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<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 \makeatother\@nolinetrue\makeatletter?>
  <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-11-2441-2018</article-id><title-group><article-title>Implementation of electrochemical, optical and denuder-based sensors and
sampling techniques on UAV for volcanic gas measurements: examples from
Masaya, Turrialba and Stromboli volcanoes</article-title><alt-title>Implementation of sensors and sampling techniques on UAV</alt-title>
      </title-group><?xmltex \runningtitle{Implementation of sensors and sampling techniques on UAV}?><?xmltex \runningauthor{J. R\"{u}diger et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff8">
          <name><surname>Rüdiger</surname><given-names>Julian</given-names></name>
          <email>j.ruediger@uni-mainz.de</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Tirpitz</surname><given-names>Jan-Lukas</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>de Moor</surname><given-names>J. Maarten</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2 aff4 aff5">
          <name><surname>Bobrowski</surname><given-names>Nicole</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Gutmann</surname><given-names>Alexandra</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2188-5384</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Liuzzo</surname><given-names>Marco</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-3099-7505</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Ibarra</surname><given-names>Martha</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Hoffmann</surname><given-names>Thorsten</given-names></name>
          <email>hoffmant@uni-mainz.de</email>
        </contrib>
        <aff id="aff1"><label>1</label><institution>Johannes Gutenberg-University, Institute of Inorganic and Analytical Chemistry, Mainz, Germany</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>University of Heidelberg, Institute for Environmental Physics, Heidelberg, Germany</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Observatorio Vulcanológico y Sismológico de Costa Rica, Heredia, Costa Rica</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Johannes Gutenberg-University, Institute of Geosciences, Mainz, Germany</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Max Planck Institute for Chemistry, Mainz, Germany</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Palermo, Italy</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Instituto Nicaragüense de Estudios Territoriales, Managua, Nicaragua</institution>
        </aff>
        <aff id="aff8"><label>a</label><institution>now at: University of Bayreuth, Atmospheric Chemistry, Bayreuth, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Julian Rüdiger (j.ruediger@uni-mainz.de) and Thorsten Hoffmann (hoffmant@uni-mainz.de)</corresp></author-notes><pub-date><day>26</day><month>April</month><year>2018</year></pub-date>
      
      <volume>11</volume>
      <issue>4</issue>
      <fpage>2441</fpage><lpage>2457</lpage>
      <history>
        <date date-type="received"><day>13</day><month>September</month><year>2017</year></date>
           <date date-type="rev-request"><day>28</day><month>November</month><year>2017</year></date>
           <date date-type="rev-recd"><day>21</day><month>February</month><year>2018</year></date>
           <date date-type="accepted"><day>30</day><month>March</month><year>2018</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2018 Julian Rüdiger et al.</copyright-statement>
        <copyright-year>2018</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/11/2441/2018/amt-11-2441-2018.html">This article is available from https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018.html</self-uri><self-uri xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018.pdf">The full text article is available as a PDF file from https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e195">Volcanoes are a natural source of several reactive gases (e.g.,
sulfur and halogen containing species) and nonreactive gases (e.g.,
carbon dioxide) to the atmosphere. The relative abundance of carbon and
sulfur in volcanic gas as well as the total sulfur dioxide emission rate from
a volcanic vent are established parameters in current volcano-monitoring
strategies, and they oftentimes allow insights into subsurface processes.
However, chemical reactions involving halogens are thought to have
local to regional impact on the atmospheric chemistry around passively
degassing volcanoes. In this study we demonstrate the successful deployment
of a multirotor UAV (quadcopter) system with custom-made lightweight payloads
for the compositional analysis and gas flux estimation of volcanic plumes.
The various applications and their potential are presented and discussed in
example studies at three volcanoes encompassing flight heights of 450 to
3300 m and various states of volcanic activity. Field applications were
performed at Stromboli volcano (Italy), Turrialba volcano (Costa Rica) and
Masaya volcano (Nicaragua). Two in situ gas-measuring systems adapted for
autonomous airborne measurements, based on electrochemical and optical
detection principles, as well as an airborne sampling unit, are introduced.
We show volcanic gas composition results including abundances of CO<inline-formula><mml:math id="M1" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>,
SO<inline-formula><mml:math id="M2" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and halogen species. The new instrumental setups were compared with
established instruments during ground-based measurements at Masaya volcano,
which resulted in CO<inline-formula><mml:math id="M3" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M4" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M5" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios of 3.6 <inline-formula><mml:math id="M6" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.4. For
total SO<inline-formula><mml:math id="M7" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux estimations a small differential optical absorption
spectroscopy (DOAS) system measured SO<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts on transversal
flights below the plume at Turrialba volcano, giving
1776 <inline-formula><mml:math id="M9" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1108 T d<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and 1616 <inline-formula><mml:math id="M11" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1007 T d<inline-formula><mml:math id="M12" 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 SO<inline-formula><mml:math id="M13" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
during two traverses. At Stromboli volcano, elevated CO<inline-formula><mml:math id="M14" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M15" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M16" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
ratios were observed at spatial and temporal proximity to explosions by
airborne in situ measurements. Reactive bromine to sulfur ratios of
0.19 <inline-formula><mml:math id="M17" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> to 9.8 <inline-formula><mml:math id="M19" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> were measured in situ
in the plume of Stromboli volcano, downwind of the vent.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

      <?xmltex \hack{\newpage}?>
<?pagebreak page2442?><sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e388">Gaseous volcanic emissions consist of a variety of different compounds and
are dominated by water vapor (H<inline-formula><mml:math id="M21" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O), carbon dioxide (CO<inline-formula><mml:math id="M22" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), sulfur
dioxide (SO<inline-formula><mml:math id="M23" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), and hydrogen sulfide (H<inline-formula><mml:math id="M24" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>S) (Symonds et al., 1994).
Minor abundant but nonetheless important gas species are halogen-bearing
compounds which are emitted as hydrogen halides (HF, HCl, HBr and HI) and
later partly transformed by heterogeneous reactions into other halogen
species, such as bromine monoxide (BrO) or chlorine dioxide (OClO) (Bobrowski
et al., 2007). The relative gas composition varies with the types of
volcanoes and magmas as well as with transport and degassing mechanisms.
Changes in the magma degassing behavior and/or the hydrothermal systems
beneath volcanoes generally influence the gas composition and gas fluxes.
Measuring the emitted gas composition can provide crucial information on
understanding subsurface processes related to activity changes (e.g., Allard
et al., 1991; Aiuppa et al., 2007; Bobrowski and Giuffrida, 2012; de Moor et
al., 2016a; Liotta et al., 2017) and help to estimate fluxes of the
geological carbon cycle (e.g., Burton et al., 2013; Mason et al., 2017) and
tectonic processes controlling volcanic degassing (e.g., Aiuppa et al., 2017;
de Moor et al. 2017). In the field of volcanic monitoring, the observation of
gas composition changes has become an important tool for detecting precursory
processes for volcanic eruptions. For instance, the CO<inline-formula><mml:math id="M25" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M26" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M27" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
emission ratio strongly varies with volcanic activity, which is associated
with
magma rising up a conduit. The solubility of magmatic gases is pressure
dependent and different gases are released from the magma at different depths
during the magma ascent, which is accompanied by a pressure decrease. Gas ratio
changes have been observed within timescales of hours to weeks prior to
eruptions (e.g., Giggenbach, 1975; Aiuppa et al., 2007; de Moor et al., 2016a,
de Moor et al., 2016b) and their magnitude, direction, and pace are highly
variable throughout different volcanic systems and states of activity. In situ
measurements of this gas ratio have become well-established in usage of
electrochemical (SO<inline-formula><mml:math id="M28" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) and infrared (CO<inline-formula><mml:math id="M29" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) sensors, which are implemented in
Multi-GAS (MG) instruments. These instruments may also contain other sensors
and are field deployable, meaning they are autonomous and can work close to volcanic emission
sources (Shinohara, 2005; Aiuppa et al., 2006). Another important parameter
for the characterization of volcanic activity is the gas emission rate.
In particular, the determination of SO<inline-formula><mml:math id="M30" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux has become a standard
procedure. It involves traversing the plume and multiplying the integrated SO<inline-formula><mml:math id="M31" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
cross section with the estimated plume transport speed (e.g., McGonigle et
al., 2002; Galle et al., 2003; López et al., 2013). With the development
of small DOAS instruments, traversing the plume is not only feasible by car,
boats, or manned aircraft, but also by walking, in the case of poorly accessible
terrain. Furthermore, knowledge about in-plume chemical reactions can be
drawn from compositional assessment of the gases, which also helps to
understand their impact on atmospheric chemistry (e.g., Lee et al., 2005;
von Glasow et al., 2009; von Glasow, 2010; Gliß et al., 2015).
