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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">ACP</journal-id>
<journal-title-group>
<journal-title>Atmospheric Chemistry and Physics</journal-title>
<abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1680-7324</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>

    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-16-11915-2016</article-id><title-group><article-title><?xmltex \hack{\vspace*{-0.3cm}}?>Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the framework of the GMOS network</article-title>
      </title-group><?xmltex \runningtitle{Atmospheric mercury concentrations at ground-based monitoring sites}?><?xmltex \runningauthor{F.~Sprovieri et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Sprovieri</surname><given-names>Francesca</given-names></name>
          <email>f.sprovieri@iia.cnr.it</email>
        <ext-link>https://orcid.org/0000-0002-6489-5339</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Pirrone</surname><given-names>Nicola</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Bencardino</surname><given-names>Mariantonia</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>D'Amore</surname><given-names>Francesco</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Carbone</surname><given-names>Francesco</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Cinnirella</surname><given-names>Sergio</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Mannarino</surname><given-names>Valentino</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Landis</surname><given-names>Matthew</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8742-496X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Ebinghaus</surname><given-names>Ralf</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Weigelt</surname><given-names>Andreas</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Brunke</surname><given-names>Ernst-Günther</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Labuschagne</surname><given-names>Casper</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7125-0029</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Martin</surname><given-names>Lynwill</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Munthe</surname><given-names>John</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Wängberg</surname><given-names>Ingvar</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Artaxo</surname><given-names>Paulo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-7754-3036</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Morais</surname><given-names>Fernando</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Barbosa</surname><given-names>Henrique de Melo Jorge</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4027-1855</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Brito</surname><given-names>Joel</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4420-9442</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Cairns</surname><given-names>Warren</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7128-7753</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8 aff9">
          <name><surname>Barbante</surname><given-names>Carlo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-4177-2288</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff10">
          <name><surname>Diéguez</surname><given-names>María del Carmen</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8241-3719</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff10">
          <name><surname>Garcia</surname><given-names>Patricia Elizabeth</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff11 aff12">
          <name><surname>Dommergue</surname><given-names>Aurélien</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8185-9604</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff11 aff12">
          <name><surname>Angot</surname><given-names>Helene</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-4673-8249</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff12 aff11">
          <name><surname>Magand</surname><given-names>Olivier</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff13">
          <name><surname>Skov</surname><given-names>Henrik</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-1167-8696</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff14">
          <name><surname>Horvat</surname><given-names>Milena</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff14">
          <name><surname>Kotnik</surname><given-names>Jože</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff15">
          <name><surname>Read</surname><given-names>Katie Alana</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff16">
          <name><surname>Neves</surname><given-names>Luis Mendes</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff17">
          <name><surname>Gawlik</surname><given-names>Bernd Manfred</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff17">
          <name><surname>Sena</surname><given-names>Fabrizio</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff18">
          <name><surname>Mashyanov</surname><given-names>Nikolay</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff19">
          <name><surname>Obolkin</surname><given-names>Vladimir</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-0063-6968</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff20">
          <name><surname>Wip</surname><given-names>Dennis</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff21">
          <name><surname>Feng</surname><given-names>Xin Bin</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7462-8998</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff21">
          <name><surname>Zhang</surname><given-names>Hui</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff21">
          <name><surname>Fu</surname><given-names>Xuewu</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-5174-7150</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff22">
          <name><surname>Ramachandran</surname><given-names>Ramesh</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff23">
          <name><surname>Cossa</surname><given-names>Daniel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff24">
          <name><surname>Knoery</surname><given-names>Joël</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff23">
          <name><surname>Marusczak</surname><given-names>Nicolas</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff25">
          <name><surname>Nerentorp</surname><given-names>Michelle</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff13">
          <name><surname>Norstrom</surname><given-names>Claus</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>CNR Institute of Atmospheric Pollution Research, Rende, Italy</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>CNR Institute of Atmospheric Pollution Research, Rome, Italy</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Helmholtz-Zentrum, Geesthacht, Germany</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Cape Point GAW Station, Climate and Environment Research &amp; Monitoring, South African Weather Service,<?xmltex \hack{\newline}?> Stellenbosch, South Africa</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>IVL, Swedish Environmental Research Inst. Ltd., Göteborg, Sweden</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>University of Sao Paulo, Sao Paulo, Brazil</institution>
        </aff>
        <aff id="aff8"><label>8</label><institution>University Ca' Foscari of Venice, Venice, Italy</institution>
        </aff>
        <aff id="aff9"><label>9</label><institution>CNR Institute for the Dynamics of Environmental Processes, Venice, Italy</institution>
        </aff>
        <aff id="aff10"><label>10</label><institution>INIBIOMA-CONICET-UNComa, Bariloche, Argentina</institution>
        </aff>
        <aff id="aff11"><label>11</label><institution>Laboratoire de Glaciologie et Géophysique de l'Environnement, University Grenoble Alpes, Grenoble, France</institution>
        </aff>
        <aff id="aff12"><label>12</label><institution>Laboratoire de Glaciologie et Géophysique de l'Environnement, CNRS, Grenoble, France</institution>
        </aff>
        <aff id="aff13"><label>13</label><institution>Department of Environmental Science, Aarhus University, Aarhus, Denmark</institution>
        </aff>
        <aff id="aff14"><label>14</label><institution>Jožef Stefan Institute, Lubliana, Slovenia</institution>
        </aff>
        <aff id="aff15"><label>15</label><institution>NCAS, University of York, York, UK</institution>
        </aff>
        <aff id="aff16"><label>16</label><institution>Cape Verde Observatory, INMG – São Vicente, Cabo Verde</institution>
        </aff>
        <aff id="aff17"><label>17</label><institution>Joint Research Centre, Ispra, Italy</institution>
        </aff>
        <aff id="aff18"><label>18</label><institution>St. Petersburg State University, St. Petersburg, Russia</institution>
        </aff>
        <aff id="aff19"><label>19</label><institution>Limnological Institute SB RAS, Irkutsk, Russia</institution>
        </aff>
        <aff id="aff20"><label>20</label><institution>Department of Physics, University of Suriname, Paramaribo, Suriname</institution>
        </aff>
        <aff id="aff21"><label>21</label><institution>Institute of Geochemistry, State Key Laboratory of Environmental Geochemistry,<?xmltex \hack{\newline}?> Chinese Academy of Sciences, Guiyang, China</institution>
        </aff>
        <aff id="aff22"><label>22</label><institution>Institute for Ocean Management, Anna University, Chennai, India</institution>
        </aff>
        <aff id="aff23"><label>23</label><institution>LER/PAC, Ifremer,Centre Méditerranée, La Seyne-sur-Mer, France</institution>
        </aff>
        <aff id="aff24"><label>24</label><institution>LBCM, Ifremer, Centre Atlantique, Nantes, France</institution>
        </aff>
        <aff id="aff25"><label>25</label><institution>Chalmers University of Technology, Gothenburg, Sweden</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Francesca Sprovieri (f.sprovieri@iia.cnr.it)</corresp></author-notes><pub-date><day>23</day><month>September</month><year>2016</year></pub-date>
      
      <volume>16</volume>
      <issue>18</issue>
      <fpage>11915</fpage><lpage>11935</lpage>
      <history>
        <date date-type="received"><day>31</day><month>May</month><year>2016</year></date>
           <date date-type="rev-request"><day>7</day><month>June</month><year>2016</year></date>
           <date date-type="rev-recd"><day>30</day><month>August</month><year>2016</year></date>
           <date date-type="accepted"><day>1</day><month>September</month><year>2016</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/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri>
<self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>


      <abstract>
    <p>Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess
its emission, transport, atmospheric chemistry, and deposition processes is
vital to understanding the impact of Hg pollution on the environment. The Global
Mercury Observation System (GMOS) project was funded by the European
Commission (<ext-link xlink:href="http://www.gmos.eu">http://www.gmos.eu</ext-link>) and started in November 2010
with the overall goal to develop a coordinated global observing system to
monitor Hg on a global scale, including a large network of ground-based
monitoring stations, ad hoc periodic oceanographic cruises and measurement
flights in the lower and upper troposphere as well as in the lower
stratosphere. To date, more than 40 ground-based monitoring sites constitute
the global network covering many regions where little to no observational
data were available before GMOS. This work presents atmospheric Hg
concentrations recorded worldwide in the framework of the GMOS project
(2010–2015), analyzing Hg measurement results in terms of temporal trends,
seasonality and comparability within the network. Major findings highlighted
in this paper include a clear gradient of Hg concentrations between the
Northern and Southern hemispheres, confirming that the gradient observed is
mostly driven by local and regional sources, which can be anthropogenic,
natural or a combination of both.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Mercury (Hg) is found ubiquitously in the atmosphere and is known to deposit
to ecosystems, where it can be taken up into food webs and transformed to
highly toxic species (i.e., methyl-Hg) which are detrimental to ecosystem and
human health. A number of activities have been carried out since the late
1980s in developed countries within European and international strategies and
programs (i.e., UNECE-CLRTAP, EU-Mercury Strategy; UNEP Governing Council) to
elaborate possible mechanisms to reduce Hg emissions to the atmosphere from
industrial facilities, trying to balance the increasing emissions in rapidly
industrializing countries of the world <xref ref-type="bibr" rid="bib1.bibx81 bib1.bibx78 bib1.bibx79 bib1.bibx72" id="paren.1"/>. Hg displays complex speciation and chemistry in the
atmosphere, which influences its transport and deposition on various spatial
and temporal scales <xref ref-type="bibr" rid="bib1.bibx27 bib1.bibx42 bib1.bibx43 bib1.bibx61 bib1.bibx93 bib1.bibx94 bib1.bibx100 bib1.bibx92" id="paren.2"/>.
