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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-20-16117-2020</article-id><title-group><article-title>Soil–atmosphere exchange flux of total gaseous mercury (TGM) <?xmltex \hack{\break}?>at subtropical and temperate forest catchments</article-title><alt-title>Soil–atmosphere exchange flux of total gaseous mercury</alt-title>
      </title-group><?xmltex \runningtitle{Soil--atmosphere exchange flux of total gaseous mercury}?><?xmltex \runningauthor{J. Zhou et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2 aff3 aff6">
          <name><surname>Zhou</surname><given-names>Jun</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-9914-6808</ext-link></contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff3">
          <name><surname>Wang</surname><given-names>Zhangwei</given-names></name>
          <email>wangzhw@rcees.ac.cn</email>
        <ext-link>https://orcid.org/0000-0002-0516-4536</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff3">
          <name><surname>Zhang</surname><given-names>Xiaoshan</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Driscoll</surname><given-names>Charles T.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-2692-2890</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Lin</surname><given-names>Che-Jen</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5990-3093</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, <?xmltex \hack{\break}?>Chinese Academy of Sciences, Beijing, 100085,
China</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>University of Chinese Academy of Sciences, Beijing, 100049, China</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Department of Civil and Environmental Engineering, Syracuse University, Syracuse, <?xmltex \hack{\break}?>New York 13244, USA</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Center for Advances in Water and Air Quality, Lamar University, Beaumont, Texas 77710, USA</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Department of Environmental, Earth and Atmospheric Sciences, University of Massachusetts Lowell,<?xmltex \hack{\break}?> Lowell, Massachusetts 01854, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Zhangwei Wang (wangzhw@rcees.ac.cn)</corresp></author-notes><pub-date><day>23</day><month>December</month><year>2020</year></pub-date>
      
      <volume>20</volume>
      <issue>24</issue>
      <fpage>16117</fpage><lpage>16133</lpage>
      <history>
        <date date-type="received"><day>3</day><month>August</month><year>2020</year></date>
           <date date-type="rev-request"><day>31</day><month>August</month><year>2020</year></date>
           <date date-type="rev-recd"><day>11</day><month>November</month><year>2020</year></date>
           <date date-type="accepted"><day>13</day><month>November</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 </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://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e159">Evasion from soil is the largest source of mercury (Hg) to the atmosphere from terrestrial ecosystems. To improve our understanding of controls and in estimates of forest soil–atmosphere fluxes of total gaseous Hg (TGM), measurements were made using dynamic flux chambers (DFCs) over 130 and 96 d for each of five plots at a subtropical forest and a temperate forest, respectively. At the subtropical forest, the highest net soil Hg emissions were observed for an open field (24 <inline-formula><mml:math id="M1" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 33 ng m<inline-formula><mml:math id="M2" 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> h<inline-formula><mml:math id="M3" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, followed by two coniferous forest plots (2.8 <inline-formula><mml:math id="M4" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.9 and 3.5 <inline-formula><mml:math id="M5" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>  4.2 ng m<inline-formula><mml:math id="M6" 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> h<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), a broad-leaved forest plot (0.18 <inline-formula><mml:math id="M8" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>  4.3 ng m<inline-formula><mml:math id="M9" 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> h<inline-formula><mml:math id="M10" 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>) and the remaining wetland site showing net deposition (<inline-formula><mml:math id="M11" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.80 <inline-formula><mml:math id="M12" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.1 ng m<inline-formula><mml:math id="M13" 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> h<inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>. At the temperate forest, the highest fluxes and net soil Hg emissions were observed for a wetland (3.81 <inline-formula><mml:math id="M15" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.52 ng m<inline-formula><mml:math id="M16" 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> h<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>) and an open field (1.82 <inline-formula><mml:math id="M18" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.79 ng 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> h<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>), with lesser emission rates in the deciduous broad-leaved forest (0.68 <inline-formula><mml:math id="M21" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.01 ng m<inline-formula><mml:math id="M22" 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> h<inline-formula><mml:math id="M23" 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>) and deciduous needle-leaved
forest (0.32 <inline-formula><mml:math id="M24" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.96 ng m<inline-formula><mml:math id="M25" 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> h<inline-formula><mml:math id="M26" 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>) plots, and net deposition at an evergreen pine forest (<inline-formula><mml:math id="M27" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.04 <inline-formula><mml:math id="M28" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.81 ng m<inline-formula><mml:math id="M29" 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> h<inline-formula><mml:math id="M30" 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>). High solar radiation and temperature during summer resulted in the high Hg emissions in the subtropical forest and the open field and evergreen pine forest at the temperate forest. At the temperate deciduous plots, the highest Hg emission occurred in spring during the leaf-off period due to direct solar radiation exposure to soils. Fluxes showed strong positive relationships with solar radiation and soil temperature and negative correlations with ambient air TGM concentration in both the subtropical and temperate forests, with area-weighted compensation points of 6.82 and 3.42 ng m<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, respectively. The values of the compensation points suggest that the atmospheric TGM concentration can play a critical role in limiting TGM emissions from the forest floor. Climate change and land use disturbance may increase the compensation points in both temperate and subtropical forests. Future research should focus on the role of legacy soil Hg in reemissions to the atmosphere as decreases in primary emissions drive decreases in TGM concentrations and disturbances of climate change and land use.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e494">Mercury (Hg) is a persistent, bio-accumulative, toxic and well-established
global contaminant (Obrist et al., 2018). Unlike other trace metals in the atmosphere, the Hg mainly exists as the gaseous elemental Hg (Hg(0)), which accounts for more than 90 % of total gaseous mercury (TGM). Hg(0) is
relatively inert and has a long atmospheric lifetime of<?pagebreak page16118?> 6 months to 1 year, which allows for long-range transport  (Kamp et al., 2018; Slemr et al., 2018;  St Louis et al., 2019). Global long-range atmospheric transport and deposition is the main pathway of Hg input to remote ecosystems  (Lin et al., 2019; Ly Sy Phu et al., 2019; Sun et al., 2019). Soils account for more than 90 % of Hg stored in terrestrial ecosystems (Obrist, 2012), with global topsoil Hg pools (0–40 cm) estimated as being <inline-formula><mml:math id="M32" display="inline"><mml:mi mathvariant="italic">&gt;</mml:mi></mml:math></inline-formula> 300 000 Mg
(Hararuk et al., 2013; Zhou et al., 2017a). The large soil Hg pools stem not only from geologic sources but also from a legacy of historically anthropogenic emissions over the centuries (Obrist et al., 2014; Du et
al., 2019).</p>
      <p id="d1e504">Although many studies have focused on primary anthropogenic Hg emissions,
releases from natural source materials are also an important pathway, but with greater uncertainty and variability, which include emissions from natural reservoirs (e.g., volcanic activity, geothermal sources and weathering of Hg from soil minerals) and re-emissions of previously deposited Hg. These natural sources can be equal to or 2 times larger than anthropogenic sources (Outridge et al., 2018; Fraser et al., 2018). Recent global Hg models estimate that 3600 Mg yr<inline-formula><mml:math id="M33" 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> of atmospheric Hg is deposited to terrestrial surfaces, with 1000 Mg yr<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> being re-emitted back to the atmosphere (Outridge et al., 2018). Moreover, compared to
primary anthropogenic emissions of Hg (2500 Mg 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>), estimates of
re-emissions from soil surfaces are highly uncertain (Outridge et al.,
2018; Wang et al., 2018). Compiling data from 132 studies, Agnan et
al. (2016) found that the Earth's surface (particularly in East Asia) is an
increasingly important source of TGM emissions, with up to half of the global emissions derived from natural sources. They estimated terrestrial TGM emissions of 607 Mg yr<inline-formula><mml:math id="M36" 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> but with a large uncertainty range of <inline-formula><mml:math id="M37" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>513 to 1353 Mg yr<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>. Additionally, a recent review suggests that future research should focus on campaigns to understand forest Hg behavior and long-term Hg observations, particularly in Asia  (Zhang et al., 2019b).</p>
      <p id="d1e575">Forest soils receive Hg inputs from (1) throughfall, including wet
deposition plus the wash-off of Hg (II) deposited on foliage surfaces,  (2) litterfall, containing foliage and other plant materials that have
assimilated atmospheric Hg(0),  and (3) direct dry Hg deposition to soil from
the atmosphere (Teixeira et al., 2018; Risch et al., 2017; Olson et al.,
2018; Cheng et al., 2020). Mercury outputs from forest soils occur from
surface or subsurface runoff and air–land surface evasion. Forest soils are
highly complex media, with important features that affect soil–air exchange,
including soil physiochemical characteristics (e.g., porosity, oxygen
availability, redox potential, organic matter and pH; Obrist et al.,
2010; Carpi et al., 2014). Other factors also influence this process, such as
meteorological conditions (e.g., solar radiation, air temperature and
precipitation; Zhou et al., 2015; O'Connor et al., 2019), atmospheric
chemistry (ozone, nitrate and hydroxyl radicals; Peleg et al.,
2015; Angot et al., 2016), atmospheric TGM concentrations (Wang et al.,
2007) and biological processes  (Obrist et al., 2010; Chen et al., 2017).
Therefore, to characterize and quantify the land–atmosphere exchange of TGM, it is necessary to understand the roles of these factors in mediating this
process.</p>
      <p id="d1e578">Field studies have shown that elevated anthropogenic Hg emissions in
Southeast Asia have resulted in high atmospheric Hg concentrations and
regional deposition (Kumari et al., 2015; Pan et al., 2010; Zhang et al.,
2019b). Forests experience particularly elevated net Hg loads due to an enhanced deposition associated with the tree canopy, especially in China (Wang et al., 2016; Zhang et al., 2019a). The annual loading of total mercury (THg) to subtropical forests in China has been shown to be much higher than forest catchments in Europe and North America (Wright et al., 2016; Zhou et al., 2020a). High Hg deposition has resulted in elevated soil Hg pools in Chinese subtropical forests (Wang et al., 2018; Wang et al., 2009). In contrast, a recent study showed that the Hg deposition and soil Hg concentrations at a temperate forest in China were similar to those in Europe and North America (Zhou et al., 2020a). The forested area in China is 2.2 <inline-formula><mml:math id="M39" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msup></mml:math></inline-formula> km<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula>, with about 50 % and 40 % occurring in subtropical and temperate zones, respectively. Therefore, it seems likely that subtropical and temperate forests in China, with contrasting climate, vegetation cover and atmospheric Hg deposition, may also show different patterns of Hg cycling.</p>
      <p id="d1e607">Forest ecosystems act not only as sinks for atmospheric Hg deposition but
can also serve as sources resulting from legacy Hg that has accumulated in
surface soil. For example, one study constructed the Hg budget in a subtropical forest in southern China, showing that the forest is a minor sink
for atmospheric Hg but a significant net Hg(0) source  (58.5 <inline-formula><mml:math id="M42" 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="M43" 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="M44" 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>; Yu et al., 2020). In contrast, another study, also in southern China, using budgets of air–foliage and air–soil Hg(0) exchange fluxes, showed that forest is a net sink of Hg(0) (20.1 <inline-formula><mml:math id="M45" 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="M46" 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="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>; Yuan et al., 2019a, b). These results indicate that there is considerable uncertainty and variability in the source–sink behavior of Hg in subtropical forests of southern China.
Furthermore, no studies have been conducted in northern China to characterize the Hg fluxes in the temperate forest.</p>
      <p id="d1e675">There has been much research characterizing Hg fluxes between the forest
floor and the atmosphere from studies worldwide, as reviewed by Zhu et
al. (2016) and Agnan et al. (2016). In this paper, we present measurements on atmosphere–land Hg fluxes conducted over 130 and 96 d, respectively, during four seasons for five sites, both at a temperate forest catchment at Mount Dongling (MDL) and a subtropical forest catchment at Tieshanping Forest Park (TFP) in China. The aims of this investigation were to (1) characterize the air–land surface Hg fluxes in different terrestrial ecosystems, (2) conduct detailed field measurements to characterize the uncertainty of land use and climate change in air–surface fluxes of TGM in forest catchments,  and (3) compare estimates of Hg emissions from forest soils at temperate<?pagebreak page16119?> and subtropical zones. We hypothesize that a multiplot and multiseasonal study of soil–air fluxes in each forest system will provide new perspectives on climate change and land use on the soil–air Hg fluxes and improve our understanding and estimates of soil Hg evasion from forest ecosystems.</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 area</title>
      <p id="d1e693">This study was conducted at TFP in the subtropical zone (106<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>41.24<inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> E, 29<inline-formula><mml:math id="M50" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>37.42<inline-formula><mml:math id="M51" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> N) and at MDL in the temperate zone (115<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>26<inline-formula><mml:math id="M53" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> E, 40<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>00<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> N) in China (Fig. 1). The TFP is dominated by a Masson pine (<italic>Pinus massoniana</italic> Lamb.) stand (conifer) with some associated species, such as camphor (<italic>Cinnamomum camphora</italic>) and guger trees (<italic>Schima superba</italic> Gardner and Champ), which were
planted in the 1960s following the loss of a natural Masson pine forest. The
forest is located about 20 km northeast of Chongqing at an altitude
from 200 to 550 m. The mean annual precipitation is 1028 mm, with 75 % of the rainfall occurring from May to October. The mean annual air temperature is 18.2<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. The total area of the study forest in the TFP is 1.06 <inline-formula><mml:math id="M57" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> ha. The soil is typically mountain yellow earth
(corresponding to an Acrisol in the Food and Agriculture Organization (FAO) classification; FAO, 1988), with clay mineralogy dominated by kaolinite (Zhou et al., 2016).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e806">Location of the five sampling plots and the estimation of soil–air (SA) fluxes (values given as g m<inline-formula><mml:math id="M59" 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="M60" 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>) at the temperate
and subtropical forest. Potential vegetation of China is from the Vegetation
Map of China (Hou, 1982). Up and down arrows represent emission and
deposition, respectively.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f01.png"/>

