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<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">OS</journal-id><journal-title-group>
    <journal-title>Ocean Science</journal-title>
    <abbrev-journal-title abbrev-type="publisher">OS</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Ocean Sci.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1812-0792</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/os-16-729-2020</article-id><title-group><article-title>Biogeochemical processes accounting for the natural mercury variations in the Southern Ocean diatom ooze sediments</article-title><alt-title>Biogeochemical processes accounting for the natural mercury variations</alt-title>
      </title-group><?xmltex \runningtitle{Biogeochemical processes accounting for the natural mercury variations}?><?xmltex \runningauthor{S. Zaferani and H. Biester}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name><surname>Zaferani</surname><given-names>Sara</given-names></name>
          <email>s.zaferani@tu-braunschweig.de</email>
        <ext-link>https://orcid.org/0000-0002-3248-376X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no">
          <name><surname>Biester</surname><given-names>Harald</given-names></name>
          
        </contrib>
        <aff id="aff1"><institution>Institut für Geoökologie, AG Umweltgeochemie, Technische
Universität Braunschweig, 38106 Braunschweig, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Sara Zaferani (s.zaferani@tu-braunschweig.de)</corresp></author-notes><pub-date><day>19</day><month>June</month><year>2020</year></pub-date>
      
      <volume>16</volume>
      <issue>3</issue>
      <fpage>729</fpage><lpage>741</lpage>
      <history>
        <date date-type="received"><day>22</day><month>December</month><year>2019</year></date>
           <date date-type="rev-request"><day>15</day><month>January</month><year>2020</year></date>
           <date date-type="rev-recd"><day>30</day><month>April</month><year>2020</year></date>
           <date date-type="accepted"><day>9</day><month>May</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 Sara Zaferani</copyright-statement>
        <copyright-year>2020</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020.html">This article is available from https://os.copernicus.org/articles/16/729/2020/os-16-729-2020.html</self-uri><self-uri xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020.pdf">The full text article is available as a PDF file from https://os.copernicus.org/articles/16/729/2020/os-16-729-2020.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e86">Due to its toxic nature and its high potential for
biomagnification, mercury is a pollutant of concern. Understanding the
marine biogeochemical cycle of mercury is crucial as consumption of mercury-enriched marine fish is the most important pathway of human exposure to
monomethylmercury, a neurotoxin. However, due to the lack of long-term
marine records, the role of the oceans in the global mercury cycle is poorly understood. We do not have well-documented data of natural mercury
accumulations during changing environmental conditions, e.g., sea surface
conditions in the ocean. To understand the influence of different sea
surface conditions (climate-induced changes in ice coverage and biological
production) on natural mercury accumulation, we used a continuous
<inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">170</mml:mn></mml:mrow></mml:math></inline-formula> m Holocene biogenic sedimentary record from Adélie
Basin, East Antarctica, which mainly consists of silica-based skeletons of
diatoms. We performed principal component analysis and regression analysis
on element concentrations and corresponding residuals, respectively, to
investigate the link between sediment mercury accumulation, terrestrial
inputs, and phytoplankton productivity. Preindustrial mercury in the remote
marine basin shows extremely high accumulation rates (median:
556 <inline-formula><mml:math id="M2" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M3" 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> yr<inline-formula><mml:math id="M4" 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>) that displayed periodic-like variations. Our analyses
show that the variations in total mercury concentrations and accumulation
rates are associated with biological production and related scavenging of
water-phase mercury by rapidly sinking algae or algae-derived organic matter
after intense algae blooms. High accumulation rates of other major and trace elements further reveal that, in regions of high primary productivity,
settling of biogenic materials removes a large fraction of dissolved or
particulate-bound elements from the free water phase through scavenging or
biological uptake. The link between mercury cycling and primary production
will need to be considered in future studies of the marine mercury cycle
under primary production enhancement through climatic, temperature, and
nutrient availability changes.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e140">Mercury (Hg) is a metal of environmental concern due to its ability to be
transported through the atmosphere from industrial point sources to remote
regions and its transformations into highly bioaccumulative and neurotoxic
methylated forms. In the global biogeochemical cycle of Hg, the ocean, as
the dominant physical feature of our planet Earth, is of specific concern. A
substantial amount of Hg (<inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">80</mml:mn></mml:mrow></mml:math></inline-formula> %) which is emitted to the
atmosphere from natural and anthropogenic sources reaches the ocean
(Horowitz et al., 2017; Schartup et al., 2019), and ocean sediments are
considered to be the ultimate sink of Hg on a timescale of tens of thousands
of years (Fitzgerald et al., 2007; Selin, 2009; Amos et al., 2013). Despite
the important role of marine sedimentation in the global Hg biogeochemical
cycle, little is known about the rates or amount of Hg accumulation in
marine sediments, especially in the open ocean. In contrast to the
well-studied Hg cycling in terrestrial environments, knowledge about the
temporal and spatial distribution of Hg in the marine environment is limited
to model estimations (Mason and Sheu, 2002; Sunderland and Mason, 2007),
water column measurements (Cossa et al., 2011; Lamborg et al., 2014b;
Canário et al., 2017), and very few sediment measurements (Kita et al.,
2013; Aksentov and Sattarova, 2020). A main reason for our limited
understanding of the fate of Hg in the oceans is<?pagebreak page730?> the lack of high-resolution
marine sedimentary records, especially from the deep ocean (Zaferani et al.,
2018).</p>
      <p id="d1e153">Hg input to the ocean is primarily through atmospheric deposition (Mason et
al., 1994; Driscoll et al., 2013). After deposition, as either mercuric ion
(<inline-formula><mml:math id="M6" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) or elemental Hg (<inline-formula><mml:math id="M7" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>), Hg can be reduced to <inline-formula><mml:math id="M8" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> and
evaded to the atmosphere or scavenged from the water column by particulate
matter and eventually buried in deep-sea sediments (Mason et al., 2012;
Lamborg et al., 2014a). Most marine surface waters are believed to be close
to equilibrium between Hg deposition and evasion or saturated in <inline-formula><mml:math id="M9" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>
due to biologically mediated (Mason et al., 1995; Rolfhus and Fitzgerald,
2004; Whalin et al., 2007) and photochemical reduction (Amyot et al., 1997;
Mason et al., 2001) followed by re-emission of <inline-formula><mml:math id="M10" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> to the atmosphere.