Most of Hg is observed in the atmosphere as Gaseous Elemental Mercury
(GEM/Hg0), representing 90 to 99 % of the total with a terrestrial background
concentration of approximately 1.5–1.7 ng m<inline-formula><mml:math 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 Northern
Hemisphere and between 1.0 and 1.3 ng m<inline-formula><mml:math 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 Southern Hemisphere
based on research studies published before Global Mercury Observation System (GMOS) <xref ref-type="bibr" rid="bib1.bibx61 bib1.bibx100" id="paren.3"/>. The results obtained from newly established GMOS
ground-based sites show a background value in the Southern Hemisphere close
to 1 ng m<inline-formula><mml:math 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>, which is lower than that obtained in the past. Oxidized Hg
species (gaseous oxidized mercury or GOM) and particulate bound mercury (PBM)
contribute significantly to dry and wet deposition fluxes to terrestrial and
aquatic receptors <xref ref-type="bibr" rid="bib1.bibx10 bib1.bibx42 bib1.bibx43 bib1.bibx47 bib1.bibx90 bib1.bibx40 bib1.bibx22" id="paren.4"/>. Although in the past
2 decades a number of Hg monitoring sites have been established (in Europe,
Canada, USA and Asia) as part of regional networks and/or European projects
(i.e., MAMCS, MOE, MERCYMS) <xref ref-type="bibr" rid="bib1.bibx68 bib1.bibx69 bib1.bibx115 bib1.bibx116 bib1.bibx77 bib1.bibx103" id="paren.5"/>, the need to establish a global
network to assess likely southern–northern hemispheric gradients and
long-term trends has long been considered  a high priority for policy
and scientific purposes. The main reason is to make consistent and globally
distributed Hg observations available that can be used to validate regional
and global-scale models for assessing global patterns of Hg concentrations
and deposition and re-emission fluxes. Therefore a coordinated global
observational network for atmospheric Hg was established within the framework
of the GMOS project (Seventh Framework
Program – FP7) in 2010. The aim of GMOS was to provide high-quality Hg
datasets in the Northern and Southern hemispheres for a comprehensive
assessment of atmospheric Hg concentrations and their dependence on
meteorology, long-range atmospheric transport and atmospheric emissions on a
global scale <xref ref-type="bibr" rid="bib1.bibx101" id="paren.6"/>. This network was developed by integrating
previously established ground-based atmospheric Hg monitoring stations with
newly established GMOS sites in regions of the world where atmospheric Hg
observational data were scarce, particularly in the Southern Hemisphere
<xref ref-type="bibr" rid="bib1.bibx100" id="paren.7"/>. The stations are located at both high altitude and
high
sea level locations, as well as in climatically diverse regions. The
measurements from these sites have been used to validate regional- and global-scale atmospheric Hg models in order to improve our understanding of global
Hg transport, deposition and re-emission, as well as to provide a contribution
to future international policy development and implementation
<xref ref-type="bibr" rid="bib1.bibx41 bib1.bibx23" id="paren.8"/>. The GMOS overarching objective to
establish a global Hg monitoring network was achieved having in mind the need
to assure high-quality observations in line with international quality assurance/quality
control (QA/QC)
standards and to fill the gap in terms of spatial coverage of measurements in
the Southern Hemisphere where data were lacking or nonexistent. One of the
major outcomes of GMOS has been an interoperable e-infrastructure developed
following the Group on Earth Observations (GEO) data sharing and
interoperability principles which allows us to provide support to UNEP for the
implementation of the Minamata Convention (i.e., Article 22 to measure the
effectiveness of measures). Within the GMOS network, Hg measurements were in
fact carried out using high-quality techniques by harmonizing the GMOS
measurement procedures with those already adopted at existing monitoring
stations around the world. Standard operating procedures (SOPs) and a QA/QC
system were established and implemented at all GMOS sites in order to assure
full comparability of network observations. To ensure a fully integrated
operation of the GMOS network, a centralized online system (termed GMOS Data
Quality Management, G-DQM) was developed for the acquisition of atmospheric
Hg data in near real time and providing a harmonized QA/QC protocol. This
novel system was developed for integrating data control and is based on a
service-oriented approach that facilitates real-time adaptive monitoring
procedures, which is essential for producing high-quality data
<xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx18" id="paren.9"/>. GMOS activities are currently part of the
GEO strategic plan (2016–2025) within the GEO flagship on “tracking
persistent pollutants”. The overall goal of this flagship is to support the
development of GEOSS by fostering research and technological development on
new advanced sensors for in situ and satellite platforms, in order to lower
the management costs of long-term monitoring programs and improve spatial
coverage of observations. In this paper we present for the first time a
complete global dataset of Hg concentrations at selected ground-based sites
in the Southern and Northern hemispheres and highlight its potential to
support the validation of global-scale atmospheric models for research and
policy scenario analysis.</p>
</sec>
<sec id="Ch1.S2">
  <title>Experimental</title>
<sec id="Ch1.S2.SSx1" specific-use="unnumbered">
  <title>GMOS global network</title>
      <p>The GMOS network currently consists of 43 globally distributed
monitoring stations located both at sea level (i.e., Mace Head, Ireland;
Calhau, Cabo Verde; Cape Point, South Africa; Amsterdam Island, southern
Indian Ocean) and high-altitude locations, such as the Everest-K2 Pyramid
station (Nepal) at 5050 m a.s.l. and the Mt. Walinguan (China) station at
3816 m a.s.l., as well as in climatically diverse regions, including polar
areas such as Villum Research Station (VRS), Station Nord (Greenland), Pallas
(Finland) and Dome Concordia and Dumont d'Urville stations in Antarctica.
It is possible to browse the GMOS monitoring sites at the
<ext-link xlink:href="http://sdi.iia.cnr.it/geoint/publicpage/GMOS/gmos_monitor.zul">GMOS
Monitoring Services</ext-link> web portal. The monitoring sites are classified as
master (M) and secondary (S) with respect to the Hg measurement programs
(Table <xref ref-type="table" rid="Ch1.T1"/>). Master stations perform speciated Hg measurements and
collect precipitation samples for Hg analysis whereas the secondary stations
perform only total gaseous mercury (TGM)/GEM measurements and precipitation
samples as well. Table <xref ref-type="table" rid="Ch1.T1"/> summarize key information about GMOS
stations, such as (a) the location, elevation and type of monitoring
stations; (b) new sites (master and/or secondary) established as part of GMOS;
and (c) existing monitoring sites established by institutions that are part of
European and international monitoring programs and managed by GMOS partners
and GMOS external partners who have agreed to share their monitoring data and
submit them to the central database following the interoperability principles
and standards set in GEOSS (Group Earth Observation System of System). The
GMOS objective of establishing a global Hg monitoring network was achieved
always bearing in mind not only the necessity to provide intercomparable data
worldwide but also international standards of intercomparability. In
particular, GMOS attempts to comply with the data sharing principles set by
the GEO that aim to develop the GEOSS through the use of “observation systems, which include ground-, air-, water- and
space-based sensors, field surveys and citizen observatories. GEO works to
coordinate the planning, sustainability and operation of these systems,
aiming to maximize their added value and use.” Additionally, GMOS makes use of “information and
processing systems, which include hardware and software tools needed for
handling, processing and delivering data from the observation systems to
provide information, knowledge, services and products.” In 2010 the Executive
Committee of GEO selected GMOS as a showcase for the work plan (2012–2015) to
demonstrate how GEOSS can support the convention and policies as well as
pioneering activity in environmental monitoring using highly advanced
e-infrastructure. More details about the sites can also be found at
<ext-link xlink:href="http://www.gmos.eu">http://www.gmos.eu</ext-link>.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Atmospheric ground-based sites locations that are part of the GMOS
network and general characteristics of the sites (i.e., code, lat, long),
including the type of monitoring station in respect to the Hg measurements
carried out as speciated (M) or not (S). In bold, external GMOS partners are indicated.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">Code</oasis:entry>  
         <oasis:entry colname="col2">Site</oasis:entry>  
         <oasis:entry colname="col3">Country</oasis:entry>  
         <oasis:entry colname="col4">Elevation (m a.s.l.)</oasis:entry>  
         <oasis:entry colname="col5">Lat (<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>)</oasis:entry>  
         <oasis:entry colname="col6">Long (<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>)</oasis:entry>  
         <oasis:entry colname="col7">GMOS site<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mi mathvariant="normal">a</mml:mi></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">AMS</oasis:entry>  
         <oasis:entry colname="col2">Amsterdam Island</oasis:entry>  
         <oasis:entry colname="col3">Terres Australes et</oasis:entry>  
         <oasis:entry colname="col4">70</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>37.79604</oasis:entry>  
         <oasis:entry colname="col6">77.55095</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3">Antarctiques Françaises</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">BAR</oasis:entry>  
         <oasis:entry colname="col2">Bariloche</oasis:entry>  
         <oasis:entry colname="col3">Argentina</oasis:entry>  
         <oasis:entry colname="col4">801</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>41.128728</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>71.420100</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">CAL</oasis:entry>  
         <oasis:entry colname="col2">Calhau</oasis:entry>  
         <oasis:entry colname="col3">Cabo Verde</oasis:entry>  
         <oasis:entry colname="col4">10</oasis:entry>  
         <oasis:entry colname="col5">16.86402</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>24.86730</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><bold>CHE</bold></oasis:entry>  
         <oasis:entry colname="col2"><bold>Cape Hedo</bold></oasis:entry>  
         <oasis:entry colname="col3"><bold>Japan</bold></oasis:entry>  
         <oasis:entry colname="col4"><bold>60</bold></oasis:entry>  
         <oasis:entry colname="col5"><bold>26.86430</bold></oasis:entry>  
         <oasis:entry colname="col6"><bold>128.25141</bold></oasis:entry>  
         <oasis:entry colname="col7"><bold>M</bold></oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">CPT</oasis:entry>  
         <oasis:entry colname="col2">Cape Point</oasis:entry>  
         <oasis:entry colname="col3">South Africa</oasis:entry>  
         <oasis:entry colname="col4">230</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.353479</oasis:entry>  
         <oasis:entry colname="col6">18.489830</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">CST</oasis:entry>  
         <oasis:entry colname="col2">Celestún</oasis:entry>  
         <oasis:entry colname="col3">Mexico</oasis:entry>  
         <oasis:entry colname="col4">3</oasis:entry>  
         <oasis:entry colname="col5">20.85838</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>90.38309</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">CMA</oasis:entry>  
         <oasis:entry colname="col2">Col Margherita</oasis:entry>  
         <oasis:entry colname="col3">Italy</oasis:entry>  
         <oasis:entry colname="col4">2545</oasis:entry>  
         <oasis:entry colname="col5">46.36711</oasis:entry>  
         <oasis:entry colname="col6">11.79341</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">DMC</oasis:entry>  
         <oasis:entry colname="col2">Concordia Station</oasis:entry>  
