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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" dtd-version="3.0"><?xmltex \makeatother\@nolinetrue\makeatletter?>
  <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-17-2067-2017</article-id><title-group><article-title>Constraining the ship contribution to the aerosol <?xmltex \hack{\newline}?> of the central Mediterranean</article-title>
      </title-group><?xmltex \runningtitle{Constraining the ship contribution to the aerosol of the central Mediterranean}?><?xmltex \runningauthor{S.~Becagli et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Becagli</surname><given-names>Silvia</given-names></name>
          <email>silvia.becagli@unifi.it</email>
        <ext-link>https://orcid.org/0000-0003-3633-4849</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Anello</surname><given-names>Fabrizio</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Bommarito</surname><given-names>Carlo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2944-1219</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Cassola</surname><given-names>Federico</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Calzolai</surname><given-names>Giulia</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-9476-1470</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Di Iorio</surname><given-names>Tatiana</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>di Sarra</surname><given-names>Alcide</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6 aff7">
          <name><surname>Gómez-Amo</surname><given-names>José-Luis</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Lucarelli</surname><given-names>Franco</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Marconi</surname><given-names>Miriam</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Meloni</surname><given-names>Daniela</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Monteleone</surname><given-names>Francesco</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Nava</surname><given-names>Silvia</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Pace</surname><given-names>Giandomenico</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Severi</surname><given-names>Mirko</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-1511-6762</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Sferlazzo</surname><given-names>Damiano Massimiliano</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Traversi</surname><given-names>Rita</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-9790-2195</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff9">
          <name><surname>Udisti</surname><given-names>Roberto</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Department of Chemistry, University of Florence, Sesto Fiorentino, 50019 Florence, Italy</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>ENEA, Laboratory for Observations and Analyses of Earth and Climate, 90141 Palermo, Italy</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Department of Physics &amp; INFN, University of Genoa, 16146 Genoa, Italy</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>ARPAL-Unità Operativa CFMI-PC, 16129 Genova, Italy</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Department of Physics, University of Florence &amp; INFN-Firenze, Sesto Fiorentino, 50019 Florence, Italy</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>ENEA, Laboratory for Observations and Analyses of Earth and Climate, 00123 Rome, Italy</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Department of Earth Physics and Thermodynamics, University of Valencia, Valencia, Spain</institution>
        </aff>
        <aff id="aff8"><label>8</label><institution>ENEA, Laboratory for Observations and Analyses of Earth and Climate, 92010 Lampedusa, Italy</institution>
        </aff>
        <aff id="aff9"><label>9</label><institution>ISAC CNR, Via Gobetti 101, 40129, Bologna, Italy</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Silvia Becagli (silvia.becagli@unifi.it)</corresp></author-notes><pub-date><day>10</day><month>February</month><year>2017</year></pub-date>
      
      <volume>17</volume>
      <issue>3</issue>
      <fpage>2067</fpage><lpage>2084</lpage>
      <history>
        <date date-type="received"><day>8</day><month>June</month><year>2016</year></date>
           <date date-type="rev-request"><day>1</day><month>July</month><year>2016</year></date>
           <date date-type="rev-recd"><day>23</day><month>November</month><year>2016</year></date>
           <date date-type="accepted"><day>19</day><month>January</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017.html">This article is available from https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017.html</self-uri>
<self-uri xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017.pdf</self-uri>


      <abstract>
    <p>Particulate matter with aerodynamic diameters lower than 10 <inline-formula><mml:math id="M1" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m, (PM<inline-formula><mml:math id="M2" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>) aerosol samples were collected during summer 2013 within the
framework of the Chemistry and Aerosol Mediterranean Experiment (ChArMEx) at
two sites located north (Capo Granitola) and south (Lampedusa Island),
respectively, of the main Mediterranean shipping route in the Straight of Sicily.</p>
    <p>The PM<inline-formula><mml:math id="M3" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> samples were collected with 12 h time resolutions at both
sites. Selected metals, main anions, cations and elemental and organic
carbon were determined.</p>
    <p>The evolution of soluble V and Ni concentrations (typical markers of heavy
fuel oil combustion) was related to meteorology and ship traffic intensity
in the Straight of Sicily, using a high-resolution regional model for
calculation of back trajectories. Elevated concentration of V and Ni at Capo
Granitola and Lampedusa are found to correspond with air masses from the
Straight of Sicily and coincidences between trajectories and positions of large
ships; the vertical structure of the planetary boundary layer also appears
to play a role, with high V values associated with strong inversions and
a stable boundary layer. The V concentration was generally lower at Lampedusa
than at Capo Granitola V, where it reached a peak value of 40 ng m<inline-formula><mml:math id="M4" 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>.</p>
    <p>Concentrations of rare earth elements (REEs), La and Ce in particular, were used to
identify possible contributions from refineries, whose emissions are also
characterized by elevated V and Ni amounts; refinery emissions are expected
to display high La <inline-formula><mml:math id="M5" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ce and La <inline-formula><mml:math id="M6" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V ratios due to the use of La in the fluid
catalytic converter systems. In general, low La <inline-formula><mml:math id="M7" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ce and La <inline-formula><mml:math id="M8" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V ratios were
observed in the PM samples. The combination of the analyses based on
chemical markers, air mass trajectories and ship routes allows us to
unambiguously identify the large role of the ship source in the Straight of Sicily.</p>
    <p>Based on the sampled aerosols, ratios of the main aerosol species arising
from ship emission with respect to V were estimated with the aim of deriving
a lower limit for the total ship contribution to PM<inline-formula><mml:math id="M9" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>. The estimated
minimum ship emission contributions to PM<inline-formula><mml:math id="M10" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> were 2.0 <inline-formula><mml:math id="M11" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M12" 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> at
Lampedusa and 3.0 <inline-formula><mml:math id="M13" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M14" 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> at Capo Granitola, corresponding
with 11 and 8.6 % of PM<inline-formula><mml:math id="M15" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>, respectively.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

      <?xmltex \hack{\newpage}?>
<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Ship emissions may significantly affect atmospheric concentrations of
several important pollutants, especially in maritime and coastal areas
(e.g. Endresen et al., 2003). Main emitted compounds are carbon dioxide (CO<inline-formula><mml:math id="M16" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>),
nitrogen oxides (NO<inline-formula><mml:math id="M17" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>), sulfur dioxide (SO<inline-formula><mml:math id="M18" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), carbon
monoxide (CO), hydrocarbons and primary as well as secondary particles. Thus, ship
emissions impact the greenhouse gas budget, (Stern, 2007), acid rain – through
NO<inline-formula><mml:math id="M19" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> and SO<inline-formula><mml:math id="M20" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> oxidation products (Derwent at al., 2005), human
health – through CO, hydrocarbons, particles (Lloyd's Register Engineering Services, 1995; Corbett et al., 2007) and solar radiation budget through
aerosol direct and indirect effects such as black carbon and sulfur containing
particles (Devasthale et al., 2006; Lauer et al., 2007; Coakley Jr. and Walsh, 2002).</p>
      <p>Heavy oil fuels used by ships contain varying transition metals. The aerosol
emitted by ship engines is formed at high temperatures (<inline-formula><mml:math id="M21" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 800 <inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C)
from V, Ni and Fe compounds (Sippula et al., 2009). The
thermodynamics predict that the metals in these particles are mainly
present as oxides. Sulfuric acid is found to form a liquid layer on the
metal oxide ultrafine particles, leading to the metal partial dissolution,
probably increasing the toxicity of the particles when inhaled.</p>
      <p>In spite of the large amount of gas and particulate emitted by ships,
maritime transport is relatively clean if calculated per kilogram of
transported good. However, maritime transport has been increasing with
respect to air and road transport (Micco and Pérez, 2001; Grewal and
Haugstetter, 2007). In addition, emissions from other transport sectors are
decreasing due to the implementation of advanced emission reduction
technologies, and the relative impact of shipping emissions is increasing.</p>
      <p>Regulations aiming at reducing emissions based on restrictions on the fuel
sulfur content (sulfur emission control areas, or SECAs) have been implemented
in several regions. Although the legislation is focussed on sulfur
emissions, the overall health and environmental effects depend in a complex
way on the physical and chemical properties of the emissions (WHO, 2013).
Several studies have been carried out to determine the detailed chemical
composition of shipping emissions (Agrawal et al., 2008a, b; Moldanová
et al., 2009; Murphy et al., 2009; Lyyränen et al., 1999;
Cooper, 2003; Sippula et al., 2014); however, the ships emissions are still
poorly characterized with respect to on-road vehicles.</p>
      <p>A large variety of anthropic sources (refineries, power plants intense ship
traffic, etc.) and natural emissions make the Mediterranean region one of
the most polluted in the world (e.g. Kouvarakis et al., 2000; Marmer and
Langmann, 2005). The multiplicity of Mediterranean sources (some of which
with the same markers of ship aerosol) makes the quantification of
ship contribution to the total aerosol amount difficult (e.g. Becagli et al., 2012).</p>
      <p>The contribution of ships and harbour emissions to local air quality, with
specific focus on atmospheric aerosol, has been investigated using models
(Trozzi et al., 1995; Gariazzo et al., 2007; Eyring et al., 2005; Marmer et
al., 2009), experimental analyses at high temporal resolution (Ault et al.,
2010; Contini et al., 2011; Jonsson et al., 2011; Diesch et al., 2013;
Donateo et al., 2014), receptor models based on the identification of
chemical tracers associated with ship emissions (Viana et al., 2009;
Pandolfi et al., 2011; Cesari et al., 2014) and integrated approaches with
receptor and chemical transport models (Bove et al., 2014). Few studies
exist in open sea (Becagli et al., 2012; Schembari et al., 2014; Bove et al., 2016).</p>
      <p>In this context, studies performed at Mediterranean sites where it is
possible to distinguish ship emission from other sources of heavy fuel oil
combustion, are important to investigate the current impact of the ship
emissions on primary and secondary aerosols. This study contributes to the
identification and characterization of the emissions from ships and the
impact on the aerosol distribution in the central Mediterranean. The
experiment was set up with the aim of unambiguously recognizing the ship
source by a combination of methods.</p>
</sec>
<sec id="Ch1.S2">
  <title>Measurements and methods</title>
      <p>In a previous study (Becagli et al., 2012), we used measurements of PM<inline-formula><mml:math id="M23" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>
concentration and chemical composition carried out at Lampedusa to
investigate the role of ship emissions in the central Mediterranean.
Vanadium and Nickel were used as tracers of heavy fuel combustion together
with trajectory analyses to assess the role of ship traffic. The ship
source, however, could not be unequivocally separated from possible
influences from refineries and power plants, which use similar fuels. In
summer 2013 we addressed the same topic by implementing a specific strategy
to target the aerosols due to ship emissions. PM<inline-formula><mml:math id="M24" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> samples were
collected in parallel at Lampedusa (LMP) and at Capo Granitola (CGR) respectively, i.e. south and north of the main shipping route through the
Mediterranean, with the aim of isolating the ship source. The chemical
analyses of the collected samples were complemented with measurements of REEs, trajectories and planetary boundary layer
information from a high resolution regional model and actual observations
of ship traffic. The combination of these approaches allows the unambiguous
identification of the ship source and permits the constraint of its contribution to
PM<inline-formula><mml:math id="M25" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> in the central Mediterranean.
an
The PM<inline-formula><mml:math id="M26" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> samples were collected in summer 2013 as a contribution to the
Chemistry and Aerosol Mediterranean Experiment (ChArMEx;
<uri>http://charmex.lsce.ispl.fr</uri>). Lampedusa is one of the supersites of the
ChArMEx experiment; a list of the instruments deployed during the special
observing period (1a) of ChArMEx, of the measurement strategy,
meteorological conditions and main observations is given by Mallet et al., (2016).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Map of the study area with the sites of Lampedusa (LMP) and Capo
Granitola (CGR) are displayed in the left panel. A–C indicate the three sites selected to study
the stability of the boundary layer in the Straight of Sicily (see Sect. 3.2.2).
The ship routes in the study area during the first 10 days of June 2013 are
displayed in the right panel. Red and blue dots show the routes of merchant and
fishing vessels, respectively.</p></caption>
        <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f01.png"/>