        </fig>

      <p id="d1e839">Mount Dongling is near the Beijing Forest Ecosystem Research Station, Chinese
Academy of Sciences, which is located 110 km southwest of the Beijing megacity in northern China. The elevation is 1300 m above sea level (a.s.l.). The annual average rainfall is 612 mm and mean relative humidity is 66 %. The climate of the region is predominantly warm temperate continent monsoon, with an annual average temperature of 4.8 <inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and precipitation of 611.9 mm. The soil type is mountain brown earth (corresponding to a Eutric cambisol in FAO; FAO, 1988; Zhou et al., 2018). The relatively cool climate in the study area has resulted in deep litter and high organic matter concentrations (Fang et al., 2007). The study area is a mature, secondary forest protected since the 1950s following extensive deforestation. Hg concentrations in the environmental media at the site are provided in the Supplement.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Dynamic flux chamber (DFC) measurement</title>
      <p id="d1e859">To reduce the spatial uncertainty in Hg fluxes, different ecosystems were
selected for study in a subcatchment at the subtropical TFP, including a
coniferous forest (plots S–A and S–B), a wetland (plot S–C), a broad-leaved (camphor) forest (plot S–D), an open field with bare soil (plot S–E) and a subcatchment at the temperate MDL, including a Chinese pine forest (plot T–A), larch forest (plots T–B), wetland (plots T–C), mixed broad-leaved forest (plots T–D) and open field (plots T–E; Fig. 1). To reduce the temporal uncertainty in Hg fluxes, 130 and 96 d of flux observations were undertaken over four seasons (about 1 month of continuous observations for each season, except for 1 week during winter at the MDL; Table S1 in the Supplement). The locations of each plot are described in Table 1 and illustrated in Fig. 1.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T1" orientation="landscape"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e865">Locations and summary of measurements (mean and standard deviation) of soil–air TGM fluxes and environmental parameters at 10 plots at the subtropical and temperate forests. Note: SOM – soil organic matter.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.91}[.91]?><oasis:tgroup cols="10">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="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:thead>
       <oasis:row>
         <oasis:entry colname="col1">Forest</oasis:entry>
         <oasis:entry colname="col2">Plots</oasis:entry>
         <oasis:entry colname="col3">Locations</oasis:entry>
         <oasis:entry colname="col4">Flux</oasis:entry>
         <oasis:entry colname="col5">Soil surface TGM</oasis:entry>
         <oasis:entry colname="col6">Soil Hg concentration</oasis:entry>
         <oasis:entry colname="col7">SOM</oasis:entry>
         <oasis:entry colname="col8">Soil moisture</oasis:entry>
         <oasis:entry colname="col9">Soil temperature</oasis:entry>
         <oasis:entry colname="col10">Solar radiation</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">(ng m<inline-formula><mml:math id="M62" 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> h<inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col5">(ng m<inline-formula><mml:math id="M64" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col6">(ng g<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col7">(0–5, %)</oasis:entry>
         <oasis:entry colname="col8">(%)</oasis:entry>
         <oasis:entry colname="col9">(<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col10">(W m<inline-formula><mml:math id="M67" 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>)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Subtropical forest</oasis:entry>
         <oasis:entry colname="col2">Plot S–A</oasis:entry>
         <oasis:entry colname="col3">Top slope of coniferous forest</oasis:entry>
         <oasis:entry colname="col4">2.8 <inline-formula><mml:math id="M68" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.9</oasis:entry>
         <oasis:entry colname="col5">3.6 <inline-formula><mml:math id="M69" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.3</oasis:entry>
         <oasis:entry colname="col6">219 <inline-formula><mml:math id="M70" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 15</oasis:entry>
         <oasis:entry colname="col7">13.6</oasis:entry>
         <oasis:entry colname="col8">0.3 <inline-formula><mml:math id="M71" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col9">16.8 <inline-formula><mml:math id="M72" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.6</oasis:entry>
         <oasis:entry colname="col10">39.9 <inline-formula><mml:math id="M73" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 27.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot S–B</oasis:entry>
         <oasis:entry colname="col3">Middle slope of coniferous forest</oasis:entry>
         <oasis:entry colname="col4">3.5 <inline-formula><mml:math id="M74" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.2</oasis:entry>
         <oasis:entry colname="col5">3.8 <inline-formula><mml:math id="M75" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.3</oasis:entry>
         <oasis:entry colname="col6">263 <inline-formula><mml:math id="M76" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 22</oasis:entry>
         <oasis:entry colname="col7">16.3</oasis:entry>
         <oasis:entry colname="col8">0.4 <inline-formula><mml:math id="M77" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col9">16.9 <inline-formula><mml:math id="M78" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.7</oasis:entry>
         <oasis:entry colname="col10">40.2 <inline-formula><mml:math id="M79" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 27.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot S–C</oasis:entry>
         <oasis:entry colname="col3">Wetland</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.80</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M81" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.1</oasis:entry>
         <oasis:entry colname="col5">3.7 <inline-formula><mml:math id="M82" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.4</oasis:entry>
         <oasis:entry colname="col6">96 <inline-formula><mml:math id="M83" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 43</oasis:entry>
         <oasis:entry colname="col7">4.9</oasis:entry>
         <oasis:entry colname="col8">0.3 <inline-formula><mml:math id="M84" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col9">16.7 <inline-formula><mml:math id="M85" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.5</oasis:entry>
         <oasis:entry colname="col10">30.5 <inline-formula><mml:math id="M86" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 27.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot S–D</oasis:entry>
         <oasis:entry colname="col3">Broad-leaved forest</oasis:entry>
         <oasis:entry colname="col4">0.18 <inline-formula><mml:math id="M87" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.3</oasis:entry>
         <oasis:entry colname="col5">3.3 <inline-formula><mml:math id="M88" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.4</oasis:entry>
         <oasis:entry colname="col6">156 <inline-formula><mml:math id="M89" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 17</oasis:entry>
         <oasis:entry colname="col7">8.8</oasis:entry>
         <oasis:entry colname="col8">0.3 <inline-formula><mml:math id="M90" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col9">16.9 <inline-formula><mml:math id="M91" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.6</oasis:entry>
         <oasis:entry colname="col10">20.3 <inline-formula><mml:math id="M92" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 27.9</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot S–E</oasis:entry>
         <oasis:entry colname="col3">Open field</oasis:entry>
         <oasis:entry colname="col4">24 <inline-formula><mml:math id="M93" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 33</oasis:entry>
         <oasis:entry colname="col5">4.1 <inline-formula><mml:math id="M94" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.7</oasis:entry>
         <oasis:entry colname="col6">159 <inline-formula><mml:math id="M95" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 18</oasis:entry>
         <oasis:entry colname="col7">4.1</oasis:entry>
         <oasis:entry colname="col8">0.3 <inline-formula><mml:math id="M96" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col9">18.3 <inline-formula><mml:math id="M97" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8.5</oasis:entry>
         <oasis:entry colname="col10">98.0 <inline-formula><mml:math id="M98" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 138.4</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Temperate forest</oasis:entry>
         <oasis:entry colname="col2">Plot T–A</oasis:entry>
         <oasis:entry colname="col3">Chinese pine forest</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M100" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.81</oasis:entry>
         <oasis:entry colname="col5">2.22 <inline-formula><mml:math id="M101" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.87</oasis:entry>
         <oasis:entry colname="col6">72 <inline-formula><mml:math id="M102" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 12</oasis:entry>
         <oasis:entry colname="col7">5.8</oasis:entry>
         <oasis:entry colname="col8">17.0 <inline-formula><mml:math id="M103" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8.55</oasis:entry>
         <oasis:entry colname="col9">9.77 <inline-formula><mml:math id="M104" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.57</oasis:entry>
         <oasis:entry colname="col10">17.09 <inline-formula><mml:math id="M105" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 29.4</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot T–B</oasis:entry>
         <oasis:entry colname="col3">Larch forest</oasis:entry>
         <oasis:entry colname="col4">0.32 <inline-formula><mml:math id="M106" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.96</oasis:entry>
         <oasis:entry colname="col5">2.30 <inline-formula><mml:math id="M107" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.94</oasis:entry>