It has been estimated that almost 96 % of the deposited Hg to the ocean
is lost through evasion from the surface, and only 30 % of the Hg flux
that reaches the deep ocean is preserved in sediments (Mason and Sheu,
2002). However, other studies indicate that the ocean surface waters become
a sink for atmospheric Hg at the high nutrient levels and related high
primary productivity (Soerensen et al., 2016).</p>
      <p id="d1e214">There are contradictory statements about the Hg deposition and evasion
to/from different surface waters. Early works suggest that Hg evasion is
high in productive upwelling regions of the ocean due to enhanced biological
reduction (Fitzgerald et al., 1984; Mason and Fitzgerald, 1993). More recent
studies, with higher spatial and temporal resolutions, suggest lower Hg
evasion in productive regions (O'Driscoll et al., 2006; Qureshi et al.,
2010; Soerensen et al., 2013, 2014). Measurements of Hg
from these recent studies show relatively low concentrations of atmospheric
and surface water-phase <inline-formula><mml:math id="M11" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mn mathvariant="normal">0</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> in regions with high productivity compared
to areas with lower productivity. These studies related their observation to
sorption and scavenging of Hg by suspended organic particles. They suggested
that removal of <inline-formula><mml:math id="M12" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> associated with sorption and scavenging by
suspended organic particles in productive regions reduces the amount of
available <inline-formula><mml:math id="M13" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Hg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> for reduction and re-emission. Therefore applying the
model estimates across the entire ocean introduces substantial uncertainty,
and one area in particular that highlights this uncertainty is the
underestimation of the role of biological productivity as a major vector of
Hg sedimentation in the oceans.</p>
      <p id="d1e256">The marine biogeochemical cycle, especially sedimentation of many elements
(Fowler and Knauer, 1986; Morel and Price, 2003; Schlesinger and Bernhardt,
2013), including Hg (Kita et al., 2013; Lamborg et al., 2016; Zaferani et
al., 2018), in the ocean is controlled directly and indirectly by biological
productivity. Biogenic particles control the distribution of elements
through primary production, sinking, and decomposition (Fowler and Knauer,
1986). Besides direct uptake across cell membranes through active
metabolism, phytoplankton and sinking biogenic particles can scavenge and
remove many other elements from the dissolved phase and transport them to
the deep sea. Sinking speed of biogenic particles plays an important role in
the final fate of those elements. Rapidly sinking particles such as diatom
agglomerates transfer elements to the deep sea (Fowler and Knauer, 1986;
Smetacek et al., 2012), whereas elements associated with the slowly sinking
particulates will release back to the water phase through remineralization
(Fowler and Knauer, 1986). In areas where pronounced seasonal blooms take
place, phytoplankton species appear to reach the deep-sea floor relatively
fast and intact. Seasonal blooms in the surface waters will also cause
temporally variable fluxes of elements in the deep ocean (Fowler and Knauer,
1986; Michel et al., 2002; Pilskaln et al., 2004). For Hg, these findings
are supported by water column (Lamborg et al., 2014b) and marine sediment
measurements (Kita et al., 2013; Aksentov and Sattarova, 2020). Lamborg et
al. (2014b) described a nutrient-like distribution of Hg in the water column
of oceans. This study indicates that, similar to carbon (C) and phosphorus
(P), Hg shows higher concentrations in the deep water due to its release
during organic matter decomposition. Kita et al. (2013) found a positive
correlation between Hg and the absolute abundance of phytoplankton species
in sediments of the Caribbean Sea. Hg in these sediments was assumed to be a
result of Hg binding by phytoplankton depositing Hg-bearing organic matter
in the photic zone. A similar conclusion was reached by Aksentov and
Sattarova (2020), who used a thermoscanning technique to detect Hg forms.
They found that biological productivity controlled the Hg burial in
northwestern Pacific bottom sediments and that the forms of Hg depended on the
diatom content.</p>
      <p id="d1e260">These observations can be due to Hg–phytoplankton interactions and uptake
or binding of Hg from the water by phytoplankton (Le Faucheur et al., 2014;
Mason et al., 1996). This interaction controls the flux of Hg from the water
column to sediments and facilitates the downward flux of Hg to the seafloor
(Soerensen et al., 2014, 2016; Lamborg et al., 2016;
Zaferani et al., 2018), which, as mentioned, has traditionally been
considered to be slow in its nature. Thus, underestimating the role of
biological productivity in the marine biogeochemical cycle of Hg may lead to
an overestimation of re-emission fluxes from surface water and an
underestimation of the Hg flux to deep-sea sediments.</p>
      <p id="d1e263">In this context, the Southern Ocean is of particular interest due to its
high concentrations of nutrients and related elevated primary productivity
(Arrigo et al., 1998). In the Southern Ocean, diatoms are major primary
producers (Crosta et al., 2005). Their siliceous cell walls preserve well in
sediments and form diatom ooze (Fütterer, 2006). The sedimentation rate
of diatom ooze is high, estimated to reach up to 2 cm yr<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (Escutia et
al., 2011), making diatom ooze deposits around Antarctica a unique
geochemical archive to study the influence of primary productivity as well
as natural and anthropogenic changes on the marine biogeochemical cycle of
Hg.</p>
      <?pagebreak page731?><p id="d1e278">Despite providing a unique geochemical archive, studies on Hg cycling in the
Southern Ocean, particularly in the Antarctic region, are generally limited
to water column (Cossa et al., 2011; Nerentorp Mastromonaco et al., 2017b;
Canário et al., 2017), surface water/air (Nerentorp Mastromonaco et al.,
2017a; Wang et al., 2017), and ice core analyses (Vandal et al., 1993).