      </fig>

<?xmltex \hack{\newpage}?>
<sec id="Ch1.S2.SS1">
  <title>Aerosol sampling and chemical analyses</title>
      <p>PM<inline-formula><mml:math id="M27" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> was sampled at two sites: at the station for climate Observations,
maintained by ENEA (the Italian Agency for New Technologies, Energy, and
Sustainable Economic Development) on the island of Lampedusa
(35.5<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 12.6<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E), and at the Italian CNR (National
Research Council) Research Centre at Capo Granitola (36.6<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 12.6<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E).</p>
      <p>Lampedusa is a small island in the Central Mediterranean sea, more than 100 km
far from the nearest Tunisian coast. At the station for climate
Observations, which is located on a  plateau 45  m a.s.l on the northeastern
coast of Lampedusa, continuous observations of aerosol properties (di Sarra
et al., 2011, 2015; Becagli et al., 2013; Marconi et al., 2014; Calzolai et
al., 2015; Sellitto et al., 2017), aerosol radiative effects (e.g.
Casasanta et al., 2011; di Sarra et al., 2011; Meloni et al., 2015) and
other climatic parameters are carried out. Figure 1 shows the map of the
central Mediterranean with the measurement stations.</p>
      <p>PM<inline-formula><mml:math id="M32" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> is routinely sampled on a daily basis at LMP (Becagli et al.,
2013; Marconi et al., 2014; Calzolai et al., 2015) by using a low-volume
dual-channel sequential sampler (HYDRA FAI Instruments) equipped with two
PM<inline-formula><mml:math id="M33" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> sampling heads, operating in accord with UNI EN12341. For the
intensive ChArMEx campaign, samples were collected at 12 h resolution
(08:00–20:00 and 20:00–08:00 LT–local time) from 1 June to 3 August 2013.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Sampling strategy and chemical measurements carried out on each filter
for the two sites: Lampedusa (LMP) and Capo Granitola (CGR). The sampling time interval is at local time (LT).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:thead>
       <oasis:row>

         <oasis:entry colname="col1">Sampling</oasis:entry>

         <oasis:entry colname="col2">Filter</oasis:entry>

         <oasis:entry colname="col3">Sampling</oasis:entry>

         <oasis:entry colname="col4">Measurements</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">site</oasis:entry>

         <oasis:entry colname="col2"/>

         <oasis:entry colname="col3">interval (LT)</oasis:entry>

         <oasis:entry colname="col4"/>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry rowsep="1" colname="col1" morerows="11">LMP</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="6">Teflon</oasis:entry>

         <oasis:entry colname="col3">08:00-20:00</oasis:entry>

         <oasis:entry colname="col4">– PM<inline-formula><mml:math id="M34" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>;</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(daytime sample)</oasis:entry>

         <oasis:entry colname="col4">– ions by IC (<inline-formula><mml:math id="M35" 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> of the filter);</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">20:00–08:00</oasis:entry>

         <oasis:entry colname="col4">– metals in HNO<inline-formula><mml:math id="M36" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> pH 1.5 room</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(nighttime</oasis:entry>

         <oasis:entry colname="col4">temperature extract by ICP-AES (<inline-formula><mml:math id="M37" 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></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">sample)</oasis:entry>

         <oasis:entry colname="col4">of the filter);</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">– metals in HNO<inline-formula><mml:math id="M38" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>-H<inline-formula><mml:math id="M39" 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="M40" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in microwave</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">oven extract by ICP-AES (<inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> filter)</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col2" morerows="3">Quartz</oasis:entry>

         <oasis:entry colname="col3">08:00–20:00</oasis:entry>

         <oasis:entry colname="col4">– EC <inline-formula><mml:math id="M42" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> OC by thermo-optical analyser</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(daytime sample)</oasis:entry>

         <oasis:entry colname="col4">(1.5 cm <inline-formula><mml:math id="M43" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 cm punch)</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">20:00–08:00</oasis:entry>

         <oasis:entry colname="col4"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(nighttime</oasis:entry>

         <oasis:entry colname="col4"/>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col2"/>

         <oasis:entry colname="col3">sample)</oasis:entry>

         <oasis:entry colname="col4"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1" morerows="9">CGR</oasis:entry>

         <oasis:entry colname="col2" morerows="9">Quartz</oasis:entry>

         <oasis:entry colname="col3">08:00–20:00</oasis:entry>

         <oasis:entry colname="col4">– PM<inline-formula><mml:math id="M44" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>;</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(daytime sample)</oasis:entry>

         <oasis:entry colname="col4">– ions by IC (1.5 cm <inline-formula><mml:math id="M45" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 cm punch);</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">20:00–08:00</oasis:entry>

         <oasis:entry colname="col4">– metals in HNO<inline-formula><mml:math id="M46" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> pH 1.5 room</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">(nighttime</oasis:entry>

         <oasis:entry colname="col4">temperature extract by ICP-AES</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">sample)</oasis:entry>

         <oasis:entry colname="col4">(1.5 cm <inline-formula><mml:math id="M47" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 cm punch);</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">– metals in HNO<inline-formula><mml:math id="M48" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>-H<inline-formula><mml:math id="M49" 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="M50" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in microwave</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">oven extract by ICP-AES (1.5 cm <inline-formula><mml:math id="M51" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">1 cm punch)</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">– EC <inline-formula><mml:math id="M52" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> OC by thermo-optical analyser</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3"/>