         <oasis:entry colname="col6">141 <inline-formula><mml:math id="M108" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 15</oasis:entry>
         <oasis:entry colname="col7">25</oasis:entry>
         <oasis:entry colname="col8">26.3 <inline-formula><mml:math id="M109" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.51</oasis:entry>
         <oasis:entry colname="col9">10.0 <inline-formula><mml:math id="M110" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.23</oasis:entry>
         <oasis:entry colname="col10">22.9 <inline-formula><mml:math id="M111" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 18.6</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot T–C</oasis:entry>
         <oasis:entry colname="col3">Wetland</oasis:entry>
         <oasis:entry colname="col4">3.81 <inline-formula><mml:math id="M112" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.52</oasis:entry>
         <oasis:entry colname="col5">2.47 <inline-formula><mml:math id="M113" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.92</oasis:entry>
         <oasis:entry colname="col6">156 <inline-formula><mml:math id="M114" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 21</oasis:entry>
         <oasis:entry colname="col7">47</oasis:entry>
         <oasis:entry colname="col8">42.9 <inline-formula><mml:math id="M115" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8.22</oasis:entry>
         <oasis:entry colname="col9">10.0 <inline-formula><mml:math id="M116" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.55</oasis:entry>
         <oasis:entry colname="col10">22.1 <inline-formula><mml:math id="M117" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 19.4</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot T–D</oasis:entry>
         <oasis:entry colname="col3">Mixed broad-leaved forest</oasis:entry>
         <oasis:entry colname="col4">0.68 <inline-formula><mml:math id="M118" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.01</oasis:entry>
         <oasis:entry colname="col5">2.37 <inline-formula><mml:math id="M119" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.87</oasis:entry>
         <oasis:entry colname="col6">74 <inline-formula><mml:math id="M120" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 9</oasis:entry>
         <oasis:entry colname="col7">16</oasis:entry>
         <oasis:entry colname="col8">25.4 <inline-formula><mml:math id="M121" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.32</oasis:entry>
         <oasis:entry colname="col9">9.86 <inline-formula><mml:math id="M122" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.26</oasis:entry>
         <oasis:entry colname="col10">25.9 <inline-formula><mml:math id="M123" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 18.6</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Plot T–E</oasis:entry>
         <oasis:entry colname="col3">Open field</oasis:entry>
         <oasis:entry colname="col4">1.82 <inline-formula><mml:math id="M124" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.79</oasis:entry>
         <oasis:entry colname="col5">1.98 <inline-formula><mml:math id="M125" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.79</oasis:entry>
         <oasis:entry colname="col6">52 <inline-formula><mml:math id="M126" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4</oasis:entry>
         <oasis:entry colname="col7">12</oasis:entry>
         <oasis:entry colname="col8">27.9 <inline-formula><mml:math id="M127" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.56</oasis:entry>
         <oasis:entry colname="col9">10.1 <inline-formula><mml:math id="M128" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.47</oasis:entry>
         <oasis:entry colname="col10">47.1 <inline-formula><mml:math id="M129" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 29.4</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <p id="d1e1806">Semi-cylindrical quartz glass and open-bottom DFCs (4.71 L) were utilized
during the sampling campaign. The area of the DFCs over the soil surface was
20 <inline-formula><mml:math id="M130" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 30 cm, with six inlet holes (1 cm diameter; Supplement Fig. S1). Local fine-grained soil was placed outside the chamber to seal any gaps between the base of the chamber and the soil. At the outlet of the chamber, an orifice was connected to two exit tubes; one was connected to a regulated suction pump and the other to a gold cartridge for trapping outlet TGM. A substream of air was trapped by a pair of gold quartz cartridges at a flow rate of 0.5 L min<inline-formula><mml:math id="M131" 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 was measured using an integrating volume flow meter. All the gold cartridges were constructed with gold silk (<inline-formula><mml:math id="M132" display="inline"><mml:mrow><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula> mm diameter). The strands of gold silk were rolled together in a small coil, and about 15 coils were used to fill a quartz cartridge with about 2 g of gold. The accuracy of all traps was evaluated (see Sect. 2.4), and non-conforming cartridges were discarded. The chamber flushing flow turnover time (TOT) was 0.47 and 0.94 min for the subtropical forest and temperate forest plots, respectively. The Hg flux was calculated using the following equation:
            <disp-formula id="Ch1.Ex1"><mml:math id="M133" display="block"><mml:mrow><mml:mi>F</mml:mi><mml:mo>=</mml:mo><mml:mo>(</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">o</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub><mml:mo>)</mml:mo><mml:mo>×</mml:mo><mml:mi>Q</mml:mi><mml:mo>/</mml:mo><mml:mi>A</mml:mi><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M134" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> is the soil Hg flux (ng m<inline-formula><mml:math id="M135" 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> h<inline-formula><mml:math id="M136" 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="M137" display="inline"><mml:mrow><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">o</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M138" display="inline"><mml:mrow><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> are the steady-state Hg concentrations (ng m<inline-formula><mml:math id="M139" 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>) of the outlet and inlet air streams, respectively, which were calculated by the Hg mass detected in gold cartridges and the corresponding air volume. <inline-formula><mml:math id="M140" display="inline"><mml:mi>A</mml:mi></mml:math></inline-formula> is the surface area enclosed by the DFC. <inline-formula><mml:math id="M141" display="inline"><mml:mi>Q</mml:mi></mml:math></inline-formula> is the flow rate of ambient air circulating through the DFC (10 L min<inline-formula><mml:math id="M142" 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> for TFP and 5 L min<inline-formula><mml:math id="M143" 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> for MDL).</p>
      <p id="d1e1982">High flow rates and short TOTs are appropriate for measuring flux from soils
with high Hg concentrations or emissions, while lower flow rates and longer
TOTs are more appropriate for soils with low Hg concentrations or emissions.
Eckley et al. (2010) suggested that the optimal flow was at the beginning of
the stable <inline-formula><mml:math id="M144" display="inline"><mml:mrow><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">o</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>C</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M145" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math></inline-formula>) period, which was chosen as a compromise between competing criteria aimed at creating conditions inside
the DFC similar to the adjacent outside air. Our previous study showed that
when <inline-formula><mml:math id="M146" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>C</mml:mi></mml:mrow></mml:math></inline-formula> was relatively stable, the corresponding flushing flow rate
was from 5 to 10 L min<inline-formula><mml:math id="M147" 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> at the subtropical forest (Zhou et al.,
2017a). To avoid the suppression of Hg emissions due to the excessive buildup of Hg within the chamber, the flow rate of ambient air circulated through the
DFC was 10 L min<inline-formula><mml:math id="M148" 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> at the subtropical forest. At the temperate forest,
the soil Hg concentrations were about 3–4 times lower than those at the
subtropical forest, so the lower flow rate of 5 L min<inline-formula><mml:math id="M149" 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> was used at
these plots. The DFC chambers in all plots were moved every week to mitigate
against changes in soil moisture due the covering of soil by the chambers.
If a precipitation event occurred, the chambers were also moved to<?pagebreak page16120?> new
positions during the sampling period (morning or evening) to be representative of soil conditions receiving ambient precipitation.</p>
      <p id="d1e2060">The pair of gold cartridges for each DFC was collected twice a day, namely every morning (at about 08:00 local time – LT; hereafter, all times are given in LT and afternoon (about 17:00) representing night (17:00–08:00 of the next day) and day (08:00–17:00) emissions, respectively. A total of 20 gold quartz cartridges were alternated during the sampling program. In addition, diurnal variations in soil–air Hg fluxes were also conducted in each season, with gold cartridges collected every 30 min. A total of four diurnal measurements were conducted over the study in each forest, with diurnal variations being measured on 1 d per season. It has been reported that the DFC measurements can introduce bias under a given design, flushing air flow rates and environmental condition (Lin et al., 2010; Zhang et al., 2002). The DFC enclosure imposes a physical constraint that can lead to accumulation in or evasion from the soil surface under measurement. Extensive experiments were conducted at our plot sites to determine the appropriate experimental conditions for accurate measurements. We followed recommendations made by  Eckley et al. (2010) for our measurements.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Environmental measurements</title>
