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  <front>
    <journal-meta><journal-id journal-id-type="publisher">ACP</journal-id><journal-title-group>
    <journal-title>Atmospheric Chemistry and Physics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1680-7324</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-22-12675-2022</article-id><title-group><article-title>Exploring the inorganic composition of the Asian Tropopause Aerosol Layer
using medium-duration balloon flights</article-title><alt-title>Exploring the inorganic composition of the ATAL</alt-title>
      </title-group><?xmltex \runningtitle{Exploring the inorganic composition of the ATAL}?><?xmltex \runningauthor{H.~Vernier et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Vernier</surname><given-names>Hazel</given-names></name>
          <email>hazel.vernier@cnrs-orleans.fr</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Rastogi</surname><given-names>Neeraj</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-4532-7827</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Liu</surname><given-names>Hongyu</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2164-6383</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Pandit</surname><given-names>Amit Kumar</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1957-5934</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Bedka</surname><given-names>Kris</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-3066-0555</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Patel</surname><given-names>Anil</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Ratnam</surname><given-names>Madineni Venkat</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Kumar</surname><given-names>Buduru Suneel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Zhang</surname><given-names>Bo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-0746-4732</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Gadhavi</surname><given-names>Harish</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-8935-1517</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Wienhold</surname><given-names>Frank</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Berthet</surname><given-names>Gwenael</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-3169-1636</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Vernier</surname><given-names>Jean-Paul</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Laboratoire de Physique et Chimie de l'Environnement et de l'Espace
(LPC2E), <?xmltex \hack{\break}?>Université d'Orléans, Orléans, France</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Geosciences Division, Physical Research Laboratory, Ahmedabad, India</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>National Institute of Aerospace, Hampton, VA, USA</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Science Directorate, NASA Langley Research Center, Hampton, VA, USA</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>National Atmospheric Research Laboratory, Department of Space, Gadanki, India</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Tata Institute of Fundamental Research Balloon Facility (TIFR-BF), Hyderabad, India</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Institute for Atmospheric and Climate Science (IAC), ETH Zurich, Zurich, Switzerland</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Hazel Vernier (hazel.vernier@cnrs-orleans.fr)</corresp></author-notes><pub-date><day>29</day><month>September</month><year>2022</year></pub-date>
      
      <volume>22</volume>
      <issue>18</issue>
      <fpage>12675</fpage><lpage>12694</lpage>
      <history>
        <date date-type="received"><day>8</day><month>November</month><year>2021</year></date>
           <date date-type="rev-request"><day>3</day><month>December</month><year>2021</year></date>
           <date date-type="rev-recd"><day>11</day><month>April</month><year>2022</year></date>
           <date date-type="accepted"><day>22</day><month>June</month><year>2022</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2022 </copyright-statement>
        <copyright-year>2022</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e235">Satellite observations have revealed an enhanced aerosol
layer near the tropopause over Asia during the summer monsoon, called the
“Asian Tropopause Aerosol Layer” (ATAL). In this work, aerosol particles in
the ATAL were collected with a balloon-borne impactor near the tropopause
region over India, using extended-duration balloon flights, in summer 2017
and winter 2018. The chemical composition of these particles was further investigated by
quantitative analysis using offline ion chromatography. Nitrate
(NO<inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and nitrite (NO<inline-formula><mml:math id="M2" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> were found to be the dominant
ions in the collected aerosols with values ranging between 87 and 343 ng m<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP (standard temperature and pressure) during the summer campaign. In
contrast, sulfate (SO<inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> levels were found to be above the detection
limit (<inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) only in winter. In addition, we
determined the origin of the air masses sampled during the flights using the
analysis of back trajectories as well as a convective proxy from cloud-top
temperature fields derived from a geostationary satellite. The results
obtained from this analysis were put into the context of large-scale transport and
aerosol distribution using GEOS-Chem chemical transport model simulations.
The first flight in summer 2017 which sampled an air mass within the Asian
monsoon anticyclone (AMA), influenced by convection over Western China, was
associated with particle size diameters from 0.05 to 0.15 <inline-formula><mml:math id="M7" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m. In
contrast, the second flight sampled air masses at the edge of the AMA
associated with a larger particle size radius (<inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M9" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) with
a higher NO<inline-formula><mml:math id="M10" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration. The sampled air masses in winter 2018 were
likely affected by smoke from the Pacific Northwest fire event in Canada,
which occurred 7 months before our campaign, associated with concentration
enhancements of SO<inline-formula><mml:math id="M11" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> and Ca<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>. Overall, our results suggest
that nitrogen-containing particles represent a large fraction of cloud-free
and in-cloud aerosols populating the ATAL, which is partially in agreement with the
results from aircraft measurements during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign. The exact
nature of those particles is still unknown, but their coincidences with
subvisible cirrus clouds and their sizes suggest nitric acid trihydrate
(NAT) as a possible candidate, as NAT has already been observed in the
tropical upper troposphere and lower stratosphere in other studies.
Furthermore, GEOS-Chem model simulations indicate that lightning NO<inline-formula><mml:math id="M13" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>
emissions could have significantly impacted the production of nitrate aerosols
sampled during the summer of 2017.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
<sec id="Ch1.S1.SS1">
  <label>1.1</label><title>The Asian summer monsoon and the transport of pollution</title>
      <p id="d1e409">Over the past 2 decades, rapid economic growth in Asia has led to serious
environmental threats to water and air quality. Every winter, pollutants can
be observed through satellites in the form of a grayish veil of particulate
matter, referred to as the “Asian brown cloud” (Ramanathan and Crutzen, 2003).
In summer, the southwest Asian monsoon (SAM) discharges polluted air over
very long distances. According to trajectory calculations, about 20 % of
air masses in the tropical lower stratosphere have been in contact with air
in the boundary layer in Asia (Orbe et al., 2015). Polluted air masses
transported from the boundary layer to higher altitudes are confined within
the Asian monsoon anticyclone (AMA) (Ploeger et al., 2017). In the AMA,
pollution is accumulated and is further dispersed over a large area of the
Northern Hemisphere, reaching latitudes from 10 to 40<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and longitudes from 10 to 140<inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (Park et al., 2007;
Randel et al., 2010; Ungermann et al., 2016). The air exported from the AMA
influences the composition of the entire lowermost stratosphere of the
Northern Hemisphere (Ploeger et al., 2017; Santee et al., 2017; Yu et al.,
2017). Deep convective clouds represent conduits for air pollution to reach
the upper-troposphere–lower-stratosphere (UTLS) region. Aerosols in the
UTLS have longer residence times than those in the lower troposphere,
influencing the chemistry of the atmosphere and the Earth's climate (Rasch
et al., 2008). In addition, they also affect the concentration of chemical
species through changes in photolysis rates and heterogenous reactions
(Pitari et al., 2014). It has been further reported that aerosols in the
UTLS can impact climate by altering the properties of cirrus clouds via
homogeneous or heterogeneous ice nucleation (Li et al., 2005, 2009;  Yin et al., 2012; Fadnavis et al., 2013; Wagner et al., 2020).</p>
      <p id="d1e430">A layer of aerosol enhancements observed by the Cloud-Aerosol Lidar and
Pathfinder Satellite Observation (CALIPSO) satellite and the Stratospheric Aerosol
and Gas Experiment (SAGE) II spaceborne instruments (Vernier et al., 2011; Thomason and Vernier,
2013), also known as the “Asian Tropopause Aerosol Layer” (ATAL), coincides
with the presence of enhanced trace gas pollutants (e.g., carbon monoxide, CO, and
hydrogen cyanide, HCN) in the UTLS region. Balloon-borne measurements
(Vernier et al., 2015, 2018) confirmed the presence of the ATAL at altitudes
of 14–18 km, connected to the AMA. The positive trend in UTLS aerosols
inferred from satellite observations since the late 1990s may reflect the
increasing influence of anthropogenic emissions on stratospheric aerosol
levels. Indeed, global chemical transport model simulations suggest that
sulfate, nitrate, and organic aerosols produced from gas-phase precursors
populate the UTLS region over Asia in various relative fractions during the
summer monsoon (Brabec et al., 2012; Gu et al., 2016; Fairlie et al., 2020).</p>
</sec>
<sec id="Ch1.S1.SS2">
  <label>1.2</label><title>What is the significance of the ATAL?</title>
      <p id="d1e441">The ATAL constitutes one of the most important sources of UTLS aerosols in
the absence of volcanic eruptions (Vernier et al., 2011). It has the
potential to affect the Earth's radiative balance (Vernier et al., 2015),
stratospheric ozone chemistry, and the properties of cirrus clouds. For
example, an increase in the solid-particle concentration relative to the liquid
background aerosol levels could trigger heterogeneous freezing and the
formation of cirrus clouds at a lower relative humidity with respect to ice
(Zawadowicz et al., 2015; Wang et al., 2020). Model simulations suggest that the
ATAL represents 20 % of the total column surface area density in the
stratosphere of the Northern Hemisphere (Yu et al., 2018) with potential
halogen heterogeneous chemistry on aerosols that can affect ozone trends
(Solomon et al., 2016). The types of aerosols populating the ATAL could
affect those chemical processes. Finally, the presence of absorbing aerosols
(e.g., soot) in the UTLS could shift the level of zero net radiative heating
upward and enhance troposphere-to-stratosphere transport (Yu et al., 2015).</p>
</sec>
<sec id="Ch1.S1.SS3">
  <label>1.3</label><title>What is known about ATAL's composition?</title>
      <p id="d1e452">The composition of the ATAL is a very active research topic.