         <oasis:entry colname="col3">Antarctica</oasis:entry>  
         <oasis:entry colname="col4">3220</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>75.10170</oasis:entry>  
         <oasis:entry colname="col6">123.34895</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">DDU</oasis:entry>  
         <oasis:entry colname="col2">Dumont d'Urville</oasis:entry>  
         <oasis:entry colname="col3">Antarctica</oasis:entry>  
         <oasis:entry colname="col4">40</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>66.66281</oasis:entry>  
         <oasis:entry colname="col6">140.00292</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">EVK</oasis:entry>  
         <oasis:entry colname="col2">Ev-K2</oasis:entry>  
         <oasis:entry colname="col3">Nepal</oasis:entry>  
         <oasis:entry colname="col4">5050</oasis:entry>  
         <oasis:entry colname="col5">27.95861</oasis:entry>  
         <oasis:entry colname="col6">86.81333</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">ISK</oasis:entry>  
         <oasis:entry colname="col2">Iskrba</oasis:entry>  
         <oasis:entry colname="col3">Slovenia</oasis:entry>  
         <oasis:entry colname="col4">520</oasis:entry>  
         <oasis:entry colname="col5">45.56122</oasis:entry>  
         <oasis:entry colname="col6">14.85805</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">KOD</oasis:entry>  
         <oasis:entry colname="col2">Kodaicanal</oasis:entry>  
         <oasis:entry colname="col3">India</oasis:entry>  
         <oasis:entry colname="col4">2333</oasis:entry>  
         <oasis:entry colname="col5">10.23170</oasis:entry>  
         <oasis:entry colname="col6">77.46524</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">LSM</oasis:entry>  
         <oasis:entry colname="col2">La Seyne-sur-Mer</oasis:entry>  
         <oasis:entry colname="col3">France</oasis:entry>  
         <oasis:entry colname="col4">10</oasis:entry>  
         <oasis:entry colname="col5">43.106119</oasis:entry>  
         <oasis:entry colname="col6">5.885250</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">LIS<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mi mathvariant="normal">b</mml:mi></mml:msup></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">Listvyanka</oasis:entry>  
         <oasis:entry colname="col3">Russia</oasis:entry>  
         <oasis:entry colname="col4">670</oasis:entry>  
         <oasis:entry colname="col5">51.84670</oasis:entry>  
         <oasis:entry colname="col6">104.89300</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">LON</oasis:entry>  
         <oasis:entry colname="col2">Longobucco</oasis:entry>  
         <oasis:entry colname="col3">Italy</oasis:entry>  
         <oasis:entry colname="col4">1379</oasis:entry>  
         <oasis:entry colname="col5">39.39408</oasis:entry>  
         <oasis:entry colname="col6">16.61348</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MHD</oasis:entry>  
         <oasis:entry colname="col2">Mace Head</oasis:entry>  
         <oasis:entry colname="col3">Ireland</oasis:entry>  
         <oasis:entry colname="col4">8</oasis:entry>  
         <oasis:entry colname="col5">53.32661</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>9.90442</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MAN</oasis:entry>  
         <oasis:entry colname="col2">Manaus</oasis:entry>  
         <oasis:entry colname="col3">Brazil</oasis:entry>  
         <oasis:entry colname="col4">110</oasis:entry>  
         <oasis:entry colname="col5"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>2.89056</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>59.96975</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MIN</oasis:entry>  
         <oasis:entry colname="col2">Minamata</oasis:entry>  
         <oasis:entry colname="col3">Japan</oasis:entry>  
         <oasis:entry colname="col4">20</oasis:entry>  
         <oasis:entry colname="col5">32.23056</oasis:entry>  
         <oasis:entry colname="col6">130.40389</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MAL</oasis:entry>  
         <oasis:entry colname="col2">Mt. Ailao</oasis:entry>  
         <oasis:entry colname="col3">China</oasis:entry>  
         <oasis:entry colname="col4">2503</oasis:entry>  
         <oasis:entry colname="col5">24.53791</oasis:entry>  
         <oasis:entry colname="col6">101.03024</oasis:entry>  
         <oasis:entry colname="col7">S/M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><bold>MBA</bold></oasis:entry>  
         <oasis:entry colname="col2"><bold>Mt. Bachelor</bold></oasis:entry>  
         <oasis:entry colname="col3"><bold>WA, USA</bold></oasis:entry>  
         <oasis:entry colname="col4"><bold>2743</bold></oasis:entry>  
         <oasis:entry colname="col5"><bold>43.977516</bold></oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo mathvariant="bold">-</mml:mo></mml:math></inline-formula><bold>121.685968</bold></oasis:entry>  
         <oasis:entry colname="col7"><bold>M</bold></oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MCH</oasis:entry>  
         <oasis:entry colname="col2">Mt. Changbai</oasis:entry>  
         <oasis:entry colname="col3">China</oasis:entry>  
         <oasis:entry colname="col4">741</oasis:entry>  
         <oasis:entry colname="col5">42.40028</oasis:entry>  
         <oasis:entry colname="col6">128.11250</oasis:entry>  
         <oasis:entry colname="col7">M/S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">MWA</oasis:entry>  
         <oasis:entry colname="col2">Mt. Walinguan</oasis:entry>  
         <oasis:entry colname="col3">China</oasis:entry>  
         <oasis:entry colname="col4">3816</oasis:entry>  
         <oasis:entry colname="col5">36.28667</oasis:entry>  
         <oasis:entry colname="col6">100.89797</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">NIK<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mi mathvariant="normal">b</mml:mi></mml:msup></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">Nieuw Nickerie</oasis:entry>  
         <oasis:entry colname="col3">Suriname</oasis:entry>  
         <oasis:entry colname="col4">1</oasis:entry>  
         <oasis:entry colname="col5">5.95679</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>57.03923</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">PAL</oasis:entry>  
         <oasis:entry colname="col2">Pallas</oasis:entry>  
         <oasis:entry colname="col3">Finland</oasis:entry>  
         <oasis:entry colname="col4">340</oasis:entry>  
         <oasis:entry colname="col5">68.00000</oasis:entry>  
         <oasis:entry colname="col6">24.23972</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">RAO</oasis:entry>  
         <oasis:entry colname="col2">Rao</oasis:entry>  
         <oasis:entry colname="col3">Sweden</oasis:entry>  
         <oasis:entry colname="col4">5</oasis:entry>  
         <oasis:entry colname="col5">57.39384</oasis:entry>  
         <oasis:entry colname="col6">11.91407</oasis:entry>  
         <oasis:entry colname="col7">M</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">SIS</oasis:entry>  
         <oasis:entry colname="col2">Sisal</oasis:entry>  
         <oasis:entry colname="col3">Mexico</oasis:entry>  
         <oasis:entry colname="col4">7</oasis:entry>  
         <oasis:entry colname="col5">21.16356</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>90.04679</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">VRS</oasis:entry>  
         <oasis:entry colname="col2">Villum Research Station</oasis:entry>  
         <oasis:entry colname="col3">Greenland</oasis:entry>  
         <oasis:entry colname="col4">30</oasis:entry>  
         <oasis:entry colname="col5">81.58033</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>16.60961</oasis:entry>  
         <oasis:entry colname="col7">S</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p><inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mi mathvariant="normal">a</mml:mi></mml:msup></mml:math></inline-formula> M indicates master, S indicates secondary.
<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mi mathvariant="normal">b</mml:mi></mml:msup></mml:math></inline-formula> These sites use Lumex, elsewhere Tekran.</p></table-wrap-foot></table-wrap>

      <p>Eleven monitoring stations managed by external partners are included within
the global network sharing their data with the GMOS central database. These
new associated stations follow the “Governance and Data Policy of the Global
Mercury Observation System” guidelines established by GMOS
<xref ref-type="bibr" rid="bib1.bibx75" id="paren.10"/>.</p>
      <p>From the start of GMOS a small number of monitoring sites have been relocated
or have become recently operational, but most of the sites have been
fully operational for the entire project period and remain active. These
original core group stations consist of 27 monitoring sites. Their spatial
coverage is better throughout the Northern Hemisphere with 17 operational
monitoring stations, whereas there are 5 sites in the tropical zone (area
between the Tropic of Cancer (<inline-formula><mml:math display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>23<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>27<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>) and the Tropic of
Capricorn (<inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>23<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>27<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>)), and 5 sites in the Southern Hemisphere. The sites
in the Southern Hemisphere include new Hg stations, such as the GMOS site in
Bariloche (Patagonia, Argentina), the station in Kodaicanal (South India)
and the site on the Amsterdam Island (Terres Australes et Antarctiques
Françaises, TAAF) in the southern Indian Ocean, and two sites in Antarctica
at the Italian–French Dome Concordia station and at the French site Dumont
d'Urville.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Hg measurements methods</title>
<sec id="Ch1.S3.SS1">
  <title>Field operation</title>
      <p>All GMOS secondary sites used the Tekran continuous mercury vapor analyzer,
model 2537A/B (Tekran Instruments Corp., Toronto, Ontario, Canada) with the
exception of Listvyanka site (LIS), Russia, and Nieuw Nickerie site (NIK),
Suriname, which used a Lumex RA-915+ mercury analyzer. The latter provides
direct continuous GEM concentrations in air flow without Hg collection on
sorbent traps <xref ref-type="bibr" rid="bib1.bibx87 bib1.bibx88" id="paren.11"/>. GMOS master sites used the
Tekran model 2537A/B mercury vapor analyzer coupled with their speciation
system model 1130 for GOM and model 1135 for particulate boundaries mercury
(PBM<inline-formula><mml:math display="inline"><mml:msub><mml:mi/><mml:mn>2.5</mml:mn></mml:msub></mml:math></inline-formula>) with fractions less than 2.5 <inline-formula><mml:math display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m in diameter to
prevent large particles from depositing on the KCl-coated denuder
<xref ref-type="bibr" rid="bib1.bibx44" id="paren.12"/>. The principles and operation of the Tekran Hg speciation
system are described in <xref ref-type="bibr" rid="bib1.bibx57" id="text.13"/>. Data were captured using either
personal computers or data loggers and were submitted to the GMOS Central
database network (<ext-link xlink:href="http://www.gmos.eu/sdi">http://www.gmos.eu/sdi</ext-link>).
During the implementation of the GMOS global network, harmonized SOPs as well as common QA/QC protocols were developed <xref ref-type="bibr" rid="bib1.bibx70 bib1.bibx11 bib1.bibx12" id="paren.14"/> according to measurement practices followed within existing
European and American monitoring networks and based on the most recent
literature <xref ref-type="bibr" rid="bib1.bibx12 bib1.bibx104 bib1.bibx39" id="paren.15"/>. The GMOS SOPs were
reviewed by both GMOS partners and external partners as experts in this issue
and finally adopted within the GMOS network <xref ref-type="bibr" rid="bib1.bibx70" id="paren.16"/>. Full SOPs are
available online (<ext-link xlink:href="http://www.gmos.eu/sdi">http://www.gmos.eu/sdi</ext-link>) and
include sections on site selection, field operations, data management, field
maintenance and reporting procedures. All monitoring sites strictly followed
the GMOS SOPs to harmonize operations and ensure the comparability of all
results obtained worldwide. At the GMOS master sites the Hg analyzers were
operated in conjunction with the Tekran 1130/1135 speciation units, and
therefore the TGM/GEM data for these sites are explicitly referred to as GEM.
