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  <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-18-14681-2018</article-id><title-group><article-title>Cloud scavenging of anthropogenic refractory particles at a mountain site in North China</article-title><alt-title>Properties of cloud residues over polluted areas</alt-title>
      </title-group><?xmltex \runningtitle{Properties of cloud residues over polluted areas}?><?xmltex \runningauthor{L.~Liu et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Liu</surname><given-names>Lei</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7171-1454</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Zhang</surname><given-names>Jian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Xu</surname><given-names>Liang</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1703-1255</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Yuan</surname><given-names>Qi</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Huang</surname><given-names>Dao</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Chen</surname><given-names>Jianmin</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5859-3070</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Shi</surname><given-names>Zongbo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7157-543X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Sun</surname><given-names>Yele</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-2354-0221</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Fu</surname><given-names>Pingqing</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-6249-2280</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Wang</surname><given-names>Zifa</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Zhang</surname><given-names>Daizhou</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1448-2325</ext-link></contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff2">
          <name><surname>Li</surname><given-names>Weijun</given-names></name>
          <email>liweijun@zju.edu.cn</email>
        <ext-link>https://orcid.org/0000-0003-4887-4260</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Environment Research Institute, Shandong University, Jinan 250100,
China</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang
University, Hangzhou 310027, China</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Shanghai Key Laboratory of Atmospheric Particle Pollution and
Prevention, Department of Environmental Science and Engineering, Fudan
University, Shanghai 200433, China</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>School of Geography, Earth and Environmental Sciences, University of
Birmingham, Birmingham, B15 2TT, UK</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Faculty of Environmental and Symbiotic Sciences, Prefectural
University of Kumamoto, Kumamoto 862-8502, Japan</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Weijun Li (liweijun@zju.edu.cn)</corresp></author-notes><pub-date><day>12</day><month>October</month><year>2018</year></pub-date>
      
      <volume>18</volume>
      <issue>19</issue>
      <fpage>14681</fpage><lpage>14693</lpage>
      <history>
        <date date-type="received"><day>2</day><month>June</month><year>2018</year></date>
           <date date-type="rev-request"><day>21</day><month>June</month><year>2018</year></date>
           <date date-type="rev-recd"><day>1</day><month>October</month><year>2018</year></date>
           <date date-type="accepted"><day>2</day><month>October</month><year>2018</year></date>
      </history>
      <permissions>
        
        
      <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>
    <p id="d1e215">Aerosol–cloud interactions remain a major source of uncertainty
in climate forcing estimates. Few studies have been conducted to characterize
the aerosol–cloud interactions in heavily polluted conditions worldwide. In
this study, cloud residual and cloud interstitial particles were collected
during cloud events under different pollution levels from 22 July to 1 August
2014 at Mt. Tai (1532 m above sea level) located in the North China Plain (NCP). A
transmission electron microscope was used to investigate the morphology, size,
and chemical composition of individual cloud residual and cloud interstitial
particles, and to study mixing properties of different aerosol components in
individual particles. Our results show that S-rich particles were predominant
(78 %) during clean periods (PM<inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M2" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), but a large number of anthropogenic refractory particles (e.g.,
soot, fly ash, and metal) and their mixtures with S-rich particles (defined as “S-refractory”)
were observed during polluted periods. Cloud droplets collected
during polluted periods were found to become an extremely complicated mixture
by scavenging abundant refractory particles. We found that 76 % of cloud
residual particles were S-refractory particles and that 26 % of cloud
residual particles contained two or more types of refractory particles.
Soot-containing particles (i.e., S-soot and S-fly ash/metal-soot) were the
most abundant (62 %) among cloud residual particles, followed by fly
<?xmltex \hack{\mbox\bgroup}?>ash/metal-containing<?xmltex \hack{\egroup}?> particles (i.e., S-fly ash/metal and S-fly
ash/metal-soot, 37 %). These complicated cloud droplets have not been
reported in clean continental or marine air before. Our findings provide an
insight into the potential impacts on cloud radiative forcing from black
carbon and metal catalyzed reactions of SO<inline-formula><mml:math id="M3" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in micro-cloud droplets
containing soluble metals released from fly ash and metals over polluted air.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e271">Clouds play a crucial role in various physical and chemical processes
occurring in the lower troposphere and hence affect the Earth's radiation
budget (Seinfeld et al., 2016; Tilgner et al., 2014). Aerosol particles,
including primary and secondary ones generated from natural and
anthropogenic sources, either directly alter radiative forcing or act as
cloud condensation nuclei (CCN) to indirectly influence it. At present,
aerosol–cloud interactions unquestionably affect radiative forcing and
global climate (McFiggans et al., 2006; Rosenfeld et al., 2014; Seinfeld
and Pandis, 2006). CCN become cloud droplets through the condensation of
water vapor when the relative humidity (RH) of an air parcel increases above
saturation (Farmer et al., 2015). Size, chemical<?pagebreak page14682?> composition,
and mixing state are main factors affecting the ability of a particle to act
as CCN (Dusek et al., 2006; Fan et al., 2016; Hudson, 2007; Li et al.,
2011a; Rosenfeld, 2000). In addition, aerosol particles incorporated into
cloud droplets can be easily lifted into the free troposphere during cloud
development and further extend their influence on cloud precipitation and
regional climate (Fan et al., 2016).</p>
      <p id="d1e274">Owing to rapid industrialization and urbanization in Asia, large
quantities of aerosol particles from anthropogenic sources are released into
the atmosphere, which can dramatically affect the chemical composition of
CCN, and furthermore change the properties of clouds such as radiative
forcing, lifetime, and precipitation patterns (Drewnick et al., 2007; Ervens,
2015; Li et al., 2011b; Twohy and Anderson, 2008). High concentrations of
aerosol particles increase the number of cloud droplets and reduce their
size, which further results in the reduction of precipitation efficiency and
in extending the lifetime of clouds (Fan et al., 2016; J. Li et al., 2017;
McFiggans et al., 2006; Qian et al., 2009; Rosenfeld, 2000). Moreover,
anthropogenic aerosol particles – especially fly ash, metal, and soot
particles – are incorporated into cloud droplets, and are transported long
distances to affect ecosystems, human health, and radiative forcing (Li et
al., 2013; Rosenfeld et al., 2014). In particular, the toxic and bioaccumulative
metals can deposit into the ecosystem following fog or precipitation and
further cause severe health problems to human beings (Liu et al., 2012).
Moreover, transition metals such as iron (Fe) and manganese (Mn) can enhance
the in-cloud oxidation of sulfur dioxide to sulfate (Harris et al., 2013).</p>
      <p id="d1e277">Recently, many studies have been performed worldwide to investigate
aerosol–cloud interactions and the composition of cloud droplets.
Schroder et al. (2015) investigated the activation of refractory
black carbon particles in stratocumulus clouds at a marine boundary layer
site using a counterflow virtual impactor and single-particle soot
photometer. Ueda et al. (2014) reported the effects of
in-cloud processes on the compositional changes of sea salt particles by
collecting individual aerosol particles in and below clouds, respectively.
Pierce et al. (2015) calculated size distribution changes and
radiative forcing effects due to the scavenging of interstitial particles by
cloud droplets in a clean remote region. Roth et al. (2016) analyzed
the composition and mixing state of cloud residues and out-of-cloud aerosol
particles by single-particle aerosol mass spectrometry (SPAMS) on a mountain site
and found that soot particles internally mixed with sulfate and nitrate were
the dominant ones in cloud residues. All of the above studies were carried
out in the clean atmosphere; they could not observe the clear interactions
between abundant anthropogenic particles and cloud droplets. However, the
latest satellite observations indicated that large numbers of anthropogenic
fine particles assembled in the cloud base and might modify cloud properties in
heavily polluted air influenced by industrial and urban emissions (Eck et
al., 2018). Field observations are needed to confirm this and understand the
interactions of aerosol–cloud over polluted areas, especially in North and
South Asia.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p id="d1e282"><bold>(a)</bold> Location of Mt. Tai in the North China Plain (NCP) and the
24 h air mass backward trajectories arriving at Mt. Tai at 1500 m a.g.l.
during the sampling period. <bold>(b)</bold> The medium-sized industrial cities
distributed within a radius of 120 km around Mt. Tai. <bold>(c)</bold> The
expanded topographic view of Mt. Tai and the sampling site near the summit of
Mt. Tai.</p></caption>
        <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f01.jpg"/>