         <oasis:entry colname="col4">(1.5 cm <inline-formula><mml:math id="M53" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 cm punch)</oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>The two channels operated in parallel and were loaded with different types
of filters: the first one with 47 mm diameter, 2 <inline-formula><mml:math id="M54" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m-nominal porosity
Teflon filters, and the second one with 47 mm pre-fired, 2 <inline-formula><mml:math id="M55" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m-nominal
porosity quartz filters. Ion chromatographic analysis of soluble ions,
atomic emission spectroscopy for soluble metals and proton-induced X-ray
emission (PIXE) for the total (soluble <inline-formula><mml:math id="M56" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> insoluble) elemental composition
were carried out on the Teflon filters. Elemental carbon (EC) and organic carbon (OC)
were measured by analysing the quartz filters.</p>
      <p>The sampling site at CGR is located at Torretta Granitola, a Research Center
of the Italian National Research Council, in southwestern Sicily (12 km
from Mazara del Vallo). The sampler was installed on the roof of one of the
research centre buildings at about 20 m a.s.l., directly on the coastline,
facing the Straight of Sicily.</p>
      <p>At CGR PM<inline-formula><mml:math id="M57" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> samples were collected at 12 h resolution (08:00–20:00 and
20:00–08:00 LT) with a TECORA Skypost sequential sampler on 47 mm
pre-fired 2 <inline-formula><mml:math id="M58" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m-nominal porosity quartz filters, which were used to
determine ions, metals, EC and OC on different fractions of the filter. Due
to technical problems, some daytime (08:00–20:00 LT) samplings were lost at CGR.</p>
      <p>The PM<inline-formula><mml:math id="M59" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> mass was determined by weighting the filters before and after
sampling with an analytical balance in controlled conditions of temperature
(20 <inline-formula><mml:math id="M60" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1 <inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) and relative humidity (50 <inline-formula><mml:math id="M62" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5 %). The
estimated error on PM<inline-formula><mml:math id="M63" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> mass is around 1 % at 30 <inline-formula><mml:math id="M64" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M65" 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> in
the applied sampling conditions.</p>
      <p>A quarter of each Teflon filter from LMP and a 1.5 cm<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> punch of the
quartz filter from CGR were analysed by Ion Chromatography (IC) in the
analytical conditions described in Marconi et al., (2014). The estimated
uncertainty for IC measurements is 5 % for all the considered ions.</p>
      <p>Blank values were negligible with respect to the concentration in the
samples for Teflon filters. Blank values for quartz filters were negligible
for most of the analysed species. For some species characterized by high
blank values, always lower than the 25th percentile value, they were
subtracted from the measured concentrations.</p>
      <p>Another quarter of the Teflon filter from LMP and another 1.5 cm<inline-formula><mml:math id="M67" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula>
punch of the quartz filter from CGR were extracted in an ultrasonic bath for
15 min with MilliQ water acidified at pH 1.5–2 with ultra pure HNO<inline-formula><mml:math id="M68" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
obtained by sub-boiling distillation. This extract was used for the metal's
soluble part determination by means of an Inductively Coupled Plasma Atomic
Emission Spectrometer (ICP-AES, Varian 720-ES) equipped with an ultrasonic
nebulizer (U5000 AT<inline-formula><mml:math id="M69" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>, Cetac Technologies Inc.). The pH chosen value is the
lowest found in rainwater (Li and Aneja, 1992) and leads to the
determination of the metals fraction available to biological organisms and,
for some metals (e.g. V and Ni), related to the anthropic source (Becagli et al., 2012).</p>
      <p>The remaining half Teflon filter from Lampedusa, another punch of the quartz
filter from CGR, was used for the determination of metals by ICP-AES through
the solubilisation procedure reported in the EU EN14902 (2005) rule, by
concentrating sub-boiling distilled HNO<inline-formula><mml:math id="M70" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and 30 % ultra pure
H<inline-formula><mml:math id="M71" 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="M72" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in a microwave oven at 220 <inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C for 25 min (P <inline-formula><mml:math id="M74" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 55 bar).
This solubilisation procedure is not able to completely dissolve the
silicate species. However, this procedure allows to the recovery at least 70 %
of the same elements measured by a proton induced X-ray emission technique
also for elements with dominant crustal source (unpublished data) due to
the low crustal aerosol load in these sampling periods (e.g. Mailler et al.,
2016). La and Ce presented very low concentrations in the collected aerosol
samples. Thus, particular attention was devoted to the minimization of the
La and Ce detection limit. In the used sampling and analytical conditions of
LMP samples the detection limits for La and Ce are 0.02 and 0.08 ng m<inline-formula><mml:math id="M75" 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, and are about 4 times higher for the CGR samples, due to the
smaller filter portion used for the analysis.
The OC and EC measurements were carried out on a 1.5 cm<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> punch of the
quartz filters from Lampedusa and Capo Granitola by means of a Sunset
thermo-optical transmittance analyser, following the NIOSH protocol (Wu et al., 2016).</p>
      <p>The overall aerosol sampling and analytical strategy for the two sites are
reported in Table 1.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Atmospheric model and trajectory calculations</title>
      <p>Numerical simulations with a non-hydrostatic mesoscale atmospheric model
were used to characterize the meteorological conditions in the Straight of Sicily
during the campaign and to support the interpretation of the
experimental results. The Weather Research and Forecasting (WRF) model
(Skamarock et al., 2008) outputs, provided by the Department of Physics of
the University of Genoa, Italy, were used, covering the entire Mediterranean
with a grid spacing of 10 km and hourly temporal resolution. Initial and
boundary conditions to drive WRF simulations were obtained from the Global
Forecast System operational global model (Environmental Modeling Center,
2003) outputs (0.5 <inline-formula><mml:math id="M77" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5 squared degrees). Some recent applications of the
modelling chain are described in Mentaschi et al., (2015) and Cassola et al., (2016),
where full details on the model configuration can also be found.</p>
      <p>In particular, the WRF 3-D hourly meteorological fields were used to
calculate backward trajectories with the NOAA HYbrid Single-Particle
Lagrangian Integrated Trajectory Model (HYSPLIT; Stein et al., 2015). The
trajectories were used to assess the origin of the air masses impacting the
monitoring sites and to support the source attribution suggested by the
analysis of specific markers (see Sect. 3.2.2). The use of a
high-resolution regional atmospheric model for trajectory calculations
allows for a better representation of boundary layer properties and mesoscale
phenomena such as land and sea breezes, which can have a relevant impact
especially in complex topography coastal sites like CGR.</p>
      <p>Also, the high temporal resolution of meteorological data (hourly instead of
three- or six-hourly products typically available from global models)
permits a better description of diurnal cycles and a more accurate
trajectory computation without time interpolation between subsequent
atmospheric fields (Solomos et al., 2015).</p>
      <p>Specifically, 48 h-long back trajectories arriving at LMP and CGR were
computed from a reference height of 10 m above the ground level, starting
every six hours for the whole period of the campaign, from 10 June to 31 July 2013.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <title>Ships/marine traffic</title>
      <p>Position and main characteristics of the ships travelling in the central
Mediterranean were derived from the MarineTraffic database
(<uri>http://www.marinetraffic.com/</uri>), which provides data with a high temporal
resolution (about 3–5 min) by means of the Automatic Identification System (AIS).</p>
      <p>Three classes of ships defined by the AIS classification were considered:
all the ships, the merchant ships (i.e. cargo and tanker) and the fishing
vessels. Merchant and fishing vessels are the most frequent ships in the
Straight of Sicily; merchant ships are expected to produce the highest impact
due to their higher emissions (<uri>http://ec.europa.eu/environment/archives/air/pdf/chapter2_ship_emissions.pdf</uri>).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>Time series of the main aerosol components at LMP <bold>(a)</bold> and
CGR <bold>(b)</bold>. Note the different vertical scales of the graphs. OA, EC, and
SSA stand for organic aerosol, elemental carbon and sea salt aerosol, respectively.</p></caption>
          <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f02.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Scatter plot of OC vs. EC at LMP <bold>(a)</bold> and CGR <bold>(b)</bold>. Note
the different vertical scales.</p></caption>
          <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f03.png"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><caption><p>Mean and standard deviation of PM<inline-formula><mml:math id="M78" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> load and composition, and
percentage with respect to PM<inline-formula><mml:math id="M79" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> (in brackets) at Lampedusa and Capo Granitola.
Mean, standard deviation and percentage are calculated on homogeneous data sets
for both sites, considering all the common sampling (“all data” columns) and
excluding the mistral events (“mistral excluded” columns).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="6">
     <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:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry rowsep="1" namest="col2" nameend="col3" align="center">Lampedusa </oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry rowsep="1" namest="col5" nameend="col6" align="center">Capo Granitola </oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">All data</oasis:entry>  
         <oasis:entry colname="col3">Mistral</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">All data</oasis:entry>  
         <oasis:entry colname="col6">Mistral</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3">excluded</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6">excluded</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">PM<inline-formula><mml:math id="M80" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> (<inline-formula><mml:math id="M81" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M82" 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">18.0 <inline-formula><mml:math id="M83" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.6</oasis:entry>  
         <oasis:entry colname="col3">16.3 <inline-formula><mml:math id="M84" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.2</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">34.1 <inline-formula><mml:math id="M85" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 18.9</oasis:entry>  
         <oasis:entry colname="col6">27.2 <inline-formula><mml:math id="M86" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.5</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Sea Salt</oasis:entry>  
         <oasis:entry colname="col2">4.63 <inline-formula><mml:math id="M87" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.30</oasis:entry>  
         <oasis:entry colname="col3">2.33 <inline-formula><mml:math id="M88" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.21</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">8.14 <inline-formula><mml:math id="M89" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 15.50</oasis:entry>  
         <oasis:entry colname="col6">2.12 <inline-formula><mml:math id="M90" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.51</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Aerosol</oasis:entry>  
         <oasis:entry colname="col2">(25.7 %)</oasis:entry>  
         <oasis:entry colname="col3">(14.3 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(23.9 %)</oasis:entry>  
         <oasis:entry colname="col6">(7.8 %)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M91" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M92" 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"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Crustal Aerosol</oasis:entry>  
         <oasis:entry colname="col2">0.82 <inline-formula><mml:math id="M93" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.44</oasis:entry>  
         <oasis:entry colname="col3">0.90 <inline-formula><mml:math id="M94" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.43</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">2.80 <inline-formula><mml:math id="M95" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.7</oasis:entry>  
         <oasis:entry colname="col6">3.02 <inline-formula><mml:math id="M96" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.75</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M97" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M98" 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">(4.6 %)</oasis:entry>  
         <oasis:entry colname="col3">(5.5 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(8.2 %)</oasis:entry>  
         <oasis:entry colname="col6">(11.1 %)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">nssSO<inline-formula><mml:math id="M99" 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></oasis:entry>  
         <oasis:entry colname="col2">3.95 <inline-formula><mml:math id="M100" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.28</oasis:entry>  
         <oasis:entry colname="col3">4.40 <inline-formula><mml:math id="M101" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.22</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">6.78 <inline-formula><mml:math id="M102" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.08</oasis:entry>  
         <oasis:entry colname="col6">7.53 <inline-formula><mml:math id="M103" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.78</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M104" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g 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>)</oasis:entry>  
         <oasis:entry colname="col2">(21.9 %)</oasis:entry>  
         <oasis:entry colname="col3">(27.0 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(19.9 %)</oasis:entry>  
         <oasis:entry colname="col6">(27.7 %)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">NH<inline-formula><mml:math id="M106" 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></oasis:entry>  
         <oasis:entry colname="col2">0.98 <inline-formula><mml:math id="M107" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.56</oasis:entry>  
         <oasis:entry colname="col3">1.09 <inline-formula><mml:math id="M108" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.55</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">1.48 <inline-formula><mml:math id="M109" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.94</oasis:entry>  
         <oasis:entry colname="col6">1.66 <inline-formula><mml:math id="M110" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.87</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M111" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M112" 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">(5.5 %)</oasis:entry>  
         <oasis:entry colname="col3">(6.7 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(4.3 %)</oasis:entry>  
         <oasis:entry colname="col6">(6.1 %)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">NO<inline-formula><mml:math id="M113" 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></oasis:entry>  
         <oasis:entry colname="col2">1.25 <inline-formula><mml:math id="M114" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.00</oasis:entry>  
         <oasis:entry colname="col3">1.02 <inline-formula><mml:math id="M115" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.02</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">1.35 <inline-formula><mml:math id="M116" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.11</oasis:entry>  
         <oasis:entry colname="col6">1.01 <inline-formula><mml:math id="M117" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.82</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M118" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M119" 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">(7.0 %)</oasis:entry>  
         <oasis:entry colname="col3">(6.2 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(4.0 %)</oasis:entry>  
         <oasis:entry colname="col6">(3.7 %)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Organic</oasis:entry>  
         <oasis:entry colname="col2">3.86 <inline-formula><mml:math id="M120" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.56</oasis:entry>  
         <oasis:entry colname="col3">4.04 <inline-formula><mml:math id="M121" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.59</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">9.02 <inline-formula><mml:math id="M122" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.52</oasis:entry>  
         <oasis:entry colname="col6">9.53 <inline-formula><mml:math id="M123" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.29</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">aerosol</oasis:entry>  
         <oasis:entry colname="col2">(21.4 %)</oasis:entry>  
         <oasis:entry colname="col3">(24.8 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(26.5 %)</oasis:entry>  
         <oasis:entry colname="col6">(35.0 %)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M124" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M125" 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"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Elemental</oasis:entry>  
         <oasis:entry colname="col2">0.15 <inline-formula><mml:math id="M126" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08</oasis:entry>  
         <oasis:entry colname="col3">0.15 <inline-formula><mml:math id="M127" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">0.44 <inline-formula><mml:math id="M128" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.28</oasis:entry>  
         <oasis:entry colname="col6">0.51 <inline-formula><mml:math id="M129" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.26</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">carbon</oasis:entry>  
         <oasis:entry colname="col2">(0.8 %)</oasis:entry>  
         <oasis:entry colname="col3">(0.9 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(1.3 %)</oasis:entry>  
         <oasis:entry colname="col6">(1.9 %)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M130" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M131" 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"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Unknown</oasis:entry>  
         <oasis:entry colname="col2">2.52 <inline-formula><mml:math id="M132" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.26</oasis:entry>  
         <oasis:entry colname="col3">2.20 <inline-formula><mml:math id="M133" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.40</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">4.11 <inline-formula><mml:math id="M134" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.78</oasis:entry>  
         <oasis:entry colname="col6">1.82 <inline-formula><mml:math id="M135" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.48</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">(<inline-formula><mml:math id="M136" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M137" 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">(14.0 %)</oasis:entry>  
         <oasis:entry colname="col3">(13.5 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(12.1 %)</oasis:entry>  
         <oasis:entry colname="col6">(6.7 %)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results</title>
<sec id="Ch1.S3.SS1">
  <?xmltex \opttitle{PM${}_{{10}}$ chemical composition at the two sites}?><title>PM<inline-formula><mml:math id="M138" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> chemical composition at the two sites</title>
      <p>The sea salt aerosol (SSA) component of PM<inline-formula><mml:math id="M139" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> was estimated as the sum
of Na<inline-formula><mml:math id="M140" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>, Mg<inline-formula><mml:math id="M141" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, Ca<inline-formula><mml:math id="M142" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, K<inline-formula><mml:math id="M143" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>, sulfate and chloride sea salt (ss)
fractions. Details on the calculation of sea salt Na<inline-formula><mml:math id="M144" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and
Ca<inline-formula><mml:math id="M145" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, and non-sea salt (nss) fractions are reported in Marconi et al., (2014).
The Mg<inline-formula><mml:math id="M146" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, Ca<inline-formula><mml:math id="M147" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, K<inline-formula><mml:math id="M148" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and sulphate sea salt fractions
were calculated from sea salt Na<inline-formula><mml:math id="M149" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> (ssNa<inline-formula><mml:math id="M150" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>) by using the ratio of
each component to Na<inline-formula><mml:math id="M151" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> in bulk sea water: Mg<inline-formula><mml:math id="M152" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M153" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Na<inline-formula><mml:math id="M154" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M155" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.129,
Ca<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M157" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Na<inline-formula><mml:math id="M158" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M159" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.038, K<inline-formula><mml:math id="M160" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M161" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Na<inline-formula><mml:math id="M162" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M163" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.036,
SO<inline-formula><mml:math id="M164" 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> <inline-formula><mml:math id="M165" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Na<inline-formula><mml:math id="M166" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M167" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.253 (Bowen, 1979). Chloride undergoes
depletion processes during the aging of sea spray, mainly due to exchange
reactions with anthropogenic H<inline-formula><mml:math id="M168" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>SO<inline-formula><mml:math id="M169" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula> and HNO<inline-formula><mml:math id="M170" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, leading to the re-emission of gaseous HCl in the atmosphere. Thus, for chloride we use the
measured chloride concentration instead of the one calculated from ssNa<inline-formula><mml:math id="M171" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>. Thus,

