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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-17-11623-2017</article-id><title-group><article-title>Atmospheric mercury in the Southern Hemisphere tropics: seasonal and diurnal variations and influence of inter-hemispheric transport</article-title>
      </title-group><?xmltex \runningtitle{Atmospheric mercury in the Southern Hemisphere tropics}?><?xmltex \runningauthor{D.~Howard et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Howard</surname><given-names>Dean</given-names></name>
          <email>dean.howard@mq.edu.au</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Nelson</surname><given-names>Peter F.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-6082-937X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Edwards</surname><given-names>Grant C.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-3521-3084</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Morrison</surname><given-names>Anthony L.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2 aff3">
          <name><surname>Fisher</surname><given-names>Jenny A.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2921-1691</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Ward</surname><given-names>Jason</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Harnwell</surname><given-names>James</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>van der Schoot</surname><given-names>Marcel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Atkinson</surname><given-names>Brad</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Chambers</surname><given-names>Scott D.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2521-959X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Griffiths</surname><given-names>Alan D.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-1135-1810</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Werczynski</surname><given-names>Sylvester</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Williams</surname><given-names>Alastair G.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-0568-8487</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Department of Environmental Sciences, Macquarie University, Sydney, New South Wales, 2109, Australia</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Centre for Atmospheric Chemistry, School of Chemistry, University of Wollongong, Wollongong,<?xmltex \hack{\newline}?> New South Wales, 2552, Australia</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>School of Earth &amp; Environmental Sciences, University of Wollongong, Wollongong, New South Wales, 2552, Australia</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Oceans and Atmosphere Flagship, Commonwealth Science and Industrial Research Organisation,<?xmltex \hack{\newline}?> Aspendale, Victoria, 3195, Australia</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Darwin Research Station, Bureau of Meteorology, Darwin, Northern Territory, 0810, Australia</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Institute for Environmental Research, Australian Nuclear Science and Technology Organisation,<?xmltex \hack{\newline}?> Sydney, New South Wales, 2232, Australia</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Dean Howard (dean.howard@mq.edu.au)</corresp></author-notes><pub-date><day>28</day><month>September</month><year>2017</year></pub-date>
      
      <volume>17</volume>
      <issue>18</issue>
      <fpage>11623</fpage><lpage>11636</lpage>
      <history>
        <date date-type="received"><day>3</day><month>April</month><year>2017</year></date>
           <date date-type="rev-request"><day>21</day><month>April</month><year>2017</year></date>
           <date date-type="rev-recd"><day>29</day><month>July</month><year>2017</year></date>
           <date date-type="accepted"><day>21</day><month>August</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017.html">This article is available from https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017.html</self-uri>
<self-uri xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017.pdf</self-uri>


      <abstract>
    <p>Mercury is a toxic element of serious concern for human and
environmental health. Understanding its natural cycling in the environment is
an important goal towards assessing its impacts and the effectiveness of
mitigation strategies. Due to the unique chemical and physical properties of
mercury, the atmosphere is the dominant transport pathway for this heavy
metal, with the consequence that regions far removed from sources can be
impacted. However, there exists a dearth of long-term monitoring of
atmospheric mercury, particularly in the tropics and Southern Hemisphere.
This paper presents the first 2 years of gaseous elemental mercury (GEM)
measurements taken at the Australian Tropical Atmospheric Research Station
(ATARS) in northern Australia, as part of the Global Mercury Observation
System (GMOS). Annual mean GEM concentrations determined at ATARS
(0.95 <inline-formula><mml:math id="M1" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.12 ng m<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) are consistent with recent observations at
other sites in the Southern Hemisphere. Comparison with GEM data from other
Australian monitoring sites suggests a concentration gradient that decreases
with increasing latitude. Seasonal analysis shows that GEM concentrations at
ATARS are significantly lower in the distinct wet monsoon season than in the
dry season. This result provides insight into alterations of natural mercury
cycling processes as a result of changes in atmospheric humidity,
oceanic/terrestrial fetch, and convective mixing, and invites future
investigation using wet mercury deposition measurements. Due to its location
relative to the atmospheric equator, ATARS intermittently samples air
originating from the Northern Hemisphere, allowing an opportunity to gain
greater understanding of inter-hemispheric transport of mercury and other
atmospheric species. Diurnal cycles of GEM at ATARS show distinct nocturnal
depletion events that are attributed to dry deposition under stable boundary
layer conditions. These cycles provide strong further evidence supportive of
a “multi-hop” model of GEM cycling, characterised by multiple surface
depositions and re-emissions, in addition to long-range transport through the
atmosphere.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Mercury (Hg) is a toxic element that has natural and anthropogenic sources,
sinks, and cycles within the environment. Human activities such as gold mining
and biomass/fossil fuel combustion have perturbed the natural cycling of
mercury through the addition of mercury emissions, which are re-deposited
from the atmosphere to land, vegetation, and water bodies. It is estimated
that currently anthropogenic emissions to the atmosphere increase the global
atmospheric mercury pool by 1960 t annually, a value that represents
30 % of estimated mercury emissions, with the remainder emitted from
natural geological sources (10 %) or re-emitted from stores of
previously deposited mercury (60 %). These mercury emission estimates are
subject to large uncertainties <xref ref-type="bibr" rid="bib1.bibx5 bib1.bibx68" id="paren.1"/>. That
anthropogenic mercury sources now exceed those from natural sources on a
global scale is of concern for both human and environmental health. Evidence
suggests these additional sources are leading to increased concentrations of
mercury in the oceans and in marine animals, with the consequence that
bioaccumulation of toxic methylmercury within aquatic food chains has also
increased <xref ref-type="bibr" rid="bib1.bibx43 bib1.bibx68" id="paren.2"/>. There exists a
significant pathway for methylmercury transfer to humans, as it is estimated
that more than 100 Mt of fish are eaten worldwide each year and
fish provide 2.5 billion people with at least 20 % of their
protein intake. Mercury in this latter form can seriously threaten human
health through impacts on the development of foetuses and young children. In
response to this threat, the United Nations Environment Programme (UNEP) has
developed the Minamata Convention on Mercury, which is expected to be
ratified in 2017.</p>
      <p>The global cycling of mercury is unique amongst metals, as within Earth's
atmosphere 90 to 99 % of mercury is found as gaseous elemental mercury
(GEM), with the remaining portion composed of operationally defined gaseous
oxidised mercury (GOM) and particulate-bound mercury (PBM) – collectively
known as reactive mercury (RM) <xref ref-type="bibr" rid="bib1.bibx31" id="paren.3"/>. The low atmospheric
reactivity and low solubility of the elemental form (GEM) results in low
wet/dry deposition rates and scavenging of GEM from the atmosphere. These
attributes result in atmospheric transport being the dominant distribution
mechanism through the environment, with long-range transport possible across
hemispheric scales. Differences in background atmospheric mercury
concentrations between the hemispheres are hence dependent on emission rates,
deposition rates, inter-hemispheric transport processes, and atmospheric
mercury lifetimes. The atmospheric lifetime is defined here as the mean time
after emission that GEM is removed from the atmosphere
<xref ref-type="bibr" rid="bib1.bibx39" id="paren.4"/> and is estimated from mass-balance approaches
utilising hemispheric background concentration and source/sink data
<xref ref-type="bibr" rid="bib1.bibx58" id="paren.5"><named-content content-type="pre">e.g.</named-content></xref>. The atmospheric lifetime of GEM is currently
estimated at 5–12 months
<xref ref-type="bibr" rid="bib1.bibx36 bib1.bibx34 bib1.bibx54 bib1.bibx37" id="paren.6"/>.</p>
      <p>With 68 % of the Earth's landmass and 88 % of the human population in
the Northern Hemisphere (NH), both natural and anthropogenic emissions of mercury
are disproportionately distributed between the hemispheres. Towards the
equator, the existence of the Intertropical Convergence Zone (ITCZ) and the
associated upward/poleward movement of the Hadley circulation leads to
reduced tropospheric mixing across the atmospheric or chemical equator
<xref ref-type="bibr" rid="bib1.bibx10 bib1.bibx32 bib1.bibx35" id="paren.7"/> and hence a broad,
hemispheric gradient of GEM concentrations
<xref ref-type="bibr" rid="bib1.bibx58 bib1.bibx65" id="paren.8"/>. Stationary observations of GEM
within the tropics are rare but those that are available report significant
changes in concentration as source regions shift across hemispheres with the
drift of the atmospheric equator <xref ref-type="bibr" rid="bib1.bibx47 bib1.bibx69" id="paren.9"/>. The
tropics also represent an important region for mercury cycling as they are
home to around 40 % of the world's population, including over 50 % of
people under the age of 15, a group at greater risk of adverse effects due to
mercury exposure during early development <xref ref-type="bibr" rid="bib1.bibx9" id="paren.10"/>.
