<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0"><?xmltex \hack{\hyphenation{several}}?><?xmltex \hack{\hyphenation{after}}?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">AMT</journal-id><journal-title-group>
    <journal-title>Atmospheric Measurement Techniques</journal-title>
    <abbrev-journal-title abbrev-type="publisher">AMT</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Meas. Tech.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1867-8548</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/amt-13-4065-2020</article-id><title-group><article-title>Capturing temporal heterogeneity in soil nitrous oxide fluxes with<?xmltex \hack{\break}?> a robust
and low-cost automated chamber apparatus</article-title><alt-title>A robust soil <inline-formula><mml:math id="M1" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> autochamber system</alt-title>
      </title-group><?xmltex \runningtitle{A robust soil {$\chem{N_{2}O}$} autochamber system}?><?xmltex \runningauthor{N.~C.~Lawrence and S.~J.~Hall}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no">
          <name><surname>Lawrence</surname><given-names>Nathaniel C.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name><surname>Hall</surname><given-names>Steven J.</given-names></name>
          <email>stevenjh@iastate.edu</email>
        <ext-link>https://orcid.org/0000-0002-7841-2019</ext-link></contrib>
        <aff id="aff1"><institution>Department of Ecology, Evolution, and Organismal Biology, Iowa State
University, Ames, IA, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Steven J. Hall (stevenjh@iastate.edu)</corresp></author-notes><pub-date><day>29</day><month>July</month><year>2020</year></pub-date>
      
      <volume>13</volume>
      <issue>7</issue>
      <fpage>4065</fpage><lpage>4078</lpage>
      <history>
        <date date-type="received"><day>9</day><month>February</month><year>2020</year></date>
           <date date-type="rev-request"><day>17</day><month>February</month><year>2020</year></date>
           <date date-type="rev-recd"><day>28</day><month>May</month><year>2020</year></date>
           <date date-type="accepted"><day>2</day><month>July</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 Nathaniel C. Lawrence</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://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020.html">This article is available from https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020.html</self-uri><self-uri xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020.pdf">The full text article is available as a PDF file from https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e103">Soils play an important role in Earth's climate system through
their regulation of trace greenhouse gases. Despite decades of soil gas flux
measurements using manual chamber methods, limited temporal coverage has led
to high uncertainty in flux magnitude and variability, particularly during
peak emission events. Automated chamber measurement systems can collect
high-frequency (subdaily) measurements across various spatial scales but
may be prohibitively expensive or incompatible with field conditions. Here
we describe the construction and operational details for a robust,
relatively inexpensive, and adaptable automated dynamic (steady-state)
chamber measurement system modified from previously published methods, using
relatively low cost analyzers to measure nitrous oxide (<inline-formula><mml:math id="M2" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>) and carbon
dioxide (<inline-formula><mml:math id="M3" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>). The system was robust to intermittent flooding of
chambers, long tubing runs (<inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m), and operational temperature extremes (<inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">12</mml:mn></mml:mrow></mml:math></inline-formula> to 39 <inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) and was entirely powered by solar energy.
Using data collected between 2017 and 2019 we tested the underlying principles
of chamber operation and examined <inline-formula><mml:math id="M7" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> diel variation and rain-pulse
timing that would be difficult to characterize using infrequent manual
measurements. Stable steady-state flux dynamics were achieved during 29 min
chamber closure periods at a relatively low flow rate (2 L min<inline-formula><mml:math id="M8" 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>).
Instrument performance and calculated fluxes were minimally impacted by
variation in air temperature and water vapor. Measurements between 08:00 and
12:00 LT were closest to the daily mean <inline-formula><mml:math id="M9" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M10" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emission. Afternoon fluxes (12:00–16:00 LT) were 28 % higher than the daily mean for
<inline-formula><mml:math id="M11" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> (4.04 vs. 3.15 nmol m<inline-formula><mml:math id="M12" 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> s<inline-formula><mml:math id="M13" 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 were 22 % higher for <inline-formula><mml:math id="M14" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> (4.38 vs. 3.60 <inline-formula><mml:math id="M15" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). High rates of <inline-formula><mml:math id="M16" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emission are frequently observed after precipitation. Following four discrete rainfall events, we found a 12–26 h delay before peak <inline-formula><mml:math id="M17" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> flux, which would be difficult to capture with manual measurements. Our observation of substantial and variable diel trends and rapid but variable onset of high <inline-formula><mml:math id="M18" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions following rainfall supports the need for
high-frequency measurements.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e334">Soils play a critical role in Earth's carbon (<inline-formula><mml:math id="M19" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula>) and nitrogen (<inline-formula><mml:math id="M20" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">N</mml:mi></mml:mrow></mml:math></inline-formula>) cycles. Managing soils to sequester <inline-formula><mml:math id="M21" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> or reduce the emission of the trace greenhouse gases <inline-formula><mml:math id="M22" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and methane (<inline-formula><mml:math id="M23" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CH</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) is often suggested as an effective tool to combat climate change (Minasny et al., 2017; Paustian et al., 2016). Therefore, reliable trace gas measurements are critical for informing management. Although manual soil gas flux measurements have been collected for several decades, the high temporal and spatial variability of emissions has often plagued attempts to obtain accurate and precise flux estimates needed to calculate annual budgets (Davidson et al., 2002; Groffman et al., 2009; Hutchinson and Mosier, 1981). Sampling at higher frequency than is practical with manual measurements may be required to constrain the role of soils in global biogeochemical cycles and validate the impacts of management practices on trace gas emissions (Barton et al., 2015; Merbold et al., 2015; Parkin, 2008). <inline-formula><mml:math id="M24" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions are
particularly variable, so relatively less is known about peak emissions such
as the time between rainfall and the subsequent <inline-formula><mml:math id="M25" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> pulse that is
frequently observed (Groffman et al., 2006, 2009). High-frequency automated flux measurements that can span the large (<inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m) spatial scales that frequently accompany local topographical and hydrological variation at a site may be<?pagebreak page4066?> critical to capture the dual spatial–temporal dynamics which are key to generating robust emission estimates.</p>
      <p id="d1e422">Prefabricated automated chambers capable of measuring soil trace gas fluxes
are available commercially and can be plumbed to a wide range of
analyzers – most commonly, infrared gas analyzers that measure <inline-formula><mml:math id="M27" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>.
Commercially available chambers typically rely on electric components for
movement which are sensitive to moisture, and they are substantially more
expensive (often many thousands of US dollars, USD) than the chamber design
described here (materials costs of <inline-formula><mml:math id="M28" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> USD 500 per chamber).
Other custom-built chamber designs have been developed to address specific
research needs (e.g., Ambus and Robertson, 1998; Butterbach-Bahl et al., 1997;
Savage et al., 2014). Chambers have been paired with analyzers to measure
other trace gases, including <inline-formula><mml:math id="M29" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M30" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CH</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, by utilizing methods such as gas chromatography (GC), photoacoustic infrared detection, tunable diode laser (TDL), or cavity ring-down laser spectroscopy (Ambus
and Robertson, 1998; Breuer et al., 2000; Courtois et al., 2019; Papen and
Butterbach-Bahl, 1999; Pihlatie et al., 2005). Fassbinder et al. (2013) provide a detailed summary of the advantages and limitations of commonly used analyzers that we briefly summarize here. GC systems with electron capture detectors (ECDs) have often been used to measure <inline-formula><mml:math id="M31" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> from automated chambers (Breuer et al., 2000; Papen and Butterbach-Bahl, 1999). However, GC systems typically have high power demand and require carrier gases and radioactive elements for ECD operation that may limit their field practicality. Interference from water vapor and other gases potentially limits the use of photoacoustic analyzers in the field (Rosenstock et al., 2013). Laser-based analytical approaches are capable of rapid (e.g., 10 Hz) and precise <inline-formula><mml:math id="M32" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> measurements, but these analyzers are considerably more expensive
(<inline-formula><mml:math id="M33" display="inline"><mml:mo lspace="0mm">&gt;</mml:mo></mml:math></inline-formula> USD 70 000) and often have relatively high power requirements
for autonomous field deployment (Fassbinder et al., 2013; Pihlatie et al., 2005). We sought to implement a lower-cost, solar-powered, soil gas flux measurement system capable of operating
unattended in a harsh field environment and where analyzers could feasibly
be replaced if stolen or damaged. For these reasons, we utilized a gas
filter correlation (GFC) infrared <inline-formula><mml:math id="M34" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer in our study
(<inline-formula><mml:math id="M35" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> USD 16 000), similar to that described previously by
Fassbinder et al. (2013), along with an infrared gas analyzer for <inline-formula><mml:math id="M36" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M37" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> measurement (<inline-formula><mml:math id="M38" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> USD 4000). However, other analyzers could be readily employed with the
chamber and manifold system described below.</p>
      <p id="d1e553">Environmental conditions, particularly those posed by flooding and
agricultural management, created several unique challenges for trace gas
measurement in our study system that could be expected in many field
settings. Extreme heat and cold (<inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">12</mml:mn></mml:mrow></mml:math></inline-formula> to 39 <inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) and occasional
submergence of chambers mandated that our apparatus be tolerant of a wide
range of conditions. Frequent agricultural management (tillage, planting,
fertilization, harvest, etc.) at our field site required the chambers and
associated equipment to be relatively portable so they could be removed to
the field edge (<inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m away) and reinstalled several times
per year (Fig. 1a). To avoid damaging crops, all equipment had to be movable
on foot. Because electric power was unavailable, solar panels and batteries
had to provide all necessary energy. Our core measurement system consisted
of eight steady-state, flow-through chambers that quantified soil gas fluxes
at each chamber every 4 h. For 1 year, a second set of chambers was paired
with the original 8 for a total of 16 chambers without sacrificing
measurement frequency. With our design, chamber number and measurement
frequency can be readily adjusted to fit study questions. The gas analyzers
were maintained in an instrument shed at the field edge (Fig. 1a). This
location was not impacted by flooding or agricultural management but was
subjected to the temperature extremes noted above.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e588"><bold>(a)</bold> Aerial image of the field site with plot locations. <bold>(b)</bold> Image
from the lowest topographic position along the transect (front left: a
closed chamber; front right: an open chamber between measurements); the
transect is visible in the background. Aerial image source: Esri,
DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS,
AeroGRID, IGN, and the GIS user community.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f01.png"/>

      </fig>

      <p id="d1e602">There is a rich literature on the impacts of chamber design and the
potential biases of soil trace gas flux measurements. We chose a chamber
design that has been shown in field and laboratory experiments to provide
accurate estimation of soil gas fluxes and isotopic composition (Bowling
et al., 2015; Moyes et al., 2010a; Norman et al., 1997; Pumpanen et al., 2004). In one comparison of different chambers, a variant of the open,
flow-through design we used here measured known <inline-formula><mml:math id="M42" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes produced in the laboratory to within 2 %–4 % of the actual values, which was
relatively accurate compared to the other designs tested (Pumpanen et al., 2004). Pressure
differential between the inside and outside of some chamber designs can
create measurement artifacts (Fang and Moncrieff, 1998;
Xu et al., 2006). The chambers described<?pagebreak page4067?> here utilize an open-lid design
(Fig. 2) that limits pressure differential to less than <inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> Pa at the flow rate (2 L min<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>) we utilized (Moyes et al., 2010b; Rayment
and Jarvis, 1997). When using static chamber designs, soil gas flux is
calculated as a function of the change in gas concentration over time within
a closed chamber headspace. In contrast, with dynamic chambers we derive gas
flux from the steady-state difference in concentration between air at the
chamber inlet and air pumped out of a chamber outlet (Fig. 2). When the outlet
gas concentration is approximately constant, the chamber is at a steady state.
Steady-state chambers with low pressure differential have been shown to
reproduce known <inline-formula><mml:math id="M45" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> values of <inline-formula><mml:math id="M46" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes (Moyes et al., 2010b), possibly because they have less impact on the diffusive profile than many non-steady-state chamber designs (Nickerson and Risk, 2009). For our study, an additional consideration was that chambers needed to be located at variable distances (80–115 m) from the gas analyzers (Fig. 1a). We required this attribute to span a large (120 m) topographic gradient and to maintain analyzers and related instruments in a permanent location with vehicle access. As sampled gas can be vented downstream of the analyzers instead of routed back to the chamber (as is required for closed-loop static chamber designs), dynamic chambers can be located at varying distances from the instruments without impacting the effective volume of the chamber headspace.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e664">Illustration modified from Rayment and Jarvis (1997) depicting the chamber lid with cutout to show the inlet tube <bold>(a)</bold> and the polyvinyl chloride (PVC) cap <bold>(b)</bold>. Inlet and outlet sampling points are noted.</p></caption>
        <?xmltex \igopts{width=199.169291pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f02.png"/>