GEM concentrations were also provided by the two secondary sites (LIS and
NIK) which used the Lumex Hg analyzer (see the Lumex measurements principle
in Sect. 2.2.2). Regarding the TGM/GEM at the other GMOS secondary sites, it
has been discussed whether the Tekran 2537A/B instruments measure
TGM <inline-formula><mml:math display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> GEM <inline-formula><mml:math display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> GOM or GEM only <xref ref-type="bibr" rid="bib1.bibx91 bib1.bibx92" id="paren.17"/>;
considering that previous modeling studies and experimental measurements
highlighted that particularly at remote/background monitoring sites the
oxidized fraction of the TGM is less than 2 % <xref ref-type="bibr" rid="bib1.bibx44" id="paren.18"/>, we
consider the Tekran 2537A/B data to represent GEM. This is also in line with
a study recently published by <xref ref-type="bibr" rid="bib1.bibx92" id="text.19"/> which reports a comparison of
Hg concentrations at several GMOS sites in the Southern Hemisphere. Following
the SOPs implemented at all GMOS sites, the Hg analyzers used at the
secondary sites were operated without the speciation units but using the PTFE
(Teflon) filters to protect the instrument from sea salt and other particles
intrusion. <xref ref-type="bibr" rid="bib1.bibx92" id="text.20"/> assumed that the surface active GOM in the humid
air of the marine boundary layer (MBL) at several GMOS secondary sites, mostly
located at the coastline (i.e., Cape Point (South Africa), Cape Grim
(Australia) as well as Sisal (Mexico), Nieuw Nickerie (Paramaribo), Calhau
(Cabo Verde), etc.), has been filtered out together with particulate matter (PM), partly by the sea
salt particles loaded PTFE filter and partly on the walls of the inlet
tubing. Consequently, they assumed that measurements at the secondary sites
represent GEM only and are thus directly comparable to those at remote master
sites. In contrast, the observations made by <xref ref-type="bibr" rid="bib1.bibx109" id="text.21"/> at Troll
(Antarctica) suggested that at the low temperature and humidity prevailing at
this site, GOM passed the inlet tubing and the PTFE filter, thus measuring
TGM and not GEM. Taking into account these findings, <xref ref-type="bibr" rid="bib1.bibx92" id="text.22"/>
calculated for the GMOS master site on Amsterdam Island (AMS) a value of GOM
less than 1 % of TGM compared to the other secondary sites in the
Southern Hemisphere, including Troll, therefore highlighting  a value which is
insignificant when compared with the uncertainties discussed in the available
peer-reviewed literature <xref ref-type="bibr" rid="bib1.bibx92" id="paren.23"/>. Since we compare results at
various stations, in this work we have taken into account analysis of both
systematic and random uncertainties associated with the measurements as well
as published results of Tekran intercomparison exercises as reported and
discussed elsewhere (<xref ref-type="bibr" rid="bib1.bibx92" id="altparen.24"/>, and references there in).</p>
</sec>
<sec id="Ch1.S3.SS2">
  <title>GEM measurements method</title>
      <p>Amalgamation with gold is the principle method used to sample Hg0 for
atmospheric measurements worldwide <xref ref-type="bibr" rid="bib1.bibx44" id="paren.25"/>. The most widely used
automated instrument is the Tekran 2537A/B analyzer (Tekran Instrument Corp.,
Ontario, Canada) which performs amalgamation on dual gold cartridges used
alternately and thermal desorption (at 500 <inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) to provide continuous GEM
measurements. One trap is sampling while the other is heated, releasing Hg0
into an inert carrier gas (usually ultra-high-purity argon); quantification
is by cold vapor atomic fluorescence spectroscopy (CVAFS) at 253.7 nm (Landis
et al., 2002). Concentrations are expressed in ng m<inline-formula><mml:math 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 standard
temperature and pressure (STP, 273.15 K, 1013.25 hPa). The sampling interval
is between 5 and 15 min based on location logistics and meteorological
conditions. Taking into account the elevation of some monitoring sites in the
network (i.e., Ev-K2CNR, Nepal (5050 m a.s.l.), Mt. Waliguan, China (3816 m a.s.l.), and Concordia Station (3220 m a.s.l.)), the Tekran 2537A/B analyzers
have been operated with a 15 min sample time resolution at a flow rate of
0.8 L min<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Following the SOPs the Tekran analyzers also perform
automatic internal permeation source calibrations every 71 h, and the
best estimate of the method detection limit is 0.1 ng m<inline-formula><mml:math 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 a flow
rate of 1 L min<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The alternative automated instrument to measure
continuous GEM concentrations is the Lumex RA-915AM, which is based on the use
of differential atomic absorption spectrometry with direct Zeeman effect,
providing a detection limit lower than 1 ng m<inline-formula><mml:math 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> <xref ref-type="bibr" rid="bib1.bibx87 bib1.bibx88" id="paren.26"/>. Comparison studies between the Tekran 2537 and the RA-915AM
performed  during EN 15852 standard development showed good agreement of
the monitoring data obtained with these systems <xref ref-type="bibr" rid="bib1.bibx12" id="paren.27"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Coverage and consistency (%), on monthly basis, of GEM data
collected at some of the ongoing GMOS secondary stations during the period
2011–2015.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f01.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS3">
  <title>GEM/GOM/PBM measurements method</title>
      <p>Speciated atmospheric Hg measurements were performed using the Tekran Hg
speciation system units (models 1130 and 1135) coupled to a Tekran 2537A/B
analyzer. PBM and GOM concentrations are expressed in picograms per cubic
meter (pg m<inline-formula><mml:math 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 STP (273.15 K, 1013.25 hPa). At most GMOS sites, the
speciation units were located on the rooftop of the station and connected to
a Tekran 2537A/B analyzer through a heated PTFE line (50 <inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, 10 m in
length). The sampling time resolution, due to some technical/location issues,
was set equal to 5, 10 and 15 min for GEM (see tables in the Supplement) and equal to 1, 2 and 3 h for GOM and PBM. Speciation
measurements were performed following the GMOS SOPs and procedure as
described elsewhere <xref ref-type="bibr" rid="bib1.bibx57" id="paren.28"/> using a size-selective impactor inlet
(2.5 <inline-formula><mml:math display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m cutoff aerodynamic diameter at 10 L min<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), a KCl-coated
quartz annular denuder in the 1130 unit and a quartz regenerable particulate
filter (RPF) in the 1135 unit.</p>
</sec>
<sec id="Ch1.S3.SS4">
  <title>Quality assurance and quality control procedures</title>
      <p>In terms of network data acquisition, QA/QC implementation
procedures and data management, the worldwide configuration of the GMOS
network was a challenge for all scientists and site operators involved in
GMOS. The traditional approaches to Hg monitoring QA/QC management that were
primarily site specific and manually implemented were no longer easily
applicable or sustainable when applied to a global network with the number
and size of data streams generated from the monitoring stations in near real
time. The G-DQM system was designed to automate the QA process, making it
available on the web with a user-friendly interface to manage all the QC
steps from initial data transmission through final expert validation. From
the user's point of view, G-DQM is a web-based application, developed using
an approach based on
Software as a Service (SaaS) <xref ref-type="bibr" rid="bib1.bibx18" id="paren.29"/>. G-DQM is part
of the GMOS cyber-infrastructure (CI), which is a research environment that
supports advanced data acquisition, storage, management, integration, mining
and visualization, built on an IT infrastructure <xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx18" id="paren.30"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>Coverage and consistency, on monthly basis, of GOM/PBM data
collected at some of the ongoing GMOS master stations during the period
2011–2015.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f02.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Box-and-whisker plots of gaseous elemental mercury yearly
distribution (GEM, ng m<inline-formula><mml:math 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 all GMOS stations for <bold>(a)</bold> 2013
and <bold>(b)</bold> 2014. The sites are organized according to their
latitude from the northern to the southern locations. Each box includes the
median (midline) and 25th and 75th percentiles (box edges), 5th and 95th
percentiles (whiskers).</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f03.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4">
  <title>Results and discussion</title>
<sec id="Ch1.S4.SS1">
  <title>GMOS data coverage and consistency</title>
      <p>Almost all GMOS stations provide near-real-time raw data that are archived
and managed by GMOS-CI. Figures <xref ref-type="fig" rid="Ch1.F1"/> and <xref ref-type="fig" rid="Ch1.F2"/>, over the
2011–2015 period and at some of the ongoing secondary and master GMOS
stations, show the elemental and speciated Hg raw data coverage,
respectively. For each station the coverage of raw data was generated
considering the percentage of the real available raw data in respect to the
total potential number of data points on monthly basis. During the first year
of the project a number of sites were being established and/or equipped and
not enough data were available to support broad network spatial analysis. In
2011 (at the effectively starting of the project) only four monitoring sites
produced Hg measurements and, step by step, an increasing number of stations
have been established and added to the network in 2012. Therefore, we
evaluated the  years 2013 and 2014 due to major data coverage (%) of the
observations. In fact, our statistical evaluations/calculations are related
to this period for all the ground-based sites taken into account within the
GMOS network in order to harmonize the discussion and compare the results
worldwide.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <title>Northern–southern hemispheric gradients</title>
      <p>A summary of descriptive statistics based on monthly and annual averages from
all GMOS sites is presented in Tables S1 and S2 in the Supplement. The 2013
and 2014 annual mean concentrations of 1.55 and 1.51 ng m<inline-formula><mml:math 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, for the sites located in the Northern Hemisphere were calculated
by averaging the 13 site means for both years. Similar calculations were made
for the Southern Hemisphere and the tropics (see Tables S1 and S2). Annual
mean concentrations of 1.23 and 1.22 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for 2013 and 2014,
respectively, were obtained in the tropical zone and 0.93 and
0.97 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for the Southern Hemisphere. Figure <xref ref-type="fig" rid="Ch1.F3"/> shows the
GEM yearly distribution for 2013 (blue) and 2014 (green). The sites have been
organized in the graphic as well as in the tables according to their latitude
from those in the Northern Hemisphere to those in the tropics and in the
Southern Hemisphere. The data so far do not cover a long enough timespan
to investigate temporal trends, but some attempts have been previously
made for the more established sites, such as Mace Head (MHD), Ireland
<xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx117" id="paren.31"/>, and Cape Point (CPT), South Africa
<xref ref-type="bibr" rid="bib1.bibx92" id="paren.32"/>. At MHD the annual baseline GEM means observed by
<xref ref-type="bibr" rid="bib1.bibx30" id="paren.33"/> decreased from 1.82 ng m<inline-formula><mml:math 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 the start of the
record in 1996 to 1.4 ng m<inline-formula><mml:math 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 2011, showing a downwards trend of
1.4–1.8 % per year. Both a downward trend of 1.6 % at MHD from 2013
and 2014 and the slight increase in Hg concentrations seen by
<xref ref-type="bibr" rid="bib1.bibx92" id="text.34"/> at CPT from 2007 to 2013 continued through the end of
2014. Some debate remains as to whether anthropogenic emissions are increasing
or decreasing <xref ref-type="bibr" rid="bib1.bibx60 bib1.bibx84 bib1.bibx81" id="paren.35"/>. A clear
gradient of GEM concentrations between the Northern and Southern hemispheres
is seen in the data for both 2013 and 2014, in line with previous studies
<xref ref-type="bibr" rid="bib1.bibx93 bib1.bibx94 bib1.bibx95 bib1.bibx61 bib1.bibx100" id="paren.36"/>.</p>
      <p>The 13 northern sites had significantly higher median concentrations than
the southern sites did. The north–south gradient is clearly evident in Fig. <xref ref-type="fig" rid="Ch1.F4"/> where the probability density
functions (PDFs) of the data are reported. The datasets have been divided into three
principal groups related to the latitude: north samples, tropical samples and
south samples. The histograms, normalized to the unit area, have been
constructed following the Scott rule for the bin width <inline-formula><mml:math display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>W</mml:mi></mml:mrow></mml:math></inline-formula>: <inline-formula><mml:math display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>W</mml:mi><mml:mo>=</mml:mo><mml:mn>3.5</mml:mn><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>/</mml:mo><mml:mroot><mml:mi>n</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:mroot></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> represents the standard deviation
and <inline-formula><mml:math display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> the number of samples. This choice is optimal when dealing with normal
distributed samples since it minimizes the integrated mean squared error of
the density estimate and is then fitted through a normal distribution (full line in
Fig. <xref ref-type="fig" rid="Ch1.F4"/>), obtained through the classical maximum likelihood
estimation method. Since a clear overlap can be observed between the three
datasets presented in Fig. <xref ref-type="fig" rid="Ch1.F4"/>, in order to make the
distinction between the distributions clear we perform the standard Student <inline-formula><mml:math display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test
against the null hypothesis (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>h</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) that the three distributions come from
the same mother distribution with the same mean (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) and unknown
standard deviation (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>).</p>
      <p>For every case the null hypothesis (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>h</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) can be rejected, as the means of
the three distribution are significantly different, with a 99 % confidence
level. If <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">N</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">S</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> are the mean of the experimental
measures,
respectively, for the northern, southern and tropical groups, the confidence
intervals evaluated from the <inline-formula><mml:math display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test are reported in Table <xref ref-type="table" rid="Ch1.T2"/>. The
interpretations of the results clearly demonstrate that <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">N</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">S</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
(Table <xref ref-type="table" rid="Ch1.T2"/>), so that a significant gradient exists in the GEM
concentrations from the Northern Hemisphere to the Southern Hemisphere. Due to
the significant difference in the PDFs, the probability <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> (<inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value) of
observing a test statistic as extreme as, or more extreme than, the observed
value under the null hypothesis is close to zero. Thus the validity of the
null hypothesis should be rejected. The spatial gradient observed from
northern
to southern regions is  highlighted in both Figs. <xref ref-type="fig" rid="Ch1.F5"/> and
<xref ref-type="fig" rid="Ch1.F6"/>, which also report the statistical monthly distribution of GEM
values obtained for 2013 and 2014, respectively, at all GMOS sites in the
Northern and Southern hemispheres as well as in the tropical area.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><caption><p>Probability density functions (PDFs) of the GEM data (ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)
for the northern, southern and tropical sample groups (dash dotted lines).
