sporre, M. K., Wierzbicka, A., Svenningsson, B., Londahl, J., Messing, M.
E., Sjogren, S., Hemmingsen, J. G., Loft, S., Pagels, J. H., and Swietlicki,
E.: Effective Density and Mixing State of Aerosol Particles in a
Near-Traffic Urban Environment, Environ. Sci. Technol., 48,
6300–6308, 10.1021/es5000353, 2014.</mixed-citation></ref>
      <ref id="bib1.bib43"><label>43</label><?label 1?><mixed-citation>Roldin, P., Swietlicki, E., Schurgers, G., Arneth, A., Lehtinen, K. E. J., Boy, M., and Kulmala, M.: Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM, Atmos. Chem. Phys., 11, 5867–5896, <ext-link xlink:href="https://doi.org/10.5194/acp-11-5867-2011" ext-link-type="DOI">10.5194/acp-11-5867-2011</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib44"><label>44</label><?label 1?><mixed-citation>Roldin, P., Ehn, M., Kurtén, T., Olenius, T., Rissanen, M. P., Sarnela,
N., Elm, J., Rantala, P., Hao, L., Hyttinen, N., Heikkinen, L., Worsnop, D.
R., Pichelstorfer, L., Xavier, C., Clusius, P., Öström, E.,
Petäjä, T., Kulmala, M., Vehkamäki, H., Virtanen, A., Riipinen,
I., and Boy, M.: The role of highly oxygenated organic molecules in the
Boreal aerosol-cloud-climate system, Nat. Commun., 10, 4370,
<ext-link xlink:href="https://doi.org/10.1038/s41467-019-12338-8" ext-link-type="DOI">10.1038/s41467-019-12338-8</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib45"><label>45</label><?label 1?><mixed-citation>
Rolph, G., Stein, A., and Stunder, B.: Real-time environmental applications
and display system: READY, Environ. Modell. Softw., 95,
210–228, 2017.</mixed-citation></ref>
      <ref id="bib1.bib46"><label>46</label><?label 1?><mixed-citation>Rose, D., Wehner, B., Ketzel, M., Engler, C., Voigtländer, J., Tuch, T., and Wiedensohler, A.: Atmospheric number size distributions of soot particles and estimation of emission factors, Atmos. Chem. Phys., 6, 1021–1031, <ext-link xlink:href="https://doi.org/10.5194/acp-6-1021-2006" ext-link-type="DOI">10.5194/acp-6-1021-2006</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bib47"><label>47</label><?label 1?><mixed-citation>Saarikoski, S., Niemi, J. V., Aurela, M., Pirjola, L., Kousa, A., Rönkkö, T., and Timonen, H.: Sources of black carbon at residential and traffic environments obtained by two source apportionment methods, Atmos. Chem. Phys., 21, 14851–14869, <ext-link xlink:href="https://doi.org/10.5194/acp-21-14851-2021" ext-link-type="DOI">10.5194/acp-21-14851-2021</ext-link>, 2021.</mixed-citation></ref>
      <ref id="bib1.bib48"><label>48</label><?label 1?><mixed-citation>Sandradewi, J., Prevot, A. S. H., Szidat, S., Perron, N., Alfarra, M. R.,
Lanz, V. A., Weingartner, E., and Baltensperger, U.: Using aerosol light
absorption measurements for the quantitative determination of wood burning
and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 3316–3323, <ext-link xlink:href="https://doi.org/10.1021/es702253m" ext-link-type="DOI">10.1021/es702253m</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib49"><label>49</label><?label 1?><mixed-citation>Schwarz, J. P., Gao, R. S., Fahey, D. W., Thomson, D. S., Watts, L. A.,
Wilson, J. C., Reeves, J. M., Darbeheshti, M., Baumgardner, D. G., Kok, G.
L., Chung, S. H., Schulz, M., Hendricks, J., Lauer, A., Karcher, B., Slowik,
J. G., Rosenlof, K. H., Thompson, T. L., Langford, A. O., Loewenstein, M.,
and Aikin, K. C.: Single-particle measurements of midlatitude black carbon
and light-scattering aerosols from the boundary layer t<?pagebreak page3064?>o the lower
stratosphere, J. Geophys. Res.-Atmos., 111, D16207, <ext-link xlink:href="https://doi.org/10.1029/2006jd007076" ext-link-type="DOI">10.1029/2006jd007076</ext-link>,
2006.</mixed-citation></ref>
      <ref id="bib1.bib50"><label>50</label><?label 1?><mixed-citation>Schwarz, J. P., Gao, R. S., Spackman, J. R., Watts, L. A., Thomson, D. S.,
Fahey, D. W., Ryerson, T. B., Peischl, J., Holloway, J. S., Trainer, M.,
Frost, G. J., Baynard, T., Lack, D. A., de Gouw, J. A., Warneke, C., and Del
Negro, L. A.: Measurement of the mixing state, mass, and optical size of
individual black carbon particles in urban and biomass burning emissions,
Geophys. Res. Lett., 35, L13810, <ext-link xlink:href="https://doi.org/10.1029/2008gl033968" ext-link-type="DOI">10.1029/2008gl033968</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib51"><label>51</label><?label 1?><mixed-citation>Sharma, S., Leaitch, W. R., Huang, L., Veber, D., Kolonjari, F., Zhang, W., Hanna, S. J., Bertram, A. K., and Ogren, J. A.: An evaluation of three methods for measuring black carbon in Alert, Canada, Atmos. Chem. Phys., 17, 15225–15243, <ext-link xlink:href="https://doi.org/10.5194/acp-17-15225-2017" ext-link-type="DOI">10.5194/acp-17-15225-2017</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib52"><label>52</label><?label 1?><mixed-citation>Slowik, J. G., Cross, E. S., Han, J. H., Davidovits, P., Onasch, T. B.,
Jayne, J. T., WilliamS, L. R., Canagaratna, M. R., Worsnop, D. R.,
Chakrabarty, R. K., Moosmuller, H., Arnott, W. P., Schwarz, J. P., Gao, R.
S., Fahey, D. W., Kok, G. L., and Petzold, A.: An inter-comparison of
instruments measuring black carbon content of soot particles, Aerosol. Sci. Tech., 41, 295–314, <ext-link xlink:href="https://doi.org/10.1080/02786820701197078" ext-link-type="DOI">10.1080/02786820701197078</ext-link>, 2007.</mixed-citation></ref>
      <ref id="bib1.bib53"><label>53</label><?label 1?><mixed-citation>
Stein, A., Draxler, R. R., Rolph, G. D., Stunder, B. J., Cohen, M., and
Ngan, F.: NOAA's HYSPLIT atmospheric transport and dispersion modeling
system, B. Am. Meteorol. Soc., 96, 2059–2077,
2015.</mixed-citation></ref>
      <ref id="bib1.bib54"><label>54</label><?label 1?><mixed-citation>Stephens, M., Turner, N., and Sandberg, J.: Particle identification by
laser-induced incandescence in a solid-state laser cavity, Appl. Opt., 42,
3726–3736, <ext-link xlink:href="https://doi.org/10.1364/Ao.42.003726" ext-link-type="DOI">10.1364/Ao.42.003726</ext-link>, 2003.</mixed-citation></ref>
      <ref id="bib1.bib55"><label>55</label><?label 1?><mixed-citation>Subramanian, R., Kok, G. L., Baumgardner, D., Clarke, A., Shinozuka, Y., Campos, T. L., Heizer, C. G., Stephens, B. B., de Foy, B., Voss, P. B., and Zaveri, R. A.: Black carbon over Mexico: the effect of atmospheric transport on mixing state, mass absorption cross-section, and BC <inline-formula><mml:math id="M128" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> CO ratios, Atmos. Chem. Phys., 10, 219–237, <ext-link xlink:href="https://doi.org/10.5194/acp-10-219-2010" ext-link-type="DOI">10.5194/acp-10-219-2010</ext-link>, 2010.</mixed-citation></ref>