The halogen chemistry is of especially great interest as BrO <inline-formula><mml:math id="M32" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M33" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios in
volcanic plumes are readily measurable by remote sensing UV spectrometry
(e.g., Bobrowski et al., 2003; Lübcke et al., 2014) and have been
discussed in recent years as another potential precursory observable parameter for
volcanic activity changes. Although several studies observed decreases in the
BrO <inline-formula><mml:math id="M34" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M35" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio before eruptive phases (e.g., Lübcke et
al., 2014) and lower ratios during periods of continuous activity (Bobrowski
and Giuffrida, 2012), it is not yet clear whether magma–gas partitioning of
bromine occurs before or after sulfur during the pressure drop associated with
magma ascents (Dinger et al., 2018). Furthermore, BrO is not a directly
emitted species; rather it is the product of complex heterogeneous chemistry in
the volcanic plume involving reactions with magmatic gases with entrained air
(e.g., Gerlach, 2004; Bobrowski et al., 2007). Differential optical absorption
spectroscopy (DOAS) measurements revealed a variation in BrO concentration
with plume age and transversal position inside the plume (Bobrowski et al.,
2007). Additionally, other reactive halogen species with oxidation states
<inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>≠</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> (e.g., Br<inline-formula><mml:math id="M37" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, Cl<inline-formula><mml:math id="M38" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, BrCl and others) have been measured in situ
in the plume of Mt. Etna, Italy (Rüdiger et al., 2017) and
Mt. Nyamuragira (Bobrowski et al., 2017). In the last decade, several model
studies (e.g., Bobrowski et al., 2007; Roberts et al., 2009; von Glasow, 2010;
Roberts et al., 2014; Jourdain et al., 2016) have engaged with the variation in
halogen variability in volcanic plumes with respect to various atmospheric
and magmatic parameters. In the case of bromine, it was modeled that the
initial emitted hydrogen bromide is depleted shortly after emission under
consumption of tropospheric ozone and is transformed to reactive species such
as BrO, HOBr, Br<inline-formula><mml:math id="M39" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, BrCl and BrONO<inline-formula><mml:math id="M40" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>. Due to the challenging task of
accessing volcanic plumes on a timescale of minutes after emission and the
lack of spectroscopic methods for most of these reactive species,
uncertainties about their relative abundances still exist. One approach
to the in situ observation of reactive halogen species is the
application of gas diffusion denuder sampling using a selectively reactive
organic coating (1,3,5-trimethoxybenzene, TMB) to trap and enrich gaseous
species containing a halogen atom with the oxidations state <inline-formula><mml:math id="M41" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>1 or 0 (e.g.,
Br<inline-formula><mml:math id="M42" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> or BrCl), while being insensitive to the particle phase (Rüdiger
et al., 2017).</p>
      <p id="d1e587">In the case of most volcanoes, sampling on the crater rim may be associated
with considerable logistical challenges and hazards for people and
instruments. During phases of high activity crater rims are usually not
accessible at all and, even during quiescent degassing, work at the crater rim
represents a considerable risk. However, the knowledge of plume gas
composition is an important component for activity assessments of volcanoes
(e.g., Carroll and Holloway, 1994; Aiuppa et al., 2006) and therefore gas
monitoring stations are deployed and maintained in close proximity to<?pagebreak page2443?> active
volcanic vents by researchers, putting themselves at risks. Advancements in
the application of remote sensing techniques have helped to minimize
personnel exposition to the volcanic danger zone (e.g., Galle et al., 2003;
Tamburello et al., 2011). However, still today the detection of certain gas
species and/or total amounts of all species of an element is not possible
remotely (neither ground based nor with satellites) and therefore in situ
measurements are an important tool, especially for resolving chemical
reactions and speciation changes in aging volcanic plumes. With an in situ
sampling strategy, obtaining samples from the freshly emitted plume is
feasible, while ground-based in situ sampling of the aged plume further
downwind is rarely possible and is dependent on specific wind and geographical
conditions. In the last decade, with the development of compact and cost
effective unmanned aerial vehicles (UAV), several deployments of gas sensors
and other in situ methods, e.g., particle detection (Altstädter et al.,
2015), as well as applications of spectrometers were realized (e.g., McGonigle
et al., 2008; Diaz et al., 2015; Mori et al., 2016; Villa et al., 2016 and
references therein). Pioneering UAV deployments were already conducted in the
late 1970s (Faivre-Pierret et al., 1980). While these drone-based applications
focused mostly on the use of sensors and spectroscopy methods, here we present
a low-cost UAV-deployable sampling (gas diffusion denuder) and sensing
(electrochemical/optical sensors) systems for the determination of CO<inline-formula><mml:math id="M43" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>,
SO<inline-formula><mml:math id="M44" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and halogen species. Our system enabled us to access the plume close
to an active vent as well as the aged plume several kilometers downwind of
the source and elevated from ground, without exposing operators to the risks
in proximity to active vents or employing manned aircrafts to potential
engine-damaging ash and gas plumes. In addition to that, the UAV deployment
of a lightweight DOAS instrument for SO<inline-formula><mml:math id="M45" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux estimations is presented
herein, which enables fast plume traversing in terrain that is usually not
accessible by car or even by foot.</p>
</sec>
<sec id="Ch1.S2">
  <title>Site description</title>
<sec id="Ch1.S2.SS1">
  <title>Stromboli</title>
      <p id="d1e628">Stromboli volcano, the northernmost island of the Aeolian volcanic
arc (Italy), rises 924 m above sea level (a.s.l.). The island represents the
top part of a large 2500 m high stratovolcano emerging from the Tyrrhenian
Sea floor. Stromboli is well known for its regular (<inline-formula><mml:math id="M46" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> every
10–20 min) explosive activity (Strombolian activity). Intermittently,
continuous passive degassing occurs from the active vents, which are located
in the crater terrace at about 750 m a.s.l. Ejected lava
material is dominantly deposited in a northwestern direction, forming a
horseshoe-shaped area (Sciara del Fuoco) that is not safely accessible on
foot. The summit above the craters is easily accessible, and numerous
monitoring stations have been installed here for continuous observation of
the ongoing volcanic activity. Thus, Stromboli has been a laboratory volcano
for studying magma degassing processes (Allard et al., 2008) and
field testing new instrumentations for many years.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><label>Figure 1</label><caption><p id="d1e640">Overview of the sampling site at Stromboli volcano with the
locations of the retrieved CO<inline-formula><mml:math id="M47" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M48" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M49" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios given in
Table 2.</p></caption>
          <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f01.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><label>Figure 2</label><caption><p id="d1e676">Overview of the fieldwork sites at <bold>(a–c)</bold> Masaya volcano
(Nicaragua) and <bold>(d)</bold> Turrialba volcano (Costa Rica). Sampling
locations mentioned in Table 3 are marked in <bold>(c)</bold> as follows:
Santiago rim, lookout south (black marker); Santiago rim, pole site (blue
marker); Nindiri rim (red marker).</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f02.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><label>Figure 3</label><caption><p id="d1e697"><bold>(a)</bold> Sampling site at Stromboli volcano with the
northeastern crater in the background and the RAVEN UAV carrying the
Sunkist gas monitor, <bold>(b)</bold> RAVEN UAV with the black box sampling
unit and three gas diffusion denuders, <bold>(c)</bold> interior view of the
Sunkist gas monitor, showing the CO<inline-formula><mml:math id="M50" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and SO<inline-formula><mml:math id="M51" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensors,
<bold>(d)</bold> passive degassing (white plume) and eruptive ash explosion
(brown ash cloud) at the northeastern crater at Stromboli volcano,
<bold>(e)</bold> ash eruption at the northeastern crater producing an ascending
ash plume with the RAVEN UAV in direct proximity (yellow circle), returning
from sampling flight.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f03.jpg"/>

        </fig>

      <p id="d1e739">While most gas-monitoring station positions benefit from a northwesterly
wind direction, a southeasterly wind only allows gas plume detection by
spectroscopic methods. In this study, due to the dominance of southeasterly winds
in early April 2016 an approach from an easterly direction was chosen, using a
multicopter as a carrier for gas sampling and sensing instruments. The UAV was
mostly launched at the northern shelter (see Fig. 1).</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Masaya</title>
      <p id="d1e748">Masaya volcano (elevation <inline-formula><mml:math id="M52" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 600 m a.s.l.), Nicaragua, is a
basaltic andesite shield volcano caldera (6 <inline-formula><mml:math id="M53" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 11 km in size)
with a set of vents. The currently active vent is situated in the Santiago
pit crater, formed in 1858–1859 (McBirney, 1956). Masaya persistently emits
voluminous quantities of SO<inline-formula><mml:math id="M54" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, with fluxes typically ranging from 500 to
2500 T d<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> (Mather et al., 2006; de Moor et al., 2013; Carn et
al., 2017), currently making this volcano one of the largest contributors
of volcanic gas emissions in the Central American Volcanic Arc (de Moor et
al., 2017). The reappearance of a superficial lava lake
(<inline-formula><mml:math id="M56" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 40 <inline-formula><mml:math id="M57" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 40 m) at Masaya in January 2016 marked an increase in
degassing activity. Due to high emission rates and the low-altitude plume,
Masaya volcano has a detrimental environmental impact on the downwind areas,
diminishing vegetation and potentially affecting human health (Delmelle et
al., 2002). Continuous monitoring of the gas emissions is realized by a
stationary MG system (through the Deep Carbon Observatory – Deep
Earth Carbon Degassing initiative, DCO-DECADE) at the crater rim and two
scanning DOAS instruments (Network for Observation of Volcanic and
Atmospheric Change (NOVAC); Galle et al., 2010) in the downwind direction.
Besides the presence of a strong plume, Masaya volcano provides perfect
conditions for field testing new methods and studying plume chemistry using
UAVs: it is easily accessible by car, at a low altitude, and has a relatively stable dominant
wind direction (northeast). In July 2016 flights were launched from the
caldera bottom, marked “flight area” in Fig. 2c.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <title>Turrialba</title>
      <p id="d1e807">Turrialba is a stratovolcano with a peak elevation of 3340 m a.s.l. and is
located about 35 km east and directly upwind of San José, the capital of
Costa Rica. It is the southernmost active volcano of the Central American
Volcanic Arc. In the 2000s, an almost 150-year-long period of quiescence
ended and since 2010 several vent opening phreatic eruptions have
occurred, marking an ongoing but erratic phase of unrest (Martini et al.,
2010) characterized by variable ash and gas emission intensities (up to
5000 tons day<inline-formula><mml:math id="M58" 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 SO<inline-formula><mml:math id="M59" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>; de Moor et al., 2016a). This made Turrialba
volcano the second most substantial emitter in the arc, besides Masaya volcano
(de Moor et al. 2017). The proximity of Turrialba volcano to the densely
populated central valley, which has Costa Rica's major international airport, and
the dominant western wind direction is responsible for ash depositions,
causing health and air traffic problems. Therefore, the activity of Turrialba
is continuously monitored by various systems including permanent Multi-GAS
stations to observe short-term precursory changes in the gas composition
prior to eruptive events (de Moor et al., 2016a). However, stations located
near the active vent suffer from ash deposition and ballistic impacts during
more frequent episodes, making maintenance demanding and risky or impossible.
Furthermore, the accessibility of the summit and surrounding areas is
decreasing due to intense erosion following vegetation destruction by acid
rain, heavy rainfall, ash deposition and remobilization, and the lack of
infrastructural maintenance following community evacuation. Thus, the use of
UAV-based systems might represent the only viable approach for in situ
measurements of the open-vent plume during periods of high activity. In 2016
flights<?pagebreak page2445?> were conducted starting at the La Silvia site (Fig. 2d) to
investigate the feasibility of a UAV-based gas sensing system in this
challenging environment (high altitude and thick ash plumes).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><label>Figure 4</label><caption><p id="d1e833">Schematics of the <bold>(a)</bold> Sunkist monitoring unit and
the <bold>(b)</bold> black box gas sampling system.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f04.pdf"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Instrumentation</title>
<sec id="Ch1.S3.SS1">
  <title>Unmanned aerial vehicle</title>
      <p id="d1e860">The UAV (called RAVEN, remote-controlled
aircraft for volcanic emission analysis; see Fig. 3a–b) used during
the field campaigns was a four-rotor multicopter with foldable arms (Black
Snapper, Globe Flight, Germany) and an E800 motor set using propellers with a
diameter of 13 inch (0.33 m) and a pitch of 4.5 inch (0.11 m) (DJI
Innovations, Shenzhen, China). It was flown manually in line-of-sight
conditions. The multicopter had a weight of 2.3 kg including a 22.2 V (6S)
4.5 Ah battery. A maximum payload of 1.3 kg was achieved with various
mounted instruments. The foldable frame of the UAV was beneficial with
regards to the usual requirement of personally carrying equipment into the
field, especially on volcanoes like Stromboli. Another advantage of this
system was that the battery capacity is within the guidelines of air travel
restrictions, allowing the system to be transported on commercial airplanes.