Furthermore, this region hosts several large coastal communities within
emerging and developing economies, in which environmental controls and
advisories are not always well developed <xref ref-type="bibr" rid="bib1.bibx18" id="paren.11"/>.</p>
      <p>Characterisation of background GEM in the tropics and Southern Hemisphere
(SH) has been hindered by a lack of observations and is based largely on
intermittent ship voyages <xref ref-type="bibr" rid="bib1.bibx61 bib1.bibx62" id="paren.12"/>, along
with a few long-term stationary records in South America, Africa, Antarctica,
and islands in the Indian and eastern Pacific oceans
<xref ref-type="bibr" rid="bib1.bibx57 bib1.bibx47 bib1.bibx69 bib1.bibx3 bib1.bibx4 bib1.bibx59" id="paren.13"/>.
A recent comparison of interannual records from four mercury monitoring
stations spanning a latitude range of 34–72<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, of which the
longest-running spans 7 years, suggests that background GEM concentrations in
the SH are between 0.85 and 1.05 ng m<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
<xref ref-type="bibr" rid="bib1.bibx59" id="paren.14"/>. Previous measurements of atmospheric mercury
concentrations have also been reviewed by
<xref ref-type="bibr" rid="bib1.bibx64 bib1.bibx65" id="text.15"/>. The Australian continent, with
its large non-Antarctic SH landmass (22 %), a
latitudinal distribution (11–44<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) spanning diverse climatic
zones, and a mercury emission profile characterised by anthropogenic sources
that are significantly smaller than natural and re-emitted sources
<xref ref-type="bibr" rid="bib1.bibx50" id="paren.16"/>, presents unique opportunities for extending
environmental mercury monitoring in a region that has largely been
under-represented.</p>
      <p>Initiated under the Global Mercury Observation System (GMOS) and considered
for inclusion with the Asia Pacific Mercury Monitoring Network (APMMN),
measurements of GEM are being undertaken at the Australian Tropical
Atmospheric Research Station (ATARS), northeast of Darwin in Australia's
Northern Territory. Of the six GMOS sites classed as tropical, ATARS is the
southernmost and one of only two (along with Kodaicanal; 10.2314<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
77.4652<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) situated in the Eastern Hemisphere. This site is
therefore important in bridging the spatial gap in GEM measurements in
equatorial regions around the globe. Originally an experimental radar site,
ATARS was expanded in 2010 to incorporate greenhouse gas measurements as part
of the Australian Greenhouse Gas Observation Network <xref ref-type="bibr" rid="bib1.bibx73" id="paren.17"/>
and is operated jointly by the Australian Bureau of Meteorology (BoM) and the
Commonwealth Science and Industrial Research Organisation (CSIRO). The
Australian Nuclear Science and Technology Organisation (ANSTO) began
continuous atmospheric radon measurements at the site in 2012 to aid in the
determination of terrestrial influence on observed air masses
<xref ref-type="bibr" rid="bib1.bibx16" id="paren.18"/>. In June 2014, an additional expansion took place
and now continuous aerosol, reactive gas (O<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, NO<inline-formula><mml:math id="M9" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>), and GEM
measurements complement the suite of atmospheric measurements at the site
<xref ref-type="bibr" rid="bib1.bibx40" id="paren.19"/>. This GEM dataset represents the first multi-year time
series of atmospheric mercury monitoring in tropical Australia.</p>
      <p>We present here the first 2 years of tropical GEM measurements from ATARS,
examine their seasonal and diurnal variations, and evaluate the contribution
of air masses transported from the NH to the observed
concentrations. These results add substantial new information to our
understanding of mercury in the SH and tropical atmosphere.</p>
</sec>
<sec id="Ch1.S2">
  <title>Methods</title>
<sec id="Ch1.S2.SS1">
  <title>Site description</title>
      <p>ATARS is situated on the Gunn Point peninsula (12.2491<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S,
131.0447<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E; Fig. <xref ref-type="fig" rid="Ch1.F1"/>), approximately 20 km northeast
from the suburban edge of Darwin <xref ref-type="bibr" rid="bib1.bibx7" id="paren.20"><named-content content-type="pre">2013 population
136 200;</named-content></xref> in Australia's Northern Territory. Between 2 and
9 km to the north and west of ATARS lies the edge of the peninsula that
gives way to the Tiwi Islands and Timor Sea, whilst the land to the east and
south is largely uninhabited and includes national parks and conservation
areas.</p>
      <p>The climate in the region is best described as tropical <xref ref-type="bibr" rid="bib1.bibx51" id="paren.21"><named-content content-type="pre">Köppen
category Aw, as reported by</named-content></xref> with mean monthly maximum
temperatures between 30 and 33 <inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C <xref ref-type="bibr" rid="bib1.bibx6" id="paren.22"><named-content content-type="pre">1941 to 2016
means;</named-content></xref> and a distinct monsoon (wet) season that coincides
generally with the austral summer (December–February). The build-up to these
monsoon seasons is characterised by steadily increasing minimum temperatures
(19 <inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C in July to 25 <inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C in December) and associated
increases in relative humidity (daily ranges of 37–60 % in July to
72–83 % in February). Mean annual rainfall is 1728 mm, with an average
of 1604 mm (&gt; 90 %) of this falling in the period
November–April. As the site is located on a peninsula, a sea–land breeze
cycle is often experienced in the dry season, resulting in mostly
southeasterly winds throughout the morning, tending northerly as the sea
breeze circulation sets in from the nearby coast. In the wet season, shifting
synoptic patterns result in an increased frequency of westerly winds.</p>
      <p>The vegetation classification is savannah with coarse grasses and scattered
tree growth immediately surrounding the site. Burning of the grassed areas
occurs frequently, with a fire return interval of 1–2 years. Direct mercury
analysis <xref ref-type="bibr" rid="bib1.bibx23" id="paren.23"><named-content content-type="pre">see</named-content><named-content content-type="post"> for methodology</named-content></xref> of vegetation
within 500 m of the station gave total mercury concentrations of
7.23 <inline-formula><mml:math id="M15" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.37 <inline-formula><mml:math id="M16" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g kg<inline-formula><mml:math id="M17" 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> (<inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">18</mml:mn></mml:mrow></mml:math></inline-formula>) for grass and
21.09 <inline-formula><mml:math id="M19" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.79 <inline-formula><mml:math id="M20" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g kg<inline-formula><mml:math id="M21" 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> (<inline-formula><mml:math id="M22" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">9</mml:mn></mml:mrow></mml:math></inline-formula>) for tree litter.