      </fig>

      <p id="d1e679">In this publication we present a method to construct a robust system of
dynamic automated soil trace gas chambers along with the maintenance and
troubleshooting lessons learned over the 3-year period the chambers were
running. In addition to presenting these operational details, we tested
three underlying assumptions of our chamber design: (1) did chambers reach
steady-state dynamics, (2) how did broad temperature fluctuations affect
instrument performance in the field, and (3) to what extent could water
vapor impact our measurement values? We further utilized the high-frequency
flux data to test two questions related to the temporal dynamics of gas
emissions to inform manual sampling efforts: (4) how strong was the diel
signal in trace gas emissions and (5) what was the average delay between
isolated rainfall events and the elevated <inline-formula><mml:math id="M47" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions that frequently followed?</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Study site</title>
      <p id="d1e710">Our chambers were located at eight plots on 17 m intervals along a topographic gradient in a conventionally managed corn–soybean (<italic>Zea mays</italic>–<italic>Glycine max</italic>) agricultural field in central Iowa, USA (41.98<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 93.69<inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W). The transect spanned a distance of 120 m (Fig. 1a), 2.25 m elevation, and included very poorly to moderately poorly drained
soils (Mollisols classified as Okoboji to Clarion series under the US Department of Agriculture taxonomy). Chambers were placed immediately adjacent to crop
plants; due to frequent tillage and herbicide application, recruitment of
other plants inside the chamber collars was uncommon, but any plants were
removed from the chamber interiors as soon as they were observed. Roots from
crop plants were not excluded and likely grew beneath chambers. The lower
half of the transect often experienced flooding after large rain events
(Logsdon and James, 2014), and chambers were occasionally
completely inundated. The foreground of Fig. 1b shows one open and one
closed chamber located in the lowest topographic position. The open chambers
in the background are positioned along the topographic transect.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Chamber design</title>
      <p id="d1e745">The chambers we utilized were constructed in-house, and various aspects were
modified from previously published methods. The chamber lid was first
described by Rayment and Jarvis (1997), and Riggs et al. (2009) pioneered a pneumatic piston and stainless-steel frame that opened and closed a chamber lid relative to a collar installed in the soil. Bowling et al. (2015)
implemented a similar chamber design to measure <inline-formula><mml:math id="M50" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M51" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> fluxes from a forest but did not include extensive details on
chamber design, construction, or operation.</p>
      <p id="d1e772">The dimensions of many of the materials used were commercially specified
with imperial units but are reported here in metric equivalents for
consistency. A table providing the instrument part names in the order that they
are described, along with use, supplier, part number, and total cost, is
supplied in the Supplement. Small, unspecified items (e.g., bolts) which do not
require exact dimensions are not listed. Approximately 130–260 h of labor
was required to construct nine chambers and assemble the associated control
system. Figure 3 shows the chamber design. Here we define the chamber base as
the rigid, rectangular polyethylene structure (Fig. 3a) and the chamber
frame as the metal structure superior to the base which allows for movement
of the chamber lid (Fig. 3). The chamber collar is defined as the length<?pagebreak page4068?> of
polyvinyl chloride (PVC) pipe that forms the interface between the chamber
lid and the soil. Chamber bases were constructed from <inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.54</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mrow class="unit"><mml:mi mathvariant="normal">cm</mml:mi></mml:mrow><mml:mo>×</mml:mo><mml:mn mathvariant="normal">7.62</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mrow class="unit"><mml:mi mathvariant="normal">cm</mml:mi></mml:mrow></mml:mrow></mml:math></inline-formula>
high-density polyethylene (HDPE) plastic (Fig. 3a). Custom L brackets cut
from 5.08 cm aluminum angle stock and bolted to the plastic base provided
two horizontal platforms to attach female spherical rod ends that served as
the pivot point for opening and closing the chamber (Fig. 3b). By routing
vertical slots in the L brackets, we provided a means to adjust the lateral
orientation of the pivot rod on each chamber after installation in the field
(Fig. 3b). This was useful to ensure that the chamber lid sealed against the
collar given the inherent variability of soil microtopography. A 0.64 cm
diameter threaded rod between the rod ends provided an axle to attach the
chamber frame (Fig. 3c). Most of the chamber frame was constructed from 0.95 cm diameter stainless-steel tubing; dimensions are listed in the caption and
correspond to the numbered labels in Fig. 3. To drill holes in the stainless-steel
tubing, we flattened the ends of each piece of tubing to a length of 1 cm in
a bench vise and then drilled holes through the flattened portion to
accommodate attachment bolts. The stainless-steel tubing was attached to the
threaded rod described above or to aluminum angle brackets bolted to the
chamber lid, noted by yellow or red circles respectively in Fig. 3. Two
lengths of 1.27 cm diameter stainless-steel tubing surrounding a second 0.64 cm diameter threaded rod and inserted into a <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mn mathvariant="normal">5.08</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mrow class="unit"><mml:mi mathvariant="normal">cm</mml:mi></mml:mrow><mml:mo>×</mml:mo><mml:mn mathvariant="normal">2.54</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mrow class="unit"><mml:mi mathvariant="normal">cm</mml:mi></mml:mrow></mml:mrow></mml:math></inline-formula> HDPE bar with a slot for a spherical rod end were attached to the end of a pneumatic
cylinder rod piston (Clippard, UDR-17-6) (Fig. 3d). Extension of the piston
moved the chamber lid open or closed, and the HDPE bar and stainless-steel tubing
were used to prevent the threaded rod from flexing during movement of the
chamber lid. The three spherical rod ends, two located on the pivot point
and one at the end of the cylinder piston, served as rotational degrees of
motion (Fig. 3, yellow circles). All other connection points were rigid
(Fig. 3, red circles).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e817">Image of chamber design: HDPE base <bold>(a)</bold>, aluminum L bracket <bold>(b)</bold>, threaded rod <bold>(c)</bold>, and pneumatic cylinder rod end <bold>(d)</bold>. The length of each numbered stainless-steel tube is as follows: 1 (16 cm), 2 (47 cm), 3 (41 cm), 4 (56 cm), 5 (65 cm), and 6 (18 cm). The yellow circles indicate points of rotation while red circles denote rigid, fixed connection points.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f03.jpg"/>

        </fig>

      <p id="d1e839">The chamber lid followed a previous design which was shown to minimize the
pressure differential between the inside and outside of the chamber
(<inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> Pa at flow rates of 4.5 L min<inline-formula><mml:math id="M55" 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>) (Moyes et al., 2010b; Rayment and Jarvis, 1997). The circular chamber lid (38 cm diameter) was cut from
an HDPE panel (1.27 cm thick). A 2.54 cm diameter hole cut into the center of
the lid allowed a vertical gas inlet tube (Fig. 2a) to be fixed to the lid
via custom-machined threads and a nut on the bottom of the tube. The inlet
tube (15 cm length) was machined from aluminum bar stock and had internal and
external diameters of 2.54 and 3.81 cm, respectively, and a taper (2.54 cm
length) at the superior end (Fig. 2a). The inlet tube was covered by a
PVC cap (10.16 cm diameter and 16 cm length; Fig. 2b)
attached to the lid surface with three bolts, each with 1 cm spacers to
create an air gap between the cap and the lid surface (Fig. 2). The gap
created by the spacers allowed air to flow to the inlet while preventing the
direct horizontal flow of wind over the inlet tube opening. On the lower
surface of the lid, a D-shaped rubber seal (EPDM foam, 2.54 cm width) was
affixed with silicone caulk in a ring where the lid contacted the collar to
create an airtight seal when pressure was applied to the piston that closed
the chamber (Fig. 1b). Early in our study, we observed that high pressure
(<inline-formula><mml:math id="M56" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">550</mml:mn></mml:mrow></mml:math></inline-formula> kPa) was needed to ensure a tight seal between the collar and chamber lid. To minimize the piston air pressure required to seal the
chamber lid against the collar, and thus conserve power, we bolted two
nested, 26 cm sections of slotted steel construction strut to the top of the
chamber lid to provide additional mass (Fig. 3). Gas from the inside of the
chamber was sampled via a circular outlet manifold consisting of polyethylene tubing (6.4 mm o.d., 3.2 mm i.d.) perforated by drilling 2 mm diameter holes through the tubing at 2 cm intervals, and it was held in place approximately 3 cm below the lower surface of the lid with three stainless-steel eyebolts. All tubing connections in our chamber and instrument manifolds were made using 0.64 cm brass Swagelok compression fittings. A threaded bulkhead union and tee fitting were used to connect to the outlet manifold to external tubing above the chamber lid.</p>
      <p id="d1e874">Chamber collars were made from PVC pipe segments (20 cm length, 30.48 cm i.d.) with the lower edge beveled with a belt sander to facilitate insertion into
the soil. The beveled edge was pounded 10 cm into the soil for a total
collar height of 10 cm and volume of approximately 7.3 L. The volume of air
inside the longest length of tubing (120 m) connecting the chamber lid to
the gas analyzers was <inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1.8</mml:mn></mml:mrow></mml:math></inline-formula> L. To hold the chamber base in place
relative to the collar, we initially used a ratchet strap. However, we found
that pressure exerted by the pneumatic arm when opening or closing the
chamber occasionally shifted the position of the chamber base or collar and
prevented a seal between the chamber lid, collar, and soil. This
occasionally occurred following tillage or when soils were extremely dry,
given that these soils contained swelling clays. To address this problem,<?pagebreak page4069?> we
anchored the chamber base using two steel rebar rods (60 cm length, 1.27 cm
diameter) pounded 45 cm into the ground on either side of the chamber base
and affixed to the outside of the chamber base with U bolts positioned along
the central axis of the collar (Fig. 3). We periodically checked that the
chamber lids were effectively sealing against the collars. Application of
this method to true Vertisols, with even greater shrink/swell behavior,
could likely be achieved using similar use of rebar to anchor the chamber.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Chamber lid operation</title>
      <p id="d1e895">Chambers were opened and sealed by alternatively applying 550 kPa
pressurized air to either side of the pneumatic cylinder described above via
two lengths of tubing connecting each chamber and the instrument shed (Fig. 4a). We used 0.64 cm o.d., 0.43 cm i.d. low-density polyethylene (LDPE) plastic tubing. We initially used aluminum composite tubing (Synflex 1300), which has been commonly used in other field trace gas measurement studies (e.g., Bowling et al., 2015), but we found this to be impractical for our
application given its vulnerability to kinking during chamber installation
and removal through dense vegetation. Pressurized gas tubing was connected
to the pneumatic cylinder via national pipe thread (NPT) to Swagelok
connections (Fig. 4a). Needle valves (Clippard JFC-2A) located between the
pressurized tubing and either side of the pneumatic piston were used to
manually adjust the rate of chamber opening and closing to prevent damage to
the frame. Pressurized gas was initially supplied by a pressurized cylinder
and regulator as described in Riggs et al. (2009). However, we found that cylinders were impractical to supply the volume of gas necessary to pressurize the <inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m lengths of tubing between the cylinder and chambers with frequent opening and closing. To provide a less-labor-intensive source of pressurized air, we installed a Gast 12 VDC oil-less air compressor regulated by an air compressor switch (Condor MDR 3) with cut-in pressure set to 450 kPa and cut-out pressure set to 550 kPa (Fig. 4b). It was important to remove excess moisture from the pressurized air to maintain downstream metal components and valves. A 15 m coil of copper tubing immediately downstream of the compressor allowed the pressurized air to cool and water to condense. Excess moisture was removed by a water trap (Speedaire no. 4ZL49) connected to an additional 1 L reservoir made from PVC pipe and Swagelok fittings, which was periodically drained via a needle valve to the exterior of the instrument enclosure (Fig. 4c). From the water trap, the pressurized air flowed to a manifold of four-channel, two-way valves (Clippard MME-41PEEC-W012) which controlled the open/sealed position of each chamber by supplying pressure to either of two lengths of tubing extending to each chamber (Fig. 4a, d). Each valve was wired to one channel of a 12 V data-logger-controlled relay controller (Campbell Scientific SDM-CD16AC) such that pressurized air maintained the chamber in an open position when the relay was closed.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e910">Illustration of the chamber pneumatic system that controls opening
and closing of chambers. The red arrow denotes the tube to drain the water
trap reservoir. Figure panel labels are defined in the main text.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f04.png"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>Principles of chamber gas sampling</title>
      <p id="d1e927">Figure 5 outlines the movement of sample gas between chamber and analyzers.
Air was pulled through two separate 0.64 cm o.d., 0.43 cm i.d. LDPE plastic tubes. One tube sampled gas adjacent to the
chamber inlet tube (Fig. 2), while the second pulled air from the perforated
tubing manifold inside the chamber (Fig. 2). The second sampling tube is
referred to here as the chamber outlet, as it served to pull ambient air
from the chamber inlet tube through the chamber. Both sampling tubes were
filtered through 1 <inline-formula><mml:math id="M59" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> Teflon (i.e., hydrophobic) filters (Pall
Corporation) affixed to LDPE tubing via Swagelok connections immediately
outside the chamber to prevent any particulates and liquid water from being
pulled through the tubing (Fig. 5a).</p>
      <p id="d1e940">Chamber sample selection was achieved by two sets of eight normally closed
solenoid valves, one for inlet and one for outlet selection (Clippard,
DV-2M-12-L, Fig. 5b). Solenoid valves were controlled by a second Campbell
relay controller. Downstream of the chamber selection manifolds, both inlet
and outlet gases flowed through additional 1 <inline-formula><mml:math id="M60" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> filters. Inlet and outlet flow rates were set independently by two mass flow controllers
(Aalborg, GFCS-010201) upstream of two 12V diaphragm gas pumps (KNF
Neuberger UNMP830; Fig. 5c). Both flow rates were set to 2 L min<inline-formula><mml:math id="M61" 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> by
the mass flow controllers, and actual flow rates were recorded on the
data logger (which was important for<?pagebreak page4070?> diagnosing potential problems during
operation, as discussed later). To mediate selection of the gas sample that
flowed to the analyzers, a third sample selection manifold with four
normally closed solenoid valves selected among gas sources: chamber inlet,
chamber outlet, high concentration standard, or low concentration standard
(Fig. 5d). To operate 16 chambers without reducing measurement period or
frequency, separate parallel selection manifolds, additional mass flow
controllers for chamber inlet/outlet, and diaphragm pumps were added. Two
additional solenoid valves on the sample selection manifold allowed
selection between each of the two inlet and outlet manifolds. To maintain a
constant flow rate through the inlet and outlet sampling tubes when the
sample was not being routed to the analyzers, needle valves vented excess
flow between the gas pumps and the selection manifold (Fig. 5). The selected
sample gas flowed through a common sample gas mass flow controller set to
0.9 L min<inline-formula><mml:math id="M62" 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> (Fig. 5e). An internal pump in the <inline-formula><mml:math id="M63" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer
sampled gas at 0.8 L min<inline-formula><mml:math id="M64" 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 this pump also served to pull sample
through the <inline-formula><mml:math id="M65" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> analyzer which had no internal pump. The remaining 0.1 L min<inline-formula><mml:math id="M66" 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 vented through a final needle valve placed upstream of the <inline-formula><mml:math id="M67" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> analyzer (Fig. 5e).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e1039">Schematic of the sample selection system. Mass flow controllers are
abbreviated MFC. Filters are denoted by black ovals. Red arrows indicate
where needle valves vent excess flow. Figure panel labels are defined in the
main text.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f05.png"/>