Cossa et al. (2011) showed a nutrient-like distribution of Hg in the water
column that ranged between 0.6 and 2.8 pmol L<inline-formula><mml:math id="M15" 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>. Nerentorp Mastromonaco
et al. (2017b) found higher total Hg concentration than Cossa et al. (2011),
with no significant vertical variations. Both studies reported seasonal
variations in Hg concentrations and related them to seasonal variations of
atmospheric Hg deposition (Cossa et al., 2011; Nerentorp Mastromonaco et
al., 2017b) as well as the Hg inputs from melting sea ice and snow
(Nerentorp Mastromonaco et al., 2017b). Total Hg concentrations in the
Atlantic sector of the Southern Ocean obtained during a study by Canário
et al. (2017) were also, in general, comparable to those obtained by Cossa
et al. (2011) except for some stations that showed higher total Hg
concentrations. Canário et al. (2017) attributed these differences to
the different stages of phytoplankton bloom during the sampling. This led to
lower dissolved Hg in water in the middle–end stage of the bloom compared to
the beginning stage of the bloom, owing to the Hg uptake by phytoplankton
(Canário et al., 2017). Measurements of gaseous elemental mercury (GEM)
and dissolved gaseous mercury (DGM) in surface water showed spatial and
seasonal variations as well (Nerentorp Mastromonaco et al., 2017a; Wang et
al., 2017). These studies related the increase in DGM and GEM concentrations
to the presence and absence of sea ice. Sea ice that could prevent Hg
evasion to the atmosphere could initially lead to an increase in Hg
emissions to the atmosphere when diminishing. Hg concentrations in an ice
core covering the past 34 kyr varied between 0.0005 and
0.0021 <inline-formula><mml:math id="M16" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></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>, corresponding to depositional fluxes of 0.009 and 0.031 <inline-formula><mml:math id="M18" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M19" 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> yr<inline-formula><mml:math id="M20" 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> during the Holocene and the Last Glacial Maximum,
respectively (Vandal et al., 1993). Vandal et al. (1993) attributed the
observed enhanced Hg flux during colder periods to marine biological
productivity and emissions of volatile Hg compounds from the ocean. The different results of the existing studies point to the gaps in our
understanding of Hg behavior in productive remote areas, which warrants
further investigation in the Southern Ocean.</p>
      <p id="d1e346">In a previous paper, we discussed the accumulation of anthropogenic Hg in
sediments of Adélie Basin, offshore East Antarctica. The <inline-formula><mml:math id="M21" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>-fold increase in Hg concentrations and accumulation rates in the upper
<inline-formula><mml:math id="M22" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2.80</mml:mn></mml:mrow></mml:math></inline-formula> m depth of the core was attributed to the onset of the
industrial revolution and the strong increase in coal burning at
<inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1850</mml:mn></mml:mrow></mml:math></inline-formula> CE (Zaferani et al., 2018). Here, we discuss the
natural processes (e.g., changes in biogenic and terrestrial material fluxes)
that controlled Hg accumulation in the same sediment core prior to 1850 CE
throughout the past 8600 years. We investigated a continuous <inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">170</mml:mn></mml:mrow></mml:math></inline-formula> m long Holocene laminated diatom ooze sediment record from the
Adélie Basin. Covering almost the entire Holocene, the core allows the
determination of natural variations of Hg accumulation rates in these
sediments prior to major anthropogenic influences. Our main objective was to
investigate the influence of different Hg sources as well as climate-induced changes in biological productivity and terrestrial fluxes (through melting of
glacier ice), which have controlled the sequestration of Hg in these
sediments. To evaluate the influence of different biogeochemical processes
on the Hg accumulation in sediments, with an emphasis on the role of changes
in planktonic productivity, we combined the data on Hg accumulation with
data derived from multielement analyses.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Materials and methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Study site and core collection</title>
      <p id="d1e404">Sediments of the Adélie Basin were collected during the Integrated Ocean
Drilling Program (IODP) Expedition from hole U1357B 318 in 2010. U1357B is
located on the continental shelf off Wilkes Land at the Mertz Glacier
polynya (region of open water surrounded by sea ice), Antarctica
(66<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>24.7990<inline-formula><mml:math id="M26" display="inline"><mml:mi mathvariant="normal">"</mml:mi></mml:math></inline-formula> S, 140<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>25.5705<inline-formula><mml:math id="M28" display="inline"><mml:mi mathvariant="normal">"</mml:mi></mml:math></inline-formula> E), at
about 1021.5 m water depth (Escutia et al., 2011) (Fig. 1). The total length
of the recovered core is 170.7 m, corresponding to nearly the entire
Holocene (Escutia et al., 2011). The core was sliced by 5 cm<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> plastic scoops
to 1 cm slices. Samples in the upper core (3.2–25.05 m b.s.f.) were taken at
<inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> cm intervals (a resolution of <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula> years)
and <inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">400</mml:mn></mml:mrow></mml:math></inline-formula> cm intervals (a resolution of <inline-formula><mml:math id="M33" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">200</mml:mn></mml:mrow></mml:math></inline-formula> years) in deeper sections (25.05–170.35 m b.s.f.), resulting in a total of 78
samples. Age data and age model (which is based on compound-specific
<inline-formula><mml:math id="M34" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi/><mml:mn mathvariant="normal">14</mml:mn></mml:msup><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> dating) were obtained from Yamane et al. (2014).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e503">Location of the IODP318-U1357B core in the Adélie Basin, East
Antarctica, indicated by a yellow dot (Antarctic image source © Google Earth; bathymetric map is reproduced from Escutia et al., 2011).</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f01.png"/>

        </fig>

      <p id="d1e512">The sediment core is characterized by light and dark laminations which are
undisturbed by sea-level changes or glacial erosion (Denis et al., 2006;
Escutia et al., 2011). Light laminations correspond to spring seasons when
light and high nutrient levels promote intense phytoplankton blooms and are
mainly composed of biogenic materials (mostly diatom with minor abundance of
silicoflagellates, sponge spicules, radiolarians, and foraminifers). Dark
layers correspond to the summer/autumn season when sea ice has retreated,
and nutrient levels are low. Dark laminations are composed of a mixture of