Sampling of soils in the same locations gave total mercury concentrations of
9.14 <inline-formula><mml:math id="M23" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.58 <inline-formula><mml:math id="M24" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g kg<inline-formula><mml:math id="M25" 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> (<inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">18</mml:mn></mml:mrow></mml:math></inline-formula>) in grassed areas and
26.49 <inline-formula><mml:math id="M27" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.31 <inline-formula><mml:math id="M28" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g kg<inline-formula><mml:math id="M29" 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> (<inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">9</mml:mn></mml:mrow></mml:math></inline-formula>) under forest canopy,
confirming that soils in the area are categorised as background
<xref ref-type="bibr" rid="bib1.bibx30" id="paren.24"><named-content content-type="pre">&gt; 100 <inline-formula><mml:math id="M31" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g kg<inline-formula><mml:math id="M32" 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>;</named-content></xref>.
Sampling was undertaken in the early dry season, approximately 10–12 months
after the last grass fire.</p>
      <p>Anthropogenic emissions of mercury and its compounds to the atmosphere in and
around Darwin are generally quite low. Australian National Pollutant
Inventory (NPI) data for 2014–2015 state that six sites situated between 20
and 40 km from ATARS in the direction of Darwin (wind directions 190 to
240<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) emitted a total of 0.12 kg Hg to the atmosphere
<xref ref-type="bibr" rid="bib1.bibx8" id="paren.25"/>. Other distributed anthropogenic mercury emissions in Darwin
are estimated at less than 0.2 kg a<inline-formula><mml:math id="M34" 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>, based on
25 km <inline-formula><mml:math id="M35" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 25 km gridded population data <xref ref-type="bibr" rid="bib1.bibx50" id="paren.26"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p>Map of region surrounding ATARS. Composed in QGIS using Natural
Earth dataset.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f01.jpg"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS2">
  <title>Measurements</title>
      <p>Continuous (5 min sample) GEM measurements were obtained using a Tekran
2537X Automated Ambient Air Analyser (2537X). This instrument is housed in an
air-conditioned structure with internal temperature set at 25 <inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C.
Air is sampled from a 10 m high tower through 7.95 mm I.D. perfluoroalkoxy
tubing using a Thomas 2688 vacuum pump drawing approximately
50 L min<inline-formula><mml:math id="M37" 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> (residence time 0.6 s). The 2537X subsamples from this
flow at 1 L min<inline-formula><mml:math id="M38" 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> through 6 m of heated polytetrafluoroethylene
(PTFE) line maintained at 50 <inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, and two 0.2 <inline-formula><mml:math id="M40" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m PTFE
filters positioned before and after the heated line. The 2537X operates on
the principle of cold vapour atomic fluorescence spectroscopy (CVAFS)
following gold amalgamation pre-concentration <xref ref-type="bibr" rid="bib1.bibx22 bib1.bibx48" id="paren.27"><named-content content-type="pre">see for
example</named-content></xref>. This technique quantifies total
gaseous mercury (TGM <inline-formula><mml:math id="M41" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> GEM <inline-formula><mml:math id="M42" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> GOM); however, experience from other
researchers suggests that the fraction of GOM in the atmosphere is generally
small and removed upstream of the 2537X. As such we present the results here
as GEM and not TGM, in line with reporting standards employed by other GMOS
secondary sites <xref ref-type="bibr" rid="bib1.bibx65" id="paren.28"/>. Reference volumes are reported at
1 atm and 0 <inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C.</p>
      <p>Quality assurance and quality control procedures were applied as per
protocols derived for GMOS sites <xref ref-type="bibr" rid="bib1.bibx65" id="paren.29"/>. Calibration of
the 2537X took place every 23 h using an internal mercury permeation source
maintained at 50 <inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. Primary calibration of this source took place
twice each year using manual injections of mercury vapour. No change in the
internal source permeation rate was detected over this period. Furthermore,
standard additions of mercury are automatically introduced to the 2537X from
the internal permeation source every 35 samples (<inline-formula><mml:math id="M45" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 3 h) in order to
verify GEM recovery performance.</p>
      <p>Continuous hourly measurements of radon were sampled at 12 m using an
ANSTO-designed and built, 700 L dual-flow-loop two-filter radon detector
<xref ref-type="bibr" rid="bib1.bibx70 bib1.bibx14" id="paren.30"/>. This detector samples at
40 L min<inline-formula><mml:math id="M46" 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> through 25 mm high-density polyethylene agricultural pipe
and has a lower limit of detection of 40–50 mBq m<inline-formula><mml:math id="M47" 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>. Calibrations are
performed monthly by injecting radon from a
101.15 <inline-formula><mml:math id="M48" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4 % kBq <inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">226</mml:mn></mml:msup></mml:math></inline-formula>Ra source (delivering
12.745 Bq <inline-formula><mml:math id="M50" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">222</mml:mn></mml:msup></mml:math></inline-formula>Rn min<inline-formula><mml:math id="M51" 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>), traceable to NIST standards. Instrumental
background is checked every 3 months. Radon measurements were corrected for
the response time of the instrument <xref ref-type="bibr" rid="bib1.bibx29" id="paren.31"/>, although the
main trends were not affected by this time correction. Time-corrected radon
data were then split into “fetch” and “diurnal” components by
interpolating between minimum afternoon (12:00 to 17:00) values when
atmospheric mixing is greatest and subtracting these interpolated values
(fetch component) from the original signal, leaving the diurnal component
<xref ref-type="bibr" rid="bib1.bibx15" id="paren.32"><named-content content-type="pre">see</named-content><named-content content-type="post">for details</named-content></xref>.</p>
      <p>Meteorological measurements are collected at ATARS using a standard automated
weather station (AWS) operated by the Australian Bureau of Meteorology.
Precipitation data were collected using a 203 mm tipping bucket rain gauge
and daily totals were summed to give cumulative season totals centred around
a hydrologic year beginning 1 June. The temporal extents of what we define
here as “wet seasons” were then determined using the method of
<xref ref-type="bibr" rid="bib1.bibx60" id="text.33"/>, whereby 15 and 85 % of the total cumulative
rainfall marked their onset and conclusion, respectively. The wet season of
2014–2015 was further extended to include two &gt; 100 mm rain events that took place in November and March.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T1" orientation="landscape"><caption><p>Annual, seasonal, and monthly mean, standard deviation, and count for
5 min GEM samples between June 2014 and June 2016. Wet-season values
calculated from hydrological years beginning in reported year.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="17">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:colspec colnum="10" colname="col10" align="right"/>
     <oasis:colspec colnum="11" colname="col11" align="right"/>
     <oasis:colspec colnum="12" colname="col12" align="right"/>
     <oasis:colspec colnum="13" colname="col13" align="right"/>