      </fig>

      <p id="d1e300">Mt. Tai, the highest mountain in the NCP, is surrounded by several
medium-sized industrial cities. The altitude of Mt. Tai is close to the top
of the planetary boundary layer (PBL) above the NCP. Therefore, Mt. Tai is an
ideal site to study the effects of regional transport and local emissions of
anthropogenic aerosols on cloud properties. Numerous studies have been
conducted on Mt. Tai, but virtually all the researchers mainly focus on the
variation of chemical composition and size distribution of aerosol particles
(Zhang et al., 2014) and the chemical composition of cloud water (J. Li et al.,
2017; Wang et al., 2011). Because of the limitation of sampling and analyzing
techniques, these studies did not consider the aerosol–cloud interactions at
the top of Mt. Tai in North China.</p>
      <p id="d1e303">Transmission electron microscopy (TEM) has become a powerful technique to
characterize the particle morphology, size, and composition and mixing
properties of different components in individual particles in recent years
(Li et al., 2016a; Ueda et al., 2014). Many studies used SPAMS to characterize the composition of
residual particles of individual cloud droplets (Lin et al., 2017; Pratt
et al., 2010; Zhang et al., 2017). Compared to SPAMS, TEM can directly
observe the morphology and different components of individual cloud droplet
residual (cloud RES) and interstitial particles (cloud INT) (Kojima et
al., 2004; Li et al., 2011a; Twohy and Anderson, 2008; Ueda et al., 2014).
Therefore, the TEM technique can not only be used to identify cloud RES and
cloud INT collected in a same cloud event but also reveal interactions
between aerosol and clouds based on the different components within individual
particles. In this study, we collected individual particles during cloud
events at the summit of Mt. Tai and applied TEM to obtain and compare the
morphology, size, and composition of cloud RES and cloud INT. This is
helpful to understand the influence of anthropogenic sources on cloud
properties above the heavily polluted region.</p>
</sec>
<sec id="Ch1.S2">
  <title>Experimental methods</title>
<sec id="Ch1.S2.SS1">
  <title>Sampling sites</title>
      <p id="d1e317">Field observations were carried out at Mt. Tai (36.251<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
117.101<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E; 1532 m above sea level (a.s.l.)) from 22 July to
1 August 2014. Mt. Tai is the highest mountain in the central NCP and is
surrounded by several medium-sized industrial cities (Fig. 1). A number of
large coal-fired power plants, oil refinery plants, steel plants, and cement
plants are located in these industrial cities (Jinan, Zibo, Laiwu,
Liaocheng, Jining, Tai'an etc.) within a radius of 120 km around Mt. Tai
(Fig. 1b). Jinan is the capital of Shandong Province and is situated 60 km
north of Mt. Tai. Tai'an is located at the southern foot of Mt. Tai.
Therefore, the local and regional emissions<?pagebreak page14683?> may have a large contribution to
the air quality at the summit of Mt. Tai. Mt. Tai's altitude is close to the
top of the PBL over the NCP, and local cloud events
frequently occur at its summit, especially in summer.</p>
      <p id="d1e338">As shown in Fig. 1c, individual particle samples were collected at a
sampling site near the summit of Mt. Tai. The sampling site was usually
covered by clouds when cloud events occurred during the sampling periods.
The 24 h air mass backward trajectories arriving at Mt. Tai at 1500 m above
ground level (a.g.l) (Fig. 1a) were calculated using the Hybrid
Single-Particles Lagrangian Integrated Trajectory (HYSPLIT) model available
at the NOAA Air Resources Laboratory's web server (Draxler and
Rolph, 2003).</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Individual particle collections</title>
      <p id="d1e347">Individual aerosol particles were collected on carbon films supported by
TEM copper grids (carbon type-B, 300-mesh copper, Beijing XXBR Technology
Co., Ltd, China) using a single-stage cascade impactor with a 0.5 mm
diameter jet nozzle at a flow rate of 1.0 L min<inline-formula><mml:math id="M6" 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 aerodynamic
diameter of particles collected with a 50 % efficiency (cutoff diameter,
<inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:msub><mml:mi>d</mml:mi><mml:mn mathvariant="normal">50</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) by the sampler is 0.24 <inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> if particle density is
2 g cm<inline-formula><mml:math id="M9" 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>. More detailed information about the setup of a modified
sampler can be found in Li et al. (2011a). When cloud events occurred at the
summit of Mt. Tai, individual particle samples were collected during the
cloud events except one cloud event at midnight on 26 July (Fig. 3).
The sample information in the present study is listed in Table 1.</p>
      <p id="d1e395">During the sampling period, meteorological data at the summit of Mt. Tai
including pressure (<inline-formula><mml:math id="M10" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>), relative humidity (RH), temperature (<inline-formula><mml:math id="M11" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>), wind speed
(WS), and wind direction (WD) were measured and recorded every 5 min using a
pocket weather meter (Kestrel 4500, Nielsen-Kellermann Inc., USA).
PM<inline-formula><mml:math id="M12" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> concentrations on Mt. Tai were monitored online by a beta
attenuation and optical analyzer (model 5030 SHARP monitor, Thermo
Scientific, USA).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p id="d1e424">Information on individual particle samples collected on
Mt. Tai.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Sample ID</oasis:entry>
         <oasis:entry colname="col2">Sampling time (LT)</oasis:entry>
         <oasis:entry colname="col3">PM<inline-formula><mml:math id="M13" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> (<inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M15" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula> (<inline-formula><mml:math id="M16" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C)</oasis:entry>
         <oasis:entry colname="col5">RH (%)</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M17" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> (hPa)</oasis:entry>
         <oasis:entry colname="col7">WS  (m s<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>)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">1</oasis:entry>
         <oasis:entry colname="col2">22 Jul 2014 16:04</oasis:entry>
         <oasis:entry colname="col3">51.6</oasis:entry>
         <oasis:entry colname="col4">22.8</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">849.1</oasis:entry>
         <oasis:entry colname="col7">0.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2</oasis:entry>
         <oasis:entry colname="col2">23 Jul 2014 08:00</oasis:entry>
         <oasis:entry colname="col3">24.2</oasis:entry>
         <oasis:entry colname="col4">20.4</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">849.4</oasis:entry>
         <oasis:entry colname="col7">2.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">3</oasis:entry>
         <oasis:entry colname="col2">24 Jul 2014 07:43</oasis:entry>
         <oasis:entry colname="col3">74.3</oasis:entry>
         <oasis:entry colname="col4">19.2</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">848.0</oasis:entry>
         <oasis:entry colname="col7">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">4</oasis:entry>
         <oasis:entry colname="col2">25 Jul 2014 17:00</oasis:entry>
         <oasis:entry colname="col3">11.8</oasis:entry>
         <oasis:entry colname="col4">13.9</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">838.0</oasis:entry>