      <ref id="bib1.bib56"><label>56</label><?label 1?><mixed-citation>
Swietlicki, E., Hansson, H.-C., Hämeri, K., Svenningsson, B., Massling,
A., McFiggans, G., McMurry, P., Petäjä, T., Tunved, P., and Gysel,
M.: Hygroscopic properties of submicrometer atmospheric aerosol particles
measured with H-TDMA instruments in various environments – a review, Tellus
B, 60, 432–469, 2008.</mixed-citation></ref>
      <ref id="bib1.bib57"><label>57</label><?label 1?><mixed-citation>Tasoglou, A., Subramanian, R., and Pandis, S. N.: An inter-comparison of
black-carbon-related instruments in a laboratory study of biomass burning
aerosol, Aerosol. Sci. Tech., 52, 1320–1331,
<ext-link xlink:href="https://doi.org/10.1080/02786826.2018.1515473" ext-link-type="DOI">10.1080/02786826.2018.1515473</ext-link>, 2018.</mixed-citation></ref>
      <ref id="bib1.bib58"><label>58</label><?label 1?><mixed-citation>Textor, C., Schulz, M., Guibert, S., Kinne, S., Balkanski, Y., Bauer, S., Berntsen, T., Berglen, T., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Feichter, H., Fillmore, D., Ghan, S., Ginoux, P., Gong, S., Grini, A., Hendricks, J., Horowitz, L., Huang, P., Isaksen, I., Iversen, I., Kloster, S., Koch, D., Kirkevåg, A., Kristjansson, J. E., Krol, M., Lauer, A., Lamarque, J. F., Liu, X., Montanaro, V., Myhre, G., Penner, J., Pitari, G., Reddy, S., Seland, Ø., Stier, P., Takemura, T., and Tie, X.: Analysis and quantification of the diversities of aerosol life cycles within AeroCom, Atmos. Chem. Phys., 6, 1777–1813, <ext-link xlink:href="https://doi.org/10.5194/acp-6-1777-2006" ext-link-type="DOI">10.5194/acp-6-1777-2006</ext-link>, 2006.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib59"><label>59</label><?label 1?><mixed-citation>US EPA: Integrated Science Assessment for Particulate Matter, US
Environmental Protection Agency, US EPA/600/R-19/188, <uri>https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=347534#tab-3</uri>
(last access: 20 February 2023), December 2019.</mixed-citation></ref>
      <ref id="bib1.bib60"><label>60</label><?label 1?><mixed-citation>Vander Wal, R. L., Bryg, V. M., and Hays, M. D.: Fingerprinting soot
(towards source identification): Physical structure and chemical
composition, J. Aerosol Sci., 41, 108–117,
<ext-link xlink:href="https://doi.org/10.1016/j.jaerosci.2009.08.008" ext-link-type="DOI">10.1016/j.jaerosci.2009.08.008</ext-link>, 2010.</mixed-citation></ref>
      <ref id="bib1.bib61"><label>61</label><?label 1?><mixed-citation>Virkkula, A.: Modeled source apportionment of black carbon particles coated with a light-scattering shell, Atmos. Meas. Tech., 14, 3707–3719, <ext-link xlink:href="https://doi.org/10.5194/amt-14-3707-2021" ext-link-type="DOI">10.5194/amt-14-3707-2021</ext-link>, 2021.</mixed-citation></ref>
      <ref id="bib1.bib62"><label>62</label><?label 1?><mixed-citation>von der Weiden, S.-L., Drewnick, F., and Borrmann, S.: Particle Loss Calculator – a new software tool for the assessment of the performance of aerosol inlet systems, Atmos. Meas. Tech., 2, 479–494, <ext-link xlink:href="https://doi.org/10.5194/amt-2-479-2009" ext-link-type="DOI">10.5194/amt-2-479-2009</ext-link>, 2009.</mixed-citation></ref>
      <ref id="bib1.bib63"><label>63</label><?label 1?><mixed-citation>WHO: Review of evidence on health aspects of air pollution–REVIHAAP
project: final technical report, Copenhagen, WHO, <uri>https://www.euro.who.int/__data/assets/pdf_file/0004/193108/REVIHAAP-Final-technical-report-final-version.pdf</uri>
(last access: 20 February 2023), 2013.</mixed-citation></ref>
      <ref id="bib1.bib64"><label>64</label><?label 1?><mixed-citation>WHO: WHO global air quality guidelines, Particulate matter (PM<inline-formula><mml:math id="M129" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> and PM<inline-formula><mml:math id="M130" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">10</mml:mn></mml:msub></mml:math></inline-formula>),
ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide, Geneva, World
Health Organization, 2021.</mixed-citation></ref>
      <ref id="bib1.bib65"><label>65</label><?label 1?><mixed-citation>Wiedensohler, A., Birmili, W., Nowak, A., Sonntag, A., Weinhold, K., Merkel, M., Wehner, B., Tuch, T., Pfeifer, S., Fiebig, M., Fjäraa, A. M., Asmi, E., Sellegri, K., Depuy, R., Venzac, H., Villani, P., Laj, P., Aalto, P., Ogren, J. A., Swietlicki, E., Williams, P., Roldin, P., Quincey, P., Hüglin, C., Fierz-Schmidhauser, R., Gysel, M., Weingartner, E., Riccobono, F., Santos, S., Grüning, C., Faloon, K., Beddows, D., Harrison, R., Monahan, C., Jennings, S. G., O'Dowd, C. D., Marinoni, A., Horn, H.-G., Keck, L., Jiang, J., Scheckman, J., McMurry, P. H., Deng, Z., Zhao, C. S., Moerman, M., Henzing, B., de Leeuw, G., Löschau, G., and Bastian, S.: Mobility particle size spectrometers: harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions, Atmos. Meas. Tech., 5, 657–685, <ext-link xlink:href="https://doi.org/10.5194/amt-5-657-2012" ext-link-type="DOI">10.5194/amt-5-657-2012</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib66"><label>66</label><?label 1?><mixed-citation>Yuan, J., Modini, R. L., Zanatta, M., Herber, A. B., Müller, T., Wehner, B., Poulain, L., Tuch, T., Baltensperger, U., and Gysel-Beer, M.: Variability in the mass absorption cross section of black carbon (BC) aerosols is driven by BC internal mixing state at a central European background site (Melpitz, Germany) in winter, Atmos. Chem. Phys., 21, 635–655, <ext-link xlink:href="https://doi.org/10.5194/acp-21-635-2021" ext-link-type="DOI">10.5194/acp-21-635-2021</ext-link>, 2021.</mixed-citation></ref>
      <ref id="bib1.bib67"><label>67</label><?label 1?><mixed-citation>Zhang, Y., Favez, O., Canonaco, F., Liu, D., Močnik, G., Amodeo, T.,
Sciare, J., Prévôt, A. S. H., Gros, V., and Albinet, A.: Evidence of
major secondary organic aerosol contribution to lensing effect black carbon
absorption enhancement, npj Climate and Atmospheric Science, 1, 47,
<ext-link xlink:href="https://doi.org/10.1038/s41612-018-0056-2" ext-link-type="DOI">10.1038/s41612-018-0056-2</ext-link>, 2018.</mixed-citation></ref>