      <p id="d1e2071">At each sampling plot, soil samples were collected from the DFC footprint
(0–5 cm). Soil Hg and soil organic matter (SOM) concentrations were
measured using a DMA-80 direct Hg analyzer (Milestone Srl, Italy) and loss
on ignition (LOI) method, respectively, using methods detailed in the SI.
Soil percent moisture and temperature were monitored with a time domain
reflectometer (TDR) Hydra Probe II (SDI<inline-formula><mml:math id="M150" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>12/RS485) and a water
cable tester (Stevens Water Monitoring Systems, Inc., USA). Solar radiation was measured by a weather station (Vantage Vue 06250 Wireless Weather Station; Davis Instruments Corporation, USA) located in the TFP Forest Station and Beijing Forest Ecosystem Research Station, within about 500 m of each plot.</p>
</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><?xmltex \opttitle{Quality assurance and quality control (QA$/$QC)}?><title>Quality assurance and quality control (QA<inline-formula><mml:math id="M151" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>QC)</title>
      <p id="d1e2097">All cartridges were transported to a laboratory at the TFP Forest Station
for Hg determination using a cold vapor atomic fluorescence spectroscopy
(CVAFS) detector (Brooks Rand Instruments). The limit of detection, based on 3 times the standard deviation of replicate measurements of the blank was 1 pg. Based on the sampled air volume, the detection limits were <inline-formula><mml:math id="M152" display="inline"><mml:mi mathvariant="italic">&lt;</mml:mi></mml:math></inline-formula> 0.10 ng m<inline-formula><mml:math id="M153" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. A calibration curve was<?pagebreak page16121?> developed using Hg saturated air, and the calibration curve was required to have a correlation coefficient greater than 0.99 before the sample analysis could proceed. Before and after the measurement of the sampling cartridges on each day, standard Hg saturated air was injected to test the accuracy of the Hg analyzer. If the deviation of the measured Hg mass was higher than 5 %, a new calibration curve would be developed.</p>
      <p id="d1e2119">A controlled volume of saturated Hg air at a known temperature was injected
to measure the Hg recovery from the gold cartridges before and after the
campaigns in each season. The recoveries of gold cartridges before and after
the operation ranged from 98.8 % to 103.2 % and 96.3 % to 102.5 % (<inline-formula><mml:math id="M154" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 155; average <inline-formula><mml:math id="M155" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 98.9 %), respectively. The collection efficiency of Hg vapor by the gold cartridges was determined by connecting two cartridges in sequence and sampling the ambient air over 24 h in the laboratory. For all cartridges, less than 1 % Hg was detected on the second cartridges compared to the first cartridge, indicating that more than <inline-formula><mml:math id="M156" display="inline"><mml:mi mathvariant="italic">&gt;</mml:mi></mml:math></inline-formula> 99 % of the TGM was absorbed by the gold cartridges during the field operation. For comparison, Hg fluxes were measured by two side-by-side chambers simultaneously. Blanks of the soil TGM flux sampling systems were measured by placing the DFC on a quartz glass surface in the five plots. The sampling time for the blank measurements was the same as the soil–air TGM flux measurements, which were collected at 08:00 and 17:00, representing night (17:00–08:00 of the next day) and day (08:00–17:00) emissions, respectively. The averaged blank was 0.13 <inline-formula><mml:math id="M157" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.21 ng m<inline-formula><mml:math id="M158" 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> h<inline-formula><mml:math id="M159" 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="M160" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 10), which was subtracted from the soil–air TGM flux for each season.</p>
</sec>
<sec id="Ch1.S2.SS5">
  <label>2.5</label><title>Statistical analysis</title>
      <p id="d1e2197">Structural equation modeling (SEM) was performed on the collected Hg flux
data using Amos software. SEM, developed from a fully conceptual model using
<inline-formula><mml:math id="M161" display="inline"><mml:mrow><mml:mi mathvariant="italic">χ</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> tests with maximum likelihood estimation, was conducted to infer
the interplay of temperature, solar radiation, soil moisture and air TGM
concentrations on measurements of soil–air TGM exchange fluxes. Seasonal and
annual fluxes were compared among the 10 plots. Separate two-way analyses of variance (ANOVA) were used to determine if differences in Hg fluxes existed among the seasons and sites. All differences in mean values were significant at the <inline-formula><mml:math id="M162" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 0.05 level, and all means are reported with <inline-formula><mml:math id="M163" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1 standard deviation from the mean. The correlations between environmental parameters and fluxes were analyzed by Pearson's correlation tests, using SPSS statistics software (SPSS Inc., 16.0), and correlation coefficient and <inline-formula><mml:math id="M164" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> values are presented and significantly correlated at the level of 0.05.</p><?xmltex \hack{\newpage}?>
</sec>
</sec>
<?pagebreak page16122?><sec id="Ch1.S3">
  <label>3</label><title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Landscape and forest species dependence on soil–air Hg fluxes at the forest catchment scale</title>
      <p id="d1e2251">The soil TGM flux measurements for the five plots were calculated for the
day and night and reported as mean daily fluxes with standard deviations
(SDs) at the subtropical (Fig. 2a) and temperate forests (Fig. 2b). Over the
course of the campaigns, net TGM emission was observed at the open field (24 <inline-formula><mml:math id="M165" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 33 ng m<inline-formula><mml:math id="M166" 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> h<inline-formula><mml:math id="M167" 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>), coniferous forest (upper elevation 2.8 <inline-formula><mml:math id="M168" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.9 ng m<inline-formula><mml:math id="M169" 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> h<inline-formula><mml:math id="M170" 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>, mid elevation 3.5 <inline-formula><mml:math id="M171" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.2 ng m<inline-formula><mml:math id="M172" 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> h<inline-formula><mml:math id="M173" 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>) and the broad-leaved forest (0.18 <inline-formula><mml:math id="M174" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>  4.3 ng m<inline-formula><mml:math id="M175" 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> h<inline-formula><mml:math id="M176" 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>), while net deposition was evident at the wetland (<inline-formula><mml:math id="M177" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.80 <inline-formula><mml:math id="M178" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.1 ng m<inline-formula><mml:math id="M179" 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> h<inline-formula><mml:math id="M180" 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, at the subtropical forest. At the temperate forest, net TGM emission was observed at the wetland (3.81 <inline-formula><mml:math id="M181" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.52 ng m<inline-formula><mml:math id="M182" 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> h<inline-formula><mml:math id="M183" 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>), open field (1.82 <inline-formula><mml:math id="M184" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.79 ng m<inline-formula><mml:math id="M185" 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> h<inline-formula><mml:math id="M186" 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>), mixed broad-leaved forest (0.68 <inline-formula><mml:math id="M187" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.01 ng m<inline-formula><mml:math id="M188" 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> h<inline-formula><mml:math id="M189" 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>) and larch forest (0.32 <inline-formula><mml:math id="M190" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.96 ng m<inline-formula><mml:math id="M191" 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> h<inline-formula><mml:math id="M192" 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>), while net deposition was evident at the Chinese pine forest (<inline-formula><mml:math id="M193" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.04 <inline-formula><mml:math id="M194" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.81 ng m<inline-formula><mml:math id="M195" 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> h<inline-formula><mml:math id="M196" 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. The fluxes at the temperate forest were 10 times lower than values at the subtropical forest due to different environmental factors, such as lower temperature, solar radiation and soil Hg concentrations (see Sect. 3.3).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e2585">Mean and standard deviations of soil–air TGM fluxes at the five
plots for the four seasons and annual values during the study at the
subtropical forest <bold>(a)</bold> and temperate forest <bold>(b)</bold>. The number of flux observations in spring, summer, autumn and winter were 62, 92, 66 and 43 at the subtropical forest and 60, 58, 60 and 14 for the temperate forest,
respectively.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f02.png"/>