         <oasis:entry colname="col7">5.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">5</oasis:entry>
         <oasis:entry colname="col2">29 Jul 2014 16:18</oasis:entry>
         <oasis:entry colname="col3">72.9</oasis:entry>
         <oasis:entry colname="col4">20.8</oasis:entry>
         <oasis:entry colname="col5">95.7</oasis:entry>
         <oasis:entry colname="col6">848.0</oasis:entry>
         <oasis:entry colname="col7">1.1</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">6</oasis:entry>
         <oasis:entry colname="col2">30 Jul 2014 19:24</oasis:entry>
         <oasis:entry colname="col3">24.2</oasis:entry>
         <oasis:entry colname="col4">17.5</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">844.2</oasis:entry>
         <oasis:entry colname="col7">0.8</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">7</oasis:entry>
         <oasis:entry colname="col2">31 Jul 2014 17:30</oasis:entry>
         <oasis:entry colname="col3">56.4</oasis:entry>
         <oasis:entry colname="col4">18.1</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">849.0</oasis:entry>
         <oasis:entry colname="col7">0.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">8</oasis:entry>
         <oasis:entry colname="col2">1 Aug 2014 17:56</oasis:entry>
         <oasis:entry colname="col3">14.7</oasis:entry>
         <oasis:entry colname="col4">18.8</oasis:entry>
         <oasis:entry colname="col5">100</oasis:entry>
         <oasis:entry colname="col6">849.1</oasis:entry>
         <oasis:entry colname="col7">1.8</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S2.SS3">
  <title>TEM analysis</title>
      <p id="d1e746">Individual aerosol particles collected on TEM grids were analyzed using a
transmission electron microscope (TEM, JEM-2100, JEOL Ltd., Japan) at a 200 kV
accelerating voltage. TEM is equipped with an energy-dispersive X-ray
spectrometer (EDS, INCA X-Max<inline-formula><mml:math id="M19" display="inline"><mml:msup><mml:mi/><mml:mi>N</mml:mi></mml:msup></mml:math></inline-formula> 80T, Oxford Instruments, UK). The EDS
semi-quantitatively detects the elemental composition of individual
particles with atomic number greater than 6 (<inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:mi>Z</mml:mi><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula>). However,
Cu peaks in the EDS spectra were not considered because of the interference
from the copper substrate of TEM grids. We acquired morphology and
composition of individual particles through the combination of TEM and EDS
(TEM–EDS).</p>
      <p id="d1e770">The distribution of aerosol particles on TEM grids was not uniform, with
particle size decreasing from the center to<?pagebreak page14684?> the edge of the TEM grids. Cloud
droplets with larger size normally impacted the center and interstitial
particles mostly distributed on the peripheral areas of TEM grids
(Li et al., 2011a). Moreover, cloud RES had large rims
compared with cloud INT, suggesting that cloud RES were droplets before
being captured (Zhang et al., 2006). According to the
distribution and morphology of individual particles on the substrate, we can
distinguish between cloud RES and cloud INT particles. Figure 2 generally
displays typical TEM images of cloud RES and cloud INT particles. Generally,
a number of previous studies using the cascade impactor have successfully
captured individual interstitial particles and cloud droplets on the
substrate during cloud events (Kojima et al., 2004; Li et al., 2011a;
Ueda et al., 2014; Zhang et al., 2006).</p>
      <p id="d1e773">To obtain the size of cloud RES and cloud INT particles, we measured the
area and equivalent circle diameter (ECD) of these analyzed particles using iTEM software (Olympus soft imaging solutions GmbH, Germany). It should be
noted that we measured ECD of the core of individual cloud RES excluding the
water rim because the water rim only contains trace organics
(Li et al., 2011a). The ECD can be further converted to
equivalent spherical diameter according to the atomic force microscopy analysis (refer to
the Supplement Fig. S1).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><caption><p id="d1e778">Low-magnification TEM images of cloud RES <bold>(a–b)</bold> and cloud
INT <bold>(c–d)</bold> particles collected on Mt. Tai.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f02.jpg"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results</title>
<sec id="Ch1.S3.SS1">
  <title>Meteorological conditions and backward trajectories</title>
      <p id="d1e805">Temporal variations of pressure (<inline-formula><mml:math id="M21" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>), relative humidity (RH), temperature
(<inline-formula><mml:math id="M22" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>), wind speed (WS), wind direction (WD), and PM<inline-formula><mml:math id="M23" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> concentration were
measured on Mt. Tai from 22 July to 2 August 2014 (Fig. 3). During the
sampling period, the temperature ranged from 12.6 to 29.4 <inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C,
and the RH varied between 48.2 % and 100 %. Each day during the sampling
period, the RH reached 100 % as temperatures decreased from the late
afternoon into the evening (Fig. 3). We noticed that PM<inline-formula><mml:math id="M25" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula>
concentrations on the mountaintop were closely related to wind direction and
speed during the regional transport of hazes. Based on backward trajectories
of air masses and PM<inline-formula><mml:math id="M26" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> concentrations, the whole sampling period can
be divided into three categories:
<list list-type="bullet"><list-item>
      <p id="d1e861"><italic>Clean period</italic> (PM<inline-formula><mml:math id="M27" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>).
The prevailing winds were from the northeast to east, and air
masses were from higher altitudes above the marine areas, which led to the
lowest PM<inline-formula><mml:math id="M29" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> concentration.</p></list-item><list-item>
      <p id="d1e909"><italic>Lightly polluted period</italic> (15 <inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M31" display="inline"><mml:mi mathvariant="italic">&lt;</mml:mi></mml:math></inline-formula> PM<inline-formula><mml:math id="M32" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M33" display="inline"><mml:mi mathvariant="italic">&lt;</mml:mi></mml:math></inline-formula> 35 <inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). The prevailing winds were from the west, and
air masses originating from higher altitudes above continental areas brought
regional pollutants to the summit of Mt. Tai.</p></list-item><list-item>
      <p id="d1e976"><italic>Polluted period</italic> (PM<inline-formula><mml:math id="M35" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M36" display="inline"><mml:mi mathvariant="italic">&gt;</mml:mi></mml:math></inline-formula> 35 <inline-formula><mml:math id="M37" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). Air masses originating from the northwest, southwest, or
south went through Tai'an.</p></list-item></list>
Back trajectories as shown in Fig. 1a during
polluted days suggest that air pollutants from industrialized cities might
be lifted along the southern slope up to Mt. Tai's summit.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p id="d1e1019">Temporal variations of pressure (<inline-formula><mml:math id="M38" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>), relative humidity
(RH), temperature (<inline-formula><mml:math id="M39" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>), wind speed (WS), and wind direction (WD) measured on
Mt. Tai from 22 July to 2 August 2014. The red arrows indicate collection
times of individual particle samples during the cloud events.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f03.png"/>