  </ref-list></back>
    <!--<article-title-html>Measurement report: Black carbon properties and concentrations in southern Sweden urban and rural air – the importance of long-range transport</article-title-html>
<abstract-html/>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
      
Ahlberg, E.: ISSA figure data, <a href="https://doi.org/10.5281/zenodo.6559236" target="_blank">https://doi.org/10.5281/zenodo.6559236</a>, Zenodo [data set], 2022.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
      
Alfoldy, B., Giechaskiel, B., Hofmann, W., and Drossinos, Y.:
Size-distribution dependent lung deposition of diesel exhaust particles, J.
Aerosol. Sci., 40, 652–663, <a href="https://doi.org/10.1016/j.jaerosci.2009.04.009" target="_blank">https://doi.org/10.1016/j.jaerosci.2009.04.009</a>, 2009.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
      
Backman, J., Schmeisser, L., Virkkula, A., Ogren, J. A., Asmi, E., Starkweather, S., Sharma, S., Eleftheriadis, K., Uttal, T., Jefferson, A., Bergin, M., Makshtas, A., Tunved, P., and Fiebig, M.: On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic, Atmos. Meas. Tech., 10, 5039–5062, <a href="https://doi.org/10.5194/amt-10-5039-2017" target="_blank">https://doi.org/10.5194/amt-10-5039-2017</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
      
Baumgardner, D., Popovicheva, O., Allan, J., Bernardoni, V., Cao, J., Cavalli, F., Cozic, J., Diapouli, E., Eleftheriadis, K., Genberg, P. J., Gonzalez, C., Gysel, M., John, A., Kirchstetter, T. W., Kuhlbusch, T. A. J., Laborde, M., Lack, D., Müller, T., Niessner, R., Petzold, A., Piazzalunga, A., Putaud, J. P., Schwarz, J., Sheridan, P., Subramanian, R., Swietlicki, E., Valli, G., Vecchi, R., and Viana, M.: Soot reference materials for instrument calibration and intercomparisons: a workshop summary with recommendations, Atmos. Meas. Tech., 5, 1869–1887, <a href="https://doi.org/10.5194/amt-5-1869-2012" target="_blank">https://doi.org/10.5194/amt-5-1869-2012</a>, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
      
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, <a href="https://doi.org/10.1002/jgrd.50171" target="_blank">https://doi.org/10.1002/jgrd.50171</a>, 2013.