     <oasis:colspec colnum="14" colname="col14" align="right"/>
     <oasis:colspec colnum="15" colname="col15" align="right"/>
     <oasis:colspec colnum="16" colname="col16" align="right"/>
     <oasis:colspec colnum="17" colname="col17" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3">Year</oasis:entry>  
         <oasis:entry colname="col4">Dry</oasis:entry>  
         <oasis:entry colname="col5">Wet</oasis:entry>  
         <oasis:entry colname="col6">Jan</oasis:entry>  
         <oasis:entry colname="col7">Feb</oasis:entry>  
         <oasis:entry colname="col8">Mar</oasis:entry>  
         <oasis:entry colname="col9">Apr</oasis:entry>  
         <oasis:entry colname="col10">May</oasis:entry>  
         <oasis:entry colname="col11">Jun</oasis:entry>  
         <oasis:entry colname="col12">Jul</oasis:entry>  
         <oasis:entry colname="col13">Aug</oasis:entry>  
         <oasis:entry colname="col14">Sep</oasis:entry>  
         <oasis:entry colname="col15">Oct</oasis:entry>  
         <oasis:entry colname="col16">Nov</oasis:entry>  
         <oasis:entry colname="col17">Dec</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">2014</oasis:entry>  
         <oasis:entry colname="col2">Mean</oasis:entry>  
         <oasis:entry colname="col3">1.02</oasis:entry>  
         <oasis:entry colname="col4">1.04</oasis:entry>  
         <oasis:entry colname="col5">0.90</oasis:entry>  
         <oasis:entry colname="col6">–</oasis:entry>  
         <oasis:entry colname="col7">–</oasis:entry>  
         <oasis:entry colname="col8">–</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">0.99</oasis:entry>  
         <oasis:entry colname="col12">1.02</oasis:entry>  
         <oasis:entry colname="col13">1.08</oasis:entry>  
         <oasis:entry colname="col14">1.08</oasis:entry>  
         <oasis:entry colname="col15">1.03</oasis:entry>  
         <oasis:entry colname="col16">0.95</oasis:entry>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">SD</oasis:entry>  
         <oasis:entry colname="col3">0.10</oasis:entry>  
         <oasis:entry colname="col4">0.10</oasis:entry>  
         <oasis:entry colname="col5">0.12</oasis:entry>  
         <oasis:entry colname="col6">–</oasis:entry>  
         <oasis:entry colname="col7">–</oasis:entry>  
         <oasis:entry colname="col8">–</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">0.07</oasis:entry>  
         <oasis:entry colname="col12">0.09</oasis:entry>  
         <oasis:entry colname="col13">0.10</oasis:entry>  
         <oasis:entry colname="col14">0.16</oasis:entry>  
         <oasis:entry colname="col15">0.13</oasis:entry>  
         <oasis:entry colname="col16">0.07</oasis:entry>  
         <oasis:entry colname="col17">0.08</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Count</oasis:entry>  
         <oasis:entry colname="col3">34 734</oasis:entry>  
         <oasis:entry colname="col4">25 060</oasis:entry>  
         <oasis:entry colname="col5">24 707</oasis:entry>  
         <oasis:entry colname="col6">–</oasis:entry>  
         <oasis:entry colname="col7">–</oasis:entry>  
         <oasis:entry colname="col8">–</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">2265</oasis:entry>  
         <oasis:entry colname="col12">8421</oasis:entry>  
         <oasis:entry colname="col13">1413</oasis:entry>  
         <oasis:entry colname="col14">2592</oasis:entry>  
         <oasis:entry colname="col15">3845</oasis:entry>  
         <oasis:entry colname="col16">8238</oasis:entry>  
         <oasis:entry colname="col17">7960</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">2015</oasis:entry>  
         <oasis:entry colname="col2">Mean</oasis:entry>  
         <oasis:entry colname="col3">0.93</oasis:entry>  
         <oasis:entry colname="col4">0.94</oasis:entry>  
         <oasis:entry colname="col5">0.93</oasis:entry>  
         <oasis:entry colname="col6">0.92</oasis:entry>  
         <oasis:entry colname="col7">0.79</oasis:entry>  
         <oasis:entry colname="col8">0.76</oasis:entry>  
         <oasis:entry colname="col9">0.82</oasis:entry>  
         <oasis:entry colname="col10">0.89</oasis:entry>  
         <oasis:entry colname="col11">0.95</oasis:entry>  
         <oasis:entry colname="col12">0.96</oasis:entry>  
         <oasis:entry colname="col13">1.00</oasis:entry>  
         <oasis:entry colname="col14">0.99</oasis:entry>  
         <oasis:entry colname="col15">1.01</oasis:entry>  
         <oasis:entry colname="col16">0.99</oasis:entry>  
         <oasis:entry colname="col17">0.96</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">SD</oasis:entry>  
         <oasis:entry colname="col3">0.12</oasis:entry>  
         <oasis:entry colname="col4">0.12</oasis:entry>  
         <oasis:entry colname="col5">0.11</oasis:entry>  
         <oasis:entry colname="col6">0.10</oasis:entry>  
         <oasis:entry colname="col7">0.11</oasis:entry>  
         <oasis:entry colname="col8">0.07</oasis:entry>  
         <oasis:entry colname="col9">0.15</oasis:entry>  
         <oasis:entry colname="col10">0.11</oasis:entry>  
         <oasis:entry colname="col11">0.08</oasis:entry>  
         <oasis:entry colname="col12">0.09</oasis:entry>  
         <oasis:entry colname="col13">0.09</oasis:entry>  
         <oasis:entry colname="col14">0.07</oasis:entry>  
         <oasis:entry colname="col15">0.06</oasis:entry>  
         <oasis:entry colname="col16">0.15</oasis:entry>  
         <oasis:entry colname="col17">0.09</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Count</oasis:entry>  
         <oasis:entry colname="col3">72 060</oasis:entry>  
         <oasis:entry colname="col4">54 071</oasis:entry>  
         <oasis:entry colname="col5">23 649</oasis:entry>  
         <oasis:entry colname="col6">8184</oasis:entry>  
         <oasis:entry colname="col7">4830</oasis:entry>  
         <oasis:entry colname="col8">2447</oasis:entry>  
         <oasis:entry colname="col9">5551</oasis:entry>  
         <oasis:entry colname="col10">8848</oasis:entry>  
         <oasis:entry colname="col11">8105</oasis:entry>  
         <oasis:entry colname="col12">6964</oasis:entry>  
         <oasis:entry colname="col13">5613</oasis:entry>  
         <oasis:entry colname="col14">2076</oasis:entry>  
         <oasis:entry colname="col15">5090</oasis:entry>  
         <oasis:entry colname="col16">7636</oasis:entry>  
         <oasis:entry colname="col17">6716</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">2016</oasis:entry>  
         <oasis:entry colname="col2">Mean</oasis:entry>  
         <oasis:entry colname="col3">0.92</oasis:entry>  
         <oasis:entry colname="col4">–</oasis:entry>  
         <oasis:entry colname="col5">–</oasis:entry>  
         <oasis:entry colname="col6">0.94</oasis:entry>  
         <oasis:entry colname="col7">0.91</oasis:entry>  
         <oasis:entry colname="col8">0.88</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">–</oasis:entry>  
         <oasis:entry colname="col12">–</oasis:entry>  
         <oasis:entry colname="col13">–</oasis:entry>  
         <oasis:entry colname="col14">–</oasis:entry>  
         <oasis:entry colname="col15">–</oasis:entry>  
         <oasis:entry colname="col16">–</oasis:entry>  
         <oasis:entry colname="col17">–</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">SD</oasis:entry>  
         <oasis:entry colname="col3">0.11</oasis:entry>  
         <oasis:entry colname="col4">–</oasis:entry>  
         <oasis:entry colname="col5">–</oasis:entry>  
         <oasis:entry colname="col6">0.11</oasis:entry>  
         <oasis:entry colname="col7">0.12</oasis:entry>  
         <oasis:entry colname="col8">0.08</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">–</oasis:entry>  
         <oasis:entry colname="col12">–</oasis:entry>  
         <oasis:entry colname="col13">–</oasis:entry>  
         <oasis:entry colname="col14">–</oasis:entry>  
         <oasis:entry colname="col15">–</oasis:entry>  
         <oasis:entry colname="col16">–</oasis:entry>  
         <oasis:entry colname="col17">–</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Count</oasis:entry>  
         <oasis:entry colname="col3">21 576</oasis:entry>  
         <oasis:entry colname="col4">–</oasis:entry>  
         <oasis:entry colname="col5">–</oasis:entry>  
         <oasis:entry colname="col6">8438</oasis:entry>  
         <oasis:entry colname="col7">7631</oasis:entry>  