        </fig>

</sec>
<?pagebreak page14685?><sec id="Ch1.S3.SS2">
  <title>Mixing properties of anthropogenic refractory particles</title>
      <p id="d1e1048">Based on the elemental composition and morphology of individual particles,
six basic types of individual particles were classified: S-rich (Fig. S2a),
soot (Fig. S2b), organic matter (OM; Fig. S2c), mineral (Fig. S2d), and fly
ash/metal (Fig. S2e–h). The classification criteria of different particle
types and their sources have been described in a separate study
(Li et al., 2016a). S-rich particles representing secondary
inorganic particles (e.g., SO<inline-formula><mml:math id="M40" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, NO<inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, and
NH<inline-formula><mml:math id="M42" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>) are transformed from gaseous SO<inline-formula><mml:math id="M43" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, NO<inline-formula><mml:math id="M44" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>, and
NH<inline-formula><mml:math id="M45" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>. OM can be divided into primary organic matter (POM) and secondary
organic matter (SOM). POM is directly emitted from coal or biomass burning
and normally has spherical or irregular shapes (Liu et al.,
2017), whereas SOM is produced from the chemical oxidation of volatile
organic compounds (VOCs) and exhibits OM-coating on S-rich particles
(Li et al., 2016b). Fly ash (e.g., Si, Al, and O) and metal
particles (e.g., Fe, Mn, Zn, and Pb) normally are emitted from coal-fired
power plants and heavy industrial activities, such as production activities
in steel mills and smelters. Soot particles are generated from incomplete
combustion processes of biomass burning and fossil fuels in both industrial
activities and vehicular emissions. In much of the climate change and
environmental literature, “soot” and “black carbon” are commonly used
interchangeably, and black carbon is the most commonly used term in the
climate science community (Andreae and Gelencsér, 2006; Buseck et
al., 2014). In the following sections, we use the term soot for the
classification of particle types and the term black carbon for the
discussion of climate issues. Mineral particles come from construction
activities, resuspended road dust, and natural soil. Among these types of
particles, soot, POM, fly ash, mineral, and metal particles were refractory
under electron beams and were thus defined as refractory particles
(Ebert et al., 2016).</p>
      <p id="d1e1118">Based on mixing properties of multicomponents within individual particles
(Figs. 4 and 5), these particles can be further classified into four
categories: S-mineral (Figs. 4a and 5a), S-soot (Figs. 4b and 5b), S-fly
ash/metal (Figs. 4c and 5c), and S-fly ash/metal-soot (Figs. 4d and 5d). Here,
these four types of particles with refractory inclusions are generally
defined as “S-refractory” particles.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F4" specific-use="star"><caption><p id="d1e1123">Typical TEM images showing mixing properties of
multicomponents within individual cloud RES particles: <bold>(a)</bold> a mixture of
S-rich and mineral particles; <bold>(b)</bold> a mixture of S-rich and soot particles; <bold>(c)</bold> a mixture of
S-rich and fly ash/metal particles; and <bold>(d)</bold> a mixture of S-rich, soot, and fly ash/metal particles.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f04.jpg"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e1147">Typical TEM images showing mixing properties of
multicomponents within individual cloud INT particles: <bold>(a)</bold> a mixture of
S-rich and mineral particles; <bold>(b)</bold> a mixture of S-rich and soot particles; <bold>(c)</bold> a mixture of
S-rich and fly ash/metal particles; and <bold>(d)</bold> a mixture of S-rich, soot, and fly ash/metal particles.</p></caption>
          <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f05.jpg"/>