                <disp-formula id="Ch1.Ex1"><mml:math id="M172" display="block"><mml:mstyle class="stylechange" displaystyle="true"/><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:mtext>SSA</mml:mtext><mml:mo>=</mml:mo><mml:mn>1.46</mml:mn><mml:mo>⋅</mml:mo><mml:mfenced close="]" open="["><mml:msup><mml:mtext>ssNa</mml:mtext><mml:mo>+</mml:mo></mml:msup></mml:mfenced><mml:mo>+</mml:mo><mml:mfenced close="]" open="["><mml:msup><mml:mtext>Cl</mml:mtext><mml:mo>-</mml:mo></mml:msup></mml:mfenced><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>

          The crustal component is calculated from Al, which represents 8.2 % of the
upper continental crust, UCC (Henderson and Henderson, 2009). A previous
study using an extensive data set at Lampedusa showed that the crustal
content determined from the total Al was in very good agreement with
calculations made from the sum of the metal oxides (Marconi et al., 2014).
However, in this study we use measurements of the soluble Al concentration
obtained by ICP-AES on the solution obtained with H<inline-formula><mml:math id="M173" 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="M174" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and
HNO<inline-formula><mml:math id="M175" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in a microwave oven instead of the total Al content. Therefore, in
this work we underestimate the crustal contribution by about 30 %
(unpublished results). However, it must be emphasized that the crustal
aerosol contribution has been very low throughout the measurement campaign.</p>
      <p>Figure 2 shows the time series of the main PM<inline-formula><mml:math id="M176" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> components at LMP and
CGR. An intense mistral event occurred from 22 June to 1 July. Mistral
events are characterized by strong winds from the northwesterly sector and
often by subsiding air masses originating from the free troposphere (Jiang
et al., 2003). Thus, elevated values of SSA and low concentrations of other
compounds are generally found during mistral at Lampedusa.</p>
      <p>Average concentrations of PM<inline-formula><mml:math id="M177" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> and of the different aerosol components
for the whole measurement campaign and for the non-mistral conditions are
reported in Table 2. The averages were calculated over a homogeneous
data set, i.e. when measurements are available at both sites.</p>
      <p>The largest PM<inline-formula><mml:math id="M178" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> values were associated with elevated SSA during the
mistral event at both sites. PM<inline-formula><mml:math id="M179" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> is about two times larger at Capo
Granitola than at Lampedusa. The PM<inline-formula><mml:math id="M180" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> measured during the campaign at
Lampedusa was significantly lower than its long-term average (31.5 <inline-formula><mml:math id="M181" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M182" 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>;
Marconi et al., 2014). No Saharan dust transport events occurred
at low altitude in this period (e.g. Mailler et al., 2016), and the crustal
aerosol contribution remained very low and almost constant at both sites
(average <inline-formula><mml:math id="M183" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 1 <inline-formula><mml:math id="M184" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M185" 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> at LMP and around 3 <inline-formula><mml:math id="M186" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M187" 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> at
CGR, corresponding to 4.6 and 8.2 % of the PM<inline-formula><mml:math id="M188" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP and CGR respectively).</p>
      <p>SSA accounted for about 26 and 24 % of PM<inline-formula><mml:math id="M189" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP and CGR,
respectively. The SSA contribution was about 14 % of PM<inline-formula><mml:math id="M190" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP and
8 % at CGR during the periods not influenced by the mistral. Non-sea salt
SO<inline-formula><mml:math id="M191" 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> was the most abundant among the secondary inorganic species.</p>
      <p><?xmltex \hack{\newpage}?>Nitrate concentrations, although relatively high at both sites, are in
agreement with the long term measurements performed at Lampedusa (e.g.
Calzolai et al., 2015) and with data from other remote sites in the western
(Mallorca; e.g. Simo et al., 1991) and eastern Mediterranean (Finokalia;
e.g. Mihalopoulos et al., 1997).</p>
      <p>Organic aerosol (OA) was the most abundant component at CGR, where its mean
concentration was <inline-formula><mml:math id="M192" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 9 <inline-formula><mml:math id="M193" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M194" 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 represented 35 % of
PM<inline-formula><mml:math id="M195" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> in the days not characterized by the mistral.</p>
      <p>Elemental carbon and organic carbon show higher values at CGR than LMP. At
CGR, moderate and elevated values of OC and EC appear correlated
(<inline-formula><mml:math id="M196" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M197" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.60; <inline-formula><mml:math id="M198" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> <inline-formula><mml:math id="M199" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 59; Fig. 3b), suggesting a strong influence of
carbon species from primary sources, characterized by the simultaneous EC and OC
emission. The influence from primary sources is apparent at EC <inline-formula><mml:math id="M200" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0.4 <inline-formula><mml:math id="M201" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M202" 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>.
At LMP, on the contrary, OC was not correlated with EC
(Fig. 3a), indicating a strong impact of OC secondary and/or natural
sources. This confirms that Lampedusa may be considered a background site in
the central Mediterranean (see e.g. Artuso et al., 2009; Henne et al.,
2010), and the observations there may be taken as representative for a
relatively wide open sea region.</p>
      <p>Thus, we used a conversion factor of 1.8 (typical for urban background
sites, Turpin and Lim, 2001) at CGR, and of 2.1 (typical for remote sites
characterized by the high impact of secondary sources, Turpin and Lim, 2001) at
LMP to estimate the total organic aerosol amount from the OC measured
values. Once we estimated OA with this method, the sum of the various species
accounted for more than 85 % of the measured mass at both sites. The
unreconstructed mass could be due to an underestimation of OA from OC, or to
the presence of bound water not removed by the desiccation procedure at
50 % relative humidity (Tsyro, 2005; Canepari et al., 2013).</p>
<sec id="Ch1.S3.SS1.SSS1">
  <title>Ship emission markers: V and Ni</title>
      <p>Several studies focussed on the identification of shipping emission
specific tracers (Viana et al., 2008; Becagli et al., 2012; Isakson et al.,
2001; Hellebust et al., 2010). Vanadium and Nickel are generally considered
the best markers for this source because, after sulfur, they are the main
impurities in heavy fuel oil (Agrawal et al., 2008a, b). The soluble
fraction of these metals is even more representative for ship sources
(Becagli et al., 2012).</p>
      <p>Following Becagli et al., (2012), we used measurements of the V and Ni
soluble fractions (V<inline-formula><mml:math id="M203" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> and Ni<inline-formula><mml:math id="M204" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula>, respectively). In the data set the V<inline-formula><mml:math id="M205" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> and Ni<inline-formula><mml:math id="M206" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> ratio with respect to Al
was always more than 10 times larger than for UCC, as expected for cases
dominated by heavy oil combustions sources (ships, refineries, power plants,
stainless steel production plants).</p>
      <p>Table 3 reports slope, correlation coefficient and number of samples of the
linear correlation between V<inline-formula><mml:math id="M207" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> and Ni<inline-formula><mml:math id="M208" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula>.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3"><caption><p>Correlation parameters between V and Ni at LMP and CGR calculated for all the samples, and for samples with V concentration higher than 6 ng m<inline-formula><mml:math id="M209" 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>.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="5">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="center"/>
     <oasis:colspec colnum="4" colname="col4" align="center"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:thead>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2"/>