Full lines the normal distribution fit of the samples.</p></caption>
          <?xmltex \igopts{width=199.169291pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f04.pdf"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2"><caption><p>The mean (<inline-formula><mml:math display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula>) of the experimental measures for the
northern (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">N</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>), southern (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">S</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and tropical
(<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) groups and the confidence intervals evaluated from the
Student <inline-formula><mml:math display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test among them.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.97}[.97]?><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1">Difference between</oasis:entry>  
         <oasis:entry colname="col2">Minimum of the</oasis:entry>  
         <oasis:entry colname="col3">Maximum of the</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">means</oasis:entry>  
         <oasis:entry colname="col2">confidence interval</oasis:entry>  
         <oasis:entry colname="col3">confidence interval</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">N</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">S</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.590</oasis:entry>  
         <oasis:entry colname="col3">0.592</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">N</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.225</oasis:entry>  
         <oasis:entry colname="col3">0.229</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">T</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi mathvariant="normal">S</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.362</oasis:entry>  
         <oasis:entry colname="col3">0.365</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p>Monthly statistical distribution and spatial gradient for 2013 year
from Northern Hemisphere to Southern Hemisphere.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f05.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p>Monthly statistical distribution and spatial gradient for 2014 from
Northern Hemisphere to Southern Hemisphere.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f06.pdf"/>

        </fig>

<sec id="Ch1.S4.SS2.SSS1">
  <title>Seasonal pattern analysis in the Northern Hemisphere</title>
      <p>Statistics describing the spatial and temporal distribution of GEM
concentrations at all GMOS sites for 2013 and 2014 are summarized in
Fig. <xref ref-type="fig" rid="Ch1.F3"/> whereas Figs. <xref ref-type="fig" rid="Ch1.F5"/> and <xref ref-type="fig" rid="Ch1.F6"/> show the monthly
statistical GEM distribution for both years considered. The GEM
concentrations highlight that the mean GEM values of most of the GMOS sites
were between 1.3 and 1.6 ng m<inline-formula><mml:math 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>, with a typical interquartile range of
about 0.25 ng m<inline-formula><mml:math 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>. Only a few sites have shown a mean values above
1.6 ng m<inline-formula><mml:math 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>, such as MCH, MIN and MAL, and only the EVK site, located
at 5050 m a.s.l. in the Eastern Himalaya of Nepal, reported mean
values below 1.3 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. This value is comparable with free
tropospheric concentrations measured in August 2013 over Europe
<xref ref-type="bibr" rid="bib1.bibx118" id="paren.37"/>. The mean GEM concentration observed at EVK is less
than the reported background GEM concentration for the Northern Hemisphere
(1.5–1.7 ng m<inline-formula><mml:math 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 more similar to expected background levels of
GEM in the Southern Hemisphere (1.1–1.3 ng m<inline-formula><mml:math 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>) <xref ref-type="bibr" rid="bib1.bibx61 bib1.bibx76" id="paren.38"/>. The values between 1.3 and 1.6 ng m<inline-formula><mml:math 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> observed at the
other GMOS sites in the Northern Hemisphere are comparable to the
concentrations measured at the long-term monitoring stations at Mace Head,
Ireland <xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx91 bib1.bibx117" id="paren.39"/>, and Zingst, Germany
<xref ref-type="bibr" rid="bib1.bibx53" id="paren.40"/>. GEM concentration means are also in good agreement with the
overall mean concentrations observed at multiple sites in the Canadian
Atmospheric Mercury Measurement Network (CAMNet) (1.58 ng m<inline-formula><mml:math 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>)
reported by <xref ref-type="bibr" rid="bib1.bibx110" id="text.41"/> and those reported from Arctic stations in this
paper (VRS, PAL). Seasonal variations of GEM concentrations have also been
observed at all GMOS sites in the Northern Hemisphere. Most sites show higher
concentrations during the winter and spring and lower concentrations in
summer and fall seasons (Figs. <xref ref-type="fig" rid="Ch1.F5"/> and <xref ref-type="fig" rid="Ch1.F6"/>). However, few
sites such as VRS, Station Nord (northeastern Greenland:
81<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>36<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> N, 16<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> W), show a slightly different seasonal
variation. In winter this high Arctic site (VRS) is sporadically impacted by
episodic transport of pollution mainly due to high atmospheric pressure
systems over Siberia and low pressure systems over the North Atlantic
<xref ref-type="bibr" rid="bib1.bibx89 bib1.bibx71" id="paren.42"/>. During the spring (April–May) and summer
(August–September) seasons GEM concentrations show a higher variability with
low concentrations near the instrumental detection limit due to episodic
atmospheric Hg depletion events (AMDEs) that occur in the spring
<xref ref-type="bibr" rid="bib1.bibx89 bib1.bibx97 bib1.bibx98 bib1.bibx48 bib1.bibx103 bib1.bibx25" id="paren.43"/> and high GEM concentrations (2 ng m<inline-formula><mml:math 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 June and
July, probably due to GEM emissions from snow and ice surfaces
<xref ref-type="bibr" rid="bib1.bibx82 bib1.bibx97 bib1.bibx98 bib1.bibx100 bib1.bibx26 bib1.bibx27" id="paren.44"/> and Hg evasion from the Arctic Ocean
<xref ref-type="bibr" rid="bib1.bibx32 bib1.bibx19" id="paren.45"/>. Models of the MBL
that simulate the temporal variations of Hg species <xref ref-type="bibr" rid="bib1.bibx45 bib1.bibx46 bib1.bibx50 bib1.bibx94" id="paren.46"/> show that photo-induced oxidation
of GEM by Br can reproduce the diurnal variation of GOM observed in the MBL
during cruise measurements better than other oxidation candidates
<xref ref-type="bibr" rid="bib1.bibx45 bib1.bibx99" id="paren.47"/> and also the seasonal variation
<xref ref-type="bibr" rid="bib1.bibx94" id="paren.48"/>. Although Br is currently considered to be the
globally most important oxidant for determining the lifetime of GEM in the
atmosphere, there are also other possible candidates that can enhance Hg
oxidation <xref ref-type="bibr" rid="bib1.bibx51 bib1.bibx7 bib1.bibx107 bib1.bibx108" id="paren.49"/>. The lack of a
full understanding of the reaction kinetics and fate of atmospheric Hg
highlights the need to have a global observation system as presented here in
order to calibrate and constrain atmospheric box and global/regional-scale
models <xref ref-type="bibr" rid="bib1.bibx45 bib1.bibx20" id="paren.50"/>.</p>
</sec>
<sec id="Ch1.S4.SS2.SSS2">
  <title>GMOS sites in Asia</title>
      <p>As can be seen in Fig. <xref ref-type="fig" rid="Ch1.F3"/>, the group with the highest GEM median
variability and maximum concentrations is in Asia, which includes the following
sites: Mt. Ailao (MAL), Mt. Changbai (MCH), Mt. Waliguan (MWA) and Minamata
(MIN), where 95th percentile values ranged from 3.26 to 2.74 ng m<inline-formula><mml:math 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
2013 (Table S2). These sites are often impacted by air masses that have
crossed emission source regions <xref ref-type="bibr" rid="bib1.bibx2" id="paren.51"/>. GEM concentrations
recorded at all remote Chinese sites (MAL, MCH and MWA) are elevated
compared to that observed at background/remote areas in Europe and North
America, and at others sites in the Northern Hemisphere <xref ref-type="bibr" rid="bib1.bibx36 bib1.bibx37 bib1.bibx38" id="paren.52"/>. A previous study by <xref ref-type="bibr" rid="bib1.bibx36" id="text.53"/> at MWA suggested that
long-range atmospheric transport of GEM from industrial and urbanized areas
in northwestern China and northwestern India contributed significantly to
the elevated GEM at MWA. MAL station is located in Southwest China, at
the summit of Ailao Mountain National Nature Reserve, in central Yunnan
province. It is a remote station, isolated from industrial sources and
populated regions in China. Kunming, one of the largest cities in
Southwest China, is located 180 km to the northeast of the MAL site. The
winds are dominated by the Indian summer monsoon (ISM) in warm seasons (May
to October), and the site is mainly impacted by Hg emission from eastern
Yunnan, western Guizhou and southern Sichuan of China and the northern part
of the Indochinese Peninsula. In cold seasons the impact of emissions from
India and northwestern part of the Indochinese Peninsula increased and
played an important role in elevated GEM observed at MAL <xref ref-type="bibr" rid="bib1.bibx122" id="paren.54"/>.
However, most of the important Chinese anthropogenic sources of Hg and other
air pollutants are located to the north and east of the station, whereas
anthropogenic emissions from southern and western Yunnan province are fairly
low <xref ref-type="bibr" rid="bib1.bibx119 bib1.bibx55 bib1.bibx122" id="paren.55"/>. Average atmospheric GEM
concentrations during this study calculated for MWA and MAL during 2013 and
2014 are in good agreement with those observed during previous measurements
at both sites from October 2007 to September 2009 at MWA and from
September 2011 to March 2013 at MAL <xref ref-type="bibr" rid="bib1.bibx38 bib1.bibx122" id="paren.56"/>. Also the
overall mean GEM concentration observed in 2013 and 2014 at MCH background
air pollution site (1.66 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.48 ng m<inline-formula><mml:math 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 2013 and
1.48 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.42 ng m<inline-formula><mml:math 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 2014, respectively) is in good agreement
with the overall mean value recorded earlier from 24 October 2008 to
31 October 2010 (1.60 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.51 ng m<inline-formula><mml:math 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>, Fu et al.,
2012b). <xref ref-type="bibr" rid="bib1.bibx36" id="text.57"/> highlighted a higher mean
TGM concentration of 3.58 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.78 ng m<inline-formula><mml:math 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> observed from
August 2005 to July 2006 that was probably due to surface winds circulation with
effect of regional emission sources, such as the large iron mining district
in the
northern part of North Korea and two large power plants and urban areas to
the southwest of the sampling site.</p>
      <p>In summary, the observed concentrations are a function of site location
relative to both natural and anthropogenic sources, elevation and local
conditions (i.e., meteorological parameters), often showing links to the
patterns of regional air movements and long-range transport. Seasonal
variations at ground-based remote sites in China have been observed. At MCH
GEM was significantly higher during cold seasons compared to that recorded in
warm seasons (from April to September) whereas the reverse has been observed
at the other two Chinese GMOS sites.</p>
      <p>In order to statistically check the difference of GEM concentrations among
the three Chinese sites an alternative statistical test has been performed,
since in this case the distributions are strongly non-normal.</p>
      <p>As in the previous case we construct the unit-area histogram, then we fit
with a log-normal distribution. It is worth noting that in this case the
histograms has been constructed by manually setting the bin width <inline-formula><mml:math display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>W</mml:mi></mml:mrow></mml:math></inline-formula>.