        </fig>

      <?pagebreak page14687?><p id="d1e1168">Figure 6 shows number fractions of S-rich, refractory, and S-refractory
particles in clean, lightly polluted, and polluted periods on Mt. Tai. In
clean periods, S-rich particles had the highest proportion (78 %),
followed by a 22 % contribution of the refractory and S-refractory
particles. This may be attributed to the clean air masses that originated
from the clean marine area and arrived at the summit of Mt. Tai through
high-altitude transport (above 1500 m) (Fig. 1). Because the air masses did
not contact the ground surface, the local anthropogenic pollutants (e.g.,
soot, fly ash, and metal) could not be lifted to the summit of Mt. Tai.
Hence, secondary particles like S-rich particles were dominant in the clean period. In
the lightly polluted and polluted periods, the fraction of S-rich particles
decreased to 59 % and 44 %, respectively; meanwhile, the fractions of
refractory and S-refractory increased up to 41 % and 56 %, respectively
(Fig. 6). The backward trajectories suggest that these air masses went
through the most heavily polluted areas before they arrived at the
mountaintop (Fig. 1). Air masses on 2 polluted days (e.g., 22 and 31 July)
were lifted from ground level to the atmospheric boundary layer. Our study
shows that number fractions of refractory and S-refractory particles
significantly increased from clean to polluted periods (Fig. 6). This result
shows that large numbers of primary refractory particles from ground-level
anthropogenic sources were lifted into the upper air and were further
internally mixed with S-rich particles.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><caption><p id="d1e1173">Number fractions of S-rich, refractory, and S-refractory
particles at different pollution levels.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f06.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS3">
  <title>Comparisons of cloud RES and INT particles</title>
      <p id="d1e1188">During the sampling period, a fog monitor was used to measure the size of
cloud droplets during cloud events (J. Li et al., 2017). This study reveals
that in the cloud events, all the cloud droplets displayed particle size
larger than 2 <inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in which size range the interstitial particles
were absent. Based on their different size, we can know that these cloud
droplets and interstitial particles impacted different positions on the
substrate. Although cloud droplets and interstitial particles dried after the collection, they can still be identified based on the distribution
and morphology of individual particles in TEM images (Kojima et al., 2004; Li
et al., 2011a; Ueda et al., 2014; Zhang et al., 2006). Cloud RES display
larger size and large rims around their CCN (Figs. 2 and 4), which has not
been observed in non-cloud events. In contrast, cloud INT impacted on the
position away from the center of the sampling spot and their morphology looks
like individual particles collected in non-cloud events. According to the
rule, we can identify cloud RES and cloud INT in the samples collected during
the cloud events.</p>
      <p id="d1e1201">Figure 7a shows that 100 % of cloud RES and 83 % of cloud INT contained
S-rich species (i.e., S-rich and S-refractory). In other words, none of
cloud RES were soot, fly ash/metal, and mineral particles, but 17 % of
cloud INT were. Soot particles were mainly distributed in the finer size bins
(<inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">600</mml:mn></mml:mrow></mml:math></inline-formula> nm) of cloud INT (Fig. S3a). Interestingly, we found that
76 % of cloud RES were a mixture of sulfates and refractory particles,
which is 3.5 times more than 22 % in cloud INT (Fig. 7a). Furthermore, 26 % of
cloud RES had two or more types of inclusions (i.e., S-fly ash/metal-soot in
Figs. 4d and 5d) but only 3 % of cloud INT did. Therefore, we can conclude
that cloud RES are extremely complex mixtures formed when cloud droplets act
like a collector to scavenge these refractory particles.</p>
      <p id="d1e1214">The size-resolved number fractions of different particle types in cloud RES
and cloud INT indicate that S-rich particles were predominant from 60 nm to
1.2 <inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in cloud INT (Fig. S3a), and S-refractory particles
(indicated by the red box) dominated from 400 nm to 5.5 <inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in
cloud RES (Fig. S3b). Figure 7b shows that the median diameters of cloud RES
and cloud INT were 1.19 <inline-formula><mml:math id="M50" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> and 422 nm, respectively. The size of
cloud RES was much larger than that of cloud INT, suggesting that size is an
important factor affecting the CCN ability (Dusek et al., 2006).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><caption><p id="d1e1249">Number fractions of different particle types in cloud RES
and INT particles <bold>(a)</bold> and size distributions of cloud RES and cloud INT
particles <bold>(b)</bold>. The measured particle sizes exclude the effects of water rims
in TEM images. In total, 292 cloud RES and 1161 cloud INT particles were
analyzed.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f07.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4">
  <title>Discussion</title>
      <p id="d1e1271">TEM observations in this study reveal that cloud RES contained large numbers
of refractory-containing particles primarily emitted from various
anthropogenic sources in the heavily polluted NCP. As much as 76 % of
cloud RES were identified as S-refractory particles (Fig. 7a). We found that
soot-containing particles (i.e., S-soot and S-fly ash/metal-soot) were the
most abundant (62 %) among the cloud RES, followed by the relatively
abundant fly ash/metal-containing particles (i.e., S-fly ash/metal and S-fly
ash/metal-soot, 37 %) compared with 18 % and 7 % in the cloud
INT, respectively (Fig. 7a). Although these refractory particles such as soot
with hydrophobic properties could not be CCN directly, they can be easily
accumulated by the existing cloud droplets as inclusions (Zuberi et al.,
2005). In the heavily polluted NCP, large numbers of soot and fly ash/metal
particles are released from anthropogenic sources (e.g., industrial
activities and vehicular exhaust). During cloud events, abundant refractory
particles can be efficiently entrained into existing liquid cloud droplets by
wet scavenging. Li et al. (2011a) reported that particle number decreased
dramatically during cloud formation at Mt. Tai with a scavenging ratio of
0.54, which demonstrated that aerosol particles could efficiently be
incorporated into cloud droplets. Physical coagulation of interstitial
particles with cloud droplets is an important process in developing clouds,
which can lead to the reduction of cloud INT number and a size increase of
cloud RES after the clouds dry (Pierce et al., 2015). As we know so far, the
extremely complicated mixture of secondary and primary particles observed in
the present study has seldom been found in cloud droplets in clean air over
developed countries (Hao et<?pagebreak page14688?> al., 2013; Kojima et al., 2004; Schneider et al.,
2017; Ueda et al., 2014), remote areas (Hiranuma et al., 2013) and the ocean
(Hopkins et al., 2008; Twohy and Anderson, 2008; Zhang et al., 2006). For
example, Zhang et al. (2006) reported that S-rich particles were predominant
in the cloud RES with a small number fraction of sea salt particles over the
Sea of Japan and soot or fly ash/metal particles were not observed. The
present study reveals that individual cloud droplets are a far more
complicated system in polluted air in North China than in the pristine
continental and clean ocean air of the world.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><caption><p id="d1e1276">TEM image of cloud RES and INT particles collected during the cloud
event that occurred on the polluted day of 31 July. Particles 1 and 2 are cloud RES
and particles 3, 4, 5, and 6 are cloud INT. The dashed lines indicate the
water rims that were left after the cloud droplets impacting the substrate dry.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f08.png"/>