Energy-dispersive X-ray analysis (EDX) of aerosols sampled near 10–12 km
aboard commercial aircraft as part of the Civil Aircraft for the Regular
Investigation of the atmosphere Based on an Instrument Container (CARIBIC)
program, at the bottom part of the ATAL, suggests a ratio of carbon to
sulfur in the range of 2–10 (Vernier et al., 2015). Aircraft limb infrared
measurements carried out during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign in Nepal and India
show the presence of ammonium nitrate in aerosol particles, validating
satellite observations from the Cryogenic Infrared Spectrometers and
Telescopes for the Atmosphere (CRISTA) and Michelson Interferometer for
Passive Atmospheric Sounding (MIPAS) instruments (Höpfner et al., 2019). A combination
of community models and aerosol–climate–chemistry models indicates that, along
with surface-emitted and secondary organic aerosols, the ATAL could be
comprised of a significant amount of mineral dust either as a major
component (Fadnavis et al., 2013; Lau et al., 2018; Ma et al., 2019;
Bossolasco et al., 2021) or minor component (Yu et al., 2015, 2017; Gu et al.,
2016; Fairlie et al., 2020).</p>
      <p id="d1e455">The aerosol particles in the ATAL are looked upon as an insignia of the
presence of pollution in the monsoon circulation from large 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> and
NO<inline-formula><mml:math id="M17" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions in South and Southeastern Asia. Human-induced biomass burning (Van
der A et al., 2008), fossil fuel combustion (Ghude et al., 2009), wildfires (Goode et al., 2000; Andrae and Merlet, 2001), and
lightning (Martin et al., 2007; Yuan et al., 2019) are the significant anthropogenic and
natural sources of NO<inline-formula><mml:math id="M18" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>. Soil biogenic emission of NO<inline-formula><mml:math id="M19" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> represents a
large fraction of total NO<inline-formula><mml:math id="M20" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> (Jalié et al., 2004). Reactive nitrogen
is emitted from the tropical soils by microbial processes as NO (Yienger and
Levy, 1995; Conrad, 1996). Investigations of the composition of the
aerosol particles in the ATAL are exiguous, although preliminary data from
balloon-borne measurements indicate the presence of nitrate aerosol
particles (Vernier et al., 2018). Recent in situ aerosol mass spectrometric
measurements also reveal the presence of nitrate, ammonium, and sulfate
within the ATAL (Höpfner et al., 2019; Yuan et al., 2019).</p>
      <p id="d1e503">Here, we investigate the inorganic composition of the ATAL over India during
the summer monsoon and in winter using a balloon-borne aerosol impactor system
with offline ion chromatography (IC) analysis. Section 2 describes the
concept of the balloon experiment and the impactor system. The results of the IC analysis of the samples collected on the ground (GRND), during the two balloon flights (ZF2 and ZF3) in the summer of 2017, and during the flight (ZFW) in winter 2018 are described in Sect. 3. Section 4
compares those results obtained from balloon-borne measurements and
satellite observations. Section 5 describes the influence of the Canadian
wildfire event on the Balloon-borne measurement
campaigns of the Asian Tropopause Aerosol Layer (BATAL) winter flight. The origin of the air masses
sampled during those flights is assessed in Sect. 6 using
back-trajectory analysis combined with convective proxies. Section 7
addresses the formation of nitrite and its measurements. The GEOS-Chem model
simulations are presented in Sect. 8 in order to put the measurements in the
context of regional aerosol transport and distribution; this is followed by a
summary and conclusions in Sect. 9.</p>
</sec>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Balloon flights, instrumentation, and chemical analysis approach</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Rationale for the experiment</title>
      <p id="d1e522">Contingent on measurements during the 2015 BATAL campaign, a
concentration of about 20 particles cm<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> was found near the tropopause
for aerosols with a radius greater than 75 nm (Vernier et al., 2018). This translates
into a mass concentration of 40 ng m<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP (standard temperature and pressure; hereafter STP is assumed when
mass concentrations are given), assuming that the aerosols were liquid
sulfate droplets. During that time, the lower detection limit for the IC
instrument at NASA Langley Research Center was around 20 ng m<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. In
order to reach the detection limit of sulfate aerosols, one would need to
sample at least 0.5 m<inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula>, assuming the sulfate concentration above. Based
on those results and weight limitations, we decided to use an impactor with
a flow rate of 7 L min<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  which would need to float in the UTLS region for
several hours to sample a sufficient air volume (2 h of sampling results in 0.84 m<inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e597"><bold>(a)</bold> Schematic diagram of the zero-pressure flight (ZP) concept.
<bold>(b)</bold> Picture of the science payload, impactor preparation, and balloon
flight launch. <bold>(c)</bold> Time–height curves of the GPS altitudes of the three
zero-pressure flights during summer 2017, in comparison with that of winter
2018, launched from TIFR-BF, Hyderabad, India.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f01.jpg"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Balloon experiment</title>
      <p id="d1e622">We used zero-pressure plastic balloons to achieve a float near the
tropopause and sample enough aerosols to reach the detection limit of the
IC. The Tata Institute of Fundamental Research Balloon Facility (TIFR-BF) in
Hyderabad, India, provided the infrastructure to conduct the experiment. Polyethylene balloons with volumes between 300
and 500 m<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> (manufactured by TIFR) were used for the
zero-pressure flights (ZF) to carry a communication/control package
(developed by TIFR), a science module (including a meteorological radiosonde), a
Compact Optical Backscatter and Aerosol Detector (COBALD) system (Vernier et al.,
2015; Yu et al., 2017), an aerosol impactor, and a ballast module at the end
of the flight train. The schematic diagram shown in Fig. 1a
describes a typical balloon flight. During the ascent, the atmospheric pressure
decreases allowing gas inside the balloon to occupy a large space (stage 2 in Fig. 1a).
The equilibrium point is reached when the hydrogen escapes from the side
escape tubes attached at the bottom of the balloon, until the inside
pressure equals the outside pressure (stage 3 in Fig. 1a), leading to a pressure
differential of zero (zero-pressure balloon). The float altitude depends upon
the volume of the balloon, the density of gas, and the total weight
of the system following a simple Archimedes principle. Extreme cold
temperatures near the tropopause affect the float due to radiative cooling,
leading to a reduction in the buoyancy force, which entrains the descent of
the system (stage 4 in Fig. 1a). To counterbalance this effect, ballast shots are
released from a container to reduce the total weight (stage 5 in Fig. 1a), leading to
the ascent of the balloon.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Balloon-borne aerosol impactor</title>
      <p id="d1e642">We developed a balloon-borne aerosol impactor (BAI) for the ZF flights.