biogenic and terrigenous materials resulting from summer production in open
water, with glacial and subglacial inputs, respectively. High levels of
primary production in surface water of this region, coupled with rapid
fluxes of biogenic debris directly to the seafloor, led to high
sedimentation rates of up to 2.0 cm yr<inline-formula><mml:math id="M35" 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> during the past 10 000 years
(Escutia et al., 2011).</p><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page732?><sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Analyses of mercury and major and trace metals</title>
      <p id="d1e536">All samples were freeze-dried and ground using a glass pestle prior to
geochemical analysis. Total Hg was determined by thermal decomposition
followed by preconcentration of Hg on a gold trap and cold vapor atomic absorption spectrometry (CVAAS) Hg detection
using a Milestone DMA-80 analyzer (US EPA Method 1998). The quality of the
analysis was ensured by including a certified reference material (CRM)
(Canmet LKSD-4 <inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">190</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">17</mml:mn></mml:mrow></mml:math></inline-formula> ng g<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>) alongside the analyzed
samples. The average measured concentration for LKSD-4 was <inline-formula><mml:math id="M38" display="inline"><mml:mrow><mml:mn mathvariant="normal">197</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">11</mml:mn></mml:mrow></mml:math></inline-formula> ng g<inline-formula><mml:math id="M39" 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>. Replicate analyses (<inline-formula><mml:math id="M40" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula>) were always within a relative standard deviation (RSD) of 10 %
of the certified value.</p>
      <p id="d1e601">The samples were analyzed for concentrations of silicon (Si), titanium (Ti),
zirconium (Zr), sulfur (S), calcium (Ca), potassium (K), aluminum (Al),
yttrium (Y), manganese (Mn), strontium (Sr), iron (Fe), lead (Pb), copper
(Cu), zinc (Zn), arsenic (As), bromine (Br), nickel (Ni), chlorine (Cl), and
rubidium (Rb) by energy dispersive X-ray fluorescence (ED-XRF). The
calibration method, accuracy, and precision are described in detail in
Cheburkin and Shotyk (1996). The CRMs (Canmet LKSD-4, NRC/CNRC-PACS-2,
NRC/CNR-Mess-3, and NCS-DC75304) and replicates were measured in each set of
samples for accuracy and precision control. Repeated analysis of CRMs gave
an RSD of less than 10 % for Si, Al, Ca, Y, Sr,
Zr, Br, and Rb; 6 %–15 % for Ti, K, Zn, S, Fe, Mn, and Pb; 6 %–19 % for
Cl; 10 %–20 % for Ni; 9 %–14 % for Cu; and 14 %–22 % for As.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Statistical analyses</title>
      <p id="d1e612">Principal component analysis (PCA) was applied to the major and trace
element concentrations to identify processes controlling the variability of
elements in the sediments. When there is a complex set of variables, PCA is
used to reduce a large number of variables to a new set of artificial
variables, called principal components. Each component includes variables
with a similar down-core pattern. The principal components are then
interpreted in terms of relevant geochemical processes that can control the
variability of the major and trace elements in the sediments. The derived
interpretation from PCA was then combined with the Hg data to examine the
processes that could affect Hg accumulations. The analysis was performed on
the standardized concentration data using <inline-formula><mml:math id="M41" display="inline"><mml:mi>Z</mml:mi></mml:math></inline-formula> scores (expressed in terms of
standard deviations from their means). Regression analysis of the
corresponding residuals was used to establish relationships between the
abundance of elements, by considering Si concentration as an independent
variable and other element concentrations as dependent variables.
Correlation analysis and PCA were performed using the statistical software
SPSS 25.0.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Geochemical processes controlling the distribution of the elements in
the sediments</title>
      <p id="d1e638">Concentration profiles and accumulation rates of Si, Al, K, Ti, S, Ca, Zn,
Fe, Br, As, and Cl are shown in Figs. 2–5. The preindustrial geochemical
record of Adélie Basin sediments is generally characterized by
periodic-like variations in the relative abundance of major and trace
elements. The records of element accumulation rates largely follow those of
periodic-like variations of concentrations and show no significant trend
with depth (except Cl).</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e643">Down-core records of Si, Al, K, Ti, S, Fe, Zn, Cl, Ca, Br, As, and
Hg concentrations of Adélie Basin sediments.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f02.png"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e654">Down-core records of Si, Al, K, Ti, S, Fe, Zn, Cl, Ca, Br, As, and
Hg concentrations of Adélie Basin sediments for the top 23 m of the
core.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f03.png"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e666">Down-core records of Si, Al, K, Ti, S, Fe, Zn, Cl, Ca, Br, As, and
Hg accumulation rates of Adélie Basin sediments.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f04.png"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e677">Down-core records of Si, Al, K, Ti, S, Fe, Zn, Cl, Ca, Br, As, and
Hg accumulation rates of Adélie Basin sediments for the top 23 m of the
core.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f05.png"/>

        </fig>

      <?pagebreak page735?><p id="d1e686">Si has the highest concentration of all elements in the sediments. On one
hand, Si is associated with the flux of terrestrial derived mineral
components and on the other hand with siliceous phytoplankton, protozoans,
protists, plant phytoliths, and sponge spicules (Croudace and Rothwell,
2015). Si is mainly biogenic in origin in Adélie Basin sediments,
as well as dominated by diatoms (Escutia et al., 2011), and contribution of terrigenous
Si is low. Therefore, it is used as a proxy for diatom abundance. The record
of Si concentrations shows periodic-like variations by a factor of
<inline-formula><mml:math id="M42" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> between 21 % and 50 %, with a median of 33 %,
corresponding to 70 % <inline-formula><mml:math id="M43" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SiO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> or biogenic silica. Concentrations of Al,
K, and Ti (as indicators of changes in the flux of lithogenic materials)
range between <inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.6</mml:mn></mml:mrow></mml:math></inline-formula> %–7.3 %, <inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.37</mml:mn></mml:mrow></mml:math></inline-formula> %–1.11 %, and <inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">716</mml:mn></mml:mrow></mml:math></inline-formula>–1778 mg kg<inline-formula><mml:math id="M47" 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>, respectively. S and Ca
concentrations, which are associated with the biogenic productivity, vary
between <inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.13</mml:mn></mml:mrow></mml:math></inline-formula> %–0.87 % and 0.72 %–1.49 %, respectively.