      </fig>

      <p id="d1e1285">Cloud properties such as albedo and lifetimes could be largely modified
by the aerosol–cloud interactions, especially in heavily polluted regions
(Wang et al., 2010, 2013). The model simulation revealed
that black carbon aerosols had a noticeable impact (up to nearly 20 %) on
cloud droplet number concentration in polluted black carbon source regions
(Cherian et al., 2017). Especially, abundant black carbon
particles incorporated into cloud droplets could lead to a decrease in cloud
albedo by absorbing radiation and an increase of temperature in the troposphere,
then an acceleration of the evaporation of the cloud droplets (Ackerman et al.,
2000; Adachi et al., 2010; Wang et al., 2013; Zuberi et al., 2005). In the
past few decades, precipitation was significantly reduced over east central China due to the large amount of anthropogenic aerosols (Qian et al.,
2009; Zhao et al., 2006). Because an excess of aerosols in clouds could
reduce precipitation, the nonprecipitating clouds in the NCP tend to
evaporate back to aerosol particles by solar radiation. It is highly
probable that abundant black carbon particles present in the cloud
droplets in the heavily polluted NCP in this study (e.g., particles 1 and 2
in Fig. 8) significantly affected the cloud properties and regional climate.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><caption><p id="d1e1291">A conceptual model illustrating mechanisms of aerosol–cloud interactions on a mountaintop influenced by anthropogenic pollutants from heavy
industrial and urban emissions.</p></caption>
        <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/14681/2018/acp-18-14681-2018-f09.png"/>

      </fig>

      <p id="d1e1300">Fly ash and metal particles are a typical “fingerprint” pointing to the
coal-fired power plants and boilers in factories and heavy industries (e.g.,
steel plant and smelting factory) (Chen et al., 2012; Li et al., 2016a;
Moffet et al., 2008). Indeed, the most intense emissions from various
industries in the world occur in Hebei and Shandong provinces in the NCP (Qi
et al., 2017). It is well known that these industrial activities continuously
release anthropogenic pollutants via high stacks into the upper air. Liu et
al. (2012) reported that the concentration of Zn reached 249.1 <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> in the cloud and fog water samples at Mt. Tai, followed by Al
(157.3 <inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), Fe (105.8 <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), Pb
(46.2 <inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), and Mn (42.8 <inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), which were
much higher than those values reported at Mt. Schmücke in Germany
(Fomba et al., 2015). Combining these results with our present study, we
infer that fine primary particles emitted from these industrial activities
might spread and be lifted to the upper air more easily than at ground level.
These metal particles, especially Pb and Zn of nanometer size, can harm
ecosystems and human health (Roberts et al., 2004). The fly ash and metal
particles incorporated into cloud droplets (e.g., particle 1 in Fig. 8) could
go<?pagebreak page14689?> through the atmospheric acid Fe dissolution processes during long-range
transport reported by W. Li et al. (2017). If they were further transported
to remote oceanic regions, soluble Fe species in the aerosol particles can
fertilize plankton on the surface of the ocean (Ito and Shi, 2016; W. Li et al.,
2017). Therefore, these anthropogenic fly ash/metal particles in polluted air
contaminate cloud droplets and further amplify potential impacts of fine
metal particles on the biogeochemical cycle in the troposphere.</p>
      <p id="d1e1398">Some studies suggested that the aqueous oxidation of SO<inline-formula><mml:math id="M56" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> to sulfate by
H<inline-formula><mml:math id="M57" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M58" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and O<inline-formula><mml:math id="M59" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in cloud droplets was dominant at Mt. Tai (Shen et
al., 2012). However, cloud water collected on Mt. Tai contained high
concentrations of soluble Fe, Mn, Zn, and Pb (Liu et al., 2012). These
soluble metals in cloud droplets are released from aqueous reactions between
metal particles and acidic sulfates in cloud droplets (W. Li et al., 2017).
Harris et al. (2013) estimated that the oxidation of SO<inline-formula><mml:math id="M60" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in cloud
droplets catalyzed by natural transition metal ions (TMIs) in mineral dust
was dominant at Mt. Schmücke in Germany. For this study, how the soluble
anthropogenic TMIs drive sulfate formation through TMI catalysis in
micro-cloud droplets is still unresolved in polluted air. We propose that
anthropogenic TMI catalysis contributing to sulfate production should be
further studied in cloud droplets in the polluted NCP.</p>
      <p id="d1e1446">The nonprecipitating cloud processes over the polluted air of NCP quickly
change the composition of aerosol particles and cloud droplets in the upper