        </fig>

      <p id="d1e1049">Two instruments in series were used to analyze <inline-formula><mml:math id="M68" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M69" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>,
respectively (Fig. 5e). The <inline-formula><mml:math id="M70" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> analyzer was placed upstream of the
<inline-formula><mml:math id="M71" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer to avoid artifacts from the high oven temperature and
Nafion drying column in the latter. We used a LI-COR 830 (or,
subsequently, a LI-COR 850) analyzer to measure <inline-formula><mml:math id="M72" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations by
infrared absorbance. Downstream, a Teledyne 320U gas filter correlation
analyzer measured <inline-formula><mml:math id="M73" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> concentration via infrared absorbance by
frequently comparing the sample to a reference gas in a rotating filter
(Fassbinder et al., 2013). Instantaneous gas concentrations, as well as the air temperature, inlet flow, outlet flow, and sample flow, were measured every 10 s and recorded on a data logger (Campbell CR3000).</p>
</sec>
<sec id="Ch1.S2.SS5">
  <label>2.5</label><title>Measurement principle</title>
      <?pagebreak page4071?><p id="d1e1134">Each chamber flux measurement was conducted over the course of a half-hour
cycle. When 16 chambers were deployed, a new chamber was closed every 15 min
and two chambers were closed simultaneously with the sample gases vented
during a 15 min equilibration period prior to a 15 min measurement period.
Here we describe the eight-chamber arrangement. To reduce possible
conflation between measurement time and plot topographic position, we chose
a consistent but staggered plot measurement sequence for each 4 h period (1,
5, 3, 7, 2, 6, 4, 8), where plot one was the lowest topographic position.
When 16 chambers were deployed, the plot sequence was maintained so paired
chambers at each plot were measured in a single half-hour cycle. At the
beginning of each half-hour cycle when a new chamber was going to be
measured, a chamber lid was closed by triggering a relay to apply pneumatic
pressure to the piston, and the inlet and outlet sampling tubes of the
respective chamber began to be sampled at 2 L min<inline-formula><mml:math id="M74" 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>. Both inlet and
outlet tubes were sampled continuously at a constant rate during the
half-hour cycle while a downstream selection manifold alternated which gas
was routed to the instruments, with residual flow vented to the instrument
shed through needle valves (Fig. 5). All pneumatic and sample selection
valves were controlled by the data logger. Calibration gases (standards) were
measured every 2 h (Fig. 5d). If standards were measured during a given
chamber measurement sequence, this was conducted at the beginning of the
half-hour period: each standard was measured for 3 min by opening a valve on
the gas selection manifold while chamber inlet and outlet flows were vented
(Fig. 6a, b). During measurement periods where standards were not measured,
the inlet sample was opened first on the selection manifold (Fig. 6c). After
11 min, the inlet was vented while the outlet sample was routed to the
instruments until the 16th minute of the half hour (Fig. 6d). The first
inlet and outlet gas concentration values from a given chamber measurement
cycle (Figs. 6c and 7d respectively) were not used to calculate fluxes, as
the chamber headspace concentrations of <inline-formula><mml:math id="M75" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M76" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> were often not at a steady state during this time. These values, however, were useful for troubleshooting and assessing temporal trends in chamber gas concentrations. Between 16–21 and 21–29 min, the inlet and outlet were respectively measured for a second time (Fig. 6e, f). The minimum 5 min measurement period for inlet and outlet samples was chosen to overcome a lagged response in the
<inline-formula><mml:math id="M77" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer following a switch in sample gas composition, which was as long as 2 min when there were large concentration differences between the inlet and outlet samples; the <inline-formula><mml:math id="M78" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> analyzer typically stabilized much faster (tens of seconds). The differences between the inlet and outlet gas
concentrations averaged over the last 2 min of their second respective
measurement periods (Fig. 6e, f) were used to calculate soil gas fluxes
(units of <inline-formula><mml:math id="M79" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) using Eq. (1). The last 10 s of data from each period were excluded because of transient values during valve
switching.
            <disp-formula id="Ch1.E1" content-type="numbered"><label>1</label><mml:math id="M80" display="block"><mml:mrow><mml:mtext>Flux</mml:mtext><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:mfenced open="(" close=")"><mml:mrow><mml:mi>P</mml:mi><mml:mo>⋅</mml:mo><mml:mi>F</mml:mi></mml:mrow></mml:mfenced><mml:mfenced close=")" open="("><mml:mrow><mml:mtext>ConcOut</mml:mtext><mml:mo>-</mml:mo><mml:mtext>ConcIn</mml:mtext></mml:mrow></mml:mfenced></mml:mrow><mml:mrow><mml:mfenced close=")" open="("><mml:mrow><mml:mi>R</mml:mi><mml:mo>⋅</mml:mo><mml:mi>T</mml:mi><mml:mo>⋅</mml:mo><mml:mi>A</mml:mi></mml:mrow></mml:mfenced></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M81" display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> is equal to mean atmospheric pressure at our study site (atm), <inline-formula><mml:math id="M82" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> is the outflow rate (L s<inline-formula><mml:math id="M83" 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>), ConcOut is the standard-corrected second outlet measurement period gas concentration (<inline-formula><mml:math id="M84" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">mol</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) (Fig. 6f), ConcIn is the standard-corrected second inlet gas
concentration (<inline-formula><mml:math id="M85" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">mol</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) (Fig. 6e), <inline-formula><mml:math id="M86" display="inline"><mml:mi>R</mml:mi></mml:math></inline-formula> is the ideal gas constant (L atm K<inline-formula><mml:math id="M87" 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> mol<inline-formula><mml:math id="M88" 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="M89" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula> is temperature (K), and <inline-formula><mml:math id="M90" display="inline"><mml:mi>A</mml:mi></mml:math></inline-formula> is the area covered by the chamber (m<inline-formula><mml:math id="M91" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula>). Following the end of the measurement period (29 min total), the chamber was opened by applying pneumatic pressure to the opposite end of the piston via the open/sealed manifold (Fig. 4a, d) and would remain open prior to the next measurement sequence.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e1392">Raw instrument output over a representative half-hour chamber measurement period: low standard <bold>(a)</bold>, high standard <bold>(b)</bold>, first inlet
measurement <bold>(c)</bold>, first outlet measurement <bold>(d)</bold>, second inlet measurement <bold>(e)</bold>, and second outlet measurement <bold>(f)</bold>. The second set of inlet/outlet measurements was used for flux calculations. Shaded bars indicate periods where output was averaged for subsequent calculations.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f06.png"/>