Ca concentration indicates that calcite-producing microorganisms are of
minor importance in the Adélie Basin. Concentration of Zn, an important
micronutrient for marine phytoplankton (Morel et al., 1994), ranges between
<inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">96</mml:mn></mml:mrow></mml:math></inline-formula> and 216 mg kg<inline-formula><mml:math id="M50" 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>. Fe is another essential
micronutrient for marine primary production (Smetacek et al., 2012) and
biochemical processes of phytoplankton such as photosynthesis, respiration,
and nitrogen fixation (Lohan and Tagliabue, 2018). Concentration of Fe
varies between <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.05</mml:mn></mml:mrow></mml:math></inline-formula> % and 3.46 %, which is similar to other
siliceous sediments but lower than the reported concentration in other ocean
sediments (Chen et al., 1996). Fe concentrations increase at 66.45 m depth
to the top of the core by a factor of <inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.6</mml:mn></mml:mrow></mml:math></inline-formula> (from a median of
<inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.50</mml:mn></mml:mrow></mml:math></inline-formula> % below the 66.45 m depth to <inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2.40</mml:mn></mml:mrow></mml:math></inline-formula> % above the 66.45 m depth). This is attributed to the upward transport of
Fe under anoxic conditions. Chlorine was found to be another major component
in these sediments. Cl can go through biological pathways (incorporation
into algae) and reach the sediments by the fast-sinking detritus (Leri et
al., 2015). Concentrations vary between <inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.3</mml:mn></mml:mrow></mml:math></inline-formula> % and 19 %,
with a median of median 4.5 % and show a decrease from the top to the
bottom of the core, which is likely attributed to the increasing
mineralization of organic matter with age and the release of chloride
through reductive dechlorination.</p>
      <p id="d1e836">The PCA resulted in five components, explaining almost 82 % of the total
variance (Table 1). The first component (Cp1) explains 33 % of the
variance and shows large (<inline-formula><mml:math id="M56" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mn mathvariant="normal">0.7</mml:mn></mml:mrow></mml:math></inline-formula>) positive loadings of Mn, Ti, Rb,
Zr, K, and Y and moderate positive loading of Fe. The second component
(Cp2), which explains 20 % of the variance, is characterized by large
positive loadings of Al, Si, S, and Cl and moderate positive loading of K
and Ca. The third component (Cp3) explains 17 % of the variance and shows
large positive loadings of Zn, Cu, and Ni and moderate positive loading of
Fe. The fourth and fifth components (Cp4 and Cp5) account for 7 % and 5 %
of the variance, respectively. Cp4 is characterized by high positive
loadings for Hg and As and moderate negative loading of Pb. Cp5 shows
positive loadings for Sr and Ca.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e852">Factor loadings for the five significant components
extracted by PCA from Adélie Basin sediment samples. Component loadings <inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:mo>≥</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula> are in bold.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="6">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Elements</oasis:entry>
         <oasis:entry rowsep="1" namest="col2" nameend="col6" align="center">Components </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">2</oasis:entry>
         <oasis:entry colname="col4">3</oasis:entry>
         <oasis:entry colname="col5">4</oasis:entry>
         <oasis:entry colname="col6">5</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Mn</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M58" display="inline"><mml:mn mathvariant="bold">0.89</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.40</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M60" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.01</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Ti</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M61" display="inline"><mml:mn mathvariant="bold">0.89</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.43</oasis:entry>
         <oasis:entry colname="col4">0.01</oasis:entry>
         <oasis:entry colname="col5">0.04</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Rb</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M63" display="inline"><mml:mn mathvariant="bold">0.84</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.03</oasis:entry>
         <oasis:entry colname="col4">0.39</oasis:entry>
         <oasis:entry colname="col5">0.10</oasis:entry>
         <oasis:entry colname="col6">0.20</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Zr</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M64" display="inline"><mml:mn mathvariant="bold">0.83</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.22</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.05</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.15</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.08</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">K</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M67" display="inline"><mml:mn mathvariant="bold">0.73</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M68" display="inline"><mml:mn mathvariant="bold">0.66</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.05</oasis:entry>
         <oasis:entry colname="col5">0.08</oasis:entry>
         <oasis:entry colname="col6">0.10</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Y</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M69" display="inline"><mml:mn mathvariant="bold">0.73</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.34</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.10</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.09</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.05</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Al</oasis:entry>
         <oasis:entry colname="col2">0.12</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M72" display="inline"><mml:mn mathvariant="bold">0.93</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.06</oasis:entry>
         <oasis:entry colname="col5">0.05</oasis:entry>
         <oasis:entry colname="col6">0.18</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Si</oasis:entry>
         <oasis:entry colname="col2">0.03</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M73" display="inline"><mml:mn mathvariant="bold">0.84</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.28</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M75" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.11</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M76" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.28</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">S</oasis:entry>
         <oasis:entry colname="col2">0.01</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M77" display="inline"><mml:mn mathvariant="bold">0.84</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.16</oasis:entry>
         <oasis:entry colname="col5">0.12</oasis:entry>
         <oasis:entry colname="col6">0.26</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Cl</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.16</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M79" display="inline"><mml:mn mathvariant="bold">0.76</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.25</oasis:entry>
         <oasis:entry colname="col5">0.22</oasis:entry>
         <oasis:entry colname="col6">0.42</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Zn</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.15</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M81" display="inline"><mml:mn mathvariant="bold">0.78</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.15</oasis:entry>
         <oasis:entry colname="col6">0.11</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Cu</oasis:entry>
         <oasis:entry colname="col2">0.31</oasis:entry>
         <oasis:entry colname="col3">0.03</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M82" display="inline"><mml:mn mathvariant="bold">0.76</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.31</oasis:entry>
         <oasis:entry colname="col6">0.21</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Ni</oasis:entry>