The main controller (NAZA M-2, DJI Innovations, Shenzhen, China) of the
multicopter was connected to a combined denuder sampling and SO<inline-formula><mml:math id="M60" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensing
instrument (hereafter named black box; see Sect. 3.3) to transmit the
measured SO<inline-formula><mml:math id="M61" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data as an 0–5 V signal to the remote control, where it
is displayed. This allowed the operator to find areas with dense plumes in
which to hover the system for stationary sampling and to react to changes in
the plume direction. This is challenging if relying only on visual
observation of the plume. A data logger (Core 2, Flytrex Aviation, Tel Aviv,
Israel) with a micro SD card was used to log the flight data from the main
controller consisting of GPS coordinates, pressure and temperature data at
2 Hz. The payloads were attached below the main body of the multicopter with
an inlet for the in situ CO<inline-formula><mml:math id="M62" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and SO<inline-formula><mml:math id="M63" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensing instrument (hereafter
called Sunkist; see Sect. 3.2), close to the center of the copter. The
sampled air volume can be assumed to originate from within a radius of a few
meters around the inlet (see e.g., Roldan et al., 2015; Alvarado et al.,
2017; Palomaki et al., 2017), which represents homogeneous plume gas for a
widely spread out plume. This assumption is confirmed by a self-developed
method for the estimation of the origin of sample air, which is described in
the Supplement (Sect. 4).</p>
</sec>
<sec id="Ch1.S3.SS2">
  <?xmltex \opttitle{CO${}_{{2}}$\,$/$\,SO${}_{{2}}$ gas sensors -- Multi-GAS (Sunkist)}?><title>CO<inline-formula><mml:math id="M64" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M65" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M66" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas sensors – Multi-GAS (Sunkist)</title>
      <p id="d1e931">A gas sensor system was developed for use in volcanic environments with a
focus on robustness and has a compact and lightweight design for application on
UAVs. The system, called Sunkist (SK), contains two gas sensors:
<list list-type="order"><list-item>
      <p id="d1e936">A
CO<inline-formula><mml:math id="M67" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (K30 FR, SenseAir, Delsbo, Sweden) uses the principle
of nondispersive infrared absorption<?pagebreak page2446?> spectroscopy: the sample gas gets
sucked into a multi-reflection cell, where it is exposed to the radiation of
a small infrared light source. The CO<inline-formula><mml:math id="M68" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration is determined by
measuring the light attenuation on distinct CO<inline-formula><mml:math id="M69" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> absorption bands in the
near infrared.</p></list-item><list-item>
      <p id="d1e967">An electrochemical SO<inline-formula><mml:math id="M70" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (CiTiceL 3MST/F,
City Technology, Portsmouth, United Kingdom) basically consists of an
electrochemical cell, where oxidation of SO<inline-formula><mml:math id="M71" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> on one of the cell's
electrodes creates charges and leads to a measurable compensating current
between the two cell electrodes.</p></list-item></list>
The CO<inline-formula><mml:math id="M72" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor is placed inside a hermetic box, which is part of the air
path (Fig. 4a). It is equipped with further on-chip sensors for humidity
(SHT21 from Sensirion, Staefa, Switzerland), temperature and pressure (BMP180
by Bosch Sensortec, Reutlingen, Germany), which allow the gas data to be
corrected for dependencies on named environmental parameters.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><label>Table 1</label><caption><p id="d1e1001">Components and specifications of the sampling and sensing
instruments.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="5">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="left"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Component/parameter</oasis:entry>
         <oasis:entry rowsep="1" namest="col2" nameend="col5" align="center">Specifications </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry namest="col2" nameend="col3">Sunkist </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">Black box  </oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">CO<inline-formula><mml:math id="M75" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">NDIR, SenseAir CO<inline-formula><mml:math id="M76" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> Engine K30 FR  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SO<inline-formula><mml:math id="M77" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">Electrochemical, CiTiceL 3MST/F  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">Electrochemical, CiTiceL 3MST/F  </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Operating temperature</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">0–50 <inline-formula><mml:math id="M78" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (CO<inline-formula><mml:math id="M79" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), <inline-formula><mml:math id="M80" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>2–50 <inline-formula><mml:math id="M81" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (SO<inline-formula><mml:math id="M82" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) </oasis:entry>
         <oasis:entry namest="col4" nameend="col5"><inline-formula><mml:math id="M83" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>20–50 <inline-formula><mml:math id="M84" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Operating humidity</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">0–95 % (CO<inline-formula><mml:math id="M85" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), 15–90 % (SO<inline-formula><mml:math id="M86" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), noncondensing  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">15–90 % (SO<inline-formula><mml:math id="M87" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), noncondensing  </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Operating pressure</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">Atmospheric <inline-formula><mml:math id="M88" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 10% (SO<inline-formula><mml:math id="M89" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">Atmospheric <inline-formula><mml:math id="M90" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 10% </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Temperature dependence</oasis:entry>
         <oasis:entry namest="col2" nameend="col3"><inline-formula><mml:math id="M91" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mi>T</mml:mi></mml:mrow></mml:math></inline-formula> (assumed for CO<inline-formula><mml:math id="M92" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), 0.25 % <inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C<inline-formula><mml:math id="M94" 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> (SO<inline-formula><mml:math id="M95" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">0.25 %/<inline-formula><mml:math id="M96" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> C </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Pressure dependence</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">1.6 %/kPa (CO<inline-formula><mml:math id="M97" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), 0.0015 %/kPa (SO<inline-formula><mml:math id="M98" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry namest="col4" nameend="col5">0.0015 % kPa<inline-formula><mml:math id="M100" 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="M101" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Response time</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">2 s (CO<inline-formula><mml:math id="M102" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), &lt; 20 s (SO<inline-formula><mml:math id="M103" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">&lt; 20 s </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Accuracy</oasis:entry>
         <oasis:entry namest="col2" nameend="col3"><inline-formula><mml:math id="M104" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>30 ppm <inline-formula><mml:math id="M105" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5 % signal (CO<inline-formula><mml:math id="M106" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>),  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5"><inline-formula><mml:math id="M107" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>1 ppm <inline-formula><mml:math id="M108" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1 % signal </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry namest="col2" nameend="col3"><inline-formula><mml:math id="M109" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>1 ppm <inline-formula><mml:math id="M110" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1 % signal (SO<inline-formula><mml:math id="M111" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) </oasis:entry>
         <oasis:entry namest="col4" nameend="col5"/>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Instrument noise (1<inline-formula><mml:math id="M112" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">5 ppm (CO<inline-formula><mml:math id="M113" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), 0.05 ppm (SO<inline-formula><mml:math id="M114" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">0.05 ppm </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Range</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">0–5000 ppm (CO<inline-formula><mml:math id="M115" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), 0–200 ppm (SO<inline-formula><mml:math id="M116" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">0–100 ppm </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Sampling rate</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">2 Hz  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">2 Hz  </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Computer</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">Arduino, with micro SD card logger </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">Arduino, with SD card data logger and p </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry namest="col2" nameend="col3"/>
         <oasis:entry namest="col4" nameend="col5">motor-shield to power the pum </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Voltage</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">9 V for SO<inline-formula><mml:math id="M117" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (alkaline battery),   </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">9 V for SO<inline-formula><mml:math id="M118" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (alkaline battery), </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry namest="col2" nameend="col3">3.7 V LiPo battery for Arduino </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">11.1 V LiPo battery for Arduino and pump </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Inlet</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">Particle filter </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">3 denuders (50 cm) or 3 <inline-formula><mml:math id="M119" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 2 denuders (15 cm) </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Others</oasis:entry>
         <oasis:entry colname="col2">Warm up</oasis:entry>
         <oasis:entry colname="col3">1 min</oasis:entry>
         <oasis:entry colname="col4">Micro solenoid</oasis:entry>
         <oasis:entry colname="col5">First Sensor, Germany</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" colname="col2">time</oasis:entry>
         <oasis:entry rowsep="1" colname="col3">(CO<inline-formula><mml:math id="M120" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry rowsep="1" colname="col4">valves</oasis:entry>
         <oasis:entry rowsep="1" colname="col5">TN2P006LM05LB</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Additional</oasis:entry>
         <oasis:entry colname="col3">Temperature, pressure,</oasis:entry>
         <oasis:entry colname="col4">Mass flow</oasis:entry>
         <oasis:entry colname="col5">First Sensor, Germany,</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">sensors</oasis:entry>
         <oasis:entry colname="col3">relative humidity</oasis:entry>
         <oasis:entry rowsep="1" colname="col4">meter</oasis:entry>
         <oasis:entry rowsep="1" colname="col5">WBAL001DUH0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">Micro</oasis:entry>
         <oasis:entry colname="col5">TCS micropumps,</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">pump</oasis:entry>
         <oasis:entry colname="col5">UK, DS250BL</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Weight</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">500 g </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">500 g </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">dimensions</oasis:entry>
         <oasis:entry namest="col2" nameend="col3">14 <inline-formula><mml:math id="M121" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 13 <inline-formula><mml:math id="M122" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 14 cm (L <inline-formula><mml:math id="M123" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> W <inline-formula><mml:math id="M124" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> H)  </oasis:entry>
         <oasis:entry namest="col4" nameend="col5">20 <inline-formula><mml:math id="M125" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 13 <inline-formula><mml:math id="M126" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 14 cm (L <inline-formula><mml:math id="M127" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> W <inline-formula><mml:math id="M128" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> H)  </oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p id="d1e1004"><inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula> The pressure dependence of 0.0015 % kPa<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>
is a second-order effect and is negligible for our application.</p></table-wrap-foot></table-wrap>

      <p id="d1e1853">The sensors are read out by a custom-built Arduino Uno Rev 3 computer with a
micro SD card logger at a sampling rate of 2 Hz and powered by a
rechargeable 3.7 V lithium polymer (LiPo) battery (Fig. 4b). The SO<inline-formula><mml:math id="M129" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
sensor was powered by a separate 9 V alkaline battery. The whole system is
sheltered in a polystyrene foam case and has a total weight of 500 g
(Fig. 3c). A 45 <inline-formula><mml:math id="M130" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m pore size PTFE filter was attached to the inlet
to prevent particles from entering the sensors. Gas was pumped through to the
sensors in series (1. SO<inline-formula><mml:math id="M131" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, 2. CO<inline-formula><mml:math id="M132" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) by a small pump using a flow
rate of 500 mL min<inline-formula><mml:math id="M133" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The system was calibrated before and after field