        </fig>

      <p id="d1e2600">These patterns suggest that soil–air Hg fluxes at the catchment scale vary according to soil properties (e.g., soil Hg concentration, moisture and soil organic matter – SOM) and forest species composition. High variability, as evidenced by high SD and coefficient of variation (SD<inline-formula><mml:math id="M197" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>mean, with a range of 14 %–2374 %), was evident in the daily Hg fluxes largely driven by meteorological variation. The fluxes at the subtropical forest plots of this study were much lower than those reported for other subtropical evergreen forests in China, such as Mount Gongga (0.5–9.3 ng m<inline-formula><mml:math id="M198" 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> h<inline-formula><mml:math id="M199" 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>)  (Fu et al., 2008), Mount Jinyun (14.2 ng m<inline-formula><mml:math id="M200" 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> h<inline-formula><mml:math id="M201" 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>; Ma et al., 2013) and Mount Simian (11.23 ng m<inline-formula><mml:math id="M202" 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> h<inline-formula><mml:math id="M203" 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>; Ma et al., 2018), all of which were generally conducted during sunny days. Our flux measurements at the temperate forest were slightly lower or comparable to those in North American deciduous forests, ranging from <inline-formula><mml:math id="M204" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.73 to 2.7 ng m<inline-formula><mml:math id="M205" 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> h<inline-formula><mml:math id="M206" 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> (Choi and Holsen, 2009b; Hartman et al., 2009; Carpi et al., 2014; Ma et al., 2018). These results demonstrated that measurements over several days may exhibit considerable temporal variability, and a long-term study should be undertaken to reduce the uncertainty in temporal patterns of soil Hg emissions.</p>
      <p id="d1e2715">The mean TGM fluxes in the open fields were about 10 and 6 times higher than
those under the forest canopy at the subtropical and temperate forests,
respectively (<inline-formula><mml:math id="M207" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> &lt; 0.001). Our results are consistent with those of Ma et al. (2013) and Xin and Gustin (2007), which show large Hg evasion following forest conversion to bare soils, due to direct exposure to sunlight, as fluxes were enhanced by increases in solar radiation and temperature. Due to frequent heavy rains at the subtropical forest catchment, a large amount of surface runoff impacted the wetland (plot S–C). Elevated runoff may have decreased Hg (96 <inline-formula><mml:math id="M208" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 43 ng g<inline-formula><mml:math id="M209" 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>) and SOM in surface soils due to erosion (Table 1). This site had the lowest TGM fluxes of the plots studied at the subtropical forest (overall net sink). In addition, soils in the wetland plot were mostly saturated throughout the year, limiting Hg fluxes and likely contributing to the sink behavior. In contrast, the mean annual rainfall was 40 % lower at the temperate forest, and the wetland was located at relatively lower terrain. Litter from surrounding higher terrain forest accumulated in the low-lying wetland. The cool and dry climate also contributed to high organic matter and low bulk density (Fang et al.,
2007). Higher SOM likely facilitated the binding of trace metals, leading to
high soil Hg concentrations (117 ng g<inline-formula><mml:math id="M210" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> at the temperate wetland.
These conditions were conducive to biological activity, promoting the
mineralization of SOM and the release of volatile Hg(0) from the soil (Choi
and Holsen, 2009b; Osterwalder et al., 2019). The wetland had the highest TGM
fluxes of the plots studied at the temperate forest (overall net source).
Previous studies have suggested that soil water is able to mobilize Hg from
binding sites on the soil (Gustin, 2003; Kocman and Horvat, 2010) and high
soil water decreases soil redox potential (Zarate-Valdez et al., 2006), both of which can facilitate the conversion of Hg(II) to Hg(0). Additionally, the climate is relatively dry in northern China, especially in spring. The high solar radiation and relatively high air temperature enhance not only the reduction of Hg(II) to Hg(0) but also increase water evaporation compared to other study sites. Enhanced water evaporation at a higher temperature facilitates Hg emissions from soils (Gustin and Stamenkovic, 2005; Lin et al., 2010). Additionally, given that Hg conversion to Hg(0) in soil profiles occurs mainly via biotic processes, maximum aerobic microbial activity has been delineated at a soil water content equivalent to 60 % of a soil's water-holding capacity (Breuer et al., 2002; Kiese and Butterbach-Bahl, 2002). Appropriate soil moisture in the wetland would likely enhance the microbial reduction of Hg(II) to Hg(0). Therefore, the highest Hg flux was observed in the temperate wetland, especially in spring. The main reasons for the significant differences between the soil Hg fluxes at the two wetland sites are likely that the saturated soil at the subtropical forest inhibited Hg(0) evasion (Gustin and Stamenkovic, 2005; see Sect. 3.3).</p>
      <p id="d1e2759">At the subtropical forest, litterfall in the broad-leaved (camphor) plot
(plot S–D) was twice as high as that of the coniferous (pine) plot (plots
S–A and S–B; Zhou et al., 2018), likely resulting in greater shielding
of sunlight to the surface soil and limiting soil Hg evasion. Increases in
light transmission through the canopy increase both solar radiation and soil
temperature, which can enhance the photochemical reduction of Hg(II) at the soil surface and Hg(0) evasion. In the mid-slope of the pine stand (plot S–B), soil Hg concentration was elevated compared to the upslope plot (Table 1), with correspondingly higher soil Hg fluxes. At the temperate forest, the lowest Hg flux and overall deposition<?pagebreak page16123?> was observed at the evergreen forest of Chinese pine, where the canopy cover likely limited Hg flux by decreasing solar radiation to soil and warming. Similarly, at the subtropical forest, the needle biomass in the larch plot was about 2.5 times greater as that in the mixed broad-leaved plot (plot T–D) at the temperate forest, resulting in shielding of the sunlight to the surface soil and limiting soil Hg evasion at the larch plot.</p>
      <p id="d1e2762">The forest canopy influences not only the soil Hg concentration by mediating
the atmospheric Hg deposition (Zhou et al.,  2017a, 2018) but also alters soil physiochemical properties (e.g., SOM, pH and porosity; Mo et al., 2011) and microbial communities (Nagati et al., 2020), which in turn affects soil–air exchange. For example, the annual litterfall Hg deposition flux at the broad-leaved plot (91 <inline-formula><mml:math id="M211" 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="M212" 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="M213" 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>) at the subtropical forest was approximately 2 times greater than the coniferous
plot (41 <inline-formula><mml:math id="M214" 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="M215" 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="M216" 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>; Zhou et al., 2018). Conversely,
the SOM and soil Hg concentrations in the broad-leaved forest were lower
than the coniferous forest. Moreover, the litter decomposition rate was lower, but the Hg mass accumulation in the litter was much higher in the coniferous forest compared to the broad-leaved forest due to higher throughfall Hg deposition at the coniferous plot  (Zhou et al., 2018), which resulted in a seemingly inconsistent pattern between litterfall mass and SOM and litterfall Hg deposition and soil Hg concentrations. At the temperate
forest, the higher litterfall Hg deposition and lower litter decomposition
in the larch plot compared to the broad-leaved plot (Zhou et al., 2017a) resulted in significantly higher SOM and soil Hg concentrations (Table 1). Tree species can change the physicochemical properties of soil (e.g., SOM and soil Hg concentrations) and influence soil–air exchange. These biological factors likely contribute to the much lower TGM evasion in the broad-leaved plot than the coniferous plot at the subtropical forest but much higher TGM evasion in the broad-leaved plot than the deciduous needle (larch) plot at the temperate forest (Fig. 2).</p>
      <p id="d1e2830">Most studies measure soil TGM fluxes at only one location or at a single
forest stand to characterize the whole ecosystem. Our observations clearly
show that soil–air Hg fluxes vary substantially across different plots (Fig. 2), indicating that forest type/cover and landscape position significantly affect the TGM fluxes, and therefore, the spatial variability in soil Hg fluxes among different subplots must be considered. Based on the areal distribution of each plot type in the study subcatchments of the
subtropical forest (coniferous upland and mid-slope, broad-leaved, wetland and open; 4.6 ha) and the temperate forest (Chinese pine, larch, wetland, mixed broad-leaved and open; 5.0 ha; Table S1), the area-weighted TGM flux was 3.2 and 0.32 ng m<inline-formula><mml:math id="M217" 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> h<inline-formula><mml:math id="M218" 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> for the entire subtropical and temperate catchments, respectively. The area-weighted TGM fluxes were 14 % higher than plot S–A and 16 % lower than plot S–B of the Masson pine stand at the subtropical forest and were 907 % higher than Chinese pine plot and 53 % lower than mixed broad-leaved plot at the temperate forest, respectively. The observations at several plots with diverse forest cover in this study should reduce the overall uncertainty associated with soil–air fluxes of TGM in the overall forest catchment.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Seasonal variations in soil–air Hg fluxes at the forest catchment scale</title>
      <p id="d1e2865">Soil TGM fluxes exhibited not only clear seasonal variations at all the
plots but were also responsive to phenological and meteorological patterns.
At the subtropical forest, soil Hg fluxes were generally the highest in the
summer (Fig. 2a), which showed net emissions at all the five plots, followed
by spring and autumn, with the lowest values during winter, which exhibited
net deposition at all plots, with the exception of plot S–B. The observed
seasonal variation was dependent on sunlight (Fig. 3) because solar
radiation<?pagebreak page16124?> drives the photochemical reduction of Hg(II) (note the correlation
between the TGM fluxes and solar radiation; Fig. S2). Additionally, greater
solar radiation increases temperature, which promotes the production of soil
Hg gas by biological and abiotic processes. At the temperate forest, the Hg
fluxes were the highest in the deciduous forest plot (wetland, mixed
broad-leaved forest and larch forest) in spring, before leaf-out, when solar
radiation could directly reach the forest floor (Fig. S3). In the open field
and evergreen forest (Chinese pine forest) plots, the Hg fluxes were highest
in summer, with the highest solar radiation and temperature (Figs. 4 and S3). The lowest Hg fluxes were measured in the winter at all plots when the
soil was covered with snow, with net Hg emission observed at the open field
and net deposition observed at the other four sites (Fig. 2b).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e2870">Daily (average flux of day and night) composite Hg flux, solar
radiation and soil temperature at a Masson pine forest <bold>(a, b)</bold> and wetland <bold>(c)</bold>, evergreen broad-leaved forest <bold>(d)</bold> and open field <bold>(e)</bold> plots in a subtropical forest. The vertical arrows represent precipitation events.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f03.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e2893">Daily (average flux of day and night) composite Hg flux, solar
radiation and soil temperature at a Chinese pine forest <bold>(a)</bold>, larch forest <bold>(b)</bold>, wetland <bold>(c)</bold>, mixed broad-leaved forest <bold>(d)</bold> and open field <bold>(e)</bold> plots in a
temperate forest. The vertical arrows represent precipitation events.</p></caption>
          <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f04.png"/>