This aerosol sampler is comprised of a four-stage impactor, a vacuum pump, a
volumetric flow controller, and a Raspberry-Pi-based controller connected to
a meteorological sonde. The mechanical part of the impactor was designed by
California Measurements, Inc. and is based upon the principle of inertia, where the flow and the
instrument dimension determine the size cutoff at different stages. The size
cutoffs with respect to the particle radius for the impactor's four stages (S-1, S-2, S-3, and S-4) are 2, 0.5,
0.15, and 0.05 <inline-formula><mml:math id="M28" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, respectively, at 7 L min<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> . The pump is controlled electronically based
on the pressure measurements from the meteorological sonde. Our objective is
to sample aerosols within the ATAL region; to achieve this, the pump was
switched on below 150 hPa (<inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula> km) and switched off above 70 hPa (<inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">18</mml:mn></mml:mrow></mml:math></inline-formula> km). However, due to a reduction in the pump
efficiency at those levels, the flow rates lay between 5 and 6 L min<inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>,  leading
to a small shift in the size cutoff by up to 18 % (e.g., 2.36 <inline-formula><mml:math id="M33" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m instead of
2 <inline-formula><mml:math id="M34" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m for a flow of 5 L min<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>  for S-1).</p>
      <p id="d1e726">In 2017, we conducted a series of balloon flights using the BAI and a COBALD sonde for aerosol backscatter measurements of cloud and
aerosol layers encountered by the BAI. The time–height evolution of the three
ZFs is shown in Fig. 1c, with flight ZF1 being a test flight to
understand and maintain the float altitude using ballast. The maximum flight
duration was obtained during ZF3, which had a float time of nearly 2 h 50 min above
150 hPa and below 70 hPa. The oscillation of the balloon trajectories is due
to the cooling of the gas inside the balloon and the subsequent release of
ballast to regain higher altitudes. The BAI was preserved in a foam box
containing dry ice during transportation to TIFR; once there, the filters were
immediately unloaded and stored in 47 mm petri dishes that were frozen at
<inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">24</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C until further analysis at the Physical Research Laboratory,
Ahmedabad, India. Figure 2 represents the time evolution of altitude,
temperature, and relative humidity inside the box containing the impactor
and also outlines the different phases of the experiment.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e750">Time series of the altitude, temperature, and relative humidity
profiles of the samples inside the foam box during the ZF2 flight.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f02.png"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>Analysis of major ions in aerosol samples</title>
      <p id="d1e767">Aerosol samples were extracted in deionized water (Milli-Q, specific
resistance <inline-formula><mml:math id="M38" display="inline"><mml:mrow><mml:mo>≥</mml:mo><mml:mn mathvariant="normal">18.2</mml:mn></mml:mrow></mml:math></inline-formula> M <inline-formula><mml:math id="M39" display="inline"><mml:mi mathvariant="normal">Ω</mml:mi></mml:math></inline-formula> cm) in sterile polypropylene vials for 30 min (three intervals of 10 min each) using ultrasonication. The extract
was further analyzed for water-soluble inorganic species (WSIS, such as
Na<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>, K<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>, Mg<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, Ca<inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, NH<inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, Cl<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula>,
NO<inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, NO<inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, and SO<inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> using an ion
chromatograph (Dionex ICS-5000 DC-5, Thermo Scientific). For calibration, 1000 mg L<inline-formula><mml:math id="M49" 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>
stock solution of each cation (using Merck high-purity analytical-grade
NaNO<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>, (NH<inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub><mml:msub><mml:mo>)</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>SO<inline-formula><mml:math id="M52" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>, KNO<inline-formula><mml:math id="M53" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, CaCl<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> <inline-formula><mml:math id="M55" display="inline"><mml:mo>⋅</mml:mo></mml:math></inline-formula> 2H<inline-formula><mml:math id="M56" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O, and
Mg metal) were prepared. In addition, mixed standards were prepared by
diluting stock solutions in polypropylene vials, thereby satisfying the primary
requirement of instrument calibration for cations. Similarly, anion
Multi-element standard II (1000 mg L<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in H<inline-formula><mml:math id="M58" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O, reference no. HC 409399, Merck) was
diluted subsequently as instrument calibration for anions. Post extraction,
the extract of each sample was then separated and eluted in the cation
column (Dionex IonPac™ CS16, 5 mm <inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mo>×</mml:mo><mml:mn mathvariant="normal">250</mml:mn></mml:mrow></mml:math></inline-formula> mm) and anion column
(Dionex IonPac™ AS23, 4 mm <inline-formula><mml:math id="M60" display="inline"><mml:mrow><mml:mo>×</mml:mo><mml:mn mathvariant="normal">250</mml:mn></mml:mrow></mml:math></inline-formula> mm) via the interaction with
the mobile phases, i.e., 30 mM methyl sulfonic acid (MSA) for cations and a
mixture of 4.5 mM carbonate <inline-formula><mml:math id="M61" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mn mathvariant="normal">0.8</mml:mn></mml:mrow></mml:math></inline-formula> mM bicarbonate solutions for anions.
The quantification of each ion was then performed using the conductivity
detector. Several blanks were analyzed along with the samples. The ionic concentrations reported here are blank corrected. As the
concentrations of different species were too low in UTLS aerosol samples,
only those values which were at least 2 times higher than their respective
blanks are reported. More than 50 % of samples were repeated for
reproducibility, and they were found to vary by between 2 % and 20 % for all of the analyzed
ions. To validate the analysis, Dionex Six Cation-I Standard (product code 040187) and Dionex Combined Seven Anion Standard II (product code 57590) were diluted and
checked in the respective cation and anion calibration curves which were
found within <inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> % relative standard deviation (RSD).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e1037"><bold>(a)</bold> Results from the analysis of inorganic aerosol for aerosol
ionic composition of the filters collected <bold>(i)</bold> on the ground <bold>(ii)</bold> during ZF2, <bold>(iii)</bold> during ZF3
in summer 2017, and <bold>(iv)</bold> during ZFW in winter 2018. <bold>(b)</bold> The percentage distribution
of individual ions. S-1 to S-4 indicate the four stages of the impactor. The
size cutoffs are <inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>, 0.5, 0.15, and 0.05  <inline-formula><mml:math id="M64" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m for S-1, S-2, S-3,
and S-4, respectively.</p></caption>
          <?xmltex \igopts{width=290.21811pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f03.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results of the IC analysis</title>
      <p id="d1e1091">Figure 3 shows the ionic concentration of ground samples (GRND) as well as those of airborne samples (ZF2 and ZF3) collected aboard zero-pressure flights on 15 and 21 August 2017. Additionally, the figure also shows the ionic concentration of the flight held during the winter 2018 campaign denoted as (ZFW). In GRND samples, Na<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and Ca<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> cations are seen on S-1 and S-2 with corresponding anions (NO<inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>,
SO<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, and NO<inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> coexisting at the same stage. High
NH<inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> is observed only on S-3, with a concentration of 212 ng m<inline-formula><mml:math id="M71" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP. K<inline-formula><mml:math id="M72" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> was also seen on S-3, with a concentration of 26 ng m<inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP
(fine mode), and could have originated from biomass burning. City pollution
from Hyderabad is likely the source of those aerosols observed on the GRND
filters. Flights ZF2 and ZF3 show significant amounts of NO<inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and
NO<inline-formula><mml:math id="M75" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (87–343 ng m<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) with trace amounts of
mineral dust proxies (Ca<inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>. Biomass burning (K<inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> was observed in the
results of flight ZF2 only. The presence of non-sea-salt Ca<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> in
aerosols is often used as a proxy for mineral dust (Schüpbach et al.,
2013), whereas non-sea-salt K<inline-formula><mml:math id="M80" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> in aerosols is often used as a proxy for biomass burning
(Li et al., 2003). Although their concentrations were too low (close to
the detection limit), their presence indicates the possibility of trace contributions from
mineral dust and biomass burning.</p>
      <p id="d1e1287">Other species were below 5 (for cations) to 10 (for anions) ng m<inline-formula><mml:math id="M81" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP,
the detection limit of the IC instrument for our analytical setup. Charge
balance was not achieved due to a higher negative charge, mainly from