        </fig>

      <p id="d1e1420">Corrected gas concentration values were obtained by applying two-point
linear standard corrections updated every 2 h (e.g., Fig. 6a, b). The
instrument output during the last minute of each standard measurement, again
excluding the last 10 s, was averaged for calibration. Corrected gas
concentrations were obtained by regressing measured standard values against
known values to obtain a linear slope and intercept used to correct raw
values. Working standards were prepared by filling two 50 L gas cylinders
with higher and lower concentrations of analytes by mixing <inline-formula><mml:math id="M92" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>- and
<inline-formula><mml:math id="M93" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>-free air (zero air) with a concentrated standard gas to achieve
values that approximately spanned the range of <inline-formula><mml:math id="M94" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M95" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
concentrations observed in the field. The mole fractions of each standard
gas were verified in our laboratory by analyzing five replicates each on a
gas chromatograph (Shimadzu 2014A) with thermal conductivity and electron
capture detectors, which were calibrated according to additional
NIST-traceable standards using a four-point curve. Gas cylinders filled to
140 MPa lasted approximately 9 months.</p>
      <p id="d1e1472">All data cleaning, flux calculation, and data analysis were conducted with R
statistical software version 3.6.1 (R Core Team, 2019). Cleaning and calibration required R packages lubridate, nlme, and reshape (Grolemund and Wickham, 2011; Pinheiro et al., 2020; Wickham, 2007). The CR3000 data logger code we used to operate the chambers and record data, along with an example dataset and R script for data cleaning and flux calculations, is provided as archived files associated with this publication.</p>
</sec>
<sec id="Ch1.S2.SS6">
  <label>2.6</label><title>Power supply: solar panel/batteries</title>
      <p id="d1e1483">At our field site, six 265 W solar panels (Kyocera) with 16 deep cell marine
batteries (Trojan J305E-AC 6V) were able to power the analysis system for
much of the year. Figure 7 illustrates the solar charging and battery storage
system. Two sets of three solar panels each were wired in series through
parallel 15 A circuit breakers within a combiner box. The positive lead
flows through a 30 A circuit breaker with a second combiner box before
joining the negative at a charge controller (Morningstar TS-MPPT-60, Fig. 7). Indicator lights on the charge controller were used to assess the remaining battery charge, and we occasionally shut the entire system down
during prolonged periods of low sunlight to avoid completely discharging the
batteries. The charge controller positive output flowed through a 63 A
circuit breaker (Fig. 7) to the final positive lead of a battery bank
consisting of four sets of four serially wired batteries, each connected in
parallel (Fig. 7). The negative output from the charge controller flowed to
the negative lead at the opposite end of the battery bank. A 24 V DC output
connected to a 60 A breaker (Fig. 7) and a DC/AC converter provided power
for the 110 V AC <inline-formula><mml:math id="M96" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer. A subset of two batteries provided 12 V DC power to the other components (data logger, <inline-formula><mml:math id="M97" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> analyzer, switches, valves, and additional sensors).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><?xmltex \currentcnt{7}?><label>Figure 7</label><caption><p id="d1e1512">Schematic of the solar and power supply system with wiring and circuit breakers. Wires are noted positive (<inline-formula><mml:math id="M98" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>) and negative (<inline-formula><mml:math id="M99" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>). Arrows from the DC–AC inverter supply 120 V AC to power the <inline-formula><mml:math id="M100" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer. Arrows from the battery back supply 12 V DC. Circuit breakers are labeled by their ampere rating. Batteries for the battery bank are labeled by individual battery voltage.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f07.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results and discussion</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Troubleshooting</title>
      <p id="d1e1564">While often no maintenance was required, we typically checked the
measurement system every several days to prevent data gaps if a failure
occurred. Under ideal conditions (permanent chamber installation, ample
sunlight, no flooding), the analysis system may be able to operate over
periods of weeks to months without maintenance. However, we found that
problems related to chamber submergence, component failure, or unintended
faunal interactions occurred on occasion. This section highlights some
common issues and practices that we found helpful for addressing them.</p>
<?pagebreak page4072?><sec id="Ch1.S3.SS1.SSS1">
  <label>3.1.1</label><title>Excess moisture</title>
      <p id="d1e1574">Periodic flooding presented one of the greatest challenges at our field
site. Chambers could not sample gas when the water level was above the
height of the perforated outlet manifold suspended from the chamber lid
(<inline-formula><mml:math id="M101" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">7</mml:mn></mml:mrow></mml:math></inline-formula> cm above the soil surface). When water exceeded this height, the filter located at the chamber outlet (Fig. 5a) became saturated with water and stopped flow, preventing damage to the downstream components. If flooding exceeded the height of the inlet (<inline-formula><mml:math id="M102" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula> cm depth), the inlet filter was similarly impacted. Data affected by saturated filters were flagged by noting below-normal inlet/outlet flows during postprocessing and were removed. We replaced saturated filters after the water level receded to return the chamber to operation. Wet filters were dried at 100 <inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and reused. Excess water also created problems when it condensed downstream of the air compressor. During humid summer conditions the compressor water trap reservoir (Fig. 4c) was emptied at least once every 2 weeks. In subfreezing conditions the trap rarely collected water but was emptied after warmer periods to prevent expansive bursting when temperatures fell below 0 <inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. Pumps and valves occasionally failed for unknown reasons. In general, we identified problems related to gas flow and sample selection by plotting flow rates over time for each chamber measurement sequence during data postprocessing and replaced any faulty components.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S3.SS1.SSS2">
  <label>3.1.2</label><title>Gnawing animals</title>
      <p id="d1e1624">Early in our experiment, animals occasionally chewed through the gas tubing
between the instrument shed and the chambers. For protection and
organization, all four tubes connecting each chamber to the instrument shed
(comprising chamber inlet and outlet gas samples, and compressed air for
opening and closing the chamber, respectively) were subsequently wrapped in
2.54 cm diameter polyethylene split corrugated wire loom tubing (Drossbach
25D260). The last several cm of each of the four tubes must be able to move
independently to allow the piston to move and the chamber lid to open and
close. To protect these final portions of tubing which could not be wrapped
in protective loom tubing, we replaced the last 30 cm of tubing with
semiflexible 0.64 cm diameter copper tubing connected with Swagelok
fittings. The copper tubing was molded by hand to enable necessary movement
of chamber components and was not impacted by animals. We documented and
isolated leaks by capping the chamber end of each tubing line, applying
pressure with an air tank to each individual tube, and checking for a drop
in regulator pressure. Large leaks were audible and could be easily found
and repaired by splicing in replacement tubing using Swagelok union
fittings. To test for small leaks, we plumbed the valves to a tank of
industrial-grade helium and used a helium-specific leak detector (Restek
28500). After protecting against animal damage, leaks were infrequent.</p>
</sec>
<sec id="Ch1.S3.SS1.SSS3">
  <label>3.1.3</label><title>Power limitation</title>
      <?pagebreak page4073?><p id="d1e1635">We experienced occasional power outages during extended periods of cloudy
weather and during winter. By periodically turning the analysis system off
for several days to allow the batteries to reach full charge, we could
collect 2–3 d of measurements even in cold/cloudy conditions. During
periods of chamber closure (3 out of every 24 h during typical operation),
rainfall was excluded from the chamber enclosure, which could potentially
alter soil moisture. Elsewhere, a rain gauge has been used to signal
automated chambers to remain open during rainfall events (Butterbach-Bahl and Dannenmann, 2011). Here, we elected to maintain a consistent measurement schedule irrespective of rainfall, due to the logistical challenges posed by prolonged rainfall events (when no measurements would be collected). A rainfall rate threshold required to open the automated chambers could be useful in future studies to limit the frequency and duration of data gaps. Future measurements will also quantify the potential magnitude of any soil moisture effect associated with our automated chamber system. To reduce the duration that the chambers were closed when the system was off for power conservation or maintenance, we either left the compressor on and the chambers in the open position or propped the chambers open. The Teledyne <inline-formula><mml:math id="M105" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer has an internal component (heated to near 70 <inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) which consumed additional power
during cold weather. We found that enclosing the <inline-formula><mml:math id="M107" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer in a
plywood box with 2.54 cm polystyrene foam insulation on four sides (leaving
one side and the back open for ventilation) reduced power use. We also
adjusted the angle of the solar array at least twice a year to increase
efficiency. Collectively, these energy-efficient measures allowed the
instrument to operate for longer periods when solar energy was limiting.
Occasionally, however, the DC/AC converter would shut down during the night
due to power limitation and would turn on again when sunlight was available.
Data from the <inline-formula><mml:math id="M108" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer were consistently biased during an 8 h
period as the instrument warmed up. We flagged and discarded these data
during postprocessing by plotting analyzer output over time and removing
peaks following periods where no output was recorded.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Measurement assumptions</title>
      <p id="d1e1695">A key principle of steady-state chamber operation is that the gas
concentration inside the chamber headspace is approximately at equilibrium
(gas flux from the soil is balanced with gas removed via the chamber outlet)
when the flux measurement is made. The time to achieve steady-state
conditions is a balance between the soil flux rate and the flow of gas
through the chamber. Here, to enable the use of smaller pumps and conserve
power we employed lower flow rates (2 L min<inline-formula><mml:math id="M109" 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>) than often employed
previously in dynamic chambers (e.g., 4 L min<inline-formula><mml:math id="M110" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>; Bowling et al., 2015).
Initial tests revealed that use of larger pumps needed to achieve 4 L min<inline-formula><mml:math id="M111" 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> flow rates over <inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m tubing runs was not
sustainable from the perspective of power supply. To validate the
steady-state assumption at 2 L min<inline-formula><mml:math id="M113" 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>, we analyzed the slope of a linear regression between concentration of <inline-formula><mml:math id="M114" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M115" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and time over the final outlet measurement period (Fig. 6f, approximately 27–29 min) using data from three separate periods chosen to cover a broad range of fluxes and spanning 2 weeks in total. We found an average increase of <inline-formula><mml:math id="M116" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.18</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">10.51</mml:mn></mml:mrow></mml:math></inline-formula> ppm <inline-formula><mml:math id="M117" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> min<inline-formula><mml:math id="M118" 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> (mean and SD) and <inline-formula><mml:math id="M119" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.57</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">8.40</mml:mn></mml:mrow></mml:math></inline-formula> ppb <inline-formula><mml:math id="M120" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> min<inline-formula><mml:math id="M121" 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, indicating that both gases were approximately at a steady state at the end of the measurement period (relative to mean chamber outlet values of 684 ppm and 494 ppb for <inline-formula><mml:math id="M122" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M123" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>, respectively). We repeated this analysis for the final inlet measurement period (Fig. 6e, approximately 19–21 min) and found a change of less than 1 ppm or ppb min<inline-formula><mml:math id="M124" 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="M125" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M126" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> relative to mean chamber inlet concentrations of 539 ppm and 331 ppb, respectively.</p>
      <p id="d1e1915">To assess temperature sensitivity of both gas analyzers under field
conditions we examined the slope and intercept of standard curves measured
during a 20 d period when air temperature ranged from <inline-formula><mml:math id="M127" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula> to 21 <inline-formula><mml:math id="M128" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and during which the instruments ran continuously. There was no significant directional trend in air temperature over this period to avoid conflating temperature-related drift and drift of the instrument over time unrelated to temperature. All four metrics examined (slope and intercept of <inline-formula><mml:math id="M129" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M130" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> calibration curves) displayed correlations with temperature. However, the impact of temperature on the slope of the <inline-formula><mml:math id="M131" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M132" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> calibrations was less than <inline-formula><mml:math id="M133" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> ppm <inline-formula><mml:math id="M134" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C<inline-formula><mml:math id="M135" 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 both values. These values correspond to <inline-formula><mml:math id="M136" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> % difference in instrument output between the highest and lowest observed temperature values at <inline-formula><mml:math id="M137" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M138" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> concentrations of 400 and 0.3 ppm, respectively. The intercept values showed greater sensitivity (0.02 and 0.003 ppm <inline-formula><mml:math id="M139" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C<inline-formula><mml:math id="M140" 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 <inline-formula><mml:math id="M141" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M142" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>,
respectively). These values correspond to a <inline-formula><mml:math id="M143" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula> ppm difference in <inline-formula><mml:math id="M144" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M145" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.08</mml:mn></mml:mrow></mml:math></inline-formula> ppm difference in <inline-formula><mml:math id="M146" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> at the high and low temperature range observed. Taken together, we found that the <inline-formula><mml:math id="M147" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> instrument had a <inline-formula><mml:math id="M148" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.006</mml:mn></mml:mrow></mml:math></inline-formula> ppm <inline-formula><mml:math id="M149" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C<inline-formula><mml:math id="M150" 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> sensitivity, in close agreement to the <inline-formula><mml:math id="M151" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.009</mml:mn></mml:mrow></mml:math></inline-formula> ppm <inline-formula><mml:math id="M152" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C<inline-formula><mml:math id="M153" 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> found by Fassbinder et al. (2013) for a similar instrument from the same manufacturer. As detailed above, standards were measured every 2 h to account for instrument sensitivity to environmental conditions. Additionally, because gas flux was calculated as the difference between and inlet and outlet concentration the intercept values canceled mathematically, thereby removing any additional bias due to temperature-related intercept drift between standard measurements. Therefore, temperature variation between measurements had negligible impact on the final flux calculation.</p>
      <?pagebreak page4074?><p id="d1e2222">Optical trace gas measurements may be affected by a number of interacting
factors including temperature, pressure, and water vapor pressure (McDermitt et al., 1993). Water vapor can be removed through chemical traps. However, the high gas flow in our system (2 L min<inline-formula><mml:math id="M154" 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>) made reagent replacement in chemical traps impractical, and preliminary work showed that membrane-based driers did not always completely remove water vapor in our operating environment, where relative humidity often reached 100 %. The <inline-formula><mml:math id="M155" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzer we utilized removed moisture through a
multitube Nafion dryer (Model NMP850KNDCB, KNF Neuberger Inc.). Water vapor
was not removed prior to measuring <inline-formula><mml:math id="M156" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentration. As we calculated
the soil <inline-formula><mml:math id="M157" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux as proportional to the concentration difference
between the inlet and outlet gases, we were primarily concerned with a change in
water vapor between the inlet and outlet measurement (Fig. 6e, f). In 2019,
measurements were made with a LI-COR 850 that included a water vapor
correction and measurement, which we used to constrain the potential impact
of water vapor on our previous <inline-formula><mml:math id="M158" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> measurements. McDermitt et al. (1993) found that the required water vapor correction using a
similar analysis was <inline-formula><mml:math id="M159" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> ppm <inline-formula><mml:math id="M160" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> at water vapor pressure of
25.3 mmol mol<inline-formula><mml:math id="M161" 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 <inline-formula><mml:math id="M162" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentration up to 1000 ppm. Water vapor pressure in the gases we measured spanned 1.0–53.6 mmol mol<inline-formula><mml:math id="M163" 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 an average difference between the inlet and outlet gas of 1.8 mmol mol<inline-formula><mml:math id="M164" 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 a maximum of 36.4 mmol mol<inline-formula><mml:math id="M165" 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>. These small observed changes in water vapor between the inlet and outlet measurements indicate a minor impact on measured <inline-formula><mml:math id="M166" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes: if the water vapor difference between the inlet and outlet caused a <inline-formula><mml:math id="M167" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> ppm bias in the measured <inline-formula><mml:math id="M168" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentration (as expected in <inline-formula><mml:math id="M169" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">99.9</mml:mn></mml:mrow></mml:math></inline-formula> % of our observations), this would impact the average measured <inline-formula><mml:math id="M170" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux (3.47 <inline-formula><mml:math id="M171" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) by <inline-formula><mml:math id="M172" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">5.2</mml:mn></mml:mrow></mml:math></inline-formula> % (0.18 <inline-formula><mml:math id="M173" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), which is within the typical range of measurement uncertainty for reproducing a known flux value under controlled conditions (Pumpanen et al., 2004). The correction under a more moderate water vapor difference between the inlet and outlet (<inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">12.6</mml:mn></mml:mrow></mml:math></inline-formula> mmol mol<inline-formula><mml:math id="M175" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) that spans <inline-formula><mml:math id="M176" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">97</mml:mn></mml:mrow></mml:math></inline-formula> % of observed differences is approximately half the impact of this extreme example (0.09 <inline-formula><mml:math id="M177" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). Unrelated to its impacts on instrument performance, water vapor can also impact flux measurements by dilution (Harazono et al., 2015). Given an
average water vapor difference between the inlet and outlet of 1.8 mmol mol<inline-formula><mml:math id="M178" 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 maximum of 36.4 mmol mol<inline-formula><mml:math id="M179" 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>, impacts of dilution on measured fluxes would also be small: typically <inline-formula><mml:math id="M180" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.18</mml:mn></mml:mrow></mml:math></inline-formula> % and as much as 3.6 %.</p>
      <p id="d1e2580">To constrain the potential impacts of water vapor on measured <inline-formula><mml:math id="M181" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
concentrations, we conducted a laboratory experiment comparing the <inline-formula><mml:math id="M182" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> instrument output between a high and low moisture measurement on a three-point standard curve. Water vapor was measured with a LI-COR 850
installed in-line and upstream of the <inline-formula><mml:math id="M183" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> sensor. To quantify the
impact of water vapor on instrument output, we compared the standard curve
created from dry standards to a curve created after bubbling the gas through
a jar of deionized water. The bubbling technique added a mean of 25.4 mmol mol<inline-formula><mml:math id="M184" 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 water vapor, spanning <inline-formula><mml:math id="M185" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">99.9</mml:mn></mml:mrow></mml:math></inline-formula> % of observations of the difference between water vapor at the inlet and outlet in the field. Standard gases ranged up to 9.96 ppm <inline-formula><mml:math id="M186" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>, greater than all differences between the inlet and outlet observed in the field. No difference was noted in <inline-formula><mml:math id="M187" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> instrument output due to the presence of water vapor, which suggested the drying column was effective at removing water vapor or that the gas filter correlation method corrected for any impacts of residual vapor.</p>
</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Temporal dynamics</title>
      <p id="d1e2679">Manual trace gas sampling by field crews is generally accomplished during
normal daytime work hours. In contrast, automated measurements can be
scheduled throughout the 24 h diel period. Figure 8 displays boxplots of
<inline-formula><mml:math id="M188" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emission from days when chambers were measured at each 4 h interval during 2017 and 2019 (the years of <italic>Zea mays</italic> cultivation). Though infrequent, we observed occasional instantaneous negative <inline-formula><mml:math id="M189" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> flux values, as observed in other ecosystems (Schlesinger, 2013; Wu et al., 2013). Figure 9 shows the <inline-formula><mml:math id="M190" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M191" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions
from two typical 1-week periods from September 2017 and August 2018. A
diel trend is visible for most chambers in August and some chambers and time
periods in September. In general agreement with previously published
automated chamber <inline-formula><mml:math id="M192" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> studies from agricultural soils, we found the
lowest rates of emission during early morning (04:00–08:00 LT) and highest
emissions during early afternoon (12:00–16:00 LT) (Akiyama et al., 2000; Alves et al., 2012; Bai et al., 2019; Flessa et al., 2002; Savage et al., 2014). Early afternoon measurements were on average 28 %
greater than the daily average from each chamber (4.04 vs. 3.15 nmol m<inline-formula><mml:math id="M193" 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> s<inline-formula><mml:math id="M194" 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 this difference varied from <inline-formula><mml:math id="M195" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">13.9</mml:mn></mml:mrow></mml:math></inline-formula> to 110 nmol m<inline-formula><mml:math id="M196" 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> s<inline-formula><mml:math id="M197" 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> among all chambers/days that were compared. The relative difference between average and peak daily emissions was in reasonable agreement with previous data from agricultural fields in the United Kingdom, Australia, and the United States (approximately 31, 47, and 33 % respectively; Alves et al., 2012; Bai et al., 2019; Savage et al., 2014). Although <inline-formula><mml:math id="M198" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes were highest and lowest during the same time periods as <inline-formula><mml:math id="M199" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>, early afternoon <inline-formula><mml:math id="M200" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes were 22 % greater than the daily mean, on average (4.38 and 3.60 <inline-formula><mml:math id="M201" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), and this difference varied between <inline-formula><mml:math id="M202" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">7.72</mml:mn></mml:mrow></mml:math></inline-formula> and 21.1 <inline-formula><mml:math id="M203" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> among all chambers/days that were compared.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><?xmltex \currentcnt{8}?><label>Figure 8</label><caption><p id="d1e2911">Boxplot of <inline-formula><mml:math id="M204" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> fluxes during each 4 h interval. Positive
outliers <inline-formula><mml:math id="M205" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> nmol m<inline-formula><mml:math id="M206" 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> s<inline-formula><mml:math id="M207" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> that comprised 1.9 % of
the total dataset are not shown for clarity.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f08.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{9}?><label>Figure 9</label><caption><p id="d1e2969"><inline-formula><mml:math id="M208" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M209" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux time series shaded by plot topographic
location over two 1-week periods in September 2017 and August 2018.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f09.png"/>