    </mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
      
Corbin, J. C., Modini, R. L., and Gysel-Beer, M.: Mechanisms of
soot-aggregate restructuring and compaction, Aerosol. Sci. Tech.,
57, 89–111, <a href="https://doi.org/10.1080/02786826.2022.2137385" target="_blank">https://doi.org/10.1080/02786826.2022.2137385</a>, 2023.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
      
Cui, X. J., Wang, X. F., Yang, L. X., Chen, B., Chen, J. M., Andersson, A.,
and Gustafsson, O.: Radiative absorption enhancement from coatings on black
carbon aerosols, Sci. Total Environ., 551, 51–56,
<a href="https://doi.org/10.1016/j.scitotenv.2016.02.026" target="_blank">https://doi.org/10.1016/j.scitotenv.2016.02.026</a>, 2016.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
      
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The ”dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, <a href="https://doi.org/10.5194/amt-8-1965-2015" target="_blank">https://doi.org/10.5194/amt-8-1965-2015</a>, 2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
      
Eriksson, A., Wittbom, C., Roldin, P., Sporre, M., Öström, E.,
Nilsson, P., Martinsson, J., Rissler, J., Nordin, E., and Svenningsson, B.:
Diesel soot aging in urban plumes within hours under cold dark and humid
conditions, Sci. Rep., 7, 1–10, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
      
Fierce, L., Onasch, T. B., Cappa, C. D., Mazzoleni, C., China, S., Bhandari,
J., Davidovits, P., Fischer, D. A., Helgestad, T., Lambe, A. T., Sedlacek,
A. J., Smith, G. D., and Wolff, L.: Radiative absorption enhancements by
black carbon controlled by particle-to-particle heterogeneity in
composition, P. Natl. Acad. Sci. USA,  117, 201919723,
<a href="https://doi.org/10.1073/pnas.1919723117" target="_blank">https://doi.org/10.1073/pnas.1919723117</a>, 2020.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
      
Glasius, M., la Cour, A., and Lohse, C.: Fossil and nonfossil carbon in fine
particulate matter: A study of five European cities, J. Geophys. Res., 116, D11302, <a href="https://doi.org/10.1029/2011JD015646" target="_blank">https://doi.org/10.1029/2011JD015646</a>, 2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
      
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi,
N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse,
C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere
Monitoring Service global and regional emissions (April 2019 version),
Copernicus Atmosphere Monitoring Service (CAMS) report,
<a href="https://doi.org/10.24380/d0bn-kx16" target="_blank">https://doi.org/10.24380/d0bn-kx16</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
      
Gysel, M., Laborde, M., Olfert, J. S., Subramanian, R., and Gröhn, A. J.: Effective density of Aquadag and fullerene soot black carbon reference materials used for SP2 calibration, Atmos. Meas. Tech., 4, 2851–2858, <a href="https://doi.org/10.5194/amt-4-2851-2011" target="_blank">https://doi.org/10.5194/amt-4-2851-2011</a>, 2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
      
Hakkarainen, H., Salo, L., Mikkonen, S., Saarikoski, S., Aurela, M.,
Teinilä, K., Ihalainen, M., Martikainen, S., Marjanen, P., and
Lepistö, T.: Black carbon toxicity dependence on particle coating:
Measurements with a novel cell exposure method, Sci. Total Environ., 834, 156543, <a href="https://doi.org/10.1016/j.scitotenv.2022.156543" target="_blank">https://doi.org/10.1016/j.scitotenv.2022.156543</a>, 2022.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
      
Hinds, W. C.: Aerosol technology: properties, behavior, and measurement of
airborne particles, John Wiley &amp; Sons,  ISBN 1118591976, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
      
Holder, A. L., Hagler, G. S. W., Yelverton, T. L. B., and Hays, M. D.:
On-road black carbon instrument intercomparison and aerosol characteristics
by driving environment, Atmos. Environ., 88, 183–191,
<a href="https://doi.org/10.1016/j.atmosenv.2014.01.021" target="_blank">https://doi.org/10.1016/j.atmosenv.2014.01.021</a>, 2014.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
      
IARC: Diesel and gasoline engine exhausts and some nitroarenes, IARC
monographs on the evaluation of carcinogenic risks to humans,   105,  PubMedID 26442290, ISBN 978 92 832 01434, 2014.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
      
ICOS, R. I.: ICOS ATC MTO Release, Hyltemossa (150.0&thinsp;m),
26 September 2017–30 April 2019,
<a href="https://hdl.handle.net/11676/DbbmB-ppi1ZsmQzHfuQ9y_oY" target="_blank"/> (last access: 18 January 2022), 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
      
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P.,  Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA,  <a href="https://report.ipcc.ch/ar6/wg1/IPCC_AR6_WGI_FullReport.pdf" target="_blank"/> (last access: 1 March 2023), 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
      
Kalbermatter, D. M., Močnik, G., Drinovec, L., Visser, B., Röhrbein, J., Oscity, M., Weingartner, E., Hyvärinen, A.-P., and Vasilatou, K.: Comparing black-carbon- and aerosol-absorption-measuring instruments – a new system using lab-generated soot coated with controlled amounts of secondary organic matter, Atmos. Meas. Tech., 15, 561–572, <a href="https://doi.org/10.5194/amt-15-561-2022" target="_blank">https://doi.org/10.5194/amt-15-561-2022</a>, 2022.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
      
Kirchstetter, T. W., Novakov, T., and Hobbs, P. V.: Evidence that the
spectral dependence of light absorption by aerosols is affected by organic
carbon, J. Geophys. Res.-Atmos., 109, D21208, <a href="https://doi.org/10.1029/2004jd004999" target="_blank">https://doi.org/10.1029/2004jd004999</a>, 2004.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
      
Laborde, M., Mertes, P., Zieger, P., Dommen, J., Baltensperger, U., and Gysel, M.: Sensitivity of the Single Particle Soot Photometer to different black carbon types, Atmos. Meas. Tech., 5, 1031–1043, <a href="https://doi.org/10.5194/amt-5-1031-2012" target="_blank">https://doi.org/10.5194/amt-5-1031-2012</a>, 2012a.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
      