NO<inline-formula><mml:math id="M82" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and NO<inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, than positive charge, mainly from
NH<inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, Ca<inline-formula><mml:math id="M85" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, and K<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> (Fig. 3), implying the existence of
NO<inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and NO<inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> in forms other than salt. For
instance, nitric acid trihydrate (NAT, HNO<inline-formula><mml:math id="M89" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M90" display="inline"><mml:mo>⋅</mml:mo></mml:math></inline-formula> 3H<inline-formula><mml:math id="M91" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O) could
be another aerosol cluster in which NO<inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> may be present in the
tropical UTLS (Voigt et al., 2000). We did not find a significant amount of
ammonium in our ZF flight samples during the summer. Overall, the
concentration of nitrate (80–100 ng m<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) found on both flights seems
to be lower than the levels observed during StratoClim (Höpfner et al.,
2019). In the only flight during the winter of 2018, Na<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and K<inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>
were almost inexistent. In comparison, the mineral dust proxy (Ca<inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>
was present in trace amounts on all four impactor stages and could be
associated with SO<inline-formula><mml:math id="M97" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, which was also found on all four stages (Fig. 3b).</p>
      <p id="d1e1482">Balloon-borne and aircraft sampling techniques have been used since the
early 1970s to study the composition of aerosols in the UTLS region (Lazarus
et al., 1970). Höpfner et al. (2016) reported the presence of enhanced amounts of NO<inline-formula><mml:math id="M98" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> between 12 and 15 km within the Asian summer monsoon region. While sulfate tends to be stable enough to be collected and
further analyzed without major chemical transformation, other
nitrate-containing particles can be more unstable. NO<inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> salts
apart from NH<inline-formula><mml:math id="M100" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>NO<inline-formula><mml:math id="M101" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> are not significantly volatile after sampling
(Newman, 1993). The dissociation of NH<inline-formula><mml:math id="M102" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>NO<inline-formula><mml:math id="M103" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> into gas-phase
HNO<inline-formula><mml:math id="M104" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M105" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> increases sharply with increasing temperature and
relative humidity (Stelson and Steinfield, 1982; Lightstone et al., 2000), leading
to a significant loss of particulate nitrate (PN). The slight retention of
HNO<inline-formula><mml:math id="M106" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> (gas) on the PTFE (polytetrafluoroethylene) filter could represent a significant source of
particulate nitrate on filters at low concentrations and has been used in the
past to estimate stratospheric HNO<inline-formula><mml:math id="M107" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> (Lazarus et al., 1970). Additional
information available during ZF2 will be discussed to assess the presence of
ice clouds.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><?xmltex \def\figurename{Figure}?><label>Figure 4</label><caption><p id="d1e1582"><bold>(a)</bold> COBALD balloon in situ scattering ratio (SR) and color index (CI) profiles and <bold>(b)</bold> CALIOP satellite SR and
volume depolarization profiles co-located in time and
space (within 20 km and 1 h, respectively) on 15 August at 19:00 UT. <bold>(c)</bold> Time
series along ZF2 of SRs at 940 and 470 nm from COBALD
as well as the GPS altitude and measured pressure from the
iMet radiosonde.</p></caption>
        <?xmltex \igopts{width=298.753937pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f04.png"/>

      </fig>

</sec>
<sec id="Ch1.S4">
  <label>4</label><title>COBALD and CALIOP point to the presence of ice clouds during
ZF2</title>
      <p id="d1e1607">We will now focus the discussion on ZF2, which included a COBALD backscatter
sonde and was launched to be co-located in space and time (within 20 km and
1 h, respectively) with satellite observations from the CALIOP lidar aboard the CALIPSO
satellite. Figure 4a and b show scattering ratio (SR) and color index (CI)
profiles from COBALD (470 and 940 nm) as well as CALIOP SR and volume
depolarization profiles at 532 nm. Both balloon and satellite observations
show a layer between 13.5 and 16 km with high depolarization (CALIOP) and
a high color ratio (COBALD), likely made of aspherical particles. The derived
particulate depolarization ratio from CALIOP Level 2v4.1 within the layer
was <inline-formula><mml:math id="M108" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.47</mml:mn><mml:mo>+</mml:mo><mml:mo>/</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.06</mml:mn></mml:mrow></mml:math></inline-formula> (Fig. S3 in the Supplement) and was associated with an optical depth of
<inline-formula><mml:math id="M109" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.03</mml:mn><mml:mo>+</mml:mo><mml:mo>/</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula>, indicating the presence of a subvisible cirrus cloud. Flight
ZF2 floated near 14.5–17 km for more than 2 h (Fig. 1c). The time
series (Fig. 4c) indicate that the measurements took place within two
different air masses: first within an ice cloud, as discussed above,
and then in a cloud-free region. The pump connected to the impactor was
switched on below 150 hPa and run for <inline-formula><mml:math id="M110" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">16</mml:mn></mml:mrow></mml:math></inline-formula> min within the cloud
and for <inline-formula><mml:math id="M111" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> h 30 min in a cloud-free region.</p>
<sec id="Ch1.S4.SS1">
  <label>4.1</label><title>In-cloud nitrate particles</title>
      <p id="d1e1669">The sampling within an ice cloud (Fig. 4) during ZF2 could, therefore,
indicate the presence of in-cloud NO<inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. HNO<inline-formula><mml:math id="M113" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, (an oxidation
product of NO<inline-formula><mml:math id="M114" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>) and NH<inline-formula><mml:math id="M115" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> (released from agricultural sources) are said
to be absorbed into cloud droplets which then aid in the conversion of
HNO<inline-formula><mml:math id="M116" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> to aerosol NO<inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (Hayden et al., 2007). HNO<inline-formula><mml:math id="M118" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, being
readily soluble, tends to completely dissolve in cloud water (Steinfeld and
Pandis, 1998). Bela et al. (2016) found an almost 90 % scavenging
efficiency for HNO<inline-formula><mml:math id="M119" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> by sampling the inflow and outflow of convective
storms over the United States during the Deep Convective Clouds and
Chemistry (DC3) field campaign. However, we found that ZF2 sampled 90 ng m<inline-formula><mml:math id="M120" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP of NO<inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> for particle sizes between 2 and 0.5 <inline-formula><mml:math id="M122" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m on stage 2 and 11 ng m<inline-formula><mml:math id="M123" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP of NO<inline-formula><mml:math id="M124" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> on stage 3, corresponding
to particle sizes between 0.5 and 0.15 <inline-formula><mml:math id="M125" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m; this indicates that other
mechanisms might be taking place for HNO<inline-formula><mml:math id="M126" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and nitrate to survive
convection. Our measurements took place at a much higher altitude (16–17 km
instead of 10–12 km) and much colder temperature (<inline-formula><mml:math id="M127" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">70</mml:mn></mml:mrow></mml:math></inline-formula> to
<inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">80</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M129" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) than DC3, which may explain this apparent contrast between
DC3 and our measurements. Bela et al. (2016) found that ice retention had
little impact on scavenging efficiency in the Weather Research and
Forecasting (WRF) model coupled with Chemistry, suggesting that HNO<inline-formula><mml:math id="M130" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
formation in ice clouds via lightning-induced NO<inline-formula><mml:math id="M131" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> could be a more efficient
source than convective transport. The GEOS-Chem chemical transport model
(CTM) showed the presence of inorganic nitrate aerosol to be dominant in the
ATAL (Gu et al., 2016), with a significant fraction from lightning-induced
NO<inline-formula><mml:math id="M132" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> (Fairlie et al., 2020). The authors concluded that gas–aerosol
conversion of HNO<inline-formula><mml:math id="M133" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> was the driving factor behind this dominance, via the
processes discussed above.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <label>4.2</label><title>NAT particles</title>
      <p id="d1e1899">Another candidate for the presence of nitrate on the filters could be NAT
particles. They have been reported in tropical ice clouds by Voigt et al. (2008) with sizes (<inline-formula><mml:math id="M134" display="inline"><mml:mrow><mml:mi>D</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M135" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) consistent with their sampling on
stages 1 (<inline-formula><mml:math id="M136" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M137" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) and 2 (0.5–2 <inline-formula><mml:math id="M138" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) of our impactor.