        </fig>

      <p id="d1e3002"><inline-formula><mml:math id="M210" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions pulses have often been observed following rain events (Savage et al., 2014; Sehy et al., 2003). To assess the length of the delay between rainfall and peak emissions, we analyzed the number of hours between heavy rainfall (defined as <inline-formula><mml:math id="M211" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> cm total over 24 h) and subsequent peak
<inline-formula><mml:math id="M212" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emission rate averaged over all chambers. A rain gauge located
on-site recorded precipitation data that were obtained through the Iowa Flood Center (2017). There were 45 d with total rainfall <inline-formula><mml:math id="M213" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> cm. To avoid conflating more than one rain event, we chose isolated events without rainfall <inline-formula><mml:math id="M214" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula> mm d<inline-formula><mml:math id="M215" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in the preceding or the following 2 d. Of the 15 isolated rain events observed, 4 were analyzed that did not span data gaps (Fig. 10). The rain-to-peak-emission delay varied from 12<?pagebreak page4075?> to 26 h among precipitation events which varied from 2.4 to 4.4 cm.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F10" specific-use="star"><?xmltex \currentcnt{10}?><label>Figure 10</label><caption><p id="d1e3074"><inline-formula><mml:math id="M216" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> flux time series shaded by plot topographic location over four 1-week periods in May 2017, August 2017, September 2017, and May
2019. The dashed black lines denote rain events analyzed for peak delay, and gray lines indicate rain events that did not fit our selection criteria and were
<inline-formula><mml:math id="M217" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> mm d<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>.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://amt.copernicus.org/articles/13/4065/2020/amt-13-4065-2020-f10.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <label>4</label><title>Conclusions</title>
      <p id="d1e3127">Our results indicate that steady-state flux conditions were achieved under
reasonable periods of chamber closure (29 min), equivalent to the common 30 min averaging interval for eddy covariance measurements (Loescher et al., 2006) and flow rates (2 L min<inline-formula><mml:math id="M219" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) that could be attained using low-power 12 V pumps. The results were minimally impacted by measurement error due to water vapor and were robust to changes in air temperature. We applied our high-frequency data to address two questions, how strong does diel variation impact trace gas emissions and how long is the delay between precipitation and the
frequently observed pulse in <inline-formula><mml:math id="M220" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>. Our observations showed that the
average daily emissions were most closely approximated by measurements made
between 08:00 and 12:00 LT. Although <inline-formula><mml:math id="M221" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> emissions were best approximated
during the same time interval, the difference between peak emissions and the
daily average was less pronounced and displayed less variability than
observed for <inline-formula><mml:math id="M222" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>. We found the delay between rainfall and peak <inline-formula><mml:math id="M223" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
emissions varied between 12 and 26 h – intervals that would be difficult to
capture using manual sampling methods. Both findings of temporal variability
support the need for high-frequency measurements to calculate annual soil
trace gas emissions budgets. This measurement system could also be adapted
to study other gases provided that the gas analyzers chosen are able to
tolerate field conditions. In particular, the steady-state chamber design
used here provides a powerful tool for future studies to couple gas flux
with isotopic measurements that may uncover the source and processes
underlying the observed flux.</p>
      <p id="d1e3192">Agricultural management required us to remove the chambers and associated
equipment several times of year. Without these constraints, experiments
utilizing this method could examine processes that take place on even
greater spatial scales than those utilized here (tubing runs <inline-formula><mml:math id="M224" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> m) and with a greater number of chambers. Despite these challenges, we
were able to construct and maintain eight (with one spare) high-frequency
automated chambers for subdaily <inline-formula><mml:math id="M225" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M226" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux measurements in a temperate agricultural field, with a total materials cost (<inline-formula><mml:math id="M227" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> USD 40 000, including parts for nine chambers, gas analyzers, control system, and power supply) that is a fraction of the cost of many laser-based
<inline-formula><mml:math id="M228" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> analyzers alone. We estimate that the chambers and control system
took us 130–260 h to construct and troubleshoot (with concomitant
labor/salary costs) and did not require specialized tools beyond those
available in a typical workshop.</p>
</sec>

      
      </body>
    <back><notes notes-type="codedataavailability"><title>Code and data availability</title>