deployments with CO<inline-formula><mml:math id="M134" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (0–1500 ppm) and SO<inline-formula><mml:math id="M135" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (0–30 ppm) test
gases. Detailed information on the specifications of the sensors is shown in
Table 1 and in the Supplement (Fig. S1).</p>
</sec>
<sec id="Ch1.S3.SS3">
  <title>Gas diffusion denuder sampler (black box)</title>
      <p id="d1e1928">An in situ gas sampling system was constructed to enable gas diffusion
denuder sampling in the plume at various distances from the vent using the
UAV. To compensate for dilution, a CiTiceL 3MST/F SO<inline-formula><mml:math id="M136" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (City
Technology, Portsmouth, United Kingdom) was implemented to obtain
halogen/sulfur ratios combining denuder samples and sensor data. The sampler
(called black box – BB) consisted of the following components, which are
introduced in the order the gas passes through:
<list list-type="order"><list-item>
      <p id="d1e1942">inlet system for three
denuders,</p></list-item><list-item>
      <p id="d1e1946">electrochemical SO<inline-formula><mml:math id="M137" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor,</p></list-item><list-item>
      <p id="d1e1959">mass flow sensor,</p></list-item><list-item>
      <p id="d1e1963">micro gas pump (see Fig. 4b and Table 1).</p></list-item></list>
The housing was made of
polystyrene foam to ensure that the weight requirements were met. An Arduino
microcontroller (Uno Rev 3) for signal processing and data logging on a SD
card was built in. Various 11.1 V LiPo batteries (500 and 1000 mAh)
supplied the power, with different capacities depending on the desired
payload and operation time. The Arduino computer transmitted a pulse width
modulated signal between 0 and 5 V, proportional to the detected SO<inline-formula><mml:math id="M138" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
mixing ratio, to the main controller of the multicopter via cable connection,
which then was sent by telemetry to the remote control to allow the operator
to assess plume strength in real time to optimize denuder exposure time. The
SO<inline-formula><mml:math id="M139" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas sensor was calibrated in the laboratory and close to field
conditions with SO<inline-formula><mml:math id="M140" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas standards in N<inline-formula><mml:math id="M141" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (0–54.1 ppm).</p>
      <p id="d1e2004">Gas diffusion denuder sampling, which enriches gaseous compounds while being
insensitive to the particle phase, was applied by using two types of coating
materials as derivatization agents for the gas diffusion sampling. Total
gaseous reactive molecular bromine species, Br<inline-formula><mml:math id="M142" display="inline"><mml:msup><mml:mi/><mml:mi>x</mml:mi></mml:msup></mml:math></inline-formula> (Br<inline-formula><mml:math id="M143" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, BrCl,
(H)OBr), were determined by denuders coated with 15 <inline-formula><mml:math id="M144" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>mol of
1,3,5-trimethoxybenzene (TMB) – which reacts to
1-bromo-2,4,6-trimethoxybenzene – and subsequent gas chromatography-mass
spectrometry (GC-MS) analysis (Rüdiger et al., 2017). Hydrogen
bromide (HBr) was sampled with denuders coated with 7.2 <inline-formula><mml:math id="M145" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>mol of
5,6-epoxy-5,6-dihydro-1,10-phenanthroline<?pagebreak page2447?> (EP) – which is selectively
reactive towards halogen acids through its epoxy function, forming
5-halogeno-6-hyrdroxy-5,6-dihydro-1,10-phenanthroline – and analyzed by
liquid chromatography mass spectrometry (LC-MS). For the UAV-based
application 15 cm long denuders were used at a sampling flow rate of
208 mL min<inline-formula><mml:math id="M146" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> to ensure quantitative sampling. Denuders with both
coating types were sampled at the same flow rate simultaneously with the
recording of Multi-GAS (Sunkist) data.</p>
</sec>
<sec id="Ch1.S3.SS4">
  <title>Drone-operated miniature differential optical absorption spectroscopy
(DROAS)</title>
      <?pagebreak page2448?><p id="d1e2059">A miniature UV spectrometer system (Galle et al., 2003) was employed to
fly mobile DOAS traverse measurements which could conduct estimations of the
SO<inline-formula><mml:math id="M147" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux at Turrialba volcano. This system consisted of an UV
spectrometer (Fig. 8a; USB2000<inline-formula><mml:math id="M148" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>, Ocean Optics, USA), a miniature telescope (Ocean
Optics 74-DA collimating lens, diameter: 5 mm, focal length 10 mm), a GPS
antenna (BU-353-S4, GlobalSat, Taipei, Taiwan) and a miniature on-board
computer (VivoStick TS10, ASUS, Taipei, Taiwan). The system was powered by a
11.1 V LiPo battery (1000 mAh), which was connected via a switching
regulator (CC BEC 10 A, Castle Creations, USA) to give 9 V at 2 A. The
spectrometer and the GPS antenna were connected (and powered) at the computer
via USB ports. The NOVAC mobile DOAS software developed at the Chalmers
University (Sweden) was run on the computer for data acquisition and later
for evaluation. The miniature PC in the spectrometer system was accessed via a
remote desktop connection on a different computer to initialize the data
acquisition by the mobile DOAS” software. Validation of the SO<inline-formula><mml:math id="M149" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
fluxes obtained by DROAS traverses was achieved by comparison with the
SO<inline-formula><mml:math id="M150" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fluxes derived by two NOVAC stationary DOAS instruments (La
Silvia and La Central; see Fig. 2d) located in proximity to the
flight area.</p>
</sec>
<sec id="Ch1.S3.SS5">
  <title>Data processing</title>
<sec id="Ch1.S3.SS5.SSS1">
  <title>Sensor calibration</title>
      <p id="d1e2108">All three in situ gas sensors (two identical SO<inline-formula><mml:math id="M151" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, one CO<inline-formula><mml:math id="M152" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) were
calibrated using test gas standards mixed with nitrogen, using either tedlar
bags, dynamic dilution or readily mixed test gases. The sensors were exposed
to different mixing ratios by pumping the gas mixtures through the system.
Calibration functions were fitted, including errors in mixing ratio and
signal (York et al., 2004) to give sensitivities (slope) and offset
levels (intercept) (Supplement Figs. S2–S4). As the CO<inline-formula><mml:math id="M153" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor responds
to the gas concentration (molecules per volume), CO<inline-formula><mml:math id="M154" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios
(molecules per molecules of air) were obtained by compensating for the
concentration signals with pressure and temperature data recorded by the
built-in sensors, assuming ideal gas behavior. The SO<inline-formula><mml:math id="M155" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor output,
however, relates directly to the mixing ratio due to the diffusivity of the
transport membrane being inversely proportional to the pressure and therefore
canceling out the pressure dependency of the concentration. The two gas
sensors operate with significantly different response times (<inline-formula><mml:math id="M156" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mn mathvariant="normal">90</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> for
CO<inline-formula><mml:math id="M157" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M158" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 2 s, for SO<inline-formula><mml:math id="M159" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M160" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> &lt; 20 s), since the sample
gas enters the SO<inline-formula><mml:math id="M161" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor only by molecular diffusion, whereas in the
CO<inline-formula><mml:math id="M162" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor it is directly driven through the optical cell. In order to
adjust the response times of the two sensors, a slow response signal for the
CO<inline-formula><mml:math id="M163" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor (CO<inline-formula><mml:math id="M164" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">sim</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula>) was simulated. This was achieved
through convolution of the original signal with a typical sensor pulse
response,

                  <disp-formula id="Ch1.Ex1"><mml:math id="M165" display="block"><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:mi>f</mml:mi><mml:mfenced open="(" close=")"><mml:mi>t</mml:mi></mml:mfenced><mml:mo>=</mml:mo><mml:mfenced close="" open="{"><mml:mtable class="array" columnalign="left left"><mml:mtr><mml:mtd><mml:mrow><mml:mn mathvariant="normal">0</mml:mn><mml:mo>,</mml:mo></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>t</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mrow><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mn mathvariant="normal">1</mml:mn><mml:mi mathvariant="italic">τ</mml:mi></mml:mfrac></mml:mstyle><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi>t</mml:mi><mml:mo>/</mml:mo><mml:mi mathvariant="italic">τ</mml:mi></mml:mrow></mml:msup><mml:mo>,</mml:mo></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mi>t</mml:mi><mml:mo>≥</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:mfenced><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>

            with <inline-formula><mml:math id="M166" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> being time and <inline-formula><mml:math id="M167" display="inline"><mml:mi mathvariant="italic">τ</mml:mi></mml:math></inline-formula> being the response-time factor, which in
this context can be regarded as a measure for the degree of smoothing. The
approach is mathematically equivalent to an approach shown by Roberts et
al. (2014). The response-time factor <inline-formula><mml:math id="M168" display="inline"><mml:mi mathvariant="italic">τ</mml:mi></mml:math></inline-formula> was tuned, such that the
correlation of CO<inline-formula><mml:math id="M169" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">sim</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> and SO<inline-formula><mml:math id="M170" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> signal were maximized for
discrete peaks (see Fig. 5a). This was already done by Arellano et
al. (2017), who also applied the Sunkist instrument to gas measurements in
Papua New Guinea in 2016.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><label>Figure 5</label><caption><p id="d1e2355"><bold>(a)</bold> Example of time series for mixing ratios of SO<inline-formula><mml:math id="M171" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
and CO<inline-formula><mml:math id="M172" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (original data in red, resampled data in black), showing
discrete gas masses at Stromboli volcano (first flight on 5 April 2016),
<bold>(b)</bold> Correlation plot for the determination of the relative response-time factor for the CO<inline-formula><mml:math id="M173" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas sensor with a
maximum at a relative response-time factor of 1.7, <bold>(c)</bold> CO<inline-formula><mml:math id="M174" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> over SO<inline-formula><mml:math id="M175" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios,
showing the outcome of the resampling of the fast CO<inline-formula><mml:math id="M176" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> with a relative
response-time factor of 1.7 (lower plot), linear regression results
CO<inline-formula><mml:math id="M177" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M178" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M179" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios of 64 <inline-formula><mml:math id="M180" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 16 the first peak and
42 <inline-formula><mml:math id="M181" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4 for the second.</p></caption>
            <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f05.pdf"/>

          </fig>

</sec>
<sec id="Ch1.S3.SS5.SSS2">
  <title>Gas diffusion denuder analysis</title>
      <p id="d1e2473">The sampled gas diffusion denuders were sealed in air-tight containers and stored in
darkness for subsequent analysis. The coating, which contained the derivate
and derivatization agent in excess (TMB or EP), was eluted off the denuders
using 5 times 2 mL of 1:1 of ethyl acetate and ethanol (in the case of TMB) or 5
times 2 mL methanol (EP). After the elution, the solvent was evaporated (at
35 <inline-formula><mml:math id="M182" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C under gentle N<inline-formula><mml:math id="M183" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas stream) to a volume of approximately
100 <inline-formula><mml:math id="M184" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>L. Internal standards (with TMB: 2,4,6-tribromoaniline; with
EP: neocuproine) were added to each sample solution to account for
evaporation losses. The condensed samples were analyzed by GC-MS (TMB) and
LC-MS (EP) and quantified using external calibration. Due to the lack of a
pure calibration, standard hydrogen bromide was only measured qualitatively.
Halogen mixing ratios in air were derived from the measured halogen amounts
on the denuders and the respective sampling volume obtained by the sampling
pump data. In addition to the actual sample denuders, open-field blank
denuders were prepared to account for potential diffusive gas precipitation
during the flights.</p>
</sec>
<sec id="Ch1.S3.SS5.SSS3">
  <title>Gas ratios</title>
      <p id="d1e2508">For a feasible data interpretation, gas ratios were calculated from the
sensor data and the denuder analysis results. Halogen mixing ratios were
interpreted concerning dilution with ambient air by relating to SO<inline-formula><mml:math id="M185" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>,
which is rather slow in its oxidation, and therefore can be treated as a
stable dilution proxy for a short-term plume observation (Porter et al.,
2002). Thus, the derived halogen mixing ratio was divided by the
time-integrated SO<inline-formula><mml:math id="M186" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios obtained during the denuder sampling
period to obtain Br<inline-formula><mml:math id="M187" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M188" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M189" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios. Due to a baseline drift in
the CO<inline-formula><mml:math id="M190" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor data, which were only observable during long-term
measurements (&gt; 45 min), the pressure- and response-time-corrected CO<inline-formula><mml:math id="M191" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data were additionally drift corrected for long-term
measurements. A linear fit was made to the sloped background signal
and subtracted from the CO<inline-formula><mml:math id="M192" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> signal (see Supplement Fig. S5).