In addition, NAT nucleation seems to be more efficient in subvisible ice
clouds at higher ambient temperature than the temperature associated with
NAT formation at <inline-formula><mml:math id="M139" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">78</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M140" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (Voigt et al., 2008). The sampling within
the ice cloud at temperatures between <inline-formula><mml:math id="M141" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">65</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M142" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">75</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M143" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C
would allow the presence of NAT. However, in the process of sampling,
transport, and extraction, there is the strong possibility of NAT particle
losses (if they were collected). In addition, if NO<inline-formula><mml:math id="M144" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> was present
in another form (refractory nitrate), it would remain relatively stable
during the abovementioned processes. Observed cations were close to or below the
detection limit compared with the significant concentrations of NO<inline-formula><mml:math id="M145" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>
and NO<inline-formula><mml:math id="M146" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. This observation along with the higher abundance of
NO<inline-formula><mml:math id="M147" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> allowed us to suggest the presence of NAT particles. However,
the reported NAT concentrations should be considered as the lower limit,
presuming some losses (unquantifiable) during the sampling, transport, and
extraction processes.</p>
</sec>
<sec id="Ch1.S4.SS3">
  <label>4.3</label><title>In-cloud calcium and its implication</title>
      <p id="d1e2054">The IC results of flight ZF2 showed the presence of particles of Ca<inline-formula><mml:math id="M148" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>
(9 ng m<inline-formula><mml:math id="M149" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) on stage 2 of
the impactor (0.5–2 <inline-formula><mml:math id="M150" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m). The erosion of calcareous soils
followed by strong convective vertical transport during summer results in
cloud water calcium (Issac et al., 1990). Cloud water experiments have shown
the formation of Ca(<inline-formula><mml:math id="M151" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>)<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> in the presence of <inline-formula><mml:math id="M153" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. Hill et al. (2007) and
Leaitch et al. (1986) found a positive correlation between Ca<inline-formula><mml:math id="M154" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> and
NO<inline-formula><mml:math id="M155" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. In addition to Ca<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, ZF2 also showed the presence of
NO<inline-formula><mml:math id="M157" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (90 ng m<inline-formula><mml:math id="M158" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) on the same stage of
the impactor (large
particles <inline-formula><mml:math id="M159" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M160" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), further implying the possibility of
Ca(<inline-formula><mml:math id="M161" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>)<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> formation in the presence of the acid HNO<inline-formula><mml:math id="M163" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>. Lastly, a high
concentration of nitrite (193 ng m<inline-formula><mml:math id="M164" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) was also found on stage 2 of
the impactor. The presence of nitrite in clouds is further discussed in
Sect. 7.</p>
</sec>
</sec>
<sec id="Ch1.S5">
  <label>5</label><title>The influence of Canadian wildfire plumes during the winter
flight</title>
      <p id="d1e2251">For the only flight during the winter of 2018, Na<inline-formula><mml:math id="M165" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and K<inline-formula><mml:math id="M166" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> were
almost inexistent. In comparison, the mineral dust proxy (Ca<inline-formula><mml:math id="M167" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> was
present on all four impactor stages: 30 ng m<inline-formula><mml:math id="M168" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 1 (particle sizes <inline-formula><mml:math id="M169" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M170" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), 46 ng m<inline-formula><mml:math id="M171" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 2 (particle
sizes between 0.5 and 2 <inline-formula><mml:math id="M172" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), 11 ng m<inline-formula><mml:math id="M173" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 3 (particle sizes between 0.15 and 0.5 <inline-formula><mml:math id="M174" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), and 29 ng m<inline-formula><mml:math id="M175" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 4 (particle sizes between 0.05 and 0.15 <inline-formula><mml:math id="M176" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m). Interestingly, SO<inline-formula><mml:math id="M177" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> was also found on all four stages
(Fig. 3b): 14 ng m<inline-formula><mml:math id="M178" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 1, 21 ng m<inline-formula><mml:math id="M179" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on
stage 2, 15 ng m<inline-formula><mml:math id="M180" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 3, and 12 ng m<inline-formula><mml:math id="M181" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on stage 4. Satellite analysis of aerosol extinction
at 1020 nm from the Stratospheric Aerosol and Gas Experiment III (SAGE III)
was conducted to understand the origin of those particles. We found high
aerosol extinction values in the Northern Hemisphere from August 2017 to
February 2018, consistent with the presence of smoke from the 2017 Canadian
fire (Fig. S2).</p>
      <p id="d1e2442">Fires that intensify towering thunderstorms have the tendency to inject aerosols into the lower stratosphere that were otherwise thought to have originated from volcanic plumes (Fromm et al., 2010). The 2017 Canadian wildfire event led to the formation of multiple pyrocumulonimbus (PyroCb)
episodes, resulting in a vast aerosol cloud. Within a few weeks, a portion of
this initial plume was transported by the polar jet streams across the
Atlantic Ocean in the Northern Hemisphere (Peterson et al., 2018), causing
a strong perturbation of the stratospheric aerosol loads (Stocker et al.,
2021). The quantity of smoke injected was enormous – so much so that it was
observed for more than 8 months (Yu et al., 2019. The presence of the
resultant aerosol layer was pointed out by high ultraviolet aerosol index
values and confirmed with CALIOP lidar observations in the UTLS (Torres et
al., 2020). The aerosol mass increase and subsequent adiabatic aerosol
self-lofting as a result of absorption of solar radiation were also observed
by the Earth Polychromatic Imaging Camera (EPIC) sensor aboard the Deep
Space Climate Observatory (DSCOVR) satellite. Kloss et al. (2019) used SAGE
III aerosol extinction values to show that the fire plume was transported
within the AMA circulation in August 2017. Our analysis suggests that the
smoke plume was still present at 18 km above Hyderabad between January and
February 2018, indicating that aerosols sampled during the winter flight were
influenced by this smoke plume.</p>
</sec>
<sec id="Ch1.S6">
  <label>6</label><title>Convective influence</title>
      <p id="d1e2453">Deep convection, emanating from Southeast Asia, and maritime convection over
surrounding seas serve as a conduit for the transport of boundary layer (BL)
pollutants (CO, HCN, CH<inline-formula><mml:math id="M182" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> to the UTLS (Belikov et al., 2013; Park et
al., 2007, 2006; Randel et al., 2010). Wind-driven physical
processes lead to the accumulation of pollutants due to the limited
exchanges of air between the interior and exterior of the Asian monsoon
anticyclone (Fairlie et al., 2014, 2020; Ploeger et al., 2015).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><?xmltex \currentcnt{5}?><?xmltex \def\figurename{Figure}?><label>Figure 5</label><caption><p id="d1e2470">Back trajectories initialized from ZF2 (15/08) and ZF3 (21/08)
measurements between 150 and 70 hPa. Black dots along the trajectories
are the position of convective systems intersecting air masses sampled
during the balloon flight.</p></caption>
        <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f05.png"/>

      </fig>

      <p id="d1e2479">To study the impact of convection on our measurements, we calculate
back trajectories from ZF2 and ZF3 using the Langley Trajectory Model (LaTM;
Fairlie et al., 2014) driven by winds from the NASA Global Modelling and
Assimilation Office (GMAO) Goddard Earth Observing System, Version 5,
Forward Processing (GEOS-5 FP) product (Lucchesi, 2018). We locate the intersection
with anvils and deep convective clouds observed through cloud-top brightness
temperature from the Himawari-8 satellite (Vernier et al., 2018). Figure 5
shows the position of those 5 d back trajectories (colored lines) and deep
convective influences (black dots). Air sampled during ZF2 on 15 August 2017 traveled along two branches influenced by convection over
southern/eastern China and western China, respectively. Air masses sampled
by ZF3 originated from convection over Laos, Myanmar, the Bay of Bengal, and
possibly local convection over the Indian eastern shore close to the
measurement location.</p>
</sec>
<sec id="Ch1.S7">
  <label>7</label><title>Nitrite measurements</title>
      <p id="d1e2490">The role of clouds in nitrite formation is further discussed in this
section. To date, only a few nitrite measurements have been reported, mainly
because of its low concentrations and the fact that nitrite ions are easily
oxidized (Lammel and Cape, 1996). The first quantitative information on
nitrite in cloud water was detected at Mt Tsukuba, Japan: values of
400–1050 <inline-formula><mml:math id="M183" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g L<inline-formula><mml:math id="M184" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> with pH levels of 5.7–6.5 were reported. In contrast,
acidic cloud water samples (pH of 3.4–4.3) collected at significantly higher
altitudes showed low nitrite values (15–104 <inline-formula><mml:math id="M185" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>g L<inline-formula><mml:math id="M186" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) (Okita, 1968).