         <oasis:entry colname="col3">Slope</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M210" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M211" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2"/>

         <oasis:entry colname="col3">(<inline-formula><mml:math id="M212" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> uncertainty)</oasis:entry>

         <oasis:entry colname="col4"/>

         <oasis:entry colname="col5"/>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry rowsep="1" colname="col1" morerows="1">LMP</oasis:entry>

         <oasis:entry colname="col2">All data</oasis:entry>

         <oasis:entry colname="col3">2.94 <inline-formula><mml:math id="M213" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.03</oasis:entry>

         <oasis:entry colname="col4">0.986</oasis:entry>

         <oasis:entry colname="col5">124</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col2">V<inline-formula><mml:math id="M214" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M215" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 6 ng m<inline-formula><mml:math id="M216" 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="col3">2.99 <inline-formula><mml:math id="M217" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.03</oasis:entry>

         <oasis:entry colname="col4">0.994</oasis:entry>

         <oasis:entry colname="col5">44</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1" morerows="1">CGR</oasis:entry>

         <oasis:entry colname="col2">All data</oasis:entry>

         <oasis:entry colname="col3">2.82 <inline-formula><mml:math id="M218" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08</oasis:entry>

         <oasis:entry colname="col4">0.950</oasis:entry>

         <oasis:entry colname="col5">59</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col2">V<inline-formula><mml:math id="M219" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M220" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 6 ng m<inline-formula><mml:math id="M221" 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="col3">3.00 <inline-formula><mml:math id="M222" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.05</oasis:entry>

         <oasis:entry colname="col4">0.989</oasis:entry>

         <oasis:entry colname="col5">34</oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p>Time series of LCR and LVR at <bold>(a)</bold> LMP, and <bold>(b)</bold> CGR. The horizontal red and grey shadow areas in each plot represent the
ranges of values for upper continental crust LVR and LCR, respectively.</p></caption>
            <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f04.png"/>

          </fig>

      <p>V<inline-formula><mml:math id="M223" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> and Ni<inline-formula><mml:math id="M224" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> are highly correlated, suggesting a common source.
The obtained slope of the regression line (2.8–2.9, that increases to 3.0
for samples with V<inline-formula><mml:math id="M225" display="inline"><mml:msub><mml:mi/><mml:mtext>sol</mml:mtext></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M226" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 6 ng m<inline-formula><mml:math id="M227" 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>) is in the range of
ratios typical for heavy fuel oil combustion sources. The same value was
found at Lampedusa by Becagli et al., (2012), considering data from 2004 to 2008.
The behaviour of V, Ni and their ratio are then representative of
heavy fuel oil combustion. It must be emphasized that the V <inline-formula><mml:math id="M228" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ni ratio is
expected to display a large variability due to varying fuel composition and
engine operating conditions (Mazzei et al., 2008; Agrawal et al., 2008a, b;
Viana et al., 2009; Pandolfi et al., 2011). It is however, difficult to
distinguish V and Ni originating from power plants, refineries, or ship
engines. Moreover, several refineries are present in Sicily (Siracusa, Gela,
Milazzo) and in Sardinia (Cagliari) and may potentially influence the sampling sites.</p>
      <p>A combination of methods is thus used in this study to unequivocally
identify the ship source. The analysis is based on: additional chemical
tracers, such as the rare earth elements, whose behaviour is specific for the
refinery and the ship sources; high-resolution back-trajectories, based on
data from the high-resolution regional model; information on the vertical
mixing in the atmospheric boundary layer; and coincidences between the high-resolution back-trajectories and the position of different types of ships in
the Straight of Sicily.</p>
</sec>
<sec id="Ch1.S3.SS1.SSS2">
  <title>Rare earth elements</title>
      <p>As discussed above, anthropogenic V and Ni originate from heavy oil
combustion and may only be considered markers of the ship source when other
sources can be excluded. Few studies propose the use of lanthanoid elements
(La to Lu) to distinguish refinery from ship emissions (Moreno et al., 2008a, b;
Du and Turner, 2015; Kulkarni et al., 2006).</p>
      <p>In particular, the ratio between the La and Ce concentrations (La <inline-formula><mml:math id="M229" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ce ratio,
hereafter LCR) and between La and V (hereafter LVR) can be used to identify
specific sources. Shipping emissions are characterised by values of LCR
between 0.6 and 0.8 and LVR <inline-formula><mml:math id="M230" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.1 (Moreno et al., 2008a, b).</p>
      <p>Crustal aerosols are characterized by LCR ranging from 0.4 to 0.6 and LVR
usually in the range of 0.2–0.3 (Moreno et al., 2008a, b). LCR depends
weakly on differences in dust source area and collected aerosol size
fraction, contrarily to LVR, which reaches 0.9 for large (<inline-formula><mml:math id="M231" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 10 <inline-formula><mml:math id="M232" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m)
particles from specific areas of the Sahara (e.g. Hoggar Massif;
Henderson and Henderson, 2009; Moreno et al., 2006; Castillo et al., 2008).</p>
      <p>Elevated values of LCR (from 1 to 13) are associated with emissions from
refineries (Moreno et al., 2008a; Du and Turner, 2015). This is because
zeolitic fluidised-bed catalytic cracking (FCC) units enriched in La are used
to crack long-chain olefins in crude oil to shorter-chain products (Bozlaker
et al., 2013; Du and Turner, 2015; Kulkani et al., 2006; Moreno et al., 2008a, b).</p>
      <p>Mixing of aerosol from different sources may produce a large variability of
LCR, with larger values corresponding to a stronger impact from refineries.</p>
      <p>The time series of LCR and LVR at LMP and CGR are displayed in Fig. 4. The
range of values expected for crustal aerosol is highlighted in the figure.
Please, note that the uncertainty on LCR is very large when La and Ce
concentrations are close to the detection limit. These cases may
produce very large values of LCR which are not significant; and were
removed from the time series.</p>
      <p>LCR at LMP and CGR was generally around the value expected for crustal
aerosol (dashed grey area in Fig. 4); 10 samples from LMP and 2 samples
from CGR show values of LCR higher than 1. LCR is <inline-formula><mml:math id="M233" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 1.5 in a single
case, at LMP. This suggests that the refineries impact is small in the
collected samples.</p>
      <p>Moreno et al., (2008b) have shown that it is possible to identify aerosol
from refineries based on the V-La-Ce-three-component plot. This type of plot
is shown in Fig. 5 for the data from LMP and CGR. La and Ce were scaled in
order to have the typical UCC composition in the centre of the plot.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><caption><p>Three-component Ce-La-V plot for LMP and CGR. Literature data for
different aerosol types are also shown.</p></caption>
            <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f05.png"/>