Laborde, M., Schnaiter, M., Linke, C., Saathoff, H., Naumann, K.-H., Möhler, O., Berlenz, S., Wagner, U., Taylor, J. W., Liu, D., Flynn, M., Allan, J. D., Coe, H., Heimerl, K., Dahlkötter, F., Weinzierl, B., Wollny, A. G., Zanatta, M., Cozic, J., Laj, P., Hitzenberger, R., Schwarz, J. P., and Gysel, M.: Single Particle Soot Photometer intercomparison at the AIDA chamber, Atmos. Meas. Tech., 5, 3077–3097, <a href="https://doi.org/10.5194/amt-5-3077-2012" target="_blank">https://doi.org/10.5194/amt-5-3077-2012</a>, 2012b.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
      
Laborde, M., Crippa, M., Tritscher, T., Jurányi, Z., Decarlo, P. F., Temime-Roussel, B., Marchand, N., Eckhardt, S., Stohl, A., Baltensperger, U., Prévôt, A. S. H., Weingartner, E., and Gysel, M.: Black carbon physical properties and mixing state in the European megacity Paris, Atmos. Chem. Phys., 13, 5831–5856, <a href="https://doi.org/10.5194/acp-13-5831-2013" target="_blank">https://doi.org/10.5194/acp-13-5831-2013</a>, 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
      
Li, H. Y., Lamb, K. D., Schwarz, J. P., Selimovic, V., Yokelson, R. J.,
McMeeking, G. R., and May, A. A.: Inter-comparison of black carbon
measurement methods for simulated open biomass burning emissions, Atmos.
Environ., 206, 156–169, <a href="https://doi.org/10.1016/j.atmosenv.2019.03.010" target="_blank">https://doi.org/10.1016/j.atmosenv.2019.03.010</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
      
Liu, D. T., Whitehead, J., Alfarra, M. R., Reyes-Villegas, E., Spracklen, D.
V., Reddington, C. L., Kong, S. F., Williams, P. I., Ting, Y. C., Haslett,
S., Taylor, J. W., Flynn, M. J., Morgan, W. T., McFiggans, G., Coe, H., and
Allan, J. D.: Black-carbon absorption enhancement in the atmosphere
determined by particle mixing state, Nat. Geosci., 10, 184–188,
<a href="https://doi.org/10.1038/Ngeo2901" target="_blank">https://doi.org/10.1038/Ngeo2901</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
      
Liu, H., Pan, X., Liu, D., Liu, X., Chen, X., Tian, Y., Sun, Y., Fu, P., and Wang, Z.: Mixing characteristics of refractory black carbon aerosols at an urban site in Beijing, Atmos. Chem. Phys., 20, 5771–5785, <a href="https://doi.org/10.5194/acp-20-5771-2020" target="_blank">https://doi.org/10.5194/acp-20-5771-2020</a>, 2020.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
      
Malmborg, V. B., Eriksson, A. C., Török, S., Zhang, Y., Kling, K.,
Martinsson, J., Fortner, E. C., Gren, L., Kook, S., Onasch, T. B.,
Bengtsson, P.-E., and Pagels, J.: Relating aerosol mass spectra to
composition and nanostructure of soot particles, Carbon, 142, 535–546,
<a href="https://doi.org/10.1016/j.carbon.2018.10.072" target="_blank">https://doi.org/10.1016/j.carbon.2018.10.072</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
      
Martinsson, J., Abdul Azeem, H., Sporre, M. K., Bergström, R., Ahlberg, E., Öström, E., Kristensson, A., Swietlicki, E., and Eriksson Stenström, K.: Carbonaceous aerosol source apportionment using the Aethalometer model – evaluation by radiocarbon and levoglucosan analysis at a rural background site in southern Sweden, Atmos. Chem. Phys., 17, 4265–4281, <a href="https://doi.org/10.5194/acp-17-4265-2017" target="_blank">https://doi.org/10.5194/acp-17-4265-2017</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
      
McMurry, P. H., Wang, X., Park, K., and Ehara, K.: The relationship between
mass and mobility for atmospheric particles: A new technique for measuring
particle density, Aerosol. Sci. Tech., 36, 227–238, <a href="https://doi.org/10.1080/027868202753504083" target="_blank">https://doi.org/10.1080/027868202753504083</a>, 2002.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
      
Michelsen, H. A., Colket, M. B., Bengtsson, P. E., D'Anna, A., Desgroux, P.,
Haynes, B. S., Miller, J. H., Nathan, G. J., Pitsch, H., and Wang, H.: A
Review of Terminology Used to Describe Soot Formation and Evolution under
Combustion and Pyrolytic Conditions, Acs Nano, 14, 12470–12490,
<a href="https://doi.org/10.1021/acsnano.0c06226" target="_blank">https://doi.org/10.1021/acsnano.0c06226</a>, 2020.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
      
Moteki, N. and Kondo, Y.: Effects of mixing state on black carbon
measurements by laser-induced incandescence, Aerosol. Sci. Tech.,
41, 398–417, <a href="https://doi.org/10.1080/02786820701199728" target="_blank">https://doi.org/10.1080/02786820701199728</a>, 2007.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
      
Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Zhang, Q., Ulbrich, I. M.,
and Worsnop, D. R.: Real-Time Methods for Estimating Organic Component Mass
Concentrations from Aerosol Mass Spectrometer Data, Environ. Sci. Technol., 45, 910–916, <a href="https://doi.org/10.1021/es102951k" target="_blank">https://doi.org/10.1021/es102951k</a>, 2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
      