Nitrite and nitrous acid are short-lived intermediates of reactive oxidized nitrogen in the atmosphere. There is limited information on nitrite measurements in the atmosphere
(Lammel and Cape, 1996). Nitrite was also measured in fog water samples in a polluted region in
Germany (Lammel and Metzig, 1998). Moreover, Bachmann et al. (1989) directly
measured nitrite in rain and fog water samples using ion chromatography;
respective values of 1.8 and 16 <inline-formula><mml:math id="M187" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>mol L<inline-formula><mml:math id="M188" 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>
were found. Photolysis of particulate nitrate, hydrolysis of <inline-formula><mml:math id="M189" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, and uptake
of HNO<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> by particles are the sources of particulate nitrite in the
atmosphere (Chen et al., 2019).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><?xmltex \currentcnt{6}?><?xmltex \def\figurename{Figure}?><label>Figure 6</label><caption><p id="d1e2576"> </p></caption>
        <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f06-part01.png"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><?xmltex \currentcnt{6}?><?xmltex \def\figurename{Figure}?><label>Figure 6</label><caption><p id="d1e2587">The two sets of six panels show the respective GEOS-Chem model-simulated carbon monoxide (CO, ppbv),
sulfate (SO<inline-formula><mml:math id="M191" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, ng m<inline-formula><mml:math id="M192" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP), nitrate (NO<inline-formula><mml:math id="M193" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>,
ng m<inline-formula><mml:math id="M194" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP), ammonium (NH<inline-formula><mml:math id="M195" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>,ng m<inline-formula><mml:math id="M196" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP), black carbon (BC, ng m<inline-formula><mml:math id="M197" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP),
and dust (Ca<inline-formula><mml:math id="M198" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, ng m<inline-formula><mml:math id="M199" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) concentrations averaged over 100–150 hPa
at 22:00 UTC on 15 August 2017 (top six panels) and 21 August 2017 (bottom six panels).
Standard temperature and pressure are 298 K and 1013.25 hPa,
respectively. Arrows denote the wind direction, and the white circle indicates the
sampling location in Hyderabad, India.</p></caption>
        <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f06-part02.png"/>

      </fig>

      <p id="d1e2709">HNO<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> is an important precursor for nitrite formation, but there are
challenges involved with making reliable HNO<inline-formula><mml:math id="M201" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> measurements at desired
concentrations, leading to a lack of information about HNO<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> in the
troposphere. Firstly, due to its short lifetime (because of photolysis) and subsequent
very low concentration from sources, HNO<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> is a challenging species to
observe. Secondly, HNO<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>, being sticky in nature, may be lost to the walls
of sampling tubes or absorbed on filters. Thus, as nitrite is present in very
low concentrations and is easily oxidized.</p>
      <p id="d1e2757">Intensive agricultural activities have led to the Indo-Gangetic Plain having the highest ammonia (NH<inline-formula><mml:math id="M205" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>
loading worldwide (Wang et al., 2020), as
revealed by satellite observations (Van Damme et al., 2018; Warner et al.,
2016) and ground-based measurements (Carmichael et al., 2003). Dentener and Crutzen (1994) reported ammonia (NH<inline-formula><mml:math id="M206" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) emissions related to DMS (dimethylsulfide). Höpfner et al. (2016) reported the first detection of ammonia in the ATAL. Nitrite and
nitrate are formed by the oxidation of NH<inline-formula><mml:math id="M207" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> through the process of
nitrification [NH<inline-formula><mml:math id="M208" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M209" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> O<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> <inline-formula><mml:math id="M211" display="inline"><mml:mo>→</mml:mo></mml:math></inline-formula> NO<inline-formula><mml:math id="M212" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M213" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> 3H<inline-formula><mml:math id="M214" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M215" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> 2e<inline-formula><mml:math id="M216" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula>]. In addition, the existence of NH<inline-formula><mml:math id="M217" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the presence of
nitrate leads to the formation of ammonium nitrate which could neutralize
aerosol particles and favor the persistence of nitrite, as revealed by a few
existing measurements in the polluted region (Lammel and Metzig, 1998). The
StratoClim campaign also revealed the presence of ammonium nitrate in the
UTLS which would confirm that neutralization of nitrate is effective at high
altitudes and may explain the persistence of nitrite found with our balloon
measurements.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><?xmltex \currentcnt{7}?><?xmltex \def\figurename{Figure}?><label>Figure 7</label><caption><p id="d1e2879">Time series of simulated 3-hourly CO, SO<inline-formula><mml:math id="M218" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, and
NO<inline-formula><mml:math id="M219" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations averaged over 100–150 hPa at Hyderabad during
the ZF2 and ZF3 flights on 15 and 21 August 2017. Also
shown are concentrations of NO<inline-formula><mml:math id="M220" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> due to lightning NO<inline-formula><mml:math id="M221" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions
(<inline-formula><mml:math id="M222" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>_LNO<inline-formula><mml:math id="M223" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>). See the text for details.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f07.png"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{8}?><?xmltex \def\figurename{Figure}?><label>Figure 8</label><caption><p id="d1e2959">GEOS-Chem model-simulated NO<inline-formula><mml:math id="M224" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, CO, and SO<inline-formula><mml:math id="M225" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>  concentrations (at STP) extracted along the trajectory lines during flights ZF2
and ZF3 (as shown in Fig. 5).</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/12675/2022/acp-22-12675-2022-f08.png"/>

      </fig>

</sec>
<sec id="Ch1.S8">
  <label>8</label><title>Comparison with GEOS-Chem simulations</title>
      <p id="d1e3003">We conducted GEOS-Chem model simulations to put our observations in the
context of the large-scale transport and distribution of atmospheric
composition. GEOS-Chem is a state-of-the-art global 3-D chemical transport
model that includes fully coupled ozone–NO<inline-formula><mml:math id="M226" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>–volatile organic compound–aerosol chemistry for
both the troposphere and stratosphere (Bey et al., 2001; Park et al., 2004;
Eastham et al., 2014). Here, we use the model version 11-01
(<uri>http://wiki.seas.harvard.edu/geos-chem/index.php/GEOS-Chem_v11-01</uri>, last access: 29 July 2022). A previous version of the model was used to study the origins of
aerosols in the ATAL by Gu et al. (2016) and Fairlie et al. (2020). The
model simulates black carbon (Park et al., 2003), primary and secondary
organic aerosols (POAs and SOAs, respectively; Pye et al., 2010), sulfate–nitrate–ammonium–aerosol
thermodynamics coupled to ozone–NO<inline-formula><mml:math id="M227" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>–hydrocarbon–aerosol chemistry (Park et
al., 2004), mineral dust (Fairlie et al., 2007; Ridley et al., 2014), and
sea salt (Jaeglé et al., 2011), treated as an external mixture. SOA simulation uses the
volatility-based scheme (VBS) of Pye et al. (2010). Sulfate–nitrate–ammonium
thermodynamics is computed using the ISORROPIA II thermodynamic equilibrium
model of Fountoukis and Nenes (2007). ISORROPIA has been evaluated with
in situ measurements during several campaigns in the United States (Guo et
al., 2016, 2020) and, more recently, in Korea (Ibikunle et al., 2020). Aerosol
wet deposition includes rainout and washout due to large-scale precipitation
as well as scavenging in convective updrafts (Liu et al., 2001). Scavenging
of aerosols by snow and mixed precipitation is described by Wang et al. (2011) and Q. Wang et al. (2014). Dry deposition of dust and sea-salt aerosols uses the
size-dependent scheme of Zhang et al. (2011). Dry deposition for other
aerosols follows the resistance-in-series scheme of Wesely (1989).