          </fig>

      <p>The compositions of UCC (Henderson and Henderson, 2009), African desert dust
(Castillo et al., 2008; Moreno et al., 2006), FCC (Kulkarni et al.,
2006), La-contaminated (refinery) Asian dust collected at Mauna Loa, Hawai'i (Olmez
and Gordon, 1985), and PM<inline-formula><mml:math id="M234" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> as well as PM<inline-formula><mml:math id="M235" display="inline"><mml:msub><mml:mi/><mml:mn>2.5</mml:mn></mml:msub></mml:math></inline-formula> that were collected at Puertollano
(Spain) in days possibly affected by refinery emissions (Moreno et al.,
2008b) are also displayed in Fig. 5.</p>
      <p>The data from CGR and LMP are grouped in a region with elevated values of V,
and La and Ce generally lower than in refinery and dust cases.</p>
      <p>Data from Puertollano shown in Fig. 5 are relative to days characterized
by winds originating from sectors where refineries are located; however,
these samples are affected by a mix of particles from several sources,
including refineries. Aerosol samples from Spain affected by refineries, in most cases
display larger LCR and LVR ratios than those found at LMP and CGR.
The composition of all samples collected in this period at LMP is consistent
with a large impact from ship emissions. Some cases at CGR may suggest the
simultaneous occurrence of crustal and ship aerosols, or dominant crustal
components (orange open dots in Fig. 5). Therefore, these cases display a
relatively low V concentration and are mainly associated with the mistral
event. A limited crustal contamination may possibly occur at CGR in these
cases, due to resuspension due to the strong wind.</p>
      <p>Cases with LCR <inline-formula><mml:math id="M236" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 1 (grey and pink open circles for CGR and LMP
respectively) are highlighted in Fig. 5. The aerosol composition is
consistent, however, with the ship source in these cases, suggesting that
the impact of refineries is limited.</p><?xmltex \hack{\newpage}?>
</sec>
</sec>
<sec id="Ch1.S3.SS2">
  <title>Trajectories and ship traffic</title>
<sec id="Ch1.S3.SS2.SSS1">
  <title>Origin of air masses during the campaign</title>
      <p>All the trajectories arriving at LMP and CGR, calculated with the HYSPLIT
model driven by WRF meteorological fields (see Sect. 2.3), are shown in an
aggregated way in Fig. 6, where the trajectory frequency at each point of
the computing grid is shown for the whole period (upper panels) and for the
10–30 June interval (lower panels). The trajectory frequency pattern is
elongated in the NW–SE direction at LMP, while it is distributed over a
wider range of directions at CGR, despite a general prevalence of northerly
sectors. The predominance of air masses coming from the northwest is
particularly evident in June (Fig. 6c and d), when areas with trajectory
frequencies exceeding 10 % are found farther to the north, up to the Gulf of Lion.</p>
      <p>During the first part of the campaign (June 2013) the synoptic situation was
characterized by a “dipolar” sea level pressure anomaly pattern, with
positive anomalies in the western Mediterranean and negative ones in the
eastern part of the basin (Denjean et al., 2016). This situation induced
stronger and more frequent than usual northwesterly winds (i.e. mistral
episodes, see Sect. 3.1) over Sardinia and Straight of Sicily.</p>
</sec>
<sec id="Ch1.S3.SS2.SSS2">
  <title>Ship traffic</title>
      <p>To further investigate the mechanisms determining the presence of ship
emissions markers at the two sites, we investigated the relationships among
the amount of V, the back-trajectory pattern, the effective number of ships
influencing the air mass, the stability of the boundary layer in the ship
source region (i.e. the Straight of Sicily) and the REE to V ratios discussed
in Sect. 3.1.2.</p>
      <p>All back-trajectories arriving at LMP and CGR were considered and all
trajectory-ship coincidences occurring within the last 36 hours before
sampling were taken into account.</p>
      <p>It was assumed that the ship plume influenced the sampled air mass if:
<list list-type="bullet"><list-item><p>the trajectory passed within 15 km of the position of a ship;</p></list-item><list-item><p>the corresponding air mass altitude was less than 500 m.</p></list-item></list>
The total number of ships fulfilling these criteria was associated with each
trajectory. The analysis was based on the available 1 h time resolution
meteorological fields (a ship influencing a trajectory was counted once every hour).</p>
      <p>To further explore the impact of different types of ships, the analysis was
carried out considering the following three ship categories: all the ships,
the merchant (i.e. cargo and tanker) and the fishing vessels.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p>Trajectory frequency computed at each grid cell with starting points
at LMP <bold>(a, c)</bold> and CGR <bold>(b, d)</bold>. Upper panels show values averaged
over the whole period of the campaign (10 June–31 July 2013), while lower
panels are relative to the 10–30 June interval.</p></caption>
            <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f06.png"/>

          </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p>Time series of Vanadium concentration (black line with dots) and number
of ships affecting the air masses sampled at CGR (upper panel) and LMP (lower
panel). Green, red and blue lines indicate, respectively, the total number of
ships and the number of merchant (i.e. cargo and tanker) and fishing vessels.
The time evolution of the temperature inversion index (d<inline-formula><mml:math id="M237" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula> in the figure) at
three different locations in the Straight of Sicily is shown in the middle panel;
brown, red and yellow curves show the behaviour at sites A–C (see text). The
orange arrows identify samples classified as crustal, based on the La-Ce-V
concentration; pink and gray arrows identify samples with LCR <inline-formula><mml:math id="M238" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 1, possibly
influenced by refineries.</p></caption>
            <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f07.png"/>

          </fig>

      <p>The atmospheric stability is also expected to play a large role in
modulating the ship impact (for an example of its influence on V amounts, see Becagli et
al., 2012). A temperature inversion (TI) index was calculated based on the
3-D atmospheric fields of the WRF model at three sites in the Straight of Sicily.
The temperature inversions were used as a proxy to identify periods
characterized by a stable boundary layer. The three sites, A (37.2<inline-formula><mml:math id="M239" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
11.5<inline-formula><mml:math id="M240" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E), B (37.0<inline-formula><mml:math id="M241" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 12.4<inline-formula><mml:math id="M242" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) and C (36.3<inline-formula><mml:math id="M243" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 13.3<inline-formula><mml:math id="M244" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) (Fig. 1)
were selected in the regions of most frequent ship passage and crossing with
the trajectories from LMP and CGR. The TI index was calculated as the
difference between the temperature at the altitude of the maximum, T, and at
the surface. A positive TI indicates an inversion and the TI value provides
an indication of the inversion strength. Only positive values are considered
in this analysis.</p>
      <p>Figure 7 summarizes the results of this analysis. It shows the time
series of the number of the ships influencing the trajectories arriving at LMP and
CGR, respectively, and the corresponding measured values of V. Samples which
show a limited influence from ship emissions, determined on the basis of the
La-Ce-V composition (see Sect. 3.1.2), are highlighted with arrows (orange
arrows for samples with La-Ce-V ratios typical for crust; pink and gray for
sample possibly influenced by refineries, i.e. with LCR <inline-formula><mml:math id="M245" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 1).
Results are shown for the three classes of ships. The positive values of TI
are also shown.</p>
      <p>In general, there is a rather good correspondence between the cases
classified as influenced by ships emissions and the number of ships
encountered along the associated air mass trajectory at CGR. The
correspondence is somewhat less evident at LMP. As discussed above, the V
concentration ascribed to ships (data points without arrows in Fig. 7) is
generally higher at CGR than at LMP. Part of this difference may be ascribed
to the shorter distance between CGR and the main shipping route crossing the
Straight of Sicily with respect to LMP, the consequent larger number of
encountered ships and an aerosol dilution effect during transport from the
sources to LMP.</p>
      <p>Maxima of V attributed to ships occurred between 19 and 20 June at CGR
(about 42 ng m<inline-formula><mml:math id="M246" 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 on 21 June at LMP (36.1 ng m<inline-formula><mml:math id="M247" 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>). Similar
concentrations were measured at CGR also around 18–19 July, in conjunction
with an increase in the number of merchant vessels. The 18–21 June period is
the only event with high V concentrations quasi simultaneously at both
sites. This is due to the peculiar circulation patterns, with air mass
trajectories from the marine sector south of Sicily to CGR, and from the
Straight of Sicily to LMP, particularly on 18 and 19 June. The 19–21 June
episode is the largest occurring at LMP, both for duration and V
concentration. Especially at the beginning of the event, large values of V
do not correspond with an increase of the number of ships along the air mass trajectories.</p>
      <p>A possible explanation for this behaviour is provided by the temporal
evolution of TI in the Straight of Sicily. The temperature inversion started to
develop on 14 June and gradually increased in intensity until 22 June; the
TI persistence and progressive increase in intensity provided suitable
conditions for the ship plumes being trapped in the boundary layer, with a
consequent build-up of the ship aerosol and V concentration. This process
appears particularly efficient at CGR between 21 and 25 June.</p>
      <p>A similar combined dependency on number of ships and TI appears also at LMP
around 7 July. It is interesting to note that V from ships seems to depend
more directly on the number of merchant ships (see, for example, the lack of V
peaks on 17 June, 12 and 29 July at LMP, when the number of fishing vessels
was high and the number of merchant ships was low) than on the total or the number of fishing ships.</p>
      <p>Thus, the trajectory analysis, carried out in combination with the available
information on the ship tracks, confirms that ship emissions are the main
factors responsible for most of the moderate and elevated values of V measured at
LMP and CGR during the campaign and in particular for those cases with LCR compatible with the ship source. This analysis also clearly suggests
that the boundary layer structure plays a very important role in determining
the impact produced by the emissions. This simplified approach confirms the
importance of carefully characterizing the emission scenario and the
meteorological conditions in studies on the ships' emissions impact on air quality.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS3">
  <title>Sulfate, nitrate and organic carbon from ships</title>
      <p>SO<inline-formula><mml:math id="M248" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> is one of the main species emitted in the ship plume in the gas
phase (Agrawal et al., 2008a, b). SO<inline-formula><mml:math id="M249" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> is produced through oxidation of
the S contained as impurity in heavy fuel oil and is an aerosol precursor.</p>
      <p>A previous study based on five years of data from Lampedusa (Becagli et al.,
2012) has shown that the non-sea salt sulfate behaviour is not directly
correlated with V and Ni because several other SO<inline-formula><mml:math id="M250" 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> sources
(anthropogenic, marine biogenic, crustal, volcanic) contribute to the
non-sea salt sulfate in the Central Mediterranean Sea.</p>
      <p>The same study suggested a lower limit of about 200 for the
nssSO<inline-formula><mml:math id="M251" 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> <inline-formula><mml:math id="M252" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V ratio for particles originating from heavy oil
combustion at Lampedusa.</p>
      <p>Figure 8a and 8b shows nssSO<inline-formula><mml:math id="M253" 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> <inline-formula><mml:math id="M254" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V vs. V at LMP and CGR. At both sites,
nssSO<inline-formula><mml:math id="M255" 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> <inline-formula><mml:math id="M256" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V decreases with increasing V and reaches a lower limit at
elevated values of V (<inline-formula><mml:math id="M257" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M258" 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 analysis on REE,
trajectories and ship traffic has shown that all samples with V <inline-formula><mml:math id="M259" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M260" 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>
are strongly influenced by ships and we assume that ship
emission is the dominant source of the sampled particles for these cases.
This implies that in these cases virtually all sulfate originated from the
ship source and the observed lower limit for nssSO<inline-formula><mml:math id="M261" 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> <inline-formula><mml:math id="M262" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V can be
considered the lower limit for the sulfate to V ratio in the ship plume.
Thus, to derive a lower limit for this ratio we calculate the mean and
standard deviation of nssSO<inline-formula><mml:math id="M263" 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> <inline-formula><mml:math id="M264" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V for V <inline-formula><mml:math id="M265" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M266" 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 mean ratio and the mean ratio minus one standard deviation are shown in Fig. 8.</p>
      <p>The nssSO<inline-formula><mml:math id="M267" 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> to V ratio may still be decreasing for V by around 15 ng m<inline-formula><mml:math id="M268" 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 we used a limit value equal to the average minus one
standard deviation (solid red lines in Fig. 8) to estimate the minimum
expected contribution from ships to the total sulfate amount.</p>
      <p>The calculated lower limit of the sulfate to V ratio at LMP is 207, in
agreement with the values of 200 estimated by Becagli et al., (2012). The
nssSO<inline-formula><mml:math id="M269" 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> <inline-formula><mml:math id="M270" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V limit value at CGR, 323, is larger than at LMP. This
difference may be due to the contribution of other sulfate sources, which
may contribute to the nssSO<inline-formula><mml:math id="M271" 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>, even at high V concentration, and
to the smaller distance from the ship source with respect to LMP. This
result highlights the importance of remote sites like LMP to obtain
information on the open Mediterranean.</p>
      <p>NO<inline-formula><mml:math id="M272" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> are among the main compounds emitted in the gas phase acting as aerosol
precursors. The photochemistry of NO<inline-formula><mml:math id="M273" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> leading to NO<inline-formula><mml:math id="M274" 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>
formation in the particulate phase is complex, especially in summer, due to
the presence of high amounts of OH radical (see, for example, Chen et al., 2005),
and the NO<inline-formula><mml:math id="M275" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> contribution to the particulate phase is not easy to be quantified.</p>
      <p>Here we try to use the same approach used for sulfate for the determination
of a lower limit for the NO<inline-formula><mml:math id="M276" 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> <inline-formula><mml:math id="M277" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V ratio in the ship plume.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><caption><p>Scatter plots of nssSO<inline-formula><mml:math id="M278" 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> <inline-formula><mml:math id="M279" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V <bold>(a, b)</bold>, NO<inline-formula><mml:math id="M280" 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> <inline-formula><mml:math id="M281" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V <bold>(c, d)</bold>,
OC <inline-formula><mml:math id="M282" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V <bold>(e, f)</bold> and EC <inline-formula><mml:math id="M283" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V <bold>(g, h)</bold> vs. V concentration at LMP
(plots on the left) and CGR (plots on the right). The red lines in the plots
represent the average (dashed line) and the average minus one standard deviation
(solid line) calculated for samples with V <inline-formula><mml:math id="M284" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M285" 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>.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/2067/2017/acp-17-2067-2017-f08.png"/>