      <?pagebreak page4076?><p id="d1e3253">Raw data, data logger code, and data processing scripts are available from the Iowa State University DataShare repository at
<ext-link xlink:href="https://doi.org/10.25380/iastate.12550790" ext-link-type="DOI">10.25380/iastate.12550790</ext-link> (Lawrence and Hall, 2020).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3259">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/amt-13-4065-2020-supplement" xlink:title="pdf">https://doi.org/10.5194/amt-13-4065-2020-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3268">NCL and SJH jointly designed and carried out research and prepared the manuscript.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3274">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3280">We thank Carlos Tenesaca, Anthony
Mirabito, Lucio Reyes, and Lindsay Mack for field assistance, as well as Dave Bowling for critical advice regarding chamber construction.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3285">This research has been supported by the USDA (award no. 2018-67019-27886), the Leopold Center for Sustainable Agriculture (award no. E2017-02), and the Iowa Nutrient Research Center (award no. 109-47-03-39-3650).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3291">This paper was edited by Christian Brümmer and reviewed by two anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><?label 1?><mixed-citation>Akiyama, H., Tsuruta, H., and Watanabe, T.: <inline-formula><mml:math id="M229" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M230" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">NO</mml:mi></mml:mrow></mml:math></inline-formula> emissions from soils after the application of different chemical fertilizers, Chemosphere, 2, 313–320, <ext-link xlink:href="https://doi.org/10.1016/S1465-9972(00)00010-6" ext-link-type="DOI">10.1016/S1465-9972(00)00010-6</ext-link>, 2000.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><?label 1?><mixed-citation>Alves, B. J. R., Smith, K. A., Flores, R. A., Cardoso, A. S., Oliveira, W.
R. D., Jantalia, C. P., Urquiaga, S., and Boddey, R. M.: Selection of the
most suitable sampling time for static chambers for the estimation of daily
mean <inline-formula><mml:math id="M231" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> flux from soils, Soil Biol. Biochem., 46, 129–135,
<ext-link xlink:href="https://doi.org/10.1016/j.soilbio.2011.11.022" ext-link-type="DOI">10.1016/j.soilbio.2011.11.022</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><?label 1?><mixed-citation>Ambus, P. and Robertson, G. P.: Automated near-continuous measurement of
carbon dioxide and nitrous oxide fluxes from soil, Soil Sci. Soc. Am. J.,
62, 394–400, <ext-link xlink:href="https://doi.org/10.2136/sssaj1998.03615995006200020015x" ext-link-type="DOI">10.2136/sssaj1998.03615995006200020015x</ext-link>, 1998.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><?label 1?><mixed-citation>Bai, M., Suter, H., Lam, S. K., Flesch, T. K., and Chen, D.: Comparison of slant open-path flux gradient and static closed chamber techniques to measure soil <inline-formula><mml:math id="M232" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions, Atmos. Meas. Tech., 12, 1095–1102, <ext-link xlink:href="https://doi.org/10.5194/amt-12-1095-2019" ext-link-type="DOI">10.5194/amt-12-1095-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><?label 1?><mixed-citation>Barton, L., Wolf, B., Rowlings, D., Scheer, C., Kiese, R., Grace, P.,
Stefanova, K., and Butterbach-Bahl, K.: Sampling frequency affects estimates
of annual nitrous oxide fluxes, Scientific Reports, 5, 15912, <ext-link xlink:href="https://doi.org/10.1038/srep15912" ext-link-type="DOI">10.1038/srep15912</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib6"><label>6</label><?label 1?><mixed-citation>Bowling, D. R., Egan, J. E., Hall, S. J., and Risk, D. A.: Environmental forcing does not induce diel or synoptic variation in the carbon isotope content of forest soil respiration, Biogeosciences, 12, 5143–5160, <ext-link xlink:href="https://doi.org/10.5194/bg-12-5143-2015" ext-link-type="DOI">10.5194/bg-12-5143-2015</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><?label 1?><mixed-citation>Breuer, L., Papen, H., and Butterbach-Bahl, K.: <inline-formula><mml:math id="M233" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emission from
tropical forest soils of Australia, Res., 105, 26353–26367, <ext-link xlink:href="https://doi.org/10.1029/2000JD900424" ext-link-type="DOI">10.1029/2000JD900424</ext-link>, 2000.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><?label 1?><mixed-citation>Butterbach-Bahl, K. and Dannenmann, M.: Denitrification and associated soil
<inline-formula><mml:math id="M234" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions due to agricultural activities in a changing climate,
Cur. Opin. Env. Sust., 3, 389–395, <ext-link xlink:href="https://doi.org/10.1016/j.cosust.2011.08.004" ext-link-type="DOI">10.1016/j.cosust.2011.08.004</ext-link>,
2011.</mixed-citation></ref>
      <ref id="bib1.bib9"><label>9</label><?label 1?><mixed-citation>Butterbach-Bahl, K., Gasche, R., Breuer, L., and Papen, H.: Fluxes of <inline-formula><mml:math id="M235" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">NO</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M236" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> from temperate forest soils: impact of forest type, <inline-formula><mml:math id="M237" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">N</mml:mi></mml:mrow></mml:math></inline-formula> deposition and of liming on the <inline-formula><mml:math id="M238" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">NO</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M239" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions, Nutr. Cycl. Agroecosys., 48, 79–90, <ext-link xlink:href="https://doi.org/10.1023/A:1009785521107" ext-link-type="DOI">10.1023/A:1009785521107</ext-link>, 1997.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><?label 1?><mixed-citation>Courtois, E. A., Stahl, C., Burban, B., Van den Berge, J., Berveiller, D., Bréchet, L., Soong, J. L., Arriga, N., Peñuelas, J., and Janssens, I. A.: Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest, Biogeosciences, 16, 785–796, <ext-link xlink:href="https://doi.org/10.5194/bg-16-785-2019" ext-link-type="DOI">10.5194/bg-16-785-2019</ext-link>, 2019.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><?label 1?><mixed-citation>Davidson, E. A., Savage, K., Verchot, L. V., and Navarro, R.: Minimizing
artifacts and biases in chamber-based measurements of soil respiration, Ag.
Forest Meteorol., 113, 21–37, <ext-link xlink:href="https://doi.org/10.1016/S0168-1923(02)00100-4" ext-link-type="DOI">10.1016/S0168-1923(02)00100-4</ext-link>, 2002.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><?label 1?><mixed-citation>Fang, C. and Moncrieff, J. B.: An open-top chamber for measuring soil
respiration and the influence of pressure difference on <inline-formula><mml:math id="M240" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> efflux
measurement, Funct. Ecol., 12, 319–325, <ext-link xlink:href="https://doi.org/10.1046/j.1365-2435.1998.00189.x" ext-link-type="DOI">10.1046/j.1365-2435.1998.00189.x</ext-link>, 1998.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><?label 1?><mixed-citation>Fassbinder, J. J., Schultz, N. M., Baker, J. M., and Griffis, T. J.:
Automated, low-power chamber system for measuring nitrous oxide emissions,
J. Environ. Qual., 42, 606–614, <ext-link xlink:href="https://doi.org/10.2134/jeq2012.0283" ext-link-type="DOI">10.2134/jeq2012.0283</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><?label 1?><mixed-citation>Flessa, H., Ruser, R., Schilling, R., Loftfield, N., Munch, J. C., Kaiser,
E. A., and Beese, F.: <inline-formula><mml:math id="M241" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M242" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CH</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> fluxes in potato fields:
automated measurement, management effects and temporal variation, Geoderma,
105, 307–325, <ext-link xlink:href="https://doi.org/10.1016/S0016-7061(01)00110-0" ext-link-type="DOI">10.1016/S0016-7061(01)00110-0</ext-link>, 2002.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><?label 1?><mixed-citation>Groffman, P. M., Altabet, M. A., Böhlke, J. K., Butterbach-Bahl, K.,
David, M. B., Firestone, M. K., Giblin, A. E., Kana, T. M., Nielsen, L. P.,
and Voytek, M. A.: Methods for measuring denitrification: diverse approaches
to a difficult problem, Ecol. Appl., 16, 2091–2122, <ext-link xlink:href="https://doi.org/10.1890/1051-0761(2006)016[2091:MFMDDA]2.0.CO;2" ext-link-type="DOI">10.1890/1051-0761(2006)016[2091:MFMDDA]2.0.CO;2</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><?label 1?><mixed-citation>Groffman, P. M., Butterbach-Bahl, K., Fulweiler, R. W., Gold, A. J., Morse,
J. L., Stander, E. K., Tague, C., Tonitto, C., and Vidon, P.: Challenges to
incorporating spatially and temporally explicit phenomena (hotspots and hot
moments) in denitrification models, Biogeochemistry, 93, 49–77,
<ext-link xlink:href="https://doi.org/10.1007/s10533-008-9277-5" ext-link-type="DOI">10.1007/s10533-008-9277-5</ext-link>, 2009.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><?label 1?><mixed-citation>Grolemund, G. and Wickham, H.: Dates and times made easy with lubridate, J.
Stat. Softw., 40, 1–25, <ext-link xlink:href="https://doi.org/10.18637/jss.v040.i03" ext-link-type="DOI">10.18637/jss.v040.i03</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><?label 1?><mixed-citation>Harazono, Y., Iwata, H., Sakabe, A., Ueyama, M., Takahashi, K., Nagano, H.,
Nakai, T., and Kosugi, Y.: Effects of water vapor dilution on trace gas flux,
and practical correction methods, J. Agric. Meteorol., 71, 65–76,
<ext-link xlink:href="https://doi.org/10.2480/agrmet.D-14-00003" ext-link-type="DOI">10.2480/agrmet.D-14-00003</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><?label 1?><mixed-citation>Hutchinson, G. L. and Mosier, A. R.: Improved soil cover method for field
measurement of nitrous oxide fluxes, Soil Sci. Soc. Am. J., 45, 311–316,
<ext-link xlink:href="https://doi.org/10.2136/sssaj1981.03615995004500020017x" ext-link-type="DOI">10.2136/sssaj1981.03615995004500020017x</ext-link>, 1981.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><?label 1?><mixed-citation>Iowa Flood Center: Iowa Flood Information System, available at: <uri>http://ifis.iowafloodcenter.org</uri> (last access: 21 November 2019), 2017.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><?label 1?><mixed-citation>Lawrence, N. and Hall, S.: Files accompanying “Capturing temporal heterogeneity in soil nitrous oxide fluxes with a robust and low-cost automated chamber apparatus”, Iowa State University, <ext-link xlink:href="https://doi.org/10.25380/iastate.12550790" ext-link-type="DOI">10.25380/iastate.12550790</ext-link>, 2020.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><?label 1?><mixed-citation>Loescher, H. W., Law, B. E., Mahrt, L., Hollinger, D. Y., Campbell, J., and
Wofsy, S. C.: Uncertainties in, and interpretation of, carbon flux estimates
using the eddy covariance technique, J. Geophys. Res., 111, D21S90,
<ext-link xlink:href="https://doi.org/10.1029/2005JD006932" ext-link-type="DOI">10.1029/2005JD006932</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><?label 1?><mixed-citation>Logsdon, S. D. and James, D. E.: Closed depression topography Harps soil,
revisited, Soil Horizons, 55, 1–7, <ext-link xlink:href="https://doi.org/10.2136/sh13-11-0025" ext-link-type="DOI">10.2136/sh13-11-0025</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><?label 1?><mixed-citation>McDermitt, D. K., Welles, J. M., and Eckles, R. D.: Effects of temperature,
pressure and water vapor on gas phase infrared absorption by <inline-formula><mml:math id="M243" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, available at:
<uri>https://www.licor.com/documents/sul40zcvtnr8t71arbua</uri> (last access: 21 November 2019), 1993.</mixed-citation></ref>
      <ref id="bib1.bib25"><label>25</label><?label 1?><mixed-citation>Merbold, L., Wohlfahrt, G., Butterbach-Bahl, K., Pilegaard, K., DelSontro,
T., Stoy, P. and Zona, D.: Preface: Towards a full greenhouse gas balance of the biosphere, Biogeosciences, 12, 453–456, <ext-link xlink:href="https://doi.org/10.5194/bg-12-453-2015" ext-link-type="DOI">10.5194/bg-12-453-2015</ext-link>,
2015.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><?label 1?><mixed-citation>Minasny, B., Malone, B. P., McBratney, A. B., Angers, D. A., Arrouays, D.,
Chambers, A., Chaplot, V., Chen, Z.-S., Cheng, K., Das, B. S., Field, D. J.,
Gimona, A., Hedley, C. B., Hong, S. Y., Mandal, B., Marchant, B. P., Martin,
M., McConkey, B. G., Mulder, V. L., O'Rourke, S., Richer-de-Forges, A. C.,
Odeh, I., Padarian, J., Paustian, K., Pan, G., Poggio, L., Savin, I.,
Stolbovoy, V., Stockmann, U., Sulaeman, Y., Tsui, C.-C., Vågen, T.-G.,
van Wesemael, B., and Winowiecki, L.: Soil carbon 4 per mille, Geoderma, 292,
59–86, <ext-link xlink:href="https://doi.org/10.1016/j.geoderma.2017.01.002" ext-link-type="DOI">10.1016/j.geoderma.2017.01.002</ext-link>, 2017.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><?label 1?><mixed-citation>Moyes, A. B., Schauer, A. J., Siegwolf, R. T. W., and Bowling, D. R.: An
injection method for measuring the carbon isotope content of soil carbon
dioxide and soil respiration with a tunable diode laser absorption
spectrometer, Rapid Commun. Mass Sp., 24, 894–900, <ext-link xlink:href="https://doi.org/10.1002/rcm.4466" ext-link-type="DOI">10.1002/rcm.4466</ext-link>,
2010a.</mixed-citation></ref>
      <ref id="bib1.bib28"><label>28</label><?label 1?><mixed-citation>Moyes, A. B., Gaines, S. J., Siegwolf, R. T. W., and Bowling, D. R.:
Diffusive fractionation complicates isotopic partitioning of autotrophic and
heterotrophic sources of soil respiration, Plant Cell Environ., 33, 1804–1819, <ext-link xlink:href="https://doi.org/10.1111/j.1365-3040.2010.02185.x" ext-link-type="DOI">10.1111/j.1365-3040.2010.02185.x</ext-link>, 2010b.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><?label 1?><mixed-citation>Nickerson, N. and Risk, D.: Physical controls on the isotopic composition of
soil-respired <inline-formula><mml:math id="M244" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, J. Geophys. Res., 114, G01013,
<ext-link xlink:href="https://doi.org/10.1029/2008JG000766" ext-link-type="DOI">10.1029/2008JG000766</ext-link>, 2009.</mixed-citation></ref>
      <?pagebreak page4078?><ref id="bib1.bib30"><label>30</label><?label 1?><mixed-citation>Norman, J. M., Kucharik, C. J., Gower, S. T., Baldocchi, D. D., Crill, P.
M., Rayment, M., Savage, K., and Striegl, R. G.: A comparison of six methods
for measuring soil-surface carbon dioxide fluxes, J. Geophys. Res., 102, 28771–28777, <ext-link xlink:href="https://doi.org/10.1029/97JD01440" ext-link-type="DOI">10.1029/97JD01440</ext-link>, 1997.</mixed-citation></ref>
      <ref id="bib1.bib31"><label>31</label><?label 1?><mixed-citation>Papen, H. and Butterbach-Bahl, K.: A 3-year continuous record of nitrogen
trace gas fluxes from untreated and limed soil of a N-saturated spruce and
beech forest ecosystem in Germany: 1. <inline-formula><mml:math id="M245" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> emissions, J. Geophys.
Res., 104, 18487–18503, <ext-link xlink:href="https://doi.org/10.1029/1999JD900293" ext-link-type="DOI">10.1029/1999JD900293</ext-link>, 1999.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><?label 1?><mixed-citation>Parkin, T. B.: Effect of sampling frequency on estimates of cumulative
nitrous oxide emissions, J. Environ. Qual., 37, 1390–1395,
<ext-link xlink:href="https://doi.org/10.2134/jeq2007.0333" ext-link-type="DOI">10.2134/jeq2007.0333</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><?label 1?><mixed-citation>Paustian, K., Lehmann, J., Ogle, S., Reay, D., Robertson, G. P., and Smith,
P.: Climate-smart soils, Nature, 532, 49–57, <ext-link xlink:href="https://doi.org/10.1038/nature17174" ext-link-type="DOI">10.1038/nature17174</ext-link>,
2016.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><?label 1?><mixed-citation>Pihlatie, M., Rinne, J., Ambus, P., Pilegaard, K., Dorsey, J. R., Rannik, Ü., Markkanen, T., Launiainen, S., and Vesala, T.: Nitrous oxide emissions from a beech forest floor measured by eddy covariance and soil enclosure techniques, Biogeosciences, 2, 377–387, <ext-link xlink:href="https://doi.org/10.5194/bg-2-377-2005" ext-link-type="DOI">10.5194/bg-2-377-2005</ext-link>, 2005.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><?label 1?><mixed-citation>Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., and R Core Team: nlme:
linear and nonlinear mixed effects models, R package version 3.1-140,  available at: <uri>https://cran.r-project.org/web/packages/nlme/index.html</uri>, last access: 1 June 2020.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><?label 1?><mixed-citation>Pumpanen, J., Kolari, P., Ilvesniemi, H., Minkkinen, K., Vesala, T.,
Niinistö, S., Lohila, A., Larmola, T., Morero, M., Pihlatie, M.,
Janssens, I., Yuste, J. C., Grünzweig, J. M., Reth, S., Subke, J.-A.,
Savage, K., Kutsch, W., Østreng, G., Ziegler, W., Anthoni, P., Lindroth,
A., and Hari, P.: Comparison of different chamber techniques for measuring
soil <inline-formula><mml:math id="M246" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> efflux, Agr. Forest Meteorol., 123, 159–176,
<ext-link xlink:href="https://doi.org/10.1016/j.agrformet.2003.12.001" ext-link-type="DOI">10.1016/j.agrformet.2003.12.001</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><?label 1?><mixed-citation>Rayment, M. B. and Jarvis, P. G.: An improved open chamber system for
measuring soil <inline-formula><mml:math id="M247" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> effluxes in the field, J. Geophys. Res., 102, 28779–28784, <ext-link xlink:href="https://doi.org/10.1029/97JD01103" ext-link-type="DOI">10.1029/97JD01103</ext-link>, 1997.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib38"><label>38</label><?label 1?><mixed-citation>R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria,
available at: <uri>https://www.R-project.org/</uri> (last access: 1 June 2020), 2019.</mixed-citation></ref>
      <ref id="bib1.bib39"><label>39</label><?label 1?><mixed-citation>Riggs, A. C., Stannard, D. I., Maestas, F. B., Karlinger, M. R., and Striegl,
R. G.: Soil <inline-formula><mml:math id="M248" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux in the Amargosa Desert, Nevada, during El Nino
1998 and La Nina 1999, US Geol. Surv. Sci. Investig. Rep., 2009–5061, 25 pp., available at: <uri>https://pubs.usgs.gov/sir/2009/5061/</uri> (last access: 1 June 2020), 2009.</mixed-citation></ref>
      <ref id="bib1.bib40"><label>40</label><?label 1?><mixed-citation>Rosenstock, T. S., Diaz-Pines, E., Zuazo, P., Jordan, G., Predotova, M.,
Mutuo, P., Abwanda, S., Thiong'o, M., Buerkert, A., Rufino, M. C., Kiese,
R., Neufeldt, H., and Butterbach-Bahl, K.: Accuracy and precision of
photoacoustic spectroscopy not guaranteed, Glob. Change Biol., 19,
3565–3567, <ext-link xlink:href="https://doi.org/10.1111/gcb.12332" ext-link-type="DOI">10.1111/gcb.12332</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib41"><label>41</label><?label 1?><mixed-citation>Savage, K., Phillips, R., and Davidson, E.: High temporal frequency measurements of greenhouse gas emissions from soils, Biogeosciences, 11, 2709–2720, <ext-link xlink:href="https://doi.org/10.5194/bg-11-2709-2014" ext-link-type="DOI">10.5194/bg-11-2709-2014</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib42"><label>42</label><?label 1?><mixed-citation>Schlesinger, W. H.: An estimate of the global sink for nitrous oxide in
soils, Glob. Change Biol., 19, 2929–2931, <ext-link xlink:href="https://doi.org/10.1111/gcb.12239" ext-link-type="DOI">10.1111/gcb.12239</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib43"><label>43</label><?label 1?><mixed-citation>Sehy, U., Ruser, R., and Munch, J. C.: Nitrous oxide fluxes from maize
fields: relationship to yield, site-specific fertilization, and soil
conditions, Agr. Ecosyst. Environ., 99, 97–111,
<ext-link xlink:href="https://doi.org/10.1016/S0167-8809(03)00139-7" ext-link-type="DOI">10.1016/S0167-8809(03)00139-7</ext-link>, 2003.</mixed-citation></ref>
      <ref id="bib1.bib44"><label>44</label><?label 1?><mixed-citation>Wickham, H.: Reshaping data with the reshape package, J. Stat. Softw.,
21, 1–20, <ext-link xlink:href="https://doi.org/10.18637/jss.v021.i12" ext-link-type="DOI">10.18637/jss.v021.i12</ext-link>, 2007.</mixed-citation></ref>
      <ref id="bib1.bib45"><label>45</label><?label 1?><mixed-citation>Wu, D., Dong, W., Oenema, O., Wang, Y., Trebs, I., and Hu, C.: <inline-formula><mml:math id="M249" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
consumption by low-nitrogen soil and its regulation by water and oxygen,
Soil Biol. Biochem., 60, 165–172, <ext-link xlink:href="https://doi.org/10.1016/j.soilbio.2013.01.028" ext-link-type="DOI">10.1016/j.soilbio.2013.01.028</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bib46"><label>46</label><?label 1?><mixed-citation>Xu, L., Furtaw, M. D., Madsen, R. A., Garcia, R. L., Anderson, D. J., and
McDermitt, D. K.: On maintaining pressure equilibrium between a soil
<inline-formula><mml:math id="M250" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux chamber and the ambient air, J. Geophys. Res., 111, D08S10,
<ext-link xlink:href="https://doi.org/10.1029/2005JD006435" ext-link-type="DOI">10.1029/2005JD006435</ext-link>, 2006.</mixed-citation></ref>