Onasch, T. B., Trimborn, A., Fortner, E. C., Jayne, J. T., Kok, G. L.,
Williams, L. R., Davidovits, P., and Worsnop, D. R.: Soot Particle Aerosol
Mass Spectrometer: Development, Validation, and Initial Application, Aerosol. Sci. Tech., 46, 804–817, <a href="https://doi.org/10.1080/02786826.2012.663948" target="_blank">https://doi.org/10.1080/02786826.2012.663948</a>, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
      
Petit, J. E., Favez, O., Albinet, A., and Canonaco, F.: A user-friendly tool
for comprehensive evaluation of the geographical origins of atmospheric
pollution: Wind and trajectory analyses, Environ. Modell. Softw., 88, 183–187, <a href="https://doi.org/10.1016/j.envsoft.2016.11.022" target="_blank">https://doi.org/10.1016/j.envsoft.2016.11.022</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
      
Petzold, A., Ogren, J. A., Fiebig, M., Laj, P., Li, S.-M., Baltensperger, U., Holzer-Popp, T., Kinne, S., Pappalardo, G., Sugimoto, N., Wehrli, C., Wiedensohler, A., and Zhang, X.-Y.: Recommendations for reporting ”black carbon” measurements, Atmos. Chem. Phys., 13, 8365–8379, <a href="https://doi.org/10.5194/acp-13-8365-2013" target="_blank">https://doi.org/10.5194/acp-13-8365-2013</a>, 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
      
Pileci, R. E., Modini, R. L., Bertò, M., Yuan, J., Corbin, J. C., Marinoni, A., Henzing, B., Moerman, M. M., Putaud, J. P., Spindler, G., Wehner, B., Müller, T., Tuch, T., Trentini, A., Zanatta, M., Baltensperger, U., and Gysel-Beer, M.: Comparison of co-located refractory black carbon (rBC) and elemental carbon (EC) mass concentration measurements during field campaigns at several European sites, Atmos. Meas. Tech., 14, 1379–1403, <a href="https://doi.org/10.5194/amt-14-1379-2021" target="_blank">https://doi.org/10.5194/amt-14-1379-2021</a>, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
      
Raatikainen, T., Brus, D., Hyvärinen, A.-P., Svensson, J., Asmi, E., and Lihavainen, H.: Black carbon concentrations and mixing state in the Finnish Arctic, Atmos. Chem. Phys., 15, 10057–10070, <a href="https://doi.org/10.5194/acp-15-10057-2015" target="_blank">https://doi.org/10.5194/acp-15-10057-2015</a>, 2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
      
Randerson, J. T., van der Werf, G. R., Giglio, L., Collatz, G. J., and
Kasibhatl, P. S.: Global Fire Emissions Database, Version 4.1 (GFEDv4), ORNL
DAAC, Oak Ridge, Tennessee, USA, <a href="https://doi.org/10.3334/ORNLDAAC/1293" target="_blank">https://doi.org/10.3334/ORNLDAAC/1293</a>,
2018.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
      
Reddington, C. L., McMeeking, G., Mann, G. W., Coe, H., Frontoso, M. G., Liu, D., Flynn, M., Spracklen, D. V., and Carslaw, K. S.: The mass and number size distributions of black carbon aerosol over Europe, Atmos. Chem. Phys., 13, 4917–4939, <a href="https://doi.org/10.5194/acp-13-4917-2013" target="_blank">https://doi.org/10.5194/acp-13-4917-2013</a>, 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>41</label><mixed-citation>
      
Rissler, J., Swietlicki, E., Bengtsson, A., Boman, C., Pagels, J.,
Sandström, T., Blomberg, A., and Löndahl, J.: Experimental
determination of deposition of diesel exhaust particles in the human
respiratory tract, J. Aerosol Sci., 48, 18–33, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>42</label><mixed-citation>
      
Rissler, J., Nordin, E. Z., Eriksson, A. C., Nilsson, P. T., Frosch, M.,
Sporre, M. K., Wierzbicka, A., Svenningsson, B., Londahl, J., Messing, M.
E., Sjogren, S., Hemmingsen, J. G., Loft, S., Pagels, J. H., and Swietlicki,
E.: Effective Density and Mixing State of Aerosol Particles in a
Near-Traffic Urban Environment, Environ. Sci. Technol., 48,
6300–6308, 10.1021/es5000353, 2014.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib43"><label>43</label><mixed-citation>
      
Roldin, P., Swietlicki, E., Schurgers, G., Arneth, A., Lehtinen, K. E. J., Boy, M., and Kulmala, M.: Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM, Atmos. Chem. Phys., 11, 5867–5896, <a href="https://doi.org/10.5194/acp-11-5867-2011" target="_blank">https://doi.org/10.5194/acp-11-5867-2011</a>, 2011.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib44"><label>44</label><mixed-citation>
      
Roldin, P., Ehn, M., Kurtén, T., Olenius, T., Rissanen, M. P., Sarnela,
N., Elm, J., Rantala, P., Hao, L., Hyttinen, N., Heikkinen, L., Worsnop, D.
R., Pichelstorfer, L., Xavier, C., Clusius, P., Öström, E.,
Petäjä, T., Kulmala, M., Vehkamäki, H., Virtanen, A., Riipinen,
I., and Boy, M.: The role of highly oxygenated organic molecules in the
Boreal aerosol-cloud-climate system, Nat. Commun., 10, 4370,
<a href="https://doi.org/10.1038/s41467-019-12338-8" target="_blank">https://doi.org/10.1038/s41467-019-12338-8</a>, 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib45"><label>45</label><mixed-citation>
      
Rolph, G., Stein, A., and Stunder, B.: Real-time environmental applications
and display system: READY, Environ. Modell. Softw., 95,
210–228, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib46"><label>46</label><mixed-citation>
      
Rose, D., Wehner, B., Ketzel, M., Engler, C., Voigtländer, J., Tuch, T., and Wiedensohler, A.: Atmospheric number size distributions of soot particles and estimation of emission factors, Atmos. Chem. Phys., 6, 1021–1031, <a href="https://doi.org/10.5194/acp-6-1021-2006" target="_blank">https://doi.org/10.5194/acp-6-1021-2006</a>, 2006.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib47"><label>47</label><mixed-citation>
      