CO<inline-formula><mml:math id="M193" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M194" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M195" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios were calculated with a linear fit to CO<inline-formula><mml:math id="M196" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
vs. SO<inline-formula><mml:math id="M197" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> scatter plots, considering the deviations (York et al., 2004) of
the two sensor signals.</p>
</sec>
<sec id="Ch1.S3.SS5.SSS4">
  <title>DROAS evaluation and gas fluxes</title>
      <?pagebreak page2449?><p id="d1e2632">SO<inline-formula><mml:math id="M198" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> emission rates during the flights at Turrialba were derived by
traversing the plume with the DROAS instrument pointing vertically upwards in
the direction of the plume. The mobile DOAS software developed at
Chalmers University was used to control the spectrometer and to retrieve
SO<inline-formula><mml:math id="M199" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts from the spectra. The SO<inline-formula><mml:math id="M200" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> columns were achieved
using a wavelength evaluation window of 310–330 nm and included O<inline-formula><mml:math id="M201" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
and SO<inline-formula><mml:math id="M202" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> absorption cross sections convoluted with a slit function as
well as a ring spectrum and a third-order polynomial in the DOAS fitting
routine. The calculation of the SO<inline-formula><mml:math id="M203" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> emission rate involves the
integration of the SO<inline-formula><mml:math id="M204" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts measured along the flight path,
resulting in a cross-sectional SO<inline-formula><mml:math id="M205" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> area, which was geometrically
corrected to obtain a surface that is orthogonal to the plume direction, and
then multiplied by the wind speed (obtained from the NOAA National Center for
Environmental Predictions (NCEP) Global Forecast System) to calculate
SO<inline-formula><mml:math id="M206" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fluxes. Further details on the spectral evaluation routines and flux
calculations can be found elsewhere (de Moor et al., 2017).</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S4">
  <title>Results and discussion</title>
<sec id="Ch1.S4.SS1">
  <title>Multicopter performance assessment</title>
      <p id="d1e2731">During the deployment at three volcanoes, the RAVEN multicopter conducted
more than 50 flights under moderate wind conditions, in most cases below 10
m 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>. The multicopter achieved a maximum operation altitude of 3320 m
at Turrialba volcano and records showed a maximum speed of 85 km h<inline-formula><mml:math id="M208" 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 a takeoff weight of 2.45 kg and a payload of maximum 1.3 kg flights at
Turrialba volcano were still possible, although the flight time was reduced
to about 5 to 8 min. At the Masaya volcano sites (takeoff altitude
<inline-formula><mml:math id="M209" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 500 m), a maximum ascent above ground level of 1080 m was recorded.
A typical flight time at this site was between 10 and 15 min. The
telemetrically transmitted SO<inline-formula><mml:math id="M210" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios from the black box
apparatus allowed the localization of high plume densities and therefore
adjustments on the optimal hover location. While flying in the line of sight
the system could be reliably controlled within a distance of 1–2 km to the
operator. However, entering the dense plume proved to challenge the
connection between the remote control and the receiver, resulting in multiple
connection losses during flights, in which the UAV also left the line of
sight of the operator. Nevertheless, a GPS connection was still present and
an automated return mechanism allowed control to be regained after the UAV
left areas of high plume densities. At Masaya this phenomenon was observed
mostly in a plume with condensed water and SO<inline-formula><mml:math id="M211" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios in low
one-digit ppmv numbers, while in a plume without condensation close to the
crater, control was maintained even with SO<inline-formula><mml:math id="M212" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> levels up to 40 ppmv. This
is probably due to the attenuation effect of fog and cloud droplets on
millimeter waves, as they are used with the 2.4 Ghz transmitter of the
remote control (Zhao and Wu, 2000).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><label>Table 2</label><caption><p id="d1e2796">Overview of the retrieved CO<inline-formula><mml:math id="M213" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M214" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M215" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios with parameters for the
linear fit at Stromboli volcano.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="8">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Date</oasis:entry>
         <oasis:entry colname="col2">Time</oasis:entry>
         <oasis:entry colname="col3">Flight/</oasis:entry>
         <oasis:entry colname="col4">CO<inline-formula><mml:math id="M216" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">Lower SO<inline-formula><mml:math id="M217" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">Data</oasis:entry>
         <oasis:entry colname="col7">Max. SO<inline-formula><mml:math id="M218" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>/</oasis:entry>
         <oasis:entry colname="col8">Estimated</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">peak</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M219" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M220" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">limit/ppmv</oasis:entry>
         <oasis:entry colname="col6">points</oasis:entry>
         <oasis:entry colname="col7">ppmv</oasis:entry>
         <oasis:entry colname="col8">distance/m</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">13:46</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M221" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">64 <inline-formula><mml:math id="M222" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 16</oasis:entry>
         <oasis:entry colname="col5">1</oasis:entry>
         <oasis:entry colname="col6">39</oasis:entry>
         <oasis:entry colname="col7">2.6</oasis:entry>
         <oasis:entry colname="col8">26</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">13:46</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M223" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">42 <inline-formula><mml:math id="M224" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4</oasis:entry>
         <oasis:entry colname="col5">1</oasis:entry>
         <oasis:entry colname="col6">48</oasis:entry>
         <oasis:entry colname="col7">8.5</oasis:entry>
         <oasis:entry colname="col8">11</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">14:31</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M225" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">43 <inline-formula><mml:math id="M226" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8</oasis:entry>
         <oasis:entry colname="col5">1</oasis:entry>
         <oasis:entry colname="col6">31</oasis:entry>
         <oasis:entry colname="col7">4.5</oasis:entry>
         <oasis:entry colname="col8">18</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">14:32</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M227" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">31 <inline-formula><mml:math id="M228" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 12</oasis:entry>
         <oasis:entry colname="col5">1</oasis:entry>
         <oasis:entry colname="col6">29</oasis:entry>
         <oasis:entry colname="col7">4.7</oasis:entry>
         <oasis:entry colname="col8">25</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">16:18</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M229" display="inline"><mml:mrow><mml:mn mathvariant="normal">3</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">7 <inline-formula><mml:math id="M230" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5</oasis:entry>
         <oasis:entry colname="col5">0.1</oasis:entry>
         <oasis:entry colname="col6">101</oasis:entry>
         <oasis:entry colname="col7">5.8</oasis:entry>
         <oasis:entry colname="col8">419</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">05.04</oasis:entry>
         <oasis:entry colname="col2">16:23</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M231" display="inline"><mml:mrow><mml:mn mathvariant="normal">3</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">11 <inline-formula><mml:math id="M232" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 11</oasis:entry>
         <oasis:entry colname="col5">0.1</oasis:entry>
         <oasis:entry colname="col6">133</oasis:entry>
         <oasis:entry colname="col7">1.9</oasis:entry>
         <oasis:entry colname="col8">399</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">13:03</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M233" display="inline"><mml:mrow><mml:mn mathvariant="normal">4</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">27 <inline-formula><mml:math id="M234" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 25</oasis:entry>
         <oasis:entry colname="col5">0.2</oasis:entry>
         <oasis:entry colname="col6">326</oasis:entry>
         <oasis:entry colname="col7">0.9</oasis:entry>
         <oasis:entry colname="col8">155</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">13:44</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M235" display="inline"><mml:mrow><mml:mn mathvariant="normal">5</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">22 <inline-formula><mml:math id="M236" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5</oasis:entry>
         <oasis:entry colname="col5">0.5</oasis:entry>
         <oasis:entry colname="col6">324</oasis:entry>
         <oasis:entry colname="col7">5.2</oasis:entry>
         <oasis:entry colname="col8">80</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">14:44</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M237" display="inline"><mml:mrow><mml:mn mathvariant="normal">6</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">10 <inline-formula><mml:math id="M238" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 13</oasis:entry>
         <oasis:entry colname="col5">0.2</oasis:entry>
         <oasis:entry colname="col6">111</oasis:entry>
         <oasis:entry colname="col7">1.6</oasis:entry>
         <oasis:entry colname="col8">170</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">14:45</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M239" display="inline"><mml:mrow><mml:mn mathvariant="normal">6</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">21 <inline-formula><mml:math id="M240" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7</oasis:entry>
         <oasis:entry colname="col5">0.5</oasis:entry>
         <oasis:entry colname="col6">415</oasis:entry>
         <oasis:entry colname="col7">2.3</oasis:entry>
         <oasis:entry colname="col8">177</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">15:10</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M241" display="inline"><mml:mrow><mml:mn mathvariant="normal">7</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">9 <inline-formula><mml:math id="M242" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5</oasis:entry>
         <oasis:entry colname="col5">0.2</oasis:entry>
         <oasis:entry colname="col6">516</oasis:entry>
         <oasis:entry colname="col7">1.6</oasis:entry>
         <oasis:entry colname="col8">167</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">06.04</oasis:entry>
         <oasis:entry colname="col2">15:16</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M243" display="inline"><mml:mrow><mml:mn mathvariant="normal">7</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">21 <inline-formula><mml:math id="M244" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5</oasis:entry>
         <oasis:entry colname="col5">0.5</oasis:entry>
         <oasis:entry colname="col6">35</oasis:entry>
         <oasis:entry colname="col7">2.3</oasis:entry>
         <oasis:entry colname="col8">107</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3" specific-use="star"><label>Table 3</label><caption><p id="d1e3490">CO<inline-formula><mml:math id="M245" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M246" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M247" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios and calculation parameters
obtained from the Sunkist (SK) and Multi-GAS (MG) instruments at Masaya
volcano. The exact locations are given in Fig. 2; errors indicate <inline-formula><mml:math id="M248" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>
interval (95.5 %) retrieved by a linear regression (York et al., 2004)
including the measurement errors of both the SO<inline-formula><mml:math id="M249" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (error: 5–10 %) and
CO<inline-formula><mml:math id="M250" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (error: 5.5 %) sensor.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Date</oasis:entry>
         <oasis:entry colname="col2">Time</oasis:entry>
         <oasis:entry colname="col3">Instrument</oasis:entry>
         <oasis:entry colname="col4">Location/flight</oasis:entry>
         <oasis:entry colname="col5">CO<inline-formula><mml:math id="M251" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M252" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M253" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">Lower SO<inline-formula><mml:math id="M254" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col7">Data</oasis:entry>
         <oasis:entry colname="col8">Max.</oasis:entry>
         <oasis:entry colname="col9">Distance to</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6">limit/ppmv</oasis:entry>
         <oasis:entry colname="col7">points</oasis:entry>
         <oasis:entry colname="col8">SO<inline-formula><mml:math id="M255" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col9">rim/km</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">14.07.2016</oasis:entry>
         <oasis:entry colname="col2">09:43–15:10</oasis:entry>
         <oasis:entry colname="col3">MG</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; lookout south</oasis:entry>
         <oasis:entry colname="col5">2.9 <inline-formula><mml:math id="M256" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">3200</oasis:entry>
         <oasis:entry colname="col8">31.1</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">14.07.2016</oasis:entry>
         <oasis:entry colname="col2">11:18–11:44</oasis:entry>
         <oasis:entry colname="col3">MG</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; lookout south</oasis:entry>
         <oasis:entry colname="col5">2.9 <inline-formula><mml:math id="M257" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">440</oasis:entry>
         <oasis:entry colname="col8">17.5</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">14.07.2016</oasis:entry>
         <oasis:entry colname="col2">11:19–11:45</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; lookout south</oasis:entry>