         <oasis:entry colname="col2">0.11</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.08</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M84" display="inline"><mml:mn mathvariant="bold">0.75</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.10</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.00</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Fe</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M86" display="inline"><mml:mn mathvariant="bold">0.62</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.03</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M87" display="inline"><mml:mn mathvariant="bold">0.64</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.20</oasis:entry>
         <oasis:entry colname="col6">0.19</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Br</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.23</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">0.35</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M89" display="inline"><mml:mn mathvariant="bold">0.50</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.46</oasis:entry>
         <oasis:entry colname="col6">0.48</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Hg</oasis:entry>
         <oasis:entry colname="col2">0.17</oasis:entry>
         <oasis:entry colname="col3">0.09</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M90" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M91" display="inline"><mml:mn mathvariant="bold">0.79</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.14</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">As</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M93" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.09</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.30</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M94" display="inline"><mml:mn mathvariant="bold">0.73</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M95" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.26</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Pb</oasis:entry>
         <oasis:entry colname="col2">0.35</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.11</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M97" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.10</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M98" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">0.62</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.18</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Sr</oasis:entry>
         <oasis:entry colname="col2">0.25</oasis:entry>
         <oasis:entry colname="col3">0.09</oasis:entry>
         <oasis:entry colname="col4">0.37</oasis:entry>
         <oasis:entry colname="col5">0.16</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M100" display="inline"><mml:mn mathvariant="bold">0.83</mml:mn></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Ca</oasis:entry>
         <oasis:entry colname="col2">0.22</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M101" display="inline"><mml:mn mathvariant="bold">0.52</mml:mn></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M102" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M103" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.13</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M104" display="inline"><mml:mn mathvariant="bold">0.67</mml:mn></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Eigenvalue</oasis:entry>
         <oasis:entry colname="col2">6.62</oasis:entry>
         <oasis:entry colname="col3">3.95</oasis:entry>
         <oasis:entry colname="col4">3.34</oasis:entry>
         <oasis:entry colname="col5">1.35</oasis:entry>
         <oasis:entry colname="col6">0.98</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">% variance</oasis:entry>
         <oasis:entry colname="col2">33.1</oasis:entry>
         <oasis:entry colname="col3">19.7</oasis:entry>
         <oasis:entry colname="col4">16.7</oasis:entry>
         <oasis:entry colname="col5">6.7</oasis:entry>
         <oasis:entry colname="col6">4.9</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e1717">In general, results of PCA imply that opening and closing of the polynya and
biological production are the most important factors influencing
sedimentation in the Adélie Basin. This has been shown by loadings of
elemental proxies for terrigenous and biological material inputs. Briefly,
Cp1, which includes positive loadings of lithogenic elements, represents the
variability of terrigenous inputs. Melting of ice releases trapped
lithogenic material into the water and leads to the sinking of lithogenic
particles and their sedimentation. Cp2 comprises loadings of elements of
both biogenic and terrigenous sources. This component appears to reflect
phytoplankton blooms and export of biological materials. After ice melt,
when the ice is opening, favorable conditions for biological productivity
lead to phytoplankton blooms and export of biogenic materials to the
seafloor (Denis et al., 2006). Biogenic material is mainly opal because
diatoms are a major component of blooms in the Adélie Basin (Escutia et
al., 2011). The sinking of diatoms from the surface and their sedimentation
can cause scavenging of elements during bloom time. Al shows positive
loadings in this component rather than in Cp1. This, other than association
with the flux of aluminosilicates material, can also be attributed to the
scavenging of Al by diatom particles (Moran and Moore, 1992). Cl also shows
loading in Cp2. The possible explanation for the observed covariation is
that marine phytoplankton is rich in polyunsaturated lipids and can account
as chlorination substrates (Leri<?pagebreak page736?> et al., 2015). However, the organic C
content of Adélie Basin sediments is generally low (between 1 wt % and 2 wt %), and we hypothesize that some of the Cl must be in an inorganic form
trapped in sediments owing to high sedimentation rates. Cp3 is mainly
characterized by elements that are associated with the organic fraction of
diatom cells. This component appears to reflect the remineralization process
like decomposition of organic particles during sinking. Trace elements
associated with organic parts of cells can be released back into the water
column during decomposition. Therefore, cellular locations of elements, i.e.,
opal frustules of diatoms or organic matter of diatom cells, created
different components of Cp2 and Cp3. Cp4 consists of organic particle
reactive metals, e.g., Hg and Pb. The possible explanation for not having
these two particle reactive metals in Cp2 is that a portion of these two metals begins to enter the system after ice melting, while Cp2 shows scavenging of
elements by diatoms that are already present in the water column. Since Pb
and Hg are negatively correlated, this component cannot reflect a pollution
signal. The reason for that could be the characteristic of Pb that decreases
its impact in remote areas such as Antarctica. Atmospheric Pb is associated
with particles and therefore is rapidly removed by wet and dry deposition.
Moreover, the Southern Ocean circumpolar vortex that isolates Antarctica from
the other continental landmasses in the Southern Hemisphere will further
limit Pb transport to Antarctica. Covariation of Ca and Sr in Cp5 represents
sedimentation of planktonic foraminifera, which appears to be of minor
importance here.</p>
      <p id="d1e1720">Cp1 explains 33 % of the variance and accounts for much of the
variability/process which controlled the geochemical composition of these
sediments. However, the high concentration of Si and low concentrations of
terrigenous elements imply that in an environment like Adélie Basin,
with extremely high productivity, input of lithogenic materials is changing
while different diatom taxa are always present in the system, e.g., as sea-ice-associated and open-ocean diatom (Escutia et al., 2011).</p>
      <p id="d1e1723">It has been shown before that seasonal blooms in ocean surface waters result
in temporary variable fluxes of elements to the deep ocean (Fowler and
Knauer, 1986; Michel et al., 2002; Pilskaln et al., 2004). Although the core
was not sampled at a 1-year resolution in our study, we suggest that the
fluctuations of elemental concentrations are likely related to the seasonal
blooms and variation of sea surface conditions like ice melting and freezing
and its subsequent biological or terrestrial material exports. Sampling in
light (associated with spring) or dark (associated with summer/autumn)
laminae, which contains different amounts of biogenic or terrestrial
materials, can cause the observed variations (see Sect. 2.1).</p>
      <p id="d1e1726">The element concentrations are comparable to other published sediment data,
while the accumulation rates are much higher than other reported values. The
existence of rapidly settling particles in the Adélie Basin can explain
the high element accumulation rates. When nonessential elements and
essential elements show high accumulation rates, it is tempting to suggest
that most elements in the water column of Adélie Basin are subjected to
removal by intense phytoplankton blooms through consumption or scavenging.