air, potentially causing various effects such as human health, regional
climate, and biogeochemical cycle at the larger regional scale. To better
illustrate the aerosol–cloud interactions in this study, we created the
conceptual model of Fig. 9. The tall stacks of plants can emit smoke plumes
that contain fine refractory particles and gaseous pollutants to the upper
air. A portion of particles in urban areas can also be lifted to the
mountaintop by prevailing valley winds. Once the clouds form on a
mountaintop (or are later transported in other directions), these cloud
droplets act as collectors to scavenge the refractory particles. These
refractory particles as inclusions might complicate the cloud chemistry in
micro-cloud droplets. Gaseous pollutants such as SO<inline-formula><mml:math id="M61" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, NO<inline-formula><mml:math id="M62" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>, and
VOCs may have enhanced aqueous oxidation potential in the complex cloud
droplets. Our study is designed to better understand the aerosol–cloud interactions on the mountaintop in polluted industrial and urban areas.
Recently, a study showed that the major aerosol pollution events with very
high fine-mode aerosol optical depth (<inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">1.0</mml:mn></mml:mrow></mml:math></inline-formula> in mid-visible) in the
China–Korean Peninsula–Japan region are often observed to be associated with
significant cloud cover (Eck et al., 2018). Therefore, we expect that
large numbers of fine refractory particles from polluted areas scavenging in
clouds have important impacts, not only at a local scale, but also at a large regional
scale.</p>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusions</title>
      <p id="d1e1484">Individual aerosol particles were collected during cloud events on Mt. Tai
from 22 July to 1 August 2014. Cloud RES and INT particles were separated by
their distribution on TEM grids, and their composition was identified by
TEM–EDS. Individual particles were classified into S-rich, refractory (i.e.,
mineral, soot, fly ash/metal), and S-refractory (i.e., S-mineral, S-soot,
S-fly ash/metal, and S-fly ash/metal-soot). According to air mass backward
trajectories and PM<inline-formula><mml:math id="M64" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5<?pagebreak page14690?></mml:mn></mml:msub></mml:math></inline-formula> concentrations on Mt. Tai, the entire sampling
period was divided into three classes: a clean period (PM<inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), a lightly polluted period (15 <inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> &lt; PM<inline-formula><mml:math id="M68" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> &lt; 35 <inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), and
a polluted period (PM<inline-formula><mml:math id="M70" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> &gt; 35 <inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). In
the clean period, individual particles were dominated by S-rich particles
(78 %), whereas the fraction of refractory particles and S-refractory
particles increased significantly and dominated during the polluted periods.
This suggested that anthropogenic pollutants from tall stacks of coal-fired
power plants and heavy industries and vehicular exhaust in cities could be
lifted to the summit of Mt. Tai under the prevailing southerly winds in
summer.</p>
      <p id="d1e1605">TEM observations showed that 76 % of cloud RES were S-refractory particles
contaminated by anthropogenic refractory particles, compared with only
22 % of cloud INT. Cloud RES displayed a larger size than cloud INT, which
indicates that particle size decidedly affects CCN ability. Our study
reveals that large numbers of anthropogenic refractory particles were
incorporated into cloud droplets through in-cloud processes. It is especially
important that abundant black carbon particles in cloud droplets could
alter the radiative forcing of clouds and accelerate the evaporation of cloud
droplets. The high concentrations of transition metal ions might favor the
aqueous-phase oxidation of SO<inline-formula><mml:math id="M72" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> by O<inline-formula><mml:math id="M73" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in cloud droplets under the
heavily polluted conditions in the NCP. Fly ash/metal-containing cloud
droplets could be transported long distances and harm ecosystems and human
health through wet deposition. We propose a conceptual model to show the
<?xmltex \hack{\mbox\bgroup}?>aerosol–cloud<?xmltex \hack{\egroup}?> interactions on mountaintops influenced by heavily polluted
air.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p id="d1e1634">All data presented in this paper are available upon
request. Please contact the corresponding author
(liweijun_atmos@gmail.com).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e1637">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-18-14681-2018-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-18-14681-2018-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution">