         <oasis:entry colname="col5">3.8 <inline-formula><mml:math id="M258" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">1460</oasis:entry>
         <oasis:entry colname="col8">17.9</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">14.07.2016</oasis:entry>
         <oasis:entry colname="col2">10:42– 12:09</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; lookout south</oasis:entry>
         <oasis:entry colname="col5">3.6 <inline-formula><mml:math id="M259" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.4</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">2600</oasis:entry>
         <oasis:entry colname="col8">18.5</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">15.07.2016</oasis:entry>
         <oasis:entry colname="col2">09:43–16:23</oasis:entry>
         <oasis:entry colname="col3">MG</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; pole site</oasis:entry>
         <oasis:entry colname="col5">3.1 <inline-formula><mml:math id="M260" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">2950</oasis:entry>
         <oasis:entry colname="col8">29.6</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">15.07.2016</oasis:entry>
         <oasis:entry colname="col2">15:28–16:19</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">Nindiri rim</oasis:entry>
         <oasis:entry colname="col5">3.3 <inline-formula><mml:math id="M261" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.2</oasis:entry>
         <oasis:entry colname="col6">1</oasis:entry>
         <oasis:entry colname="col7">3100</oasis:entry>
         <oasis:entry colname="col8">5.8</oasis:entry>
         <oasis:entry colname="col9">0.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">16.07.2016</oasis:entry>
         <oasis:entry colname="col2">11:18–12:19</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; pole site</oasis:entry>
         <oasis:entry colname="col5">4.7 <inline-formula><mml:math id="M262" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">3000</oasis:entry>
         <oasis:entry colname="col8">28</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17.07.2016</oasis:entry>
         <oasis:entry colname="col2">08:56–08:59</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. A2</oasis:entry>
         <oasis:entry colname="col5">2.9 <inline-formula><mml:math id="M263" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 13</oasis:entry>
         <oasis:entry colname="col6">1</oasis:entry>
         <oasis:entry colname="col7">150</oasis:entry>
         <oasis:entry colname="col8">2.8</oasis:entry>
         <oasis:entry colname="col9">1.8</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17.07.2016</oasis:entry>
         <oasis:entry colname="col2">11:21–11:28</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. A5</oasis:entry>
         <oasis:entry colname="col5">4.8 <inline-formula><mml:math id="M264" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.2</oasis:entry>
         <oasis:entry colname="col6">1</oasis:entry>
         <oasis:entry colname="col7">630</oasis:entry>
         <oasis:entry colname="col8">4.8</oasis:entry>
         <oasis:entry colname="col9">1.8</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17.07.2016</oasis:entry>
         <oasis:entry colname="col2">11:53–12:01</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. A6</oasis:entry>
         <oasis:entry colname="col5">6.5 <inline-formula><mml:math id="M265" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.4</oasis:entry>
         <oasis:entry colname="col6">0.2</oasis:entry>
         <oasis:entry colname="col7">620</oasis:entry>
         <oasis:entry colname="col8">3.4</oasis:entry>
         <oasis:entry colname="col9">1.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17.07.2016</oasis:entry>
         <oasis:entry colname="col2">12:10–12:20</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. A7</oasis:entry>
         <oasis:entry colname="col5">6.2 <inline-formula><mml:math id="M266" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.6</oasis:entry>
         <oasis:entry colname="col6">0.4</oasis:entry>
         <oasis:entry colname="col7">1150</oasis:entry>
         <oasis:entry colname="col8">2.2</oasis:entry>
         <oasis:entry colname="col9">1.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">18.07.2016</oasis:entry>
         <oasis:entry colname="col2">07:55–09:36</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">Santiago rim; pole site</oasis:entry>
         <oasis:entry colname="col5">4.1 <inline-formula><mml:math id="M267" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3</oasis:entry>
         <oasis:entry colname="col6">4</oasis:entry>
         <oasis:entry colname="col7">4350</oasis:entry>
         <oasis:entry colname="col8">36.7</oasis:entry>
         <oasis:entry colname="col9">0</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">18.07.2016</oasis:entry>
         <oasis:entry colname="col2">13:19–13:27</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. B4</oasis:entry>
         <oasis:entry colname="col5">5.1 <inline-formula><mml:math id="M268" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4</oasis:entry>
         <oasis:entry colname="col6">1</oasis:entry>
         <oasis:entry colname="col7">560</oasis:entry>
         <oasis:entry colname="col8">4.4</oasis:entry>
         <oasis:entry colname="col9">1.7</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20.07.2016</oasis:entry>
         <oasis:entry colname="col2">12:55–13:04</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. C1</oasis:entry>
         <oasis:entry colname="col5">7.5 <inline-formula><mml:math id="M269" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.8</oasis:entry>
         <oasis:entry colname="col6">0.5</oasis:entry>
         <oasis:entry colname="col7">310</oasis:entry>
         <oasis:entry colname="col8">2.8</oasis:entry>
         <oasis:entry colname="col9">1.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20.07.2016</oasis:entry>
         <oasis:entry colname="col2">13:29–13:35</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. C2</oasis:entry>
         <oasis:entry colname="col5">7.7 <inline-formula><mml:math id="M270" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.1</oasis:entry>
         <oasis:entry colname="col6">0.75</oasis:entry>
         <oasis:entry colname="col7">470</oasis:entry>
         <oasis:entry colname="col8">2.9</oasis:entry>
         <oasis:entry colname="col9">1.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20.07.2016</oasis:entry>
         <oasis:entry colname="col2">13:58–14:07</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. C3</oasis:entry>
         <oasis:entry colname="col5">2.2 <inline-formula><mml:math id="M271" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 11</oasis:entry>
         <oasis:entry colname="col6">0.5</oasis:entry>
         <oasis:entry colname="col7">380</oasis:entry>
         <oasis:entry colname="col8">1.9</oasis:entry>
         <oasis:entry colname="col9">1.9</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20.07.2016</oasis:entry>
         <oasis:entry colname="col2">16:22–16:29</oasis:entry>
         <oasis:entry colname="col3">SK</oasis:entry>
         <oasis:entry colname="col4">caldera valley; flight no. C7</oasis:entry>
         <oasis:entry colname="col5">5.3 <inline-formula><mml:math id="M272" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.4</oasis:entry>
         <oasis:entry colname="col6">0.5</oasis:entry>
         <oasis:entry colname="col7">550</oasis:entry>
         <oasis:entry colname="col8">3.4</oasis:entry>
         <oasis:entry colname="col9">2</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><label>Figure 6</label><caption><p id="d1e4326">Comparison of SO<inline-formula><mml:math id="M273" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and CO<inline-formula><mml:math id="M274" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> time series of a Multi-GAS (MG)
instrument and the Sunkist (SK) unit at the Masaya volcano crater
rim (for SK CO<inline-formula><mml:math id="M275" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> raw data in grey, resampled data in black), both
instrument inlets were placed in proximity to each other (14 July 2016);
SK CO<inline-formula><mml:math id="M276" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M277" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M278" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M279" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 3.63 <inline-formula><mml:math id="M280" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.43 (background
CO<inline-formula><mml:math id="M281" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M282" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 439 ppm); MG CO<inline-formula><mml:math id="M283" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M284" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M285" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M286" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 2.94 <inline-formula><mml:math id="M287" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.30
(background CO<inline-formula><mml:math id="M288" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M289" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 413 ppm); additional scatter plots in the
Supplement.</p></caption>
          <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f06.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS2">
  <?xmltex \opttitle{CO${}_{{2}}$\,$/$\,SO${}_{{2}}$ gas sensors}?><title>CO<inline-formula><mml:math id="M290" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M291" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M292" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas sensors</title>
      <p id="d1e4506">During two field deployments, at the Stromboli (Table 2) and Masaya (Table 3)
volcanoes, the lightweight gas-monitoring system SK determined
CO<inline-formula><mml:math id="M293" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M294" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M295" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas ratios at various airborne and ground-based
locations. A comparison with a stationary MG instrument at Masaya
volcano for the same site and time (lookout point south, 14 July 2016,
<inline-formula><mml:math id="M296" display="inline"><mml:mrow><mml:mn mathvariant="normal">11</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">19</mml:mn></mml:mrow></mml:math></inline-formula>) and with<?pagebreak page2450?> inlets of both systems in proximity to each other gave
results on CO<inline-formula><mml:math id="M297" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M298" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M299" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios that were within each other's
<inline-formula><mml:math id="M300" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula> intervals (CO<inline-formula><mml:math id="M301" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M302" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M303" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> of 2.9 <inline-formula><mml:math id="M304" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3 for MG and
3.6 <inline-formula><mml:math id="M305" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.4 for SK). The time series of the SO<inline-formula><mml:math id="M306" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios of SK
and MG also showed good agreement (<inline-formula><mml:math id="M307" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M308" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.89) (Fig. 6). An
application of SK further downwind (0.5 km from the rim) gave a
CO<inline-formula><mml:math id="M309" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M310" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M311" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio of 3.3 <inline-formula><mml:math id="M312" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.2, while the MG measured a
CO<inline-formula><mml:math id="M313" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M314" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M315" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio of 3.1 <inline-formula><mml:math id="M316" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>  0.1 during the same time at the
rim. This shows SK's ability to be deployed in a more diluted plume,
but with the disadvantage of higher errors, due to the higher relative
background in CO<inline-formula><mml:math id="M317" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> at more distant locations. Furthermore, UAV-based
application (nine flights, 17–20 July 2017) between 1.5 km and 2 km downwind
of the Masaya plume resulted in 42 % higher
CO<inline-formula><mml:math id="M318" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M319" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M320" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios on average with a larger standard deviation compared to
the crater rim (14–16 July 2017), but still within each other's errors
(CO<inline-formula><mml:math id="M321" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M322" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M323" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>: 5.4 <inline-formula><mml:math id="M324" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.3 at 1.5–2 km; 3.8 <inline-formula><mml:math id="M325" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3 at
the rim). Due to the limitations of the CO<inline-formula><mml:math id="M326" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensing, acquiring
useful CO<inline-formula><mml:math id="M327" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M328" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M329" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data with SK is more feasible in dense plumes
close to the crater rim but not limited to it, as the airborne application has
shown. Additionally, SO<inline-formula><mml:math id="M330" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios were measured as a plume dilution
proxy by the black box (BB) system. Both the BB and SK systems use an
identical SO<inline-formula><mml:math id="M331" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> sensor and showed a good agreement of their SO<inline-formula><mml:math id="M332" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> time
series and time-integrated SO<inline-formula><mml:math id="M333" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratio (SK:
1.75 <inline-formula><mml:math id="M334" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08 ppmv, BB: 1,84 <inline-formula><mml:math id="M335" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.08 ppmv) (Supplement S6).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><label>Figure 7</label><caption><p id="d1e4877"><bold>(a)</bold> Measured CO<inline-formula><mml:math id="M336" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M337" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M338" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas ratios over a
5-day period by a Multi-GAS station (located east of the crater terrace) and
airborne measurements with the Sunkist system at Stromboli volcano.
Data point shapes indicate the lower SO<inline-formula><mml:math id="M339" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratio limits for the
linear fit over the CO<inline-formula><mml:math id="M340" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> vs. SO<inline-formula><mml:math id="M341" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data. <bold>(b)</bold> Development of
the gaseous reactive bromine species over SO<inline-formula><mml:math id="M342" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> over the estimated plume
age (derived from distance to crater and estimated wind speed).