This agrees with the study of Fowler and Knauer (1986) that demonstrated the
role of large particles in the transport of elements through the oceanic
water column. Aggregations of diatoms, which create large particles (Turner,
2015), sink to the seafloor and can create a space in which elements can be
trapped (Shanks and Trent, 1979). This enhances removal of elements from the
water column and their sedimentation as well.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e1731">Depth records of scores of the principal components extracted by
PCA on the elemental composition of the sediments along with <inline-formula><mml:math id="M105" display="inline"><mml:mi>Z</mml:mi></mml:math></inline-formula> score of Hg
of the Adélie Basin sediments.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f06.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><?xmltex \currentcnt{7}?><label>Figure 7</label><caption><p id="d1e1750">Depth records of scores of the principal components extracted by
PCA on the elemental composition of the sediments along with <inline-formula><mml:math id="M106" display="inline"><mml:mi>Z</mml:mi></mml:math></inline-formula> score of Hg
of the Adélie Basin sediments for the top 23 m of the core.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f07.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><?xmltex \currentcnt{8}?><label>Figure 8</label><caption><p id="d1e1768">Adélie Basin schematic Hg cycle model indicating the processes
controlling Hg deposition and accumulation under high primary production.
Fast-sinking diatom particles remove dissolved water-phase Hg from the water
column through scavenging (figure is adapted from Jansen et al., 2018).</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://os.copernicus.org/articles/16/729/2020/os-16-729-2020-f08.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Holocene record of mercury concentrations and accumulation rates</title>
      <p id="d1e1785">In the preindustrial period, i.e., from the bottom of the core at
<inline-formula><mml:math id="M107" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">170</mml:mn></mml:mrow></mml:math></inline-formula> to 2.80 m depth (8600 years ago to <inline-formula><mml:math id="M108" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1850</mml:mn></mml:mrow></mml:math></inline-formula> CE), the Hg record shows no obvious trend with depth but rather
periodic-like variations. Hg concentrations fluctuate by a factor of about 2
between 12.6 and 21.1 <inline-formula><mml:math id="M109" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g kg<inline-formula><mml:math id="M110" 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> within 170–137 m depth and
between 21.7 and 44.6 <inline-formula><mml:math id="M111" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g kg<inline-formula><mml:math id="M112" 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> within 137–2.80 m depth of the
core, with two more pronounced peaks at around 9.99 and 8.20 m depth (Figs. 2
and 3). The lower concentration of Hg within 170–137 m depth of the core is
probably attributed to cooler conditions in Adélie Basin (Crosta et al.,
2007) and sea ice cover during this period. Hg accumulation rates in the
preindustrial period (Figs. 4 and 5) largely follow the Hg concentration
record, with periodic-like variations and a median of 556 <inline-formula><mml:math id="M113" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M114" 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> yr<inline-formula><mml:math id="M115" 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>, which largely surpass the reported Hg deposition rates to the
oceans (Mason and Sheu, 2002).</p>
      <p id="d1e1881">The high preindustrial Hg accumulation rates in Adélie Basin sediments
cannot be explained by preindustrial atmospheric Hg depositions alone, which
did not exceed 20 <inline-formula><mml:math id="M116" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M117" 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> as recorded in an Antarctic ice core
(Vandal et al., 1993). Therefore, nonatmospheric sources, such as dissolved
water-phase Hg or terrestrial inputs, are needed for the observed high Hg
enrichment in these sediments.</p>
      <p id="d1e1904">To identify driving forces behind the variations in Hg accumulation we used
our PCA results. PCA demonstrated that two main processes, i.e., biogenic
productivity and lithogenic inputs, controlled the flux of elements to
Adélie Basin sediments. The component scores, which illustrate the depth
dependency of the extracted components, are characterized by seesaw
patterns throughout the entire core. This indicates different contributions
of biogenic and terrigenous inputs most likely associated with spring and
summer/autumn seasons, respectively.</p>
      <?pagebreak page738?><p id="d1e1907">The variance of Hg was not captured by Cp1, Cp2, or Cp3. Hg instead forms a
group on Cp4 together with positive loading of As and negative loading of
Pb. The absence of significant loading of Hg on Cp1, Cp2, and Cp3 (Table 1)
and the lack of similarity between component scores and Hg concentrations
(Figs. 6 and 7), in the preindustrial period, indicate that Hg fluxes are
not significantly influenced by changes in lithogenic inputs through ice
melting. These results further indicate that changes in the contribution of
biogenic material cannot explain the variation in Hg accumulation in the
sediments.</p>
      <p id="d1e1911">Although, the high Hg accumulation rates observed in the Adélie Basin
sediments could not be explained by atmospheric Hg deposition, but we expect
that the Hg flux from the atmosphere will probably increase during algae
blooms attributed to the removal of dissolved Hg through scavenging by
algae. Hg removal from the upper water column by diatom organic matter will
also likely decrease Hg re-evasion to the atmosphere as previously assumed
in model studies (Soerensen et al., 2014, 2016).</p>
      <p id="d1e1914">We have hypothesized that the high Hg enrichment in Adélie Basin
sediments has been caused by scavenging of dissolved water-phase Hg by a
large amount of fast-sinking algal debris. To prove this hypothesis we
calculated the maximum amount of Hg which could be scavenged by a single
bloom event using the Hg concentration of <inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mn mathvariant="normal">271</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">78</mml:mn></mml:mrow></mml:math></inline-formula> pg L<inline-formula><mml:math id="M119" 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> in
Antarctic bottom water, as determined by Cossa et al. (2011). The amount of
Hg in a water column of 1 m<inline-formula><mml:math id="M120" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> and 1000 m depth would then amount to
<inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:mn mathvariant="normal">271</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">78</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M122" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g. This means that only about two to three algae blooms and
scavenging events per year are necessary to obtain the average Hg
accumulation rate in Adèlie Basin diatom ooze sediments, i.e., <inline-formula><mml:math id="M123" display="inline"><mml:mrow><mml:mn mathvariant="normal">556</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">137</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M124" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g m<inline-formula><mml:math id="M125" 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> yr<inline-formula><mml:math id="M126" 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>. This appears to be likely taking
into account that bloom events are frequent during Antarctic summer and that
the sinking speed of diatom agglomerates at Adélie Basin is high
(100–400 m d<inline-formula><mml:math id="M127" 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>) (Jansen et al., 2018). The annual cycle of water mass
transformation beneath the Mertz Glacier polynya system (Williams et al.,
2008) and the exchange of water masses can rapidly refill the Hg
inventory in the water column after a scavenging event. While algal bloom is
a local event at the surface water of the Adèlie Basin, the exchange of
water masses, which have not been affected by algae blooms, could refill the
Hg inventory in the water column (Fig. 8).</p>
      <p id="d1e2027">The main reason for not finding any statistical relation between Hg and
biogenic materials is that the amount of algal material during blooms is
always large and therefore not a limiting factor for the scavenging of Hg.