      <p id="d1e1646">LL and WL conceived the study and wrote the manuscript.
LL and JZ collected the individual particle samples. LL, JZ, QY, and LX carried
out the TEM and AFM measurements. All authors reviewed and commented on the paper.</p>
  </notes><notes notes-type="competinginterests">

      <p id="d1e1652">The authors declare that they have no conflict of interest.</p>
  </notes><notes notes-type="sistatement">

      <p id="d1e1658">This article is part of the special issue “Regional transport
and transformation of air pollution in eastern China”. It is not associated
with a conference.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e1664">We appreciate Peter Hyde's comments and proofreading. We thank Liang Wen at
Shandong University for his assistance of sample collections. This work was
funded by the National Key R&amp;D Program of China (2017YFC0212700), the National
Natural Science Foundation of China (41575116, 41622504, and 41805099), the State
Key Laboratory of Atmospheric Boundary Physics and Atmospheric Chemistry
(LAPC-KF-2017-02), and the Hundred Talents Program in Zhejiang
University.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by: Zhanqing
Li<?xmltex \hack{\newline}?> Reviewed by: two anonymous referees</p></ack><ref-list>
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    <!--<article-title-html>Cloud scavenging of anthropogenic refractory particles at a mountain site in North China</article-title-html>
<abstract-html><p>Aerosol–cloud interactions remain a major source of uncertainty
in climate forcing estimates. Few studies have been conducted to characterize
the aerosol–cloud interactions in heavily polluted conditions worldwide. In
this study, cloud residual and cloud interstitial particles were collected
during cloud events under different pollution levels from 22 July to 1 August
2014 at Mt. Tai (1532&thinsp;m above sea level) located in the North China Plain (NCP). A
transmission electron microscope was used to investigate the morphology, size,
and chemical composition of individual cloud residual and cloud interstitial
particles, and to study mixing properties of different aerosol components in
individual particles. Our results show that S-rich particles were predominant
(78&thinsp;%) during clean periods (PM<sub>2.5</sub><i>&lt;</i>15&thinsp;µg m<sup>−3</sup>), but a large number of anthropogenic refractory particles (e.g.,
soot, fly ash, and metal) and their mixtures with S-rich particles (defined as <q>S-refractory</q>)
were observed during polluted periods. Cloud droplets collected
during polluted periods were found to become an extremely complicated mixture
by scavenging abundant refractory particles. We found that 76&thinsp;% of cloud
residual particles were S-refractory particles and that 26&thinsp;% of cloud
residual particles contained two or more types of refractory particles.
Soot-containing particles (i.e., S-soot and S-fly ash/metal-soot) were the
most abundant (62&thinsp;%) among cloud residual particles, followed by fly
<span style="" class="text">ash/metal-containing</span> particles (i.e., S-fly ash/metal and S-fly
ash/metal-soot, 37&thinsp;%). These complicated cloud droplets have not been
reported in clean continental or marine air before. Our findings provide an
insight into the potential impacts on cloud radiative forcing from black
carbon and metal catalyzed reactions of SO<sub>2</sub> in micro-cloud droplets
containing soluble metals released from fly ash and metals over polluted air.</p></abstract-html>
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