Saarikoski, S., Niemi, J. V., Aurela, M., Pirjola, L., Kousa, A., Rönkkö, T., and Timonen, H.: Sources of black carbon at residential and traffic environments obtained by two source apportionment methods, Atmos. Chem. Phys., 21, 14851–14869, <a href="https://doi.org/10.5194/acp-21-14851-2021" target="_blank">https://doi.org/10.5194/acp-21-14851-2021</a>, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib48"><label>48</label><mixed-citation>
      
Sandradewi, J., Prevot, A. S. H., Szidat, S., Perron, N., Alfarra, M. R.,
Lanz, V. A., Weingartner, E., and Baltensperger, U.: Using aerosol light
absorption measurements for the quantitative determination of wood burning
and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 3316–3323, <a href="https://doi.org/10.1021/es702253m" target="_blank">https://doi.org/10.1021/es702253m</a>, 2008.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib49"><label>49</label><mixed-citation>
      
Schwarz, J. P., Gao, R. S., Fahey, D. W., Thomson, D. S., Watts, L. A.,
Wilson, J. C., Reeves, J. M., Darbeheshti, M., Baumgardner, D. G., Kok, G.
L., Chung, S. H., Schulz, M., Hendricks, J., Lauer, A., Karcher, B., Slowik,
J. G., Rosenlof, K. H., Thompson, T. L., Langford, A. O., Loewenstein, M.,
and Aikin, K. C.: Single-particle measurements of midlatitude black carbon
and light-scattering aerosols from the boundary layer to the lower
stratosphere, J. Geophys. Res.-Atmos., 111, D16207, <a href="https://doi.org/10.1029/2006jd007076" target="_blank">https://doi.org/10.1029/2006jd007076</a>,
2006.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib50"><label>50</label><mixed-citation>
      
Schwarz, J. P., Gao, R. S., Spackman, J. R., Watts, L. A., Thomson, D. S.,
Fahey, D. W., Ryerson, T. B., Peischl, J., Holloway, J. S., Trainer, M.,
Frost, G. J., Baynard, T., Lack, D. A., de Gouw, J. A., Warneke, C., and Del
Negro, L. A.: Measurement of the mixing state, mass, and optical size of
individual black carbon particles in urban and biomass burning emissions,
Geophys. Res. Lett., 35, L13810, <a href="https://doi.org/10.1029/2008gl033968" target="_blank">https://doi.org/10.1029/2008gl033968</a>, 2008.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib51"><label>51</label><mixed-citation>
      
Sharma, S., Leaitch, W. R., Huang, L., Veber, D., Kolonjari, F., Zhang, W., Hanna, S. J., Bertram, A. K., and Ogren, J. A.: An evaluation of three methods for measuring black carbon in Alert, Canada, Atmos. Chem. Phys., 17, 15225–15243, <a href="https://doi.org/10.5194/acp-17-15225-2017" target="_blank">https://doi.org/10.5194/acp-17-15225-2017</a>, 2017.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib52"><label>52</label><mixed-citation>
      
Slowik, J. G., Cross, E. S., Han, J. H., Davidovits, P., Onasch, T. B.,
Jayne, J. T., WilliamS, L. R., Canagaratna, M. R., Worsnop, D. R.,
Chakrabarty, R. K., Moosmuller, H., Arnott, W. P., Schwarz, J. P., Gao, R.
S., Fahey, D. W., Kok, G. L., and Petzold, A.: An inter-comparison of
instruments measuring black carbon content of soot particles, Aerosol. Sci. Tech., 41, 295–314, <a href="https://doi.org/10.1080/02786820701197078" target="_blank">https://doi.org/10.1080/02786820701197078</a>, 2007.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib53"><label>53</label><mixed-citation>
      
Stein, A., Draxler, R. R., Rolph, G. D., Stunder, B. J., Cohen, M., and
Ngan, F.: NOAA's HYSPLIT atmospheric transport and dispersion modeling
system, B. Am. Meteorol. Soc., 96, 2059–2077,
2015.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib54"><label>54</label><mixed-citation>
      
Stephens, M., Turner, N., and Sandberg, J.: Particle identification by
laser-induced incandescence in a solid-state laser cavity, Appl. Opt., 42,
3726–3736, <a href="https://doi.org/10.1364/Ao.42.003726" target="_blank">https://doi.org/10.1364/Ao.42.003726</a>, 2003.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib55"><label>55</label><mixed-citation>
      
Subramanian, R., Kok, G. L., Baumgardner, D., Clarke, A., Shinozuka, Y., Campos, T. L., Heizer, C. G., Stephens, B. B., de Foy, B., Voss, P. B., and Zaveri, R. A.: Black carbon over Mexico: the effect of atmospheric transport on mixing state, mass absorption cross-section, and BC&thinsp;∕&thinsp;CO ratios, Atmos. Chem. Phys., 10, 219–237, <a href="https://doi.org/10.5194/acp-10-219-2010" target="_blank">https://doi.org/10.5194/acp-10-219-2010</a>, 2010.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib56"><label>56</label><mixed-citation>
      
Swietlicki, E., Hansson, H.-C., Hämeri, K., Svenningsson, B., Massling,
A., McFiggans, G., McMurry, P., Petäjä, T., Tunved, P., and Gysel,
M.: Hygroscopic properties of submicrometer atmospheric aerosol particles
measured with H-TDMA instruments in various environments – a review, Tellus
B, 60, 432–469, 2008.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib57"><label>57</label><mixed-citation>
      