        </fig>

      <p id="d1e2918">We also observed strong variations in TGM evasion under different weather
conditions. Rain events decreased TGM fluxes at all plots in both forests
(Fig. S4) as the rainwater decreased soil pore space, leading to decreases
in evasion from the soil. Furthermore, the solar radiation and temperature
during rainy days was much lower than those for sunny days for a given
season (Figs. 3 and 4). Manca et al. (2013) studied snow–air Hg exchange at Ny-Ålesund, showing on average a small net deposition <inline-formula><mml:math id="M219" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.24 ng m<inline-formula><mml:math id="M220" 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> h<inline-formula><mml:math id="M221" 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>. Likewise, overall deposition between <inline-formula><mml:math id="M222" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.6 and <inline-formula><mml:math id="M223" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>23.8 ng m<inline-formula><mml:math id="M224" 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> h<inline-formula><mml:math id="M225" 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> was observed at snow-covered agricultural areas in northeastern China (Wang et al., 2013; Zhang et al., 2013). However, some studies of snowpack have shown net Hg deposition at nighttime and net
emissions during daytime due to high solar radiation (Maxwell et al.,
2013; Spolaor et al., 2019). Empirical models suggest that most of the Hg(0)
deposited to snow was re-emitted back to the atmosphere (Durnford
and Dastoor, 2011). During the campaigns in winter, the solar radiation was
relatively lower, which may be why net deposition occurred (Fig. 4).
Additionally, refrozen ice/snow layers are characterized by elevated Hg
concentrations, and the deposited Hg from atmosphere could be potentially
released to meltwater (Zhang et al., 2012; Perez-Rodriguez et al., 2019),
which is consistent with our results that atmospheric Hg deposition could be
released to meltwater during snow melt. Our observations through the annual
climatic cycle reduce the uncertainty and bias of temporal patterns of soil–air Hg fluxes. Moreover, multiplot observations reduce the uncertainty and bias associated with spatial variation. Together, these more detailed measurements improved estimates of overall ecosystem soil Hg evasion and confirm our hypothesis.</p>
</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Correlations between environmental factors and fluxes</title>
      <p id="d1e2999">To investigate the correlation between soil–atmosphere fluxes and
environmental factors, data over the four seasons were used. These data
offer a long, continuous time series for the five measurement plots in each
forest (Figs. 3 and 4). According to a global database, atmospheric fluxes at
Hg-enriched sites are positively correlated with substrate Hg concentrations, but this relationship is not observed at sites with lower background concentrations of soil Hg (Agnan et al., 2016). Our soil Hg fluxes were strongly correlated with soil Hg concentrations at vegetated sites (forests and wetland) at the subtropical forest (Fig. S5) but not at the temperate forest.</p>
      <p id="d1e3002">Photo-reduction is a major driver of TGM evasion from the Earth's surface
(Howard and Edwards, 2018; Kuss et al., 2018; Gao et al., 2020). This
process is due to a photochemically mediated reduction that converts soil
water Hg(II) to volatile Hg(0) and enhances the Hg(0) pool in soil pores (Xin and Gustin, 2007; Choi and Holsen, 2009a). Therefore, the elevated soil pore Hg(0) concentrations increased the potential for TGM diffusion from the soil to the atmosphere, which drives an increase of Hg emissions from soil. At all the study sites, no matter the daily average fluxes (Figs. 3 and 4), daytime fluxes (Figs. S2 and S3) were all significantly correlated with solar radiation, and the solar radiation also increased daytime fluxes compared to nighttime values (Fig. S6). In the evergreen plots of the subtropical (plots S–A, S–B and S–D) and temperate (plot T–A) forests, Hg fluxes were the most highly dependent on soil temperature compared to the solar radiation during the four seasons, likely due to evergreen canopy limiting solar radiation to the forest floor. With the consistent shade of the coniferous forest canopy, the Hg flux was highly dependent on soil surface temperature rather than solar radiation to the forest floor.</p>
      <p id="d1e3005">To consider the synergistic effects from multiple factors, SEM was applied to
infer the soil–air TGM exchange processes (Fig. 5). It is clear that
temperature was a more dominant factor driving the air–soil TGM exchange flux over the four seasons in the subtropical forest plots, while solar radiation was a more dominant factor at the temperate forest due to direct exposure of the forest floor to solar radiation the leaf-off seasons. At the open fields of both forests, temperature and solar radiation had a synergistic effect on soil Hg fluxes. A recent study of soil–air TGM fluxes at a subtropical evergreen broadleaf forest in southern China also suggested that temperature is the most important driver of air–soil TGM exchange  (Yuan et al., 2019b). Therefore, we may infer that, under the shade of the forest canopy, temperature is the dominant factor causing variation in TGM evasion from forest soil.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e3011">Interplays of environmental factors on the air–soil TGM exchange flux, obtained by structural equation model (SEM), in the temperate <bold>(a)</bold> and subtropical <bold>(b)</bold> forests.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f05.png"/>