Anthropogenic emissions use the Emissions Database for Global Atmospheric Research (EDGAR; Olivier and Berdowski,
2001) with regional options, including the MIX inventory over East Asia (Li
et al., 2014) and the EPA/NEI 2011 inventory over North America (Travis et
al., 2016). Biofuel emissions are from Yevich and Logan (2003). Carbonaceous
aerosol emissions are provided by Bond et al. (2007). Biogenic emissions are
calculated by the Model of Emissions of Gases and Aerosols from Nature (MEGAN; Guenther et al., 2012). Biomass burning
emissions use the Quick Fire Emissions Dataset (QFED; Darmenov and da
Silva, 2015). Lightning NO<inline-formula><mml:math id="M228" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions (LNO<inline-formula><mml:math id="M229" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> are as described by
Murray et al. (2012) and match the Lightning Imaging Sensor and the Optical
Transient Detector (LIS/OTD) climatological observations of lightning
flashes.  Volcanic SO<inline-formula><mml:math id="M230" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> emissions are provided by the AeroCom project
(data available from <uri>http://wiki.seas.harvard.edu/geos-chem/index.php/Volcanic_SO2_emission</uri>, last access: 29 July 2022). The model simulations
are driven by the Modern-Era Retrospective analysis for Research and
Applications (MERRA-2) reanalysis from the NASA GMAO (Gelaro et al., 2017). For computational efficiency,
MERRA-2 fields have been mapped from the native grid to a 2.5<inline-formula><mml:math id="M231" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M232" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 2<inline-formula><mml:math id="M233" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> (longitude <inline-formula><mml:math id="M234" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> latitude) horizontal resolution for input to GEOS-Chem. Further, we used
the simulations with and without lightning NO<inline-formula><mml:math id="M235" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions to understand
the contribution of lightning to the formation of nitrate aerosol.</p>
      <p id="d1e3103">In situ chemical analysis are compared with GEOS-Chem simulations. Figure 6
shows the maps of CO, nitrate, sulfate, ammonium, black carbon (BC), and
dust aerosol concentrations averaged over 100–150 hPa at 22:00 UTC for 15 and 21 August during the ZF2 and ZF3 flights, respectively (white
circle on the map). On 15 August, CO, BC, nitrate, ammonium, and dust
aerosol concentrations are enhanced over West China, Nepal, and northeastern
India, with the center of the anticyclone positioned over West China. On the
contrary, on 21 August during ZF3, the position of the anticyclone was
shifted to the east, and the flight apparently sampled air at the edge of the
anticyclone. The simulation shows a 20 % and
50 % increase in CO and BC on 21 August, respectively, compared with 15 August.
Additionally, the ammonium concentration was decreased by 50 % and dust was reduced by
60 % on 21 August compared with the first flight on 15 August.
However, the <inline-formula><mml:math id="M236" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration is seen to be stable at <inline-formula><mml:math id="M237" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">80</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M238" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for both 15 and 21 August above Hyderabad. The simulated
<inline-formula><mml:math id="M239" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentrations near the location of ZF2 and ZF3 are spatially
inhomogeneous, with variations between 30 and 2700 ng m<inline-formula><mml:math id="M240" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> across South India.
Figure 7 shows the time series of model 3-hourly CO, sulfate, and nitrate
concentrations averaged over 100–150 hPa within the model grid point where
Hyderabad is located during August 2017. The CO concentration shows a decrease
of 14 %, while an increase of 21 % in the <inline-formula><mml:math id="M241" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> concentration is seen in the
ZF3 flight that took place on 21 August. The measured nitrate concentration
during ZF2 and ZF3 (around <inline-formula><mml:math id="M242" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M243" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) is within the
range of values simulated within 24 h of the observations. The results of
the GEOS-Chem model simulation indicate that lightning NO<inline-formula><mml:math id="M244" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> could
significantly contribute (up to <inline-formula><mml:math id="M245" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">75</mml:mn></mml:mrow></mml:math></inline-formula> % on 10 August) to
the formation of nitrates during certain time periods. The lifetime of
NO<inline-formula><mml:math id="M246" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> is approximately 3 h in the region of the outflow of thunderstorms
due to the production of methyl proxy nitrate and alkyl, and multifunctional
nitrate species and their lifetime is believed to increase downwind of the outflow
(Nault et al., 2017). Also shown in Fig. 7 are nitrate concentrations
attributed to lightning, as determined by the difference between simulations
with and without lightning NO<inline-formula><mml:math id="M247" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions. ZF2 and ZF3 occurred during a
period where the levels of nitrate were <inline-formula><mml:math id="M248" display="inline"><mml:mrow><mml:mo>≈</mml:mo><mml:mn mathvariant="normal">50</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M249" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP on
15 August and <inline-formula><mml:math id="M250" display="inline"><mml:mrow><mml:mo>≈</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M251" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> at STP on 21 August. The influence of lightning NO<inline-formula><mml:math id="M252" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> emissions was minimal during this time. Nevertheless, CO
levels are slightly higher during ZF2 (80 ppbv) than during ZF3 (60 ppbv),
indicating that measurements made during ZF2 may have been more influenced
by pollution. The latter is also reflected by the higher BC levels during
ZF2 in the model.</p>
      <p id="d1e3286">We extracted CO, nitrate, and sulfate concentrations from the GEOS-Chem
simulation along the calculated trajectories initialized from the ZF2 and ZF3
measurement locations in Fig. 8. The lines are colored according to the
balloon GPS altitudes that are used to initialize the trajectory model.
Figure 5 uses GEOS-FP winds (meteorology) to convey that GEOS-Chem could
simulate convective activities reaching levels between 14 and 15 km. This is
confirmed by cloud-top heights (black circle) derived from Himawari-8
crossed by trajectories originating from the troposphere for both ZF2 and
ZF3. ZF2 was influenced by convective activities over Western China, whereas
ZF3 sampled air masses originating from convection in Southeastern Asia (Myanmar,
Laos). CO levels with initial altitudes near 14–15 km (green color) for ZF2
are shown to decrease from 120 to 80 ppbv along the back trajectories,
confirming the influence of Chinese pollution and its progressive dilution.
At the same initial altitudes, the CO levels along ZF3 back trajectories are
significantly lower (near 50–80 ppbv), possibly indicating minimal impacts from
polluted sources. The levels of NO<inline-formula><mml:math id="M253" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> show significant variability
along the trajectories for both cases but are more pronounced in ZF3, with
levels above 400 ng m<inline-formula><mml:math id="M254" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula>, again emphasizing the likely importance of LNO<inline-formula><mml:math id="M255" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> in
the production of nitrate aerosols.</p>
      <p id="d1e3319">Sulfate concentrations are much higher (100–200 ng m<inline-formula><mml:math id="M256" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> at STP) for air parcels
initialized near 16–17 km for ZF2 and ZF3, likely indicating stratospheric
sources, whereas air parcels near 14–15 km show levels below 100 ng m<inline-formula><mml:math id="M257" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> at STP. We
note that sulfate along the trajectories influenced by Chinese pollution
during ZF2 increases by 60 % approximately 50 h before our measurements,
which could indicate the formation of sulfate aerosol from <inline-formula><mml:math id="M258" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. It has
previously been reported that sulfate has a lifetime of a few days in the
troposphere (Hidy and Blanchard, 2016). The rather short lifetime of sulfate
is due to absorption in precipitation or its solubility (Hidy, 1973). The global
mean residence time of tropospheric sulfate against dry and wet deposition
is approximately a few days (e.g., Park et al., 2004).</p>
      <p id="d1e3352">The GEOS-Chem model showed higher sulfate levels than the results from IC
due to relatively weak scavenging of SO<inline-formula><mml:math id="M259" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and/or SO<inline-formula><mml:math id="M260" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>.</p>
      <p id="d1e3379">The aircraft field campaigns of the StratoClim project were held in July and
August 2017 at the Tribhuvan International Airport (KTM; 27.70<inline-formula><mml:math id="M261" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
85.36<inline-formula><mml:math id="M262" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E; Katmandu, Nepal). In situ aerosol measurements within the
AMA were carried out using the ERICA (European Research Council Instrument for Chemical composition of Aerosols) aerosol mass spectrometer. Flights KTM 01 and KTM 02 held on 27 and 29 July showed a low level of
sulfate at 360 K (potential temperature), corresponding to an
altitude of 15 km. The sulfate concentration was almost equal to zero on
10 August during flight KTM 08 at 16 km and 370 K  (Stephan
Borrmann, 4th ACAM workshop, 28 June 2019). The very low levels of sulfate
sometimes observed in the StratoClim campaign near 360–380 K are consistent with our IC analysis results with respect to the sulfate
ionic concentration during flight ZF2 held on 15 August at the same
altitude and potential temperature.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S9" sec-type="conclusions">
  <label>9</label><title>Summary and conclusions</title>
      <p id="d1e3409">The chemical composition of the ATAL has been investigated using offline IC
analysis of aerosol-impacted samples collected aboard zero-pressure
balloon flights as part of the BATAL campaigns. The measurements of the 2017
summer campaign indicate the dominant presence of nitrate and nitrite
aerosols with concentrations between 88 and 374 ng m<inline-formula><mml:math id="M263" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP. Our first
flight (ZF2) on 15 August 2017 occurred within the AMA and, thus,
sampled air masses therein. In situ measurements revealed the presence of
NO<inline-formula><mml:math id="M264" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, and NO<inline-formula><mml:math id="M265" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> aerosols (60–200 ng m<inline-formula><mml:math id="M266" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) with
sizes ranging from 0.05 to 2 <inline-formula><mml:math id="M267" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m. The second flight (ZF3) on 21 August 2017, however, occurred at the edge of the anticyclone, and subsequent
in situ measurements revealed the presence of larger-particle-size
NO<inline-formula><mml:math id="M268" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and NO<inline-formula><mml:math id="M269" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> aerosols at higher concentrations
(87.3–343 ng m<inline-formula><mml:math id="M270" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP). Throughout the flights during the 2017 summer
campaign, sulfate aerosol remained below the detection limit of the system
(10 ng m<inline-formula><mml:math id="M271" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) and were much lower than the results from the GEOS-Chem model
simulation (80–120 ng m<inline-formula><mml:math id="M272" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP). The higher model sulfate levels compared with the values from IC are believed to be due to relatively weak scavenging 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/or SO<inline-formula><mml:math id="M274" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> in the model. Unlike the summer, Ca<inline-formula><mml:math id="M275" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>
and SO<inline-formula><mml:math id="M276" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> were found on all four stages (sizes ranging between
0.2 and 0.05 <inline-formula><mml:math id="M277" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) along with traces of NH<inline-formula><mml:math id="M278" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, which could not be
quantified in the winter campaign. The winter flight sampled residuals from
the 2017 Canadian wildfires affected stratospheric aerosol loadings
for several months.</p>
      <p id="d1e3601">We study the influence of convection on those measurements using back-trajectory calculations co-located with geostationary satellite
observations. We show that ZF2 and ZF3 were influenced by convection over
Western China, the Bay of Bengal, and Myanmar, Thailand, and Laos. The
model was able to reproduce the convective transport from the
mid-troposphere (9–12 km) to the upper troposphere (14–15 km). There was no
indication of the transport of these air parcels from the boundary layer.