         <oasis:entry colname="col8">5507</oasis:entry>  
         <oasis:entry colname="col9">–</oasis:entry>  
         <oasis:entry colname="col10">–</oasis:entry>  
         <oasis:entry colname="col11">–</oasis:entry>  
         <oasis:entry colname="col12">–</oasis:entry>  
         <oasis:entry colname="col13">–</oasis:entry>  
         <oasis:entry colname="col14">–</oasis:entry>  
         <oasis:entry colname="col15">–</oasis:entry>  
         <oasis:entry colname="col16">–</oasis:entry>  
         <oasis:entry colname="col17">–</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S2.SS3">
  <title>Modelling</title>
      <p>As the atmospheric equator changes its position relative to the geographic
equator, we employed a system of passive tracers within the GEOS-Chem
chemical transport model to help assess the impact of air originating from
the NH on the site, based on the work of
<xref ref-type="bibr" rid="bib1.bibx35" id="text.34"/>. We use GEOS-Chem v10-01 driven by assimilated
meteorology from the NASA Goddard Earth Observing System Forward Processing
(GEOS-FP) data product, run at 2<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M53" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 2.5<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> horizontal
resolution and 47 vertical levels from the surface to 0.01 hPa. Tracers with
90-day lifetimes were uniformly released from the surface in all model boxes
poleward of 45<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude within each hemisphere. The atmospheric
equator is then defined as the point where mixing ratios of tracers from the
two hemispheres are equal. Tracer concentrations in surface air over ATARS
were saved as daily mean values in the model grid box containing the site
(2<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude by 2.5<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> longitude and an approximate atmospheric
depth of 130 m). Increasing the number of grid squares over which tracer
values were averaged did not significantly affect the results.</p>
      <p>The NOAA Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT)
model <xref ref-type="bibr" rid="bib1.bibx20 bib1.bibx21 bib1.bibx67" id="paren.35"/> was also employed to
assess influences of air mass source regions. Global Data Assimilation System
(GDAS) 0.5<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> meteorological reanalysis data were used to drive the
model, and trajectories were initialised at 0.5 times the mixed layer height
as determined by HYSPLIT. To reduce the influence of local daily variation in
GEM concentrations on this analysis, back trajectories were calculated for
each hour of the day rather than as a daily or part-daily mean. For each
trajectory, air parcel coordinates were calculated every 2 h and
weighted per the corresponding GEM concentration. These weighted values were
then averaged over 0.5<inline-formula><mml:math id="M59" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M60" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid cells.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <title>Overall means and seasonal trends</title>
      <p>Measurements of GEM at ATARS began on 5 June 2014 and were still ongoing at
the time of writing. Instrument maintenance/downtime plus application of QC
protocols, including calibration and standard additions, resulted in
68.1 % temporal measurement coverage during the first 2 years of
operation (Fig. <xref ref-type="fig" rid="Ch1.F2"/>, Table <xref ref-type="table" rid="Ch1.T1"/>).
Concentrations are normally distributed across this period with an overall
mean of 0.95 <inline-formula><mml:math id="M62" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.12 ng m<inline-formula><mml:math id="M63" 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> (<inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 130 312), which is within the
range of long-term background GEM concentrations for the SH
as reported by <xref ref-type="bibr" rid="bib1.bibx59" id="text.36"/>. Mean GEM concentrations reported by
<xref ref-type="bibr" rid="bib1.bibx59" id="text.37"/> over 2012–2013 at Cape Grim, Tasmania
(40.6832<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, 144.6899<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E), and by <xref ref-type="bibr" rid="bib1.bibx46" id="text.38"/>
over 2014–2015 at Singleton, NSW (32.4777<inline-formula><mml:math id="M67" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S,
151.1018<inline-formula><mml:math id="M68" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E),
were both 0.86 ng m<inline-formula><mml:math id="M69" 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> (9 % lower), suggesting a slight latitudinal
gradient in GEM across the Australian continent. These differences are
statistically significant (Student's <inline-formula><mml:math id="M70" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test, <inline-formula><mml:math id="M71" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> <inline-formula><mml:math id="M72" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.0001), though
differences in the sampling periods introduces additional uncertainty due to
seasonal variation at the sites. Further, an analysis of systematic
instrument uncertainty for the Tekran 2537 by <xref ref-type="bibr" rid="bib1.bibx59" id="text.39"/> showed
this to be <inline-formula><mml:math id="M73" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 10 %. A latitudinal gradient within the SH was more generally seen in median annual GEM concentrations for
GMOS sites in 2013–2014, based on data from five sites <xref ref-type="bibr" rid="bib1.bibx65" id="paren.40"/>.
GEM measurements at ATARS were coincident with those reported by
<xref ref-type="bibr" rid="bib1.bibx65" id="text.41"/> for only the latter 6 months of 2014, a period
spanning the late dry season and early wet season. Concentrations during this
period were 1.02 <inline-formula><mml:math id="M74" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.10 ng m<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
– higher than the overall mean at ATARS, though still lower than mean
values reported for other tropical GMOS sites.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p><bold>(a)</bold> 5 min GEM data, daily rainfall, and daily min/max
relative humidity values plus wet-season ranges as defined by
<xref ref-type="bibr" rid="bib1.bibx60" id="text.42"/>. <bold>(b)</bold> 5 min GEM, hourly fetch-component radon
and daily NH tracers. Days defined as NH-influenced are marked with
diamonds.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f02.png"/>

        </fig>

      <p>A seasonal trend is apparent in the GEM time series
(Fig. <xref ref-type="fig" rid="Ch1.F2"/>), which shows higher concentrations during the dry
season compared to the wet. Wind sector analysis also shows distinctly
different wind patterns between wet and dry seasons (Fig. <xref ref-type="fig" rid="Ch1.F3"/>).
During the wet season, <inline-formula><mml:math id="M76" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 60 % of winds come to the site from a
westerly direction, consistent with shifting of the ITCZ and associated low-pressure systems towards northern Australia. In the dry season,
southeasterly to northeasterly winds are more common (<inline-formula><mml:math id="M77" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 65 %
between 30 and 150<inline-formula><mml:math id="M78" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>), although there is also a notable westerly
element. Concentration distributions vary between seasons, with a larger
fraction of values above 1 ng m<inline-formula><mml:math id="M79" 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> seen in the dry period. Within each
season, however, these distributions do not change significantly with wind
direction. Furthermore, the small percentage of winds arriving from the
southwest show no change in GEM distribution, implying that the low mercury
emissions from Darwin are not significantly impacting measurements and that
overall trends are indicative of influences from the global atmospheric
mercury pool rather than local sources.</p>
      <p>Figure <xref ref-type="fig" rid="Ch1.F2"/> shows that the highest GEM values are concentrated
into short peaks, clustered more heavily around the mid- to late dry season.