        </fig>

      <p id="d1e3026">Mercury fluxes in wetlands in both forests (plots S–C and T–C) were less
strongly correlated with soil temperature compared to the other plots in
both forests (Figs. S7 and S8). Generally, temperature is an important factor
that promotes TGM evasion after its formation from Hg(II), more by biotic
than abiotic processes in soils (Pannu et al., 2014). The Hg(0) in
soil pore gas mainly results from biotic production. For example, soil
sterilization can decrease the Hg converted to Hg(0) by <inline-formula><mml:math id="M226" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> %;
additionally, 1 % of the soil Hg is converted to Hg(0) via abiotic
processes, compared to<?pagebreak page16125?> 6.8 % by biotic processes at 283 K, and the
fraction of Hg reduction by biotic processes increases with temperature
increases (Pannu et al., 2014). At the subtropical forest, the wetland soil was largely saturated. This condition likely limited the soil pore release of TGM to the atmosphere, resulting in a weaker correlation between soil temperature and Hg fluxes. Furthermore, the Hg exchange fluxes were more dependent on solar radiation and less dependent on temperature during
the leaf-off period at the temperate deciduous plots; therefore, the Hg
fluxes were more solar-radiation driven in the deciduous forests, especially
in the wetland (Figs. S3 and S7).</p>
      <p id="d1e3039">During the campaign, significant negative correlations were evident between the soil moisture and soil–air fluxes of TGM at the five plots at the
subtropical forest (<inline-formula><mml:math id="M227" display="inline"><mml:mrow><mml:msup><mml:mi>r</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 0.03–0.39; <inline-formula><mml:math id="M228" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula> for all; Fig. S9), but there was no significant correlation with soil moisture for the temperate forest (Fig. S10). Generally, there is an optimum soil moisture
condition that maximizes soil TGM flux (Gustin and Stamenkovic, 2005; Lin
et al., 2010; Obrist et al., 2014; Osterwalder et al., 2018; Johnson et al.,
2003), which ranges from 60 % to 80 % of the water-holding capacity of a soil (Pannu et al., 2014). A laboratory experiment using undisturbed
soil collected from the our subtropical study area showed that increasing
soil moisture from 2 % to 20 % increased the TGM flux to 80 % at 24 <inline-formula><mml:math id="M229" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (Wang et al., 2014). A second field experiment was
conducted to study the effects of higher soil moisture on TGM flux at the
subtropical forest, showing that increasing soil moisture gradually
decreased the soil Hg emissions over the range of 31 %–39 % (Zhou
et al., 2017b). Combining the results of these experiments, the soil Hg
fluxes at the subtropical forest catchment appear to increase from low
values of soil moisture, reaching an optimum in the range of 20 %–30 %, and then decreasing with increasing soil moisture above these values. In the current study, we observed that following an extended dry period with an extended wet period enhanced the Hg fluxes in both forests; however, individual rainfall events did not enhance or decrease the Hg fluxes due to short-term increases in soil moisture and lower solar radiation associated with those events (Figs. 3 and 4). Additionally, Lin et al. (2010) observed the synergistic effects (20 %–30 % of an additional flux enhancement) between air temperature (15 and 30 <inline-formula><mml:math id="M230" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) and soil moisture (2.5 % and 27.5 %). Perennially humid weather results in relatively high soil moisture at the subtropical forest (largely <inline-formula><mml:math id="M231" display="inline"><mml:mrow><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">25</mml:mn></mml:mrow></mml:math></inline-formula> % during the campaigns). Considering the relatively high bulk density and low porosity of soil at the subtropical forest (Sørbotten, 2011), soil moisture likely exceeded the optimum range for TGM evasion during the campaigns, resulting in significantly negative<?pagebreak page16126?> correlations (Fig. S9). In contrast, lower bulk density and higher soil porosity would result in a higher optimum range of soil moisture at the temperate forest. Moreover, the temperate forest had a large range of soil moisture (2 % to 60 %) in the five plots which, when combined with the synergistic effects of soil moisture with temperature (Lin et al., 2010), resulted in a condition in which moisture was not a main driver of TGM evasion.</p>
      <p id="d1e3098">Soil–air Hg fluxes also showed significant negative correlations with
atmospheric TGM concentrations at the 10 plots at both forests (<inline-formula><mml:math id="M232" display="inline"><mml:mrow><mml:msup><mml:mi>r</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo></mml:mrow></mml:math></inline-formula> 0.023–0.26, <inline-formula><mml:math id="M233" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>, Figs. 6 and 7), which had a greater effect than soil moisture at both forests, except for plots T–C, S–A and S–E (Fig. 5). According to the two-resistance exchange interface model, the exchange fluxes of Hg are controlled by the gradient of TGM concentrations at both interfaces (Zhang et al., 2002). As a result, elevated
atmospheric TGM concentrations should decrease the diffusion of soil pore
TGM to the atmosphere. In a companion study, the soil pore TGM
concentrations were measured at all the plots at the subtropical and
temperate forests, except the wetlands (Zhou et al., 2020b). These results showed that gradient of TGM concentrations between the surface air
and pore air at 3 cm were significantly correlated with the soil–air TGM
fluxes at all the plots (Figs. S11 and S12). These results are consistent
with an experiment conducted at this subtropical forest, where artificially
increasing ambient air TGM concentrations significantly inhibited soil Hg
volatilization (Zhou et al., 2017b). SEM inferred that air TGM concentrations was the second important driver influencing the soil–air TGM exchange in Masson pine (Plot S–B), evergreen broad-leaved and wetland plots at the subtropical forest (Fig. 5).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e3130">Correlation between the air TGM concentration and air–surface Hg
flux measured in the daytime and nighttime over four seasons for Masson pine forest plots <bold>(a, b)</bold> and wetland <bold>(c)</bold>, evergreen broad-leaved forest <bold>(d)</bold> and open field <bold>(e)</bold> plots in a subtropical forest.</p></caption>
          <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f06.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><?xmltex \currentcnt{7}?><label>Figure 7</label><caption><p id="d1e3154">Correlation between the air TGM concentration and air–surface Hg
flux measured in daytime and nighttime over four seasons for the five plots at a Chinese pine forest <bold>(a)</bold> and larch forest <bold>(b)</bold>, wetland <bold>(c)</bold>, mixed broad-leaved forest <bold>(d)</bold> and open field <bold>(e)</bold> plots in a temperate forest.</p></caption>
          <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f07.png"/>