With this choice the total number of bins can be evaluated as
              <disp-formula id="Ch1.E1" content-type="numbered"><mml:math display="block"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mo>(</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mo>max⁡</mml:mo></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mo>min⁡</mml:mo></mml:msub><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>W</mml:mi><mml:mo>=</mml:mo><mml:mn>61.</mml:mn></mml:mrow></mml:math></disp-formula>
            By looking at Fig. <xref ref-type="fig" rid="Ch1.F7"/>, is easy to notice that the skewness
(<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub><mml:mo>/</mml:mo><mml:msup><mml:mi mathvariant="italic">σ</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msup><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> where <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> is third-order moment of the
distribution and <inline-formula><mml:math display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> is the standard deviation) and the kurtosis
(<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub><mml:mo>/</mml:mo><mml:msubsup><mml:mi mathvariant="italic">μ</mml:mi><mml:mn mathvariant="normal">2</mml:mn><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup><mml:mo>∼</mml:mo><mml:mn>10</mml:mn></mml:mrow></mml:math></inline-formula> where <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the <inline-formula><mml:math display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>th-order moment of the
distribution) are far from being zero. In the following the alternative is
briefly described. Let us consider a pair of our three time series, namely
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math display="inline"><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>), which corresponds to independent random samples described
by the log-normal distributions. Then the random variables <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mi>ln⁡</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>
are close to normal distribution with
means <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and variances <inline-formula><mml:math display="inline"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">σ</mml:mi><mml:mi>i</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup></mml:mrow></mml:math></inline-formula>, namely <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>∼</mml:mo><mml:mi>N</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>,</mml:mo><mml:msubsup><mml:mi mathvariant="italic">σ</mml:mi><mml:mi>i</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><caption><p>Probability density functions (PDFs) of the GEM data (ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)
for the Chinese sample groups (dash dotted lines). Full lines the log-normal
distribution fit of the samples.</p></caption>
            <?xmltex \igopts{width=170.716535pt}?><graphic xlink:href="https://acp.copernicus.org/articles/16/11915/2016/acp-16-11915-2016-f07.pdf"/>

          </fig>

      <p>Since <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mi>exp⁡</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi mathvariant="italic">μ</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>+</mml:mo><mml:mn>0.5</mml:mn><mml:msubsup><mml:mi mathvariant="italic">σ</mml:mi><mml:mi>i</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> is the expectation value for
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, the problem of our interest is then to test the null hypothesis on
<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. More formally, we test <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msub><mml:mo>:</mml:mo><mml:mi mathvariant="italic">θ</mml:mi><mml:mo>≤</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math display="inline"><mml:mrow><mml:mi mathvariant="italic">θ</mml:mi><mml:mo>=</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. In other words, we test the null hypothesis to see if there is a
significant difference in the sample means. Using the algorithm described in
<xref ref-type="bibr" rid="bib1.bibx54" id="text.58"/> and <xref ref-type="bibr" rid="bib1.bibx1" id="text.59"/>, specifically designed to
perform the inference on difference of means of two log-normal distributions, we obtain the estimates for the <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>-values which are close to <inline-formula><mml:math display="inline"><mml:mn mathvariant="normal">1</mml:mn></mml:math></inline-formula> and the
confidence intervals, calculated at a confidence level of 95 % (reported in Table <xref ref-type="table" rid="Ch1.T3"/>).</p>
      <p>From the statistical results we can conclude that a clear distinction  exists
between the MWA site and the other two (MCH, MAL) as shown from the values in
Table <xref ref-type="table" rid="Ch1.T3"/>. However, despite the large overlap in the samples
distributions of MCH and MAL the difference in their <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MCH</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>
and <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MAL</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, respectively) is also significant, with a smaller confidence
interval.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3"><caption><p>Differences between the <inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> obtained for MCH, MWA and MAL,
confidence intervals and associated <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> values.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.95}[.95]?><oasis:tgroup cols="4">
     <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:thead>
       <oasis:row>  
         <oasis:entry colname="col1">Difference of</oasis:entry>  
         <oasis:entry colname="col2">Minimum of the</oasis:entry>  
         <oasis:entry colname="col3">Maximum of the</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">confidence interval</oasis:entry>  
         <oasis:entry colname="col3">confidence interval</oasis:entry>  
         <oasis:entry colname="col4"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MCH</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MWA</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.285</oasis:entry>  
         <oasis:entry colname="col3">0.286</oasis:entry>  
         <oasis:entry colname="col4">1</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MCH</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MAL</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.043</oasis:entry>  
         <oasis:entry colname="col3">0.043</oasis:entry>  
         <oasis:entry colname="col4">1</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MWA</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi mathvariant="italic">η</mml:mi><mml:mi mathvariant="normal">MAL</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col2">0.328</oasis:entry>  
         <oasis:entry colname="col3">0.329</oasis:entry>  
         <oasis:entry colname="col4">1</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <p>Several hypothesis have been made to explain the seasonal variations of GEM
in China, including seasonal changes in anthropogenic GEM emissions and
natural emissions. The seasonal emission changes mainly resulted from coal
combustion for urban and residential heating during cold seasons. This source
lacks emission control devices and releases large amounts of Hg, leading to
elevated GEM concentrations in the area and thus at MCH <xref ref-type="bibr" rid="bib1.bibx31 bib1.bibx33 bib1.bibx34 bib1.bibx35" id="paren.60"/>. Conversely, GEM at MAL and MWA was higher in warm
seasons than in cold seasons. These findings highlight that emissions from
domestic heating during the winter could not explain the lower winter GEM
concentrations observed at MWA and MAL, but there might be other
not-yet-understood factors that played a key role in the observed GEM
seasonal variations at these sites, such as the monsoonal winds influence
which can change the source–receptor relationship at observational sites and
subsequently the seasonal GEM trends <xref ref-type="bibr" rid="bib1.bibx3 bib1.bibx38" id="paren.61"/>. Among the remote
Chinese sites, MAL started as secondary site and in 2014 was upgraded to a
master site; conversely, MWA started as a master site and then became a
secondary site whereas MCH operated continuously as a master site. Therefore,
PBM and GOM concentrations have been measured during the years 2013 and 2014
at all Chinese sites even if not continuously (see Fig. <xref ref-type="fig" rid="Ch1.F2"/> for Hg
speciation data coverage). The GOM and PBM concentrations measured at these
sites were substantially elevated compared to the background values in the
Northern Hemisphere, from 1.8 to 42.8 pg m<inline-formula><mml:math 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 from 40.4 to 167.4 pg m<inline-formula><mml:math 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 the MCH and MWA, respectively, in 2013. The 2014 PBM maxima
were 44.2 and 45.0 pg m<inline-formula><mml:math 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 MCH and MAL, respectively. Regional
anthropogenic emissions and long-range transport from domestic source regions
are likely to be the primary causes of these elevated values
<xref ref-type="bibr" rid="bib1.bibx86" id="paren.62"/>. Seasonal variations of PBM observed at the Chinese master
sites mostly showed lower concentrations in summer and higher concentrations
(up to 1 order of magnitude higher) in winter and fall <xref ref-type="bibr" rid="bib1.bibx113 bib1.bibx114 bib1.bibx34 bib1.bibx124 bib1.bibx121 bib1.bibx120 bib1.bibx123" id="paren.63"/>. The higher PBM in
winter was likely caused by direct PBM emissions, formation of secondary
particulate Hg via gas–particle partitioning and a lack of wet scavenging
processes <xref ref-type="bibr" rid="bib1.bibx113 bib1.bibx34 bib1.bibx124" id="paren.64"/>. PBM has an atmospheric
residence time ranging from a few hours to several days and can therefore be
transported to the remote sites when conditions are favorable
<xref ref-type="bibr" rid="bib1.bibx86" id="paren.65"/>. Atmospheric PM pollution is of special
concern in China due to the spatial distribution of anthropogenic emission
concentrations of PM2.5 in heavily populated areas of eastern and northern
China, which are among the highest in the world <xref ref-type="bibr" rid="bib1.bibx112" id="paren.66"/>. The GOM
concentrations observed at both master sites show high variability and
several episodes with high GOM values were probably due to local emission
sources (such as domestic heating in small settlements) rather than to
long-range transport from industrial and urbanized areas <xref ref-type="bibr" rid="bib1.bibx38" id="paren.67"/>. GOM
has a shorter atmospheric residence time that limits long-range transport
<xref ref-type="bibr" rid="bib1.bibx59 bib1.bibx78" id="paren.68"/>. However, with low RH and high winds, the
possibility of regional transport of GOM cannot be ruled out. For example,
the observations at MWA exhibit a number of high GOM events related to air
plumes originating from industrial and urbanized centers that are about 90 km
east of the sampling site <xref ref-type="bibr" rid="bib1.bibx36 bib1.bibx76" id="paren.69"/>. MWA is a remote
site situated at the edge of the northeastern part of the Qinghai–Xizang
(Tibet) plateau. The monitoring station is relatively isolated from
industrial point sources and there are no known local Hg sources around the
site. Most of the Chinese industrial and populated regions associated with
anthropogenic Hg emissions are situated to the east of MWA. Predominantly
winds are from the west to southwest in cold seasons and the east in warm
seasons <xref ref-type="bibr" rid="bib1.bibx76" id="paren.70"/>. East Asia is, in fact, the largest Hg source
region in the world, contributing to nearly 50 % of the global anthropogenic
Hg emissions to the atmosphere <xref ref-type="bibr" rid="bib1.bibx105 bib1.bibx106 bib1.bibx80 bib1.bibx58" id="paren.71"/>.</p>
</sec>
<sec id="Ch1.S4.SS2.SSS3">
  <title>Seasonal pattern analysis in the Southern Hemisphere</title>
      <p>For the sites located in the Southern Hemisphere, the GEM concentrations
highlight that the mean GEM values ranged between 0.84 and
1.09 ng m<inline-formula><mml:math 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 both 2013 and 2014, with a typical interquartile range
of about 0.25 ng m<inline-formula><mml:math 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> (see Figs. <xref ref-type="fig" rid="Ch1.F3"/>, <xref ref-type="fig" rid="Ch1.F5"/> and
<xref ref-type="fig" rid="Ch1.F6"/>). The mean GEM concentrations observed at the southern sites are
lower than those reported in the Northern Hemisphere but in good agreement
with the southern hemispherical background (1.1 ng m<inline-formula><mml:math 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>)
<xref ref-type="bibr" rid="bib1.bibx61 bib1.bibx100 bib1.bibx60 bib1.bibx26 bib1.bibx4 bib1.bibx92 bib1.bibx93" id="paren.72"/> and the expected range for remote
sites in the Southern Hemisphere. As in the Northern Hemisphere, a seasonal
variation of GEM concentrations was observed in the Southern Hemisphere. In
particular, GEM concentrations from the coastal Global Atmosphere Watch
station, Cape Point (CPT), South Africa, show seasonal variations with maxima
during austral winter and minima in summer. The site is located in a nature
reserve at the southernmost tip of the Cape Peninsula on a hill,
230 m a.s.l. It is characterized by dry summers with moderate temperatures
and increased precipitation (cold fronts) during austral winter. During the
summer months, biomass burning events sometimes occur within the
southwestern Cape region, affecting GEM levels. The dominant wind direction
at CPT is from the southeastern sector, advecting clean maritime air from the
South Atlantic Ocean <xref ref-type="bibr" rid="bib1.bibx13 bib1.bibx14" id="paren.73"/> which occurs primarily
during austral summer (December till February). Furthermore, the station is
also at times subjected to air from the northern sector, mainly during
austral winter. During such continental airflow events, anthropogenic
emissions from the industrialized area in Gauteng, 1500 km to the northeast
of CPT, can sometimes be observed <xref ref-type="bibr" rid="bib1.bibx14 bib1.bibx92" id="paren.74"/>. The GEM
seasonal variability at CPT is hence in good agreement with the prevailing
climatology at the site. Also GEM data at Amsterdam Island followed a similar
trend, with slightly but significantly higher concentrations in winter
(July–September) than in summer (December–February). Amsterdam Island is a
remote and very small island of 55 km<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> with a population of about
30 residents, located in the southern Indian Ocean at 3400 and 5000 km
downwind from the nearest lands, Madagascar and South Africa, respectively
<xref ref-type="bibr" rid="bib1.bibx4" id="paren.75"/>. GEM concentrations at AMS were remarkably steady with an
average hourly mean concentration of 1.03 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and a
range of 0.72–1.55 ng m<inline-formula><mml:math 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>. A small seasonal cycle has been observed
by <xref ref-type="bibr" rid="bib1.bibx4" id="text.76"/> and despite the remoteness of the island, wind sector
analysis, air mass back trajectories and satellite observations suggest the
presence of a long-range contribution from the southern African continent to
the GEM regional/global budget from July to September during the biomass
burning season extended from May to October <xref ref-type="bibr" rid="bib1.bibx4" id="paren.77"/>. The higher GEM
concentrations at AMS are comparable with those recorded at Calhau (Cabo
Verde), Nieuw Nickerie (Paramaribo) and Sisal (Mexico) in the tropical zone,
whereas the lower concentrations of GEM observed, less than 1 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>,
were associated with air masses coming from southern Indian Ocean and the
Antarctic continent. Bariloche (BAR) master site in North Patagonia also
shows higher concentrations during the austral winter (from end of May to
September) and lower concentrations in other seasons <xref ref-type="bibr" rid="bib1.bibx24" id="paren.78"/>.