        </fig>

      <p>Figure 8c and d show the NO<inline-formula><mml:math id="M286" 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> <inline-formula><mml:math id="M287" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V ratio vs. V at the two
sites. Similarly to sulfate, the average value of NO<inline-formula><mml:math id="M288" 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> <inline-formula><mml:math id="M289" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V for
V <inline-formula><mml:math id="M290" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M291" 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> is larger at CGR than at LMP. However, the
standard deviation at CGR is significantly larger at CGR. The NOx
concentration in the ship plume close to the source is larger than that of
SO<inline-formula><mml:math id="M292" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and is strongly dependent on the engine operating conditions
(Agrawal et al., 2008b). The NO<inline-formula><mml:math id="M293" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> lifetime is extremely low (1.8 h during
the daytime and 6.5 h during the nighttime, Chen et al., 2005). However, the
NO<inline-formula><mml:math id="M294" 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> <inline-formula><mml:math id="M295" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V limit ratio values is low compared to the limit ratio for
SO<inline-formula><mml:math id="M296" 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>. It has to be considered that NO<inline-formula><mml:math id="M297" 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> takes part in
other photochemical atmospheric reactions that lead to its removal. In
addition, the presence of HNO<inline-formula><mml:math id="M298" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the gas phase, not neutralized by NH<inline-formula><mml:math id="M299" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
or by sea salt, could explain the low NO<inline-formula><mml:math id="M300" 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> <inline-formula><mml:math id="M301" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> nssSO<inline-formula><mml:math id="M302" 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> ratio
in the aerosol. Indeed, the NO<inline-formula><mml:math id="M303" 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> concentration measured at LMP and
CGR is four to six times lower than that of nssSO<inline-formula><mml:math id="M304" 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> (Table 1). Low
amounts of NO<inline-formula><mml:math id="M305" 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>, with respect to SO<inline-formula><mml:math id="M306" 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> from ship
emissions, are found in model simulations in southern California (Dabdub,
2008). Indeed, Dabdub (2008) shows that the aerosol contribution from ship
emissions is 0.05 % for NO<inline-formula><mml:math id="M307" 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 44 % for SO<inline-formula><mml:math id="M308" 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>.</p>
      <p>Elemental and Organic Carbon are also present in the ship plume (Shah et
al., 2004). In particular, OC constitutes about 15–25 % and EC is
generally lower than 1 % of the PM sampled at the plume of main ship
engine powered by heavy fuel oil (Agrawal et al., 2008b).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4" specific-use="star"><caption><p>Estimates of the average and maximum of the lower limit of nssSO<inline-formula><mml:math id="M309" 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="M310" 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>, OA and PM<inline-formula><mml:math id="M311" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> from ships. Concentrations and percent with
respect to the total amount of each species are reported. The maxima are derived
by selecting cases with the largest ship impact (i.e. highest V concentration).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="12">
     <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:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="left"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:colspec colnum="10" colname="col10" align="left"/>
     <oasis:colspec colnum="11" colname="col11" align="right"/>
     <oasis:colspec colnum="12" colname="col12" align="right"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry namest="col2" nameend="col3" align="center">nssSO<inline-formula><mml:math id="M312" 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></oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry namest="col5" nameend="col6" align="center">NO<inline-formula><mml:math id="M313" 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></oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry namest="col8" nameend="col9" align="center">OA </oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry rowsep="1" namest="col2" nameend="col3" align="center">(nssSO<inline-formula><mml:math id="M314" 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> <inline-formula><mml:math id="M315" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M316" display="inline"><mml:mrow><mml:mi>V</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>min</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M317" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 207 </oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry rowsep="1" namest="col5" nameend="col6" align="center">(NO<inline-formula><mml:math id="M318" 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> <inline-formula><mml:math id="M319" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M320" display="inline"><mml:mrow><mml:mi>V</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>min</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M321" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 12.5 </oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry rowsep="1" namest="col8" nameend="col9" align="center">(OC <inline-formula><mml:math id="M322" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M323" display="inline"><mml:mrow><mml:mi>V</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>min</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M324" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 43.1 </oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry rowsep="1" namest="col11" nameend="col12" align="center">PM<inline-formula><mml:math id="M325" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">LMP</oasis:entry>  
         <oasis:entry colname="col3">CGR</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">LMP</oasis:entry>  
         <oasis:entry colname="col6">CGR</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">LMP</oasis:entry>  
         <oasis:entry colname="col9">CGR</oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11">LMP</oasis:entry>  
         <oasis:entry colname="col12">CGR</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">Average</oasis:entry>  
         <oasis:entry colname="col2">1.35</oasis:entry>  
         <oasis:entry colname="col3">2.1</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">0.082</oasis:entry>  
         <oasis:entry colname="col6">0.13</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">0.59</oasis:entry>  
         <oasis:entry colname="col9">0.78</oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11">2.0</oasis:entry>  
         <oasis:entry colname="col12">3.0</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">contribution</oasis:entry>  
         <oasis:entry colname="col2">(34 %)</oasis:entry>  
         <oasis:entry colname="col3">(31 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(4.5 %)</oasis:entry>  
         <oasis:entry colname="col6">(9.0 %)</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">(15 %)</oasis:entry>  
         <oasis:entry colname="col9">(8.7 %)</oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11">(11 %)</oasis:entry>  
         <oasis:entry colname="col12">(8.6 %)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"><inline-formula><mml:math id="M326" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M327" 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"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Maximum</oasis:entry>  
         <oasis:entry colname="col2">7.5</oasis:entry>  
         <oasis:entry colname="col3">8.8</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">0.45</oasis:entry>  
         <oasis:entry colname="col6">0.53</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">3.3</oasis:entry>  
         <oasis:entry colname="col9">3.3</oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11">11.2</oasis:entry>  
         <oasis:entry colname="col12">12.7</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">contribution</oasis:entry>  
         <oasis:entry colname="col2">(69 %)</oasis:entry>  
         <oasis:entry colname="col3">(77 %)</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">(62 %)</oasis:entry>  
         <oasis:entry colname="col6">(100 %)</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">(99 %)</oasis:entry>  
         <oasis:entry colname="col9">(22 %)</oasis:entry>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11">(50 %)</oasis:entry>  
         <oasis:entry colname="col12">(42%)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math id="M328" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M329" 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"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>Figure 8 shows EC <inline-formula><mml:math id="M330" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V and OC <inline-formula><mml:math id="M331" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V vs. V at LMP and CGR. Similarly to sulfate
and nitrate, OC <inline-formula><mml:math id="M332" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V decreases with increasing V and reaches a minimum value
for V <inline-formula><mml:math id="M333" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M334" 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> (43.1 and 179 at LMP and CGR, respectively)
As discussed in Sect. 3.1, other OC sources in addition to ships are
present at CGR even at high values of V.</p>
      <p>The pattern of the ratio EC <inline-formula><mml:math id="M335" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V vs. V is less clear; in particular, several
very low values of EC <inline-formula><mml:math id="M336" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V also appear at small values of V. This result is
unexpected because V and EC are both markers of the primary ship aerosol,
but the data here presented seem to suggest that non negligible EC
contributions from other sources were present at CGR and that different
fractionating effects acted during the transport. Also in this case the
limit value is lower at LMP than at CGR.</p>
      <p>Finally, as the limit ratios at CGR are likely affected by other sources
than shipping, we assume that the limit ratios obtained at Lampedusa for
V <inline-formula><mml:math id="M337" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 15 ng m<inline-formula><mml:math id="M338" 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> are more representative of cases dominated by
ship emissions during summer in a wide region. For this reason, the
retrieved lower limits at LMP are also used to quantify the ship contribution at CGR.</p>
</sec>
<sec id="Ch1.S3.SS4">
  <?xmltex \opttitle{Contribution of the ship aerosol to PM${}_{{10}}$}?><title>Contribution of the ship aerosol to PM<inline-formula><mml:math id="M339" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula></title>
      <p>With all the limitations described above, by using the lower limits for the
ratios nssSO<inline-formula><mml:math id="M340" 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> <inline-formula><mml:math id="M341" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V, NO<inline-formula><mml:math id="M342" 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> <inline-formula><mml:math id="M343" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V and OC <inline-formula><mml:math id="M344" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V (representative
for ship aerosol) it is possible to estimate the minimum contribution of
nssSO<inline-formula><mml:math id="M345" 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="M346" 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 OC emitted by ships to the total
budget of these components and also to the total PM<inline-formula><mml:math id="M347" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> mass. It has to
be noticed that the aerosol quantification obtained by this method is a