In the absence of local anthropogenic sources, this is considered consistent
with biomass-burning events and the associated release of mercury from
volatilisation and thermal desorption from vegetation and soils
<xref ref-type="bibr" rid="bib1.bibx44" id="paren.43"/>. These biomass-burning events occur extensively
in northern Australia throughout the dry season as the result of natural and
accidental lighting, as well as part of local land management practices
<xref ref-type="bibr" rid="bib1.bibx53" id="paren.44"/>. <xref ref-type="bibr" rid="bib1.bibx49" id="text.45"/> concluded that burning in
the northernmost part of Australia can contribute up to around
2 kg Hg km<inline-formula><mml:math id="M80" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> a<inline-formula><mml:math id="M81" 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> to the atmosphere (2006 data,
25 km <inline-formula><mml:math id="M82" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 25 km grid resolution).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Directional GEM concentration distributions for <bold>(a)</bold> dry season
and <bold>(b)</bold> all wet-season half-hourly GEM data.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f03.png"/>

        </fig>

      <p>An intensive study of these biomass-burning events undertaken at ATARS during
the early dry season in 2014 also confirmed spikes in GEM concentration that
were associated with biomass burning
<xref ref-type="bibr" rid="bib1.bibx40 bib1.bibx19" id="paren.46"/>. The distance to the fire and
atmospheric dispersion, as well as vegetation type and associated mercury
loading, were all identified as factors influencing the strength of these
biomass-burning signals. <xref ref-type="bibr" rid="bib1.bibx19" id="text.47"/> calculated emission
factors for GEM between 0.0035 and 0.032 g Hg per kg dry fuel, around 2
orders of magnitude higher than that reported by <xref ref-type="bibr" rid="bib1.bibx2" id="text.48"><named-content content-type="post">and references
within</named-content></xref> for savannah grasslands. The fires observed by
<xref ref-type="bibr" rid="bib1.bibx19" id="text.49"/> were shown to be from scrubland fires
rather than grassland fires, excluding the possibility of direct comparison
between the two results. With a full suite of greenhouse gas and aerosol
measurements taking place at ATARS, further identification of smoke plumes
and precise calculation of emission factors is possible in a manner that is
comparable with previous studies.</p>
      <p>Wet-season GEM concentrations in 2014–2015 were characterised by a steady,
gradual decrease that reversed abruptly in early April shortly after the
onset of the dry season (Fig. <xref ref-type="fig" rid="Ch1.F2"/>). GEM concentrations during
the 2015–2016 wet season saw a similar, though much less distinct decrease
over a shorter and drier season. Figure <xref ref-type="fig" rid="Ch1.F2"/> also shows that
fetch-component radon concentrations begin to drop in both years around
September–October, which HYSPLIT trajectories show is coincident with air
mass origin shifting away from the Australian continent and towards the
northern Arafura and Timor seas. Throughout the wet season fetch-component
radon remains low, though not at baseline levels
<xref ref-type="bibr" rid="bib1.bibx72 bib1.bibx16" id="paren.50"/>, implying that there is still
some terrestrial influence on incoming air masses from the Australian
continent or surrounding islands to the north. Wet-season wind data
(Fig. <xref ref-type="fig" rid="Ch1.F3"/>) confirm that the predominant fetch during this period
is from the west, where the Timor Sea lies less than 2 km from ATARS. Air–sea
exchange of mercury is complex, with the ocean generally considered a net
sink for atmospheric mercury <xref ref-type="bibr" rid="bib1.bibx42 bib1.bibx63" id="paren.51"/>. Reduction of
mercury within the photolytic zone can give rise to increased concentrations
of elemental mercury and hence evasion of GEM to the atmosphere
<xref ref-type="bibr" rid="bib1.bibx62" id="paren.52"/>. Terrestrial surfaces are also commonly sources of
GEM; <xref ref-type="bibr" rid="bib1.bibx50" id="text.53"/> modelled terrestrial mercury emission fluxes over
Australia that were generally between 8 and
44 <inline-formula><mml:math id="M83" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g m<inline-formula><mml:math id="M84" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> a<inline-formula><mml:math id="M85" 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> from soil and vegetation.
Figure <xref ref-type="fig" rid="Ch1.F3"/> does not show a strong difference in concentration
distributions between the two source regions.</p>
      <p>The increase in GEM concentrations in the early 2015 dry season was
coincident with a shift to largely terrestrial-influenced fetch, as evidenced
by a coincident increase in fetch-component radon, as well as with the
conclusion of the monsoon season. The timing offset between decreases in GEM
and fetch-component radon in the early wet and late dry seasons suggests that
air mass origin is not the only influence on wet-season GEM decreases. Within
tropical regions, wet deposition has been shown to be a significant pathway
for mercury from the atmosphere to both oceanic and terrestrial ecosystems,
even in relatively low-mercury air and despite the low solubility of mercury
in its elemental form <xref ref-type="bibr" rid="bib1.bibx25 bib1.bibx18 bib1.bibx33 bib1.bibx62 bib1.bibx55" id="paren.54"/>. Mercury “rainout” – or the tendency
for mercury rainwater loading to decrease with increasing precipitation –
has also been demonstrated in Mercury Deposition Network (MDN) data in North
America <xref ref-type="bibr" rid="bib1.bibx27 bib1.bibx52" id="paren.55"/> and positive correlations
between GEM (TGM) and rainwater mercury have been reported in MDN data
<xref ref-type="bibr" rid="bib1.bibx17" id="paren.56"><named-content content-type="pre">GEM;</named-content></xref> and at Cape Point, South Africa
<xref ref-type="bibr" rid="bib1.bibx13" id="paren.57"><named-content content-type="pre">TGM;</named-content></xref>. Re-emission of any deposited mercury is
likely to be inhibited throughout the wet season, as it has been shown that
GEM emission from background mercury soils is suppressed when the soils are
saturated <xref ref-type="bibr" rid="bib1.bibx11" id="paren.58"/>. Mercury wet deposition is currently not
being measured at ATARS; however, given the large differences in GEM trends
between the wet and dry seasons, these measurements could help to highlight
differing processes between these periods.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p>Diurnal composites of hourly radon (<bold>a, b</bold>), GEM
(<bold>c, d</bold>), and wind direction (<bold>e, f</bold>) for (left) dry-season data
and (right) all wet-season data. Edges of shading denote median
sunset/sunrise times for each season. Data have been split into stability
categories based on diurnal-component radon quartiles at sunrise (marked in
top panels). Lines are median values, and error bars indicate inter-quartile
ranges.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f04.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS2">
  <title>Diurnal variation</title>
      <p>Short, significant troughs in GEM values can be seen in
Fig. <xref ref-type="fig" rid="Ch1.F2"/>, down to a minimum value of 0.28 ng m<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>.
These are more pronounced in the dry season, though still common during the
wet. GEM recoveries from standard additions during these periods were
investigated and remained within 10 % of expected values with no evident
pattern throughout the day, implying the drops in observed GEM were due to
natural phenomena and not a change in instrument GEM recovery. Atmospheric
mercury depletion events (AMDEs) and the mechanisms behind them have been
well documented in polar regions <xref ref-type="bibr" rid="bib1.bibx66" id="paren.59"/>, though other
similar events have been observed within the mid-latitudes
<xref ref-type="bibr" rid="bib1.bibx41 bib1.bibx12 bib1.bibx24 bib1.bibx45 bib1.bibx46 bib1.bibx26 bib1.bibx38" id="paren.60"/>.