The Patagonian site has been established inside Nahuel Huapi National Park, a
well-protected natural reserve, located east of the Patagonian Andes.
The area is included in the Southern Volcanic Zone (SVZ) of the Andes, under
the influence of at least three active volcanoes with high eruption frequency
located at the west of the Andes cordillera <xref ref-type="bibr" rid="bib1.bibx17" id="paren.79"/>. The climate of
the region is influenced by the year-round strong westerly winds blowing from
the Pacific which discharge the humidity in a markedly seasonal way
(fall–winter) in the western area of the park. GEM records at BAR station
show background concentrations comparable to those found in Antarctica and
other remote locations of the South Hemisphere with concentrations ranging
between 0.2 and 1.3 ng m<inline-formula><mml:math 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>, with an annual mean of
0.89 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.15 ng m<inline-formula><mml:math 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>. Previous records of GEM concentrations from
a short-term survey in 2007 along a longitudinal transect across the Andes
with Bariloche as the eastern endpoint reported concentrations below
2 ng m<inline-formula><mml:math 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> close to BAR <xref ref-type="bibr" rid="bib1.bibx49" id="paren.80"/>. In this survey, the
highest GEM concentrations were recorded in the proximity and downwind from
the volcanic area, reaching concentrations up to 10 ng m<inline-formula><mml:math 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>
<xref ref-type="bibr" rid="bib1.bibx49" id="paren.81"/>. Similarly to the seasonal trends at other GMOS sites in
the Southern Hemisphere, GEM concentrations were at their lowest level in
summer on the Antarctic Plateau at Concordia Station (DMC, altitude 3220 m)
but at their highest level in fall <xref ref-type="bibr" rid="bib1.bibx6" id="paren.82"/>. GEM concentrations
reached levels of 1.2 ng m<inline-formula><mml:math 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> from mid-February to May (fall) likely
due to a low boundary layer oxidative capacity under low solar radiation
limiting GEM oxidation and/or a shallow boundary layer (<inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 50 m in
average) limiting the dilution. In summer (November to mid-February), the DMC
GEM data showed a high variability with a concentration range varying from
below the detection limit to levels comparable to those recorded at
midlatitude background Southern Hemisphere stations due to an intense
chemical exchange at the air/snow interface. Additionally, the mean
summertime GEM concentration at DMC was <inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 25 % lower than at other
Antarctic stations in the same period of the year, suggesting a continuous
oxidation of GEM as a result of the high oxidative capacity of the Antarctic
plateau boundary layer in summer. GEM depletion events occurred each year in
summer (January–February 2012 and 2013) with GEM concentrations remaining
low (<inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 0.40 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) for several weeks. These depletion events
did not resemble the ones observed in the Arctic. They were not associated
with depletion of ozone and occurred as air masses stagnated over the
Plateau,
which could favor an accumulation of oxidants within the shallow boundary
layer. These observations suggest that the inland atmospheric reservoir in
Antarctica is depleted in GEM and enriched in GOM in summer. Measurements at
DDU on the East Antarctic coast were dramatically influenced by air masses
exported from the Antarctic Plateau by strong katabatic winds
<xref ref-type="bibr" rid="bib1.bibx5" id="paren.83"/>. These results, along with observations from earlier
studies, demonstrate that, in Antarctica, the inland atmospheric reservoir
can influence the cycle of atmospheric Hg at a continental scale
<xref ref-type="bibr" rid="bib1.bibx96 bib1.bibx109 bib1.bibx74 bib1.bibx6 bib1.bibx5" id="paren.84"/>. Observations at DDU also highlighted that the Austral Ocean
is a net source of GEM in summer and a net sink in spring, likely due to
enhanced oxidation by halogens over sea-ice-covered areas.</p>
</sec>
<sec id="Ch1.S4.SS2.SSS4">
  <title>Seasonal pattern analysis in the tropical zone</title>
      <p>Relatively few observations of atmospheric Hg had been carried out in the
tropics, before the start of GMOS. Until recently atmospheric Hg data for the
tropics were only available from short-term measurement campaigns. To date,
therefore, there is no information in the tropical area that can be used to
establish long-term trends. Observations in this region may provide a
valuable input to our understanding of key exchange processes that take place
in the Hg cycle considering that the Intertropical Convergence Zone (ITCZ)
passes twice each year over this region and the northern and southern
hemispheric air masses may well influence the evolution of Hg concentrations
observed in this region. As can be seen in Fig. <xref ref-type="fig" rid="Ch1.F3"/>, five GMOS sites
are located in the tropics: Sisal (SIS) in Mexico, Nieuw Nickerie
(NIK) in Suriname, Manaus (MAN) in Brazil, Calhau (CAL) in Cabo Verde and
southern Kodaikanal (KOD) in southern India. GEM concentrations observed in
2013 and 2014 at all sites are comparable with Hg levels recorded at remote
sites in the Southern Hemisphere (1.1 to 1.3 ng m<inline-formula><mml:math 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>; Lindberg et al.,
2007). Among these sites, the Kodaikanal site (KOD) shows the highest monthly
mean GEM concentrations (see Figs. <xref ref-type="fig" rid="Ch1.F5"/> and <xref ref-type="fig" rid="Ch1.F6"/> as well as
Tables S1 and S2) ranging between 1.25 ng m<inline-formula><mml:math 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> (5th percentile) to
1.87 ng m<inline-formula><mml:math 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> (95th percentile) during 2013 with an annually based
statistic mean of 1.54 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.20 ng m<inline-formula><mml:math 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 between
1.20 ng m<inline-formula><mml:math 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> (5th percentile) to 2.03 ng m<inline-formula><mml:math 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> (95th percentile)
during 2014 with an annually average of 1.48 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.26 ng m<inline-formula><mml:math 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>. KOD
is a Global Atmospheric Watch (GAW) regional site which is operated by the
Indian Meteorological Department. It is worthwhile to point out that the other
tropical GMOS sites are close to sea level and on the coast, whereas KOD is a
high-altitude site (2333 m a.s.l.). Therefore different meteo-climatic
conditions influence the long-range transport of air masses to this site.
This site is also influenced by anthropogenic sources such as the well-known,
but not close, Hg thermometer plant, 2150 m far away from the monitoring
station at Kodaikanal <xref ref-type="bibr" rid="bib1.bibx52" id="paren.85"/>. Due to this anthropogenic
influence, atmospheric Hg concentrations from 3 to 8 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for the
years 2000 and 2001 have been reported <xref ref-type="bibr" rid="bib1.bibx83" id="paren.86"/>. India is the
third largest hard coal producer in the world after the People's Republic of
China and the USA <xref ref-type="bibr" rid="bib1.bibx80 bib1.bibx62 bib1.bibx73" id="paren.87"/>. For the past
3 decades, India has increased the production of metals, cement,
fertilizers and electricity through burning of coal, natural gas and oil,
becoming one of the most rapidly growing economies <xref ref-type="bibr" rid="bib1.bibx66 bib1.bibx52" id="paren.88"/>. Relatively little attention has been paid to potential Hg
pollution problems due to mining operations, metal smelting, energy and fuel
consumption, which could impact on ecosystem health <xref ref-type="bibr" rid="bib1.bibx64" id="paren.89"/>. Hg
concentrations are in fact enhanced in India due to industrial emissions of
Hg mostly from coal combustion (the major source category (48 %),
followed by waste disposal (31 %), the iron and steel industry,
chloralkali plants, the cement industry and other minor sources (i.e.,
clinical thermometers) <xref ref-type="bibr" rid="bib1.bibx65 bib1.bibx111" id="paren.90"/>. Unfortunately,
details of Hg emissions from these facilities and atmospheric Hg data in
general are scarce. Therefore it is necessary for India as well as for the
other place in the world where Hg measurement are yet lacking to generate
continuous data, which can then be used by scientists for modeling applications
to improve emission inventories in order to prevent inaccurate assessments of
Hg emission and deposition.</p>
      <p>GEM levels observed at Sisal (SIS), Mexico, were below the expected global
average concentration (<inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 1.5 ng m<inline-formula><mml:math 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>). Monthly mean GEM
concentrations ranged between 1.0 and 1.47 ng m<inline-formula><mml:math 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 2013 with an
annual average of 1.20 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.24 ng m<inline-formula><mml:math 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> (5th and 95th percentiles: 0.8
and 1.58 ng m<inline-formula><mml:math 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>), whereas in 2014 the range varied from 0.82 to 1.45 ng m<inline-formula><mml:math 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>, with an annual average of 1.11 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.37 ng m<inline-formula><mml:math 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> (5th
and 95th percentiles: 0.82 and 1.45 ng m<inline-formula><mml:math 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>). GEM measurements at SIS
showed, in addition, very little variability over the sampling period,
indicating that this relatively remote site on the Yucatán Peninsula was not
subject to any significant anthropogenic sources of Hg at all. During 2013
and 2014, the SIS site was typically influenced by the marine air
originating from the Atlantic Ocean before entering the Gulf of Mexico
<xref ref-type="bibr" rid="bib1.bibx85" id="paren.91"/>. Average GEM concentrations reported at SIS are lower than
those recorded in other rural places in Mexico, such as Puerto Angel (on the
Pacific coast in Oaxaca state) and Huejutla (a rural area in the state of
Hidalgo), where average values of 1.46 and 1.32 ng m<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> were
determined, respectively <xref ref-type="bibr" rid="bib1.bibx21" id="paren.92"/>. Low GEM concentrations were
recorded in 2013 during the later part of the wet season (July/October).
Those values may indicate a slight decrease, probably due to deposition
processes since the site is a coastal station and subject to frequent
episodes with high humidity caused by rain <xref ref-type="bibr" rid="bib1.bibx102" id="paren.93"/>. These
findings have also been confirmed through wind roses and backward
trajectories that show the predominant wind direction from east-southeast
most of the time and sometimes from east-northeast (Atlantic Ocean)
<xref ref-type="bibr" rid="bib1.bibx102" id="paren.94"/>. In addition, the ITCZ moves north of the Equator
passing over the Yucatán peninsula during the northern hemispheric summer,
causing tropical rain events which could contribute to the slight decrease of
Hg concentrations. Highest GEM levels were observed during the winter period
(December–January) in 2013, whereas 2014 had the lowest GEM concentration in January
and higher GEM levels during spring and summer. The background Hg
concentrations measured at Sisal are closely comparable to those recorded at
Nieuw Nickerie (NIK), Paramaribo, Suriname, located on the northeastern
coast of the South American continent, the first long-term measurement site
in the tropics which has been in operation since 2007 <xref ref-type="bibr" rid="bib1.bibx67" id="paren.95"/>.
Analysis of data shows that the annual mean GEM for 2013 and 2014 at NIK are
a little lower than those at SIS: 1.13 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.42 and 1.28 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.46 ng m<inline-formula><mml:math 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 (see Tables S1 and S2). NIK is also a
background site because most of the time the air masses arriving at the site
come from the clean marine air of the Atlantic Ocean and the influence of
possible local anthropogenic sources and continental air is minimal. As the
ITCZ crosses Suriname twice each year, the NIK site samples both northern and
southern hemispheric air masses. Occasionally higher values are seen: 1.57 ng m<inline-formula><mml:math 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 February/March 2013 and 1.51 in August/September 2014 (see Figs. S1 and
S2). Manaus (MAN) in Amazonia (Brazil) is a GMOS master site located in the
Amazon region, an area with a history of important land use change and
significant artisanal and small-scale gold mining activities since the 1980s.