<bold>(c)</bold> Gaseous reactive bromine <inline-formula><mml:math id="M343" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M344" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios vs.
CO<inline-formula><mml:math id="M345" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M346" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M347" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio.</p></caption>
          <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f07.pdf"/>

        </fig>

      <p id="d1e4998">At Stromboli volcano, the Sunkist and black box systems were deployed on 2
days (5 and 6 April 2016), resulting in<?pagebreak page2451?> seven flights into the plume. These
flights covered distances of between 11 and 419 m from the vent in a
downwind direction (northeast), above the Sciara del Fuoco. As shown in
Fig. 1, discrete gas clouds with different CO<inline-formula><mml:math id="M348" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M349" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M350" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
compositions were measured. The retrieved CO<inline-formula><mml:math id="M351" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M352" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M353" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios
ranged between 7 and 64, with the higher values typically detected directly
above the vent (11 to 26 m) (see Table 3 and Fig. 1). During the multicopter
operations close to the vent regular strombolian ash explosions occurred (see
Fig. 3d and e), which are likely accompanied by CO<inline-formula><mml:math id="M354" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>-rich gas clouds (La
Spina et al., 2013) and therefore act as a possible explanation for the
detected high CO<inline-formula><mml:math id="M355" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M356" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M357" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios. On both flight days the
predominant wind direction was southwest (207<inline-formula><mml:math id="M358" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M359" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 15<inline-formula><mml:math id="M360" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
and 210<inline-formula><mml:math id="M361" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M362" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 18<inline-formula><mml:math id="M363" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, data from weather station at
77 m a.s.l., commercially available from <uri>http://www.windfinder.com</uri>, Kiel,
Germany), which resulted in the plume mostly being present across the Sciara del Fuoco
and therefore only accessible by UAV. Nevertheless, a local Multi-GAS station
(placed on the SE rim of the crater terrace) discontinuously measured the
plume during the period of the UAV survey, showing CO<inline-formula><mml:math id="M364" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M365" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M366" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
ratios between 2.2 and 13.6, which is in agreement with some of the
multicopter-based measurements. Similar CO<inline-formula><mml:math id="M367" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M368" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M369" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios have
been observed in the past and are exemplary for ordinary Strombolian
activity (Aiuppa et al., 2009). It has to be taken into account that both instruments
did not measure simultaneously or in proximity to each other. The MG
instrument only measures four times a day for 30 min and averages over
this time, while with the SK instrument we identified discrete peaks of gas
clouds with different CO<inline-formula><mml:math id="M370" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M371" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M372" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios. Furthermore, a
comparison of SK and MG CO<inline-formula><mml:math id="M373" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M374" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M375" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data might be more accurate
with the high SK CO<inline-formula><mml:math id="M376" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M377" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M378" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> values (associated with eruptive
degassing) left aside, as we lack the observations on passive or
eruptive degassing behavior for the MG data records.</p>
</sec>
<sec id="Ch1.S4.SS3">
  <title>Halogen measurements</title>
      <p id="d1e5274">Bromine species were detected by gas diffusion denuder sampling on three of
the seven flights at Stromboli volcano. Reactive bromine species were
measured between 0.14 and 0.65 ppb (see Table 4), while HBr was determined
qualitatively in all three samples.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4"><label>Table 4</label><caption><p id="d1e5280">Sample parameter and bromine measurement results for three denuder
samples at Stromboli volcano.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.9}[.9]?><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Sample number</oasis:entry>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">2</oasis:entry>
         <oasis:entry colname="col4">3</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Date</oasis:entry>
         <oasis:entry colname="col2">05.04.2016</oasis:entry>
         <oasis:entry colname="col3">06.04.2016</oasis:entry>
         <oasis:entry colname="col4">06.04.2016</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Time</oasis:entry>
         <oasis:entry colname="col2">14:31</oasis:entry>
         <oasis:entry colname="col3">13:46</oasis:entry>
         <oasis:entry colname="col4">14:45</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Duration /s</oasis:entry>
         <oasis:entry colname="col2">53</oasis:entry>
         <oasis:entry colname="col3">364</oasis:entry>
         <oasis:entry colname="col4">320</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Sample volume/L</oasis:entry>
         <oasis:entry colname="col2">0.18</oasis:entry>
         <oasis:entry colname="col3">1.26</oasis:entry>
         <oasis:entry colname="col4">1.11</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Pressure/mbar</oasis:entry>
         <oasis:entry colname="col2">906</oasis:entry>
         <oasis:entry colname="col3">914</oasis:entry>
         <oasis:entry colname="col4">914</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Integrated SO<inline-formula><mml:math id="M379" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>/ppmv</oasis:entry>
         <oasis:entry colname="col2">1.85 <inline-formula><mml:math id="M380" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.09</oasis:entry>
         <oasis:entry colname="col3">0.34 <inline-formula><mml:math id="M381" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.04</oasis:entry>
         <oasis:entry colname="col4">0.74 <inline-formula><mml:math id="M382" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.05</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Br<inline-formula><mml:math id="M383" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>/ppb</oasis:entry>
         <oasis:entry colname="col2">0.65 <inline-formula><mml:math id="M384" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.06</oasis:entry>
         <oasis:entry colname="col3">0.34 <inline-formula><mml:math id="M385" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.01</oasis:entry>
         <oasis:entry colname="col4">0.14 <inline-formula><mml:math id="M386" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Br<inline-formula><mml:math id="M387" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M388" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M389" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M390" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M391" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">3.5 <inline-formula><mml:math id="M392" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.4</oasis:entry>
         <oasis:entry colname="col3">9.8 <inline-formula><mml:math id="M393" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.3</oasis:entry>
         <oasis:entry colname="col4">1.9 <inline-formula><mml:math id="M394" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CO<inline-formula><mml:math id="M395" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M396" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M397" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">43 <inline-formula><mml:math id="M398" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 9</oasis:entry>
         <oasis:entry colname="col3">27 <inline-formula><mml:math id="M399" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4</oasis:entry>
         <oasis:entry colname="col4">17 <inline-formula><mml:math id="M400" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Distance/m</oasis:entry>
         <oasis:entry colname="col2">21 <inline-formula><mml:math id="M401" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2</oasis:entry>
         <oasis:entry colname="col3">80 <inline-formula><mml:math id="M402" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2</oasis:entry>
         <oasis:entry colname="col4">177 <inline-formula><mml:math id="M403" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Wind speed/m s<inline-formula><mml:math id="M404" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2">3.4 <inline-formula><mml:math id="M405" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5</oasis:entry>
         <oasis:entry colname="col3">4.8 <inline-formula><mml:math id="M406" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5</oasis:entry>
         <oasis:entry colname="col4">4.8 <inline-formula><mml:math id="M407" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Plume age/s</oasis:entry>
         <oasis:entry colname="col2">6 <inline-formula><mml:math id="M408" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1</oasis:entry>
         <oasis:entry colname="col3">17 <inline-formula><mml:math id="M409" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2</oasis:entry>
         <oasis:entry colname="col4">37 <inline-formula><mml:math id="M410" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T5" specific-use="star"><label>Table 5</label><caption><p id="d1e5746">SO<inline-formula><mml:math id="M411" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fluxes obtained by DROAS traverses and two stationary
scanning DOAS instruments at Turrialba volcano. The average fluxes from La
Silvia and La Central were derived for a 2 h period in which the DROAS
flights were conducted, maximum fluxes for this period as presented as well.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="5">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Instrument/traverse</oasis:entry>
         <oasis:entry colname="col2">SO<inline-formula><mml:math id="M412" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux at 1 m s<inline-formula><mml:math id="M413" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">Error</oasis:entry>
         <oasis:entry colname="col4">Wind speed</oasis:entry>
         <oasis:entry colname="col5">SO<inline-formula><mml:math id="M414" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">(unit)</oasis:entry>
         <oasis:entry colname="col2">(T d<inline-formula><mml:math id="M415" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col3">(%)</oasis:entry>
         <oasis:entry colname="col4">(m s<inline-formula><mml:math id="M416" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col5">(T d<inline-formula><mml:math id="M417" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">DROAS traverse A</oasis:entry>
         <oasis:entry colname="col2">419.9 <inline-formula><mml:math id="M418" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 38.6</oasis:entry>
         <oasis:entry colname="col3">9.2</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M419" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">1776 <inline-formula><mml:math id="M420" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1108</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">DROAS traverse B</oasis:entry>
         <oasis:entry colname="col2">381.6 <inline-formula><mml:math id="M421" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 35.5</oasis:entry>
         <oasis:entry colname="col3">9.3</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M422" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">1614 <inline-formula><mml:math id="M423" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1007</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">La Silvia NOVAC station AVERAGE</oasis:entry>
         <oasis:entry colname="col2">362.3 <inline-formula><mml:math id="M424" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 72.5</oasis:entry>
         <oasis:entry colname="col3">20</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M425" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">1533 <inline-formula><mml:math id="M426" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 986</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">La Silvia NOVAC station MAX</oasis:entry>
         <oasis:entry colname="col2">481.72 <inline-formula><mml:math id="M427" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 96.3</oasis:entry>
         <oasis:entry colname="col3">20</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M428" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">2038 <inline-formula><mml:math id="M429" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1312</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">La Central NOVAC station AVERAGE</oasis:entry>
         <oasis:entry colname="col2">258.6 <inline-formula><mml:math id="M430" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 51.7</oasis:entry>
         <oasis:entry colname="col3">20</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M431" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">1094 <inline-formula><mml:math id="M432" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 704</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">La Central NOVAC station MAX</oasis:entry>
         <oasis:entry colname="col2">448.1 <inline-formula><mml:math id="M433" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 89.6</oasis:entry>
         <oasis:entry colname="col3">20</oasis:entry>
         <oasis:entry colname="col4">3.78 <inline-formula><mml:math id="M434" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.62</oasis:entry>
         <oasis:entry colname="col5">1896 <inline-formula><mml:math id="M435" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1220</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e6117">The obtained ratios of reactive bromine (Br<inline-formula><mml:math id="M436" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>) to SO<inline-formula><mml:math id="M437" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
(1.9 <inline-formula><mml:math id="M438" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M439" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>–9.8 <inline-formula><mml:math id="M440" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M441" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) are within the
range of bromine to sulfur ratios produced by other methods at Stromboli
volcano, e.g., alkaline trap sampling by Wittmer
et al. (2014) (4.3 <inline-formula><mml:math id="M442" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M443" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>–2.36 <inline-formula><mml:math id="M444" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M445" 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>). Figure 7b
shows the Br<inline-formula><mml:math id="M446" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M447" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M448" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios for different plume ages, which
was calculated by taking wind speeds into account. Although the<?pagebreak page2452?> general
feasibility of the used methods for the investigation of reactive halogen
species in an aging plume is demonstrated in this proof-of-principle
approach, a trend in the Br<inline-formula><mml:math id="M449" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M450" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M451" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio over age is not
recognizable for this limited data set. Without information on abundances of
other halogen species such as BrO<inline-formula><mml:math id="M452" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mo>(</mml:mo><mml:mi mathvariant="normal">g</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:msub></mml:math></inline-formula>, HBr<inline-formula><mml:math id="M453" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mo>(</mml:mo><mml:mi mathvariant="normal">g</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:msub></mml:math></inline-formula> and aqueous
particulate bromine (HBr<inline-formula><mml:math id="M454" display="inline"><mml:msub><mml:mi/><mml:mrow><mml:mo>(</mml:mo><mml:mi mathvariant="normal">aq</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:msub></mml:math></inline-formula>), interpretation of the
Br<inline-formula><mml:math id="M455" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M456" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M457" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio is difficult, as the emitted gas composition may
also change on shorter timescales (La Spina et al., 2013) compared to the
campaign duration. However, an increase in the reactive bromine species BrO
with distance from the crater rim has previously been observed by DOAS
measurements at various volcanoes and is well described in the literature
(Oppenheimer et al., 2006; Bobrowski et al., 2007). Although the bromine
speciation in volcanic plumes has been the subject of several ground-based (e.g.,
Gliß et al., 2015) airplane (e.g., General et al., 2015), satellite (e.g.,
Theys et al., 2009; Hörmann et al., 2013) and model studies (e.g.,
Bobrowski et al., 2007; Roberts et al., 2009, 2014; von Glasow, 2010;
Jourdain et al., 2016) in recent years, in situ measurements are
scarce. The data presented here for the first minute after emission highlight
the potential for UAV-based measurements to improve the sample acquisition and
thus obtain a better understanding of plume aging.</p>
      <p id="d1e6334">As shown in Fig. 7c, the Br<inline-formula><mml:math id="M458" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> to SO<inline-formula><mml:math id="M459" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio seems to change not
only with the plume age but also with CO<inline-formula><mml:math id="M460" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M461" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M462" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> mixing ratios,
which were simultaneously obtained. However, with only three data points a
further interpretation is inadequate due to the lack of a statistical basis.