        </fig>

      <p id="d1e3178">Xin and Gustin (2007) and Gustin et al. (2006) defined an associated
concept of the compensation point for soils, which is the atmospheric Hg
concentration at which the net Hg flux between the soil and the atmosphere
is zero. If the atmospheric TGM concentration is above the compensation point, atmospheric deposition occurs; if the concentration is below the
compensation point, soil emission occurs. The strong linear relationships are
shown in Figs. 5 and 6 (<inline-formula><mml:math id="M234" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>), resulting in compensation points of 2.47, 2.97, 6.00, 3.33 and 3.50 ng m<inline-formula><mml:math id="M235" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for Chinese pine, larch, wetland, mixed broad-leaved forests and open field at the temperate forest, with an area-weighted compensation point of 3.42 ng m<inline-formula><mml:math id="M236" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The compensation points were much higher at the subtropical forest, with values of 6.50, 7.71, 3.92, 3.83 and 12.91 ng m<inline-formula><mml:math id="M237" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for Masson pine upland and mid-slope, wetland, broad-leaved and open field at the subtropical forest, with an area-weighted compensation point of 6.82 ng m<inline-formula><mml:math id="M238" 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>. Another study of subtropical coniferous forest showed similar compensation points (7.75 ng m<inline-formula><mml:math id="M239" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) to those in the Masson pine forests of our study (Luo, 2015).</p>
      <?pagebreak page16127?><p id="d1e3256">Diurnal variations in soil–air TGM fluxes were measured in plot S–A at the
subtropical forest (Fig. 8) and in plot T–D at the temperate forest (Fig. 9). Soil TGM fluxes were well correlated with soil and air temperature (<inline-formula><mml:math id="M240" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> for all) and were highly dependent on solar radiation in spring, summer and autumn (<inline-formula><mml:math id="M241" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&lt;</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula> for all) but not in winter (<inline-formula><mml:math id="M242" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">&gt;</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>), which is similar to seasonal patterns from other studies (Howard and Edwards, 2018; Osterwalder et al., 2018; Johnson et al., 2003). Solar radiation has been shown to promote a photochemical reduction in soil-bound Hg and enrich Hg(0) in soil pore gas. This reaction is kinetically enhanced at higher temperatures (Eckley et al., 2015; Lin et al., 2010; Zhang et al., 2001). Compared to the other three seasons, the relatively low soil
temperature (5.95 <inline-formula><mml:math id="M243" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at the subtropical forest and  <inline-formula><mml:math id="M244" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5.66</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M245" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at the temperate forest) may have limited the relationship between the soil TGM flux and solar radiation during the winter season.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><?xmltex \currentcnt{8}?><label>Figure 8</label><caption><p id="d1e3332">Diurnal patterns of soil Hg fluxes with meteorological parameters in
spring <bold>(a)</bold>, summer <bold>(b)</bold>, autumn <bold>(c)</bold> and winter <bold>(d)</bold> in the coniferous forest of a subtropical forest.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f08.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{9}?><label>Figure 9</label><caption><p id="d1e3355">Diurnal patterns of soil Hg fluxes with meteorological parameters in
spring <bold>(a)</bold>, summer <bold>(b)</bold>, autumn <bold>(c)</bold> and winter <bold>(d)</bold> in the deciduous broad-leaved forest of a temperate forest.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/20/16117/2020/acp-20-16117-2020-f09.png"/>

        </fig>

</sec>
</sec>
<?pagebreak page16128?><sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Conclusions and study implications</title>
      <p id="d1e3385">Prior to undertaking these measurements of Hg air–surface exchange flux, no
direct measurements of Hg exchange flux were available for background
landscapes in northern China. Our detailed direct observations have important
implications for the role of forests in global and regional Hg cycles.
Through multiplot measurements over 130 and 96 d at the subtropical and
temperate forests in China, we were able to reduce the uncertainty in
soil–atmosphere TGM fluxes at the catchment scale and improve our understanding of how landscape attributes contribute to variability in soil Hg evasion. It is inferred that forest soils acts as net TGM sources to the atmosphere. Strong correlations were evident between the soil Hg flux and environmental variables in some plots, such as solar radiation, temperature, soil moisture and air TGM concentrations.</p>
      <p id="d1e3388">The compensation points were determined for background forest soils from
full-scale field data showing area-weighted values of 6.82 and 3.42 ng m<inline-formula><mml:math id="M246" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for the entire subtropical and temperate catchments, respectively. The values of compensation indicate that the atmospheric TGM concentration can play a critical role in limiting TGM fluxes between the forest floor and atmosphere. Future studies need to focus on forest soils as an increasingly important source of Hg to the atmosphere because of recent declines in anthropogenic Hg emissions and TGM concentrations  (Liu et al., 2019). Moreover, TGM re-emissions are partially derived from legacy Hg stored in surface soils. A recent study using models simulating the dynamics of the
subtropical forest landscape under climate change, harvesting and land use
disturbances in southern China showed that coniferous forest area increased by approximately 3.7 times compared to broad-leaved forest area (Wu et
al., 2019). In the temperate forest, climatic changes in northern China
are expected to cause coniferous stands to transition to deciduous forests
over the next<?pagebreak page16130?> 100 years (Ma et al., 2014). Climate change and land use disturbances may increase the compensation points in both temperate
and subtropical forests and, therefore, increase the emissions of legacy Hg from terrestrial soils to the atmosphere. Some studies have emphasized that
climate and land use change will potentially enhance deposition of Hg to
forested landscapes (Haynes et al., 2017; Richardson and Friedland,
2015; Li et al., 2020); however, our study suggests that legacy Hg in forest
soils could be emitted back to atmosphere, offsetting enhanced atmospheric
Hg deposition. Better understanding of the response of Hg emissions from
forest soils to climate and land use change is an important topic for future
research.</p>
</sec>

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

      <p id="d1e3408">The data will be made available upon request to the corresponding author.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3411">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-20-16117-2020-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-20-16117-2020-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3420">ZW and XZ conceived the experiment. JZ conducted the measurements. JZ wrote the paper with input from CTD, CL and ZW. All authors reviewed the paper.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3426">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3432">This work was funded by the Second Tibetan Plateau Scientific Expedition
and Research Program (STEP; grant no. 2019QZKK0307), the Natural Science
Foundation of China (grant nos. 42077345 and 42077381) the National 973 Program of China (grant no. 2013CB430002) and the National Key Research and Development Program of China (grant no. 2017YFC0210106). The authors would like to thank Mingquan Zou and the Beijing Forest Ecosystem Research Station, Chinese Academy of Sciences, for the help with our sampling and for providing the meteorological data.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3437">This research has been supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP; grant no. 2019QZKK0307), the Natural Science Foundation of China (grant nos. 42077345 and 42077381), the National 973 Program of China  (grant no. 2013CB430002) and the National Key Research and Development Program of China (grant no. 2017YFC0210106).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3443">This paper was edited by Ralf Ebinghaus and reviewed by two anonymous referees.</p>
  </notes><ref-list>
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    <!--<article-title-html>Soil–atmosphere exchange flux of total gaseous mercury (TGM) at subtropical and temperate forest catchments</article-title-html>
<abstract-html><p>Evasion from soil is the largest source of mercury (Hg) to the atmosphere from terrestrial ecosystems. To improve our understanding of controls and in estimates of forest soil–atmosphere fluxes of total gaseous Hg (TGM), measurements were made using dynamic flux chambers (DFCs) over 130 and 96&thinsp;d for each of five plots at a subtropical forest and a temperate forest, respectively. At the subtropical forest, the highest net soil Hg emissions were observed for an open field (24&thinsp;±&thinsp;33&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>), followed by two coniferous forest plots (2.8&thinsp;±&thinsp;3.9 and 3.5&thinsp;±&thinsp; 4.2&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>), a broad-leaved forest plot (0.18&thinsp;±&thinsp; 4.3&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>) and the remaining wetland site showing net deposition (−0.80&thinsp;±&thinsp;5.1&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>). At the temperate forest, the highest fluxes and net soil Hg emissions were observed for a wetland (3.81&thinsp;±&thinsp;0.52&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>) and an open field (1.82&thinsp;±&thinsp;0.79&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>), with lesser emission rates in the deciduous broad-leaved forest (0.68&thinsp;±&thinsp;1.01&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>) and deciduous needle-leaved
forest (0.32&thinsp;±&thinsp;0.96&thinsp;ng&thinsp;m<sup>−2</sup>&thinsp;h<sup>−1</sup>) plots, and net deposition at an evergreen pine forest (−0.04&thinsp;±&thinsp;0.81&thinsp;ng&thinsp;m<sup>−2</sup> h<sup>−1</sup>). High solar radiation and temperature during summer resulted in the high Hg emissions in the subtropical forest and the open field and evergreen pine forest at the temperate forest. At the temperate deciduous plots, the highest Hg emission occurred in spring during the leaf-off period due to direct solar radiation exposure to soils. Fluxes showed strong positive relationships with solar radiation and soil temperature and negative correlations with ambient air TGM concentration in both the subtropical and temperate forests, with area-weighted compensation points of 6.82 and 3.42&thinsp;ng&thinsp;m<sup>−3</sup>, respectively. The values of the compensation points suggest that the atmospheric TGM concentration can play a critical role in limiting TGM emissions from the forest floor. Climate change and land use disturbance may increase the compensation points in both temperate and subtropical forests. Future research should focus on the role of legacy soil Hg in reemissions to the atmosphere as decreases in primary emissions drive decreases in TGM concentrations and disturbances of climate change and land use.</p></abstract-html>
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