rough estimate useful to constrain the ship aerosol contribution. In
addition, due to possibly different meteorological conditions and
photochemical activity, these values may vary spatially and seasonally.</p>
      <p>The minimum ratio of each species with respect to V and the minimum estimated
contribution of ship emissions, for the average amount and for the maxima,
of the total concentration of these species and of PM<inline-formula><mml:math id="M348" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> are reported
in Table 4. As previously discussed, the measured OC contribution is
multiplied by 2.1 at LMP and by 1.8 at CGR to obtain the total organic
aerosol contribution.</p>
      <p>The estimated minimum concentration of non-sea-salt sulfate from ship
emissions was 1.35 <inline-formula><mml:math id="M349" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M350" 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> on average during this campaign at LMP.
This value is lower than in the previous study by Becagli et al., (2012)
obtained over a longer period (2004–2008). The relative contribution to the
total sulfate is, however, similar here and in Becagli et al., (2012),
suggests a similar role of nssSO<inline-formula><mml:math id="M351" 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> from ship emissions to the
total nssSO<inline-formula><mml:math id="M352" 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> budget. The study by Becagli et al., (2012) covered
an extended time period (2004–2008); the consistency with that study
suggests that the results obtained during ChArMEx are not specific of summer 2013,
but are representative for a wider temporal and spatial range.</p>
      <p>At CGR the minimum ship contribution to sulfate, averaged over the same time
period, is higher than at LMP (2.1 <inline-formula><mml:math id="M353" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M354" 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>), but this higher value
corresponds to a lower contribution to the total nssSO<inline-formula><mml:math id="M355" 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>,
confirming that other nssSO<inline-formula><mml:math id="M356" 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> sources are important at CGR.</p>
      <p>Marmer and Langmann (2005) estimate that ship emissions contribute by 50 %
to the total amount of nssSO<inline-formula><mml:math id="M357" 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> in the Mediterranean. This value
is, as expected, larger than the estimated minimum contribution we derive (about 30 %).</p>
      <p>The estimated minimum contribution by ships to the total nssSO<inline-formula><mml:math id="M358" 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>
for cases with the largest ship impact (i.e. highest V concentration) is
69 and 77 % at LMP and CGR, respectively.</p>
      <p>Ships appear to contribute, by small fractions, to the total budget of
NO<inline-formula><mml:math id="M359" 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>. As previously mentioned, the NO<inline-formula><mml:math id="M360" 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> atmospheric
chemistry is complex and the contribution of nitrate from ship emission
could be highly variable, especially in the Mediterranean region where high
amounts of UV radiation and highly reactive radical species are present.</p>
      <p>Organic aerosol from ships also contributes significantly to the total OA
amount and to the total PM; in particular, at LMP virtually all the OA
present in cases with maximum ship impact may be attributed to the ship source.</p>
      <p>By summing these three contributions, it is possible to estimate the total
aerosol mass due to ship emissions and its contribution to the total mass
of PM<inline-formula><mml:math id="M361" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>. The lower limit for the ship contribution was 2.0 and 3.0 <inline-formula><mml:math id="M362" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M363" 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>,
corresponding to 11 and 8.6 % of PM<inline-formula><mml:math id="M364" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP and CGR, respectively.</p>
      <p>These percent contributions are higher than the annual average for the
Mediterranean region estimated by Viana et al., (2014). It has to be
considered that these authors used data from harbour or coastal sites, which
are highly affected by other sources in addition to ships, and where
gas-to-particle conversion is still at its initial phase. Moreover, the
percentages reported in this study are relative to the summer season, when
the ship contribution in the Mediterranean region is highest (Becagli et al., 2012).</p>
      <p>The estimated lower limit for the ship contribution in cases with maximum
ship impact was between 42 and 50 % of the total PM<inline-formula><mml:math id="M365" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>.</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Summary and conclusions</title>
      <p>In this study we have investigated the impact of the ship emissions to PM<inline-formula><mml:math id="M366" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula>
on measurements made at two sites in the central Mediterranean. The main
objectives of the study were to unambiguously identify the tracers of ship
emissions in the sampled aerosol and to obtain a lower limit for the
produced impact.</p>
      <p>The PM<inline-formula><mml:math id="M367" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> samples were collected in summer 2013, as a contribution to
the Chemistry and Aerosol Mediterranean Experiment, in parallel at LMP
and at CGR, respectively, south and north of the main shipping
route through the Mediterranean.</p>
      <p>The identification of aerosol originating from ships was based on an
integrated analysis combining chemical analyses, calculations of backward
trajectories using a high resolution regional model and on tracking of ship
traffic in the Mediterranean through the Automatic Identification System.</p>
      <p>The main results of this study may be summarized as follows:
<list list-type="order"><list-item><p>Moderate and elevated values of V and Ni in the aerosol were unambiguously
associated with the ship source; this attribution was based on:
<list list-type="bullet"><list-item><p>the V to Ni ratio, which corresponds to what is expected for heavy fuel oil
combustion;</p></list-item><list-item><p>low amounts of La and Ce with respect to V and La <inline-formula><mml:math id="M368" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> Ce ratios similar to those
in the UCC, which allowed the exclusion of power plants or refineries as sources
significantly contributing to the observed aerosol;</p></list-item><list-item><p>coincidences between air mass trajectories and travelling ships.</p></list-item></list></p></list-item><list-item><p>In addition to travelling ships, also the planetary boundary layer vertical
structure played an important role in determining the dispersion of aerosols
from the ship source; temperature inversions appeared associated with
elevated amounts of ship emissions tracers, suggesting that they favoured
the build-up of aerosol concentration in the lowest atmospheric layers.</p></list-item><list-item><p>As expected, merchant ships (cargo and tankers) appeared to produce a larger
impact on the measured aerosol than fishing vessels.</p></list-item><list-item><p>Lower limits for the ratios nssSO<inline-formula><mml:math id="M369" 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> <inline-formula><mml:math id="M370" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V, NO<inline-formula><mml:math id="M371" 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> <inline-formula><mml:math id="M372" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V, and
OC <inline-formula><mml:math id="M373" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> V, identifying the ship-dominated emission cases, were derived from the
observations. The lower limits found at Lampedusa, which may be taken as a
background site less affected by other types of anthropic emissions, are
respectively 207, 12.5 and 44.1. These lower limits are expected to be season dependent.</p></list-item><list-item><p>By using these ratios, the lower limits to the contribution of the ship
source to nssSO<inline-formula><mml:math id="M374" 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="M375" 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>, OA, and to PM<inline-formula><mml:math id="M376" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> during
the measurement campaign were estimated. Ship emissions contributed to the total amount of sulfate by at least 34 %, to the
total amount of NO<inline-formula><mml:math id="M377" 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> by at least 5–9 %, and to the total amount of organic aerosol by at least 9–15 %. All these contributions correspond at least to 11 % of
PM<inline-formula><mml:math id="M378" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP (2.0 <inline-formula><mml:math id="M379" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M380" 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 about 8.6 % of PM<inline-formula><mml:math id="M381" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at
CGR (3.0 <inline-formula><mml:math id="M382" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M383" 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>). In cases with largest ship impact, ships
contributed up to about 12 <inline-formula><mml:math id="M384" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M385" 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> to PM<inline-formula><mml:math id="M386" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> in both sites,
corresponding to 50 % of PM<inline-formula><mml:math id="M387" display="inline"><mml:msub><mml:mi/><mml:mn>10</mml:mn></mml:msub></mml:math></inline-formula> at LMP and 42 % at CGR.</p></list-item><list-item><p>Lampedusa is a small island in the southern sector of the central
Mediterranean, relatively far from the main Mediterranean shipping route;
thus, results at Lampedusa may be taken as representative of the impact of
ships on the aerosol properties in a wide open sea area in the central
Mediterranean during summer.</p></list-item></list></p>
</sec>
<sec id="Ch1.S5">
  <title>Data availability</title>
      <p>All the data presented in this paper are available upon request. Please contact
the corresponding author (silvia.becagli@unifi.it).</p>
</sec>

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

      <p>The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p>Measurements at Lampedusa were partly supported by the Italian Ministry for
University and Research through the NextData and Ritmare projects.</p><p>We thank the Institute for Coastal Marine Environment of the National Research
Council (IAMC-CNR) for hosting the instruments at Capo Granitola. Thanks are
due to MarineTraffic (<uri>http://www.marinetraffic.com</uri>) for providing the
information on the ship traffic in the Straight of Sicily.
<?xmltex \hack{\newpage}?><?xmltex \hack{\noindent}?>Edited by: M. Beekmann <?xmltex \hack{\newline}?>
Reviewed by: two anonymous referees</p></ack><ref-list>
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    <!--<article-title-html>Constraining the ship contribution to the aerosol  of the central Mediterranean</article-title-html>
<abstract-html><p class="p">Particulate matter with aerodynamic diameters lower than 10 µm, (PM<sub>10</sub>) aerosol samples were collected during summer 2013 within the
framework of the Chemistry and Aerosol Mediterranean Experiment (ChArMEx) at
two sites located north (Capo Granitola) and south (Lampedusa Island),
respectively, of the main Mediterranean shipping route in the Straight of Sicily.</p><p class="p">The PM<sub>10</sub> samples were collected with 12 h time resolutions at both
sites. Selected metals, main anions, cations and elemental and organic
carbon were determined.</p><p class="p">The evolution of soluble V and Ni concentrations (typical markers of heavy
fuel oil combustion) was related to meteorology and ship traffic intensity
in the Straight of Sicily, using a high-resolution regional model for
calculation of back trajectories. Elevated concentration of V and Ni at Capo
Granitola and Lampedusa are found to correspond with air masses from the
Straight of Sicily and coincidences between trajectories and positions of large
ships; the vertical structure of the planetary boundary layer also appears
to play a role, with high V values associated with strong inversions and
a stable boundary layer. The V concentration was generally lower at Lampedusa
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