Although Himawari-8 observations showed the convective transport reproduced
in MERRA-2, the mixture between horizontal and vertical transport was not
visible in trajectory calculations. Tropical convection could explain the
rapid ascent of the air parcels to higher altitudes because other mechanisms,
namely radiative heating, would delay the transport of air parcels from the
middle to the upper troposphere. While the model seems to represent
convection in the upper troposphere (14–15 km), with the rapid ascension of
air parcels, the model's ability to simulate convective influence at higher
altitudes seems to be limited.</p>
      <p id="d1e3604">We used the GEOS-Chem model simulations with and without lightning NO<inline-formula><mml:math id="M279" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>
emissions to understand the contribution of lightning to nitrate aerosol.
Flights ZF2 (15 August) and ZF3 (21 August) occurred during a
period when the levels of nitrate were relatively small (<inline-formula><mml:math id="M280" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:math></inline-formula> ng m<inline-formula><mml:math id="M281" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at STP) with minimal influence of lightning NO<inline-formula><mml:math id="M282" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>, in
contrast with other periods largely affected by nitrate produced by LNO<inline-formula><mml:math id="M283" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>. As
shown by trajectory calculations in Fig. 5, flights ZF2 and ZF3 sampled air
masses localized at the border of the Asian anticyclone. Fairlie et al. (2020) showed that the eastern part of the ATAL anticyclone depicts a peak of
ammonium contribution from Chinese emissions. The western core of the ATAL,
on the other hand, is seen to be enriched with 80 % of anthropogenic
sources from India, with the southern and eastern flanks of the anticyclone
showing peaks of Chinese contribution wherein nitrate concentrations were
found to be the highest.</p>
      <p id="d1e3656">As the ASM (Asian summer monsoon) varies with respect to spatial dimensions and methodology, inconsistencies
in the seasonal and interannual contribution to the ATAL are expected.
Mineral dust is considered to be the most abundant type in the troposphere,
with its main emission source being from arid and semiarid regions (Huneeus et
al., 2011). CaCO<inline-formula><mml:math id="M284" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> is considered to be one of the most important
components of mineral dust, and about 1.3 Tg of CaCO<inline-formula><mml:math id="M285" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> is loaded in
the troposphere, corresponding to approximately 8 % of the total loading of mineral dust (Scanza et al., 2015). During atmospheric transport,
heterogeneous reactions occur with trace gases, forming more soluble
species and resulting in the increased CCN (cloud condensation nuclei) activity
of mineral dust particles. Flight ZF2 sampled air masses within a cloud
showing the presence of Ca<inline-formula><mml:math id="M286" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> and NO<inline-formula><mml:math id="M287" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> on the same stage (particle size <inline-formula><mml:math id="M288" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.15</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M289" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m). This implies the formation of Ca(<inline-formula><mml:math id="M290" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>)<inline-formula><mml:math id="M291" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
in the presence of HNO<inline-formula><mml:math id="M292" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>.</p>
      <p id="d1e3750">Indeed, the atmosphere is an amalgamated den in which gaseous species,
particulates, and liquid droplets coexist at the same time. Through our
balloon campaigns during the ASM with simultaneous offline measurements of
inorganic species and, subsequently, comparing these results with model simulations,
we were able to understand, if not fully answer, the many unanswered questions
regarding the existence and behavioral patterns of these ionic species of interest.
We will continue to research this area with improved techniques and
additional experimentation.</p>
</sec>

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

      <p id="d1e3757">IC data are available from <ext-link xlink:href="https://doi.org/10.6084/m9.figshare.20398653" ext-link-type="DOI">10.6084/m9.figshare.20398653</ext-link> (Vernier, 2022a);
the balloon data shown are available from <ext-link xlink:href="https://doi.org/10.6084/m9.figshare.20398764" ext-link-type="DOI">10.6084/m9.figshare.20398764</ext-link> (Vernier, 2022b);
trajectory data are available from <ext-link xlink:href="https://doi.org/10.6084/m9.figshare.20398812" ext-link-type="DOI">10.6084/m9.figshare.20398812</ext-link> (Vernier, 2022c); GEOS-Chem simulation results are available from  <uri>https://figshare.com/articles/dataset/Goes-Chem_simulation_results-2017/20398839</uri> (Vernier, 2022d); and
the NASA MLS and CALIPSO data used are publicly available from <uri>https://www.earthdata.nasa.gov/</uri> (last access: 25 August 2022).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3776">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-22-12675-2022-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-22-12675-2022-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3785">HV led the preparation of the paper. AP and NR contributed to the chemical
analysis of the balloon samples. MVR, HG, JPV, SK, AKP, and GB organized the
balloon flights. FW contributed to the analysis of the COBALD data. HL and
BZ performed GEOS-Chem model simulations and assisted with model output
analysis. KB analyzed Himawari-8 data.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3791">The contact author has declared that none of the authors has any competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e3797">Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><notes notes-type="sistatement"><title>Special issue statement</title>

      <p id="d1e3803">This article is part of the special issue “StratoClim stratospheric and upper tropospheric processes for better climate predictions (ACP/AMT inter-journal SI)”. It is not associated with a conference.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3809">Hongyu Liu, Kris Bedka, Bo Zhang, and Jean-Paul Vernier acknowledge funding support from the NASA
Atmospheric Composition Modeling and Analysis Program (ACMAP) and the Upper
Atmospheric Research Program (UARP). The NASA Center for Computational Sciences
(NCCS) provided supercomputing resources. The GEOS-Chem model is managed by
the Atmospheric Chemistry Modeling Group at Harvard University with support
from the NASA ACMAP and MAP programs. The authors acknowledge Duncan T. Fairlie
for his contribution to this effort as well as Chaoyang
Xue and Christophe Guimbaud from LPC2E for their contribution to this paper.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3814">This research has been supported by the NASA Atmospheric Composition
Modeling and Analysis Program (ACMAP) and by the ANR (Agence Nationale de
La Recherche; grant ANR-10-LABX-100-01 from Labex VOLTAIRE, managed
by the University of Orleans).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3820">This paper was edited by Manvendra Krishna Dubey and reviewed by two anonymous referees.</p>
  </notes><ref-list>
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