Burning of natural vegetation to produce agriculture lands or pastures
represents an important diffuse source of Hg to the atmosphere in Brazil
<xref ref-type="bibr" rid="bib1.bibx56 bib1.bibx28" id="paren.96"/>. The analysis of atmospheric Hg species at
this site is thus important for the determination of the dynamics of
atmospheric Hg. Annual mean Hg concentrations in 2013 and 2014 at MAN are
slightly lower than those at both SIS and NIK, with little variability
between the two years (see Tables S1 and S2). The measurements from MAN
station may therefore suggest that although the Hg emissions from regional
biomass burning and artisanal and small-scale gold mining represent the major emission sources in the Amazon
basin as reported in a study performed by <xref ref-type="bibr" rid="bib1.bibx8" id="text.97"/>, they may not
have a significant impact locally but contribute to the global Hg background
(concerning Hg from biomass burning see <xref ref-type="bibr" rid="bib1.bibx22" id="text.98"/>. Unfortunately
the emissions from both these sources are associated with large uncertainties
and vary over time. Quantifying their impact in South America is extremely
important and there is a strong case for expanding the number of GMOS
measurement sites in the region. MAN is in fact a very remote site, inside
the campus of the Embrapa Amazonia Oriental and upwind from the three main
gold mining areas in the Amazon basin, which are located in Rondonia, Mato
Grosso and in the south of the Parà states <xref ref-type="bibr" rid="bib1.bibx8" id="paren.99"/>. Previous Hg
measurements performed by <xref ref-type="bibr" rid="bib1.bibx8" id="text.100"/> during an aircraft experiment
over different sites in the Amazon basin highlighted Hg concentrations
between 0.5 and 2 ng m<inline-formula><mml:math 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 pristine sites (and among them also MAN)
not impacted by air masses enriched with emissions from gold mining areas
and/or biomass burning. Those data collected from August to September 1995
are comparable to ours observed in 2013 and 2014 at MAN during the same
period, whereas  other sites over areas with intense biomass burning and
near areas with strong Hg emissions (Alta Floresta and Rondonia, for example)
reported very high Hg levels (5–14 ng m<inline-formula><mml:math 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>)<xref ref-type="bibr" rid="bib1.bibx8" id="paren.101"/>. These
high Hg concentrations were never observed at MAN during the 2013 and 2014
period. Monthly mean GEM concentrations at MAN ranged between 1.01
and 1.18 ng m<inline-formula><mml:math 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 2013 and between 0.94 and 1.10 ng m<inline-formula><mml:math 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 2014.
Also PBM and GOM recorded during 2013 show little variation and varied
between 1.35 and 12.70 pg m<inline-formula><mml:math 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> (5th and 95th percentile,
respectively) with a median value of 3.17 pg m<inline-formula><mml:math 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 2014, the range
was from 0.53 to 5.24 pg m<inline-formula><mml:math 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> (5th and 95th percentile,
respectively) with a median value of 1.48 pg m<inline-formula><mml:math 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 MAN Hg
concentrations therefore seem not to be influenced by regional emissions.
However, a number of parameters, such as the intense air mass convection
occurring in the Amazon basin and meteorological condition in general, clearly
contribute to the observed Hg concentrations, and they do not necessarily
reflect only regional emissions <xref ref-type="bibr" rid="bib1.bibx8 bib1.bibx28" id="paren.102"/>. Most of the
air masses that reach the site in 2013 and 2014 come from tropical Atlantic
and travel for about 1500 km over pristine forest before reaching the site
<xref ref-type="bibr" rid="bib1.bibx9" id="paren.103"/>; the prevailing winds during the wet seasons (from
January–March) were from north-northeast, northeast and east-northeast,
whereas during the dry seasons (from August to October) they were from north and
north-northeast as well as north-northwest <xref ref-type="bibr" rid="bib1.bibx9" id="paren.104"/>.</p>
      <p>The Cape Verde Atmospheric Observatory's Calhau Station (CAL) contributes data
from the eastern tropical Atlantic Ocean, where GMOS provides the only
existing dataset. CAL is an important GAW station located on Sao Vicente
Island, approximately 50 m from the coastline. GEM measurements from 2012 to
2014 were broadly consistent with previously published oceanographic campaign
measurements in the region, with typical Hg values between 1.1 and 1.4 ng m<inline-formula><mml:math 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 prevailing wind was from the northeast open ocean, bringing air
masses from the tropical Atlantic and from the African continent
<xref ref-type="bibr" rid="bib1.bibx63" id="paren.105"/>. Due to its relatively long residence time in the
atmosphere, the ground-level background GEM concentration tends to be
relatively constant over the year in tropical regions, unlike midlatitude
and polar regions where a more noticeable seasonal variation has been
observed. When compared with measurements from cruise campaigns from North to
South Atlantic, we can see that the GEM data at CAL are similar to previously
reported South Atlantic data, where Hg concentrations are lower than the
northern part of the Atlantic. Monthly mean GEM concentrations in 2013 ranged
from 1.12 to 1.38 ng m<inline-formula><mml:math 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>, with an annually based mean of 1.22 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.14 ng m<inline-formula><mml:math 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> (5th and 95th percentile equal to 1.04
and to 1.46 ng m<inline-formula><mml:math 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), whereas in 2014 the monthly mean
observed varied from 1.12 to 1.33 ng m<inline-formula><mml:math 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>, with an
annually based mean of 1.20 <inline-formula><mml:math display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.09 ng m<inline-formula><mml:math 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> (5th and 95th percentile
equal to 1.08 and to 1.36 ng m<inline-formula><mml:math 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). The
highest GEM concentrations in air originating from central Africa have been
recorded at CAL when the relative humidity was lowest (occasionally during
dust events) <xref ref-type="bibr" rid="bib1.bibx15" id="paren.106"/>. All tropical GMOS sites show little
atmospheric Hg variability through both the years (2013 and 2014) with small
GEM fluctuations during the months, which agrees well with a relatively long
atmospheric lifetime of Hg in the background troposphere and small variations
in the source strength <xref ref-type="bibr" rid="bib1.bibx29" id="paren.107"/>. However, clear diurnal cycles
of Hg have been conversely observed.</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusions</title>
      <p>The higher Hg concentrations and  spatiotemporal variability observed in
the Northern Hemisphere compared to the tropical area and Southern Hemisphere
confirm that the majority of emissions and re-emissions are located in the
Northern Hemisphere. The inter-hemispherical gradient with higher GEM
concentrations in the Northern Hemisphere has remained nearly constant over
the years,  confirmed by the observations carried out in the Southern
Hemisphere and other locations where previously GMOS Hg measurements were lacking
or absent. Previous results on all cruises carried out over the oceans
highlighted that in the Northern Hemisphere GEM mean values are almost
generally higher than those obtained in the Southern Hemisphere, with a
rather homogeneous distribution of GEM in the Southern Hemisphere. The
stability of these background concentrations can be seen as evidence that the
atmospheric lifetime of Hg is reasonably long to explain the extent of its
dispersion but would not be in accord with the most recent theoretical and
experimental studies of the reaction rates of Hg with atmospheric oxidants.
The oxidation of atmospheric Hg can occur with extraordinary rapidity in the
polar troposphere during the springtime Hg depletion events as well as within
the MBL due to the reactions between Hg and bromine
compounds, although there are other possible reactants that can enhance Hg
oxidation depending upon environmental factors and setting. These
uncertainties highlight several Hg issue which have to be improved to better
understand the atmospheric transport and transformation mechanisms of Hg. One
such issue
concerns the chemical composition of the oxidized phase of atmospheric Hg,
GOM and PBM, which are currently operationally defined but still not well
understood. Field and laboratory studies highlighted analytical interferences
within the methods currently adopted to measure oxidized Hg species which
suggest the variation of the chemical compounds across space and
time. This has significant implications for refining existing measurement
methods and developing new techniques/methodologies capable of distinguishing
between Hg compounds within different environmental compartments. Knowing the
precise chemical composition of GOM would immediately provide impetus to
those who study reaction kinetics to refine rate constants and reaction
mechanisms as well as allow modeling studies chemical mechanisms to be
verified, thus  improving our understanding of the important processes
characterizing the atmospheric transport and transformation of Hg. The
variation of observed Hg concentration across GMOS network shows increased
amplitude in areas strongly influenced by anthropogenic sources. There are,
however, uncertainties in the emission estimates especially for the tropical
region and the Southern Hemisphere and not enough long-term information in
either areas to identify long-term trends. The lack of an advanced global
emission inventory for regional- and global-scale models application
represented another important objective of the GMOS network. In the last
years several modeling studies have highlighted the discrepancy between
modeled and observed concentrations of GEM at background sites primarily due
to existing gaps in biomass burning, artisanal small-scale gold mining and
open-coal bed fire contributions within the emission inventories for
anthropogenic sources. Therefore, long-term atmospheric Hg measurements
across the GMOS global network and additional new GMOS ground-based sites
increasingly incorporated into strategic areas are crucial to continue in the
next future in order to provide high-quality measurement datasets which can
give new insights and information about the worldwide trends of atmospheric
Hg. The overarching benefit of this coordinated Hg monitoring network would
clearly be the advancement of  knowledge about Hg processes on a global scale
due to model/measurement comparisons, models development and validation on
different spatial and temporal scales, and assessing trends with significant
implications within the Task Force on Hemispheric Transport of Air Pollutants
(HTAP-TF) in the context of a global model intercomparison aimed to study
long-range transport pathways of pollutants and their precursors. The
experience gained during GMOS, the development of SOPs for Hg monitoring and
the establishment of the Spatial Data Infrastructure (SDI; <ext-link xlink:href="http://www.gmos.eu/sdi/">http://www.gmos.eu/sdi/</ext-link>) (along GEOSS lines),
which includes the G-DQM system, provide a template to aid countries complying
with the requirements of  Article 22 of the Minamata Convention.</p>
</sec>
<sec id="Ch1.S6">
  <title>Data availability</title>
      <p>Mercury data discussed in this manuscript are reported within the GMOS
central database and are available upon request at
<uri>http://sdi.iia.cnr.it/geoint/publicpage/GMOS/gmos_historical.zul</uri> (GMOS
Database, 2014). The GMOS database coordinated by the CNR-IIA is part of the
GMOS Cyber-Infrastructure (CI), which supports advanced data acquisition,
storage, management, integration, mining and visualization. All GMOS stations
provide near-real-time raw data that are archived and managed for the QA/QC
process by the GMOS-Data Quality Managment System (G-DQM), a web-based
application which is part of the GMOS-CI, developed by the CNR-IIA in 2011,
and is currently ongoing.</p>
</sec>

      
      </body>
    <back><app-group>
        <supplementary-material position="anchor"><p><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="http://dx.doi.org/10.5194/acp-16-11915-2016-supplement" xlink:title="pdf">doi:10.5194/acp-16-11915-2016-supplement</inline-supplementary-material>.</bold></p></supplementary-material>
        </app-group><ack><title>Acknowledgements</title><p>The number of people and institutions to acknowledge for their great
contribution during field studies is quite significant for a project like
GMOS, but we greatly acknowledge the European Commission for funding GMOS
as part of the FP7 (contract no. 26511). Special thanks to those research
scientists and technicians that helped to set up aircraft-based platform for
UTLS measurements, ground-based sites in remote locations including EV-K2 in
Karakorum, Amsterdam Island and Dome C in Antarctica, and all those involved
in GMOstral 1028 (IPEV) project for field logistics and technical support.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: N. Pirrone<?xmltex \hack{\newline}?>
Reviewed by: T. Dvonch, J. Pacyna, and one anonymous referee</p></ack><ref-list>
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