Tasoglou, A., Subramanian, R., and Pandis, S. N.: An inter-comparison of
black-carbon-related instruments in a laboratory study of biomass burning
aerosol, Aerosol. Sci. Tech., 52, 1320–1331,
<a href="https://doi.org/10.1080/02786826.2018.1515473" target="_blank">https://doi.org/10.1080/02786826.2018.1515473</a>, 2018.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib58"><label>58</label><mixed-citation>
      
Textor, C., Schulz, M., Guibert, S., Kinne, S., Balkanski, Y., Bauer, S., Berntsen, T., Berglen, T., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Feichter, H., Fillmore, D., Ghan, S., Ginoux, P., Gong, S., Grini, A., Hendricks, J., Horowitz, L., Huang, P., Isaksen, I., Iversen, I., Kloster, S., Koch, D., Kirkevåg, A., Kristjansson, J. E., Krol, M., Lauer, A., Lamarque, J. F., Liu, X., Montanaro, V., Myhre, G., Penner, J., Pitari, G., Reddy, S., Seland, Ø., Stier, P., Takemura, T., and Tie, X.: Analysis and quantification of the diversities of aerosol life cycles within AeroCom, Atmos. Chem. Phys., 6, 1777–1813, <a href="https://doi.org/10.5194/acp-6-1777-2006" target="_blank">https://doi.org/10.5194/acp-6-1777-2006</a>, 2006.


    </mixed-citation></ref-html>
<ref-html id="bib1.bib59"><label>59</label><mixed-citation>
      
US EPA: Integrated Science Assessment for Particulate Matter, US
Environmental Protection Agency, US EPA/600/R-19/188, <a href="https://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=347534#tab-3" target="_blank"/>
(last access: 20 February 2023), December 2019.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib60"><label>60</label><mixed-citation>
      
Vander Wal, R. L., Bryg, V. M., and Hays, M. D.: Fingerprinting soot
(towards source identification): Physical structure and chemical
composition, J. Aerosol Sci., 41, 108–117,
<a href="https://doi.org/10.1016/j.jaerosci.2009.08.008" target="_blank">https://doi.org/10.1016/j.jaerosci.2009.08.008</a>, 2010.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib61"><label>61</label><mixed-citation>
      
Virkkula, A.: Modeled source apportionment of black carbon particles coated with a light-scattering shell, Atmos. Meas. Tech., 14, 3707–3719, <a href="https://doi.org/10.5194/amt-14-3707-2021" target="_blank">https://doi.org/10.5194/amt-14-3707-2021</a>, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib62"><label>62</label><mixed-citation>
      
von der Weiden, S.-L., Drewnick, F., and Borrmann, S.: Particle Loss Calculator – a new software tool for the assessment of the performance of aerosol inlet systems, Atmos. Meas. Tech., 2, 479–494, <a href="https://doi.org/10.5194/amt-2-479-2009" target="_blank">https://doi.org/10.5194/amt-2-479-2009</a>, 2009.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib63"><label>63</label><mixed-citation>
      
WHO: Review of evidence on health aspects of air pollution–REVIHAAP
project: final technical report, Copenhagen, WHO, <a href="https://www.euro.who.int/__data/assets/pdf_file/0004/193108/REVIHAAP-Final-technical-report-final-version.pdf" target="_blank"/>
(last access: 20 February 2023), 2013.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib64"><label>64</label><mixed-citation>
      
WHO: WHO global air quality guidelines, Particulate matter (PM<sub>2.5</sub> and PM<sub>10</sub>),
ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide, Geneva, World
Health Organization, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib65"><label>65</label><mixed-citation>
      
Wiedensohler, A., Birmili, W., Nowak, A., Sonntag, A., Weinhold, K., Merkel, M., Wehner, B., Tuch, T., Pfeifer, S., Fiebig, M., Fjäraa, A. M., Asmi, E., Sellegri, K., Depuy, R., Venzac, H., Villani, P., Laj, P., Aalto, P., Ogren, J. A., Swietlicki, E., Williams, P., Roldin, P., Quincey, P., Hüglin, C., Fierz-Schmidhauser, R., Gysel, M., Weingartner, E., Riccobono, F., Santos, S., Grüning, C., Faloon, K., Beddows, D., Harrison, R., Monahan, C., Jennings, S. G., O'Dowd, C. D., Marinoni, A., Horn, H.-G., Keck, L., Jiang, J., Scheckman, J., McMurry, P. H., Deng, Z., Zhao, C. S., Moerman, M., Henzing, B., de Leeuw, G., Löschau, G., and Bastian, S.: Mobility particle size spectrometers: harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions, Atmos. Meas. Tech., 5, 657–685, <a href="https://doi.org/10.5194/amt-5-657-2012" target="_blank">https://doi.org/10.5194/amt-5-657-2012</a>, 2012.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib66"><label>66</label><mixed-citation>
      
Yuan, J., Modini, R. L., Zanatta, M., Herber, A. B., Müller, T., Wehner, B., Poulain, L., Tuch, T., Baltensperger, U., and Gysel-Beer, M.: Variability in the mass absorption cross section of black carbon (BC) aerosols is driven by BC internal mixing state at a central European background site (Melpitz, Germany) in winter, Atmos. Chem. Phys., 21, 635–655, <a href="https://doi.org/10.5194/acp-21-635-2021" target="_blank">https://doi.org/10.5194/acp-21-635-2021</a>, 2021.

    </mixed-citation></ref-html>
<ref-html id="bib1.bib67"><label>67</label><mixed-citation>
      
Zhang, Y., Favez, O., Canonaco, F., Liu, D., Močnik, G., Amodeo, T.,
Sciare, J., Prévôt, A. S. H., Gros, V., and Albinet, A.: Evidence of
major secondary organic aerosol contribution to lensing effect black carbon
absorption enhancement, npj Climate and Atmospheric Science, 1, 47,
<a href="https://doi.org/10.1038/s41612-018-0056-2" target="_blank">https://doi.org/10.1038/s41612-018-0056-2</a>, 2018.

    </mixed-citation></ref-html>--></article>