There has always been excess algal material within or passing through the
water column to scavenge all water column Hg. Thus, we assume that nearly
all Hg in the water column is removed through scavenging during diatom
blooms but that Hg scavenging events occur less frequently during winter
and summer/autumn seasons when primary productivity is lower and open ice
expansion is at its maximum. Similar to other elements, the periodic-like
variations observed in the preindustrial Hg record. The influence of
periodically climatic changes of phytoplankton activity on periodical
changes of Hg content was suggested before for the Caribbean Sea (Kita et
al., 2013). It is likely that the periodic-like variations observed in the
Adèlie Basin Hg record are also attributed to the seasonal export of
biological materials. This could be in line with findings of Hg levels in water (Canário et al., 2017), which suggested that different development stages of a phytoplankton bloom lead to different amounts of dissolved Hg<?pagebreak page739?> taken up by phytoplankton. However, investigation at seasonal resolution is needed to
further confirm our observations and hypotheses.</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Conclusions</title>
      <p id="d1e2039">Investigation of Antarctic biogenic bottom sediments revealed that
biological productivity and related scavenging of water-phase Hg by rapidly
sinking algae or algae-derived organic matter controlled preindustrial Hg
accumulation in Adélie Basin, Antarctica. Our study suggests that the
periodic-like variations in total Hg concentrations and accumulation rates
are likely associated with the opening and closing of polynya and its
related changes in biological productivity. Although the high Hg
accumulation in diatom ooze does not represent the Hg sedimentation process
across all the world's oceans, our data show that Hg scavenging by algae or
fast-sinking algae-derived organic matter is a key process controlling the
sequestration of Hg in marine sediments and therefore the marine
biogeochemical cycle of Hg in general. This can be similar to the
association between very high benthic organic C fluxes with diatom
production at the surface water, which can be accelerated by aggregation
(Sachs et al., 2009).</p>
      <p id="d1e2042">Our observations also suggest that re-emission of Hg from ocean surface
waters as a result of reduction of Hg (II) might be reduced due to Hg
scavenging by algae, at least in areas of high primary productivity
ecosystems comparable to the Adélie Basin ecosystem setup. Moreover, Hg
fluxes to marine sediments might be higher than previously assumed in global
model estimations. More data from marine sediments are needed to support this
assumption. A future increase in marine productivity including algae blooms
especially in coastal areas and semiclosed shallow seas will likely
increase the Hg flux to bottom sediments. The model study of Soerensen et
al. (2016) for the Baltic Sea might serve as an example for changes in
marine Hg cycling caused by eutrophication. The area of the seafloor which
is covered by remains of calcareous phytoplankton needs to be considered in
future studies as well owing to the role of calcareous species on Hg content
(Kita et al., 2013).</p>
</sec>

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

      <p id="d1e2050">All data are available in the Supplement.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e2053">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/os-16-729-2020-supplement" xlink:title="pdf">https://doi.org/10.5194/os-16-729-2020-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e2062">SZ carried out the analyses. HB planned the study and
supervised the findings of this work. The manuscript was written by both
authors.</p>
  </notes><?xmltex \hack{\newpage}?><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e2069">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e2075">This research was supported by TU Braunschweig. We thank Petra Schmidt and Adelina Calean for technical assistance, as well as David McLagan for the constructive
comments on the manuscript.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e2080">This open-access publication was funded <?xmltex \hack{\newline}?> by Technische Universität Braunschweig.</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e2088">This paper was edited by Yuelu Jiang and reviewed by C. H. Lamborg and two anonymous referees.</p>
  </notes><ref-list>
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<abstract-html><p>Due to its toxic nature and its high potential for
biomagnification, mercury is a pollutant of concern. Understanding the
marine biogeochemical cycle of mercury is crucial as consumption of mercury-enriched marine fish is the most important pathway of human exposure to
monomethylmercury, a neurotoxin. However, due to the lack of long-term
marine records, the role of the oceans in the global mercury cycle is poorly understood. We do not have well-documented data of natural mercury
accumulations during changing environmental conditions, e.g., sea surface
conditions in the ocean. To understand the influence of different sea
surface conditions (climate-induced changes in ice coverage and biological
production) on natural mercury accumulation, we used a continuous
 ∼ 170&thinsp;m Holocene biogenic sedimentary record from Adélie
Basin, East Antarctica, which mainly consists of silica-based skeletons of
diatoms. We performed principal component analysis and regression analysis
on element concentrations and corresponding residuals, respectively, to
investigate the link between sediment mercury accumulation, terrestrial
inputs, and phytoplankton productivity. Preindustrial mercury in the remote
marine basin shows extremely high accumulation rates (median:
556&thinsp;µg&thinsp;m<sup>−2</sup>&thinsp;yr<sup>−1</sup>) that displayed periodic-like variations. Our analyses
show that the variations in total mercury concentrations and accumulation
rates are associated with biological production and related scavenging of
water-phase mercury by rapidly sinking algae or algae-derived organic matter
after intense algae blooms. High accumulation rates of other major and trace elements further reveal that, in regions of high primary productivity,
settling of biogenic materials removes a large fraction of dissolved or
particulate-bound elements from the free water phase through scavenging or
biological uptake. The link between mercury cycling and primary production
will need to be considered in future studies of the marine mercury cycle
under primary production enhancement through climatic, temperature, and
nutrient availability changes.</p></abstract-html>
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