The mechanisms behind these mid-latitude depletion events are less clear and
likely varied – with hypotheses such as chemical conversion of GEM to RM and
subsequent deposition, transport of GEM-depleted air masses, or deposition of
GEM from isolated atmospheric pools being offered. Closer inspection of the
dips in GEM observed at ATARS reveals that they occur overnight and are
particularly pronounced in the early hours of the morning, with a marked
rebound following sunrise.</p>
      <p>The pattern of overnight GEM depletion is shown in diurnal composite data in
Fig. <xref ref-type="fig" rid="Ch1.F4"/>, along with diurnal-component radon and wind
direction. Days have been defined from midday to midday, then sorted into
groups according to quartiles of the diurnal-component radon value at sunrise
(marked in the top figures). As radon fluxes are, across daily timescales,
constant to first-order approximation, nocturnal build-up of radon is
indicative of atmospheric stability, with highest radon values indicating the
most stable atmospheres. This follows the radon-based stability
categorisation method described by <xref ref-type="bibr" rid="bib1.bibx15" id="text.61"/> and
<xref ref-type="bibr" rid="bib1.bibx71" id="text.62"/>. In the dry season (left), it can clearly be seen
that the magnitude of nocturnal GEM depletion increases with increasing
stability and, conversely, little to no depletion occurs under well-mixed
boundary layers. Wind directions for the well-mixed category shift from
coastal (westerly) in the early evening to terrestrial during the night. In
contrast, wind directions for moderately mixed to stable boundary layer
categories are very similar to each other, shifting from a northeasterly to
southeasterly direction shortly after sunset. Terrestrial fetches encompass
this range of directions and the abrupt shift in wind direction at around
20:00 has little impact on the rates of GEM depletion or radon accumulation
under these stability categories. This shows that changes in advection of GEM
from local source/sink regions are not responsible for observed depletion.</p>
      <p>Wet-season diurnal-component radon values (right) are lower than in the dry
season, which fits with wind profile and fetch-component radon data showing
greater influence of oceanic fetch. Additionally, during the wet season rates
of radon emission may be reduced in saturated soils, as reduction of pore
space inhibits upward mobility to the point where radon within the soil will
undergo radioactive decay before reaching the surface
<xref ref-type="bibr" rid="bib1.bibx28" id="paren.63"/>. During the wet season, well-mixed and
moderately mixed categories are more indicative of the influence of ocean
fetch than stability, as evidenced by wind directions of
273 <inline-formula><mml:math id="M87" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8<inline-formula><mml:math id="M88" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> for these two categories. For weakly mixed and stable
categories, wind direction shifts southerly and easterly throughout the
evening, from an oceanic fetch to a terrestrial fetch. It is not until this
shift in wind direction occurs that GEM depletion is observed, at a similar
rate to that seen in the dry season under moderately mixed to stable
categories.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><caption><p>Normalised frequency for all 5 min GEM data, split into dry season,
SH wet season, and NH wet season. Vertical lines at bottom of figure indicate
mean values.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f05.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p>10th percentile (left), median (centre), and 90th percentile (right)
of hourly GEM-weighted HYSPLIT trajectories for
0.5<inline-formula><mml:math id="M89" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M90" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math id="M91" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid squares. Panels <bold>(a)</bold>–<bold>(c)</bold>
are for dry-season data, <bold>(d)</bold>–<bold>(f)</bold> for SH wet-season data,
and <bold>(g)</bold>–<bold>(i)</bold> for NH wet-season data. NH wet-season map
created using 10-day back trajectories, all others using 5-day trajectories.</p></caption>
          <?xmltex \igopts{width=312.980315pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/11623/2017/acp-17-11623-2017-f06.png"/>

        </fig>

      <p>We suggest from these observations during the wet and dry seasons that the
observed depletion results from deposition of GEM over terrestrial surfaces.
Under increasingly lower capping inversions associated with more stable
boundary layers, a near-constant rate of surface deposition would result in
greater concentration drops within the boundary layer, consistent with the
observations at ATARS. Turbulent break-up of the nocturnal boundary layer at
sunrise is also consistent with the rebound of GEM concentrations and drop in
diurnal-component radon observed at this time. The rebound of GEM, however,
begins the hour before diurnal-component radon signals the break-up of the
nocturnal boundary layer. In the absence of changes to advection or
entrainment, this suggests emission of GEM from the surface. Furthermore, for
stability categories where GEM depletion has taken place, daytime GEM
concentration peaks at around 10:00 before decreasing to a minimum at around
15:00, where low radon values indicate the strongest turbulent mixing with
free-tropospheric air. This “overshoot” of GEM in the early morning also
cannot be explained by entrainment and, at least in the dry season, by
changes to fetch. Early-morning GEM emission would likely be from the most
readily volatile surface mercury, released under low-light conditions
(shading denotes the period between geometric sunset/sunrise and so
astronomical twilight will begin up to 75 min prior to the shaded edge). We
propose that this initial release of GEM is volatilised from the reduction of
mercury deposited overnight, as it has been shown that the most
recently deposited mercury during AMDEs is preferentially released due to
photochemical reactions <xref ref-type="bibr" rid="bib1.bibx56" id="paren.64"/>.</p>
      <p>Previous studies have shown that surface GEM fluxes over soils with mercury
concentration at background levels are generally bidirectional, with little
controlling influence from soil mercury concentration <xref ref-type="bibr" rid="bib1.bibx1" id="paren.65"><named-content content-type="post">and references
within</named-content></xref>. Correlations with solar radiation and air temperature
tend to lead to emission fluxes throughout the day and deposition or
near-zero flux overnight. <xref ref-type="bibr" rid="bib1.bibx38" id="text.66"/>, whilst undertaking
micrometeorological measurements of surface GEM fluxes over a background
mercury substrate grassland, observed nocturnal atmospheric mercury depletion
events (NAMDEs) similar to the ones seen at ATARS. They attributed these
events to enhanced nocturnal deposition of GEM under shallow, stable boundary
layers. Enhancements in morning GEM emission were seen in days following the
depletion events, similarly providing evidence for volatilisation of
recently deposited mercury. Further, cumulative GEM exchange over the 20-day
study was near zero, highlighting the short-lived nature of this nocturnal
GEM sink. This result, and the radon-based analyses presented earlier,
provides strong evidence for a “multi-hop” process of atmospheric transport.</p>
      <p>NAMDEs have also been observed in the NH, in a range of
ecosystems ranging from coastal to forested
<xref ref-type="bibr" rid="bib1.bibx41 bib1.bibx24 bib1.bibx26" id="paren.67"/>. <xref ref-type="bibr" rid="bib1.bibx41" id="text.68"/> attributed
70 % of their observed depletion to surface deposition and
<xref ref-type="bibr" rid="bib1.bibx26" id="text.69"/> provided modelling evidence showing that stable boundary
layers of height 100 m can be completely depleted of GEM due to deposition
processes. The pervasiveness of NAMDEs across multiple ecosystems, and their
pervasiveness throughout the ATARS time series across all seasons, suggests that
this multi-hop process is widespread. It is important to note that, due to
inhibited mixing at the top of the nocturnal boundary layer, the extent of
any nocturnal depletion is limited to within tens to hundreds of metres above
the surface. Beyond this, movement of free-tropospheric air continues to
enable long-range transport of GEM. Nevertheless, extensive and rapid
bidirectional exchange with the surface would have a significant impact on
our understanding of atmospheric mercury transport, impacting the relative
importance of intermediate and regional-scale sources, as well as expected
timescales for observed decreases in environmental mercury following actions
proposed under the Minamata Convention <xref ref-type="bibr" rid="bib1.bibx39" id="paren.70"/>.</p>
<sec id="Ch1.S3.SS2.SSS1">
  <title>Long-range transport</title>
      <p>With seasonal changes in the latitudinal position of the ITCZ, ATARS is
periodically located north of the atmospheric equator
<xref ref-type="bibr" rid="bib1.bibx32" id="paren.71"/> and so the possibility of interhemispheric transport
to the site was also of interest. Figure <xref ref-type="fig" rid="Ch1.F2"/> shows the
GEOS-Chem output for NH-released tracer concentrations at ATARS. Throughout
most of the year – and consistently through the dry season – this value
remains low, indicating that the site is far enough below the atmospheric
equator to not be affected by transport of NH air. However, there are notable
periods when this tracer value increases, along with coincident GEM
increases. We arbitrarily defined air masses at the site to be significantly
influenced by NH air (herein termed “NH wet season”) when
the ratio of NH tracers to SH tracers was greater than 0.5 (ratio not shown).