Nevertheless, these first results show the principal practicality of the used
denuder sampling and gas sensing methods for simultaneous investigation of
halogen, carbon and sulfur emissions.</p>
</sec>
<?pagebreak page2453?><sec id="Ch1.S4.SS4">
  <title>DROAS measurements</title>
      <p id="d1e6386">On 27 September, two DROAS plume transects were performed at Turrialba
volcano during mild ash emission at around 2800 m a.s.l. with a total
flight time of approximately 10 min. The flight was conducted in the
downwind direction west of the active vent and crossed underneath the plume
on a south–north axis (Fig. 8b), exiting the plume on both ends of the
flight path, which is indicated by the low SO<inline-formula><mml:math id="M463" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts close to
the baseline in the northern- and southernmost section of the flight path
(Fig. 8c). SO<inline-formula><mml:math id="M464" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fluxes were calculated for that flight and resulted in
1776 <inline-formula><mml:math id="M465" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1108 T d<inline-formula><mml:math id="M466" 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> SO<inline-formula><mml:math id="M467" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> for traverse A and
1616 <inline-formula><mml:math id="M468" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1007 T d<inline-formula><mml:math id="M469" 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> SO<inline-formula><mml:math id="M470" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> for traverse B (see Table 5).
Calculation of the SO<inline-formula><mml:math id="M471" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fluxes obtained by the two scanning DOAS
instruments from the NOVAC network, located on the southern edge of the plume,
gave average results of 1533 <inline-formula><mml:math id="M472" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 986  T d<inline-formula><mml:math id="M473" 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> SO<inline-formula><mml:math id="M474" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> for
La Silvia and 1094 <inline-formula><mml:math id="M475" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 704 T d<inline-formula><mml:math id="M476" 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> SO<inline-formula><mml:math id="M477" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> from La
Central for a 2 h period, in which the flight took place. Therefore, the
results of the DROAS traverses are in good agreement with the scanning DOAS
stations. De Moor et al. (2016a) conducted car-based mobile
DOAS transects, which typically take <inline-formula><mml:math id="M478" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 45 min for a round trip due
to rough terrain. Dynamic gas plumes can significantly change the plume's
travel direction on scales of minutes, introducing a significant source of
error to car traverses. A major advantage of the UAV method is that it is
much quicker, about 10 min for a round trip, thus providing a more
accurate snapshot of the plume.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><label>Figure 8</label><caption><p id="d1e6539"><bold>(a)</bold> Drone-operated miniature DOAS setup,
<bold>(b)</bold> Illustration of SO<inline-formula><mml:math id="M479" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts measured by DROAS at
Turrialba volcano, <bold>(c)</bold> SO<inline-formula><mml:math id="M480" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column amounts during the
transversal flight underneath the plume.</p></caption>
          <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://amt.copernicus.org/articles/11/2441/2018/amt-11-2441-2018-f08.pdf"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusion and outlook</title>
      <p id="d1e6581">In this study we have demonstrated the feasibility of a multicopter-based
approach for volcanic in situ plume measurements to investigate
the compositional variability of an aging plume. The use of a multicopter UAV
proved to be a suitable alternative to ground-based operations, especially in
hard to access or inaccessible areas, like active volcanic vents or
elevated downwind plumes. The aerial sampling systems demonstrated robustness
and effectiveness during the field missions with harsh environmental and
meteorological conditions, including ash-laden plumes. With the newly
developed sampling system, reactive halogen species were observable in
previously inaccessible downwind plume areas. Halogen speciation information
enhances our understanding of plume chemistry in the aging plume, which
represents important knowledge for new volcano-monitoring approaches.
Therefore, in situ speciation methods for halogens should be extended and
optimized for other gaseous and aqueous compounds including chlorine and
iodine species. Additionally, at Stromboli volcano changes in the
Br<inline-formula><mml:math id="M481" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M482" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M483" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratios were observed with different CO<inline-formula><mml:math id="M484" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M485" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M486" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
ratios, which represent an interesting matter and should be further explored
in future studies.</p>
      <p id="d1e6635">Furthermore, multicopter-based CO<inline-formula><mml:math id="M487" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M488" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> SO<inline-formula><mml:math id="M489" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> ratio measurements
showed their reliability, creating a promising approach<?pagebreak page2454?> to monitoring
inaccessible volcanoes or during dangerous eruptions minimizing personnel
risk at highly active volcanoes. Although we demonstrated the applicability
of the Sunkist lightweight gas sensing system for potential UAV-based
monitoring, challenges in the acquisition of high-quality data for diluted
plumes still exist. Thus, more sophisticated components (e.g., sensors,
microcontroller or data logger) promise to achieve better sensitivities, but
with the disadvantage of higher losses in the case of a crash.</p>
      <p id="d1e6663">Moreover, the UAV application presented here of a miniature DOAS
instrument (DROAS) for SO<inline-formula><mml:math id="M490" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> gas flux measurements has shown its quality
in the harsh environment of Turrialba volcano. Its potential to be an
excellent alternative to walking or car-based traverses for SO<inline-formula><mml:math id="M491" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> flux
acquisition has been proven with a significant reduction in risk and
operation time.</p>
      <p id="d1e6684">The case studies presented here explored the general feasibility of
multirotor UAVs in volcanic plume studies and are an initial step in the
direction of remotely operated gas measurements at active volcanoes. We have
shown the potential of UAV-based sampling to gain insights into reactive
halogen chemistry and processes of plume aging, and further application of
this method could yield data from previously physically inaccessible plume
regions. Technological advances promise to enable scheduled, preprogrammed
and autonomous UAV operations (e.g., from hangars close to volcanoes), with
extended flight times for regular hazard assessments.</p>
</sec>

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

      <p id="d1e6691">All the data in this study are available from the authors upon request. If you
are interested in obtaining access to them, please send a message
to hoffmant@uni-mainz.de.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e6694">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/amt-11-2441-2018-supplement" xlink:title="zip">https://doi.org/10.5194/amt-11-2441-2018-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e6703">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e6709">Julian Rüdiger, Nicole Bobrowski, Alexandra Gutmann and Thorsten Hoffmann
acknowledge support by the research center “Volcanoes and Atmosphere in
Magmatic, Open Systems” (VAMOS), University of Mainz, Germany. Julian
Rüdiger is thankful for funding from the Max Planck Graduate School at the
MPIC (MPGS), Mainz, the German Academic Exchange Service (DAAD) and the
support by OVSICORI (Costa Rica) and INETER (Nicaragua). The authors also
thank Ulrich Platt for his support on the theoretical assessment of
multicopter sampling and Christoph Kern for reviewing and improving the
manuscript.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: Kimberly Strong <?xmltex \hack{\newline}?>
Reviewed by: Christoph Kern, Jorge Andres Diaz, and one anonymous referee</p></ack><ref-list>
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    <!--<article-title-html>Implementation of electrochemical, optical and denuder-based sensors and sampling techniques on UAV for volcanic gas measurements: examples from Masaya, Turrialba and Stromboli volcanoes</article-title-html>
<abstract-html><p>Volcanoes are a natural source of several reactive gases (e.g.,
sulfur and halogen containing species) and nonreactive gases (e.g.,
carbon dioxide) to the atmosphere. The relative abundance of carbon and
sulfur in volcanic gas as well as the total sulfur dioxide emission rate from
a volcanic vent are established parameters in current volcano-monitoring
strategies, and they oftentimes allow insights into subsurface processes.
However, chemical reactions involving halogens are thought to have
local to regional impact on the atmospheric chemistry around passively
degassing volcanoes. In this study we demonstrate the successful deployment
of a multirotor UAV (quadcopter) system with custom-made lightweight payloads
for the compositional analysis and gas flux estimation of volcanic plumes.
The various applications and their potential are presented and discussed in
example studies at three volcanoes encompassing flight heights of 450 to
3300&thinsp;m and various states of volcanic activity. Field applications were
performed at Stromboli volcano (Italy), Turrialba volcano (Costa Rica) and
Masaya volcano (Nicaragua). Two in situ gas-measuring systems adapted for
autonomous airborne measurements, based on electrochemical and optical
detection principles, as well as an airborne sampling unit, are introduced.
We show volcanic gas composition results including abundances of CO<sub>2</sub>,
SO<sub>2</sub> and halogen species. The new instrumental setups were compared with
established instruments during ground-based measurements at Masaya volcano,
which resulted in CO<sub>2</sub>&thinsp;∕&thinsp;SO<sub>2</sub> ratios of 3.6&thinsp;±&thinsp;0.4. For
total SO<sub>2</sub> flux estimations a small differential optical absorption
spectroscopy (DOAS) system measured SO<sub>2</sub> column amounts on transversal
flights below the plume at Turrialba volcano, giving
1776&thinsp;±&thinsp;1108&thinsp;T&thinsp;d<sup>−1</sup> and 1616&thinsp;±&thinsp;1007&thinsp;T&thinsp;d<sup>−1</sup> of SO<sub>2</sub>
during two traverses. At Stromboli volcano, elevated CO<sub>2</sub>&thinsp;∕&thinsp;SO<sub>2</sub>
ratios were observed at spatial and temporal proximity to explosions by
airborne in situ measurements. Reactive bromine to sulfur ratios of
0.19&thinsp; × &thinsp;10<sup>−4</sup> to 9.8&thinsp; × &thinsp;10<sup>−4</sup> were measured in situ
in the plume of Stromboli volcano, downwind of the vent.</p></abstract-html>
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