  </ref-list></back>
    <!--<article-title-html>Capturing temporal heterogeneity in soil nitrous oxide fluxes with a robust and low-cost automated chamber apparatus</article-title-html>
<abstract-html><p>Soils play an important role in Earth's climate system through
their regulation of trace greenhouse gases. Despite decades of soil gas flux
measurements using manual chamber methods, limited temporal coverage has led
to high uncertainty in flux magnitude and variability, particularly during
peak emission events. Automated chamber measurement systems can collect
high-frequency (subdaily) measurements across various spatial scales but
may be prohibitively expensive or incompatible with field conditions. Here
we describe the construction and operational details for a robust,
relatively inexpensive, and adaptable automated dynamic (steady-state)
chamber measurement system modified from previously published methods, using
relatively low cost analyzers to measure nitrous oxide (N<sub>2</sub>O) and carbon
dioxide (CO<sub>2</sub>). The system was robust to intermittent flooding of
chambers, long tubing runs ( &gt; 100&thinsp;m), and operational temperature extremes (−12 to 39&thinsp;°C) and was entirely powered by solar energy.
Using data collected between 2017 and 2019 we tested the underlying principles
of chamber operation and examined N<sub>2</sub>O diel variation and rain-pulse
timing that would be difficult to characterize using infrequent manual
measurements. Stable steady-state flux dynamics were achieved during 29&thinsp;min
chamber closure periods at a relatively low flow rate (2&thinsp;L&thinsp;min<sup>−1</sup>).
Instrument performance and calculated fluxes were minimally impacted by
variation in air temperature and water vapor. Measurements between 08:00 and
12:00&thinsp;LT were closest to the daily mean N<sub>2</sub>O and CO<sub>2</sub> emission. Afternoon fluxes (12:00–16:00&thinsp;LT) were 28&thinsp;% higher than the daily mean for
N<sub>2</sub>O (4.04 vs. 3.15&thinsp;nmol&thinsp;m<sup>−2</sup>&thinsp;s<sup>−1</sup>) and were 22&thinsp;% higher for CO<sub>2</sub> (4.38 vs. 3.60&thinsp;µmol m<sup>−2</sup> s<sup>−1</sup>). High rates of N<sub>2</sub>O emission are frequently observed after precipitation. Following four discrete rainfall events, we found a 12–26&thinsp;h delay before peak N<sub>2</sub>O flux, which would be difficult to capture with manual measurements. Our observation of substantial and variable diel trends and rapid but variable onset of high N<sub>2</sub>O emissions following rainfall supports the need for
high-frequency measurements.</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Akiyama, H., Tsuruta, H., and Watanabe, T.: N<sub>2</sub>O and NO emissions from soils after the application of different chemical fertilizers, Chemosphere, 2, 313–320, <a href="https://doi.org/10.1016/S1465-9972(00)00010-6" target="_blank">https://doi.org/10.1016/S1465-9972(00)00010-6</a>, 2000.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Alves, B. J. R., Smith, K. A., Flores, R. A., Cardoso, A. S., Oliveira, W.
R. D., Jantalia, C. P., Urquiaga, S., and Boddey, R. M.: Selection of the
most suitable sampling time for static chambers for the estimation of daily
mean N<sub>2</sub>O flux from soils, Soil Biol. Biochem., 46, 129–135,
<a href="https://doi.org/10.1016/j.soilbio.2011.11.022" target="_blank">https://doi.org/10.1016/j.soilbio.2011.11.022</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Ambus, P. and Robertson, G. P.: Automated near-continuous measurement of
carbon dioxide and nitrous oxide fluxes from soil, Soil Sci. Soc. Am. J.,
62, 394–400, <a href="https://doi.org/10.2136/sssaj1998.03615995006200020015x" target="_blank">https://doi.org/10.2136/sssaj1998.03615995006200020015x</a>, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Bai, M., Suter, H., Lam, S. K., Flesch, T. K., and Chen, D.: Comparison of slant open-path flux gradient and static closed chamber techniques to measure soil N<sub>2</sub>O emissions, Atmos. Meas. Tech., 12, 1095–1102, <a href="https://doi.org/10.5194/amt-12-1095-2019" target="_blank">https://doi.org/10.5194/amt-12-1095-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Barton, L., Wolf, B., Rowlings, D., Scheer, C., Kiese, R., Grace, P.,
Stefanova, K., and Butterbach-Bahl, K.: Sampling frequency affects estimates
of annual nitrous oxide fluxes, Scientific Reports, 5, 15912, <a href="https://doi.org/10.1038/srep15912" target="_blank">https://doi.org/10.1038/srep15912</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Bowling, D. R., Egan, J. E., Hall, S. J., and Risk, D. A.: Environmental forcing does not induce diel or synoptic variation in the carbon isotope content of forest soil respiration, Biogeosciences, 12, 5143–5160, <a href="https://doi.org/10.5194/bg-12-5143-2015" target="_blank">https://doi.org/10.5194/bg-12-5143-2015</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Breuer, L., Papen, H., and Butterbach-Bahl, K.: N<sub>2</sub>O emission from
tropical forest soils of Australia, Res., 105, 26353–26367, <a href="https://doi.org/10.1029/2000JD900424" target="_blank">https://doi.org/10.1029/2000JD900424</a>, 2000.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Butterbach-Bahl, K. and Dannenmann, M.: Denitrification and associated soil
N<sub>2</sub>O emissions due to agricultural activities in a changing climate,
Cur. Opin. Env. Sust., 3, 389–395, <a href="https://doi.org/10.1016/j.cosust.2011.08.004" target="_blank">https://doi.org/10.1016/j.cosust.2011.08.004</a>,
2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Butterbach-Bahl, K., Gasche, R., Breuer, L., and Papen, H.: Fluxes of NO and N<sub>2</sub>O from temperate forest soils: impact of forest type, N deposition and of liming on the NO and N<sub>2</sub>O emissions, Nutr. Cycl. Agroecosys., 48, 79–90, <a href="https://doi.org/10.1023/A:1009785521107" target="_blank">https://doi.org/10.1023/A:1009785521107</a>, 1997.
</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
Courtois, E. A., Stahl, C., Burban, B., Van den Berge, J., Berveiller, D., Bréchet, L., Soong, J. L., Arriga, N., Peñuelas, J., and Janssens, I. A.: Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest, Biogeosciences, 16, 785–796, <a href="https://doi.org/10.5194/bg-16-785-2019" target="_blank">https://doi.org/10.5194/bg-16-785-2019</a>, 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
Davidson, E. A., Savage, K., Verchot, L. V., and Navarro, R.: Minimizing
artifacts and biases in chamber-based measurements of soil respiration, Ag.
Forest Meteorol., 113, 21–37, <a href="https://doi.org/10.1016/S0168-1923(02)00100-4" target="_blank">https://doi.org/10.1016/S0168-1923(02)00100-4</a>, 2002.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
Fang, C. and Moncrieff, J. B.: An open-top chamber for measuring soil
respiration and the influence of pressure difference on CO<sub>2</sub> efflux
measurement, Funct. Ecol., 12, 319–325, <a href="https://doi.org/10.1046/j.1365-2435.1998.00189.x" target="_blank">https://doi.org/10.1046/j.1365-2435.1998.00189.x</a>, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
Fassbinder, J. J., Schultz, N. M., Baker, J. M., and Griffis, T. J.:
Automated, low-power chamber system for measuring nitrous oxide emissions,
J. Environ. Qual., 42, 606–614, <a href="https://doi.org/10.2134/jeq2012.0283" target="_blank">https://doi.org/10.2134/jeq2012.0283</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
Flessa, H., Ruser, R., Schilling, R., Loftfield, N., Munch, J. C., Kaiser,
E. A., and Beese, F.: N<sub>2</sub>O and CH<sub>4</sub> fluxes in potato fields:
automated measurement, management effects and temporal variation, Geoderma,
105, 307–325, <a href="https://doi.org/10.1016/S0016-7061(01)00110-0" target="_blank">https://doi.org/10.1016/S0016-7061(01)00110-0</a>, 2002.
</mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
Groffman, P. M., Altabet, M. A., Böhlke, J. K., Butterbach-Bahl, K.,
David, M. B., Firestone, M. K., Giblin, A. E., Kana, T. M., Nielsen, L. P.,
and Voytek, M. A.: Methods for measuring denitrification: diverse approaches
to a difficult problem, Ecol. Appl., 16, 2091–2122, <a href="https://doi.org/10.1890/1051-0761(2006)016[2091:MFMDDA]2.0.CO;2" target="_blank">https://doi.org/10.1890/1051-0761(2006)016[2091:MFMDDA]2.0.CO;2</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
Groffman, P. M., Butterbach-Bahl, K., Fulweiler, R. W., Gold, A. J., Morse,
J. L., Stander, E. K., Tague, C., Tonitto, C., and Vidon, P.: Challenges to
incorporating spatially and temporally explicit phenomena (hotspots and hot
moments) in denitrification models, Biogeochemistry, 93, 49–77,
<a href="https://doi.org/10.1007/s10533-008-9277-5" target="_blank">https://doi.org/10.1007/s10533-008-9277-5</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
Grolemund, G. and Wickham, H.: Dates and times made easy with lubridate, J.
Stat. Softw., 40, 1–25, <a href="https://doi.org/10.18637/jss.v040.i03" target="_blank">https://doi.org/10.18637/jss.v040.i03</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
Harazono, Y., Iwata, H., Sakabe, A., Ueyama, M., Takahashi, K., Nagano, H.,
Nakai, T., and Kosugi, Y.: Effects of water vapor dilution on trace gas flux,
and practical correction methods, J. Agric. Meteorol., 71, 65–76,
<a href="https://doi.org/10.2480/agrmet.D-14-00003" target="_blank">https://doi.org/10.2480/agrmet.D-14-00003</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
Hutchinson, G. L. and Mosier, A. R.: Improved soil cover method for field
measurement of nitrous oxide fluxes, Soil Sci. Soc. Am. J., 45, 311–316,
<a href="https://doi.org/10.2136/sssaj1981.03615995004500020017x" target="_blank">https://doi.org/10.2136/sssaj1981.03615995004500020017x</a>, 1981.
</mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
Iowa Flood Center: Iowa Flood Information System, available at: <a href="http://ifis.iowafloodcenter.org" target="_blank"/> (last access: 21 November 2019), 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
Lawrence, N. and Hall, S.: Files accompanying “Capturing temporal heterogeneity in soil nitrous oxide fluxes with a robust and low-cost automated chamber apparatus”, Iowa State University, <a href="https://doi.org/10.25380/iastate.12550790" target="_blank">https://doi.org/10.25380/iastate.12550790</a>, 2020.
</mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
Loescher, H. W., Law, B. E., Mahrt, L., Hollinger, D. Y., Campbell, J., and
Wofsy, S. C.: Uncertainties in, and interpretation of, carbon flux estimates
using the eddy covariance technique, J. Geophys. Res., 111, D21S90,
<a href="https://doi.org/10.1029/2005JD006932" target="_blank">https://doi.org/10.1029/2005JD006932</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
Logsdon, S. D. and James, D. E.: Closed depression topography Harps soil,
revisited, Soil Horizons, 55, 1–7, <a href="https://doi.org/10.2136/sh13-11-0025" target="_blank">https://doi.org/10.2136/sh13-11-0025</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
McDermitt, D. K., Welles, J. M., and Eckles, R. D.: Effects of temperature,
pressure and water vapor on gas phase infrared absorption by CO<sub>2</sub>, available at:
<a href="https://www.licor.com/documents/sul40zcvtnr8t71arbua" target="_blank"/> (last access: 21 November 2019), 1993.
</mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
Merbold, L., Wohlfahrt, G., Butterbach-Bahl, K., Pilegaard, K., DelSontro,
T., Stoy, P. and Zona, D.: Preface: Towards a full greenhouse gas balance of the biosphere, Biogeosciences, 12, 453–456, <a href="https://doi.org/10.5194/bg-12-453-2015" target="_blank">https://doi.org/10.5194/bg-12-453-2015</a>,
2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
Minasny, B., Malone, B. P., McBratney, A. B., Angers, D. A., Arrouays, D.,
Chambers, A., Chaplot, V., Chen, Z.-S., Cheng, K., Das, B. S., Field, D. J.,
Gimona, A., Hedley, C. B., Hong, S. Y., Mandal, B., Marchant, B. P., Martin,
M., McConkey, B. G., Mulder, V. L., O'Rourke, S., Richer-de-Forges, A. C.,
Odeh, I., Padarian, J., Paustian, K., Pan, G., Poggio, L., Savin, I.,
Stolbovoy, V., Stockmann, U., Sulaeman, Y., Tsui, C.-C., Vågen, T.-G.,
van Wesemael, B., and Winowiecki, L.: Soil carbon 4 per mille, Geoderma, 292,
59–86, <a href="https://doi.org/10.1016/j.geoderma.2017.01.002" target="_blank">https://doi.org/10.1016/j.geoderma.2017.01.002</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
Moyes, A. B., Schauer, A. J., Siegwolf, R. T. W., and Bowling, D. R.: An
injection method for measuring the carbon isotope content of soil carbon
dioxide and soil respiration with a tunable diode laser absorption
spectrometer, Rapid Commun. Mass Sp., 24, 894–900, <a href="https://doi.org/10.1002/rcm.4466" target="_blank">https://doi.org/10.1002/rcm.4466</a>,
2010a.
</mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
Moyes, A. B., Gaines, S. J., Siegwolf, R. T. W., and Bowling, D. R.:
Diffusive fractionation complicates isotopic partitioning of autotrophic and
heterotrophic sources of soil respiration, Plant Cell Environ., 33, 1804–1819, <a href="https://doi.org/10.1111/j.1365-3040.2010.02185.x" target="_blank">https://doi.org/10.1111/j.1365-3040.2010.02185.x</a>, 2010b.
</mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
Nickerson, N. and Risk, D.: Physical controls on the isotopic composition of
soil-respired CO<sub>2</sub>, J. Geophys. Res., 114, G01013,
<a href="https://doi.org/10.1029/2008JG000766" target="_blank">https://doi.org/10.1029/2008JG000766</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
Norman, J. M., Kucharik, C. J., Gower, S. T., Baldocchi, D. D., Crill, P.
M., Rayment, M., Savage, K., and Striegl, R. G.: A comparison of six methods
for measuring soil-surface carbon dioxide fluxes, J. Geophys. Res., 102, 28771–28777, <a href="https://doi.org/10.1029/97JD01440" target="_blank">https://doi.org/10.1029/97JD01440</a>, 1997.
</mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
Papen, H. and Butterbach-Bahl, K.: A 3-year continuous record of nitrogen
trace gas fluxes from untreated and limed soil of a N-saturated spruce and
beech forest ecosystem in Germany: 1. N<sub>2</sub>O emissions, J. Geophys.
Res., 104, 18487–18503, <a href="https://doi.org/10.1029/1999JD900293" target="_blank">https://doi.org/10.1029/1999JD900293</a>, 1999.
</mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
Parkin, T. B.: Effect of sampling frequency on estimates of cumulative
nitrous oxide emissions, J. Environ. Qual., 37, 1390–1395,
<a href="https://doi.org/10.2134/jeq2007.0333" target="_blank">https://doi.org/10.2134/jeq2007.0333</a>, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
Paustian, K., Lehmann, J., Ogle, S., Reay, D., Robertson, G. P., and Smith,
P.: Climate-smart soils, Nature, 532, 49–57, <a href="https://doi.org/10.1038/nature17174" target="_blank">https://doi.org/10.1038/nature17174</a>,
2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
Pihlatie, M., Rinne, J., Ambus, P., Pilegaard, K., Dorsey, J. R., Rannik, Ü., Markkanen, T., Launiainen, S., and Vesala, T.: Nitrous oxide emissions from a beech forest floor measured by eddy covariance and soil enclosure techniques, Biogeosciences, 2, 377–387, <a href="https://doi.org/10.5194/bg-2-377-2005" target="_blank">https://doi.org/10.5194/bg-2-377-2005</a>, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., and R Core Team: nlme:
linear and nonlinear mixed effects models, R package version 3.1-140,  available at: <a href="https://cran.r-project.org/web/packages/nlme/index.html" target="_blank"/>, last access: 1 June 2020.
</mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
Pumpanen, J., Kolari, P., Ilvesniemi, H., Minkkinen, K., Vesala, T.,
Niinistö, S., Lohila, A., Larmola, T., Morero, M., Pihlatie, M.,
Janssens, I., Yuste, J. C., Grünzweig, J. M., Reth, S., Subke, J.-A.,
Savage, K., Kutsch, W., Østreng, G., Ziegler, W., Anthoni, P., Lindroth,
A., and Hari, P.: Comparison of different chamber techniques for measuring
soil CO<sub>2</sub> efflux, Agr. Forest Meteorol., 123, 159–176,
<a href="https://doi.org/10.1016/j.agrformet.2003.12.001" target="_blank">https://doi.org/10.1016/j.agrformet.2003.12.001</a>, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
Rayment, M. B. and Jarvis, P. G.: An improved open chamber system for
measuring soil CO<sub>2</sub> effluxes in the field, J. Geophys. Res., 102, 28779–28784, <a href="https://doi.org/10.1029/97JD01103" target="_blank">https://doi.org/10.1029/97JD01103</a>, 1997.

</mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
R Core Team: R: A Language and Environment for Statistical Computing, R
Foundation for Statistical Computing, Vienna, Austria,
available at: <a href="https://www.R-project.org/" target="_blank"/> (last access: 1 June 2020), 2019.
</mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
Riggs, A. C., Stannard, D. I., Maestas, F. B., Karlinger, M. R., and Striegl,
R. G.: Soil CO<sub>2</sub> flux in the Amargosa Desert, Nevada, during El Nino
1998 and La Nina 1999, US Geol. Surv. Sci. Investig. Rep., 2009–5061, 25 pp., available at: <a href="https://pubs.usgs.gov/sir/2009/5061/" target="_blank"/> (last access: 1 June 2020), 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
Rosenstock, T. S., Diaz-Pines, E., Zuazo, P., Jordan, G., Predotova, M.,
Mutuo, P., Abwanda, S., Thiong'o, M., Buerkert, A., Rufino, M. C., Kiese,
R., Neufeldt, H., and Butterbach-Bahl, K.: Accuracy and precision of
photoacoustic spectroscopy not guaranteed, Glob. Change Biol., 19,
3565–3567, <a href="https://doi.org/10.1111/gcb.12332" target="_blank">https://doi.org/10.1111/gcb.12332</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>41</label><mixed-citation>
Savage, K., Phillips, R., and Davidson, E.: High temporal frequency measurements of greenhouse gas emissions from soils, Biogeosciences, 11, 2709–2720, <a href="https://doi.org/10.5194/bg-11-2709-2014" target="_blank">https://doi.org/10.5194/bg-11-2709-2014</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>42</label><mixed-citation>
Schlesinger, W. H.: An estimate of the global sink for nitrous oxide in
soils, Glob. Change Biol., 19, 2929–2931, <a href="https://doi.org/10.1111/gcb.12239" target="_blank">https://doi.org/10.1111/gcb.12239</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib43"><label>43</label><mixed-citation>
Sehy, U., Ruser, R., and Munch, J. C.: Nitrous oxide fluxes from maize
fields: relationship to yield, site-specific fertilization, and soil
conditions, Agr. Ecosyst. Environ., 99, 97–111,
<a href="https://doi.org/10.1016/S0167-8809(03)00139-7" target="_blank">https://doi.org/10.1016/S0167-8809(03)00139-7</a>, 2003.
</mixed-citation></ref-html>
<ref-html id="bib1.bib44"><label>44</label><mixed-citation>
Wickham, H.: Reshaping data with the reshape package, J. Stat. Softw.,
21, 1–20, <a href="https://doi.org/10.18637/jss.v021.i12" target="_blank">https://doi.org/10.18637/jss.v021.i12</a>, 2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib45"><label>45</label><mixed-citation>
Wu, D., Dong, W., Oenema, O., Wang, Y., Trebs, I., and Hu, C.: N<sub>2</sub>O
consumption by low-nitrogen soil and its regulation by water and oxygen,
Soil Biol. Biochem., 60, 165–172, <a href="https://doi.org/10.1016/j.soilbio.2013.01.028" target="_blank">https://doi.org/10.1016/j.soilbio.2013.01.028</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib46"><label>46</label><mixed-citation>
Xu, L., Furtaw, M. D., Madsen, R. A., Garcia, R. L., Anderson, D. J., and
McDermitt, D. K.: On maintaining pressure equilibrium between a soil
CO<sub>2</sub> flux chamber and the ambient air, J. Geophys. Res., 111, D08S10,
<a href="https://doi.org/10.1029/2005JD006435" target="_blank">https://doi.org/10.1029/2005JD006435</a>, 2006.
</mixed-citation></ref-html>--></article>