Under this definition, ATARS saw 13 NH-influenced days over three distinct
periods, all during the wet season and indicated in the lower panel of
Fig. <xref ref-type="fig" rid="Ch1.F2"/>. Hereafter, wet-season data that exclude these
periods of NH influence are termed “SH wet season”.</p>
      <p>The normalised frequency distribution of NH wet-season GEM data is compared
against those of dry season and SH wet-season data in
Fig. <xref ref-type="fig" rid="Ch1.F5"/>. Mean values for each were
1.08 <inline-formula><mml:math id="M92" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.12 ng m<inline-formula><mml:math id="M93" 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> (<inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">3048</mml:mn></mml:mrow></mml:math></inline-formula>), 0.97 <inline-formula><mml:math id="M95" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.13 ng m<inline-formula><mml:math id="M96" 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>
(<inline-formula><mml:math id="M97" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">81</mml:mn><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">073</mml:mn></mml:mrow></mml:math></inline-formula>), and 0.90 <inline-formula><mml:math id="M98" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.10 ng m<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (<inline-formula><mml:math id="M100" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">46</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">191</mml:mn></mml:mrow></mml:math></inline-formula>),
respectively. The differences between these means were small but significant;
Student's <inline-formula><mml:math id="M101" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> tests showed the minimum differences between the 95 %
confidence interval of each mean to be 0.10 ng m<inline-formula><mml:math id="M102" 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> (NH wet – dry) and
0.07 ng m<inline-formula><mml:math id="M103" 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> (dry – SH wet). Comparison with log-normal probability
density functions for other GMOS sites over the years 2013–2014
<xref ref-type="bibr" rid="bib1.bibx65" id="paren.72"><named-content content-type="pre">Fig. 4;</named-content></xref> shows that GEM data sampled at ATARS are
more closely related to those from other SH sites, rather
than tropical or NH sites. This is likely due to the
location of ATARS within the Maritime Continent – a region of high
variability in the latitudinal position of the ITCZ – and its southerly
latitude that places it outside this range and hence within the atmospheric
SH for most of the year.</p>
      <p>Air mass source transport to ATARS across seasons was further investigated
using 5-day HYSPLIT back trajectories. For NH-influenced air masses, use of
5-day trajectories and the geographic equator was found to be a poor
predictor of NH influence at this site, with only 1.2 % of these
trajectories originating from within the geographical NH. This is likely due
to the significant disconnect between the geographical and meteorological
equators over the Maritime Continent during the wet season. As such, 10-day
back trajectories were calculated for these periods.
Figure <xref ref-type="fig" rid="Ch1.F6"/> shows median, 10th, and 90th percentile
GEM-weighted trajectory coordinates for 0.5<inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M105" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.5<inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
grid cells. During the dry season (top row), the influence of persistent high-pressure cells across the Australian continent can be seen, with most air
parcels flowing over central and northeastern Australia. Changes to air mass
source regions are seen with the southward movement of the ITCZ and
associated low-pressure cells that characterise the SH wet season (centre
row). The differing GEM concentration distributions between the two seasons
outlined earlier are further apparent in these two figures. For NH-influenced
air masses (bottom row), this analysis shows that most air masses –
particularly those with the highest GEM concentrations – passed over the
Indonesian archipelago. North of this, air masses moved over the South China
Sea or western Pacific Ocean, with little influence from terrestrial South
East Asia. Given that Indonesia's population is greater than 250 million and
its biomass-burning season coincides with the Australian monsoon, it is
likely that the observed increases in GEM concentrations in NH-influenced air
masses are more indicative of anthropogenic or biomass GEM source influence
from the Indonesian archipelago than the NH background
source pool. Further investigation using chemical transport and mercury
emission modelling is needed. Regardless, the current analysis shows that
ATARS does observe air masses of NH origin and that
measurements of GEM and other atmospheric species during these periods may
help to assess the effectiveness of transport models investigating
hemispheric air exchange associated with movement of the atmospheric equator.</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Conclusions</title>
      <p>We present here the first 2 years of ongoing
measurements of GEM taken in tropical Australia. Comparison with other
Australian datasets suggests that a latitudinal gradient of GEM exists across
the continent, with higher values towards the equator. Air masses from the
NH were shown to intermittently impact the tropical site
ATARS, with associated increases in GEM. Generally, the concentrations seen
at ATARS were indicative of SH rather than tropical air, as
determined by comparison with other GMOS monitoring stations around the
globe.</p>
      <p>Seasonal variation in GEM was observed, with higher values observed in the
tropical dry season compared to the wet. Spikes in GEM associated with
biomass burning in the region were measured, taking place during the mid- to late dry season. Wet-season GEM showed a decreasing trend throughout
2014–2015; this was apparent though not as pronounced in the drier
2015–2016 season. The cessation of this downward trend coincides with shifts
of air mass source regions from oceanic to terrestrial; however, the reverse
is not the case for the onset of this trend. It is likely that precipitation
rainout or aqueous-phase oxidation of GEM is responsible for this observed
downward trend. Continued monitoring and wet deposition data may help to
explain these seasonal features.</p>
      <p>Daily cycles in GEM were observed at the site, characterised by nocturnal
decreases in concentration followed by rapid increases around sunrise, then
further decreases throughout the day. Differences in these daily trends
between wet and dry seasons, along with associated changes in wind direction
and stability, suggest that these nocturnal atmospheric mercury depletion
events are related to dry deposition of GEM over terrestrial surfaces under
increasingly stable boundary layers. Analyses using diurnal-component radon
suggest the rapid increases around sunrise are partly due to volatilisation
of newly deposited mercury, such as seen in other NAMDEs and in Arctic AMDEs.
The extent of this multi-hop phenomenon may be widespread, which would have a
significant impact on our understanding of atmospheric mercury transport, the
delivery of atmospheric mercury to the environment, and the legacy of
anthropogenic emissions of mercury.</p>
      <p>Currently, multi-annual atmospheric mercury datasets for tropical and SH
sites are rare, impacting the skill of regional and global models designed to
further our understanding of the natural mercury cycle and its potential
impacts on human and environmental health. The value of measurements such as
these is in comparisons with other similar measurements around the globe. As
such, the addition of this site to monitoring networks such as the Global
Mercury Observation System (GMOS) or the Asia Pacific Mercury Monitoring
Network (APMMN) is important in achieving greater understanding of the
mercury cycle, as it is currently only one of two monitoring sites located in
the tropical Eastern Hemisphere.</p>
      <p>Article 19 of the Minamata Convention commits parties to develop and improve
anthropogenic mercury inventories; efforts to monitor mercury and mercury
compounds in environmental media; and modelling of mercury transport
(including long-range transport and deposition), transformation and fate in a
range of ecosystems. ATARS is uniquely positioned to enhance the information
required for these monitoring and modelling activities.</p>
</sec>

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

      <p>GEM data used for this publication are available from the
GMOS data repository (<uri>http://gmos.eu/sdi/</uri>). Weather data are collected
and supplied by the Australian Bureau of Meteorology
(<uri>http://www.bom.gov.au/climate/data-services/</uri>).</p>
  </notes><notes notes-type="competinginterests">

      <p>The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p>The authors would like to thank Mark Cohen for his assistance with HYSPLIT
modelling and  Chris Holmes for supplying code and assistance for
GEOS-Chem tracer modelling. This research was undertaken with the assistance
of resources provided at the NCI National Facility systems at the Australian
National University through the National Computational Merit Allocation
Scheme supported by the Australian Government. <?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by: Aurélien Dommergue<?xmltex \hack{\newline}?> Reviewed by:
two anonymous referees</p></ack><ref-list>
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    <!--<article-title-html>Atmospheric mercury in the Southern Hemisphere tropics: seasonal and diurnal variations and influence of inter-hemispheric transport</article-title-html>
<abstract-html><p class="p">Mercury is a toxic element of serious concern for human and
environmental health. Understanding its natural cycling in the environment is
an important goal towards assessing its impacts and the effectiveness of
mitigation strategies. Due to the unique chemical and physical properties of
mercury, the atmosphere is the dominant transport pathway for this heavy
metal, with the consequence that regions far removed from sources can be
impacted. However, there exists a dearth of long-term monitoring of
atmospheric mercury, particularly in the tropics and Southern Hemisphere.
This paper presents the first 2 years of gaseous elemental mercury (GEM)
measurements taken at the Australian Tropical Atmospheric Research Station
(ATARS) in northern Australia, as part of the Global Mercury Observation
System (GMOS). Annual mean GEM concentrations determined at ATARS
(0.95 ± 0.12 ng m<sup>−3</sup>) are consistent with recent observations at
other sites in the Southern Hemisphere. Comparison with GEM data from other
Australian monitoring sites suggests a concentration gradient that decreases
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